Banana Systems in Sub-Saharan Africa.Pdf

Banana Systems in the Humid Highlands of Sub-Saharan Africa

Enhancing Resilience and Productivity This page intentionally left blank Banana Systems in the Humid Highlands of Sub-Saharan Africa

Enhancing Resilience and Productivity

Edited by

Guy Blomme

Bioversity International, Uganda

Piet van Asten

International Institute of Tropical Agriculture, Uganda

and

Bernard Vanlauwe

International Institute of Tropical Agriculture, Kenya CABI is a trading name of CAB International

CABI CABI Nosworthy Way 38 Chauncey Street Wallingford Suite 1002 Oxfordshire OX10 8DE Boston, MA 02111 UK USA

Tel: +44 (0)1491 832111 Tel: +1 800 552 3083 (toll free) Fax: +44 (0)1491 833508 Tel: +1 617 395 4051 E-mail: [email protected] E-mail: [email protected] Website: www.cabi.org © CAB International 2013. All rights reserved. No part of this publication may be reproduced in any form or by any means, electronically, mechanically, by photocopying, recording or otherwise, without the prior permission of the copyright owners. A catalogue record for this book is available from the British Library, London, UK. Library of Congress Cataloging-in-Publication Data Banana systems in the humid highlands of Sub-Saharan Africa enhancing resilience and productivity / edited by Guy Blomme, Piet van Asten and Bernard Vanlauwe. p. cm. Includes bibliographical references and index. ISBN 978-1-78064-231-4 (alk. paper) 1. Bananas--Africa, Sub-Saharan. 2. Plantain banana--Africa, Sub-Saharan. I. Blomme, G. II. Asten, Piet van, 1972- III. Vanlauwe, B. (Bernard) SB379.B2B3493 2013 634'.7720967--dc23 2013016574 ISBN-13: 978 1 78064 231 4 Commissioning editor: Claire Parﬁtt Editorial assistants: Emma McCann and Alexandra Lainsbury Production editor: Shankari Wilford

Typeset by SPi, Pondicherry, India Printed and bound in the UK by CPI Group (UK) Ltd, Croydon, CR0 4YY The book evolved from an international conference that was organized by the Consortium for Improving Agriculture-based Livelihoods in Central Africa (CIALCA) and was held in Kigali, Rwanda, from 24 to 27 October 2011. The conference addressed the challenges and opportunities for agricultural intensification of the humid highland systems of sub-Saharan Africa.

CIALCA is a Consortium of the International Agricultural Research Centers (IARCs) and their national research and development partners that aims at close technical and administrative collaboration and planning in areas of common interest, thereby enhancing returns to the investments made by DGD, Belgium and accelerating impact at the farm level.

The cover photo of the book was taken by Concretedreams (Sophie Spillemaeckers and Ludovic Schweitzer). CIALCA is coordinated by three CGIAR institutions: Bioversity International, the International Center for Tropical Agriculture (CIAT) and the International Institute of Tropical Agriculture (IITA) in collaboration with Belgian Universities and national agricultural research and development partners.

Financial contributions to the conference were made by: Contents

Contributors xi Preface xvii Acknowledgements xix

PART 1: MUSA GERMPLASM DIVERSITY AND EVALUATION

1 Plantain Collection and Morphological Characterization in Democratic Republic of Congo: Past and Present Activities and Prospects 1 J.G. Adheka, D.B. Dhed’a, C. Sivirihauma, D. Karamura, E. De Langhe, R. Swennen and G. Blomme 2 Musa Germplasm Diversity Status across a Wide Range of Agro-ecological Zones in Rwanda, Burundi and Eastern Democratic Republic of Congo 8 W. Ocimati, D. Karamura, A. Rutikanga, C. Sivirihauma, V. Ndungo, J. Adheka, D.B. Dhed’a, H. Muhindo, J. Ntamwira, S. Hakizimana, F. Ngezahayo, P. Ragama, P. Lepoint, J.-P. Kanyaruguru, E. De Langhe, S.V. Gaidashova, A. Nsabimana, C. Murekezi and G. Blomme 3 Banana Genotype Composition along the Uganda–Democratic Republic of Congo Border: A Gene Pool Mix for Plantain and Highland Bananas 22 D. Karamura, W. Ocimati, R. Ssali, W. Jogo, S. Walyawula and E. Karamura 4 Analysis of Farmer-preferred Traits as a Basis for Participatory Improvement of East African Highland Bananas in Uganda 30 A. Barekye, P. Tongoona, J. Derera, M.D. Laing and W.K. Tushemereirwe 5 Agronomic Evaluation of Common and Improved Dessert Banana Cultivars at Different Altitudes across Burundi 37 M. Kamira, R.J. Crichton, J.-P. Kanyaruguru, P.J.A. van Asten, G. Blomme, J. Lorenzen, E. Njukwe, I. Van den Bergh, E. Ouma and P. Muchunguzi

vii viii Contents

6 Growth and Yield of Plantain Cultivars at Four Sites of Differing Altitude in North Kivu, Eastern Democratic Republic of Congo 48 I. Sikyolo, C. Sivirihauma, V. Ndungo, E. De Langhe, W. Ocimati and G. Blomme

PART 2: NOVEL SEED SYSTEMS 7 Macropropagation of Musa spp. in Burundi: A Preliminary Study 58 P. Lepoint, F. Iradukunda and G. Blomme 8 Challenges and Opportunities for Macropropagation Technology for Musa spp. among Smallholder Farmers and Small- and Medium-scale Enterprises 66 E. Njukwe, E. Ouma, P.J.A. van Asten, P. Muchunguzi and D. Amah 9 Impact of Arbuscular Mycorrhizal Fungi on Growth of Banana Genotypes in Three Different, Pasteurized and Non-pasteurized Soils of Rwanda 72 S.V. Gaidashova, A. Nsabimana, P.J.A. van Asten, B. Delvaux, A. Elsen and S. Declerck 10 Indigenous Arbuscular Mycorrhizal Fungi and Growth of Tissue-cultured Banana Plantlets under Nursery and Field Conditions in Rwanda 83 J.M. Jefwa, E. Rurangwa, S.V. Gaidashova, A.M. Kavoo, M. Mwashasha, J. Robinson, G. Blomme and B. Vanlauwe

PART 3: BANANA PESTS AND DISEASES

11 Development of ELISA for the Detection of Xanthomonas campestris pv. musacearum, the Causal Agent of BXW: Banana Xanthomonas Wilt 93 G.V. Nakato, S.A. Akinbade, P. Lava Kumar, R. Bandyopadhyay and F. Beed 12 Systemicity and Speed of Movement of Xanthomonas campestris pv. musacearum in the Banana Plant after Garden Tool-mediated Infection 101 W. Ocimati, F. Ssekiwoko, M. Buttibwa, E. Karamura, W. Tinzaara, S. Eden-Green and G. Blomme 13 Use of DNA Capture Kits to Collect Xanthomonas campestris pv. musacearum and Banana Bunchy Top Virus Pathogen DNA for Molecular Diagnostics 109 I. Ramathani and F. Beed 14 Banana Xanthomonas Wilt Management: Effectiveness of Selective Mat Uprooting Coupled with Control Options for Preventing Disease Transmission. Case Study in Rwanda and Eastern Democratic Republic of Congo 116 A. Rutikanga, C. Sivirihauma, C. Murekezi, U. Anuarite, V. Ndungo, W. Ocimati, J. Ntamwira, P. Lepoint and G. Blomme Contents ix

15 Effect of Length of Fallow Period after Total Uprooting of a Xanthomonas Wilt-infected Banana Field on Infection of Newly Established Planting Materials: Case Studies from Rwanda and Eastern Democratic Republic of Congo 125 C. Sivirihauma, A. Rutikanga, C. Murekezi, G. Blomme, U. Anuarite, W. Ocimati, P. Lepoint and V. Ndungo 16 Distribution, Incidence and Farmer Knowledge of Banana Xanthomonas Wilt in Rwanda 131 G. Night, S.V. Gaidashova, A. Nyirigira, Theodomir Mugiraneza, A. Rutikanga, C. Murekezi, A. Nduwayezu, E. Rurangwa, Thierry Mugiraneza, F. Mukase, O. Ndayitegeye, W. Tinzaara, E. Karamura, W. Jogo, I. Rwomushana, F. Opio and D. Gahakwa 17 Xanthomonas Wilt Incidence in Banana Plots Planted with Asymptomatic Suckers from a Diseased Field Compared with Plots Using Suckers from a Disease-free Zone in North Kivu, Eastern Democratic Republic of Congo 138 C. Sivirihauma, N. Ndungo, W. Ocimati and G. Blomme PART 4: BANANA INTERCROPPING SYSTEMS 18 Coffee/Banana Intercropping as an Opportunity for Smallholder Coffee Farmers in Uganda, Rwanda and Burundi 144 L. Jassogne, A. Nibasumba, L. Wairegi, P.V. Baret, J. Deraeck, D. Mukasa, I. Wanyama, G. Bongers and P.J.A. van Asten 19 The Use of Trees and Shrubs to Improve Banana Productivity and Production in Central Uganda: An Analysis of the Current Situation 150 S. Mpiira, C. Staver, G.H. Kagezi, J. Wesiga, C. Nakyeyune, G. Ssebulime, J. Kabirizi, K. Nowakunda, E. Karamura and W.K. Tushemereirwe 20 Effect of Banana Leaf Pruning on Legume Yield in Banana–Legume Intercropping Systems in Eastern Democratic Republic of Congo 158 J. Ntamwira, P. Pypers, P.J.A. van Asten, B. Vanlauwe, B. Ruhigwa, P. Lepoint and G. Blomme 21 A Comparative and Systems Approach to Banana Cropping Systems in the Great Lakes Region 166 J. Van Damme, D. De Bouver, M. Dupriez, P.J.A. van Asten and P.V. Baret 22 Agronomic Practices for Musa across Different Agro-ecological Zones in Burundi, Eastern Democratic Republic of Congo and Rwanda 175 W. Ocimati, D. Karamura, A. Rutikanga, C. Sivirihauma, V. Ndungo, J. Ntamwira, M. Kamira, J.-P. Kanyaruguru and G. Blomme

PART 5: BANANA USE, POSTHARVEST AND NUTRITION

23 The Beer Banana Value Chain in Central Uganda 191 A.M. Rietveld, S. Mpiira, W. Jogo, C. Staver and E.B. Karamura 24 Contribution of Bananas and Plantains to the Diet and Nutrition of Musa-dependent Households with Preschoolers in Beni and Bukavu Territories, Eastern Democratic Republic of Congo 202 B.N. Ekesa, J. Kimiywe, M. Davey, C. Dhuique-Mayer, I. Van den Bergh and G. Blomme x Contents

PART 6: SURVEILLANCE, ADOPTION AND COMMUNICATING KNOWLEDGE 25 Processes and Partnerships for Effective Regional Surveillance of Banana Diseases 210 F. Beed, J. Kubiriba, A. Mugalula, H. Kolowa, S. Bulili, A. Nduwayezu, C. Murekezi, E. Sakayoya, P. Ndayihanzamaso, R. Mulenga, M. Abass, L. Mathe, B. Masheka, M. Onyango, E. Shitabule, V. Nakato, I. Ramathani and H. Bouwmeester 26 Adoption and Impact of Tissue Culture Bananas in Burundi: An Application of a Propensity Score Matching Approach 216 E. Ouma, T. Dubois, N. Kabunga, S. Nkurunziza, M. Qaim and P.J.A. van Asten 27 Communication Approaches for Sustainable Management of Banana Xanthomonas Wilt in East and Central Africa 224 W. Tinzaara, E. Karamura, G. Blomme, W. Jogo, W. Ocimati and J. Kubiriba 28 A Global Information and Knowledge Sharing Approach to Facilitate the Wider Use of Musa Genetic Resources 235 N. Roux, M. Ruas and B. Laliberté

Index 241 Contributors

M. Abass, Ministry of Agriculture and Livestock (MAL), Lusaka, Zambia. J.G. Adheka, Laboratoire de Génétique, Amélioration des Plantes et Biotechnologies, Faculté des Sciences, Université de Kisangani (UNIKIS), Kisangani, Democratic Republic of Congo. E-mail: [email protected] S.A. Akinbade, International Institute of Tropical Agriculture (IITA), PMB 5320, Oyo Road, Ibadan, Nigeria. Present address: Irrigated Agriculture Research and Extension Center, Washington State University, Prosser, WA 99350, USA. D. Amah, International Institute of Tropical Agriculture (IITA), PMB 5320, Oyo Road, Ibadan, Nigeria. E-mail: A.Delphine@cgiar.org U. Anuarite, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: weran14@ yahoo.fr R. Bandyopadhyay, International Institute of Tropical Agriculture (IITA), PMB 5320, Oyo Road, Ibadan, Nigeria. E-mail: [email protected] A. Barekye, African Centre for Crop Improvement, School of Agricultural Sciences and Agri- business, University of KwaZulu-Natal, P/Bag X01, Pietermaritzburg, 3209, South Africa and National Banana Research Programme, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected] P.V. Baret, Earth and Life Institute, Université Catholique de Louvain (UCL), Croix du Sud, 2 L7.05.14, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected] F. Beed, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. Present address: IITA, PO Box 34441, Dar es Salaam, Tanzania. E-mail: [email protected] G. Blomme, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: G.Blomme@ cgiar.org G. Bongers, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected] H. Bouwmeester, International Institute of Tropical Agriculture (IITA), PO Box 34441, Dar es Salaam, Tanzania. E-mail: [email protected] S. Bulili, Maruku Agricultural Research Institute (ARI-Maruku), PO Box 127, Bukoba, Kagera, Tanzania. E-mail: [email protected] M. Buttibwa, National Crops Resources Research Institute, National Agricultural Research Organisation (NARO), Namulonge, Uganda. E-mail: [email protected]

xi xii Contributors

R.J. Crichton, Bioversity International, Parc Scientiﬁque Agropolis II, 34397 Montpellier Cedex 5, France. E-mail: [email protected] M. Davey, Katholieke Universiteit Leuven (KUL), Leuven, Belgium. E-mail: Mark.Davey@ biw.kuleuven.be D. De Bouver, Earth and Life Institute, Université Catholique de Louvain (UCL), Croix du Sud, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected] S. Declerck, Earth and Life Institute, Mycology, Université Catholique de Louvain (UCL), Croix du Sud, 2 bte L7.05.06, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected] E. De Langhe, Laboratory of Tropical Crop Improvement, Katholieke Universiteit Leuven (KUL), Leuven, Belgium. E-mail: [email protected] B. Delvaux, Université Catholique de Louvain (UCL), 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected] J. Deraeck, Earth and Life Institute, Université Catholique de Louvain (UCL), Croix du Sud, 2 L7.05.14, 1348 Louvain-la-Neuve, Belgium. J. Derera, African Centre for Crop Improvement, School of Agricultural Sciences and Agribusi- ness, University of KwaZulu-Natal, P/Bag X01, Pietermaritzburg, 3209, South Africa. D.B. Dhed’a, Laboratoire de Génétique, Amélioration des Plantes et Biotechnologies, Faculté des Sciences, Université de Kisangani (UNIKIS), Kisangani, Democratic Republic of Congo. E-mail: [email protected] C. Dhuique-Mayer, La Recherche Agronomique pour le Développement/Agricultural Research for Development (CIRAD), TA B-95/16, 73 rue Jean-François Breton, 34398 Montpellier Cedex 5, France. E-mail: [email protected] T. Dubois, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected] M. Dupriez, Earth and Life Institute, Université Catholique de Louvain (UCL), 1348 Louvain- la-Neuve, Belgium. E-mail: [email protected] S. Eden-Green, EG Consulting, 470 Lunsford Lane, Larkﬁeld, Kent, ME20 6JA, UK. E-mail: [email protected] B.N. Ekesa, Bioversity International, Plot 106, Katalima Road, PO Box, 24384, Kampala, Uganda. E-mail: [email protected] A. Elsen, Soil Service of Belgium, 48 W. de Croylaan, 3001, Leuven, Belgium. E-mail: annemie. [email protected] D. Gahakwa, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: daphrose. [email protected] S.V. Gaidashova, Rwanda Agricultural Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: [email protected] S. Hakizimana, Institut de Recherche Agronomique et Zootechnique (IRAZ), Mashitsi, Burundi. E-mail: [email protected] F. Iradukunda, Bioversity International, PO Box 1893, Bujumbura, Burundi and Université du Burundi, Faculté des Sciences Agronomiques, PO Box 2940, Bujumbura, Burundi. E-mail: [email protected] L. Jassogne, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda and Earth and Life Institute, Université Catholique de Louvain, Croix du Sud, 2 L7.05.14, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected] J.M. Jefwa, Mycorrhizal Specialist, PO Box 0050-21872, Ngong Road, Nairobi, Kenya. E-mail: [email protected] W. Jogo, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: [email protected] J. Kabirizi, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. N. Kabunga, International Food Policy Research Institute (IFPRI), PO Box 28565, Kampala, Uganda. E-mail: [email protected] G.H. Kagezi, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected] Contributors xiii

M. Kamira, Bioversity International/CIALCA project, Bukavu, South Kivu, Democratic Republic of Congo. E-mail: [email protected] J.-P. Kanyaruguru, Bioversity International/CIALCA project, PO Box 7180, Bujumbura, Burundi. E-mail: [email protected] D. Karamura, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: d.karamura@ cgiar.org E.B. Karamura, Bioversity International, P.O. Box 24384, Kampala, Uganda. E-mail: [email protected] A.M. Kavoo, Jomo Kenyatta University of Agriculture and Technology (JKUAT), PO Box 62,000, 00200 Nairobi, Kenya. J. Kimiywe, Kenyatta University (KU), PO Box 43844, 00100 Nairobi, Kenya. H. Kolowa, Ministry of Agriculture, Food Security and Cooperatives, PO Box 9192, Dar es Salaam, Tanzania J. Kubiriba, National Banana Research Programme, Kawanda Agricultural Research Institute (KARI), National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected] P. Lava Kumar, International Institute of Tropical Agriculture (IITA), PMB 5320, Ibadan, Nigeria. E-mail: [email protected] M.D. Laing, African Centre for Crop Improvement, School of Agricultural Sciences and Agri- business, University of KwaZulu-Natal, P/Bag X01, Pietermaritzburg, 3209, South Africa. B. Laliberté, Commodity Systems and Genetic Resources Programme, Bioversity Interna- tional, Parc Scientiﬁque Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: brig.lalib@ gmail.com P. Lepoint, Bioversity International/CIALCA project, PO Box 7180, Bujumbura, Burundi. E-mail: [email protected] J. Lorenzen, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected] B. Masheka, Institut National pour l’Etude et la Recherche Agronomique (INERA), Kinshasa, Democratic Republic of Congo. L. Mathe, Université Catholique du Graben (UCG), Butembo, North Kivu, Democratic Repub- lic of Congo. E-mail: [email protected] S. Mpiira, Bioversity International, PO Box 24384, Kampala, Uganda and National Agricul- tural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: smpiira@ gmail.com P. Muchunguzi, International Institute of Tropical Agriculture (IITA), BP 7878, Kampala, Uganda. E-mail: [email protected] A. Mugalula, Ministry of Agriculture, Animal Industries and Fisheries (MAAIF), PO Box 34518, Kampala, Uganda. Theodomir Mugiraneza, Centre for Geographic Information Systems and Remote Sensing, National University of Rwanda (NUR), PO Box 212, Huye, Rwanda. Thierry Mugiraneza, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: [email protected] H. Muhindo, Institut Facultaire des Sciences Agronomiques (IFA-Yangambi), PO Box 1232, Kisangani, Democratic Republic of Congo. E-mail: [email protected] D. Mukasa, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected] F. Mukase, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. R. Mulenga, Zambia Agricultural Research Institute (ZARI), Lusaka, Zambia. C. Murekezi, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: [email protected] M. Mwashasha, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, PO Box 62,000, 00200 Nairobi, Kenya. xiv Contributors

G.V. Nakato, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected] C. Nakyeyune, SSC Vi Agroforestry, PO Box 1732, Kampala, Uganda. P. Ndayihanzamaso, Institut des Sciences Agronomique du Burundi (ISABU), Avenue de la Cathédrale, BP 795, Bujumbura, Burundi. E-mail: [email protected] O. Ndayitegeye, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. V. Ndungo, Université Catholique du Graben (UCG), Butembo, North Kivu, Democratic Republic of Congo. E-mail: [email protected] A. Nduwayezu, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. F. Ngezahayo, Institut de Recherche Agronomique et Zootechnique (IRAZ), Mashitsi, Burundi. E-mail: [email protected] A. Nibasumba, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda; Earth and Life Institute, Université Catholique de Louvain (UCL), Croix du Sud, 2 L7.05.14, 1348 Louvain-la-Neuve, Belgium; and Institut des Sciences Agronomique du Burundi (ISABU), Avenue de la Cathédrale, BP 795, Bujumbura, Burundi. G. Night, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: gmn27@ yahoo.com E. Njukwe, International Institute of Tropical Agriculture (IITA), BP 7878 Kampala, Uganda and IITA-CIALCA, Bujumbura, Burundi. E-mail: [email protected] S. Nkurunziza, International Institute of Tropical Agriculture (IITA), PO Box 7180, Bujumbura, Burundi. K. Nowakunda, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected] A. Nsabimana, Kigali Institute of Science and Technology (KIST), PO Box 3900, Kigali, Rwanda. E-mail: [email protected] J. Ntamwira, Institut National pour l’Etude et la Recherche Agronomique (INERA), Mulungu Research Station, Bukavu, South Kivu, PO Box 2037 Kinshasa 1, Avenue de Cliniques, Kinshasa-Gombe, Democratic Republic of Congo and Bioversity International/CIALCA Project, Bukavu, South Kivu, Democratic Republic of Congo. E-mail: ingjules2007@ yahoo.fr A. Nyirigira, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. W. Ocimati, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: w.ocimati@ cgiar.org M. Onyango, Kenya Agricultural Research Institute (KARI), Nairobi, Kenya. E-mail: maonyango [email protected] F. Opio, Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), Entebbe, Uganda. E-mail: [email protected] E. Ouma, International Institute of Tropical Agriculture (IITA), PO Box 7180, Bujumbura, Burundi. E-mail: [email protected] P. Pypers, Tropical Soil Biology and Fertility Institute of the International Center for Tropical Agriculture (TSBF-CIAT), PO Box 30677, Nairobi, Kenya. E-mail: [email protected] M. Qaim, Georg-August University of Göttingen, 37073 Göttingen, Germany. P. Ragama, Kabarak University, Private Bag 20157, Kabarak, Kenya. E-mail: peragama55@ yahoo.co.uk I. Ramathani, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected] A.M. Rietveld, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: a.rietveld@ cgiar.org J. Robinson, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, PO Box 62,000, 00200 Nairobi, Kenya. N. Roux, Commodity Systems and Genetic Resources Programme, Bioversity International, Parc Scientiﬁque Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: [email protected] Contributors xv

M. Ruas, Commodity Systems and Genetic Resources Programme, Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: [email protected] B. Ruhigwa, Institut Facultaire des Sciences Agronomiques (IFA-Yangambi), PO Box 1232 Kisangani, Democratic Republic of Congo. E-mail: [email protected] E. Rurangwa, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: [email protected] A. Rutikanga, Bioversity International/CIALCA project, Kigali, Rwanda. E-mail: alexandrerut@ yahoo.fr I. Rwomushana, Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), Entebbe, Uganda. E. Sakayoya, Département de la Protection des Végéteaux (DPV), BP 114, Gitega, Burundi. E. Shitabule, Kenya Plant Health Inspectorate Services (KEPHIS), Nairobi, Kenya. I. Sikyolo, Université Catholique du Graben (UCG), Butembo, North Kivu, Democratic Republic of Congo. E-mail: [email protected] C. Sivirihauma, Université Catholique du Graben (UCG), Butembo, North Kivu, Democratic Republic of Congo and Bioversity International/CIALCA project, Butembo, North Kivu, Democratic Republic of Congo. E-mail: [email protected] R. Ssali, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. G. Ssebulime, Kyankwanzi District Local Government, PO Box 90, Kiboga, Uganda. F. Ssekiwoko, National Banana Research Programme, Kawanda Agricultural Research Insti- tute (KARI), National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected] C. Staver, Commodity Systems and Genetic Resources Programme, Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: [email protected] R. Swennen, Laboratory of Tropical Crop Improvement, Katholieke Universiteit Leuven (KUL), Leuven, Belgium. E-mail: [email protected] W. Tinzaara, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: w.tinzaara@ cgiar.org P. Tongoona, African Centre for Crop Improvement, School of Agricultural Sciences and Agri- business, University of KwaZulu-Natal, P/Bag X01, Pietermaritzburg, 3209, South Africa. W.K. Tushemereirwe, National Banana Research Programme, Kawanda Agricultural Research Institute (KARI), National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected] P.J.A. van Asten, International Institute of Tropical Agriculture (IITA), BP 7878, Kampala, Uganda. E-mail: [email protected] J. Van Damme, Earth and Life Institute, Université Catholique de Louvain (UCL), Croix du Sud, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected] I. Van den Bergh, Commodity Systems and Genetic Resources Programme, Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: [email protected] B. Vanlauwe, International Institute of Tropical Agriculture (IITA), c/o ICIPE, PO Box 30772- 00100, Nairobi, Kenya. E-mail: [email protected] N. Vigheri, Bioversity International/CIALCA project, Butembo, North Kivu, Democratic Republic of Congo. E-mail: [email protected] L. Wairegi, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda and CAB International, ICRAF Complex, PO Box 633-00621,Nairobi, Kenya. E-mail: [email protected] S. Walyawula, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. I. Wanyama, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected] J. Wesiga, Volunteer Efforts for Development Concern (VEDCO), PO Box 1244, Kampala, Uganda. This page intentionally left blank Preface

Banana Systems in the Humid Highlands of Sub-Saharan Africa: Enhancing Resilience and Productivity addresses issues related to intensification of banana-based cropping systems in the (sub)humid highland areas of Africa. Bananas are a staple food in the East African highlands, where they have some of the highest per capita consumption rates in the world. The crop is a permanent source of food and income throughout the year for millions of smallholder farmers. Its reliable and continuous production has spared the humid highland region from drought-induced famines that have plagued other areas in sub-Saharan Africa. Moreover, the permanent canopy cover and self-mulch of banana- based systems also prevent run-off and erosion in this hilly landscape. However, in times of rapid population growth, urbanization and increasing regional trade, actors in the private and public sector are particularly encouraging the production of easily tradable and storable dry foods such as maize. Bananas have further suffered from major pest and disease outbreaks over the past few years. Maintaining and enhancing the socio- economic and biophysical buffer function of banana-based systems has, therefore, become a formidable challenge that affects the livelihoods of millions of poor producers and consumers in the region. This book brings together key contributions on banana-based systems that were presented as part of an international conference that was organized by the Consortium for Improving Agriculture-based Livelihoods in Central Africa (CIALCA) and was held in Kigali, Rwanda, from 24 to 27 October 2011. The conference was entitled the Challenges and Opportunities for Agricultural Intensification of the Humid Highland Systems of sub- Saharan Africa. The information that is presented in the 28 chapters of the book is based on research carried out in the Great Lakes Region by CIALCA and partners, and is arranged in six sections. Part 1 covers banana germplasm, Part 2 innovative seed systems, Part 3 pests and diseases, Part 4 cropping systems, Part 5 postharvest use and nutrition, and Part 6 technology adoption and dissemination of knowledge. The book provides a valuable resource for researchers, development actors, students and policy makers in agricultural systems and economics and in international development. It highlights and

xvii xviii Preface

addresses key challenges and opportunities that exist in maintaining and improving the vital buffer function that bananas provide in the agricultural systems of the humid highlands of sub-Saharan Africa. Guy Blomme Bioversity International, Uganda Piet van Asten International Institute of Tropical Agriculture, Uganda Bernard Vanlauwe International Institute of Tropical Agriculture, Kenya Acknowledgements

Special thanks go to Michael Bolton (consultant under contract to Bioversity International) and to David Turner (Associate Professor, Honorary Research Fellow, School of Plant Biology Faculty of Natural and Agricultural Sciences, The University of Western Australia) for their contributions to the scientific editing of all the chapters.

xix This page intentionally left blank 1 Plantain Collection and Morphological Characterization in Democratic Republic of Congo: Past and Present Activities and Prospects

J.G. Adheka,1* D.B. Dhed’a,1 C. Sivirihauma,2 D. Karamura,3 E. De Langhe,4 R. Swennen4 and G. Blomme3 1Université de Kisangani (UNIKIS), Democratic Republic of Congo; 2Université Catholique du Graben (UCG), Butembo, Democratic Republic of Congo; 3Bioversity International, Kampala, Uganda; 4Katholieke Universiteit Leuven (KUL), Belgium

Abstract The collection and morphological characterization of Musa spp. (bananas and plantains) started during the 1950s in the Democratic Republic of Congo (DR Congo) at the Institut National pour l’Etude Agronomique du Congo (INEAC) Yangambi Research Station, where 56 plantain cultivars were established in a collection. Unfortunately, that collection no longer exists as a result of years of social unrest and instability in the region. Collection and characterization restarted in 2005 at the University of Kisangani (UNIKIS) within the framework of a UNIKIS/Bioversity International-led project funded by the Gatsby Charitable Foundation. From January 2005 to May 2007, three missions were carried out by UNIKIS to collect plantain cultivars in different parts of Oriental Province and recover major parts of the extinct plantain collection of INEAC Yangambi. A total of 65 plantain cultivars were collected in the framework of the Gatsby-funded project. From 2009 to 2012, nine MSc students, working with a PhD student, carried out collection work in 66 territories of Oriental, North Kivu, South Kivu, Maniema, Katanga, Eastern Kasai, Western Kasai, Bandundu and Equateur provinces. The percentage of forest cover, and to a lesser extent province size, were positively linked to plantain diversity. Katanga, which is the second largest surveyed province and has savannah-type ecology had the lowest number of plantain cultivars. The highest plantain diversity was observed in forest zones across the Congo Basin. These comprise Oriental Province, where 69 plantain cultivars were recorded, followed by Equateur, with 60 cultivars, and Maniema, with 31 cultivars. Lower plantain diversity was recorded in the provinces where savannah ecologies predominate (Bandundu (25 cultivars), Western Kasai (22), Eastern Kasai (21), South Kivu (14), North Kivu (11) and Katanga (8)). Several putative new plantain cultivars were recorded. The highest cultivar diversity was observed within the ‘French’ plantain clone set, followed by the ‘False Horn’ and the ‘Horn’ clone sets. Nevertheless, ‘False Horn’ and ‘Horn’ plantain take up the largest proportion of the production landscape owing to their short cycle duration and the marketability of some of their cultivars (e.g. ‘Libanga Likale’, ‘Libanga Lifombo’ or ‘Lokusu’, which has large fruit). In-depth synonymy studies are needed and synonymy reconciliation between cultivars of the defunct INEAC Yangambi collection and the current UNIKIS collection is ongoing. In addition, agronomic, postharvest and molecular aspects of characterization should be considered as a means of enhancing the knowledge, use and conservation of Musa diversity across DR Congo.

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 1 2 J.G. Adheka et al.

1.1 Introduction (iv) to back up this plantain material at the International Transit Centre (ITC), Leuven, Bananas (Musa spp.) and plantains (a particular Belgium for subsequent virus indexing/clean- subgroup of Musa spp. – Musa AAB) are key ing and exchange for possible future use. components of food security in the Democratic From January 2005 to May 2007, four col- Republic of Congo (DR Congo), which pro- lection missions were carried out by UNIKIS to duces 1.57 million t/year of these foods collect plantains in Oriental Province and to (FAOSTAT, 2010), particularly in Oriental recover major parts of the extinct plantain col- province, which covers a large part of the lection of INEAC Yangambi. The missions took Congo Basin. For example, Tshopo District, place in: Tshopo – around Kisangani and Oriental Province, produced 444,435 t of plan- Yangambi; Ituri – around Kilo, close to the bor- tain in 2009. Plantains are mainly cultivated der with Uganda; Haut Uele – around Wamba, at lower elevations in the Congo Basin, while close to the border with Sudan; and Bas Uele – the eastern Congolese highlands along the close to the border with the Central African Albertine Rift Valley are considered as a Republic. A total of 65 plantain cultivars were meeting place of East African highland collected in the framework of the Gatsby pro- banana (Musa spp. AAA-EA) and plantain ject. A minimum set of morphological descrip- (Musa AAB) cultivation. tors was recorded for each new plantain cultivar Musa (especially plantain and AAA-EA) and a minimum set of photographs was taken cultivars were established during the 1950s (De Langhe, 1961; Tezenas du Montcel et al., in collections at four research stations of the 1983; Swennen, 1990; Daniells et al., 2001). The Institut National pour l’Etude Agronomique majority of the plantain cultivars characterized du Congo (INEAC) – Yangambi (Oriental), had a medium plant size (65%), with giant plan- Bambesa (Oriental), Lubarika (South Kivu) and tains making up 20%, dwarf plantains, 12%, Mulungu (South Kivu). Characterization of the and semi-dwarf plantains, 3%. No dwarf or wide variety of plantain cultivars in the Congo semi-dwarf cultivars had been observed in Basin started at INEAC Yangambi and, by West Africa (Dhed’a et al., 2011). Likewise, 1960, 56 plantain cultivars had been collected many of the 56 plantain cultivars collected dur- and characterized by Edmond De Langhe. ing the 1950s in the eastern Congo basin, DR However, social unrest, civil war and political Congo, and more particularly in Tshopo instability prevented work on Musa characteri- District, Oriental Province, did not seem to exist zation for several decades afterwards, and in West Africa, where over 110 plantain culti- none of these early Musa collections still exists. vars had been collected (De Langhe, 1961; Nevertheless, studies of these collections had Tezenas du Montcel et al., 1983; Swennen, 1990). led to a series of publications, especially for Further collaboration between UNIKIS, plantain, which revealed that humid Africa is Université Catholique du Graben (UCG, DR the major secondary centre of diversity for both Congo), Bioversity-CIALCA (Consortium for groups of Musa (Dhed’a et al., 2011). Still, the Improving Agriculture-based Livelihoods in Musa collection missions carried out by INEAC Central Africa) and Katholieke Universiteit scientists only covered part of Oriental Province Leuven (KUL, Belgium) was established in 2009 and it was thus assumed that only samples rep- to boost Musa collection, characterization and resenting a part of the wide plantain diversity conservation work in DR Congo. Since 2009, a that existed had been collected. team of nine MSc students and one PhD stu- In 2005, funds were obtained from the dent have carried out Musa germplasm collec- Gatsby Charitable Foundation to start a tion and morphological characterization work University of Kisangani (UNIKIS)/Bioversity in nine provinces (Oriental, North Kivu, South International-led project on ‘Plantain in the Kivu, Maniema, Katanga, Eastern Kasai, Eastern Congo Basin’. The objectives of the Western Kasai, Bandundu and Equateur). The project were: (i) to (re-)collect in Oriental MSc students each carried out their work in a Province part of this unique set of plantain specific province, while the UNIKIS PhD stu- cultivars; (ii) to establish and maintain the dent (2011–2014) is currently analysing the cultivars in a field collection at UNIKIS; combined data from all the provinces surveyed. (iii) to duplicate the collection in vitro; and An important aspect of this work comprises the Plantain Collection and Characterization in the Congo 3

comparison of the 56 plantain cultivars col- set of digital photographs (e.g. entire plant lected by INEAC in the 1950s and the UNIKIS with bunch, close-up of the inflorescence) plantain collection. As different ethnic groups (Kepler and Rust, 2006) was also taken of a use different names for a particular cultivar, mature plant for each new cultivar. Three vis- synonymy work is an important aspect of the ibly healthy sword suckers of each putative ongoing Musa germplasm research. In addition, new cultivar were collected for subsequent maps will be made depicting the diversity of establishment at the UNIKIS and UCG Musa plantain cultivars and the geographical distri- collections, and additional morphological bution of the most common plantain cultivars. characterization will be carried out on these at maturity. Diagnostic surveys were also conducted with ten households, each with at 1.2 Materials and Methods least 30 plantain mats per village. Overall, a total of 198 villages and 1980 households Since 2009, Musa germplasm surveys have were surveyed, and the following informa- been carried out in nine provinces and 66 ter- tion was collected: the most widely grown ritories (five territories in, respectively, Musa cultivars, the name of each cultivar in Katanga, Eastern Kasai, Western Kasai and the local dialect, the meaning of this name, Bandundu provinces; six territories in, respec- the origin of each cultivar, its positive and tively, Maniema, North Kivu and South Kivu; negative traits and its use. 14 territories in Equateur; and 19 territories in Oriental). Three villages in which Musa production systems dominated were selected in 1.3 Results and Discussion each territory. Where only one main road was present within a territory, villages were selected The total number of Musa cultivars grown at 50 km intervals. If several road axes were varied by province, with highest diversity present, a village was selected on each axis. observed in Oriental, Equateur, North Kivu, In each selected village, a focus group Maniema and South Kivu (Tables 1.1 and 1.2). discussion was conducted with a group of at Most of the larger provinces had a higher num- least 30 men, and with a separate group of ber of Musa cultivars, as is the case for Oriental 30 women, to establish a list of all banana and Province which ranked first in size and plantain cultivars grown and known by farm- Equateur which ranked second (Table 1.3). The ers. The presence of each listed cultivar was size of a province is, however, not the only fac- verified by UNIKIS/UCG staff/students and tor that influenced banana and plantain div- descriptor data were subsequently collected ersity in DR Congo provinces. The percentage for each new cultivar using the Bioversity of forest cover is also highly related to plantain International banana descriptor guidelines diversity (Table 1.3). Plantains clearly dominate (IPGRI-INIBAP/CIRAD, 1996). A minimum the production landscape in the Congo basin

Table 1.1. Number of cultivars of Musa spp.: for cooking and beer (East African highland banana, AAA-EA subgroup); for dessert use (AAA, ABB subgroups); and plantain (AAB subgroup) in nine provinces in Democratic Republic of Congo.

AAA-EA AAA-EA AAA, ABB AAB Province cooking beer dessert plantain Total

Bandundu 1 0 6 25 32 Eastern Kasai 4 0 7 21 32 Equateur 2 0 6 60 68 Katanga 5 0 9 8 22 Maniema 2 2 5 31 40 North Kivu 17 9 11 11 48 Oriental 8 2 7 69 86 South Kivu 10 7 9 14 40 Western Kasai 3 0 5 22 30 4 J.G. Adheka et al.

Table 1.2. Name, local synonym and clone set (type) of the five most widely spread cultivars of the plantain subgroup (AAB) in nine provinces of Democratic Republic of Congo.

Province Name Local synonym Clone set

Bandundu ‘Egbe-O-mabese I’ Moasi ‘False Horn’ ‘Ikpolo Rouge’ Mbuli ‘Horn’ ‘Libanga Likale’ Ntsila ‘False Horn’ ‘Litete’ Mimbuka ‘French’ ‘Lokusu’ Nkombe ‘Horn’ Eastern Kasai ‘Chwachwa’ Ateta ‘False Horn’ ‘Egbe-O-mabese I’ Kalunga mbumba ‘False Horn’ ‘Ikpolo Rouge’ Makonda bianza ‘Horn’ ‘Libanga Likale’ Makondji mampadji ‘False Horn’ ‘Lokusu’ Makonda ‘Horn’ Equateur ‘Egbe-O-mabese I’ Mbuli ‘False Horn’ ‘Libanga Likale’ Embanga ‘False Horn’ ‘Libanga type C’ Mogbokuma ‘False Horn’ ‘Litete’ Lolipili ‘French’ ‘Lokusu’ Mopanza ‘Horn’ Katanga ‘Boofo Noire’ Kanyongolo ‘French’ ‘Ikpolo Rouge’ Konde ‘Horn’ ‘Libanga Lifombo’ Kamatadji ‘False Horn’ ‘Libanga Likale’ Kabuzigonde ‘False Horn’ ‘Lokusu’ Gondelilume ‘Horn’ Maniema ‘Chwachwa’ Sombi ‘French’ ‘Egbe-O-mabese I’ Mogogo ‘False Horn’ ‘Ikpolo Rouge’ Mbudji ‘Horn’ ‘Libanga Likale’ Abholo ‘False Horn’ ‘Lokusu’ Mogomba ‘Horn’ North Kivu ‘Kotina’ Kikothina ‘False Horn’ ‘Musilongo’ Munzabo ‘French’ ‘Nguma’ Nguma ‘French’ ‘Vuhindi’ Vuhindi ‘French’ ‘Vulambya’ Nyalambya ‘French’ Oriental ‘Amakake’ Kanamusungudile ‘False Horn’ ‘Chwachwa’ Ayele ‘French’ ‘Libanga Lifombo’ Kasombo ‘False Horn’ ‘Libanga Likale’ Ambulu ‘False Horn’ ‘Litete’ Losau ‘French’ South Kivu ‘Boofo Noire’ Namasolu ‘French’ ‘Chwachwa’ Lubinja ‘French’ ‘Ikpolo Rouge’ Chibulanana ‘Horn’ ‘Libanga Likale’ Ngange ‘False Horn’ ‘Lokusu’ Musisa ‘Horn’ Western Kasai ‘Chwachwa’ Djeke tokoleke ‘French’ ‘Egbe-O-mabese I’ Yemba too ‘False Horn’ ‘Libanga Etshuma kawelo ‘French’ Libokoikoi’ ‘Libanga type C’ Shenga dikondo ‘False Horn’ ‘Lokusu’ Lokoma ‘Horn’

(Oriental, Maniema, the northern parts of the coexistence of different Musa genome groups two Kasai provinces, Bandundu and Equateur), contributes to a higher overall cultivar number but not in Katanga (which ranks second in as, for example, in the Kivu provinces where size but has savannah-type ecology) or in AAA-EA, dessert (AAA, ABB) Musa spp. and the eastern highland regions. In addition, the plantains (AAB) are all cultivated. Plantain Collection and Characterization in the Congo 5

Table 1.3. The relative importance of forest cover in relation to Musa diversity in provinces of Democratic Republic of Congo. Sources: SPIAF (1995); Ministère de Plan (2004, 2005a,b); Bikumu (2005); PNUD (2009).

Province Total area (km2) Forest cover (%) No. Musa cultivars No. plantain cultivars

Bandundu 295,658 40.6 32 25 Eastern Kasaï 168,216 59.4 32 21 Equateur 403,293 99.7 68 60 Katanga 496,865 2.0 22 8 Maniema 132,250 75.0 40 31 North Kivu 59,631 30.0 48 11 Oriental 503,239 73.5 86 69 South Kivu 56,128 30.0 40 14 Western Kasaï 156,967 25.5 30 22

The five most important plantain cultivars zones of DR Congo (Sebasigari, 1985). In in each province are well known (Table 1.2). this region, green or ripe plantain is cooked However, across DR Congo there are about or both cooked and pounded. Pounded 450 ethnic groups speaking about 200 different plantain is often mixed with cassava. Ripe languages (WFP et al., 2009). It is, therefore, to plantain is also fried in oil, while plantain be expected that different plantain names exist flour is used for making dough or fritters for a given cultivar (especially if this cultivar is (Bakelana and Muyunga, 1998). In some geographically widespread) and that syno- isolated villages of Tshopo District, Oriental nyms can occur within a province or between Province, beer is prepared from fermented provinces if different ethnic groups are pre- plantain and sold in order to maximize sent. As a result, the total number of plantain income. In the highlands of North and cultivars may have to be adjusted once all in- South Kivu, the landscape is mostly occu- depth morphological characterization and pied by East African highland bananas description work is completed. Initial survey (AAA-EA), while cassava and maize domi- results indicate that plantain diversity is high- nate in the savannah regions of southern est in Oriental Province (69 cultivars), followed Katanga, southern Kasai and southern by Equateur (60), Maniema (31), Bandundu Bandundu. (25), Western Kasai (22), Eastern Kasai (21), The plantain cultivars ‘Ikpolo Rouge’, South Kivu (14), North Kivu (11) and Katanga ‘Libanga Likale’ and ‘Lokusu’ dominate the (8). Primary forest dominates in the provinces plantain landscape across the provinces with the highest plantain diversity (Table 1.3). that have been surveyed (Table 1.2) and the Plantain cultivation and diversity are low in ‘Horn’ and ‘False Horn’ clone sets are the the eastern highlands and the savannah zones most common (Table 1.2). In accordance of southern Kasai or Katanga. Plantain is more with past observations (Adheka, 2010; widely grown in the hot and humid climates Dhed’a et al., 2011), the predominance of in lowland regions at 0–750 m above sea level ‘False Horn’ and ‘Horn’ plantains can be (masl). An exception is the plantain cultiva- explained by their short cycle duration and tion system in Mutwanga, North Kivu (1049 high market demand. All plantain cultivars masl), where high yields are obtained owing with large hands (i.e. ‘Horn’ and ‘False to excellent, volcanic derived soils and a Horn’ clone sets) are commonly called favourable microclimate. The plantain culti- ‘Ambulu’ (i.e. ‘great banana’) in the local mar- var ‘Vuhembe’ is cultivated on a farm at kets. None the less, the diversity of the ‘Horn’ Ndihira, North Kivu (2172 masl), which dem- and ‘False Horn’ plantain clone sets is over- onstrates the exceptional adaptation of this shadowed by the diversity in ‘French’ types cultivar to high altitude and thus low temper- (Table 1.4). It is postulated that the ‘False ature conditions. Horn’ and ‘Horn’ types evolved from ‘French’ Plantains are a staple food for the clones through mutation, resulting in a grad- majority of ethnic groups in the forest ual reduction of the male inflorescence parts. 6 J.G. Adheka et al.

Table 1.4. Number of plantain cultivars by clone set observed across the nine provinces in Democratic Republic of Congo. ‘French’ plantain has a male bud and persistent bracts on the rachis; ‘False Horn’ plantain has some bracts at the end of rachis but no male bud; ‘Horn’ plantain has no male bud, no bracts and a short rachis.

Plantain clone set

Province ‘French’ ‘False Horn’ ‘Horn’ Total

Bandundu 14 7 4 25 Eastern Kasai 10 8 3 21 Equateur 36 18 6 60 Katanga 2 2 4 8 Maniema 21 6 4 31 North Kivu 8 2 1 11 Oriental 45 18 6 69 South Kivu 10 2 2 14 Western Kasai 11 7 4 22

1.4 Conclusion distribution could pinpoint sites where mutation may have taken place. Moreover, agro- This chapter gives a general overview of plan- nomic, postharvest and molecular aspects of tain diversity across DR Congo. Initial results characterization should be considered in the from the nine provinces surveyed show that future in order to enhance the knowledge and primary forest dominates in those with the improve the use and conservation of Musa highest plantain diversity (31–69 plantain cul- diversity across DR Congo. tivars). Plantain cultivation and diversity are low in the eastern highlands (North and South Kivu) and in the savannah zones of southern Acknowledgements Bandundu, eastern and western Kasai and Katanga (8–25 plantain cultivars). In addition, We would like to thank the Directorate the plantain production landscape across the General for Development (DGD), Belgium for nine provinces is dominated by ‘False Horn’ funding this research through the CIALCA and ‘Horn’ clone sets. Nevertheless, the diver- project and the KUL-led VLIR-UOS project sity of the ‘Horn’ and ‘False Horn’ plantain for contributing to this work. UNIKIS, clone sets is overshadowed by the diversity of Kisangani and UCG, Butembo, North Kivu the ‘French’ clone set. are gratefully acknowledged for their crucial In-depth synonymy work is now needed technical support. Finally, the help of the to pinpoint similar cultivars across ethnic group farmers of the nine provinces of DR Congo boundaries or across provinces. In addition, who provided the information used in this maps of cultivar diversity and geographical study is also gratefully acknowledged.

References

Adheka, G. (2010) Diversité morphologique de bananiers et bananiers plantains utilisés dans le Bassin du Congo et leur culture en région forestière du District de la Tshopo dans la Province Orientale en République Démocratique du Congo. MSc thesis, University of Kisangani, Kisangani, Democratic Republic of Congo. Bakelana, K. and Muyunga, T. (1998) La production de bananes et de bananes plantain en République Démocratique du Congo. In: Picq, C., Fouré, E. and Frison, E.A. (eds) Bananas and Food Security, Les productions Bananières: Un Enjeu Économique Majeur pour la Sécurité Alimentaire, International Symposium, Douala, Cameroon, 10–14 November 1998. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France, pp. 103–112. Plantain Collection and Characterization in the Congo 7

Bikumu, F. (2005) La Problématique du Déficit Énergétique dans la Sous Région des Grands-Lacs Africains. Rapport de l’Institut Interculturel dans la Région des Grands Lacs, Goma, Democratic Republic of Congo. Daniells, J., Jenny, C., Karamura, D. and Tomekpe, K. (2001) Musalogue: a Catalogue of Musa Germplasm Diversity in the Genus Musa. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France. De Langhe, E. (1961) La taxonomie du bananier plantain en Afrique Equatoriale. Journal d’Agriculture Tropicale et de Botanique Appliquée 8, 418–453. Dhed’a, D.B., Nzawele, B.D., Roux, N., Ngezahayo, F., Vigheri, N., De Langhe, E., Karamura, D., Picq, C., Mobambo, P., Swennen, R. and Blomme, G. (2011) Musa collection and characterization in central and eastern DR Congo: a chronological overview. Acta Horticulturae 897, 87–94. FAOSTAT (2010) FAO Online statistical database. Food and Agriculture Organization of the United Nations, Rome. Available at: http://faostat.fao.org/ (accessed 22 June 2012). IPGRI-INIBAP/CIRAD (1996) Descriptors for Banana (Musa spp.) International Plant Genetic Resources Institute-International Network for the Improvement of Banana and Plantain, Montpellier, France/ Centre de Coopération International en Recherche Agronomique pour le Développement, Montpellier, France. Kepler, A. and Rust, F. (2006) Simmonds’ Scoring, a Pictorial Review, Technical Advisory Group (TAG) Workshop, Cameroun, 29 May–3 June, 2006. Ministère de Plan (2004) Monographie de la Province de Maniema. Unité de Pilotage du Processus DSRP [Document de la Stratégie de Réduction de la Pauvreté], Kinshasa, Democratic Republic of Congo. Ministère de Plan (2005a) Monographie de la Province de Nord Kivu. Unité de Pilotage du Processus DSRP [Document de la Stratégie de Réduction de la Pauvreté]. Kinshasa, Democratic Republic of Congo. Ministère de Plan (2005b) Monographie de la Province de Sud Kivu. Unité de Pilotage du Processus DSRP [Document de la Stratégie de Réduction de la Pauvreté]. Kinshasa, Democratic Republic of Congo. PNUD (2009) Province de Maniema, RD Congo. Pauvreté et Conditions de Vie des Ménages. Unité de Lutte contre la Pauvreté, Programme des Nations Unies pour le Développement (PNUD/UNDP), New York. Sebasigari, K. (1985) Aperçu sur la culture du bananier et ses problèmes dans la Communauté Economique des Pays des Grands Lacs (CEPGL). In: Kirkby, R.A. and Ngendahayo, D. (eds) Banana Production and Research in Eastern and Central Africa. Proceedings of a Regional Workshop held in Bujumbura, Burundi, 14–17 December 1983. Publication No. IDRC-MR114e [available in English and French], International Development and Research Centre, Ottawa, Canada, pp. 12–28. SPIAF (1995) Carte Forestière de Synthèse de la République Démocratique du Congo. Service Permanent d’Inventaire et d’Aménagement Forestier, Kinshasa, Democratic Republic of Congo. Swennen, R. (1990) Limits of morphotaxonomy. Names and synonyms of plantains in Africa and elsewhere. In: Jarret, R.L. (ed.) The Identification of Genetic Diversity in the Genus Musa. Proceedings of an International Workshop. Los Bãnos, Philippines, 5–10 September 1988. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France, pp. 172–210. Tezenas du Montcel, H., De Langhe, E. and Swennen, R. (1983) Essai de classification de bananiers plantains (AAB). Fruits 38, 318–325. WFP (World Food Programme) et al. (2009) Analyse Globale de la Sécurité Alimentaire et de la Vulnérabilité (CVFSA): Données Juillet 2007–Février 2008. World Food Programme/Programme Alimentaire Mondial des Nations Unies (PAM), Rome, Ministère du Plan et Institut National de la Statistique (INS), Kinshasa-Gombe, Democratic Republic of Congo. 2 Musa Germplasm Diversity Status across a Wide Range of Agro-ecological Zones in Rwanda, Burundi and Eastern Democratic Republic of Congo

W. Ocimati,1* D. Karamura,1 A. Rutikanga,2 C. Sivirihauma,3 V. Ndungo,3 J. Adheka,4 D.B. Dhed’a,4 H. Muhindo,5 J. Ntamwira,6 S. Hakizimana,7 F. Ngezahayo,7 P. Ragama,8 P. Lepoint,9 J.-P. Kanyaruguru,9 E. De Langhe,10 S.V. Gaidashova,11 A. Nsabimana,12 C. Murekezi11 and G. Blomme1 1Bioversity International, Kampala, Uganda; 2Bioversity International, Kigali, Rwanda and Higher Institute for Agriculture and Animal Husbandry (ISAE); 3Université Catholique du Graben (UCG), Butembo, Democratic Republic of Congo; 4University of Kisangani (UNIKIS), Democratic Republic of Congo; 5Institut Facultaire des Sciences Agronomiques (IFA-Yangambi), Kisangani, Democratic Republic of Congo; 6Institut National pour l’Etude et la Recherche Agronomique (INERA), Mulungu Research Station, Bukavu, Democratic Republic of Congo; 7Institut de Recherche Agronomique et Zootechnique (IRAZ), Mashitsi, Burundi; 8Kabarak University, Kabarak, Kenya; 9Bioversity International, Bujumbura, Burundi; 10Katholieke Universiteit Leuven (KUL), Belgium, 11Rwanda Agricultural Board (RAB), Kigali, Rwanda; 12Kigali Institute of Science and Technology, Rwanda

Abstract Musa (bananas and plantains), an important food and income crop in the east and central African Great Lakes countries (Rwanda, Burundi and the Democratic Republic of Congo (DR Congo)), has suffered declines in production and diversity over the past 20 years. The loss in cultivar diversity is mainly attributed to land pressure, agricultural intensification, market demands, pests and diseases and civil unrest. Knowledge on the current Musa cultivar diversity across Rwanda, Burundi and eastern DR Congo will provide valuable information to breeders and taxonomists. This study assessed the on-farm and community level Musa germplasm diversity across different districts of Rwanda and Burundi, and across the South and North Kivu provinces of eastern DR Congo. Spatial diversity was computed using cultivar richness and the Gini–Simpson index of diversity. A total of 92 cultivars was recorded across the surveyed regions, with the highest number of cultivars observed in Rwanda and lowest in North Kivu. The mean number of cultivars across households varied from seven to eight. North Kivu had the highest diversity index, suggesting a more even distribution of plant populations among cultivars. For example, the two most predominant cultivars occupied 35% of the land area in North Kivu, 44% in Rwanda, 61% in Burundi and 70% in South Kivu. In addition, only 26% of the cultivars had a Gini–Simpson score greater than zero, i.e. were more uniformly spread and widely adapted. Hence, 74% of the cultivars, especially those with no cultural significance, are prone to genetic erosion; ex situ conservation would

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 8 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Musa Germplasm Status across Agro-ecological Zones 9

maintain these. Beer and cooking bananas dominate the Musa landscape. However, plantains gain importance in North Kivu, especially in the regions bordering the humid Congo basin and in Mutwanga – at the foothills of the Rwenzori mountain chain. The predominance of the AAA-EA highland banana subgroup can be attributed to the predominantly mid to high altitudes (>1500 masl) found in these regions. Mid to high altitudes support East African highland banana cultivars, while humid lowlands support the growth of plantains.

2.1 Introduction to land pressure, pests and diseases, agricultural intensification, market demands and civil Bananas and plantains (Musa spp.) are impor- unrest (Okech et al., 2002, 2005; Nsabimana tant staple and income-generating fruit crops and van Staden, 2005; Ndungo et al., 2008). For for millions of people in the tropical and example, in Rwanda, civil unrest led to the subtropical regions of the world (Ssebuliba near complete staff turnover of the Rwandan et al., 2005; Robinson and Galán Saúco, 2010). Banana Programme, loss of archived informa- The countries of the Great Lakes region of East tion (Okech et al., 2002, 2005) and confusion in and Central Africa, including Rwanda, the nomenclature of cultivars (Nsabimana and Burundi and the Democratic Republic of van Staden, 2005). The recent drive for on-farm Congo (DR Congo) rank among the top banana conservation of genetic resources (Brush, 1995; and plantain producers in the world, with Bellon et al., 1997; Bretting and Duvick, 1997; annual production estimated at 2.75 million Fowler and Hodgkin, 2004) is hampered by tonnes (Mt) in Rwanda, 0.13 Mt in Burundi the need for food security and agricultural and 1.57 Mt in DR Congo (FAOSTAT, 2010). In intensification that results in the selection and addition, the crop ranks first in overall produc- promotion of a few of the more productive cul- tion in Rwanda and second in Burundi and tivars for which there is a high market demand. DR Congo (FAOSTAT, 2010). The Musa crop is Adequate knowledge of existing cultivar grown across a wide range of agro-ecologies diversity is lacking in the Great Lakes region of and provides an important ecological func- Central Africa (De Langhe, 2004). tion. The large banana leaves, a widespread Knowledge of Musa genetic diversity and super ficial root system and mulch obtained the geographical spread of banana and plan- from old leaves and harvested plants protect tain cultivars will provide valuable informa- the soil against erosion (Baragengana, 1985). tion to breeders and taxonomists (Swennen The banana crop covers 23% of the total culti- and Vuylsteke, 1987). Knowledge of the cur- vated landscape (Mpyisi et al., 2000) and is rent cultivar diversity and synonyms is there- grown by 90% of households (Lassoudière, fore urgently needed to formulate strategies 1989) in Rwanda, whereas in Burundi approxi- for the conservation of threatened cultivars mately 17% of the landscape is devoted to it. with good/promising yield/marketing or Much lower soil erosion levels have been breeding qualities. Consequently, this study reported in plots with bananas compared with assessed on-farm and community Musa germ- plots with annual crops (Lufafa et al., 2003). plasm diversity and cultivar synonyms across The Great Lakes region of East Africa, of Rwanda, Burundi and the South and North which Rwanda, Burundi and DR Congo are Kivu provinces of eastern DR Congo. It is part, constitutes one of the secondary cen- envisaged that the information generated will tres of Musa diversity and especially for the provide a baseline and a precursor for a more East African highland bananas (Musa spp. detailed germplasm characterization study AAA-EA subgroup) (Karamura et al., 2004; using descriptors for banana (IPGRI-INIBAP/ Dhed’a et al., 2011). Despite the great impor- CIRAD, 1996; Dadzi and Orchard, 1997). tance of the crop, its yield and diversity have been declining over the past decades (Rishirumuhirwa, 1997; Baijukya and de 2.2 Materials and Methods Steenhuijsen Piters, 1998; Woomer et al., 1998; MINECOFIN, 2001; Karamura et al., 2004). A Musa germplasm survey was carried out in Loss in cultivar diversity is mainly attributed different agro-ecologies of Rwanda, Burundi 10 W. Ocimati et al.

and eastern DR Congo (North Kivu and Agronomique (INERA) in South Kivu veri- South Kivu) in 2007. In Rwanda, five districts fied Musa cultivar names obtained during the representing different agro-ecologies were farmer interviews. selected along a transect from Rusizi, border- Cultivar spatial diversity was calculated ing Lake Kivu (Western Province), to Kirehe using the proportional area of the cultivars District (Eastern Province) at the border with grown by farmers (Smale et al., 2003; Gauchan, Tanzania. Three provinces were selected in 2004). The number of mats per identified Musa Burundi, namely, Cibitoke in the north-west, cultivar in each of the household farms sam- Kirundo in the north and Gitega in the central pled was counted, summed and expressed as a region. In eastern DR Congo, four represent- percentage of the total mats for all the cultivars ative and key banana-growing localities in each country or region. Cultivar spatial were selected in both North and South Kivu. diversity was computed using two indices: The sampled localities included Maboya, cultivar richness, which is diversity of order Mangodomu, Munoli and Mutwanga in zero, and the Gini–Simpson index of diversity – North Kivu, and Burhale, Kabamba, Luhihi using an order of diversity of two (Jost, 2006). and Lurhala in South Kivu. The survey site These indices can help to determine which selection criteria included biophysical and populations to target for conservation (to socio-economic characteristics (e.g. wealth maximize diversity) or for demonstrating status and land holding size), access to mar- the services that are provided by diversity kets and the presence of local farmers’ organi- (Gauchan et al., 2005). zations and non-government organizations Cultivar richness, which is the number of (NGOs) that have an interest in banana pro- cultivars in a region, is completely insensitive duction and the capacity to disseminate gen- to cultivar frequencies (Jost, 2006). It gives as erated knowledge. much weight to those cultivars that are repre- The on-farm germplasm survey activi- sented by very few plants as to those cultivars ties were to build on Participatory Rural that are represented by many plants (Jost, Appraisal (PRA) and baseline surveys that 2006; Dyke, 2008; Colwell, 2009). The cultivar were conducted in the same provinces in richness (D, order of diversity zero) was com- 2006 (CIALCA, 2008). Whereas the PRA and puted as: baseline surveys were solely based on infor- D º Ss Pi 0 (2.1) mation derived through focus group discus- i =1 sions and household interviews, the on-farm where cultivar i comprises the proportion Pi germplasm surveys took a step further to of the total individuals in a community of quantifying farming systems through actual S cultivars. field measurements. In each region, farms The Gini–Simpson index (1 – D) takes with at least 50 banana mats were identified. account of the number of individuals of each In Rwanda, a total of 118 farmers/farms cultivar as well as the number of cultivars were sampled, while 132 farms were sam- within a community (Gauchan et al., 2005; Jost, pled in Burundi. In the North and South 2006). If the order of diversity in the Gini– Kivu provinces of DR Congo, 30 farms were Simpson index is zero, then the index is the randomly sampled per locality, giving a total cultivar richness (Jost, 2006). Values of order of of 120 farmers/farms per province. diversity less than one favour rare cultivars The list of cultivars, their names and and those above one favour the more common uses were recorded for each farm surveyed. cultivars. The Simpson Index, D, with an order Data were also collected on the synonyms of diversity of two, was calculated as: of each cultivar. Regional/national scien- D = S {n ×(n –1)}/(N×(N – 1)) (2.2) tists from the Institut de Recherche Agro- i i i nomique et Zootechnique (IRAZ) in Burundi, where ni is the number of individuals of cul- the Rwandan Agricultural Board (RAB) in tivar i and N is total number of individuals Rwanda, the Université Catholique du of all cultivars. Graben (UCG) in North Kivu and the The Simpson Index, D, assesses the Institut National pour l’Etude et la Recherche probability that two randomly selected Musa Germplasm Status across Agro-ecological Zones 11

individuals (i.e. order of diversity two) from a ‘Pisang awak’ (ABB, 7%) dominated the site will belong to the same cultivar (Simpson, banana landscape. In Burundi, ‘Intuntu’ 1949). In a complementary way, the Gini– (31%), ‘Igisahira gisanzwe’ (AAA-EA cook- Simpson index (1 – D) is the probability that ing, 30%) and ‘Igipaca’ (AAA-EA beer, 9%) two independent samples will yield individu- dominated the landscape. In North Kivu, als belonging to different cultivars (Frosini, ‘Vulambya’ (AAA-EA cooking, 22%), ‘Nguma’ 2004). The Gini–Simpson index, with D calcu- (AAB plantain, 13%), ‘Intuntu’ (10%), ‘Pisang lated using Eqn 2.2, indicates greater diversity awak’ (8%) and ‘Mukingiro’ (AAA-EA as the index value approaches 1.0. The index beer, 7%) dominated the landscape while assumes values between 0 and (S – 1)/S ‘Ishika’/‘Nshikazi’ (AAA-EA beer, 62%) and (almost exactly normalized between 0 and 1 ‘Kamaramasenge’ (AAB dessert, 7%) domi- for large values of S) (Frosini, 2004). For exam- nated in South Kivu (Table 2.1). ple, if a location contains 15 cultivars with The number of Musa cultivars on each 100 mats of each cultivar, then the cultivar farm across the four regions varied from one richness is 15 and the Gini–Simpson index is to 15. The average population of household/ 0.96, indicating high diversity in the popula- farm cultivars was relatively large, varying tion. If, in contrast, one of the 15 cultivars has from 7.9 cultivars in North Kivu Province to 10,000 mats, and the others only 100 each, 6.7 in South Kivu Province (Fig. 2.1). High then the richness remains unchanged but the diversity has also been reported among sub- value of 1 – D falls to 0.23, indicating a less sistence farmers for other crops: for example, diverse population. The software GenStat up to 12 types of maize were found on farms (11th edition) from VSN International (2008) in Chiapas, Mexico (Bellon and Brush, 1994) was used to calculate the Simpson index, and and 26 distinct types of potato on farms in the also to compute the analysis of variance, Andes of South America (Quiros et al., 1990). means and standard errors for the household Some of this diversity is preserved to spread level cultivar richness. The Microsoft Excel the potentially limiting requirements of package was used to generate figures. labour at planting and to spread the harvests so as to minimize the ‘hunger gap’ that occurs between harvests (Pickersgill, 2000). Farmers also mix cultivars to avoid complete crop 2.3 Results and Discussion losses due to biotic and abiotic constraints as mixtures contain cultivars with different lev- 2.3.1 Musa cultivar richness els of resistance (Ortega, 1997). Cultivar mixtures also offer a variety of tastes, flavour, A total of 92 Musa cultivars was recorded texture, colours and uses to the farmers. across all the study areas (North and South Kivu in eastern DR Congo, Burundi and Rwanda) (Table 2.1). Rwanda ranked highest with 42 cultivars, followed by South Kivu 2.3.2 The Gini–Simpson index with 32, Burundi with 31 and finally North of diversity Kivu with 30. Of these cultivars, only five (‘Gisukari’ (AAA), ‘Intuntu’ (AAA-EA), The Gini–Simpson index varied from 0.60 in ‘Kamaramasenge’ (AAB), ‘Pisang awak’ (ABB) South Kivu to 0.91 in North Kivu. Rwanda and ‘Yangambi Km5’ (AAA)) were widely had an index of 0.87 and Burundi an index grown across the four regions. Another nine of 0.80 (Fig. 2.2). This indicates that North cultivars were grown in at least three regions; Kivu, despite having the lowest cultivar rich- ten cultivars were grown in at least two ness (30) has a more even population distri- regions, while the remaining 68 cultivars bution between cultivars. For example, the were grown in only one region (Table 2.1). two predominant cultivars in North Kivu In Rwanda, the beer cultivars ‘Intuntu’ occupied 35% of the Musa landscape com- (AAA-EA, 33% of mats), ‘Yangambi Km5’ pared to 44% in Rwanda, 61% in Burundi and (AAA, 11%), ‘Umuzibwe’ (AAA-EA, 7%) and 70% in South Kivu. 12 W. Ocimati et al.

Table 2.1. Musa cultivars recorded in the four study regions (Rwanda, Burundi and North Kivu and South Kivu in Democratic Republic of Congo), their respective genome groups (subgroups), main use, mat coverage (%) and comparison of the Gini–Simpson index of diversity of the cultivars across the study regions. Dashes (–) indicate that the cultivar was not detected in this location in this survey. The data were collected during a Musa germplasm survey in 2007. In the main use column, M is multiple use, B is beer, C is cooking, D is dessert and P is plantain.

Musa mat coverage (%) Genome Gini–Simpson Cultivar name group Use Burundi Rwanda North Kivu South Kivu index (1 – D) ‘Bakungu’ AAA-EA C – 0.17 – – 0.00 ‘Barabeshya’ AAA-EA C – 5.20 – 2.23 0.49 ‘Buhake’ AAA-EA B – – – 0.82 0.00 ‘Bulengere’ AAA-EA C – – – 0.07 0.00 ‘Bushoki’ AAA-EA C – 0.02 – – 0.00 ‘Butembo’ AAB P – – – 0.01 0.00 ‘Cibula nana’ AAB P – – – 0.07 0.00 ‘Cindege’ AAA D – – – 1.25 0.00 FHIA hybrida Tetraploid M 0.03 – – – 0.00 ‘Gisubi’ ABB B 1.40 0.02 – – 0.09 ‘Gisukari’ AAA D 0.20 0.10 0.20 2.82 0.39 ‘Goma’ AAB P – – – 0.01 0.00 ‘Gros Michel’ AAA D 1.50 2.20 – 1.06 0.81 ‘Icyerwa’ AAA-EA C – 1.31 0.16 – 0.60 ‘Igifysi’ AAA-EA B 0.01 – – – 0.00 ‘Igihonyi’ AAA-EA B 0.70 – – – 0.00 ‘Igihuna’ AAA-EA B – 0.10 – – 0.00 ‘Igipaca’ AAA-EA B 9.20 – – – 0.00 ‘Igisahira gisanzwe’ AAA-EA C 30.4 – – – 0.00 ‘Igisahira namwezi’ AAA-EA C 0.01 – – – 0.00 ‘Igisahira Uganda’ AAA-EA C 0.01 – – – 0.00 ‘Ikingurube’ AAA D 0.52 1.60 – – 0.70 ‘Ikiyove’ AAA-EA B 2.20 – – – 0.00 ‘Imporogoma’ AAA-EA C 0.05 – – – 0.00 ‘Inabukumu’ AAA-EA B 0.20 – – – 0.00 ‘Incakara’ AAA-EA C 1.90 – – – 0.00 ‘Indundi’ AAA-EA C – 0.02 – – 0.00 ‘Ingagara’ AAA-EA C – 0.20 – – 0.00 ‘Ingaju’ AAA-EA C – 3.70 – – 0.00 ‘Ingenge’ AAA-EA C – 0.80 2.30 0.42 0.71 ‘Ingumba’ AAA-EA C – 0.40 – – 0.00 ‘Injagi’ AAA-EA C – 1.30 – – 0.00 ‘Intembe’ AAA-EA B – 0.20 – – 0.00 ‘Intobe’ AAA-EA C 1.10 0.01 – – 0.18 ‘Intokatoke’ AAA-EA B – 5.60 – – 0.00 ‘Intutsi’ AAA-EA C – 0.90 – – 0.00 ‘Intutu’ AAA-EA B 31.0 33.0 9.84 4.64 0.66 ‘Inyabupfunsi’ AAA-EA C – 0.01 – – 0.00 ‘Inyabutembe’ AAA-EA C – 0.40 – – 0.00 ‘Inyamunyo’ AAA-EA C – 0.50 – – 0.00 ‘Inyonya’ AAA-EA C – 0.20 – – 0.00 ‘Isanzi’ AAB P – – – 0.05 0.00 ‘Isha’ AAA-EA B 3.30 0.02 – 0.01 0.03 ‘Ishika’ AAA-EA B – 0.30 – 62.2 0.01 ‘Kafukama’ AAA-EA C – – – 0.08 0.00 Musa Germplasm Status across Agro-ecological Zones 13

Table 2.1. Continued.

Musa mat coverage (%) Genome Gini–Simpson Cultivar name group Use Burundi Rwanda North Kivu South Kivu index (1 – D)

‘Kamaramasenge’ AAB D 1.70 1.70 4.66 7.39 0.70 ‘Kampala’ AAA B – 1.10 – – 0.00 ‘Kashulye’ AAA-EA B – – – 0.11 0.00 ‘Kingulungulu’ AAB P – – 0.41 – 0.00 ‘Kintu’ AAA-EA C – 0.17 – – 0.00 ‘Kisamunyu’ AAA-EA C – – – 2.32 0.00 ‘Kisubi Katarina’ ABB B – – 2.42 – 0.00 ‘Kithavwira’ AAA-EA C – – 0.18 – 0.00 ‘Kitika sukari kikuhi 1’ AAA D – – 0.44 – 0.00 ‘Kitika sukari kikuhi 2’ AAA D – – 0.48 – 0.00 ‘Kitika sukari kiri’ AAA D – – 5.62 – 0.00 ‘Kiware’ AAA-EA C – – 2.33 – 0.00 ‘Kotina’/‘Kikotina’ AAB P – – 1.20 – 0.00 ‘Malaya’ AAA D 0.50 – – 3.50 0.29 ‘Mbwazirume’ AAA-EA C 2.61 1.20 – 0.10 0.62 ‘Mujuba’ AAA-EA C 2.20 2.90 1.40 – 0.76 ‘Mukingiro’ AAA-EA B – – 7.15 – 0.00 ‘Munyamimba’ AAA-EA B – – – 0.04 0.00 ‘Musheba’ AAB P – – – 1.14 0.00 ‘Musilongo’ AAB P – – 3.40 – 0.00 ‘Muzuzu’ AAB P 0.01 1.1 0.01 – 0.26 ‘Ndaminya AAA-EA C – – 0.18 – 0.00 mughendi’ ‘Ngorya’ AAA-EA B – – – 0.01 0.00 ‘Nguma’ AAB P – – 13.0 4.6 0.41 ‘Nshungurhi’ AAB P – – – 0.01 0.00 ‘Nyakitembe’ AAA-EA C 0.30 0.11 5.58 – 0.16 ‘Nyiramabuye’ AAA-EA B – 1.90 – – 0.00 ‘Nzirabahima’ AAA-EA C – 1.10 0.07 – 0.00 ‘Nzirabahima AAB P – – 0.81 – 0.77 plantain’ ‘Nzirabushera’ AAA-EA C 0.01 0.10 – 1.10 0.33 ‘Nzovu’ AAA-EA B 0.01 – – – 0.00 ‘Pisang awak’ ABB B 3.00 6.90 7.62 0.03 0.67 ‘Pome’ AAB D – – – 0.01 0.00 ‘Poyo’ AAA D 0.01 4.46 – 0.27 0.14 ‘Rugamba’ AAA D 0.02 – – – 0.00 ‘Rumaripfa’ AAA-EA C – 0.80 – – 0.00 ‘Sanza moja’ AAB P – – 1.1 0.01 0.18 ‘Sila’ AAA-EA C 0.10 – – – 0.00 ‘Umugumira’ AAA-EA B – 0.05 – – 0.00 ‘Umuzibwe’ AAA-EA B – 7.22 – – 0.00 ‘Vuhethera’ AAB P – – 0.16 – 0.00 ‘Vuhindi’ AAB P – – 1.16 – 0.00 ‘Vukamatha-yira’ AAA-EA C – – 0.12 – 0.00 ‘Vukelekele’ AAB P – – 0.05 – 0.00 ‘Vulambya cooking’ AAA-EA C – – 22.0 – 0.00 ‘Walungu 16’ AAB P – – – 0.01 0.00 ‘Yangambi Km5’ AAA B 5.80 11.0 5.93 3.61 0.74 aFHIA, Fundacion Hondureña de Investigación Agricola. 14 W. Ocimati et al.

9.0 c 8.0 bc ab a 7.0

6.0

5.0

4.0

3.0

No. cultivars/household 2.0

1.0

0.0 Burundi Rwanda North Kivu South Kivu Regions

Fig. 2.1. Number of Musa cultivars grown per household across Burundi, Rwanda and the eastern Democratic Republic of Congo (North and South Kivu provinces). Data were obtained during a germplasm survey carried out in 2007. Columns with the same letters did not differ significantly at P = 0.05. Vertical bars are standard errors.

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2

Gini–Simpson index (1– D) 0.1 0.0 Burundi Rwanda North South Total Kivu Kivu Regions

Fig. 2.2. Gini–Simpson indices of diversity of Musa cultivars assessed during a germplasm survey in 2007. Regions covered included Burundi, Rwanda and the North Kivu and South Kivu provinces of eastern Democratic Republic of Congo. Vertical bars are jackknife standard errors.

Across the study region, only 24 cultivars These findings have important implica- (26%) had a Gini–Simpson index greater than tions for conservation. Values below the aver- zero (Table 2.1). This suggests that only a age Gini–Simpson index (i.e. the dominance small portion of the 92 cultivars were uni- of one or few cultivars, with much of the rich- formly spread. Some of the 68 cultivars with a ness held in low frequencies) suggest above- low Gini–Simpson index, especially those average richness for a given evenness while with little country-specific importance and values above the average index indicate a with low cultural significance, are at a great comparatively more even distribution of cul- risk of genetic erosion. tivars (Jarvis et al., 2008). It is further argued Musa Germplasm Status across Agro-ecological Zones 15

by Jarvis et al. (2008) that high dominance, ranked top at about 35%, followed by beer with much of the richness held at low fre- cultivars (»34%), plantains (»20%) and dessert quency, signals a management strategy for cultivars at about 11%. diversity maintained as an insurance to meet The dominance of beer cultivars in the future environmental changes, social and study region could be attributed to the relatively economic needs. In contrast, an even fre- high altitudes that favour the growth of beer quency distribution of cultivars shows that cultivars (D. Karamura, Kampala, Uganda, 2011, farmers are selecting cultivars to meet a personal communication). The altitudes of diversity of specific current needs and pur- the sampled communities varied from 1553 poses. Dyke (2008) argues that when a com- to 1992 m above sea level (masl) in South munity is dominated by only one or a few Kivu, from 1310 to 1706 masl in Rwanda and species, it may be that the rarer species are at from 1130 to 1609 masl in Burundi. Beer risk of disappearing from the site. The more bananas are also considered to be more toler- common species might even be part of the ant of adverse growing conditions and low problem if their behaviour is detrimental to levels of management, and are better suited to the less abundant species. In addition, a dis- regions with low market access, because the tribution pattern in which one or a few spe- beer produced has a longer shelf life than cies are far more abundant than all others bunches of bananas (Gaidashova et al., 2005). may indicate that the habitat lacks a sufficient In contrast, in North Kivu (969–1733 masl), diversity of structure, patchiness or resources cooking cultivars and plantains occupy sub- to allow many species to exist together (Dyke, stantial proportions of the Musa landscape. 2008). For example, some Musa cultivars, This can be attributed to the great variation in such as ‘Mbwazirume’, an AAA-EA cooking the Musa agro-ecologies in North Kivu, with cultivar, have been reported not to withstand its mid-altitude areas that support the produc- competition in mixed cultivar plots, while tion of AAA-EA cooking cultivars and low AAA-EA beer types thrive well at high alti- humid altitude areas where plantains are tudes (> 1500 m) that do not always support grown (Fig. 2.3). The plantains in North Kivu AAA-EA cooking types and especially plan- are mainly cultivated in the regions bordering tains (D. Karamura, Kampala, Uganda, 2011, the humid Congo Basin and in Mutwanga at personal communication). the foothills of the Rwenzori mountain chain.

2.3.3 Cultivar distribution by use 2.3.4 Musa cultivar synonyms

Beer cultivars generally dominate the Musa In this study, 41 Musa cultivars had several landscape in the study regions, except in alternative names (synonyms) (Table 2.2) North Kivu (see Fig. 2.3). In Rwanda, beer cul- within a region/country and across the dif- tivars occupy about 67% of the banana land- ferent regions/countries. The cultivar names scape, followed by cooking cultivars (»22%), given are those commonly used across the dessert bananas (»10%) and plantains, which region or among farmers, and so less widely cover only a meagre 1%. In Burundi, beer cul- used names were taken as synonyms. For tivars occupy about 57%, of the Musa land- example, the cultivar ‘Gisukari’ had three scape, cooking cultivars about 38%, dessert synonyms in both Burundi and Rwanda, but cultivars about 4% and plantains are absent. 13 synonyms in eastern DR Congo (North In South Kivu, beer cultivars also ranked and South Kivu). Similarly, the cultivars highest in importance (»75% of Musa grown), ‘Kamaramasenge’ and ‘Yangambi Km5’ also followed by dessert bananas (»16%), plan- had a large number of synonyms, especially tains (»6%) and cooking cultivars (»5%). in DR Congo. The presence of numerous North Kivu, in contrast to the other three names and synonyms in different lan- regions, had all the cultivar groups much guages, dialects and countries is a common more evenly distributed; cooking bananas problem confronting banana taxonomists 16 W. Ocimati et al.

Banana germplasm Beer Cooking Mangodumu Dessert Plantain Maboya Mutwanga

0 12.5 25 50 Munoli Uganda km N

North Kivu

DRC

Rwanda

Kabamba Karongi Ruhango Bugesera Kirehe South Kivu Luhihi

Rusizi Kirundo Tanzania Lurhala Burhala

Cibitoke

DRC Burundi

Gitega

Fig. 2.3. Musa cultivar distribution by use across four regions in central Africa (Rwanda, Burundi and North Kivu and South Kivu, Democratic Republic of Congo). Data were collected during a banana germplasm survey in 2007. Musa Germplasm Status across Agro-ecological Zones 17 Continued mufupi’ ‘Kamela ya Rwanda’, ‘Cimera’, ‘Kamela munene’, ‘Vandiward’, ‘Vandiward’, ‘Kamela munene’, ‘Cimera’, Rwanda’, ‘Kamela ya ‘Kamela ‘Cinyaburungu’, Buganda’ ‘Bumpavu’, ‘Sukumba’, ‘Mugombozi’, ‘Kisukari’, ‘Cisukari‘Bumpavu’, Rouge’, ‘Cuduku’, ‘Cingurube c’eka’, ‘Ikirisirya’, ‘Gisukari green’ Dwarf Cavendish’, ‘Kitika Kikuhi’, ‘Kitika sukari kikuhi’ ‘Kitika Kikuhi’, Cavendish’, Dwarf ‘Buganda Red ‘Cisukari’,mweupe’, ‘CisukariBanana’ mweupe’, ‘Ndundu’ Tundu’, Nakashuliye’ Bluggoe’ Cavendish’ Dwarf Cavendish’ Dwarf ‘Mabunga’, ‘Kalole’, ‘Sukarindizi’, ‘Kamela’, ‘Manzaka ‘Mabunga’, na mukari’, ‘Dwarf Cavendish’ ‘Dwarf ‘ ‘ ’ ’ ‘ ‘ ‘ ‘Horn Plantain’ ‘Cinamunyu’ ‘Ngagara’ ‘Maware’, ‘Ndabaware’, Synonyms ‘Ikiziramuhoro’ Chihuna’, ‘Igihuni’ ‘Ikingurube maraya’ ’ ‘Igisukari’, ‘Igihushwamuhoro’, ‘Igisukari’, ‘Igihushwamuhoro’, spp. and their synonyms in Burundi, Rwanda and eastern Democratic Republic of Congo (DR Congo). and eastern in Burundi, Republic and their synonyms Rwanda Democratic spp. Musa ‘Grande Naine’ ‘Grande ‘Ikinyarwanda gisanzwe’ ‘Ikinyarwanda ‘Ikinyangurube’, ‘Petite ‘Petite Naine’, ‘Ikinyangurube’, Cultivar names of Cultivar Cavendish’) ‘Intutu’ ‘Igitsiri’, ‘Makara’ ‘Insiri’, ‘Inkara’, ‘Igishumbu’ ‘Kampala’‘Kashulye’ ‘Madame’, ‘Prata’ ‘Igihuna’ ‘Kamaramasenge’ ‘Ingenge’ ‘Ingege’, ‘Nyabutembe’ ‘Kagenge’, ‘Ngenge’, ‘Kisamunyu ya ‘Pakuma’, ‘Nyaghenge’, ‘Icyerwa’ ‘Icywera-ntoya’‘Kitika sukari kikuhi 2’ ‘Nyambururu’ ‘Ishika’‘Kitika sukari kikuhi 1’ ‘Ishika’ ‘Magizi’, ‘Nshikazi’, ‘Nshika’ ‘Ikingurube’ (‘Dwarf (‘Dwarf ‘Ikingurube’ ‘Inabukumu’‘Indundi’‘Ingagara’ – beer variant ‘Intobe’ ‘Incakara’ ‘Ingagara’ ‘Maware’ ‘Kiwari’, ‘Muhuna ‘Ndabaware’, ‘Ntabawali’, Binyoko’, Cultivar nameCultivar nana’ ‘Cibula ‘Cindege’ Burundi Rwanda DR Congo (North Kivu, South Kivu) Table 2.2. ‘Gisubi’‘Gisukari’ ‘Igisubi’‘Ikisukari’, ‘Red Banana’, ‘Isha’ ‘Kisubi’, ‘Ney Povan’ ‘Kisamunyu’ ‘Insha’ ‘Umushya’, ‘Kisubi Katarina’ ‘Kithavwira’‘Kitika sukari kiri’ ‘Kiware’ ‘Isha’ ‘Nsha’, ‘Insha’ ‘Kitawira’ ‘Kithavwira’ 18 W. Ocimati et al. ‘Bukere’, ‘Kamela’, ‘Nakabusimbu’, ‘Kaganda’, ‘Kamira ‘Kaganda’, ‘Kamira ‘Kamela’, ‘Nakabusimbu’, simbu’, ‘Bukere’, ‘Kisubi mangango’ mbili’, ‘Kingalu’, ‘Sanza ‘Kingalwa’ tatu’, ‘Angalwa’, ‘Giant Cavendish’ ‘Depre’, ‘Kanuka’, ‘Tembo’, ‘Kagame’, ‘Buganda’, ‘Nakasimbu’, ‘Kagame’, ‘Buganda’, ‘Nakasimbu’, ‘Tembo’, ‘Depre’, ‘Kanuka’, ‘Asombo’ ‘Chanjo ‘Sanza mbili’, ‘Cibirangondo’, nana 2 mains’, ‘Cibula ‘Vuhetera’ ‘Kimanzobonzo’ ‘Kinamutobisa’, ‘Mayaya’, ‘Ayaya’, ‘Makelekele’ ‘Makelelele’, ‘Edidi’, ‘Cinyamunyu’ ‘Nyalambya’, ‘Malambya’, ‘Mzuzu’ ‘Baguma’, ‘Magondi’ ’Mazizi’, ‘Magizi ordinaire’ Synonyms ‘Ingame’ ‘False Horn’ plantain, Horn’ ‘False ‘Umushaba plantain’ ‘French’ = 2’ ‘Inamujuba’ ‘Mudjuva’, ‘Igisahira ‘Igisahira ‘Mudjuva’, namujuba’, Continued. ‘Nzirabahima’‘Nzirabushera’‘Sanza moja’ ‘Umuzibwe’‘Vuhethera’ ‘Indyabarangira’‘Vuhindi’ ‘Vukelekele’ cooking’ ‘Vulambya Km5’‘Yangambi ‘Mutsimawuburo’ ‘Inzirabahima’ ‘Inyamakure’ ’Umuzibo’, ‘Indaya’, ‘Tembo’, ‘Kanuka’, ‘Nyiramabuye’ plantain’ ‘Nzirabahima ’Imbotabota’ ‘Nguma’ ‘Nyakitembe’ ‘Mitoke’ ‘Matoke’ ‘Kitika’, ‘Kitoke’, Cultivar nameCultivar ‘Malaya’‘Mujuba’ Burundi‘Mukingiro’ ‘Muzuzu’ ‘Ikimaraya’ ‘Imuzuzu’ Rwanda ‘Umushaba1’= ‘Umuzuzu’, DR Congo (North Kivu, South Kivu) Rwanda’, ‘Cindege ya munene’, ‘Cindege ya ‘Cingulube’, Table 2.2. Musa Germplasm Status across Agro-ecological Zones 19

and horticulturists (Valmayor et al., 2000). For for food security and by agricultural intensi- example, in Rwanda, population migrations fication, which both result in the selection and before and during the 1994 genocide led to promotion of a few of the more productive the disappearance or renaming of some of the cultivars, ex situ conservation, especially for cultivars (Nsabimana and van Staden, 2005), cultivars with low cultural or market value, thus creating confusion in their nomencla- would maintain them. Further studies on culture. A more exhaustive and systemic study tivar interactions within the different agro- on synonyms in the region is recommended, ecologies are needed. This study revealed the using this study as a reference to complement/ dominance of beer cultivars in all the regions supplement the new study. Knowledge of except North Kivu where cooking cultivars synonyms is helpful in reducing/prevent- predominate and plantains occupy a fair share ing wasteful duplication in basic studies of the Musa landscape. There was a strong alti- on banana cultivars and will also promote tude effect on cultivar distribution, with beer regional understanding, communication, cultivars more prevalent at high altitudes and and banana trade and commerce (Valmayor plantains in the humid low altitude regions. et al., 2000).

Acknowledgements 2.4 Conclusion The Belgian Directorate General for Devel- The distribution pattern (richness and index of opment, which provided the necessary funds diversity) of Musa cultivars demonstrated in for this study, is gratefully acknowledged. this study indicates that some of the agro- The Institut de Recherche Agronomique et ecologies in the study region lack sufficient Zootechnique in Burundi, the Rwandan diversity. Despite the relatively large number Agricultural Board, the Université Catholique of cultivars of each farm or household (seven du Graben in North Kivu, DR Congo and the to eight) and high richness, some cultivars Institut National pour l’Étude et la Recherche dominated the landscape, especially in South Agronomique in South Kivu are also acknowl- Kivu. For example, despite having 32 culti- edged for their crucial role in data collection vars, only two occupied 74% of the banana and verification of synonyms. The authors landscape in South Kivu; moreover, only also gratefully acknowledge the help of the 18 cultivars (19% of the total) had a Gini– farmers who provided the information for the Simpson index above zero. Given that on-farm study from the localities that were surveyed conservation is often hampered by the need across the three countries.

References

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D. Karamura,1* W. Ocimati,1 R. Ssali,2 W. Jogo,1 S. Walyawula2 and E. Karamura1 1Bioversity International, Kampala, Uganda; 2National Agricultural Research Organization, Kampala, Uganda

Abstract Landraces contain many genotypes, which makes them a good source of genes for crop improvement and hence provide an incentive to conserve them. Banana sampling and collection were carried out along the Uganda– Democratic Republic of Congo (DR Congo) border, which is home to the largest in situ diversity of the Musa AAA Lujugira-Mutika subgroup (Uganda) and the Musa AAB Plantain subgroup (DR Congo). The objectives of the collecting mission were to explore Musa genetic resources along the border districts, sample and collect unique Musa germplasm and assess the cross-border genotype diversity. A combination of stratified purposive sampling and respondent-driven snowball sampling was employed. Sub-counties, parishes and villages with high Musa production were sampled in three districts. A descriptor checklist and the germplasm catalogue for the Mbarara, Uganda, regional collection were used to study the existing banana diversity in situ. The minimum set of Musa descriptors technique was applied to the ‘unique’ collected materials to discriminate cultivars at the subgroup level. GPS (geographic positioning system) data were obtained for reference. Results showed that 44% of the bananas found in the Ugandan districts of Arua and Zombo were cooking types (Musa AAA Lujugira-Mutika), 44% were dessert types (Musa AAA, AAB), 9% were roasting types (Musa AAB Plantains) and 3% were beer types (Musa AB, ABB). Musa diversity in Bundibugyo, Uganda, was 49% cooking types, 27% roasting types, 13% dessert types and 11% beer and juice types. Eighteen new genotypes were collected and among them were two suspected diploids (‘Bura’ and ‘Menvu’), collected from Arua. Twenty five out of 32 minimum descriptors, with an additional descriptor, which was not part of the minimum set, explained 70% of variation when subjected to principal component analysis, and separated the Musa genome groups and, to a lesser extent, the subgroups. Of the seven descriptors that were not used, two were unable to differentiate between the clones.

3.1 Introduction and other researchers involved in germplasm development. A regional germplasm collec- Germplasm constitutes the basic material for tion was established in 2008 at Mbarara, crop improvement and for this reason it needs Uganda, to conserve maximum variability to be accessed, studied and used by breeders of both local and exotic germplasm to meet

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 22 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Banana Genotype Composition along the Uganda–Congo Border 23

the needs of Musa improvement. While germ- identification and isolation of genotypes with plasm can be accessed from other regional maximum potential for resistance, yield and and global field genebanks, representative export, and thus meet the needs of Musa crop samples from farmers’ fields will ensure that improvement in the region. this collection is and remains representative of the genetic diversity of this region (Karamura, 1998). Farmers’ fields remain the 3.2 Methodologies greatest repositories of landraces, which contain many genotypes, and this makes them a A combination of stratified purposive good source of genes for crop improvement sampling and respondent-driven snowball and hence justifies their conservation sampling was employed in this study. Sub- (Pickersgill, 1994). counties and parishes with high Musa pro- The regional collection established at duction were purposively sampled in the Mbarara was for the conservation and identi- districts of Arua, Zombo and Bundibugyo, fication of genotypes with high levels of with guidance from the district and national resistance against pests, diseases and adverse agricultural advisory services officers. environmental factors, as well as having A higher chance of obtaining more Musa good agronomic characteristics. In addition, diversity was anticipated in these areas as no the collection would facilitate the mainte- collection of germplasm had taken place here nance and supply of virus-indexed materials since the 1950s. A total of seven sub-counties for research, disease exclusion strategies, were visited in Arua and Zombo districts. and the demonstration of new technologies. In Arua, two sub-counties, Logiri and Vurra, Although the Mbarara collection was only considered to be areas of banana concentra- established in 2008, a number of gaps still tion, and Adumi and Pajulu sub-counties, exist in relation to the materials found in the which had a lower banana concentration, collection. This is particularly evident in rela- were visited, while in Zombo district, the tion to wild relatives of bananas in the region; sub-counties of Zeu, Paidha and Abanga there is also a lack of representation of some were visited. In Bundibugyo, seven sub- clones from regionally important banana- counties were visited, namely Bubandi and growing areas. These factors necessitated Busaru in Bwambwa County, Sindila, Nduguto further collection of germplasm so that there and Harugali in Bughendera County, and would be a full representation of genotypes Karuguto and Kanara in Ntoroko County conserved locally. (now Ntoroko District). Sindila, Nduguto and Arua, Zombo and Bundibugyo districts Harugali sub-counties had the highest banana in Uganda are some of the areas bordering the concentrations. Democratic Republic of Congo (DR Congo). Within the sampled sub-counties, two to While banana growing has been going on in three representative parishes were randomly these districts, no studies have been carried selected and, within the parishes, two vil- out there since the 1950s to assess the types lages were randomly selected for exploration and composition of genotypes that are and sampling. In the selected villages, three being used. The DR Congo is home to some to four representative clusters of farmers, of the largest in situ diversity of plantains comprising at least three farms, were sam- in the region and a survey of the border pled for exploration through a snowball sam- region would discover some of that diversity. pling technique (Table 3.1). The snowball The objectives of collecting germplasm along sampling technique allowed the develop- the border points were, therefore, to capture ment of a research sample, whereby the exist- Musa genetic resources in Arua, Zombo and ing study subjects recruited future subjects Bundibugyo districts, sample and collect from among their acquaintances. This tech- unique Musa germplasm in these regions and nique was helpful, given that the motive of assess cross-border genotype composition. the study was to identify unique germplasm This would create a wider Musa gene pool for inclusion in the regional germplasm in the Mbarara field genebank, enable the collection. The existing Musa germplasm in 24 D. Karamura et al.

Table 3.1. The strata of the sampling design used during data collection and sample collection.

Village Farm cluster Clusters with new District stratum Sub-county stratum stratum sampled/farm stratum material/interviewed

Arua and Zombo Abanga, Adumi, 28 villages 84 clusters 10/84 Logiri, Paidha, Pajulu, Vurra, Zeu Bundibugyo and Bubandi and Busaru, 28 villages 84 clusters 15/84 Ntoroko Harugali, Kanara, Karuguto, Nduguto, Sindila

84 farm clusters in each district was explored, Zombo) were also identified through farmer and only clusters with unique germplasm not interviews. Global positioning system (GPS) already existing in the current banana data for each location where materials were national germplasm collection were identi- collected were obtained for reference. The fied and characterized. data presented in this chapter only cover the The existing cultivars were identified, villages from which plants were sampled. listed and those considered to be not present in the Mbarara collection were sampled for further characterization. The unique materi- 3.3 Results als collected were initially analysed using a minimum set of 32 highly discriminating Banana diversity in both Arua and Zombo descriptors (Horry and Channelière, 2011) was not very high (Fig. 3.1), being repre- out of more than 50 descriptors that had been sented by only 18 cultivars. Among the com- developed by IPGRI-INIBAP/CIRAD (1996). monest East African highland banana In the final analysis, seven descriptors were cultivars found were: ‘Cuula’, ‘Mukotolia’, not used, but an additional one was added. ‘Nakyetengu’ (also called ‘Namutengu’ by Of the more than 50 descriptors in the pub- the farmers), ‘Abua-enya’ (which looked lished list (IPGRI-INIBAP/CIRAD, 1996), like ‘Nzirabahima’), ‘Siira’ (identified as this minimum set of 32 was initially chosen ‘Mbwazirume’ by the collecting team) and because they had been developed further by a ‘Nyajudongo’. The farmers indicated that taxonomic advisory group to characterize the those cultivars mentioned came from the reference material at the International Transit central region of Uganda, although a few of Centre, Leuven, Belgium; this represents the them suggested that ‘Nyajudongo’ might major and widely recognized subgroups of have come from DR Congo a long time ago. Musa (Horry and Channelière, 2011). The pro- These East African highland bananas were cess of discrimination involved a pairwise found to be cultivated along the mountain comparison of accession by accession in a cor- slopes, though ‘Nyajudongo’ was present relation matrix, using the minimum set of much more in the valleys than on the moun- descriptors that were recorded in the field, tain slopes. ‘Nyajudongo’ was unique to and calculating the correlation coefficient of these districts and was therefore collected for each pair. The correlation matrix was sub- further examination at the Mbarara collec- jected to principal component analysis using tion. One plantain (‘False horn’ type) called the NTSYS-pc numerical taxonomy software ‘Makimba’ was found to be the most widely package (Rohlf, 1998) and the vector loadings distributed in these areas. Other common that represented the weighting given to each cultivars were the small-fruited dessert descriptor recorded for the first principal bananas, including ‘Yangambi Km5’ (Musa component (PC1). AAA). One of the small-fruited types was The key Musa production constraints in collected because it looked as if it was very the three districts (Arua, Bundibugyo and well adapted in Arua and was unique in Banana Genotype Composition along the Uganda–Congo Border 25

20 Frequency (%) 10

0 ‘Siira’ ‘Bura’ ‘Cuula’ ‘Menvu’ ‘FHIA 1’ ‘Bogoya’ ‘Makimba’ ‘Abua-enya’ ‘Sukali Ndizi’ ‘Nakyetengu’ ‘Muvubo’ variant ‘Yangambi Km5’ ‘Bokora’/‘Kivuvu’ ‘Mukotolia’/‘Lakiliech’ ‘Serere’/‘Pisang awak’ ‘Opu’/‘Giant Cavendish’ ‘Nyakandia’/‘Nyajudongo’ Musa cultivars ‘Tiki tiki’/‘Dwarf Cavendish’

Fig. 3.1. Frequency of occurrence of different Musa cultivars in farm clusters in Arua/Zombo districts of Uganda. Interviews were done with a total of ten farm clusters comprising at least three farms each. Vertical bars are 95% confidence intervals. the region. ‘Bluggoe’ (Musa ABB, locally found were mainly ‘False Horn’ and ‘French’ named ‘Bokora’), ‘Dwarf Cavendish’ (Musa types, with ‘Kibedha’ (‘False Horn’) and AAA, locally called ‘Tiki tiki’) and ‘Giant ‘Kikonjakonja’ (‘French’) being more widely Cavendish’ (Musa AAA, locally called ‘Opu’) cultivated than others. Farmers mentioned were also common. that most of the plantains originated from Of the seven clones collected from Arua DR Congo, although there were some farmers and Zombo, site AZ (Table 3.2), only one cul- that considered them to be indigenous to tivar looked like a diploid and this was said the district. In Bundibugyo, plantains were to have been brought by missionaries in not roasted as in other parts of Uganda; Ediofe Catholic missionary station, Arua. As rather, they were cooked and dried to make farmers did not have a name for it, the team a certain type of flour. Other common named it ‘Bura’, based on the village where it cultivars were ‘Yangambi Km5’ (AAA), was collected. Results further indicated that ‘Bogoya’ (‘Gros Michel’, AAA), the small- 44% of cultivars found in Arua and Zombo fruited dessert bananas such as ‘Akasukali’ were cooking types (AAA-EA), 44 % were (AAB) and ‘Kisubi’ (AB), ‘Bluggoe’ (locally dessert types (AAA, AAB), 9% were plantains called ‘Kipepepe’) and ‘Ekimusa’ (ABB). The (AAB) and 3% were beer bananas (AB, ABB). diversity in Bundibugyo was composed of The diversity in Bundibugyo was higher 49% cooking types (AAA-EA), 27% plantains than that in Arua/Zombo, with 32 cultivars (AAB), 13% dessert types (AAA, AAB) and (Fig. 3.2). The most widely cultivated East 11% beer and juice types (AB, ABB). Of the African highland bananas in Bundibugyo 11 clones collected from Bundibugyo (Table were ‘Nzirabahima’, ‘Kitika’ (‘Nakyetengu’), 3.2), four were highland bananas (Lujugira- ‘Entabawali’, ‘Mbwazirume’, ‘Nyalambya’ and Mutika) and seven were plantains. ‘Enyanja’ (beer type). Plantain diversity in Bun- From the 32 minimum descriptors on dibugyo increased as one moved closer to the which data were collected, only 25 were used, DR Congo border with Uganda. The plantains with an addition of one that was able to 26 D. Karamura et al.

Table 3.2. Germplasm accessions collected from the Arua and Zombo (site AZ) and Bundibugyo districts (site B) of Uganda.

Accessions collected Genome group Subgroup Altitude (masl)a Site

‘Abua-enya’ AAA-EA Lujugira-Mutika 1918 AZ ‘Bebebasali’/‘Ndyabagole’ AAA-EA Lujugira-Mutika 923 B ‘Bura’ AA? Unknown 1252 AZ ‘Cuula’ AAA-EA Lujugira-Mutika 1665 AZ ‘Empurumura’ AAA-EA Lujugira-Mutika 1131 B ‘Enyanja’ AAA-EA Lujugira-Mutika 1194 B ‘Kabila’ AAB ‘French’ plantain 1084 B ‘Kajabo’ AAB ‘False Horn’ plantain 914 B ‘Kalasa’ AAB ‘French’ plantain 920 B ‘Kikonjakonja’ AAB ‘French’ plantain 914 B ‘Majabaga’ AAB ‘False Horn’ plantain 1051 B ‘Mbiya’ AAB ‘French’ plantain 1075 B ‘Menvu’ AA or AAB Silk or Ney Poovan 1252 AZ ‘Muvubo’ variant AAA-EA Lujugira-Mutika 1264 AZ ‘Namutobisho’ AAB ‘French’ plantain 922 B ‘Nyajudongo’/‘Nyakandia’ AAA-EA Lujugira-Mutika 1918 AZ ‘Nyakisangani’/‘Opu’ AAA ‘Cavendish’ 1266 AZ ‘Nyalambya’ AAA-EA Lujugira-Mutika 1328 B amasl, metres above sea level.

90 80 70 60 50 40 30 Frequency (%) 20 10 0 ‘Kitika’ ‘Mbiya’ ‘Kisubi’ ‘Nkobe’ ‘Kabila’ ‘Kalasa’ ‘Mujuba’ ‘Kingalu’ ‘Bogoya’ ‘Enyanja’ ‘Kibedha’ ‘Ekimusa’ ‘Akasukali’ ‘Musakala’ ‘Majabaga’ ‘Namaputo’ ‘Nyalambya’ ‘Nakabululu’ ‘Nyaghenge’ ‘Nzirabahima’ ‘Mbwazirume’ ‘Empurumura’ ‘Nyamaswere’ ‘Namutobisho’ ‘Kikonjakonza’ ‘Mukazi alanda’ ‘Akanjabo’/‘Kajabo’ ‘Kipepepe’/‘Bluggoe’ ‘Kisira’/‘green-red bog’ ‘Kisira’/‘green-red ‘Yangambi Km5’/‘Mario’ ‘Yangambi ‘Entabawali’/‘Nandigobe’ ‘Ndyabagole’ (‘Bebebasali’) Musa cultivars

Fig. 3.2. Frequency (%) of occurrence of different Musa cultivars in farm clusters in Bundibugyo district. A total of 15 clusters comprising of at least three farms each were interviewed. Vertical bars are 95% confidence intervals.

discriminate the cultivars that had been col- differentiate accessions were considered inva- lected (see Table 3.3). The additional descrip- lid, meaning that the accessions were all similar tor was the pigmentation of the underlying with regard to that particular character. Of the pseudostem. The descriptors that could not seven descriptors of the minimum set that Banana Genotype Composition along the Uganda–Congo Border 27

Table 3.3. Minimum set of descriptors used for discriminating sampled Musa accessions based on the booklet IPGRI-INIBAP/CIRAD (1996). For descriptor codes and names in italics data were collected but were not used in the analysis. PC1, principal component 1.

Descriptor

Code Name Loading on PC1 Comments

6.2.1 Pseudostem height: <2.0–>3.0 m 0.518 6.2.5 Predominant underlying colour of the pseudostem Not used 6.2.6 Pigmentation of the underlying pseudostem 0.696 Additional descriptor 6.2.7 Sap colour Not used 6.3.1 Blotches at the petiole base 0.224 6.3.3 Petiole canal leaf III: open or closed 0.970 6.3.4 Petiole margins winged/undulating or not 0.489 6.3.6 Petiole margin colour 0.749 6.3.7 Edge of petiole margin colour Not used 6.3.22 Colour of outer surface of cigar leaf Not used 6.4.6 Bunch position: vertical or erect 0.814 6.4.7 Bunch shape: cylindrical or spiral 0.452 6.4.12 Rachis position: falling vertically or erect 0.747 6.4.13 Rachis appearance: bare or other 0.983 6.4.15 Male bud shape: like a top or rounded –0.534 6.4.16 Male bud size at harvest Not used 6.5.2 Bract apex shape: small, medium or large shoulder –0.877 6.5.3 Bract imbrication –1.052 6.5.4 Colour of the bract external face –0.087 6.5.5 Colour of the bract internal face –0.383 6.5.12 Bract behaviour before falling: revolute or not –0.555 6.6.2 Compound tepal basic colour: white or purple –0.750 6.6.4 Lobe colour compound tepal: cream or green –0.841 6.6.13 Anther colour: white or purple or aborted –0.624 6.6.24 Dominant colour of male flower Not used 6.7.2 Number of fruits in hand: <12–>17 –0.235 6.7.3 Fruit length (cm): <15–>31 0.746 6.7.4 Fruit shape: straight or curved 0.805 6.7.6 Fruit apex: pointed or rounded 0.975 6.7.7 Remains of flower relicts at fruit apex 0.224 6.7.8 Fruit pedicel length (mm): <10–>21 0.644 6.7.11 Fusion of pedicels Not used 7.10 Number of hands in a bunch 0.570

were not used, three of them were not including the East African highland bananas sufficient ly discriminating to differentiate the and the other two grouping the major plan- clones. These three descriptors were the colour tain types, ‘French’ and ‘False Horn’ plantains of the outer surface of the emerging (cigar) leaf, (Fig. 3.3). A number of descriptors contributed the degree of fusion of pedicels and sap colour. to the clustering and spatial arrangement of Other descriptors could not be very easily these accessions. The vector loadings (which applied in the field, for example the male bud explain the relative influence and contribu- size, the colour of the edge of the petiole margin tion of the original descriptors to the varia- (confused with petiole margin colour), the domi- tion existing among the cultivars) of the first nant colour of male flowers and the predomi- principal component (PC1) were high: above nant underlying colour of the pseudostem. 0.9 for descriptors such as rachis appearance, Based on the minimum descriptors, three fruit apex and petiole canal leaf III (degree major clusters exist in the data, one cluster of openness of the canal) (see Table 3.3). 28 D. Karamura et al.

0.6 PC1 PC2 East African highland bananas Abua-enya 1 0.9249 0.2973 0.4 7 ‘Horn’ plantains 16 1 Nyajudongo 2 0.9419 0.2535 3 Cuula 3 0.9241 0.2937 10 5 0.2 2 9 Opu 4 0.8476 0.0604 14 17 Muv-variant 5 0.938 0.2579 13 4 8 Menvu 6 0.6046 –0.6513 0.0 Bura 7 0.4494 0.3947 Nyalambya 8 0.9539 0.1113 Enyanja 9 0.9596 0.2311 PC2 –0.2 Majabaga 10 –0.0889 0.2477 Namutobisho 11 0.6807 –0.6479 –0.4 Kikonjakonja 12 0.531 –0.736 ‘French’ plantains Kajabo 13 0.0017 0.0003 15 Kalasa 14 –0.1781 0.1538 –0.6 18 Kabila 15 0.755 –0.5588 6 11 Empuramura 16 0.8856 0.3324 12 Ndyabagole 17 0.9149 0.1856 –0.8 Mbiya 18 0.5598 –0.6268 –0.4 –0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2 PC1

Fig. 3.3. Position of the 18 newly collected Musa accessions with respect to the first (PC1) and second (PC2) principal components. The largest cluster was composed of East African Highland bananas: 1, ‘Abua-enya’ (almost similar to 3); 2, ‘Muvubo’ variant (almost similar to 5); 3, ‘Nyajudongo’; 4, ‘Opu’; 5, ‘Cuula’; 8, ‘Nyalambya’; 9, ‘Enyanja’; 16, ‘Empuramura’; and 17, ‘Ndyabagole’. The mid-sized cluster was mainly composed of ‘French’ plantains: 11, ‘Namutobisho’; 12, ‘Kikonjakonja’; 15, ‘Kabila’; and 18, ‘Mbiya’. The smallest cluster was mainly composed of ‘Horn’ plantains: 10, ‘Majabaga’; 13, ‘Kajabo’; and 14, ‘Kalasa’. ‘Menvu’ (6) clustered with the ‘French’ plantains while ‘Bura’ (7) stood alone but closer to the highland bananas than to the other two clusters.

Other descriptors whose loadings were high plantains and East African highland bananas. and which contributed much to this pattern of It is not easy to explain how this mixed variation were bract apex shape, lobe colour composition came about, though ethnic of compound tepal, bunch position and fruit migrations and the ecology of the region must shape. PC1 accounted for 55% of the variation both have played a part. The people on both found in the collected materials while PC2 sides of the border are ethnically related accounted for only 16%. The descriptors were and share both culture and agro-ecological useful in separating the genome groups and, systems. ‘Bura’, a suspected diploid, ‘Cuula’ to a lesser extent, the subgroups, as most of and ‘Nyajudongo’ were some of the distinct the materials belonged to only two major genotypes found in Arua and Zombo, for groups and subgroups. which further characterization is needed. Xanthomonas wilt was found to be a ‘Cuula’, widely grown in Zombo, showed major constraint in both Bundibugyo and some resemblances to ‘Mutore’ of Kenya, a Arua, to such an extent that people in clone with a high content of carotenoids Bundibugyo have left banana fields unweeded (Karamura et al., 2006). and were concentrating on cassava farming. The ecology of Arua and Zombo, which The disease was clearly a threat to banana is characterized by medium to high alti- diversity and on-farm conservation in the tudes, long dry seasons and low humidity, region. Although labour shortage was found probably has not favoured high plantain to be an important constraint, it was over- diversity and, as such, ‘Makimba’, a ‘False shadowed by the Xanthomonas wilt problem. Horn’ plantain, is the only commonly found plantain in the area, in addition to ‘Menvu’, another clone with a B genome. Plantains however, were very common in Bundibugyo, 3.4 Discussion which is in the rift valley and is more humid than Arua. A number of names of both plan- The Musa genotypes along the Uganda side tains and the highland bananas were associ- of the Uganda/DR Congo border are of a ated with dialects across both Uganda and mixed composition, but mainly comprise DR Congo, a further confirmation that ethnic Banana Genotype Composition along the Uganda–Congo Border 29

groups along the border seem to be respon- similar information. For example, informa- sible for the local genotype composition. tion on the predominant underlying colour ‘Nyalambya’ or ‘Nyarambi’ (‘Vulambya’ in of the pseudostem could be providing north Kivu) as well as ‘Ndyabawali’, similar information to the pigmentation on (‘Kiware’, ‘Maware’ in north Kivu) are good the underlying pseudostem. On the whole, examples of cultivars widely grown across descriptors are always selected on criteria the DR Congo–Uganda border. Among the such as ease of observation and access, avail- plantains is ‘Namutobisho’, a very much- ability and usefulness in grouping or sepa- preferred plantain in Bundibugyo as well as rating materials. Nevertheless, principal in North Kivu (where it is called ‘Vuhindi’ or component analysis, to which data from the ‘Kinamutobisa’). Several gigantic plantains minimum set of descriptors were subjected, (‘Kabila’, ‘Mbiya’ and ‘Majabaga’) are some was useful in identifying patterns of variation of the new genotypes collected from among the materials and hence proved to be Bundibugyo and their characterization will of value in their classification. be completed in their first or second cycle. Descriptors were found to be not all of equal value for purposes of comparison; for example, sap colour, which did not vary Acknowledgements among the collected materials, was not useful. Furthermore, some descriptors that seemed The authors thank the Government of Uganda to be logically correlated were also of limited and Bioversity International for funding usefulness because they would provide this work.

References

Horry, J.P. and Channelière, S. (2011) Morphological characterization descriptors: objectives, limits and appropriateness. In: MusaNet Strategic Meeting; Documents and Presentations, 28 February–3 March 2011, Montpellier, France. Available at: http://www.crop-diversity.org/banana/MusaNet// Presentations/11-Day2-Horry-Presentation.pdf (accessed 23 October 2012). IPGRI-INIBAP/CIRAD (1996) Descriptors for Banana (Musa spp.) International Plant Genetic Resources Institute-International Network for the Improvement of Banana and Plantain, Montpellier, France/ Centre de Coopération International en Recherche Agronomique pour le Développement, Montpellier, France. Karamura, D.A. (1998) Numerical taxonomic studies of the East African Highland banana (Musa AAA-East Africa) in Uganda. PhD thesis, University of Reading, Reading, UK. Karamura, D., Njuguna, J.K. and Nyamongo, D. (2006) The Kenya Musa Expedition. Bioversity International, Montpellier, France. Pickersgill, B. (1994) From descriptors to DNA: new tools and new tasks in the evaluation of genetic resources. In: Balfourier, F. and Perretant, M.R. (eds) Evaluation and Exploration of Genetic Resources: Pre-breeding. Proceedings of the Genetic Resources Section Meeting of EUCARPIA, 15–18 March, Clermont-Ferrand, France. EUCARPIA (European Association for Research on Plant Breeding), pp. 1–10. Rohlf, J.F. (1998) NTSYS-pc: Numerical Taxonomy and Multivariate Analysis System, Version 2.0. Exeter Software, Setauket, New York. 4 Analysis of Farmer-preferred Traits as a Basis for Participatory Improvement of East African Highland Bananas in Uganda

A. Barekye,1* P. Tongoona,2 J. Derera,2 M.D. Laing2 and W.K. Tushemereirwe1 1National Agricultural Research Organisation (NARO), Kampala, Uganda; 2University of KwaZulu-Natal, Pietermaritzburg, South Africa

Abstract Our aim was to establish farmers’ knowledge of black Sigatoka disease, farmers’ and consumers’ preferences for East African highland bananas (Musa spp. AAA-EA), and the qualities desired in new disease-resistant banana genotypes. A structured questionnaire was given to 59 households during October to December 2007. Results indicated that 7% and 3% of farmers in medium and low production zones, respectively, were aware of black Sigatoka disease. East African highland bananas were preferred to introduced banana cultivars because of their superior qualities when cooked, early maturity and easy marketability. However, these preferred bananas produced small bunches, lacked pest and disease resistance and did not tolerate poor soils or drought. Farmers desired new banana cultivars with heavy bunches, resistance to pests and diseases, tolerance of drought, early maturity and marketable traits that would retain the most important attributes of pleasant taste, soft texture, aroma and yellow colour that characterize local East African highland bananas. These findings highlight the importance of farmer involvement in the identification of traits for the improvement of East African highland bananas.

4.1 Introduction highland bananas face production, use and marketing constraints. In Uganda, banana consumption is largely One of the major constraints affecting limited to highland banana cultivars, popu- banana production in Uganda is black Sigatoka, larly known as East African highland bananas caused by the fungus Mycosphaerella fijiensis. (Musa spp. AAA-EA), that are endemic to the The disease attacks the leaves, decreasing the East African region (Purseglove, 1972). These functional leaf area, which reduces the quality bananas constitute more than 75% of the total and quantity of the fruit because fruit from bananas grown in Uganda (Gold et al., 1994; infected plants ripens prematurely, before 2002b; Rutherford and Gowen, 2003). Despite proper filling. Black Sigatoka can cause yield their popularity and uniqueness, East African losses of up to 37% in East African highland

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 30 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Farmer-preferred Traits for Improvement of Bananas 31

bananas (Tushemereirwe, 1996). Cultural con- 4.2 Materials and Methods trol measures have been recommended to farmers (Tushemereirwe et al., 2000; Rutherford 4.2.1 Study area and sampling and Gowen, 2003), yet the disease appears to procedure be increasing rapidly. It is not clear whether it is the deployment of unreliable control measures A survey was carried out in the districts of or a lack of knowledge of the disease by farm- Nakaseke and Masaka, which were selected ers that is contributing to this increase. to represent areas with low and medium lev- Based on the magnitude of banana pro- els of banana production, respectively. The duction constraints and levels, banana produc- survey was conducted in October 2007 in tion zones in Uganda have been classified into Nakaseke and in November 2007 in Masaka. three major zones (Rutherford and Gowen, Administratively, several sub-counties 2003): the east and central zone, where banana (8–12) make up a district. Each sub-county is production has severely declined and many further divided into smaller units called farmers have abandoned the crop because of parishes (6–8 per sub-county). The lowest pests, diseases and poor soils (among other structure is the village and several villages reasons); the south, where banana productiv- make up a parish. In each zone, one sub- ity is at an intermediate level, but where there county was selected and a list of its parishes is moderate decline; and the western zone, obtained. Three parishes were randomly where banana productivity remains high but selected in the low production zone and four there has been some decline. The Ugandan parishes in the medium production zone in National Banana Research Programme has order to have proportional representation of established benchmark sites at Luwero (east- parishes in the two sub-counties. Five to six ern/central zone, low productivity), Masaka/ villages were randomly selected in each par- Ntungamo (southern zone, medium produc- ish. With the help of field assistants and the tivity), and Mbarara/Bushenyi (western zone, local chief, farmers were selected randomly high productivity). Black Sigatoka is one of the from each village by ballot, each household major constraints reducing banana productiv- being allocated a ballot paper. The numbers ity in the low and medium production zones; of farmers selected per village were propor- however, it was not clear whether farmer per- tional to the number of households in the vil- ceptions of the disease in these two zones lage, with a maximum of two farmers would be the same. selected per village. In total, 30 respondents Conventional breeding has improved the were selected from Nakaseke and 29 from disease and pest resistance of East African Masaka district. highland bananas (Ssebuliba et al., 2000; Pillay et al., 2004; Tushemereirwe et al., 2005), but the pest- and disease-resistant genotypes have largely not been acceptable to end users 4.2.2 Data collection and analysis because they do not meet consumer requirements (Rutherford and Gowen, 2003; A structured questionnaire was administered Nowakunda and Tushemereirwe, 2004). This involving open-ended questions that allowed might suggest that the banana breeders’ farmers to give responses on pests, diseases selection criteria were not entirely in agree- and reasons for their preferences for East ment with the farmers’ requirements. The African highland bananas, in comparison objectives of this study were to assess farm- with introduced banana hybrids, as well as to ers’ knowledge of black Sigatoka disease in suggest traits that should be incorporated into central Uganda and to document the unique the new banana hybrids. The respondents traits that give East African highland bananas were also requested to quantify the relative their special status among banana farming importance of cooked food colour, aroma, communities in Uganda, as a basis for the taste and texture/mouth feel in influencing development of new black Sigatoka-resistant overall acceptability of new banana materials. bananas. As a measure of the relative importance of 32 A. Barekye et al.

each attribute, respondents were given a fixed 4.3.1 Problems of East African highland number of beans (10/respondent) to distrib- bananas in Uganda ute among cards representing each attribute. The frequencies of farmers’ responses to Farmers noted that the local bananas had the questionnaire were computed using SPSS serious constraints: they were highly statistical software, version 15.0. The responses affected by pests and diseases, did not tol- on aroma, texture, colour and taste were also erate poor soils, were affected by drought analysed and computed into frequencies of and produced small bunches (Table 4.2). approval or non-approval of the trait. Although identified by only a small proportion of farmers (2.5%), banana bacterial wilt (Xanthomonas wilt) was considered as 4.3 Results a constraint in the low banana production zone and about 44% of farmers were able About 30% of farmers in the low production to describe its symptoms (Table 4.3). About zone and 37% of the farmers in the medium 21% of farmers in the medium production production zone liked East African highland zone and 2% in the low production zone bananas because they are soft, have the pre- were able to identify the symptoms of ferred taste and have a yellow colour after banana streak virus. Some 36% of farmers cooking. About 28% of farmers in the low in the low production zone and 35% of production zone and 12% of farmers in the farmers in the medium production zone medium production zone liked East African were able to describe the symptoms and highland bananas because they were market- damage associated with the banana weevil. able. From an agronomic perspective, 14% of In both areas, very few farmers (3.1% the farmers in the medium production zone and 6.9% in low and medium production preferred East African highland bananas zones, respectively) were able to describe because they mature early, compared with 6% the symptoms of black Sigatoka or men- who preferred them in the low production tioned it as a constraint of banana produc- zone (Table 4.1). tion (Table 4.3).

Table 4.1. Reasons for farmers preferring East African highland bananas compared with introduced genotypes in low and medium production zones of Uganda. N, number of respondents per production zone.

Proportion of responses (%)

Low production Medium production Reason zone (N = 30) zone (N = 29)

Accessible planting material 0.0 3.8 Demands less labour 4.7 3.8 Early maturing 5.8 14.1 Easily intercropped 7.0 0.0 Good food qualities (soft, taste) 30.3 37.1 Highly marketable 27.9 11.5 Lives longer than 5 years 14.0 10.3 Locally known 0.0 1.3 Meets cultural norms 0.0 1.3 Produces heavy bunches 2.3 6.4 Produces many suckers 3.5 2.6 Provides shelter 0.0 1.3 Tolerates drought 3.5 2.6 Tolerates poor soil fertility 1.2 2.6 Used to feed animals 0.0 1.3 Farmer-preferred Traits for Improvement of Bananas 33

Table 4.2. Problems of East African highland bananas in low and medium production zones of Uganda. N, number of respondents per production zone.

Proportion of responses (%)

Low production zone Medium production zone Reason (N = 30) (N = 29)

Affected by banana bacterial wilt 2.5 0.0 Affected by drought 2.5 5.6 Affected by nematodes 2.5 2.8 Affected by weevils 17.5 33.3 Difficult to manage 2.5 13.9 Do not tolerate poor soils 2.5 19.4 Not resistant to diseases 10.0 8.3 Produce small bunches 60.0 16.7

Table 4.3. Farmers’ knowledge of pests and diseases on local bananas in low and medium production zones of Uganda. N, number of respondents per production zone.

Proportion of responses (%)

Constraint Low production zone (N = 30) Medium production zone (N = 29)

Banana bacterial wilt 43.8 0.0 Banana nematodes 9.4 17.2 Banana streak virus 1.6 20.7 Banana thrips 0.0 6.9 Banana weevils 35.9 34.5 Black Sigatoka 3.1 6.9 Cigar end rot 1.6 6.9 Fusarium wilt 4.7 6.9

4.3.2 Traits preferred by farmers in 4.3.3 Verification of quality traits new banana genotypes preferred by farmers

Farmers were asked to guide the breeders According to farmers, taste and texture were on what traits they should include in new the most important food quality traits that materials being developed to meet con- influenced the overall acceptability of new sumer needs. The preferences were that materials. Food colour and aroma were less new genotypes should have good food but equally important in determining accept- qualities, heavy bunches, resistance to dis- ability (Table 4.5). eases and pests, early maturity, tolerance to drought and high market value (Table 4.4). When the farmers’ rankings of preferred 4.4 Discussion traits were computed into aggregate scores, good food qualities (taste, softness, colour) Farmers identified that East African highland had the highest aggregate score, followed bananas produce small bunches (Table 4.2), closely by the attribute of heavy bunches. which is an indicator of reduced yields. Overall, farmers attached equal impor- The reduced annual banana yield of 14 t/ha tance to resistance to diseases and pests, estimated from a local banana cultivar – tolerance to drought and early maturity ‘Mbazirume’ (Erima, 2011) compared with (Table 4.4). the annual yield potential of 40–60 t/ha 34 A. Barekye et al.

Table 4.4. Qualities that would be desired in new cultivars by farmers in Uganda. For each quality attribute the aggregate was calculated by multiplying number of responses by a weighting given to each importance ranking (1st = 4; 2nd = 3; 3rd = 2; 4th = 1) and summing the results.

Number of farmers (N = 59)

Trait Rank 1 Rank 2 Rank 3 Rank 4 Aggregate

Early maturing 8 3 4 1 50 Good food quality (taste, softness, colour) 10 19 11 6 125 Heavy bunches 13 15 9 5 120 Live longer 3 1 1 1 18 Marketable 3 2 6 7 37 Resistant to pests and diseases 8 5 2 1 52 Tolerant to drought 7 6 2 0 50 Tolerant to poor soils 2 0 0 1 9

Table 4.5. Relative importance of food quality farmers about banana diseases. This is impor- attributes as perceived by farmers. N, number of tant because farmer knowledge of disease will respondents. enhance the adoption of control strategies. Allocation by farmers (%) Attribute (N = 59) 4.4.1 Traits preferred by farmers Aroma 15 Food colour 15 Farmers liked the East African highland Taste 41 bananas because of their food quality and Texture 29 their easy marketability. Consumers are willing to pay a higher price for the local bananas compared with the introduced banana (Bagamba et al., 2000) was perceived to be hybrids (from the International Transit caused by banana weevils, low levels of Centre, ITC-Belgium), mainly because of banana management (Bagamba et al., 2000) their superior taste (Akankwasa et al., 2008). and Xanthomonas wilt. Xanthomonas wilt One of the reasons that led to an expansion of was only identified in the low banana pro- banana cultivation in south-western Uganda duction zone, where it has recently appeared was increased access to urban markets for the first time (Tushemereirwe et al., 2003). (Bagamba, 2007). A higher percentage of At the time of the survey, the disease had not farmers in the medium production zone pre- spread to the medium banana production ferred early maturing varieties (Table 4.1), zone. Also, because of the presence of this possibly because of competition for the mar- new disease outbreak, there was an intensive ket, whereas in the low production zone there training programme in areas where the dis- was high demand for bananas, so the local ease occurred. banana market is always guaranteed. A low proportion of farmers had knowl- In a study by Katungi et al. (2001) and edge of black Sigatoka as a banana production Gold et al. (2002a) in the low banana produc- constraint (Table 4.3). Earlier studies by tion zone, in which farmers were requested to Bagamba et al. (2000) had indicated that farm- give their selection criteria for choosing ers in central Uganda where banana produc- among traditional cooking banana cultivars, tion had declined were not aware of black they chose bunch size, taste, longevity and Sigatoka and attributed its symptoms to the marketability. The most important outcome banana weevil. The current study suggests of the survey reported here is that farmers that the situation has not changed since then from the low and medium banana production and that there is a need to work with exten- zones expressed preference for the traits of sion staff to design programmes to educate food quality, heavy bunches, resistance to Farmer-preferred Traits for Improvement of Bananas 35

pests and diseases, and tolerance of drought, nutritional value of the product is important among others (Table 4.4). This implies that (Ayinde et al., 2010). For most crops, consumer the same materials can be bred and promoted preferences are an important component of the in the two banana production zones. overall acceptability of new varieties (IRRI, 1985; Janick, 2005). However, consumer qualities are complex traits for which to breed 4.4.2 Verification of farmer-preferred (Spillane and Thro, 2000), and success in secur- traits in new banana materials ing acceptability is not guaranteed.

In the present investigation, farmers were asked to quantify the consumer traits they 4.5 Conclusion considered important. A pleasant taste, soft texture, yellow food colour and aroma, in that This study has shown that farmers were not order, were identified as the most important very aware of black Sigatoka as a banana pro- consumer traits in the choice of new banana duction constraint. The survey also estab- materials. lished that farmers desired to have new In a study carried out in Luwero, one of banana materials that maintain the traits the areas in the low banana production zone, desired by consumers and the early maturity farmers indicated to Rutherford and Gowen of local bananas. Also, breeders should aim to (2003) that taste and soft texture were among select new materials with heavy bunches, the traits that constituted acceptable food. resistance to pests and diseases, tolerance of Recently, Batte et al. (2008) reported that the soft drought and early maturity if they are to be texture and yellow colour of the cooked prod- adopted by farmers. The verification of the uct were the most important sensory parame- preferred food quality traits indicated that ters determining the acceptability of new the desired taste, soft texture, yellow colour banana hybrids to farmers. In another recent and aroma of any new materials influence study, Akankwasa et al. (2008) reported that overall acceptability of the new product. taste was an important attribute for accepting a Therefore, banana breeders should aim to new product, while other studies have sug- incorporate these end user-preferred traits if gested that in addition to sensory aspects, the the new materials are to be adopted.

References

Akankwasa, K., Mugisha, J., Tushemereirwe, W. and Abele, S. (2008) Consumer acceptability and willing- ness to pay for introduced dessert bananas. In: Banana 2008 Abstracts. Banana and Plantain in Africa: Harnessing International Partnerships to Increase Research Impact, 5–9 October 2008. Leisure Lodge Resort Mombasa, Kenya. International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria, p. 25. Ayinde, O.E., Adewumi, M.O. and Folorunsho, W.O. (2010) Consumer preferences of banana (Musa spp.) in Kwara State, Nigeria. Acta Horticulturae 879, 89–93. Bagamba, F. (2007) Market access and agricultural production: the case of banana production in Uganda. PhD thesis, Wageningen University, Wageningen, The Netherlands. Bagamba, F., Ssenyonga, J., Tushemereirwe, W., Katungi, E., Gold, C. and Katwijukye, A. (2000) Characterisation of banana production systems in central Uganda. Research Report, National Agricultural Research Organisation (NARO), Entebbe, Uganda. Batte, M., Tukamuhabwa, P., Pillay, M. and Tushemereirwe, W. (2008) Sensory qualities and acceptability of East African highland banana derived secondary triploid hybrids. In: Banana 2008 Abstracts. Banana and Plantain in Africa: Harnessing International Partnerships to Increase Research Impact, 5–9 October 2008. Leisure Lodge Resort Mombasa, Kenya. International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria, p. 118. Erima, R. (2011) Performance of East African highland banana derived hybrids in Uganda. MSc thesis, Makerere University, Kampala, Uganda. 36 A. Barekye et al.

Gold, C.S., Speijer, P.R., Karamura, E.B., Tushemereirwe, W.K. and Kashaija, I.N. (1994) Survey methodologies for pest and disease assessment in Uganda. African Crop Science Journal 2, 309–321. Gold, C.S., Kiggundu, A., Abera, A.M.K. and Karamura, D. (2002a) Selection criteria of Musa cultivars through a farmer participatory appraisal survey in Uganda. Experimental Agriculture 38, 29–38. Gold, C.S., Kiggundu, A., Abera, A.M.K. and Karamura, D. (2002b) Diversity, distribution and farmer preference of Musa cultivars in Uganda. Experimental Agriculture 38, 39–50. IRRI (1985) Annual Report for 1984, International Rice Research Institute, Los Baños, Philippines. Janick, J. (2005) Horticultural plant breeding: past accomplishments, future directions. Acta Horticulturae 694, 61–65. Katungi, E., Tushemereirwe, W., Ngambeki, D., Namaganda, J., Nankinga, C., Ragama, P., Kikulwe, E., Katwijukye, A., Barekye, A., Nowakunda, K. and Atiku, L. (2001) Characterisation of Banana Production Systems in Central Uganda: Resource Access, Survival Strategies and Propensity to Adopt Technological Options. Baseline Draft Report. National Agricultural Research Organisation (NARO), Entebbe, Uganda. Nowakunda, K. and Tushemereirwe, W. (2004) Farmer acceptance of introduced banana genotypes in Uganda. African Crop Science Journal 12, 1–6. Pillay, M., Ssebuliba, R., Hartman, J., Vuylsteke, D., Talengera, D. and Tushemereirwe, W. (2004) Conventional breeding strategies to enhance the sustainability of Musa biodiversity conservation for endemic cultivars. African Crop Science Journal 12, 59–66. Purseglove, J. W. (1972) Tropical Crops. Monocotyledons. Longman, London. Rutherford, M. and Gowen, S. (2003) Crop Protection Programme: Integrated Management of Banana Diseases in Uganda, R7567(ZA0372). Final Technical Report, 1 January 2000–30 June 2003. CABI Bioscience/University of Reading, UK. Spillane, C. and Thro, A.M. (2000) Participatorisk forskning og fattigdomsbekæmpende bioteknologi (Farmer participatory research and pro-poor agricultural biotechnology). Den Ny Verden – Tidsskrift for Internationale Studier (DNV) (The New World – Journal for International Studies) 33(1), 59–91. Dansk Institut for Internationale Studier (DIIS) (Danish Institute for International Studies (DIIS), Copenhagen. [Journal no longer published, and early articles not available]. Ssebuliba, R., Vuylsteke, D., Hartman, J., Makumbi, D., Talengera, D., Rubaihayo, P., Magambo, S., Nuwagaba, L., Namanya, P. and Karamura, E. (2000) Towards improving highland bananas. Uganda Journal of Agricultural Sciences 5, 36–38. Tushemereirwe, W.K. (1996) Factors influencing the expression of leaf spot diseases of highland bananas in Uganda. PhD thesis, University of Reading, UK. Tushemereirwe, W.K., Holderness, M., Gold, C.S., Karamura, E.B. and Deadman, M. (2000) Effects of disease induced defoliation and leaf pruning on growth and yield in highland bananas. Acta Horticulturae 540, 336–341. Tushemereirwe, W.K., Kangire, A., Smith, J., Ssekiwoko, F., Nakyanzi, M., Kataama, D., Musitwa, C. and Karyeija, R. (2003) An outbreak of bacterial wilt on banana in Uganda. Infomusa 12(2), 6–8. Tushemereirwe, W.K., Gahakwa, D., Batte, M., Ssali, T., Namanya, P., Pillay, M. and Talengera, D. (2005) Development and promotion of banana genotypes resistant to weevils, black Sigatoka, nematodes and bacterial wilt. In: Abstracts. Biotechnology, Breeding and Seed Systems for African Crops, 24–27 January 2005, Nairobi, Kenya. The Rockefeller Foundation, Nairobi, Kenya, p. 186. 5 Agronomic Evaluation of Common and Improved Dessert Banana Cultivars at Different Altitudes across Burundi

M. Kamira,1* R.J. Crichton,2 J.-P. Kanyaruguru,3 P.J.A. van Asten,4 G. Blomme,5 J. Lorenzen,4 E. Njukwe,6 I. Van den Bergh,2 E. Ouma6 and P. Muchunguzi4 1Bioversity International, Bukavu, Democratic Republic of Congo; 2Bioversity International, Montpellier, France; 3Bioversity International, Bujumbura, Burundi; 4International Institute of Tropical Agriculture (IITA), Kampala, Uganda; 5Bioversity International, Kampala, Uganda; 6IITA, Bujumbura, Burundi

Abstract Banana is an important crop for food and income in Burundi. However, average annual yields are low (5 t/ha) because of low and declining soil fertility, and pest and disease pressure. To help overcome the challenges to banana production in the Great Lakes region of Central Africa, the Consortium for the Improvement of Agriculture-based Livelihoods in Central Africa (CIALCA) has been promoting and facilitating access to new high-yielding, pest- and disease-resistant improved hybrid banana cultivars with good consumer acceptability. The agronomic performance of the improved hybrid ‘FHIA-17’ and six commonly grown dessert banana cultivars was evaluated at six sites with contrasting altitudes across Burundi from 2008 to 2012. The data were analysed using linear mixed-effects modelling. ‘FHIA-17’ significantly outperformed the other cultivars as it had the heaviest bunch weight, was in the group of cultivars with the most hands and fruits, and the fruits were long and thick. The cultivars ‘ITC0680’, ‘Gros Michel’, ‘Prata’ and ‘Yangambi Km5’ had the next best agronomic performance, while the cultivars ‘Ikigurube’ and ‘Kamaramasenge’ had the poorest performance. The high agronomic performance of ‘FHIA-17’ shown in this research demonstrates how its increased cultivation may help to ensure the continued production of dessert types of bananas in Burundi and the food and income security of the population.

5.1 Introduction the Great Lakes region, is one of the poorest countries in the world, with more than half of The Great Lakes region in Central Africa is a the population living below the poverty line major production area of bananas (Musa spp.), (UNDP, 2011). The majority of the population which has a higher per capita consumption depends on agriculture for a living. With an than anywhere else in the world (Karamura annual production of close to 2 million t, et al., 1998). Burundi, located at the heart of banana is the main crop grown in Burundi,

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 37 38 M. Kamira et al.

before sweet potato and cassava (FAOSTAT, To help overcome the challenges to 2010). The crop occupies approximately 17% of banana production in Central Africa, the the cultivated land area, represents 40% of the Con sortium for the Improvement of total agricultural production (CIALCA, 2007) Agriculture-based Livelihoods in Central and provides an important source of food and Africa (CIALCA) has been promoting and income. The banana fruit is eaten cooked as a facilitating access to new high-yielding, pest- vegetable or ripe as a fruit and is also used to and disease-resistant improved hybrid produce beer and wine (Rishirumuhirwa, 2010). banana cultivars that have good consumer The most common cultivars in the Great acceptability (CIALCA, 2010). In this chapter, Lakes region belong to the East African high- the results of a CIALCA-led agronomic land banana group (EAHB; AAA genome), evaluation in Burundi of the improved hybrid and are mainly used for cooking and beer/ ‘FHIA-17’ (FHIA, 1993) and commonly wine production. EAHB plants grow well at grown dessert banana cultivars are reported. altitudes of 1000–2000 m above sea level If ‘FHIA-17’ shows high agronomic (masl) (Karamura et al., 1998). Other cooking performance, it is hoped that its wider types include the plantains (AAB) and ABB dissemination to farmers and smallholders cooking bananas such as ‘Bluggoe’ and in the Great Lakes region could help to ensure ‘Pisang Awak’. Both of these are more vigor- food and income security in the face of ous at lower elevations (0–600 masl for present and future challenges to banana plantains and <1000 masl for ABB cooking production. types). The most common dessert cultivars in Burundi are ‘Kamaramasenge’ (AAB) and ‘Dwarf Cavendish’ (AAA) (Rishirumuhirwa, 2010), both of which can also be used for beer 5.2 Materials and Methods making. A number of newly introduced dessert banana cultivars are also grown, Trials of the dessert banana hybrid ‘FHIA- including ‘Gros Michel’ (AAA) and its dwarf 17’ and the commonly grown cultivars mutant ‘Highgate’, and the ‘Giant Cavendish’ ‘Gros Michel’, ‘Ikigurube’, ‘ITC0680’, ‘Kamara- types (AAA) ‘Poyo’, ‘Lacatan’ and ‘Williams’. masenge’, ‘Prata’ and ‘Yangambi Km5’ The Cavendish dessert bananas are generally (Table 5.1) were carried out between found at lower altitudes (<800 masl), whilst January 2008 to March 2012 at six sites Gros Michel types are found at a slightly across Burundi (Table 5.2). The cultivars higher altitude range (Karamura et al., 1998). were planted from December 2007 to ‘Prata’ (AAB, ‘Pome’) is another dessert February 2008, with the exception of cultivar, mainly grown at lower altitudes in ‘FHIA-17’, which was planted in January– the region, though in Burundi it still performs February 2010. Site latitude and longitude well in the highlands (De Langhe, 1986). data were obtained by GPS (global position- Average annual yields, however, are ing system) (Table 5.2). The annual rainfall very low, at around 5 t/ha (FAOSTAT, 2010). was derived from radar images provided Major production constraints include pests by the CGIAR (Consultative Group on and diseases (Xanthomonas wilt, Fusarium International Agricultural Research) Research wilt, bunchy top disease, black leaf streak, Program on Climate Change, Agriculture nematodes and weevils), low and declining and Food Security (CCAFS) for each year soil fertility (Gold et al., 1994; INIBAP, 2003; from 2008 to 2011, and averaged (Table 5.2). CIALCA, 2007) and irregular weather pat- The soil chemical characteristics of the sites terns (CIALCA, 2008). These production con- were determined by collecting soil samples straints are exacerbated by the fact that using an auger, from 0 to 30 cm depth, at farmers have poor access to improved agro- the middle and corners of each block. Soil nomic practices and production inputs, such samples were analysed at the Ugandan as fertilizers, clean planting materials and National Agri cultural Research Organisa- improved cultivars with high yield and tion (NARO) Kawanda soils laboratory disease resistance traits. (Table 5.3). Agronomic Evaluation of Dessert Banana Cultivars 39

Table 5.1. Origin, classification and use of cultivars.

Cultivar Landrace/hybrid Subgroup Genome group Use

‘FHIA-17’ ‘Highgate’ hybrid Gros Michel AAAA Dessert ‘Gros Michel’ Synthetic hybrid Gros Michel AAA Dessert ‘Ikigurube’ Landrace Cavendish AAA Dessert, beer ‘ITC0680’ Landrace Cavendish AAA Dessert ‘Yangambi Km5’ Landrace Ibota AAA Dessert, beer ‘Kamaramasenge’ Landrace Kamaramasenge AAB Dessert, beer, wine ‘Prata’ Landrace Pome AAB Dessert, beer

Table 5.2. Site location, altitude and annual rainfall.

Province Site Latitude (S) Longitude (E) Altitude (masl)a Annual rainfall (mm)

Cibitoke Muyange 2°46′17″ 29°7′2″ 1162 1245 Gitega Gisuru 3°22′44″ 29°52′16″ 1600 1068 Mashitsi 3°18′58″ 29°54′14″ 1646 1068 Muririmbo 3°11′35″ 29°50′40″ 1682 1140 Kirundo Murore 2°32′58″ 30°14′17″ 1632 1162 Yaranda 2°30′42″ 30°6′53″ 1409 1162 amasl, metres above sea level

Table 5.3. Soil characteristics of the sites.

Organic N P Ca Mg K

Province Site pH matter (%) (%) (mg/kg) (cmolc/kg) (cmolc/kg) (cmolc/kg)

Cibitoke Muyange 6.2 7.07 0.33 8.82 3.37 1.88 0.91 Gitega Gisuru 5.3 6.78 0.29 6.77 0.91 0.51 0.69 Mashitsi 4.7 7.82 0.34 trace 0.25 0.03 0.04 Muririmbo 4.5 10.72 0.47 3.01 0.20 trace 0.25 Kirundo Murore 5.5 10.06 0.42 trace 3.23 1.97 0.44 Yaranda 5.3 5.07 0.26 trace 1.64 0.99 0.72

Tissue culture plantlets of the cultivar (Carlier et al., 2003). Not all of the cultivars ‘FHIA-17’ were obtained from the Inter- were planted at each site (Table 5.4). Plants national Transit Centre (ITC), Leuven, were spaced at 3 × 2 m, providing a density Belgium and multiplied at the Agrobiotech of 1667 plants/ha. The planting hole was tissue culture laboratory at Bujumbura, 60 × 60 × 60 cm. Decomposed cow manure Burundi. Plantlet hardening was done at was added into each of the holes at plant- the Institut de Recherche Agronomique et ing, at 10 kg/hole. Weeding was done at Zootechnique (IRAZ) nurseries in Burundi. monthly intervals. De-suckering and de- Suckers of the cultivars ‘Gros Michel’, leafing (of dead leaves) were carried out as ‘Ikigurube’, ‘ITC0680’, ‘Yangambi Km5’, and when required. Some plants died after ‘Kamaramasenge’ and ‘Prata’ were obtained planting owing to extreme heat and these from the IRAZ germplasm collection at were replaced promptly where possible, Mashitsi. Fifteen plantlets of each variety, in either with new plantlets or with suckers three replicates of five plantlets, were planted from surviving mats of the same cultivar type out on the sites in a randomized design in the trial. Three plants were kept per mat. 40 M. Kamira et al.

Table 5.4. Sites of the experiments and the cultivars planted at each site.

Site Cultivars

Gisuru ‘FHIA-17’, ‘Yangambi Km5’, ‘Kamaramasenge’, ‘Prata’ Mashitsi ‘FHIA-17’, ‘Yangambi Km5’, ‘Kamaramasenge’, ‘Prata’, ‘Ikigurube’ Muririmbo ‘FHIA-17’, ‘Yangambi Km5’, ‘Kamaramasenge’, ‘Prata’, ‘Ikigurube’, ‘Gros Michel’ Murore ‘FHIA-17’, ‘Yangambi Km5’, ‘Kamaramasenge’, ‘Prata’, ‘Gros Michel’, ‘ITC0680’ Muyange ‘FHIA-17’, ‘Yangambi Km5’, ‘Kamaramasenge’, ‘Prata’, ‘Gros Michel’, ‘ITC0680’ Yaranda ‘FHIA-17’, ‘Yangambi Km5’, ‘Gros Michel’, ‘ITC0680’

Mulching (with grass) was done at the begin- interacting effects), comparing them with ning of each dry season. Where necessary, one another and choosing the model with forked wooden sticks were used to provide the lowest Akaike Information Criteria support for the plants to prevent them from (AIC) value. toppling over. The model fit was assessed by plotting Data on growth and yield were the residuals. Data points outside the collected from the plant and ratoon crop biologically acceptable range were cycles at flowering and at harvest. removed as necessary. The following traits Variables measured at flowering were: were square root transformed: pseudostem days from planting to flowering (only girth, bunch weight, number of hands/ measured using plants that were not bunch and total number of fruits. Parameter replaced); pseudostem height; pseudostem estimates with lower and upper 95% girth at 1 m above soil level; and number confidence intervals (CIs) were obtained of functional leaves. Variables measured at using the languageR package. Because of harvest were: days from planting to the small sample sizes, the CIs were very harvest (only measured using plants that large and so the tables are presented using were not replaced); bunch weight; number the mean and standard deviation (sd) of of hands/bunch; total number of fruits; the raw data. To assess whether the means length of fruits; and the girth of fruits. For of each trait, by cultivar, where significantly descriptions of how each trait was different from one another or not, a Tukey measured, see Carlier et al., (2003). HSD (honestly significant difference) test Statistical analysis was carried out was done on the output of a one-factor using the R language and environment ANOVA, implemented using the ‘agricolae’ (R Devel opment Core Team, 2010) and the package. R packages lme4 (Bates et al., 2012), languageR Average annual yield (t/ha) for each (Baayen, 2011) and agricolae (Mendiburu, cultivar was calculated as: (average bunch 2012). To account for the replication across weight over all crop cycles (kg)/1000) × the six sites and the pseudo-replication (days in a year, 365/crop cycle of the plant across crop cycles, the data were analysed crop) × (planting density, 1667 plants/ha); using linear mixed-effects modelling, with this is based on a modified version of the a Gaussian distribution. Each plant trait yield calculation in Gaidashova et al. (2008). was analysed as the response variable. The As the first crop cycle tends to be longer, and random effects were site and crop cycle, and the bunch weights of the parent plant tend no model selection was done on these. Fixed to be lower than subsequent ratoon crop effects were cultivar and altitude. Model cycles, the average annual yield estimates are selection of the fixed effects was done by likely to be conservative. The average creating all possible models (a ‘null’ model annual yield was calculated using cultivar using the intercept, cultivar only, altitude averages for bunch weight and crop cycle, only, cultivar and altitude as additive instead of data from individual plants, as effects, and cultivar and altitude as the plants that had both crop cycle and Agronomic Evaluation of Dessert Banana Cultivars 41

bunch weight data were too few and highly basis (Plate 1). ‘Ikigurube’ was the shortest skewed across the cultivars and sites. cultivar (mean height 156 cm) while ‘Gros Because the yield estimates use cultivar Michel’ and ‘Prata’ were the tallest (352 averages, no statistical analyses were and 324 cm). ‘Kamaramasenge’ had the performed on this variable. thinnest girth (35 cm) whilst ‘FHIA-17’, ‘Gros Michel’, ‘ITC0680’ and ‘Prata’ had the thickest (ranging from 48 to 53 cm) (Table 5.5). 5.3 Results The number of functional leaves was significantly affected by cultivar only 5.3.1 Plant performance at flowering (P < 0.001). ‘Kamaramasenge’ and ‘ITC0680’ had the lowest number of functional leaves The number of days from planting to (6.4 and 7.6, respectively), while the remaining flowering was significantly affected by cultivars made up a group with a greater cultivar only (P < 0.001). ‘Gros Michel’ and number of leaves (ranging from 7.7 to 8.4) ‘Kamaramasenge’ took the least amount of (Table 5.5). time to reach shooting (476 days) while ‘FHIA-17’ took the longest (563 days) (Table 5.5). The pseudostem height and girth at 5.3.2 Plant performance at harvest 1 m above soil level were significantly affected by an interaction between cultivar The number of days from planting to harvest and altitude (P < 0.001). All cultivars had (the crop cycle) was significantly affected by the tallest and thickest pseudostems at the cultivar only (P < 0.001). ‘Kamaramasenge’, site with the lowest altitude, Muyange, ‘Yangambi Km5’ and ‘Gros Michel’ took the 1162 masl. Between the altitudes of 1409 least amount of time to reach harvest and 1682 masl, the cultivars tended to (ranging from 612 to 621 days), while grow to a lower height and a thinner girth, ‘Ikigurube’ took the longest (718 days) though this occurred on a case-by-case (Table 5.6).

Table 5.5. Plant performance traits of cultivars at flowering, averaged over sites. Means followed by the same letter within a row are not significantly different at P = 0.05.

‘Yangambi Cultivar ‘FHIA-17’ ‘Gros Michel’ ‘Ikigurube’ ‘ITC0680’ Km5’ ‘Kamaramasenge’ ‘Prata’

Days from planting to flowering No. plants 57 19 17 13 86 31 29 Mean 563a 476b 556ab 520ab 516ab 476b 516ab sd 74 106 78 91 119 69 70 Pseudostem girth (cm) No. plants 101 34 27 27 182 100 72 Mean 48ab 53a 43bc 48ab 40cd 35d 53a sd 12 9 9 10 12 6 8 Pseudostem height (cm) No. plants 101 34 27 27 182 100 72 Mean 207c 352a 156d 271b 247b 268b 324a sd 35 85 30 76 56 41 45 No. functional leaves No. plants 101 34 27 27 182 100 72 Mean 7.8a 7.9a 8.4a 7.6ab 7.7a 6.4b 7.8a sd 2.1 2.0 2.1 1.8 2.4 2.2 2.4 42 M. Kamira et al.

Table 5.6. Plant performance traits of cultivars at harvest. Means followed by the same letter within a row are not significantly different at P = 0.05. The average annual yield (t/ha) was calculated using the following formula: average bunch weight over all crop cycles (kg/1000) × (days in a year, 365/crop cycle of plant crop) × (planting density, 1667 plants/ha) and was not subject to statistical analyses because cultivar averages were used rather than individual data points.

‘Yangambi Cultivar ‘FHIA-17’ ‘Gros Michel’ ‘Ikigurube’ ‘ITC0680’ Km5’ ‘Kamaramasenge’ ‘Prata’

Average annual yield (t/ha) Mean 23.6 12.7 8.1 14.2 11.7 8.0 12.6 Bunch weight (kg) No. plants 67 14 11 11 119 76 47 Mean 26.7a 13.0bc 9.5cd 15.7b 11.9bc 8.0d 13.3bc sd 9.8 2.4 3.0 6.1 4.0 3.5 3.4 Days from planting to harvest (crop cycle) No. plants 55 13 16 8 67 26 24 Mean 688ab 621b 718a 670ab 620b 612b 641ab sd 74 98 61 59 122 68 81 Fruit girth (cm) No. plants 67 14 11 11 119 76 47 Mean 12.7a 11.4ab 11.2ab 12.8a 10.1bc 8.4c 10.7b sd 1.8 1.9 2.4 1.1 2.0 2.9 1.9 Fruit length (cm) No. plants 67 14 11 11 119 76 47 Mean 15.2a 14.1abc 13.5abc 14.5ab 11.9cd 9.8d 12.9bc sd 2.6 2.5 2.7 2.6 2.4 2.4 2.6 Number of fruits/bunch No. plants 67 14 11 11 119 76 46 Mean 171a 166ab 105de 145abc 127bcd 91e 111cde sd 55 52 30 17 52 51 29 Number of hands/bunch No. plants 67 14 11 11 119 76 47 Mean 10.8a 9.1ab 7.0c 8.7bc 9.3ab 8.3bc 8.5bc sd 1.9 3.3 2.0 2.1 2.3 2.4 1.7

Bunch weight was significantly affected ‘Kamaramasenge’ and ‘Ikigurube’ had the by an interaction between cultivar and altitude lightest bunch weights (8.0 and 9.5 kg, (P < 0.001). ‘Yangambi Km5’, ‘Kamaramasenge’ respectively) (Table 5.6). and ‘Prata’ tended to produce heavier bunches Average annual yield was calculated at lower altitudes, ‘Gros Michel’ tended to using cultivar averages for crop cycle and produce bunches with similar weights across bunch weight and thus the difference between all altitudes, while ‘ITC0680’ tended to produce cultivars was not statistically tested. ‘FHIA- heavier bunches at higher altitudes (Plate 2). 17’ had the greatest average annual yield of ‘Ikigurube’ was only grown at two sites 23.6 t/ha. ‘ITC0680’ had the next greatest (Mashitsi and Muririmbo), both at an altitude average annual yield (14.2 t/ha), ‘Gros greater than 1600 masl, and there was a Michel’, ‘Prata’ and ‘Yangambi Km5’ had significant difference between the bunch similar yields to one another (12.7 t/ha, weights at these sites. ‘FHIA-17’ had the 12.6 t/ha and 11.7 t/ha respectively), while heaviest bunches (26.7 kg). This bunch weight ‘Kamaramasenge’ and ‘Ikigurube’ had the was almost 11 kg heavier than the bunch lowest (8.0 and 8.1 t/ha respectively). weights of the cultivars ‘Yangambi Km5’, ‘Gros The number of hands per bunch was Michel’, ‘Prata’ and ‘ITC0680’, which formed significantly affected by cultivar only (P < 0.001). the next group (weight range 11.9 to 15.7 kg). ‘Gros Michel’, ‘Yangambi Km5’ and ‘FHIA-17’ Agronomic Evaluation of Dessert Banana Cultivars 43

had the most hands per bunch (ranging from an average length crop cycle compared with 9.1 to 10.8), while ‘Ikigurube’, ‘Kamara- the other cultivars. Using this information, masenge’, ‘Prata’ and ‘ITC0680’ had the least average annual yield (t/ha) for ‘FHIA-17’ was (ranging from 7.0 to 8.7 hands) (Table 5.6). calculated as 23.6 t/ha using a modified and The number of fruits per bunch was conservative version of the yield calculation significantly affected by an interaction that appears in Gaidashova et al. (2008). This between cultivar and altitude (P < 0.001). average annual yield is much greater than the ‘FHIA-17’, ‘Yangambi Km5’ and ‘Prata’ estimated annual banana yield currently tended to produce more fruits at lower attained in Burundi of 5 t/ha (FAOSTAT, 2010). altitudes, while ‘ITC0680’ tended to produce ‘FHIA-17’ was also in the group of cultivars more fruits at higher altitudes. For the with the most hands and fruits per bunch, and remaining cultivars, altitude either the fruits were long and thick. Furthermore, increased or decreased the number of fruits ‘FHIA-17’ had a robust, short and thick pseu- per bunch on a case-by-case basis (similar to dostem, which is a desirable trait in East Africa, bunch weight, Plate 2). ‘ITC0680’, ‘Gros where bananas are often cultivated in hilly Michel’ and ‘FHIA-17’ had the greatest conditions (Vigheri, 1997) and the short plant number of fruits per bunch (ranging from stature makes the removal of the early male 145 to 171), while ‘Kamaramasenge’, buds – to prevent insect vector transmission of ‘Ikigurube’ and ‘Prata’ had the least (91 to Xanthomonas wilt – easier. 111) (Table 5.6). This strong agronomic performance of The length and girth of a fruit were both ‘FHIA-17’ has also been demonstrated in significantly affected by an interaction between Uganda (Nowakunda et al., 2000), Kenya cultivar and altitude (P < 0.001). Finger girth (Njuguna et al., 2008), Rwanda (Gaidashova tended to be a more stable trait across altitude et al., 2008) and Mozambique (Uazire et al., than finger length (Table 5.6). ‘Gros Michel’, 2008), where it outperformed all other banana ‘Yangambi Km5’ and ‘Kamaramasenge’ tended cultivars. The agronomic performance of to produce longer fruits at lower altitudes, ‘FHIA-17’ in the Burundi experiment while ‘FHIA-17’, ‘Ikigurube’ and ‘Prata’ tended described in this chapter is, however, lower to produce a stable fruit length across altitude, than the performance attained in most of and ‘ITC0680’ tended to produce longer fruits these other experiments. For instance, in at higher altitudes (Plate 3). ‘Ikigurube’, ‘Gros Rwanda, at an altitude of 980 masl, ‘FHIA-17’ Michel’, ‘ITC0680’ and ‘FHIA-17’ had the long- had a crop cycle of 462 days and a mean est fruits (ranging from 13.5 to 15.2 cm); bunch weight of 53.4 kg (Gaidashova et al., ‘Ikigurube’, ‘Gros Michel’, ‘FHIA-17’ and 2008), and in Kenya, at an altitude of 1500 ‘ITC0680’ had the thickest fruits (ranging from masl, ‘FHIA-17’ had a crop cycle of 565 days 11.2 to 12.8 cm); and ‘Kamaramasenge’ and and a mean bunch weight of 36.03 kg ‘Yangambi Km5’ had the shortest (9.8 and 11.9 (Njuguna et al., 2008). In Mozambique, at an cm, respectively) and thinnest (8.4 and 10.1 cm, altitude of 12 masl, ‘FHIA-17’ had a shorter respectively) (Table 5.6). crop cycle (461 days) than was attained in Burundi, but also produced lighter bunches (21.5 kg) (Uazire et al., 2008). The next best performing cultivars in the 5.4 Discussion trials were ‘ITC0680’, ‘Gros Michel’, ‘Prata’ and ‘Yangambi Km5’. These cultivars had The agronomic performance of the introduced crop cycles that were shorter than that of improved hybrid dessert banana ‘FHIA-17’ ‘FHIA-17’ (but not significantly so) and were and six commonly grown ‘local’ dessert banana the group that had the second heaviest bunch cultivars was evaluated in up to six sites weights after ‘FHIA-17’. Both ‘Gros Michel’ across Burundi. and ‘ITC0680’ tended to perform equally well The improved hybrid cultivar ‘FHIA-17’ or better at higher, rather than lower, alti- significantly outperformed the other cultivars tudes. ‘Gros Michel’ has been noted as grow- as it had the heaviest bunch weight and ing well at higher altitudes around Lake 44 M. Kamira et al.

Victoria (above 1100 masl) (De Langhe, 1986). f.sp. cubense race 1 (Nowakunda et al., 2000; ‘ITC0680’, though, belongs to the ‘Cavendish’ Orjeda et al., 2000), Mycosphaerella fijiensis subgroup and cultivars of this subgroup are (FHIA, 1993; Nowakunda et al., 2000; Molina generally grown in low-lying (less than 800 Tirado and Castaño Zapata, 2003); M. eumusae masl) coastal regions (Karamura et al., 1998). (Mourichon et al., 1997; Sulliman et al., 2012) These results, which are contrary to general and the banana weevil (Nowakunda et al., expectations, may be a result of the absence of 2000). ‘FHIA-17’ may, therefore, be a good sites at altitudes lower than 1162 masl, and to cultivar to use in areas where these pests and a lack of replication among sites at the lower diseases are present. But is susceptible to altitudes, i.e. there was only one site at 1162 Xanthomonas campestris pv. musacearum masl and one site at 1409 masl, compared with (Tripathi et al., 2008), banana bunchy top four sites above 1600 masl. Thus, strong differ- virus (BBTV) (Gaidashova et al., 2008; Molina ences between high and low altitude sites et al., 2010) and the nematode Radopholus may simply represent differences due to site similis (Viaene et al., 1997; Moens et al., 2005). (e.g. management practices, local weather pat- A major impediment to the wider uptake terns, observer effect), rather than to altitude. of ‘FHIA-17’ may be a lack of consumer The cultivars with the poorest perfor- acceptability. For example, of 200 respondents mance were ‘Ikigurube’ and ‘Kamaramasenge’. in Mozambique, 46% thought it did not smell The crop cycles for these cultivars were not good, 38% thought it was not similar to tradi- significantly different from that of ‘FHIA-17’, tional varieties, 64% rated it as ‘not ideal’ and but the bunch weights were much lower, at 9.5 kg 53% would not continue to consume it (Uazire and 8.0 kg respectively. The corresponding et al., 2008). Similar consumer acceptance average annual yields for these cultivars were results have been reported around the world low, at 8.1 t/ha and 8.0 t/ha, respectively. for the FHIA hybrids, and the hybrids of other Cultivars in the AAA ‘Cavendish’ subgroup, breeding programmes (Molina et al., 2010). such as ‘Ikigurube’, and AAB genome culti- Nevertheless, in Burundi, ‘FHIA-17’ is vars such as ‘Kamaramasenge’, are generally appreciated for its short height, sweet fla- considered to be lowland varieties (Karamura vour and large finger size, and is gradually et al., 1998) and this may account for the rela- replacing the most common dessert bananas – tively poor performance of these cultivars at ‘Kamaramasenge’ and ‘Gros Michel’. ‘Gros the comparatively high altitude sites used in Michel’ and ‘Kamaramasenge’ are widely these trials. Although the average annual cultivated in the rural areas surrounding yields obtained for these cultivars are low, Bujumbura, the capital of Burundi, and these they are still greater than the current annual zones are now increasingly affected by yield for banana production in Burundi. This Xanthomonas wilt. ‘FHIA-17’ is grown by improved performance may be the result of farmers in Kayanza, Ngozi, Karusi, Kirundo, improved agricultural practices, such as Muyinga and Makamba provinces. In paral- mulching, as taught by CIALCA. lel, top government officials are also involved A key reason for introducing improved in its cultivation in Ngozi and Muyinga hybrids into production systems is their provinces. increased resistance to, or tolerance of, pests ‘FHIA-17’ is sold as a dessert banana in the and diseases because of their genetically Bujumbura markets, where a bunch is sold for diverse pedigrees. Pests and diseases were around 10,000 Burundian Francs (1 US$ = 1494 not specifically measured during these exper- BIF, January 2013) (J.-P. Kanyaruguru and iments, though they are thought to be low/ E. Njukwe, December 2012, Bujumbura, per- absent at the trial sites that were used. It is, sonal observation). The ‘Garukirigitoke Farmers’ however, possible that pests and diseases Association’ in Muyinga province, eastern may have been partially responsible for the Burundi, sells FHIA bunches to factories in lower performance of the commonly grown Tanzania where they are processed into banana local cultivars compared with that of ‘FHIA- juice and banana chips (J.-P. Kanyaruguru and 17’. For instance, ‘FHIA-17’ has demonstrated E. Njukwe, December 2012, Bujumbura, resistance/tolerance to Fusarium oxysporum personal observation). These farmers, trained Agronomic Evaluation of Dessert Banana Cultivars 45

to use macropropagation technology by farmers. With technical support from CIALCA, CIALCA, have installed four macropropa- Floresta received financial support from the gation units; in December 2012, they had over governments of Belgium, the Netherlands 8 ha of both ‘FHIA-17’ and ‘FHIA-25’varieties and USA, while CADEK received financial established. They recently started selling support from the government of Italy to plantlets of FHIA varieties to farmers in neigh- expand macropropagation activities. With bouring provinces and are involved in farmer- the support of the Belgian government, the organized training on macropropagation and NGOs Concern Worldwide in Kirundo and field management practices led by NGOs and Caritas International Belgique in Mwakiro the Provincial Department for Agriculture and Muyinga are also promoting the false and Livestock (DPAE). decapitation technique for the production of With an ever-increasing interest in healthy ‘FHIA-17’ planting material. The pri- ‘FHIA-17’, this cultivar is now also multiplied vate tissue culture laboratory Phytolabu, using macropropagation techniques in based in Bujumbura, has also received mate- Makamba Province by the NGO (non- rial and technical support from the govern- government organization) CADEK (Collectif ment of Belgium to expand and produce des Associations pour le Développement more tissue culture-derived banana planting Economique de la Paroisse Kibago), for its material as starting stocks to establish new own use, and around Bujumbura by the NGO fields free of Xanthomonas wilt. Floresta as an income-generating activity. Because of the high agronomic perfor- Floresta has already sold over 1700 ‘FHIA-17’ mance of improved hybrids, the govern- plantlets. A remaining bottleneck is the higher ment of Burundi has ordered a large amount cost of macropropagation-derived FHIA of FHIA planting material for distribution plantlets (1200 BIF) compared with suckers of throughout the regions. Donors have also local cultivars (500 BIF). The higher cost of shown interest in fast-tracking the distribu- macropropagation-derived FHIA plantlets tion of healthy ‘FHIA-17’ plantlets to over- may be attributed to the scarcity of FHIA come food insecurity in Burundi. Wide-scale varieties and to the high demand for them. cultivation of ‘FHIA-17’ in Burundi may FHIA suckers are sold for 800–1000 BIF. In con- contribute to the sustainable production of trast, macropropagation-derived plantlets of a dessert banana cultivar in the region ‘Incakara’ and ‘Sohokunkorere’ (local AAA-EA and to food and income security for the cultivars) are sold for only 700 BIF by Muyinga population.

References

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I. Sikyolo,1* C. Sivirihauma,1 V. Ndungo,1 E. De Langhe,2 W. Ocimati3 and G. Blomme3 1Université Catholique du Graben (UCG), Butembo, Democratic Republic of Congo; 2Katholieke Universiteit Leuven (KUL), Belgium; 3Bioversity International, Uganda

Abstract The Congo Basin is an important centre of diversity for plantain. Plantain is mainly grown below 1200 m above sea level (masl). However, some plantain cultivars can be found up to 2200 masl in the highlands along the Albertine Rift Valley in North Kivu. This study assessed the effect of altitude on plantain growth and yield at four sites in North Kivu (Mavivi, 1066 masl; Maboya, 1412 masl; Butembo, 1815 masl; Ndihira, 2172 masl). Five plantain (AAB genome group) cultivars commonly grown in North Kivu were assessed at each site. The cultivars were three from the ‘French’ clone set – ‘Nguma’, ‘Vuhindi’ and ‘Vuhembe’, and two ‘False Horn’ cultivars – ‘Kotina’ and ‘Musilongo’. Fifteen vigorous sword suckers of each cultivar obtained from farmers’ fields were planted in three replications of five plants, at each site. Growth and yield parameters were assessed over a period of 2.5 years. The same parameters were also assessed in 20 farmers’ fields in Butembo, Maboya and Mavivi for ‘Musilongo’ and ‘Kotina’, while ‘Vuhembe’ was assessed at only one farm in Ndihira. At the experimental sites, plant height, pseudostem circumference and bunch weight generally decreased with an increase in altitude, while first crop cycle duration, time from flowering to harvest and mean number of suckers increased with altitude. At the flowering stage, the average parent plant height across the five cultivars varied significantly by site and was 239 cm at Maboya, 251 cm at Butembo, 258 cm at Ndihira and 316 cm at Mavivi. First crop cycle duration across all plantain cultivars ranged from 15.6 months at Mavivi to 28.8 months at Ndihira, while time from flowering to harvest ranged from 4.4 months at Mavivi to 7.9 months at Ndihira. The number of suckers per parent plant at flowering across the five cultivars increased from two at Mavivi to seven at Ndihira. The average bunch weight was significantly higher at the lowest site compared with the highest. The cultivars ‘Kotina’ and ‘Vuhembe’ seemed to be adapted to both low and higher altitude sites. A large number of partially developed and hence non- harvestable bunches were observed at Ndihira and, to a lesser extent, at Butembo. In addition, a significant increase in total rachis length was observed at Ndihira. Although there is a 400 m altitude difference between Maboya and Butembo, no significant difference was observed in bunch weight. The altitude effect is most probably overshadowed by the clayey and compact soil that reduced yield at Maboya. Similar growth and yield trends were observed in farmers’ fields for plant height at flowering, time from flowering to harvest and bunch weight. These findings indicate that an increase in altitude and the corresponding lower temperatures negatively influence plant growth, first crop cycle duration and yield, while positively influencing suckering.

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 48 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Growth and Yield of Plantain Cultivars 49

6.1 Introduction 1200 mm and for Mutwanga 1000 mm (Engineers Without Borders, 2007; Enzyme Bananas and plantains are a staple food in Refiners Association, 2010). The average tropical and subtropical regions, including price of a 30 kg bunch of plantains in 2011 in West, Central and East Africa (Frison and Beni, Butembo and Mutwanga was US$6.00. Sharrock, 1998). The Congo Basin and the In contrast, the average price of a 30 kg countries around the Gulf of Guinea are a bunch of AAA-EA cooking bananas was secondary centre of diversity for plantains US$3.00 in 2011, while the price for a 30 kg (Musa AAB), while the East and Central bunch of AAA-EA brewing bananas was African highlands are a centre of diversity only US$1.50 (Ndungo, Vigheri, 2011, for the East African highland cooking and personal communication). beer bananas (Musa AAA-EA) (Swennen As a result of the high market price for et al., 1995). Over 100 plantain cultivars have plantains in the Beni and Lubero territories, so far been recorded in the Congo Basin North Kivu, there is a high demand for plan- (Dhed’a et al., 2011). tain planting material, even in villages located Although plantains grow best at lower at higher elevations, but knowledge of the elevations (<1200 m above sea level – masl), adaptability of a wide range of plantain culti- a few plantain cultivars are also found at vars to higher elevations (1400 to 2200 masl) higher elevations along the Albertine Rift is lacking. Experiments were thus established Valley in North Kivu, eastern Democratic at different altitudes in North Kivu to assess Republic of Congo (DR Congo) (Ndungo, the effect of altitude on plantain growth and Vigheri, 2011, personal communication). For yield. In addition, plantain growth and yield example, the plantain cultivar ‘Vuhembe’ is data were collected from ratoon plants on grown in farmers’ fields at Ndihira, located farms at these same sites. at 2172 masl. In North Kivu, plantains and highland bananas are often intercropped with annual crops (e.g. legumes and taro) and 6.2 Materials and Methods perennial tree crops (e.g. coffee and cacao) (Katungu, 2011). Annual yields of plantains The study assessed the effect of altitude on and bananas in eastern DR Congo are relatively plantain growth and yield at four sites in low and range from 3 to 6 t/ha (CIALCA, North Kivu: Mavivi at 1066 masl, 00.56902°N, 2007). Plantain growth and yield are, however, 29.4789°E; Maboya at 1412 masl, 00.25019°N, strongly affected by microclimate (i.e. tempera- 29.3299°E; Butembo at 1815 masl, 00.11786°N, ture and rainfall), soil fertility and altitude in 29.2587°E and Ndihira at 2172 masl, North Kivu. For example, Mutwanga, located 00.24963°S, 29.2049°E. Five plantain (AAB at 1049 masl and at the foot of the Rwenzori genome group) cultivars commonly grown in Mountains, has a microclimate with excellent North Kivu were assessed at each site. The volcanic-derived soils and the annual plantain cultivars were three from the ‘French’ clone yield is 40 t/ha (Ndungo, Vigheri, 2011, per- set: ‘Nguma’, ‘Vuhindi’ and ‘Vuhembe’, and sonal communication). two ‘False Horn’ cultivars: ‘Kotina’ and Over 70% of plantain bunches produced ‘Musilongo’. Vigorous sword suckers of in Mutwanga are exported, via the Kasindi ‘Kotina’ were obtained in Butembo, suckers border crossing, to urban markets in Uganda. of ‘Musilongo’ from Maboya, suckers of Plantain cultivation in the districts sur- ‘Nguma’ from Mavivi, while suckers of rounding the Ugandan capital of Kampala ‘Vuhembe’ were obtained from Ndihira and seems very difficult. Poor soil fertility in suckers of ‘Vuhindi’ were obtained from central Uganda seems to be the main limiting farmers’ fields at Mutwanga (1049 masl). factor (Sseguya et al., 1999) as the altitude Fifteen vigorous sword suckers of each ranges from 1150 to 1250 masl, which is cultivar obtained from farmers’ fields were comparable to that of Mutwanga. Rainfall planted in October 2008, in three replications patterns (i.e. seasons) are similar, with the of five plants, at each site. Plant spacing was average annual rainfall for Central Uganda 2.5 × 3 m (1333 mats/ha). 50 I. Sikyolo et al.

Growth and yield were assessed over a measure against insect vector transmission period of 2.5 years. Growth traits were of Xanthomonas wilt. This disease is pre- assessed during the first crop cycle at 4 and sent in most banana-producing zones of 8 months after planting and at flowering North Kivu. stage. The following growth and yield traits Soil samples were collected at each site were assessed at the four sites: plant height (0–20 cm soil layer) in February 2009 (i.e. (cm), pseudostem girth at soil level (cm), 4 months after the experiment was estab- number of functional leaves (with at least lished) and were analysed at the Kawanda 50% of green leaf lamina), number of lateral soils laboratory of the National Agricultural shoots (i.e. suckers), number of days from Research Organisation (NARO) in Uganda. planting to flowering (bunch emergence), Statistical analysis was carried out using number of days from flowering to harvest the SAS Version 8.2 statistical package (SAS and bunch weight (kg). Institute, 1989). The number of plantain mats among the total number of Musa mats was assessed in eight farmers’ fields at Mavivi, 12 fields at 6.3 Results and Discussion Mutwanga, ten fields each in Maboya and Mabuku (1349 masl, 0.3081°N; 29.3065°E), At the experimental sites, plant height, pseu- 20 fields in Butembo and in one plot at dostem circumference and bunch weight Ndihira. Farms containing at least 50 Musa (Table 6.1) generally decreased with an mats were randomly selected at each loca- increase in altitude, while first crop cycle tion, except at Ndihira where only one farmer duration, i.e. time from planting to harvest grew ‘Pisang Awak’ (ABB) and five mats of (Table 6.2), and number of suckers (Table 6.3) ‘Vuhembe’. In addition, growth and yield increased with altitude. At flowering stage, of the widely grown plantain cultivars the tallest and most vigorous plants were ‘Musilongo’ and ‘Kotina’ were assessed in the observed at the lowest altitude (1066 masl) same farmers’ fields in Mutwanga, Mavivi, site at Mavivi. At flowering stage, the plan- Mabuku, Maboya and Butembo, while the tains in Butembo had the highest number of plantain ‘Vuhembe’ was assessed at one farm functional leaves (Table 6.1). in Ndihira. Mean first crop cycle duration across all Plant height at flowering (cm), number plantain cultivars ranged from 15.6 months of days from flowering to harvest and bunch at Mavivi to 28.8 months at Ndihira, while weight (kg) were assessed on two or three mean time from flowering to harvest ranged ratoon plants per selected variety at each from 4.4 months at Mavivi to 7.9 months at farm. The length of the rachis/inflorescence Ndihira (Table 6.2). The cycle duration at (i.e. female and male parts) of different Ndihira (2172 masl) was particularly long, plantain cultivars growing in farmers’ fields nearly double the cycle duration at Mavivi, at Mavivi (the lowest altitude) and in the and ranged from 26.1 to 30.4 months for experiment at Ndihira (the highest altitude) the different plantain cultivars. The altitude was assessed. At least four plants were difference between Ndihira and Mavivi is assessed per cultivar at each site. The total 1106 m, which corresponds to an average rachis was divided into three parts and daily temperature difference of 7.4°C length of the bunch or female inflorescence, (Table 6.4). Cottin et al. (1987) reported for length of the rachis from the last hand of Martinique that time of flowering is female fruit to tip of the male bud or extrem- strongly influenced by altitude. An altitude ity, and length from the tip of male bud/ shift from 80 to 210 masl resulted in a shift rachis extremity to soil/ground level were in peak flowering time of 2.8 months dur- measured. It was not possible to take ing the 1st cycle to 3.2 months during the additional measurements of rachis length in 2nd cycle, and this extended to 4.2 months the experiments at Mavivi, Maboya and in the 3rd cycle. Butembo as all male inflorescence parts Across the five plantain cultivars, the were continuously removed as a preventive mean number of suckers per parent plant at Growth and Yield of Plantain Cultivars 51

Table 6.1. Plant height, pseudostem circumference at soil level, number of functional leaves at flowering and bunch weight for 5 plantain cultivars at 4 locations. For bunch weight, plants in Butembo and Ndihira that produced non-harvestable bunches were not included in the analysis. Percentages of non-harvestable bunches per cultivar are stated in the text. Within a trait, means followed by the same letter (a–d) in a row or the same letter (w–z) in a column are not significantly different according to Tukey’s HSD test (P < 0.05). Elevations above sea level: Ndihira, 2172 m; Butembo, 1815 m; Maboya, 1412 m; Mavivi, 1066 m.

Cultivar/trait Location in order of decreasing altitude ‘Musilongo’ ‘Vuhembe’ ‘Kotina’ ‘Nguma’ ‘Vuhindi’ Mean

Bunch weight (kg) Ndihira 9.9ax 11.2bx 12.5bx 6.8cx 3.9dx 8.9x Butembo 15.7ay 16.0ay 16.9ay 13.8by 12.0by 14.9y Maboya 16.3ay 15.9ay 15.8ay 19.7bz 13.1cy 16.2y Mavivi 25.0az 20.5bz 23.0az 31.5cw 27.8az 25.6z Functional leaves at flowering Ndihira 8.5ax 6.5bx 6.6bx 6.7bx 7.7ax 7.2 Butembo 9.7ax 9.9ay 9.8ay 8.2by 8.5bx 9.2 Maboya 7.1ax 7.9ax 7.4ax 8.5by 7.9ax 7.8 Mavivi 8.9ax 7.2bx 7.3bx 8.0ay 7.3bx 7.7 Plant height (cm) Ndihira 256ax 272ax 262ax 240bx 262ax 258 Butembo 245ax 217by 276cx 266cy 252ax 251 Maboya 215ay 253bx 231by 254by 245bx 240 Mavivi 325az 309bz 278cx 330az 337a 316 Pseudostem circumference (cm) Ndihira 60ax 61ax 58ax 57ax 55bx 58 Butembo 62ax 62ax 64by 54cy 54cx 59 Maboya 58ax 58ay 61bx 59ax 62bx 59 Mavivi 76ay 72bz 64cy 84dz 78ay 75

flowering ranged from 2.1 at Mavivi to 6.9 at was contrary to observations made in the Ndihira (Table 6.3). This indicates that altitude Congo basin (e.g. at the INEAC Yangambi and the corresponding lower temperatures research station) where the first bunch (Table 6.4) had a significant effect on reducing (1st crop) was far larger than ratoon the apical dominance of the mother plant on bunches. It was postulated that this could, sucker development. The ratio of the number to some extent, explain the vigorous plan- of suckers per month from planting to flower- tain suckering observed at the high altitude ing was 0.19 for Mavivi, 0.24 for Maboya, 0.36 sites in eastern DR Congo. The first bunch for Butembo and 0.33 for Ndihira. This indi- was three to four times smaller in the high- cates that a larger number of suckers were land zones, thus leaving far more assimi- produced per unit time at the two highest lates for vigorous sucker development altitude sites. (INEAC, 1960). One could also postulate, as The increased suckering behaviour of part of a source and sink model, that photo- plantains at high altitude sites has been synthates from the leaves of the parent plant reported by INEAC (1960). Plantains grown have to go via the corm and perhaps the in the eastern DR Congo highlands pro- suckers act as a stronger sink for these than duced a small bunch during the first crop the more remote bunches. cycle, while larger bunches were observed Significantly larger bunches were pro- during subsequent cycles. This phenomenon duced at Mavivi than at the other locations 52 I. Sikyolo et al.

Table 6.2. Time from planting to flowering, from flowering to harvest and from planting to harvest for the first crop of 5 plantain cultivars at 4 locations. Within a trait, means followed by the same letter (a–c) in a row or the same letter (x–z) in a column are not significantly different, according to Tukey’s HSD test (P < 0.05). Elevations above sea level: Ndihira, 2172 m; Butembo, 1815 m; Maboya, 1412 m; Mavivi, 1066 m.

Cultivar/trait Location in order of decreasing altitude ‘Musilongo’ ‘Vuhembe’ ‘Kotina’ ‘Nguma’ ‘Vuhindi’ Mean

Flowering to harvest (months) Ndihira 7.8ax 7.1ax 8.0ax 8.0ax 8.5bx 7.9 Butembo 5.3ay 4.6by 4.9by 5.4ay 6.0cy 5.2 Maboya 4.1az 4.4ay 4.9by 5.0by 5.0bz 4.7 Mavivi 4.3az 3.9az 4.8by 4.0az 5.4cz 4.4 Planting to flowering (months) Ndihira 20.9ax 19.0bx 21.2ax 21.6cx 21.9cx 20.9 Butembo 11.0ay 11.9ay 10.7ay 13.1by 14.1by 12.2 Maboya 10.9ay 12.0ay 9.9by 11.6az 12.7cz 11.4 Mavivi 10.0ay 12.6by 9.9ay 12.0bz 11.1bz 11.1 Planting to harvest (months) Ndihira 28.7ax 26.1bx 29.2ax 29.6ax 30.4cx 28.8 Butembo 16.3ay 16.5ay 15.6ay 18.5by 20.1cy 17.4 Maboya 15.1az 16.4ay 14.8by 16.6az 17.7cz 16.1 Mavivi 14.3az 16.4by 14.7ay 15.9az 16.5bz 15.6

Table 6.3. Number of suckers at 4 and 8 months after planting, and at flowering for 5 plantain cultivars at 4 locations. Within each trait, means followed by the same letter (a–c) in a row or by the same letter (w–z) in a column are not significantly different, according to Tukey’s HSD test (P < 0.05). Elevations above sea level: Ndihira, 2172 m; Butembo, 1815 m; Maboya, 1412 m; Mavivi, 1066 m.

Cultivar/trait Location in order of decreasing altitude ‘Musilongo’ ‘Vuhembe’ ‘Kotina’ ‘Nguma’ ‘Vuhindi’ Mean

Suckers per plant at 4 months after planting Ndihira 0.20ax 1.20bx 0.30ax 0.00cx 0.00cx 0.34 Butembo 0.27ax 0.33ay 0.00by 0.08by 0.33ay 0.20 Maboya 0.80ay 0.00bz 0.20az 0.08by 0.15az 0.20 Mavivi 0.00az 0.00az 1.08bw 0.58cz 0.00ax 0.30 Suckers per plant at 8 months after planting Ndihira 0.40ax 2.20bx 1.50cx 0.40ax 0.10dx 0.90 Butembo 2.13ay 2.03ax 1.37bx 0.58cx 1.63ay 1.50 Maboya 2.18ay 2.20ax 2.06ay 1.23by 0.58cz 1.70 Mavivi 1.53az 0.72by 0.33cz 2.61az 1.06aw 1.30 Suckers per plant at flowering Ndihira 6.75ax 8.40bx 6.40ax 7.40bx 5.70ax 6.90 Butembo 3.87ay 4.90ay 3.60ay 5.25ay 4.00ay 4.30 Maboya 2.80az 2.20az 2.07az 2.87az 3.62by 2.70 Mavivi 2.33az 1.83az 1.37aw 2.00aw 2.83az 2.10

(Table 6.1). Bunch weight at Mavivi was 2× the largest bunches at Ndihira (Table 6.1). (for ‘Kotina’) to 7× (for ‘Vuhindi’) higher than However, although there is a 400 m altitude for the same cultivars at Ndihira (Table 6.1). difference between Maboya and Butembo, ‘Musilongo’, ‘Vuhembe’ and ‘Kotina’ produced no significant difference in bunch weight Growth and Yield of Plantain Cultivars 53

Table 6.4. (a) Temperature and rainfall data for Mutwanga, Beni/Mavivi, Butembo and Ndihira (2009–2011). Temperature data were computed from records during 2009, 2010 and 2011 at the ENRA (Enzyme Refiners Association) meteorological station in Beni, the meteorological station at Rughenda airport in Butembo and the INERA (Institut National pour l’Étude et la Recherche Agronomique) meteorological station at Ndihira. Rainfall data for Mutwanga, Beni/Mavivi and Butembo were obtained from CIAT (International Centre for Tropical Agriculture), Colombia (computed from radar images), while rainfall data for Ndihira were obtained from the INERA meteorological station at Ndihira. (b) Separate data for 2009– 2011 on mean rainfall for Maboya and mean evaporation for Ndihara. The data for Maboya were obtained from CIAT and the evaporation data for Nidhara data from the INERA meteorological station at Ndihira. (a)

Temperature (°C) Temperature (°C) Rain Rain Max. Min. Mean(mm) Max. Min. Mean (mm)

Month Mutwanga (1049 masl)a Beni/Mavivi (1066 masl)

Jan. 28.8 16.7 22.9 40 27.8 18.6 23.2 37 Feb. 29.3 17.3 23.3 71 29.9 19.2 24.6 102 Mar. 29.0 17.3 23.1 111 29.2 19.9 24.6 138 April 28.7 17.0 23 44 29.6 19.6 24.6 80 May 28.7 16.9 23 51 28.3 19.8 24 93 June 28.4 16.9 22.6 67 27.2 19.6 23.4 110 July 25.4 16.4 21.6 63 27.3 19.3 23.3 100 Aug. 28.0 17.2 22.6 158 27.5 19.3 23.4 303 Sep. 28.6 17.0 22.7 117 25.4 18.9 21.1 150 Oct. 28.0 17.0 22.5 78 27.3 19.1 23.2 128 Nov. 27.9 17.0 22.4 88 26.8 19.7 23.2 106 Dec. 28.3 16.8 22.5 60 27.7 19.7 23.7 63 Annual 28.3 17.0 22.7 948 27.8 19.4 23.5 1411

(b)

Evaporation Rain (mm) (mm/day)

Maboya Ndihira Butembo (1815 masl) Ndihira (2172 masl) (1412 masl) (2172 masl)

Jan. 23.6 12.7 18.2 32 20.2 10.7 15.5 48 48 4.5 Feb. 26.2 12.5 19.4 103 21.8 10.6 16.2 101 88 4.5 Mar. 25.4 12.4 18.9 107 21.8 11.5 16.7 129 108 5.2 April 25.5 13.4 19.5 46 21.5 12.3 16.9 131 68 5.1 May 25 14.4 19.7 50 20.3 11.2 15.8 52 73 2.9 June 24.3 13.1 18.7 65 19.9 11.2 15.6 69 83 2.6 July 24.4 13.3 18.9 39 21.4 10.4 15.9 45 77 4.1 Aug. 25.2 13.2 19.2 140 21.1 10.9 16 134 251 3.9 Sep. 24.8 13 18.9 142 20.9 11.1 16 141 168 5.4 Oct. 24.6 12.9 18.8 124 21.3 10.4 15.9 107 119 3.1 Nov. 24.5 13.1 18.8 112 20.8 11.4 16.1 235 146 5.8 Dec. 24.1 13.6 18.9 79 21.8 10.7 16.3 146 70 4.9 Annual 24.8 13.1 19.0 1038 21.1 11.0 16.1 1338 1299 4.3 amasl, metres above sea level. was observed (Table 6.1); the altitude A large number of partially developed difference/effect here might have been over- and hence non-harvestable bunches were shadowed by the more compact and clayey observed at Ndihira (47% for ‘Vuhembe’, soil at Maboya (Table 6.5). 53% for ‘Musilongo’, 47% for ‘Kotina’, 60% for 54 I. Sikyolo et al.

Table 6.5. Soil characteristics at the four experimental sites (0–20 cm soil layer).

Location/altitude (masl)

Soil property Unit Mavivi (1066) Maboya (1412) Butembo (1815) Ndihira (2172)

Ca cmol(+)/kg soil 6.36 6.00 6.20 6.13 K cmol(+)/kg soil 0.83 0.82 1.14 0.90 Mg cmol(+)/kg soil 1.85 0.98 1.43 1.06 N % 0.23 0.32 0.26 0.25 P mg/kg 2.2 4.2 10.6 36.1 Clay % 16.3 42.3 42.3 30.3 Organic matter % 5.0 5.0 5.1 5.1 pH – 6.7 5.0 5.7 5.2 Sand % 64.4 24.4 32.4 46.4 Silt % 19.3 33.3 25.3 23.3 Texture class – Sandy loam Clay Sandy clay Sandy clay loam

‘Nguma’ and 67% for ‘Vuhindi’) and to a grown mats in Butembo and 1% in Ndihira. lesser extent at Butembo (27% for ‘Vuhindi’ Plantains are associated with coffee (Coffea and 7% for ‘Nguma’). In addition to poor robusta), cacao (Theobroma cacao), papaya fruit filling, a significant increase in rachis (Carica papaya), aloe vera (Aloe vera) and length (male inflorescence part) was moringa (Moringa oleifera) at the low altitude observed at Ndihira (Table 6.6). In fact, the sites (Mavivi and Mutwanga). At Maboya total length of the rachis was significantly and Mabuku, only 5% of farmers grow plan- longer for all plantain cultivars at Ndihira tains in association with coffee or annual than for those at Mavivi (Table 6.6). A signifi- crops. At the higher elevation sites (Butembo cantly shorter plant height and a longer and Ndihira) plantains and bananas are rachis length at Ndihira meant that the mainly intercropped with annual crops. rachis or male bud grew up to slightly over Similar growth and yields to those at 1 m from soil level (Table 6.6). The ratio of the four experimental sites were observed the height of the male bud above the ground on ratoon plants in farmers’ fields for mean to plant height ranged from 0.68 to 0.71 for plant height at flowering, time from the cultivars at Mavivi and from 0.38 to 0.45 flowering to harvest and bunch weight at Ndihira (Table 6.6). This shows clearly (Table 6.7). There was a significant effect of that the male buds were much closer to the altitude on plant height at flowering stage, ground in relation to plant height at Ndihira number of days from flowering to harvest than at Mavivi. If the total rachis length and and bunch weight for both ‘Kotina’ and plant height are added, this approximates ‘Musilongo’. Mean parent plant height at the total length of the true stem of the parent flowering in farmers’ fields for the cultivars plant. In that case, the plants at Ndihira have assessed was 292 cm at Ndihira (‘Vuhembe’ a true stem length that is 14 to 23% less than only), 286 cm at Butembo, 276 cm at those at Mavivi, depending on the cultivar. Maboya, 297 cm at Mabuku, 338 cm at So altitude reduces total length of the true Mutwanga and 322 cm at Mavivi. Mean stem, but increases the length of true stem time from flowering to harvest in farmers’ allocated to the male section of the inflores- fields for the cultivars assessed ranged cence. The plantains at Ndihira invested from 8.1 months at Ndihira (‘Vuhembe’ their photosynthesis products in lateral only) down to 4.3 months at Mutwanga shoot and male rachis development instead and 4.7 months at Mavivi. Mean bunch of fruit filling/producing large bunches. weight across all plantain cultivars ranged Plantains occupy 61% of all grown mats from 11.2 kg at Ndihira (‘Vuhembe’ only) in Mavivi, 65% in Mutwanga, 23% in up to 29.1 kg at Mutwanga and 22.6 kg at Maboya, 34% in Mabuku, but only 10% of all Mavivi. Growth and Yield of Plantain Cultivars 55

Table 6.6. Measurements (cm) of length of the inflorescence (female, male, total), height of the male bud above ground and plant height of five plantain cultivars at Mavivi (1066 m above sea level – masl) and Ndihira (2172 masl). At least 4 plants of each cultivar were assessed at each site. Means followed by the same letter (a–c) in a row or followed by the same letter (x or y) within a trait in a column are not significantly different according to Tukey’s HSD test (P < 0.05).

Cultivars/location

‘Musilongo’ ‘Vuhembe’ ‘Kotina’ ‘Nguma’ ‘Vuhindi’ Mean

Trait Mavivi (farmers’ fields)

Inflorescence length Female 72bx 61cx 59cx 87ax 72bx 70 Male 59ax 62ax 50bx 49bx 65ax 57 Total 132x 122x 109x 135x 137x 127 Height of male bud 283bx 295bx 272cx 317ax 292bx 292 above ground (H) Plant height (P) 415x 418x 381x 453x 429x 419 H/P 0.68 0.71 0.71 0.70 0.68 0.70

Trait Ndihira (experimental site)

Inflorescence length Female 35by 47ay 34by 47ay 32by 39 Male 117ay 112ay 114ay 133ay 147ay 125 Total 152y 159y 148y 180y 179y 164 Height of male bud 126ay 96ay 119ay 143ay 135ay 124 above ground (H) Plant height (P) 278y 255y 267y 323y 314y 288 H/P 0.45 0.38 0.45 0.44 0.43 0.43

Table 6.7. Plant height at flowering, time from flowering to harvest and bunch weight for widely grown plantain cultivars at the six on-farm sites. Means followed by the same letter (a or b) in a column within a site or the same letter (w–z) in a column for a specific cultivar across sites are not significantly different according to Tukey’s HSD test (P < 0.05).

Site in order of Plant height at Time from flowering Bunch decreasing altitude Cultivar flowering (cm) to harvest (months) weight (kg)

Ndihira ‘Vuhembe’ 292 8.1 11.2 (2172 m) Butembo ‘Kotina’ 286az 6.0az 15.6az (1815 m) ‘Musilongo’ 287az 6.2bz 14.1az Mean 286 6.1 14.9 Maboya ‘Kotina’ 283az 5.4ay 15.6az (1412 m) ‘Musilongo’ 269bw 4.7bx 16.7az Mean 276 5.1 16.2 Mabuku ‘Kotina’ 302ay 5.1ax 16.5az (1349 m) ‘Musilongo’ 292az 4.9ax 16.1az Mean 297 5.0 16.3 Mavivi ‘Kotina’ 317ax 4.9ax 21.5ax (1066 m) ‘Musilongo’ 327bx 4.6bx 23.6bx Mean 322 4.7 22.6 Mutwanga ‘Kotina’ 327ax 4.5ax 28.1ay (1049 m) ‘Musilongo’ 348by 4.2by 30.0by Mean 338 4.3 29.1 56 I. Sikyolo et al.

Table 6.8. Postulated scenario for bunch size and suckering behaviour of plantains according to altitude classes.

1st cycle 2nd cycle

Altitude (masl)a Bunch Suckering Bunchb Suckering

<1200 Large Poorc Smaller Very weakd 1200–1500 Medium Medium Larger Trend to mat permanency 1500–1900 Small Profusee Follow-up studies Follow-up studies needed needed >1900 Very small to not Profuse and Follow-up studies Follow-up studies developed vigorous needed needed amasl, metres above sea level; bCompared with 1st cycle; cDue to strong apical dominance; dGenerally leads to disappearance of the mat; eDue to low apical dominance.

6.4 Conclusion Ndihira. Further studies, at other high altitude sites and during the second cycle, The results of this study indicate that an are needed to confirm the observed vigorous increase in altitude and the resulting lower suckering behaviour of plantains. temperatures negatively influence plantain From the observations on the effect of growth, first crop cycle duration and yield. altitude on plantains by INEAC scientists Plantains grow best and produce larger (INEAC, 1960) and the results of the present bunches at lower elevations. Cultivars study, we postulate in Table 6.8 a scenario ‘Nguma’, ‘Musilongo’ and ‘Vuhindi’ pro- regarding the effect of altitude on bunch size duced the largest bunches at the lowest alti- and suckering behaviour. tude site. ‘Kotina’ and ‘Vuhembe’ seemed to be adapted to both low and higher altitude sites. Altitude significantly affected crop Acknowledgements cycle duration. The average first crop cycle duration at Ndihira (the highest altitude We would like to thank the Directorate General site) was nearly twice as long as that at for Development, Belgium for funding this Mavivi (the lowest altitude experimental research through the Consortium for Improving site). In addition to poor fruit filling, a sig- Agriculture-based Livelihoods in Central Africa nificant increase in rachis length was (CIALCA). In addition, the contributions of the observed at Ndihira. Apical dominance Katholieke Universiteit Leuven (KUL), Belgium exerted by the parent plants seemed to be and the Université Catholique du Graben (UCG), suppressed at the high altitude site at North Kivu, DR Congo are highly appreciated.

References

CIALCA (2007) Musa Sub-Sector Strategic Plan for the Democratic Republic of Congo: 2006–2011. Addressing the Challenges of Integrating Bananas into the Market Economy. Available at: http://www. cialca.org/files/files/Musa%20Sector%20Strategic%20Plans/MSSP-DR-Congo.pdf (accessed 17 July 2012). Cottin, R., Melin, P. and Ganry, J. (1987) Modélisation de la production bananière. Influence de quelques paramètres en Martinique. Fruits 42, 691–701. Dhed’a, D.B., Nzawele, B.D., Roux, N., Ngezahayo, F., Vigheri, N., De Langhe, E., Karamura, D., Picq, C., Mobambo, P., Swennen, R. and Blomme, G. (2011) Musa collection and characterization in central and eastern DR Congo: chronological overview. Acta Horticulturae 897, 87–94. Growth and Yield of Plantain Cultivars 57

Enzyme Refiners Association (ENRA) (2010) Rapport Synthèse Annuelle d’Observation Météorologique pour les Années 2009 et 2010. Beni, Democratic Republic of Congo. Engineers Without Borders (2007) Mulobere–Masaka–Uganda Site Assessment Booklet. Uganda Rural Fund, Richmond, Virginia, Rotary International and Engineers Without Borders USA (EWB-USA), Boulder, Colorado. Available at: https://wiki.umn.edu/pub/EWB/Uganda/Assessment_Booklet.doc (accessed 18 April 2013). Frison, E.A. and Sharrock, S. (1998) The economic, social and nutritional importance of banana in the world. In: Picq, C., Fouré, E., Frison, E.A (eds). Bananas and Food Security: Un Enjeu Économique Majeur pour la Sécurité Alimentaire. Proceedings of an International Symposium held in Douala, Cameroon, 10–14 November 1998. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France, pp. 21-35. INEAC (1960) Rapport Annuel, Groupe Planification Agricole, Volume 1. Institut National pour l’Étude Agronomique du Congo, Bruxelles, Belgium. Katungu, M.G. (2011) Enquête sur l’utilisation des organes (parties) du bananier à part le régime (fruit) en territoire de Beni et de Lubero. BSc thesis, Université Catholique de Graben, Butembo, Democratic Republic of Congo. SAS Institute (1989) SAS/STAT User’s Guide, Version 6, 4th edn, Volume 1. SAS Institute Inc., Cary, North Carolina. Sseguya, H., Semana, A.R. and Bekunda, M.A. (1999) Soil fertility management in the banana-based agriculture of central Uganda: farmers constraints and opinions. African Crop Science Journal 7, 559–567. Swennen, R., Vuylsteke, D. and Ortiz, R. (1995) Phenotypic diversity and patterns of variation in West and Central African plantains (Musa spp., AAB group, Musaceae). Economic Botany 49, 320–327. 7 Macropropagation of Musa spp. in Burundi: A Preliminary Study

P. Lepoint,1* F. Iradukunda1,2 and G. Blomme3 1Bioversity International, Bujumbura, Burundi; 2Université du Burundi, Bujumbura, Burundi; 3Bioversity International, Kampala, Uganda

Abstract Macropropagation is considered as a rapid means of producing, at a local level, numerous plantlets of preferred and/or improved Musa spp. cultivars at a putative low cost. The technology was evaluated in an on-station research-led experiment covering two contrasting agro-ecological sites in Burundi: Bujumbura (818 m above sea level – masl, mean temperature 25°C) and Gitega (1655 masl, mean temperature 19°C). Two types of humidity chambers (a ‘standard’ unit made of wooden planks and plastic sheeting placed under 50% natural shading, versus a ‘prototype’ unit made out of locally available Eucalyptus wood and papyrus [Cyperus] mats), three non-sterilized substrates (sawdust, rice hull and coffee husks) and four Musa cultivars (‘FHIA-17’, AAAA; ‘Igisahira’, AAA-EA, cooking; ‘Kamaramasenge’, AAB, dessert; and the plantain ‘Mzuzu’, AAB) were evaluated in two successive experiments at each site. A third experiment, comprising similar treatments, was subsequently carried out solely in Bujumbura using rice hull and sawdust as substrates. Corm viability, number of days to emergence of the first shoot (latency period) and number of shoots produced per viable corm after scarification (productivity) were recorded. Independent of Musa genotype, unit type and/or substrate, a cooler climate such as that of Gitega was found to be less suitable for macropropagation because corm viability and productivity were reduced and the latency period was doubled. Despite lower temperatures observed in the prototype unit, corm viability and latency period were not significantly altered. Sawdust and rice hull performed significantly better than coffee husks as initiation substrates. Differences linked to genotype were observed in viability of corms, latency period and productivity. Out of the four cultivars tested, ‘Kamaramasenge’ performed poorly with low productivity. In contrast, ‘Igisahira’ produced up to 22 shoots/corm, while ‘FHIA-17’ produced up to 25 and ‘Mzuzu’ produced up to 28. The study has identified a prototype humidity chamber made out of local materials using non-sterilized rice hull (initiation media) as an alternative low-cost option for skilled and motivated resource-poor farmers, farmer groups or associations looking to multiply banana and/or plantain locally at lower altitudes in Burundi. Moreover, clean planting material can be successfully produced under such conditions despite the high pressure from banana bunchy top disease in the Rusizi valley (Bujumbura).

7.1 Introduction generating crops for millions of people in Central and East Africa. In Burundi, they are Bananas (bananas and plantains, Musa spp.) regarded as the most important cash and staple are considered key food security and income- crop, and are typically intercropped around

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 58 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Macropropagation of Musa spp. in Burundi 59

households by smallholders. Reduced soil preferred by the majority of farmers. This is fertility, limited access to land, lack of clean likely to stem from the ease of sucker acquisi- planting material and increasing pest and tion from within a farmer’s own field or through disease pressure are reported by farmers as exchange, the low/symbolic cost and reduced the major constraints reducing banana pro- technical skills involved in the use of conven- duction in the country (Niyongere et al., 2012). tional suckers and low farmer awareness of the The recent introduction to Burundi of banana importance of using ‘clean’ planting materials Xanthomonas wilt, and its swift spread across (Plate 4). However, major disadvantages in 15 of the 17 provinces (N. Niko, Bujumbura the use of conventional suckers include their 2013, personal communication), in addition unknown phytosanitary status, low multiplicat- to the already well-established banana ion rate in the field, cumbersome transport and bunchy top disease (BBTD) in the lowlands the increased timespan needed to produce these and Fusarium wilt throughout the country materials. Moreover, random and uncontrolled (Sebasigari and Stover, 1988), emphasizes the exchange and movement of suckers is reported importance of farmer access to ‘clean’ and as the principal means of pest and disease affordable planting material to replenish dev- spread – in any country. Therefore, natural astated plantations. regeneration cannot suffice (qualitatively or Since the initial studies carried out by the quantitatively) to respond to the huge gap of Institut National pour l’Etude Agronomique ‘healthy’ planting material needed to rejuve- du Congo Belge (INEAC) (Anon., 1955; nate/repopulate diseased plantations and De Langhe, 1961), United Fruit Company increase the acreage under Musa. Honduras, presently known as Chiquita In the context of ‘resource-constrained’ (Barker, 1959; Hamilton, 1965), Empresa (P. van Asten et al., 2013, unpublished results) Brasileira de Pesquisa Agropecuária (Embrapa) Burundian smallholders in need of large (Dantas et al., 1986, 1987) and Corporación quantities of ‘clean’/improved planting mate- Bananera Nacional (CORBANA, Costa Rica) rial, the innovative method for horticultural (Molina, 1986; Perez, 1992; Laprade and Perez, multiplication developed/fine-tuned by the 1994), five distinct methods have been Centre Africain de Recherches sur Bananiers described in the literature for producing large et Plantains (CARBAP) strikes a balance amounts of planting material in a reduced between ‘costly’ in vitro plants and potentially timespan, and are commonly used to establish diseased conventional suckers (Auboiron, new plots. These include: (i) conventional 1997; Kwa, 2000, 2003). PIBS (macropropaga- suckers extracted from fields in production tion) is a technique that enables the produc- (multiplication rate of 1–3/parent plant); tion of numerous shoots from an existing (ii) suckers produced in field multiplication corm, whose lateral buds have been exposed plots (multiplication rate of 10–20/parent beforehand, using a humidity chamber and plant); (iii) plants from micro-corms grown out moistened initiation substrate. When mas- in nurseries; (iv) plants originating from lateral tered, and carried out in disease-free condi- buds on whole corms (PIBS, ‘plants issus de tions, it can be a means of producing locally fragments de bourgeons secondaires’; multiplica- and within 3–4 months, 15–60 ‘healthy’ plant- tion rate of 15–60/parent corm); and (v) tissue lets of preferred and/or improved cultivars culture (TC, multiplication rate of 1000/initial (Lescot and Staver, 2010) at a reduced produc- meristem) plants (Lescot and Staver, 2010). tion cost ranging from US$0.40 (Lefranc et al., Recent surveys (Niyongere et al., 2012) cov- 2010) to US$0.66 (Ouma et al., 2011). The selec- ering CIALCA (Consortium for Improving tion of healthy sword suckers in a disease-free Agriculture-based Livelihoods in Central field, removal of weevil galleries during par- Africa) countries (Rwanda, Burundi and the ing in situ, boiling water treatment of corms to Democratic Republic of Congo – DR Congo) control weevil and nematodes (Tenkouano have confirmed that among the multiple et al., 2006), judicious use of a systemic insecti- sources of available Musa spp. planting mate- cide throughout the macropropagation cycle rial, conventional suckers are often the only (within the unit and in the nursery) are sine known material, and are therefore used and qua non conditions for the production of 60 P. Lepoint et al.

disease/pest-free plantlets in areas where (‘Mzuzu’). The collection was made at the BBTD, nematodes and weevils are prevalent. sword sucker stage, and the corms were sub- In this chapter, the mass-propagation of Musa sequently pared and subjected to boiling spp. within a humidity chamber is evaluated water treatment (for 30 s) before being pre- in distinct Burundian agro-ecologies, using pared (i.e. by removal of leaf sheaths), scari- farmer-friendly options, in a bid to identify fied and placed in the humid chamber. the best package and optimal conditions for A secondary scarification of the shoots that out-scaling to farmers. were produced was carried out to maximize production. Watering of the substrate was carried out directly after planting and subsequently when necessary. Keeping in mind that 7.2 Materials and Methods farmer end users are resource constrained, humid chamber substrates were not steam An on-station CIALCA experiment was initi- sterilized before use, as firewood is scarce and ated in early 2010 in two contrasting agro- costly in the region. ecological sites. Humidity chambers were Data collected included corm viability installed in Bujumbura (818 m above sea (a corm is considered viable if it produces at level (masl), mean temperature 25°C, pres- least one shoot during the multiplication ence of BBTD) and Gitega (1655 masl, mean cycle), latency (number of days from place- temperature 19°C, no BBTD). Four Musa spp. ment in the chambers until emergence of cultivars (‘FHIA-17’ AAAA; ‘Igisahira’ the first shoot from the corm) and produc- AAA-EA, cooking; ‘Kamaramasenge’ AAB, tivity (total number of shoots produced per dessert; and the plantain ‘Mzuzu’ AAB), three viable corm). Air temperature (minimum locally available substrates (sawdust, rice and maximum) within each unit type was hull and coffee husk) and two types of units measured using a mercury min–max ther- (a ‘standard’ unit made out of wooden planks mometer and mean monthly external tem- and plastic sheeting placed under 50% natu- peratures were collected from the closest ral shading, versus a ‘prototype’ unit made weather station for each site. Analysis of out of local materials) were evaluated at data was carried out using the GenStat soft- both sites (Plate 5). The prototype humidity ware package (GenStat, 2008). ANOVA chamber, based on the materials used for its analysis was carried out to determine sig- construction, allows little or no light to filter nificant differences between treatments. through, therefore forcing plantlets to grow Treatment means were separated using in a light-deprived environment. least significant difference at P = 0.05. The Three successive experiments, organ- data from Experiment 3 were analysed ized in a randomized block design, were con- separately as its design differed from that of ducted from January 2010 to January 2011, Experiments 1 and 2. with the third experiment carried out solely in Bujumbura using rice hull and sawdust as initiation substrates. Five corms per cultivar were assessed for each com bination of treat- 7.3 Results ments and at each site in Experiment 1, while four corms per cultivar were assessed for The results confirmed that, independent of each combination of treatments and at each cultivar, substrate and/or type of chamber, a site in Experiment 2, which was replicated cooler climate such as that in Gitega (Table 7.1) two times. Four corms per cultivar were is less suitable for macropropagation than a assessed for each combination of treatments warmer climate. The latency period was in Experiment 3, and each combination of almost twice as long in Gitega as it was in treatments was replicated four times. Bujumbura, whereas the viability and num- The whole Musa spp. corms used in the ber of shoots produced per corm were directly experiments were collected in the field in proportional to temperature and increased Burundi (‘FHIA-17’, ‘Igisahira’, ‘Kamara- with subsequent experiments/experience of masenge’) and in South Kivu, DR Congo the technique (Tables 7.2–7.4). Macropropagation of Musa spp. in Burundi 61

Significant cultivar differences were 2.4 shoots per viable corm in successive observed in the number of plantlets (shoots) experiments. Conversely, ‘Igisahira’, ‘FHIA- produced per corm (Table 7.2). Of the four 17’ and ‘Mzuzu’ respond better to the tech- cultivars tested, it appears clearly that nique, producing from 3.8 to 4.4 shoots per ‘Kamaramasenge’ is not well adapted to the viable corm in Gitega (Experiments 1 and 2), macropropagation technique used in this from 7.8 to 11.0 shoots per viable corm in study, yielding a mean of only 2.6, 2.0 and Bujumbura (Experiments 1 and 2) and from 5.7 to 10.3 shoots per viable corm in Bujumbura Table 7.1. Mean temperatures inside and outside (Experiment 3). In turn, a maximum of seven standard and prototype humidity chambers shoots were formed per corm for ‘Kamara- spanning three consecutive macropropagation masenge’ and up to 28 shoots for ‘Mzuzu’ experiments carried out from January 2010 to under the warm Rusizi plain conditions of January 2011 in Bujumbura and Gitega provinces Bujumbura (Experiment 3). (Burundi). As for the initiation substrates used Temperature (°C) (Table 7.3), the performance of coffee husk was significantly poorer than that of sawdust Treatment Bujumbura Gitega and rice hull, causing both a reduction in shoot production/corm viability and an Inside the prototype unit 25.0 17.6 increase in latency period. Inside the standard unit 26.9 20.0 The type of humidity chamber used Outside 25.1 17.6 (Table 7.4) did not significantly alter corm

Table 7.2. Effect of Musa cultivar on corm viability, latency period, mean and maximum number of shoots produced per viable corm spanning three consecutive macropropagation experiments carried out from January 2010 to January 2011 in Bujumbura (Experiments 1, 2 and 3) and Gitega (Experiments 1 and 2) provinces. ‘n’ = number of corms; means followed by the same letter within a column and experiment are not significantly different at P < 0.05.

No. shoots for Proportion a single corm (no.) viable Latency Site Cultivar n corms (days) Mean Maximum

Experiments 1 and 2 Bujumbura ‘FHIA-17’ 62 76%a (47) 34.3a 8.0b 20 ‘Igisahira’ 62 58%b (36) 32.9a 7.8b 20 ‘Kamaramasenge’ 62 47%b (29) 36.7a 2.6d 4 ‘Mzuzu’ 62 48%b (30) 33.5a 11.0a 24 Gitega ‘FHIA-17’ 62 44%b (27) 61.4b 4.2c 7 ‘Igisahira’ 62 55%b (34) 60.2b 3.8cd 8 ‘Kamaramasenge’ 62 26%c (16) 67.6c 2.0d 4 ‘Mzuzu’ 62 44%b (27) 65.6bc 4.4c 12 LSD (cultivar, P = 0.05) 14** 5.9* 1.3*** LSD (cultivar × site 20NS 8.3NS 1.9** interaction, P = 0.05) CV% 53 22 47 Experiment 3 Bujumbura ‘FHIA-17’ 64 78%a (50) 32.8b 8.4b 25 ‘Igisahira’ 64 84%a (54) 29.1a 5.7c 22 ‘Kamaramasenge’ 64 84%a (54) 36.9c 2.4d 7 ‘Mzuzu’ 64 88%a (56) 29.5ab 10.3a 28 LSD (P = 0.05) 15NS 3.4 2.4*** CV% 25 15 50 ***

NSCultivar means do not differ significantly at P < 0.05; *Cultivar means differ significantly at P < 0.05; **Cultivar means differ significantly at P < 0.01; and ***Cultivar means differ significantly at P < 0.001. 62 P. Lepoint et al.

Table 7.3. Effect of initiation substrate on corm viability, latency period, mean and maximum number of shoots produced per viable corm spanning three consecutive macropropagation experiments carried out from January 2010 to January 2011 in Bujumbura (Experiments 1, 2 and 3) and Gitega (Experiments 1 and 2) provinces. ‘n’ = number of corms; means followed by the same letter within a column and experiment are not significantly different at P < 0.05.

No. shoots for Proportion a single corm (no.) viable Latency Site Substrate n corms (days) Mean Maximum

Experiments 1 and 2 Bujumbura Sawdust 104 65%a (68) 33.6ab 8.3a 24 Rice hull 72 49%b (35) 31.5a 8.3a 16 Coffee husk 72 54%ab (39) 37.9b 5.4b 14 Gitega Sawdust 104 50%b (52) 65.7d 3.8c 12 Rice hull 72 43%b (31) 57.9c 4.0cb 8 Coffee husk 72 29%c (21) 64.1d 3.5c 8 LSD (substrate, 13** 5.2* 1.4* P = 0.05) LSD (substrate × site 18NS 7.2NS 2.0NS interaction, P = 0.05) CV% 55 23 59 Experiment 3 Bujumbura Sawdust 128 90%a (115) 32.9a 6.4a 25 Rice hull 128 77%a (99) 31.2a 7.1a 28 LSD (P = 0.05) 11NS 2.4NS 1.7NS CV% 25 15 50

NSSubstrate means do not differ significantly at P < 0.05; *Substrate means differ significantly at P < 0.05; **Substrate means differ significantly at P <0.01.

Table 7.4. Effect of humid chamber type on corm viability, latency period, mean and maximum number of shoots produced per viable corm spanning three consecutive macropropagation experiments carried out from January 2010 to January 2011 in Bujumbura (Experiments 1, 2 and 3) and Gitega (Experiments 1 and 2) provinces. ‘n’ = number of corms; means followed by the same letter within a column and experiment are not significantly different at P < 0.05.

No. shoots for Proportion a single corm (no.) viable Latency Site Unit type n corms (days) Mean Maximum

Experiments 1 and 2 Bujumbura Standard 124 58%a (72) 33.7a 7.8a 20 Prototype 124 57%a (70) 34.8a 7.2a 24 Gitega Standard 124 46%b (57) 61.1b 4.0b 12 Prototype 124 38%b (47) 65.3b 3.6b 8 LSD (unit type, P = 0.05) 10.7NS 4.3NS 1.2NS LSD (unit type × site 15NS 6.0NS 1.7NS interaction, P = 0.05) CV% 56 23 61 Experiment 3 Bujumbura Standard 128 85%a (109) 31.3a 7.7b 28 Prototype 128 82%a (105) 32.9a 5.7a 22 LSD (P = 0.05) 10NS 2.4NS 1.7* CV% 25 15 50

NSUnit type means do not differ significantly at P<0.05; *Unit type means differ significantly at P < 0.05. Macropropagation of Musa spp. in Burundi 63

viability, latency or shoot production in equally emphasized the importance of high Experiments 1 and 2, although shoot pro- temperatures and relative humidity in cham- duction was significantly reduced with the bers for achieving the best multiplication use of the prototype unit (mean of 5.7 versus rates. Previous reports (e.g. Dantas et al., 1987) – 7.7 shoots produced per viable corm) under that not all cultivars respond equally to the the warm conditions of Bujumbura in technology – are confirmed, and in the case of Experiment 3. Overall, the results suggest this study, the multiplication rates of ‘Kamara- that the prototype humidity chamber can masenge’ were poor. perform as well as the standard chamber The shoot production data presented, with regard to corm viability, latency and irrespective of cultivar, are low in compari- possibly shoot production. son with previous studies. Dantas et al. (1987), Muñoz and Vargas (1996), Kwa (2003) and Tenkouano et al. (2006) reported means across cultivars tested ranging from 2.0 7.4 Discussion (‘Prata Ana’, AAB Pome subgroup) to 72.8 (‘Grande Naine’, AAA Cavendish subgroup), In the presently grave phytosanitary context 39.3 (‘Curraré’, AAB plantain), 11.5 (‘Grande of Burundi (the presence of quarantine dis- Naine’) to 23.2 (‘Kelong Mekintu’, AAB eases such as BBTD and Xanthomonas wilt, plantain), and 10.0 (‘Elat’, AAB plantain among others), it is vital that an alternative landrace) to 33.0 (‘PITA 21’, AAB plantain source of planting material – other than con- hybrid) shoots produced per corm, respec- ventional suckers – be made available to farm- tively. In addition, reduced corm viability ers at an affordable price. Macropropagation, due to corm rotting was observed in this reported as requiring minor technical skills study (Tables 7.2–7.4). Phaka and Bakelana and potentially producing a large amount of (1998) are among the few authors, to our planting material within a short timespan, knowledge, to equally report high corm rot- has been identified as a good candidate for ting within their experiments (up to 34%). producing such materials. The scaling up of Studies carried out at INEAC (Anon., 1955) this technology in Burundi is also a chance to suggested that the longer the parent corm is multiply new introductions and preferred kept in a good state, the more shoots can be superior local cultivars. It is also an opportu- potentially produced. It is, therefore, possi- nity to raise awareness of farmer-accessible ble that, among other unidentified parame- and cost-effective measures that can be used ters, the non-sterilized substrate could have to eliminate nematodes and weevils from led to increased rotting of corms and so to planting materials through paring and treat- reduced corm viability and shoot produc- ment (of corms) with boiling water. tion. Moreover, the red sawdust (Eucalyptus) In countries where (i) farmers own large used in experiments has been reported by plots, (ii) banana cultivation is commercially Ngo-Samnick (2011) as being potentially orientated, (iii) producers of TC bananas are toxic to plantlets, along with black and certified and (iv) linkages between TC pro- yellow sawdust, and should be avoided. ducers and farmers are established, in vitro It is concluded from this study that, at plantlets would be the ideal option. This is lower altitudes, a prototype macropropaga- not yet the case in Burundi. tion chamber made out of local, low-cost In this study, the data revealed that materials using rice hull as the initiation sub- macropropagation, carried out in light- strate could be a viable alternative to stand- deprived (prototype) chambers, does not sig- ard chambers made of costly, hard to obtain, nificantly alter the viability and latency period plastic sheeting. In addition, coffee husk – as of corms. However, cooler temperatures, such an initiation substrate – is not an option in as those in Gitega, have a significantly nega- Burundi due to a high termite infestation rate. tive impact on the viability of corms, the Limiting factors to the use/adoption of latency period for shoot production and num- macropropagation in Burundi could be the ber of shoots produced per corm. Kwa (2003) need for warmer climates to reach optimum 64 P. Lepoint et al.

productivity, thus restricting the use of Burundian farmers, in addition to being the technology to the Rusizi valley, and sustainable for the environment. the costs and skills that are required by the technology. However, experience has shown that the success of the technology (reduced corm mortality and increased corm produc- Acknowledgements tivity) increases with successive cycles. Nevertheless, the large amount of firewood This study was supported by the Directorate that is needed to carry out the different steps General for Development Belgium-funded (boiling water treatment of suckers, sterili- project ‘CIALCA’ (Consortium for Improving zation of initiation media) warrants research Agriculture-based Livelihoods in Central into a viable alternative if macropro pagation Africa) and carried out in collaboration with is to be adopted by resource-constrained the University of Burundi.

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Niyongere, C., Losenge, T., Ateka, E.M., Nkezabahizi, D., Blomme, G. and Lepoint, P. (2012) Occurrence and distribution of banana bunchy top disease in the Great Lakes region of Africa. Tree and Forestry Science and Biotechnology 6, 102–107. Ouma, E., van Asten, P., Umuhoza, N. Zagabe, R. and Muhiwa, K. (2011) Banana Seed Systems in Central Africa: Constraints and Cost–benefit Assessments. CIALCA Technical Report, Consortium for Improving Agriculture-based Livelihoods in Central Africa. Perez, L. (1992) Comparación de varios métodos de propagación en banana. CORBANA – Revista 16, 28–33. Phaka, V. and Bakelana B. (1998) Multiplication de rejets de bananiers par fragmentation de la souche. In: Akyeampong, E. (ed.) Musa Network for West and Central Africa, Report of the Second Steering Committee Meeting, Douala, Cameroon. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France, pp. 51–52. Sebasigari, K. and Stover, R.H. (1988) Banana Diseases and Pests in East Africa: Report of a Survey Made in November 1987. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France. Tenkouano, A., Hauser, S., Coyne, D. and Coulibaly, O. (2006) Clean planting materials and management practices for sustained production of banana and plantain in Africa. Chronica Horticulturae 46, 14–18. 8 Challenges and Opportunities for Macropropagation Technology for Musa spp. among Smallholder Farmers and Small- and Medium-scale Enterprises

E. Njukwe,1* E. Ouma,1 P.J.A. van Asten,2 P. Muchunguzi2 and D. Amah3 1IITA, Bujumbura, Burundi; 2International Institute of Tropical Agriculture (IITA), Kampala, Uganda; 3IITA, Ibadan, Nigeria

Abstract Lack or shortage of healthy and improved planting material is a major constraint to the expansion of banana and plantain production. The situation is made worse by the lack of formal systems for producing and distributing quality planting material, thereby forcing farmers to depend on natural regeneration of plants for their supply. This is usually a very slow process, and produces small amounts of planting material that are likely to be contaminated with soil-borne pathogens such as nematodes. To overcome this constraint, several techniques have been developed to rapidly multiply banana and plantain planting material, including micropropagation under aseptic conditions in the laboratory. While micropropagation techniques can provide large amounts of planting material, they are not adapted to the conditions of smallholder farmers. Therefore, user-friendly techniques that require little technical skill or equipment would prove more attractive to adoption by such farmers. The International Institute of Tropical Agriculture (IITA) has been looking at alternative means of producing planting material for wide-scale distribution of improved banana and plantain cultivars. The alternative methods are classified into two categories: field techniques based on complete or partial decapitation of suckers; and the macropropagation of suckers practised away from the field. Treatment of suckers to reduce the risks of transmitting soil-borne contaminants is strongly recommended and forms an integral component of the dissemination package for smallholder farmers. Macropropagation techniques, although genotype dependent, can produce 8–15 new plants/corm within 15 days, while secondary scarification of newly emerging buds has the potential to further increase the number of plantlets by a factor of 2–3, within the same time frame. Plantlets obtained through this method have the uniformity of micropropagated seedlings while being less prone to post-establishment factors in the field. This method is simple and cheap, although it requires some minimum investment to set up propagators and weaning facilities, so it is suitable for small- and medium-scale enterprises. However, its utilization is undermined by several factors, the most critical of which are lack of initial capital investment and technical skills.

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 66 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Musa Macropropagation Technology 67

8.1 Introduction To overcome these constraints, several techniques have been developed for rap- A major constraint to the expansion of idly multiplying banana and plantain plant- banana and plantain cultivation is the scar- ing materials, including micropropagation city of healthy planting material (Schill under aseptic conditions in the laboratory et al., 1997; Nkendah and Akyeampong, (Vuylsteke, 1998). While micropropagation 2003). Farmers usually depend on the natural can provide large numbers of healthy plant- regeneration of suckers for the supply of lets, it is usually expensive, although well- planting material because it is easily available off farmers can probably afford such and affordable compared with other sources of plantlets. In addition, tissue-cultured plants planting material (Table 8.1). Although suck- cannot withstand dry weather if estab- ers are easily obtained, field regeneration is a lished towards the end of the rainy season very slow process that often produces small and require extra care and management amounts of planting material that is usually for successful field establishment. Hence, contaminated by various soil-borne patho- macropropagation that is cost effective gens such as nematodes (Swennen, 1990; and affordable has been promoted by the Faturoti et al., 2002). Also, transplanting of the International Institute of Tropical Agri- contaminated material often spreads diseases culture (IITA) as an alternative method for and shortens the lifespan of plantations. producing and rapidly multiplying healthy

Table 8.1. Banana planting material type: advantages, disadvantages and challenges.

Planting material Advantages Disadvantages Challenges

Suckers from the field Easy to obtain Carriers of pests and Limited quantity to satisfy Cheap diseases need Ease of transport Bulky to transport Spread of pathogens if Easy to manage Low multiplication rate not treated Little field care required Risk of variety mix-up Lack of improved cultivars resistant to endemic pests and diseases Macropropagation Minimum skills to set up Risk of diseases Lack of improved cultivars germination chambers Requires clean substrate resistant to endemic and weaning facilities Initial investment pests and diseases Easily operated Quality control Acceptable multiplication Transport of pots rate Moderate care required in Uniform growth the field Good for an agricultural enterprise Tissue culture Healthy planting material Planting material costly Virus indexing High quantity Instability of electricity Lack of improved cultivars Uniform growth Require aseptic resistant to endemic conditions pests and diseases Requires skilled and competent personnel Sensitive to adverse factors Easily damaged during transport High level of field care required High cost of installation and functioning 68 E. Njukwe et al.

planting material; one that may prove 8.2 Macropropagation: more attractive for adoption by farmers. Opportunities and Challenges Macropropagation techniques, although genotype dependent, can produce 8–15 new Macropropagation techniques (Plate 7) plants/corm within 15 days, while second- involve methods that employ whole suckers ary scarification of newly emerging buds or relatively large pieces of corm tissue to has the potential to further increase the produce planting material in a propagator number of plantlets by a factor of 2–3 within (Tenkouano et al., 2006). the same time frame. Furthermore, plantlets Propagators are humidity chambers with obtained by macropropagation have the uni- sawdust beds that provide an appropriate formity of tissue-cultured plants while being environment for the sprouting of suckers. less prone to adverse post- establishment Alternative, easily available substrates such as factors in the field. To ensure easier access rice hulls, coffee husks, shredded cacao husks, for farmers and a regular source of healthy groundnut shells or oil palm fibres can be used, suckers, non-governmental organizations but sawdust provides the most suitable envi- (NGOs) in Burundi are adopting the concept ronment, as it is easy to use and can be recycled of tissue culture mother gardens for subse- by steaming for reuse (Njukwe et al., 2006). quent macropropagation and false decapita- For easy manipulation, propagators should be tion of suckers. The approach of tissue about 2 m long, 1.2 m wide and 1.5 m high. culture mother gardens managed by NGOs The sides should be covered with 30 cm high and agricultural extension agents has cement blocks or other material (such as wood increased the demand for tissue culture or zinc sheets) to contain the sawdust bed. plantlets and has bridged the gap between Temporary structures can be made from locally the farmer and the private suppliers of tissue available materials such as wood or bamboo, culture plantlets by disseminating healthy and roofed with mats or palm leaves (pruned banana planting material from properly to inhibit/limit fungal and insect attack) as managed plots and thereby preventing the appropriate for smallholder farmers. Such spread of pests and diseases. structures are permeable to rainwater but do, The banana ‘seed systems’ model that however, reduce the effects of heavy rainfall, uses small and medium-sized enterprises which could damage plants. Permanent struc- in macropropagation seems to be highly tures can be made from wooden posts in con- successful and more sustainable than that crete foundations and roofed with transparent of project-supported smallholder farmers plastic and zinc sheets to allow for 50% illumi- who may give up when a project ends nation. A shading structure could also be built owing to lack of financial resources. with metal pipes in concrete posts, with shade Healthy banana seed production is an netting as a cover to provide a 50% shade level, enterprise needing relatively low cash out- but this would be a more expensive option, lays, although investment is required for although it would be ideal for small- and the installation of humidity chambers, medium-scale enterprises. acquisition of substrates and nursery equipment and inputs such as fungicides and pesticides. In contrast, project targeting of smallholder farmers to implement 8.2.1 Challenges macropropagation faces major challenges, such as their lack of financial resources, Although macropropagation can be appro- technical know-how and ownership of the priate for small- and medium-scale enter- technology when a project ends. Hence, prises, its utilization is undermined by several field techniques (Plate 6) are more suited to factors, the most critical of which are lack of the needs and conditions of smallholder initial capital investment and technical skills. farmers seeking to obtain healthy suckers Other limiting factors include climatic condi- for new fields and to replenish old farms. tions (a higher sprouting level is observed Musa Macropropagation Technology 69

under lowland than under highland condi- cutting site; hence, clean knives should be used tions), sucker quality, proximity to the propa- for detachment. Plants should be detached at gator for regular monitoring, availability of the right stage, when they have developed materials and water, and susceptibility of roots and have 2–3 leaves. Younger plants wooden poles/planks to fungal and insect with 2–3 leaves are less prone to shock and sur- attack. Labour requirements are also often vive better in pots than more mature plants. overlooked. Problems encountered during Sometimes, plantlets are detached without macropropagation may include the type of their growing point/meristem because this is sucker to be used (preferably healthy sword quite close to the parent plant corm, or without suckers), substrate source and type (prefera- their own roots. This can be prevented by bly fresh and pasteurized sawdust), poor detaching the plantlets together with part of sprouting rate resulting from inadequate the mother plant corm tissue for subsequent technical skills and diseased corms, prema- rooting in rooting chambers with a sawdust ture rotting of corms, low plantlet survival bed; acclimatization then takes 2 weeks. rates after detachment from the parent corm, pest and disease attack and varietal mix-up. 8.2.5 Diseases and pests

8.2.2 Poor sprouting It is common to find fungi growing on sawdust in the propagators and this can be Poor sprouting is commonly observed when reduced by using fresh sawdust, or by pas- the apical meristem is not properly destroyed. teurizing the sawdust before use. Pests such Thus, one or two large shoots can be seen as insects, maybe as caterpillars, or mites can sprouting from the apical shoot portion of the invade propagators, especially in forest areas. corm and suppressing the growth of lateral If this is observed, pesticides can be used. shoots. In this case, the growing apical shoots Plants will rarely be diseased if they were should be cut back and the corm’s meristem obtained from clean parent plants and care- destroyed by drilling (for maiden suckers) or fully observed before the initiation of macro- cutting across/scarifying the meristem region propagation. However, if diseased plants are of the corm (for sword suckers). noticed they should be removed to prevent disease spread. Because temperature and humidity are normally higher in propagators 8.2.3 Premature rotting of corms than outside, the incidence of disease is greater. Diseases thrive in environments that allow the easy survival and transmission of Corms can start to rot even without produc- fungi and bacteria, so sanitation measures ing plantlets in the propagator. This may be should be implemented in propagators to caused either by too much watering or by prevent diseases and optimize production. existing intrinsic infection in the corm. To prevent the spread of disease, rotted corms should be removed from the propagator as soon as they are noticed. 8.2.6 Paring and hot/boiling water treatment

8.2.4 Low plantlet survival rates after It is very important that the starting material detachment from the parent corm for macropropagation is clean, and this can be achieved by the paring of suckers, followed The most crucial aspect of macropropagation by immersion in boiling water for 30 s. The is detaching and establishing plantlets, and a use of pesticides is also an option, but it is not low survival rate is the most common problem. always economically worthwhile or, indeed, A detached plantlet may be infected at the environmentally friendly. 70 E. Njukwe et al.

8.2.7 Substrate source and type Generally, the financial capability and technical skills of smallholder farmers in the Rice hulls are used as a substrate in areas production of planting material are low and where rice cultivation is important, but the they are unable to carry out the basic agro- incidence of fungi is greater when these are nomic practices required to produce healthy pasteurized owing to the development of planting material. Field techniques are, there- spores on the cooked rice grains that are com- fore, best suited to the needs and conditions monly found in the rice hulls. of smallholder farmers who only need relatively small quantities of planting material to replenish old fields. Problems encountered with field tech- 8.2.8 Variety mix-up niques include the limited number of suckers produced, more vigorous sucker When working with more than one cultivar, development in the rainy season than in the these should be clearly identified and sepa- dry season, the non-uniformity of suckers rated at all stages of propagation. Propagator in field establishment, their bulkiness, the space can be partitioned for the various culti- incidence of pests and diseases, and irregu- vars using ropes, and labelling can be done lar fruiting and harvests. So these tech- using permanent markers or lead pencils to niques are not suitable for enterprising, write on plastic or zinc sheets. seed production-oriented farmers.

8.3 Field Techniques: Opportunities 8.4 The Way Forward and Challenges To sustain the rapid production and distribu- Field techniques (Plate 6) can be classified tion of healthy banana planting material, a into two: false and complete decapitation. three-tier (primary, secondary and tertiary) Both involve stimulating lateral bud produc- multiplication scheme is promoted by IITA in tion by destroying the active growing point the Consortium for Improving Agriculture- (meristem) in the pseudostem, and both based Livelihoods in Central Africa (CIALCA) methods increase sprouting and sucker mul- project. For example, tissue culture plantlets tiplication in the field. The rate of suckering are distributed to development partners, ranges from 9–14 suckers/pseudostem a while macropropagated materials are deliv- year. In false decapitation, a small hole is ered by development partners to farmer created in the pseudostem of a 6–8 month associations. Healthy suckers (pared and old plant, at 15 cm above the soil, to destroy boiling water treated) (Coyne et al., 2010) can the meristem. The foliage remains photo- then reach the farmers. Regular technical sup- synthetically active for about 3 months. port on multiplication techniques is essen- In complete decapitation, the pseudostem of tial and the provision of nuclear stocks of a 6–8 month old plant is completely cut improved varieties to rejuvenate seed pro- down at 15 cm above the soil to destroy the duction nurseries, or replenish them with meristem. In both techniques, the sprouting new varieties every 3–4 years, is very impor- of suckers begins after 3 weeks. The suckers tant. Smallholders’ knowledge of and techni- are detached when they attain 3–4 leaves cal skills in the use of healthy planting material (at a height of 20–30 cm), pared, treated in should be reinforced through field inspections boiling water for 30 s and planted directly in as well as exchange visits with other farmers. the field. This treatment of the suckers is The concept of a three-tier multiplication strongly recommended to reduce the risks of scheme, starting with tissue-cultured plants transmitting soil-borne contaminants such for onward macropropagation, may lead to as nematodes, and forms an integral compo- an excellent trade-off in terms of costs, pest/ nent of the package. disease risks, plantlet numbers produced and Musa Macropropagation Technology 71

local ownership, which will eventually bridge water before further distribution. Nursery the gap between the farmer and the supply gardens should be rejuvenated with new chain providers of planting material. stocks of tissue-cultured plants or replenished with new cultivars after every 3–4 years. In Burundi, over ten NGOs have adopted the concept of nursery gardens for onward 8.5 Conclusion and Perspectives macropropagation and false decapitation, and have received financial support from the The purpose of banana seed systems is to governments of Belgium, the Netherlands, assist with the dissemination of superior the USA and Italy. This approach has bridged varieties and to improve the effectiveness of the gap between the farmer and the private propagation techniques so that farmers have suppliers of tissue-cultured planting mate- a better availability of high-quality planting rial, and a significant increase in the demand materials of superior varieties. The three-tier for tissue-cultured plants has been observed. (primary, secondary and tertiary) multipli- Because macropropagation requires initial cation scheme is promoted by IITA in the financial investment and technical capa- CIALCA project to ensure equitable, fast bility for the production of healthy banana and sustainable distribution of healthy planting material, it is more suitable for planting material. Tissue culture plantlets small- and medium-scale enterprises than should be the sole source for nuclear stocks for smallholder farmers. These farmers often to small- and medium-sized enterprises to suffer from inadequate planning skills, establish nursery gardens, from where corms poor management ability, lack of know-how can be obtained for macropropagation. and insufficient capital, making it very diffi- Macropropagated plantlets can subsequently cult for them to sustain the production of be distributed to smallholder farmers in sec- healthy planting material via macropropaga- ondary sites for field multiplication. Suckers tion. Field techniques that do not require obtained from field multiplication plots financial investment are, therefore, more suit- should be pared and treated with boiling able for them.

References

Coyne, D.L., Wasukira, A., Dusabe, J., Rotifa, I. and Dubois, T. (2010) Boiling water treatment: a simple, rapid and effective technique for producing healthy banana and plantain (Musa spp.) planting material. Crop Protection 29, 1478–1482. Faturoti, B., Tenkouano, A., Lemchi, J. and Nnaji, N. (2002) Rapid Multiplication of Plantain and Banana. Macropropagation Techniques. A Pictorial Guide. International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. Nkendah, R. and Akyeampong, E. (2003) Socioeconomic data on the plantain commodity chain in West and Central Africa. InfoMusa 12(1), 8–13. Njukwe, E. Tenkouano, A., Amah, D., Kassim, S., Muchunguzi, P., Nyine, M. and Dubois, T. (2006) Training Manual Macro-propagation of Banana and Plantain. International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. Schill, P., Afreh-Nuamah, K., Gold, C.S., Ulzen-Aprah, F., Paa Kwesi, E., Peprah, S.A. and Twumasi, J.K. (1997) Farmers’ perception of constraints in plantain production in Ghana. International Journal of Sustainable Development and World Ecology 7, 12–24. Swennen, R. (1990) Plantain Cultivation under West African Conditions: A Reference Manual. International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. Tenkouano, A., Hauser, S., Coyne, D. and Coulibaly, O. (2006) Clean planting materials and management practices for sustained production of banana and plantain in Africa. Chronica Horticulturae 46, 14–18. Vuylsteke, D. (1998) Shoot-tip Culture for The Propagation, Conservation and Distribution of Musa Germplasm. International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. 9 Impact of Arbuscular Mycorrhizal Fungi on Growth of Banana Genotypes in Three Different, Pasteurized and Non-pasteurized Soils of Rwanda

S.V. Gaidashova,1* A. Nsabimana,2 P.J.A. van Asten,3 B. Delvaux,4 A. Elsen5 and S. Declerck4 1Rwanda Agricultural Board (RAB), Kigali, Rwanda; 2Kigali Institute of Science and Technology (KIST), Rwanda; 3International Institute of Tropical Agriculture (IITA), Kampala, Uganda; 4Université Catholique de Louvain (UCL), Louvain-la-Neuve, Belgium; 5Soil Service of Belgium, Leuven, Belgium

Abstract Arbuscular mycorrhizal (AM) fungi are known to improve the growth of many crops of agricultural importance. The amplitude of this growth improvement may vary depending on soil type. Here, we report the effect of the application of indigenous AM fungi, isolated from a Nitisol from Kirehe (eastern Rwanda), on the growth and root characteristics of three banana (Musa spp.) genotypes: ‘FHIA-17’ (AAAA), ‘Musakala’ (AAA-EA) and ‘Sukali Ndiizi’ (AAB), grown in pasteurized and non-pasteurized Acrisol, Ferralsol or Nitisol. Root characteristics differed significantly between soil types (P < 0.001) and banana genotypes (P < 0.05). The poorest root development was observed on the Acrisol and the best on the Nitisol, irrespective of genotype. ‘Musakala’ had a smaller root system than ‘FHIA-17’ and ‘Sukali Ndiizi’. Inoculation resulted in highly significant (P < 0.001) differences in frequency of root colonization between soil types in all genotypes and treatments, with the highest frequency observed in the Nitisol and Ferralsol and the lowest in the Acrisol. Inoculation increased plant growth and dry weight (P < 0.05) but the effect was less marked in non- pasteurized treatments than in pasteurized treatments in all soils and genotypes. The exception was the Ferralsol, where pasteurization did not result in a significant increase in plant growth. The highest relative plant growth increase caused by AM fungi was observed in the Acrisol. This was observed for all genotypes and treatments and could possibly be linked to the greater limitations to root growth in this soil type. Poorer root development of ‘Musakala’ coincided with its highest response to the AM fungi inoculation compared with other genotypes, which suggested its higher AM fungal dependency.

9.1 Introduction cash crop and essential element in landscape and soil conservation in the East African high- The important role of East African highland lands (EAH) has been emphasized by different bananas (Musa spp., AAA-EA) as a staple crop, authors (Davies, 1995; Rishirumuhirwa, 1997;

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 72 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Impact of Arbuscular Mycorrhizal Fungi 73

Kangasniemi, 1998; Karamura et al., 1999). soil, I-NP); (iii) inoculated AM fungi There is high soil type diversity in the EAH alone (inoculated, pasteurized soil, I-P); region (Eswaran et al., 1989) and bananas are and (iv) absence of inoculum (non-inoculated, grown under a wide range of agro-ecological pasteurized soil, NI-P). conditions (Davies, 1995). However, declining yields throughout the region compromise production (Okech et al., 2004, 2005; Baijukya et al., 2005; Macharia et al., 2008). Among the major 9.2 Material and Methods constraints causing yield decline are low inher- ent soil fertility (Sanchez et al., 1997), inade- 9.2.1 Biological material quate soil management (Bekunda et al., 2002), nutrient mining (van Asten et al., 2004, 2006) Micropropagated banana plantlets (Musa and pests and diseases (Tushemereirwe and spp. ‘FHIA-17’ (AAAA), ‘Musakala’ (AAA-EA) Bagabe, 1999; Okech et al., 2002; Mwangi and and ‘Sukali Ndiizi’ (AAB)) were supplied Nakato, 2009). by the Agro-Genetic Technologies Laboratory To overcome some of these yield con- (Uganda). Plantlets measuring 5 ± 1 cm height straints, the application of beneficial soil with two fully developed leaves were re - microorganisms such as arbuscular mycor- ceived in nutrient agar (Murashige and rhizal (AM) fungi has received increasing Skoog, 1962). The genotype ‘FHIA-17’ is an attention (Jaizme-Vega and Azcón, 1995; improved tetraploid hybrid with a well- Declerck et al., 2002; Jefwa et al., 2008). The developed root system and was recently potential impact of AM fungi in helping to introduced to the EAH region, while ‘Sukali overcome plant nutrient constraints in EAH Ndiizi’ and ‘Musakala’ are traditional culti- cropping systems may be particularly high vars with medium and less developed root (Jefwa et al., 2008), as these systems generally systems and have been grown in EAH region do not receive chemical inputs (i.e. inorganic for more than 50 years. fertilizers and pesticides) and are, therefore, The inoculum consisted of a natural more AM fungi ‘friendly’ (Adriano-Anaya mixed population of AM fungi containing et al., 2006; Jansa et al., 2006). the genera Rhizophagus, Gigaspora and Scutello- The positive effect of AM fungi on banana spora (not identified at the species level) growth has been shown in several studies isolated from a banana farm at Kirehe (eastern conducted under controlled conditions Rwanda). Pot cultures were initiated from (Jaizme-Vega and Azcón, 1995; Yano-Melo banana root fragments and multiplied on leeks et al., 1999; Thaker and Jasrai, 2002). The mag- for 6 months. Fresh leek roots were used for nitude of the effect of the AM fungi on the inoculation, and these were colonized at a fre- growth of annual crops may vary with soil quency of 89% and intensity of 73%. type (Plenchette et al., 1989; Plenchette, 2000), The fresh soils used in the experiment but it is still unknown how the response of originated from Huye, southern Rwanda banana to AM fungal inoculation is modu- (Acrisol: 56% sand, 37% clay, 7% silt texture lated in different soil types. with gravel ratio above 10% soil weight and In the present study, we investigated low water-holding capacity), Rusizi, south- the effects of soil inoculation with AM fungi western Rwanda (Ferralsol: 80% clay, 12% on banana growth parameters in three soils sand and 8% silt, with thin capillaries of differing in physical and chemical properties <0.2 mm diameter accumulating water that is and three banana genotypes differing in root not accessible for plant roots) and Kirehe, system development. Soils were either pas- eastern Rwanda (Nitisol: 71% clay, 11% sand, teurized or non-pasteurized, and the effects 18% silt, with good water-holding capacity). of the following soil treatments were evaluated: These soils were characterized earlier for fer- (i) natural microflora (non-inoculated, non- tility, infestation by the nematode Pratylenchus pasteurized soil, NI-NP) alone; (ii) natural goodeyi, and AM fungi populations both in microflora in combination with introduced AM the soil and capable of colonizing banana fungal inoculum (inoculated, non-pasteurized roots (Gaidashova et al., 2009, 2010). 74 S.V. Gaidashova et al.

9.2.2 Inoculation process, plant care recently and fully opened leaf), biomass and experimental design (fresh and dry shoot weight and fresh root weight) and root characteristics (number and The micropropagated plantlets were removed length of primary roots). Shoot water was calcu- from their flasks and washed free of rooting lated as the difference between fresh and dry medium. They were transplanted into free- shoot weight, divided by dry shoot weight, draining pots (15 cm diameter, 15 cm height) and expressed in g water/g dry weight. A leaf filled with 800 g of dry soil. Plants were was considered functional if it had at least ino culated after the removal of their rooting 50% of green photosynthetic surface. Before medium as they were planted in the soil transplanting, soil samples were collected substrate. The inoculated plants received 1 g from pasteurized and non-pasteurized soils fresh leek root pieces and 30 g non-pasteurized for nutrient analysis to determine the physico- spore-containing sand from a leek trap chemical changes caused by soil pasteuriza- culture substrate (number not estimated) tion. Three soil samples of 200 g were collected mixed into the soil substrate in proximity per treatment and soil type. After air drying to the roots. The non-inoculated plants for 3 days, soil samples were oven dried at received 1 g of boiled leek roots and 30 g of 40°C for 24 h, ground and sieved on a 2 mm pasteurized sand. mesh. Soil pH was measured in 1:2.5 ratio of The experiment included four treatments sediment:water suspension, as described in with the three soils (Acrisol, Ferralsol and Okalebo et al. (2003). Total N was measured Nitisol), which were either pasteurized (P) or using a spectrophotometer in a sulfuric acid not (NP). The plants were either inoculated (I) and selenium acid extract as described in or not (NI) with the AM fungi. Ten replicates Okalebo et al. (2003). Available P was extracted were used per treatment and the plants were using Mehlich-3 solution (Mehlich, 1984) arranged in a complete randomized design. before colorimetric deter mination. Exchan ge- Pasteurization involved the use of oven heat- able cations (Ca, Mg, K and Zn) were extrac- ing at 100°C for 2 h. ted using 1 M ammonium acetate and then The experiment was conducted at the determined using an atomic absorption Institut des Sciences Agronomiques du spectrophotometer. Rwanda (ISAR), Rubona research station, Root samples were used to assess coloni- southern Rwanda. Pots were kept under zation by AM fungi. Fine root fragments greenhouse conditions (22/18°C mean day/ were placed in 10% KOH solution for 1 h at night temperatures and 12 h daylight). 80°C. Roots were subsequently bleached for During the first 4 weeks, the plants were 30 min in 3% H2O2 solution freshly alkalin- covered with transparent plastic cups to ized by NH4OH (8 ml of 25% NH4OH for ensure high air humidity for plant acclima- 100 ml 3% H2O2), as described by Koske and tization, and they were sprayed with steri- Gemma (1989). After bleaching, roots were lized water. From the fifth week, the cups stained in acidified ink solution (20 ml of were removed and the plants were watered permanent ink ‘Parker’ in 1 l of 1% HCl) (at least 50 ml/plant) regularly every 1–3 days, overnight (Vierheilig et al., 1998). Stained depending on soil desiccation. Overall, the root samples were destained in water for 1 h Acrisol treatments were watered every day, and observed under a compound micro- while the Nitisol and Ferralsol treatments scope (Leica DME) at 200× magnification. were watered every 2 or 3 days. The frequency and intensity of root colonization were evaluated using 50 root fragments (1 cm long) for each sample following the 9.2.3 Data assessment procedures method of Plenchette and Morel (1996). Frequency was estimated as the percent- Plants were harvested 20 weeks from the age of root fragments containing AM fun- planting date. At harvest, data were recorded gal structures (i.e. arbuscules, vesicles or on plant growth (plant height, number of hyphae). Intensity, which is the abundance of functional leaves, length of the 3rd most these respective structures (hyphae, vesicles Impact of Arbuscular Mycorrhizal Fungi 75

and arbuscules, separately or all together) in 9.3.2 AM fungal population density roots, was assessed by estimation of the pro- in the three selected soils portion of the root surface containing the respective AM fungal structures related Infectious propagule density of the AM fungi to the total surface of the root fragment in the three soils was estimated on leek and (Plenchette and Morel, 1996). determined using the most probable number method (Declerck et al., 1999; Gaidashova et al., 2010). The Ferralsol from Gashonga contained significantly (P < 0.05) higher soil den- 9.2.4 Statistical data analysis sities of AM fungal propagules than the Acrisol and Nitisol (Table 9.2). The variables that had been recorded were transformed to achieve normality: (i) arcsin transformation for percentages; and (ii) power 9.3.3 Root development transformations for plant growth variables. Analysis of variance under the General Linear Root characteristics differed significantly Model and Scheffe’s multiple comparison between soil types (P < 0.001) and banana tests were used to test the significance of the genotype (P < 0.05). Whatever the genotype, differences observed between means and to the poorest root development was observed separate homogenous groups. SAS 9.1 on the Acrisol and the greatest on the Nitisol Enterprise Guide 4 statistical software was (Table 9.3). The number of primary roots for used for these analytical steps. ‘Musakala’ was significantly lower than those for ‘FHIA-17’ and ‘Sukali Ndiizi’ on the Ferralsol (P < 0.05) and Nitisol (P < 0.001). Similarly, the fresh root weight of ‘Musakala’ 9.3 Results was significantly lower (P < 0.05) than those for ‘FHIA-17’ and ‘Sukali Ndiizi’ on these 9.3.1 Soil fertility in pasteurized two soils (Table 9.3). and non-pasteurized soils

Soil pasteurization did not affect soil nutri- 9.3.4 Root colonization by the AM ent content significantly, except for organic fungi in different soils and genotypes matter in the Nitisol, which was significantly (P < 0.05) reduced in the pasteurized soil Highly significant (P < 0.001) differences (Table 9.1). were observed in root colonization between

Table 9.1. Physico-chemical characteristics of the pasteurized (P) and non-pasteurized (NP) soils.

Organic matter N Ca Mg K P Effect of soil

Soil treatment pH % cmolc / kg mg/kg

Acrisol P 6.53 4.65 0.24 3.23 1.45 0.37 48.4 NP 6.50 4.45 0.23 2.91 1.36 0.33 30.0 Significance NSa NS NS NS NS NS NS Ferralsol P 5.73 3.36 0.19 1.76 1.14 0.66 12.9 NP 5.70 3.32 0.19 1.74 1.12 0.63 12.7 Significance NS NS NS NS NS NS NS Nitisol P 6.57 6.32 0.32 6.71 2.36 0.58 12.9 NP 6.53 6.73 0.31 6.61 2.28 0.52 12.8 Significance NS P < 0.05 NS NS NS NS NS aNS, not significant at P = 0.05. 76 S.V. Gaidashova et al.

Table 9.2. Arbuscular mycorrhizal fungi population density in three selected soils of Rwanda. Means followed by the same letter are not significantly different at P = 0.05. Propagule data from Gaidashova et al. (2010); estimated on leek by most probable number method (Declerck et al., 1999).

Soil type (ecoregion) No. infective propagules/100 g soil 95% confidence intervals

Acrisol (Huye) 2b 1–5 Ferralsol (Rusizi) 60a 27–133 Nitisol (Kirehe) 9b 4–19

Table 9.3. Root characteristics of three banana genotypes (‘FHIA-17’, ‘Sukali Ndiizi’, ‘Musakala’) in different soils (pasteurization and inoculation treatments combined) at 20 weeks after planting. For each root parameter, means followed by the same letters within a column (a, b) are not significantly different and means followed by the same letters (x, y) within a row are not significantly different at P = 0.05.

Genotypes

Root parameter Soil type ‘FHIA-17’ ‘Sukali Ndiizi’ ‘Musakala’

No. primary roots Acrisol 9.9bx 10.4bx 9.7bx Ferralsol 12.1axy 13.4ax 11.4ay Nitisol 12.1ax 13.3abx 10.6ay Length primary roots (cm) Acrisol 76bx 62bx 60bx Ferralsol 179ax 191ax 177ax Nitisol 182ax 174ax 193ax Fresh root weight (g) Acrisol 5.0bx 2.6by 3.1bxy Ferralsol 18.0ax 16.2ax 12.5ay Nitisol 16.7ax 17.5ax 13.5ay the soils in the I-P, I-NP and NI-NP treat- than in the pasteurized (I-P) treatments, ments. Irrespective of the genotype, the fre- irrespective of genotype (Table 9.4). quency and intensity of root colonization in On the Nitisol, ‘FHIA-17’ plants had sig- these treatments were highest (almost 70% nificantly (P < 0.001) higher root colonization and above for each genotype) in plants grown frequency in both the inoculated treatments on the Nitisol (see Table 9.4 for frequency (I-P and I-NP) than in the non-inoculated (NI) data; intensity data are not shown). Similarly, treatments. ‘Musakala’ and ‘Sukali Ndiizi’ plants grown on the Acrisol exhibited signifi- were strongly and similarly colonized in both cantly (P < 0.001) lower frequency and inten- inoculated treatments as well as in the non- sity of root colonization in the I-P, I-NP and inoculated and non-pasteurized (NI-NP) NI-NP treatments than the plants grown on treatments (Table 9.4). the Nitisol (Table 9.4). Soils had a strong effect on root coloniza- On the Acrisol, plants of the ‘FHIA-17’ tion at each treatment level (Table 9.4). In both and ‘Sukali Ndiizi’ genotypes in the inocu- inoculated treatments (I-P and I-NP), root lated treatments (I-P and I-NP) were signifi- colonization was the highest in the Nitisol for cantly (P < 0.001) better colonized by the all three genotypes. In the NI-NP treatments, AM fungi (higher frequency of colonization) root colonization was significantly higher than those in NI-NP treatments, while the in the Nitisol and Ferralsol for ‘FHIA-17’ and ‘Musakala’ plants only had a significantly ‘Musakala’, while for ‘Sukali Ndiizi’ it was (P < 0.001) higher frequency of colonization significantly higher in the Nitisol than in the in the I-NP treatment (Table 9.4). Plants Ferralsol. For all genotypes in the NI-NP grown on the Ferralsol had a significantly treatment, root colonization was significantly higher frequency of root colonization in the lower in the Acrisol than in the Ferralsol and non-pasteurized (I-NP and NI-NP) treatments Nitisol (Table 9.4). Impact of Arbuscular Mycorrhizal Fungi 77

Table 9.4. Frequency (%) of colonization of the roots of three banana genotypes grown in different soils 20 weeks after inoculation with a mix of Rhizophagus, Gigaspora and Scutellospora spp of arbuscular mycorrhizal (AM) fungi. Treatments are: P, pasteurized; NP, not pasteurized; I,, inoculated, NI, not inoculated. Within a genotype, means followed by the same letter (a–c) in columns are not significantly different and means followed by the same letter (x–z) in rows are not significantly different at P = 0.05.

Soil type

Genotype (genome) Treatment Acrisol Ferralsol Nitisol Significance

‘FHIA-17’ (AAAA) I-P 31.2ay 16.6by 92.2ax P < 0.001 I-NP 33.3az 65.0ay 84.0ax P < 0.001 NI-NP 3.6by 80.0ax 69.2bx P < 0.001 NI-P 0.0c 0.0c 0.0c NEa Significance level P < 0.001 P < 0.001 P < 0.001 ‘Musakala’ (AAA-EA) I-P 5.0by 4.8by 79.2ax P < 0.001 I-NP 23.9ay 62.4ax 70.2ax P < 0.01 NI-NP 3.3by 73.8ax 82.8ax P < 0.0001 NI-P 0.0c 0.0c 0.0b NE Significance level P < 0.05 P < 0.01 P < 0.001 ‘Sukai Ndiizi’ (AAB) I-P 30.2ay 19.6by 96.5ax P < 0.0001 I-NP 11.7az 76.6ay 97.2ax P < 0.0001 NI-NP 0.0bz 61.3ay 90.5ax P < 0.0001 NI-P 0.0b 0.0c 0.0b NE Significance level P < 0.001 P < 0.01 P < 0.001 aNE, NI-P treatment estimated for columns but not for rows.

9.3.5 Effect of inoculation, soil dry weight (Table 9.5), primary root number, pasteurization, soil and banana genotype fresh root weight and specific root length on banana growth and biomass (Table 9.6). Plant growth on the Ferralsol was almost as good as on the Nitisol, with almost Both soil pasteurization and inoculation no significant differences between the two with AM fungi significantly improved soils except for the number of functional plant growth. Pasteurization increased plant leaves and third leaf length, which were sig- height, length of the third most recently nificantly better on Nitisol (Table 9.5). emerged leaf, fresh and dry shoot weight The ‘FHIA-17’ and ‘Sukali Ndiizi’ geno- (Table 9.5) and number and fresh weight types had thicker primary roots (i.e. the of primary roots (Table 9.6), although it least specific root length among the three decreased shoot water content and specific genotypes) than ‘Musakala’, and ‘FHIA-17’ root length (Tables 9.5 and 9.6). Inoculation had significantly greater root fresh weight increased the height, number of functional than ‘Musakala’ (Table 9.6) and also had less leaves, length of the third most recently fresh shoot weight (Table 9.5). ‘Sukali emerged leaf, fresh and dry shoot weight Ndiizi’ was the tallest genotype among the (Table 9.5), number of primary roots and three with the highest shoot dry weight, sig- specific root length (Table 9.6). Past eurization nificantly higher shoot weight than resulted generally in a greater magnitude of ‘Musakala’ (both dry and fresh), and signifi- increases in growth para meters compared cantly lower shoot water. with inoculation with AM fungi. Soil type and genotype strongly affected plant growth. Significantly poorer plant 9.4 Discussion growth was on the Acrisol, which gave the least height, number of functional leaves, Root colonization in the study seems to have third leaf length, shoot water, shoot fresh and been affected by (i) soil type, (ii) inoculation 78 S.V. Gaidashova et al.

Table 9.5. Shoot growth characteristics in different treatments (pasteurization, inoculation, soil type and genotypes). For each parameter, means followed by the same letter within a column (a–c) are not significantly different.

Shoots

No. Leaf Fresh Dry Shoot water Treatment/soil Height functional length weight weight (g water/g Factor type/genotype (cm) leaves (cm) (g) (g) dry weight)

Pasteurization Pasteurized 15.9a 3.8a 21.8a 32.4a 3.0a 10.1b Not pasteurized 9.8b 3.9a 15.2b 13.2b 1.1b 11.1a Significance P < 0.001 NSa P < 0.001 P < 0.001 P < 0.001 P < 0.05 level Inoculation Inoculated 13.5a 4.2a 19.3a 24.7a 2.3a 10.5a Not inoculated 12.1b 3.4b 17.6b 20.6b 1.8b 10.6a Significance P < 0.05 P < 0.001 P < 0.01 P < 0.05 P < 0.05 NS level Soil type Acrisol 9.8b 1.5c 14.8c 9.5b 1.6b 5.9b Ferralsol 14.2a 4.2b 19.4b 28.3a 2.4a 11.8a Nitisol 14.3a 5.8a 21.3a 30.2a 2.3a 13.0a Significance P < 0.05 P < 0.05 P < 0.05 P < 0.05 P < 0.05 P < 0.05 level Genotype ‘FHIA-17’ 11.0ab 4.0a 17.7a 23.8ab 1.9b 11.4a ‘Musakala’ 12.0b 3.7a 18.5a 18.6b 1.6b 12.0a ‘Sukali 15.6 a 3.7a 19.3a 26.2a 2.7a 8.4b Ndiizi’ Significance P < 0.001 NS NS P < 0.01 P < 0.01 P < 0.001 level aNS, not significant at P = 0.05.

Table 9.6. Root characteristics in different treatments (pasteurization, inoculation, soil type and genotypes). NS = not significant at P = 0.05. For each parameter, means followed by the same letter within a column (a–c) are not significantly different.

Roots

Treatment/soil No. primary Fresh Specific root length Factor type/genotype roots weight (g) (cm/g fresh root weight)

Pasteurization Pasteurized 12.6a 16.0a 10.6b Not pasteurized 9.2b 6.9b 16.5a Significance level P < 0.05 P < 0.05 P < 0.05 Inoculation Inoculated 11.9a 11.6a 12.5b Not inoculated 9.8b 11.2a 11.3a Significance level P < 0.05 NSa P < 0.05 Soil type Acrisol 8.4b 2.6b 27.5a Ferralsol 12.3a 15.8a 16.1b Nitisol 11.9a 15.8a 11.8c Significance level P < 0.05 P < 0.05 P < 0.05 Genotype ‘FHIA-17’ 14.1a 13.1a 11.8b ‘Musakala’ 13.1a 9.0b 14.6a ‘Sukali Ndiizi’ 14.0a 12.4ab 11.4b Significance level NS P < 0.05 P < 0.05 aNS, not significant at P = 0.05. Impact of Arbuscular Mycorrhizal Fungi 79

with AM fungi, and (iii) soil pasteurization. size of the native population of AM fungi pre- There were very low root colonization levels sent in non-pasteurized soil was small and its for all three genotypes in the non-inoculated effect was minimal. This was very different in non-pasteurized treatment on the Acrisol, the Ferralsol, where the frequency of root compared with the Ferralsol and Nitisol. For colonization was very low in pasteurized and some reason, the natural population of AM very high in non-pasteurized treatments. This fungi in the Acrisol could not colonize banana suggests that the native AM fungal popula- roots to any significant level, as in the other tion was important and that its effect sur- two soils. This may be related to soil physical passed the effect of the introduced inoculum. and biological properties. For example, the A high infective propagule density in the soil, coarser texture of Acrisols limits water-hold- as observed in the Ferralsol (Gaidashova ing capacity, and while roots may grow under et al., 2010), increased the percentage of root suboptimal soil water due to water deficit colonization (Smith and Smith, 1981; Smith and excessive water drainage, the Acrisol also and Read, 2008). Conversely, a low infective had low cation exchange capacity and nutri- propagule density, as observed in the Acrisol ent supply (e.g. K). Although limited research (Gaidashova et al., 2010), combined with low has been conducted to investigate the effect water retention and less favourable condi- of environmental factors on AM colonization tions for root growth, led to poor root coloni- of roots (Smith and Read, 2008), a few studies of zation. On the Nitisol, lack of significant infective AM fungal population densities in differences in colonization frequency between agricultural soil under intensive banana pro- inoculated pasteurized and non-pasteurized duction have indicated lower AM fungal treatments may signify the highest ‘compati- populations in sandy soils under experimen- bility’ between the introduced and native tal conditions, and higher AM fungal popula- inoculum. Interestingly, the introduced inoc- tions in clay soils (Declerck et al., 1999; ulum was isolated from the soil sample origi- Plenchette, 2000). In this experiment, plants nating from a banana grown on a Nitisol grown in the more clayey Ferralsol and (Rwanda, Kibungo), a location close to where Nitisol had higher root colonization than in the Nitisol soil substrate was collected for this the sandier Acrisol. The fact that these clayey experiment. This further suggests that the soils were also low in P may have favoured inoculum used is particularly adapted to this the establishment of the AM fungi (Smith soil environment. and Read, 2008). Various shoot and root growth character- The biological properties of the soils that istics showed a positive response to AM fun- might have affected root colonization could gal inoculation, which is in line with reports be the size and the activity of natural AM in the existing literature (e.g. Declerck et al., fungal populations. Assessment of the infec- 1995; Jaizme-Vega and Azcón, 1995; Yano- tive propagule density in Acrisol showed Melo et al., 1999; Thaker and Jasrai, 2002). that it was very low (Gaidashova et al., 2010), This increase was proportionally the largest and inoculation with AM fungi significantly on poor soil (Acrisol), where even modest increased root colonization of ‘FHIA-17’ and colonization levels were associated with the ‘Sukali Ndiizi’ in the Acrisol, and also highest relative plant growth response. increased the root colonization of ‘FHIA-17’ Genotype also seems to affect the magni- on the Nitisol, while it had no effect on roots tude of the plant response to the AM fungi, in the Ferralsol. both in terms of plant growth and AM fungal The variations in trends of root coloniza- colonization of roots. Declerck et al. (1995) tion observed between pasteurized and non- have already demonstrated that relative myc- pasteurized treatments suggested that the orrhizal dependency is cultivar dependent in native AM fungi present in non-pasteurized bananas and is related to cultivar-specific soil could have influenced root colonization. characteristics such as root hair development. In the Acrisol, the increase of root coloniza- Increased root branching may also increase tion after inoculation with AM fungi, irre- the chances of encounters between roots and spective of pasteurization, suggests that the infective hyphae (Koske and Gemma, 1992). 80 S.V. Gaidashova et al.

In this study, the response of ‘FHIA-17’ and positive impacts on plant growth on the ‘Sukali Ndiizi’ – both of which have larger Ferralsol. These results are most probably root systems – to inoculation with AM fungi linked to the greater physical limitations to was lower than for ‘Musakala’, which has a root growth and the nutritional limitations to less developed root system. plant growth in the Acrisol. Antagonistic rela- The introduced inoculum probably com- tionships and competition for root resources peted with the AM fungal populations pre- between soil microorganisms, including the sent in non-pasteurized soil, or both the plant introduced (inoculated) and native AM fungi, and inocula were affected by soil conditions – seem to have limited plant responses to inoc- especially in the Acrisol, and differently in the ulation in non-pasteurized treatments. This Ferralsol. However, the observed coloniza- effect was minimized when the inoculum tion levels are not directly associated with came from a site close to where the soil sub- better plant growth. For example, in the strate originated. The practical implications Ferralsol, higher root colonization in non- of this study may be: (i) use of the higher pasteurized treatments did not result in potential of AM fungal application in geno- height, root and biomass increases (Tables 9.5 types that have a relatively poor root system; and 9.6). Antagonistic relationships and com- and (ii) the use of indigenous inoculum, espe- petition for root resources between soil micro- cially in sites where high AM fungal popula- organisms, including the introduced and tions are present. native AM inoculum (Declerck et al., 2002), may have contributed to the lack of plant growth response in non-pasteurized treat- Acknowledgements ments. This effect was more pronounced on the Ferralsol than on the Nitisol – from which The authors thank Belgian Technical the introduced inoculum originated. Cooperation for providing a research grant for this study through the Project ‘Sustain- able and Profitable Banana Production for 9.5 Conclusion the African Great Lakes Region’, involving Université Catholique de Louvain (UCL), The positive effect of inoculation by the AM the International Institute of Tropical fungi on plant growth was relatively larger Agriculture (IITA) and Institut des Sciences on a poor, more sandy Acrisol, than on the Agronomiques du Rwanda (ISAR). other soils used in the study (Ferralsol and Mr Claude Habimana is thanked for assis- Nitisol), and inoculation did not produce tance in data collection.

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Okech, S.H.O., Gaidashova, S.V., Gold, C.S., Nyagahungu, I. and Musumbu, J.T. (2005) The influence of socio-economic and marketing factors on banana production in Rwanda: results from a participatory rural appraisal. International Journal of Sustainable Development and World Ecology 12, 149–160. Plenchette, C. (2000) Receptiveness of some tropical soils from banana fields in Martinique to the arbuscular fungi Glomus intraradices. Applied Soil Ecology 15, 253–260. Plenchette, C. and Morel, C. (1996) External phosphorus requirements of mycorrhizal and non-mycorrhizal barley and soybean plants. Biology and Fertility of Soils 21, 303–308. Plenchette, C., Perrin, R. and Duvert, P. (1989) The concept of soil infectivity and a method for its determination as applied to endomycorrhizas. Canadian Journal of Botany 67, 112–115. Rishirumuhirwa, T. (1997) Rôle du bananier dans le fonctionnement des exploitations agricoles sur les hauts plateaux de l’Afrique orientale (application au cas de la région du Kirimiro – Burundi). Thèse N 1636 (PhD thesis), EPFL (École Polytechnique Fédérale de Lausanne), Lausanne, Switzerland. Sanchez, P.A., Shepherd, K.D. and Soule, M.J. (1997) Soil fertility replenishment in Africa: an investment in natural resource capital. In: Buresh, R.J., Sanchez, P.A. and Calhoon, F. (eds) Replenishing Soil Fertility in Africa. SSSA Special Publication No. 51, Soil Science Society of America Madison, Wisconsin, pp. 219–236. Smith, S.A. and Read, D. (2008) Mycorrhizal symbiosis, 3rd edn. Elsevier Academic Press, London. Smith, S.A. and Smith, S.E. (1981) Mycorrhizal infection and growth of Trifolium subterraneum: comparison of natural and artificial inocula. New Phytologist 88, 311–325. Thaker, M.N. and Jasrai, Y.T (2002) Increased growth of micro-propagated banana (Musa paradisiaca) with VAM symbiont. Plant Tissue Culture 12, 147–154. Tushemereirwe, W.K. and Bagabe, M. (1999) Review of disease distribution and pest status in Africa. In: Frison, E.A., Gold, C.S., Karamura, E.B. and Sikora, R.A. (eds) Proceedings of a Workshop, Mobilizing IPM for Sustainable Banana Production in Africa, Nelspruit, South Africa, 23–28 November 1998. INIBAP (International Network for the Improvement of Banana and Plantain), Montpellier, France, pp. 139–147. van Asten, P.J.A., Gold, C.S., Okech, S.H., Gaidashova, S.V., Tushemereirwe, W.K. and De Waele, D. (2004) Actual and potential soil quality constraints in East African Highland banana systems and their relation with other yield loss factors. InfoMusa 13(2), 20–25. van Asten, P.J.A., Gold, C.S., Wendt, J., De Waele, D., Okech, S.H.O., Ssali, H. and Tushemereirwe, W. (2006) The contribution of soil quality to yield and its relationship with other factors in Uganda. In: Blomme, G., Gold, C. and Karamura, E. (eds) Proceedings of the Workshop Farmer-participatory Testing of Integrated Pest Management Options for Sustainable Banana Production in Eastern Africa, Seeta, Uganda, 8–9 December 2003. Bioversity International, Montpellier, France, pp. 100–115. Vierheilig, H., Kughlan, A.P., Wyss, U. and Piché, Y. (1998) Ink and vinegar, a simple staining technique for arbuscular-mycorrhizal fungi. Applied and Environmental Microbiology 64, 5004–5007. Yano-Melo, A.M., Saggin Júnior, O.J., Lima-Filho, J.M., Melo, N.F. and Maia, L.C. (1999) Effect of arbuscular mycorrhizal fungi on the acclimatization of micropropagated banana plantlets. Mycorrhiza 9, 119–123. 10 Indigenous Arbuscular Mycorrhizal Fungi and Growth of Tissue-cultured Banana Plantlets under Nursery and Field Conditions in Rwanda

J.M. Jefwa,1* E. Rurangwa,2 S.V. Gaidashova,2 A.M. Kavoo,3 M. Mwashasha,3 J. Robinson,3 G. Blomme4 and B. Vanlauwe5 1Mycorrhizal Specialist, Nairobi, Kenya; 2Rwanda Agricultural Board (RAB), Kigali, Rwanda; 3Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, Kenya; 4Bioversity International, Kampala, Uganda; 5International Institute of Tropical Agriculture (IITA), Nairobi, Kenya

Abstract Arbuscular mycorrhizal fungi (AMF) have been widely evaluated for their suitability in the acclimatization and nursery management of tissue-cultured (TC) plantlets of banana and plantain. Improved growth and vigour of plantlets has been documented with exotic AMF species. A wide range of AMF species are associated with banana and plantain (Musa spp.) systems. In this study, the use of indigenous AMF from banana and plantain systems was evaluated for nursery management of TC plantlets. A single species inoculum with Glomus mosseae was compared with two mixed inoculants, all derived from banana and plantain systems; these were evaluated on the cultivars ‘Mpologoma’ (AAA-EA) and ‘Kamaramasenge’ (AAB) established in two soil types, one with a low P concentration (16–22 mg/kg) and another with high P (50–80 mg/kg). Inoculation with AMF enhanced height and leaf surface area growth of TC plantlets in both soils and both cultivars. The inoculation was more effective on ‘Mpologoma’ than on ‘Kamaramasenge’, and mixed inoculants were more effective than the single-species inoculum, particularly under field conditions, where up to 30% increase in height, girth and leaf surface area was recorded in ‘Mpologoma’. The mixed AMF inoculant comprising species from the soil with low P availability (AMF Kibungo) was most effective in soils with a P concentration of 50–80 mg/kg. High yield was evident in inoculated plants, with a slightly over 30% yield increase for ‘Mpologoma’ and ‘Kamaramasenge’ at both the Rubona and Kibungo sites.

10.1 Introduction mycorrhizal fungi (AMF). Mycorrhization increased the growth and nutrition of banana There are numerous reports on the benefits cultivars to the magnitude of the application derived by tissue-cultured (TC) bananas of standard fertilizer regimes in commercial (Musa spp.) from inoculation with arbuscular nurseries (Sosa Hernández, 1997). Significant

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 83 84 J.M. Jefwa et al.

growth response of micropropagated banana conditions and monitored for growth and was obtained when plants were inoculated yield. Mycorrhization was done at the hard- at the inception of the hardening phase ening and potting phase. Before the experi- (Declerck et al., 1994), with the response ment started, a mycorrhizal soil infectivity depending on the banana varieties and the (MSI) test was conducted on the indigenous AMF used (Declerck et al., 1995). Exotic AMF inoculants that were to be used with soils species are more widely used to colonize TC from the sites where the field experiment was banana plants than are indigenous isolates, to be established to determine the strength of and TC bananas have proved to benefit from the inoculants and the need for inoculation. colonization by exotic commercial AMF (mainly Glomus spp.) (Yano-Melo et al., 1999; Mwashasha, 2006; Jefwa et al., 2010). These 10.2 Materials and Methods results show that there are advantages in using AMF when the inoculum is applied The work involved three indigenous inoculants during the root production and acclimatiza- prepared from AMF associated with banana tion stages of micropropagated banana systems and two of the most preferred banana plants. AMF species are sensitive to soil con- cultivars – ‘Mpologoma’ (AAA-EA) and ditions, showing preference among soil types ‘Kamaramasenge’ (AAB) – evaluated under (Sieverding, 1991), and unless a species is nursery to field conditions (Rurangwa, 2009). adapted to a wide range of conditions, the The source of the two TC banana cultivars was positive effects of inoculation may not be AGRO Genetic Technologies Ltd (AGT) reflected in the field. Indigenous AMF species Laboratories, Kampala, Uganda. are more adapted to existing soil conditions, Before evaluation of the inoculants on although they have not been screened for TC plants in the nursery, and subsequently in their effectiveness on the growth of TC the field, the natural mycorrhizal soil infectiv- bananas during the hardening phase. ity (MSI) was determined for soil samples There is rarely any rationale for the selec- from the two banana-growing sites in tion of particular AMF endophytes for use in Rwanda where field tests of inoculated plants the growth promotion of plants (Bagyaraj, were to be conducted – Rubona (in Butare) 1992). In early research, most species were and Kibungo. The MSI test was to establish selected for inoculation of the desired host whether the original soils needed to be sup- plants due to their easy availability, and most plemented by inoculation with AMF by first of the species used in inoculation pro- determining the viability of the natural infec- grammes are exotic to their sites of applica- tive propagules (spores, infected root frag- tion, which may explain the occurrence of ments and mycelia) of those original soils. As failed inoculations under field conditions. previously determined by Gaidashova et al. The response of TC bananas to indigenous (2010), these two sites had quite different soil AMF is still under-explored, and the objec- properties, with notably dissimilar P concen- tive of this work was to determine the effi- trations (Table 10.1). cacy of indigenous AMF inoculants in TC Samples of the original (non-sterile) soils bananas. It was assumed that as indigenous were collected from each of the two banana- AMF species are more adapted to local con- growing regions (Kibungo and Rubona) and ditions, they should enhance the perfor- their MSI values compared with those of mance of TC bananas. This work aimed to three inoculants: two prepared mixed inocu- establish the effects of indigenous AMF from lants (AMF Kibungo and AMF Rubona) and a Rwandan banana plantations on the growth single AMF species inoculum (Glomus mosseae and subsequent yield of TC bananas in Nico. & Gerd.). The two prepared mixed inoc- Rwanda. Indigenous AMF inoculants derived ulants, AMF Kibungo and AMF Rubona, from AMF species from the banana-growing were derived, respectively, from the banana- regions of Rwanda were evaluated under growing sites at Kibungo and Rubona, and nursery conditions, and the inoculated plants had gone through trapping and bulking were subsequently established under field processes, initially with Sorghum bicolor (L.) Indigenous Arbuscular Mycorrhizal Fungi 85

Table 10.1. Soil pH, carbon, nitrogen, phosphorus, soil type and texture in two banana-growing regions. Data from Gaidashova et al. (2010).

Ecoregion pH (KCl) C (%) N (%) P (mg/kg) Soil type Soil texture

Butare 5.0–5.5 1.3–1.5 0.14–0.17 50.9–80.1 Acrisol Sandy clay Kibungo 6.2–6.5 3.5–3.6 0.30–9.32 17.4–19.8 Nitisol Clay

Moench, and then with Allium porrum (leek), maintained under nursery conditions. A total to build up inoculants with high concentra- of 48 plants were established per treatment tions of infective propagules; the inoculants and growth parameters (height, length and were prepared at the National Museums of width of the youngest leaf, stem girth, num- Kenya (NMK) and finally bulked at Jomo ber of functional leaves) were assessed every Kenyatta University of Technology (JKUAT), 2 weeks. A destructive harvest was under- Kenya (Munro et al., 1999). The single AMF taken to evaluate colonization and root dry species inoculum of G. mosseae was isolated weight at 22 weeks after deflasking – at the from unspecified banana plantations in end of the potting stage, when plants were Rwanda and prepared at Katholieke transferred to the field. Universiteit Louven (KUL), Belgium. The There is limited evidence on the sustained infectivities of the two (original) non-sterile performance of inoculated plantlets after estab- soils and the three AMF preparations were lishment under field conditions, so a field evaluated at three concentrations – full, half experiment was carried out next. At the end of and a quarter (100%, 50% and 25%), which the potting stage, i.e. 12 weeks after potting, the were prepared by diluting each with sterile inoculated plantlets were transferred to the soil. There were ten replications for each two field sites at Rubona and Kibungo from concentration, and the infectivity was which the nursery test soil had been collected. determined as the mean percentage AMF As already noted, these two sites have contrast- colonization of TC banana plantlets as test ing soil fertility (Table 10.1). The experiment (trap) plants, as estimated by the magnified was established and maintained under natural intersect method (McGonigle et al., 1990). For conditions, but with watering undertaken in this, the presence of hyphae, arbuscules or extremely dry seasons. Manual weeding was vesicles was recorded for 30 root fragments done continuously so that fields were kept weed (1 cm long)/sample of the two TC banana free. A total of 30 plants per treatment were cultivars at each of the three concentrations, established at each site, with three replicates and the total colonization calculated as the per treatment and ten plants per replicate. The percentage of intersections with any replicates were randomly distributed, although occurrence of mycorrhizal structures. each treatment was deliberately placed in one The MSI test was followed by a nursery block to avoid cross-contamination, and repli- study. This was conducted to establish the cates were separated by a 3 m grass strip. Three efficacy of the same three inoculants (mixed plants were maintained per mat. Growth was AMF Kibungo; mixed AMF Rubona; G. mosseae) monitored after every 2 weeks until flowering, in improving the performance of the two and yield was evaluated at harvest. banana cultivars potted in the two non-sterile An analysis of variance (ANOVA) was soils from Kibungo and Rubona, compared carried out to test the effect of AMF treatment with their performance in the non-inoculated on banana growth, and arcsine square root non-sterile soils (as controls). The mycorrhi- transformed percentage colonization data were zal inoculum was first administered at the subjected to statistical analysis using a general hardening stage, when plantlets were trans- linear model (GLM) and GENSTAT version ferred from in vitro conditions to the two test 11 software (VSN International, 2008). When soils. After 8 weeks, the now hardened plants significant factor effects were noted means were potted into 1 l plastic containers, inocu- were separated by least significant difference lum was administered again and the plants (LSD) at a significance level of a = 0.05. 86 J.M. Jefwa et al.

10.3 Results and Discussion maintained similar infectivity at all three of the concentrations that were tested. 10.3.1 Mycorrhizal soil infectivity (MSI) The results from the MSI test established of two site soils and three AMF inoculants the need for inoculation of the two soils from Kibungo and Rubona as they had lower infectivity than did the three inoculated soils The mixed inoculants AMF Kibungo and (except for the most dilute G. mosseae inocu- AMF Rubona, and the single species G. mosseae lum). The mixed inoculants AMF Kibungo inoculum, had higher infectivity at full con- and AMF Rubona had the highest infectivity centrations than did the non-sterile site soils at 50% and 100% concentrations; dilution to from Kibungo and Rubona (Fig. 10.1). The 25% reduced their infectivity almost to levels infectivity of all three inoculants was highly similar to the non-inoculated soils from the reduced when diluted to a quarter, with a two sites. marked decline observed for the mixed AMF Kibungo inoculant and the G. mosseae inoculum. The non-sterile non-inoculated soils from Kibungo and Rubona had lower infec- 10.3.2 Nursery studies of inoculated tivity at all concentrations than did the AMF TC banana plantlets Kibungo and AMF Rubona preparations, respectively. However, the mixed AMF The effectiveness of the same three AMF Rubona inoculant and the non-sterile non- inoculants and the same two site soils used in inoculated soils from Kibungo and Rubona the MSI test on the mycorrhizal colonization

30 % colonization 20

0 Glomus AMF Kibungo AMF Rubona Kibungo original Rubona original Inoculant or soil Full Half Quarter

Fig. 10.1. Comparative mycorrhizal soil infectivity (MSI) of two site soils and inoculants of three arbuscular mycorrhizal fungi (AMF). The site soils were unprocessed (i.e. non-sterilized) soils from two banana-growing regions in Rwanda (Kibungo and Rubona) and are denoted Kibungo original and Rubona original. The three AMF inoculants are: Glomus, a single species inoculum of G. mosseae from an unspecified banana-growing region in Rwanda; AMF Kibungo, a mixed concentrated AMF inoculant prepared from the banana-growing region of Kibungo: and AMF Rubona, a mixed concentrated inoculant prepared from the banana-growing region of Rubona. Each of the samples was tested for their infectivity of TC banana plantlets at three concentrations: full (100%), half (50%), quarter (25%), with dilutions performed using sterilized soil. Error bar, standard error of difference between means (SED). Indigenous Arbuscular Mycorrhizal Fungi 87

of TC plantlets of the banana cultivars differed in their responses to inoculation, ‘Kamaramasenge’ and ‘Mpologoma’ under with ‘Mpologoma’ more responsive than nursery conditions is shown in Fig. 10.2. ‘Kamaramasenge’. The mixed AMF Kibungo Colonization intensity (%) was higher in the inoculant significantly (P < 0.05) increased plants treated with mixed inoculants (AMF the height of both cultivars in the Rubona Kibungo and AMF Rubona) than in plantlets soil – by 35% and 19%, respectively, compared inoculated with the single species inoculum with the control heights in non-inoculated (G. mosseae) and in plantlets growing in the non-sterile Rubona (Fig. 10.3). However, in non-inoculated, non-sterile Kibungo and the Kibungo soil, the same AMF Kibungo Rubona control soils. The two banana culti- inoculant only increased the height growth vars did not show any significant difference of one of the cultivars – ‘Mpologoma’, by 17%. (P < 0.05) in percentage colonization. Although growth of the plantlets was gener- The growth response to AMF inoculation ally poor in the Kibungo soil, an increase in of the two banana cultivars under nursery height was observed for both cultivars with conditions differed with AMF treatments and the mixed AMF Rubona inoculant – 18% for soil conditions; only data on plant height ‘Mpologoma’ and 15% for ‘Kamaramasenge’, (Fig. 10.3) and leaf surface area (derived from while inoculation with G. mossease increased leaf width and length) (Fig. 10.4) are pre- the height of ‘Mpologoma’ by 43% and sented as indicators of efficacy. The main ‘Kamaramasenge’ by 18%. effects of AMF, cultivar and soil, and their Inoculation with AMF affected leaf interactions, were highly significant (P < 0.001) surface area (LSA) of both banana cultivars for plant height. The response to inoculation (Fig. 10.4). This was more pronounced in was more evident in the Rubona soil than in ‘Mpologoma’, where increases were evident the soil from Kibungo. The two cultivars also with all inoculants, though they were small

% colonization 20

0 original original Glomus Rubona Kibungo AMF Rubona AMF Kibungo Inoculant or soil ‘Kamaramasenge’ ‘Mpologoma’

Fig. 10.2. Mycorrhizal colonization intensity (%) of potted banana plantlets of ‘Mpologoma’ and ‘Kamaramasenge’ cultivars inoculated with (i) each of two mixed AMF (arbuscular mycorrhizal fungi) inoculants, AMF Kibungo and AMF Rubona, prepared, respectively, from the banana-growing regions of Kibungo and Rubona in Rwanda, and (ii) a single species inoculum of Glomus (G. mosseae) from an unspecified banana-growing region in Rwanda. Comparative colonization intensity is given for two non- sterile, non-inoculated control soils from Kibungo and Rubona (Kibungo original and Rubona original). Measurements were made 22 weeks after inoculation, i.e. at the time of planting out in the field. Error bars represent the variability in % colonization. 88 J.M. Jefwa et al.

Height (cm) 8

0 AMF-K AMF-R Glomus Control AMF-K AMF-R Glomus Control ‘Mpologoma’ ‘Kamaramasenge’ Treatments and cultivars Rubona Kibungo

Fig. 10.3. Effect of AMF (arbuscular mycorrhizal fungi) inoculants on height of two banana cultivars, ‘Mpologoma’ and ‘Kamaramasenge’, established in two soils from banana-growing regions in Rwanda (Kibungo and Rubona) under nursery conditions at 22 weeks after deflasking. AMF-K and AMF-R, inoculants prepared from banana-growing soils from Kibungo and Rubona; Glomus, a single species inoculum of G. mosseae from an unspecified banana-growing region in Rwanda. Controls are non-sterile, non-inoculated site soil from Kibungo or Rubona. Error bars, standard error of difference between means (SED) for AMF treatments, cultivars and site soils.

400

350

300 ) 2

250

200

150 Leafarea surface (cm 100

0 AMF-K AMF-R Glomus Control AMF-K AMF-R Glomus Control ‘Mpologoma’ ‘Kamaramasenge’ Treatments and cultivars Rubona Kibungo

Fig. 10.4. Effect of AMF (arbuscular mycorrhizal fungi) inoculants on mean leaf surface area of third leaf from the sword leaf of two banana cultivars, ‘Mpologoma’ and ‘Kamaramasenge’, established in two soils from banana-growing regions in Rwanda (Kibungo and Rubona) under nursery conditions at 22 weeks after deflasking. AMF-K and AMF-R, inoculants prepared from banana-growing soils from Kibungo and Rubona; Glomus, a single species inoculum of G. mosseae from an unspecified banana-growing region in Rwanda. Controls are non-sterile, non-inoculated site soil from Kibungo or Rubona. Error bars, standard error of difference between means (SED) for AMF treatments, cultivars and site soils. Indigenous Arbuscular Mycorrhizal Fungi 89

with G. mosseae; the increases were more nota- was still reflected under field conditions, and ble in soils from Rubona than from Kibungo. subsequently observed on yield. At 28 weeks The effect of inoculation in increasing the LSA after establishment in the field, the differ- of ‘Kamaramasenge’ was also evident with all ences had increased, in part because the three inoculants, but less pronounced. plants at Rubona had started at a greater height and in part because the relative growth rate of plants at Rubona was greater than 10.3.3 Field performance of inoculated those at Kibungo during the 12 weeks after TC banana plants planting. This suggested that conditions at Rubona were more conducive for growth of As already mentioned, inoculum was admin- banana plants than they were at Kibungo. istered only at the nursery stage (i.e. there Inoculation generally improved height was none administered under field condi- and leaf surface area growth compared with tions), hence plantlets transferred to field non-inoculated control treatments at both conditions were already colonized by AMF Rubona and Kibungo (Figs 10.5 and 10.6), but and of variable growth, as indicated in the significantly increased the height and leaf preceding results. The plants raised in surface area of both cultivars (‘Mpologoma’ Rubona soils at the nursery stage were taller and ‘Kamaramasenge’) only at Rubona. than those raised in the Kibungo soils when However, the effect of inoculation was more they were planted. The positive effect of inoc- evident on ‘Mpologoma’, decreasing with ulation that was shown under nursery condi- inoculant type in the order AMF Kibungo, tions on plant height and leaf surface area AMF Rubona and the G. mosseae.

140

120

100

80 (cm)

60 Height

0 AMF-K AMF-R Glomus Control AMF-K AMF-R Glomus Control

‘Mpologoma’ ‘Kamaramasenge’

Treatments and cultivars

Rubona Kibungo

Fig. 10.5. The effect of AMF (arbuscular mycorrhizal fungi) inoculation in the nursery on the height growth of two cultivars, ‘Mpologoma’ and ‘Kamaramasenge’, at 28 weeks after field establishment at two banana-growing sites in Rwanda, Rubona and Kibungo. AMF-K and AMF-R, inoculants prepared from banana-growing soils from Kibungo and Rubona; Glomus, a single species inoculum of G. mosseae from an unspecified banana-growing region in Rwanda. Controls are non-inoculated treatments at Kibungo and Rubona. Error bars represent variability in mean height of two banana cultivars treated with AMF in the two soils. 90 J.M. Jefwa et al.

9000

8000

7000 ) 2 6000

5000

4000

3000 Leaf surface area (cm 2000

1000

0 AMF-K AMF-R Glomus Control AMF-K AMF-R Glomus Control

‘Mpologoma’ ‘Kamaramasenge’

Treatments and cultivars Rubona Kibungo

Fig. 10.6. The effect of AMF (arbuscular mycorrhizal fungi) inoculation in the nursery on the mean leaf surface area (LSA) of the third leaf from sword leaf of plants of two cultivars (‘Mpologoma’ and ‘Kamaramasenge’) 28 weeks after field establishment at two banana-growing sites in Rwanda, Rubona and Kibungo. AMF-K and AMF-R, inoculants prepared from banana-growing soils from Kibungo and Rubona; Glomus, a single species inoculum of G. mosseae from an unspecified banana-growing region in Rwanda. Controls are non-inoculated treatments at Kibungo and Rubona. Error bars represent variability in LSA of two banana cultivars treated with AMF in the two site soils.

There was a clear distinction in yield 10.4 Conclusion between inoculated and non-inoculated treatments, with yield highest in the inocu- It is evident from this study that inoculation lated treatments for both cultivars at both of TC banana plantlets at the nursery stage sites. The treatments with AMF resulted in gives a comparative advantage to the growth significantly (P < 0.001) higher yields com- of plantlets, which translates into improved pared with non-inoculated plants of the two growth and subsequent yield under field cultivars (Fig. 10.7), with the yield of both cul- conditions. This has practical significance in tivars highest for mixed AMF inoculant treat- that AMF application at the nursery stage is ments and less for the single species G. mosseae easier than at the field stage. The differences inoculum at both sites. The highest yield was in responsiveness of TC banana cultivars to from plants inoculated with AMF Kibungo at inoculation at the two experimental sites the Rubona site: 31.4 t/ha for ‘Mpologoma’ may perhaps be explained by their differ- and 29.3 t/ha for ‘Kamaramasenge’. ences in P concentration. The Kibungo soil At the Kibungo site, the differences in had a P concentration of 17.4–19.8 mg/kg, the effect of the three inoculants on yield was while the Rubona soil had a P concentration more evident in ‘Mpologoma’, with the highest of 50.9–80.1 mg/kg (Gaidashova et al., 2010). yield recorded in treatments with AMF The performance of the two cultivars was Kibungo, followed by AMF Rubona and consistently poorer in the low P Kibungo soil G. mosseae. For ‘Kamaramasenge’, the three than in the high P Rubona soil, and inocu- inoculants were similar in their effect on lation with AMF did not always improve yield, but all gave better yields than the non- performance. However, the ‘Mpologoma’ inoculated control treatment. (AAA-EA) cultivar derived more benefits Indigenous Arbuscular Mycorrhizal Fungi 91

15 Yield (tYield /ha)

0 AMF-K AMF-R Glomus Control AMF-K AMF-R Glomus Control ‘Mpologoma’ ‘Kamaramasenge’ Treatments and cultivars Rubona Kibungo

Fig. 10.7. Yield at harvest of banana cultivars ‘Mpologoma’ and ‘Kamaramasenge’ inoculated in the nursery with AMF (arbuscular mycorrhizal fungi) and established at two banana-growing sites in Rwanda, Kibungo and Rubona. AMF-K and AMF-R, inoculants prepared from banana-growing soils from Kibungo and Rubona; Glomus, a single species inoculum of G. mosseae from an unspecified banana-growing region in Rwanda. Controls, non-inoculated treatments at Kibungo and Rubona. Error bars, standard error of means (SE) for cultivars and soil conditions. from inoculation than the ‘Kamaramasenge’ evaluated for its effectiveness in this study, (AAB) cultivar, indicating variation in there is still a need to screen individual AMF responses between the two. Several other species both singly and in various combina- studies have indicated that the genetic variations to verify the optimum number and type bility of plant cultivars could influence the of isolates required for effective performance. efficiency of AMF isolates (Declerck et al., There is also still limited information on the 1995; Clark and Zeto, 2000). This study has threshold P concentrations required for opti- demonstrated that indigenous AMF isolates, mum effectiveness of such mycorrhizal although variable in their effects on plant inoculants. growth, have great potential for improving It is clear then that TC bananas can ben- banana growth in the nursery, which subse- efit from indigenous AMF inoculants, even quently translates to yield improvement though there is need to understand the best under field conditions. conditions for optimum performance of AMF A survey that was conducted before this species to maximize benefits. This informa- experiment in the banana-growing regions of tion is still lacking, particularly for crops that Rwanda (which included Kibungo and Rubona) could benefit immensely from AMF interven- revealed a diverse range of AMF species com- tions such as micropropagated plants, nursery position in the soil, with the number of iso- managed plants, and root and tuber crops. lates that were found higher in Kibungo (ten) than in Rubona (two) (Gaidashova et al., 2010). In this study, the AMF inoculants derived Acknowledgements from Kibungo consistently performed better than the single species inoculum and the We would like to acknowledge Bioversity mixed inoculants from Rubona. Except for International through the CIALCA (Con- the G. mosseae inoculum, which was directly sortium for Improving Agriculture-based 92 J.M. Jefwa et al.

Livelihoods in Central Africa) project for technical assistance. The study was conducted supporting this study, the International Centre by CIAT-TSBF (International Centre for for Tropical Agriculture (CIAT) and the Tropical Agriculture – Tropical Soil Biology Rwanda Agriculture Board (RAB) for and Fertility) and ISAR (Institut des Sciences implementing the activities, and Elias Mwangi, Agronomiques du Rwanda) supported by Susan Njuguini and Victor Otieno for their Bioversity International.

References

Bagyaraj, D.J. (1992) Vesicular arbuscular mycorrhizae: applications in agriculture. Methods in Microbiology 24, 359–374. Clark, R.B. and Zeto, S.K. (2000) Mineral acquisition by arbuscular mycorrhizal plants. Journal of Plant Nutrition 23, 867–902. Declerck, S., Devos, B., Delvaux, B. and Plenchette, C. (1994) Growth response of micropropagated banana plants to VAM inoculation. Fruits 49, 103–109. Declerck, S., Plenchette, C. and Stullu, D.G. (1995) Mycorrhizal dependency of banana (Musa acuminata, AAA group) cultivar. Plant and Soil 176, 183–187. Gaidashova, S.V., van Asten, P.J.A., Jefwa, J.M., Delvaux, B.M and Declerck, S. (2010) Arbuscular mycorrhizal fungi in East African highland banana cropping systems as related to edapho-climatic conditions and management practices: case study of Rwanda. Fungal Ecology 3, 225–233. Jefwa, J., Vanlauwe, B., Coyne, D., van Asten, P., Gaidashova, S., Rurangwa, E., Mwashasha, M. and Elsen, A. (2010) Benefits and potential use of arbuscular mycorrhizal fungi (AMF). Acta Horticulturae 879, 479–486. McGonigle, T.P., Miller, M.H., Evans, G.L., Fairchild, G.L., and Swan, J.L. (1990) A new method which gives an objective measure of colonization of roots by vesicular arbuscular mycorrhizal fungi. New Phytologist 115: 495-501. Munro, R.C., Wilson, J., Jefwa, J. and Mbuthia, K.W. (1999) A low-cost method of mycorrhizal inoculation improves growth of Acacia tortilis seedlings in the nursery. Forest Ecology and Management 113, 51–56. Mwashasha, R. (2006) Arbuscular mycorrhizal dependency of different tissue cultured banana cultivars. MSc thesis, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, Kenya. Rurangwa, E. (2009) The influence of arbuscular mycorrhizal fungi on nursery and initial performance of banana. MSc thesis, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, Kenya. Sieverding, E. (1991) Vesicular-arbuscular Mycorrhiza Management in Tropical Agrosystems. Deutsche Gesellschaft für Technische Zusammenarbeit (German Technical Cooperation, GTZ) Eschborn, Germany. Sosa Hernández, B. (1997) Estudio de la interacción de los hongos formadores de micorrizas arbusculares (MA) y el patógeno vascular Fusarium oxysporum f.sp. cubense sobre platnera en fase de vivero. Proyecto Fin Carrera, Centro Superior de Ciencias Agrarias [now Escuela Técnica Superior de Ingeniería Agraria], Universidad de la Laguna, La Laguna, Santa Cruz de Tenerife, Spain. VSN International (2008) Genstat, 11th edn. VSN International, Hemel Hempstead, UK. Yano-Melo, A.M., Saggin Júnior, O.J., Lima-Filho, J.M., Melo, N.F. and Maia, L.C. (1999). Effect of arbuscular mycorrhizal fungi on the acclimatization of micropropagated banana plantlets. Mycorrhiza 9, 119–123. 11 Development of ELISA for the Detection of Xanthomonas campestris pv. musacearum, the Causal Agent of BXW: Banana Xanthomonas Wilt

G.V. Nakato,1* S.A. Akinbade,2 P. Lava Kumar,2 R. Bandyopadhyay2 and F. Beed1 1International Institute of Tropical Agriculture (IITA), Kampala, Uganda; 2IITA, Ibadan, Nigeria

Abstract Rabbit polyclonal antibodies (PAbs) were produced against a pure isolate of Xanthomonas campestris pv. musacearum (Xcm), which is the causal organism of banana Xanthomonas wilt (BXW) disease of banana (Musa spp.) in the Great Lakes region of Africa. Anti-Xcm PAbs were used to develop a direct antigen coating enzyme-linked immunosorbent assay (DAC-ELISA) for the detection of Xcm in leaf and pseudostem tissues of infected banana and plantain (Musa spp.). The anti-Xcm PAbs in DAC-ELISA specifically reacted with Xcm but not with Escherichia coli, X. vasicola pv. vasculorum of maize and sugarcane or X. vasicola pv. holcicola of sorghum. Results of the DAC-ELISA detection of Xcm are comparable with the results of PCR and culture-based detection assays for the same pathogen.

11.1 Introduction diagnosis of BXW in the fields is complicated because of its similarities to symptoms of For the people of the Great Lakes region of another disease in bananas, Panama disease, Africa, which incorporates Burundi, Kenya, which is caused by Fusarium oxysporum f.sp. Rwanda, Tanzania, Uganda and the cubense. PCR-based diagnostic assays have Democratic Republic of Congo, bananas and been developed for Xcm detection (Aritua plantains (Musa spp.) are staple food. Banana et al., 2008; Adikini et al., 2011; Adriko et al., Xanthomonas wilt (BXW) caused by the bac- 2011), but the use of this technique requires terium Xanthomonas campestris pv. musacearum considerable skills, reagents and equipment, (Xcm) has emerged as a major constraint to which are in short supply in the BXW-affected banana production in the Great Lakes region countries. (Tripathi et al., 2009). Xcm infection results in Diagnostics assays based on the ELISA progressive wilting and death of the plant principle are known to be simple, cost-effective (Tushemereirwe et al., 2003). Symptom-based and relatively easy for adoption in developing

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 93 94 G.V. Nakato et al.

countries. The development of an ELISA-based 11.2.2 Bacterial cultures method for Xcm would offer a convenient and cost-effective alternative method for reliable The Xcm used in this study was isolated diagnosis of disease in the field-collected from naturally infected banana plants (cv. samples. ELISA is a plate-based assay designed Kayinja) from the Kifu experimental site and for detecting and quantifying proteins using cultured on yeast peptone agar (YPGA) antibodies (Clark and Adams, 1977). One of (Schaad et al., 2001). Close relatives of Xcm the methods by which detection can be accom- that infect sorghum (X. vasicola pv. holcicola) plished is by assessing the activity of an (NCPPB 1060 and 2417), maize (X. vasicola pv. enzyme-labelled antibody conjugate via incu- vasculorum) (NCPPB 206) and sugarcane bation with a substrate to produce a measure- (X. vasicola pv. vasculorum) (NCPPB 889) able product (Unson et al., 1998). Among the (Aritua et al., 2008) were obtained from the advantages of using direct antigen coating National Collection of Plant Pathogenic (DAC)-ELISA is its ability to perform using a Bacteria in the UK, and used as controls to common enzyme-labelled antibody conjugate determine antibody specificity. These three that is available commercially (Narayanasamy, isolates were cultured on yeast D(+)-glucose 2011). In this study, polyclonal antibodies agar (YDC) as detailed in Goszczynska et al. (PAbs) against Xcm were produced and a (2000). In addition, Escherichia coli (JM 0109) DAC-ELISA-based assay was developed for in Luria-Bertani medium (LB) (Bertani, 2004) Xcm detection in infected plant tissues. The was also used as a control. results of this assay were compared with previously developed PCR methods (Adikini et al., 2011) and culturing on semi-selective media: 11.2.3 Production of polyclonal cellobiose cephalexin agar (CCA) (Mwangi antibodies et al., 2007) and yeast extract trypton sucrose agar cephalexin cycloheximide (YTSA-CC) Overnight growth cultures of Xcm in YPGA (Tripathi et al., 2007). The results confirmed that media were treated with 1% (v/v) formalde- DAC-ELISA offers reliable detection of Xcm in hyde for 1 h at room temperature. The for- infected plants. maldehyde-fixed cells were precipitated by centrifugation at 10,000 rpm for 5 min. The cell pellet was washed three times in phosphate-buffered saline (PBS) (20 mM sodium 11.2 Materials and Methods phosphate, pH 7; 300 mM NaCl) and resus- pended in 0.5 ml PBS. A 100 μl sample of the 11.2.1 Plant samples cell suspension was emulsified with equal volumes of Freund’s complete adjuvant Leaf and pseudostem samples that were free of (Sigma, USA) and used for immunization via Xcm were obtained from the tissue culture lab- intramuscular injection at multiple sites into oratory and germplasm fields of the National a New Zealand White inbred rabbit. A sub- Banana Research Programme of the National sequent two further injections at a weekly Agricultural Research Organisation (NARO) interval were given using Xcm cells emulsi- located in Kawanda, Uganda. BXW-affected fied with equal volumes of Freund’s incom- samples were sourced from experimental plots plete adjuvant. The rabbit was bled for in Kifu Forest, located 32 km from Kampala polyclonal antiserum 1 week after the last (Uganda) on the research site of the National injection for 4 weeks at weekly intervals. The Forestry Resources Research Institute. Samples titre of anti-Xcm antibodies in the unfraction- were collected from asymptomatic (Xcm infec- ated polyclonal serum was determined by tion ascertained by PCR) and symptomatic an indirect ELISA as described below using plants (with yellow and wilted leaves, vascular alkaline phosphatase (ALP)-labelled goat discoloration and yellow ooze, premature rip- anti-rabbit IgG (Sigma) as reporter antibody ening of bunches and wilting of male buds) for and para-nitrophenylphosphate (pNPP) as various assays in the study. substrate (Mowat and Dawson, 1987). ELISA for Detection of Xanthomonas campestris pv. musacearum 95

11.2.4 The ELISA procedure 100 μl of the serial dilution was used for Xcm detection in DAC-ELISA using anti-Xcm The DAC-ELISA procedure described by PAbs at 1:1 × 10–4 for detection as in the proce- Hobbs et al. (1987) was used for Xcm detection. dure described in Section 11.2.4. An appropriate concentration of purified Xcm cells or leaf tissue extract were diluted in 0.2 M carbonate coating buffer, pH 9.6, and 100 μl of 11.2.7 Comparison of DAC-ELISA this was loaded into the wells of a 96 well with morphological and molecular microtitre plate (Nunc microplates). The plate diagnostics was incubated for 1 h at 37°C and then washed with three changes of PBS containing 0.05% Tissue samples from Xcm-infected and unin- (v/v) Tween-20 (PBST). An appropriate dilu- fected plants were collected and used for tion of anti-Xcm PAbs was made in PBST con- Xcm detection using a culturing technique on taining 0.2% (w/v) ovalbumin and 2% (w/v) YPGA (Schaad et al., 2001), PCR (Adikini μ polyvinyl pyrrolidine (PBS-TPO), 100 l was et al., 2011) and DAC-ELISA (this study). For dispensed into the antigen-coated wells and PCR detection, total DNA was isolated from the plate was incubated at 37°C for 1 h. After 0.2 g of plant tissue using the CTAB (cetyltri- washing with three changes of PBST, the wells methylammonium bromide) buffer extrac- μ were filled with 100 l of 1:5000 (v/v) ALP- tion method (Zhang et al., 1998). PCR was labelled anti-rabbit IgG in PBS-TPO and the performed using 1, 2 or 3 μl of the DNA sus- plate was incubated at 37°C for 1 h. The wells pension using the Xcm primer pair described were washed with three changes of PBST and in Adikini et al. (2011). then filled with 100 μl of substrate (1 mg/ml pNPP in 10% (v/v) diethanolamine buffer, pH 9.8). The plate was incubated at 37ºC for 11.3 Results 1 h or overnight at 4°C. Optical densities (OD) were measured in an ELISA plate reader 11.3.1 Antibody specificity (Conquer Scientific) fitted with a 405 nm filter.

Anti-Xcm PAbs were tested with a pure cul- 11.2.5 Specificity of anti- X. c. pv. ture of Xcm, using E. coli and coating buffer as musacearum polyclonal antibodies the negative controls. Analysis of variance of the OD values from the ELISA plate reader Xcm, E. coli and other reference isolates were revealed highly significant differences (P < 0.001) reconstituted in carbonate coating buffer, between the Xcm culture and the E. coli and pH 9.6, and their concentrations adjusted to coating buffer controls: the OD values for 0. 1, 0.5 and 1 OD at 560 nm in sterile cuvettes Xcm were twice those of E. coli and the coat- in a spectrophotometer. A sample of 100 μl of ing buffer (Table 11.1). the bacterial cell suspension was used for Xcm antiserum was tested on pure cul- testing in ELISA using anti-Xcm PAbs diluted tures of other xanthomonads affecting sor- to 1:1 × 10–4 in PBS-TPO for detection as in the ghum, maize and sugarcane at 0.1, 0.5 and 1.0 procedure described in Section 11.2.4. OD concentration, as read by the spectrophotometer at 620 nm. For bacterial concentrations of 0.1 and 0.5, analysis of variance of the 11.2.6 Detection of X. c. pv. musacearum OD values indicated significant differences in symptomatic, asymptomatic and (P < 0.001) between the organisms tested, with healthy banana plant materials Xcm having the highest OD values, followed by X. vasicola pv. holcicola from sorghum, Samples (100 mg) of symptomatic, asympto- X. vasicola pv. vasculorum from sugarcane and matic and healthy fresh plant tissues were X. vasicola pv. vasculorum from maize, in ground in 1 ml of carbonate coating buffer. descending order (Table 11.2). Significant dif- The extract was serially diluted six times and ferences (P < 0.001) were also observed in the 96 G.V. Nakato et al.

ELISA plates that received bacterial concen- 11.3.2 Determining working dilution in trations of 1.0 OD. Xcm had the highest OD ELISA tests for X. c. pv. musacearum value, followed by X. vasicola pv. vasculorum from sugarcane, X. vasicola pv. vasculorum In the tests on the effects of reciprocal PAbs from maize and lastly X. vasicola pv. holcicola and Xcm dilutions to determine the sensitivity from sorghum. X. campestris pv. musacearum of the Xcm ELISA assay, significant differences OD values were twice those of X. vasicola pv. were observed in the 1:1 × 10–4 and 1:5 × 10–3 PAb vasculorum from sugarcane (Table 11.2). dilutions (Table 11.3). This implies that Xcm

Table 11.1. Anti-Xanthomonas campestris pv. musacearum (Xcm) polyclonal antibodies (PAbs) tested against Xcm and Escherichia coli and coating buffer as controls tested by ELISA. Mean optical density was measured at 405 nm from the ELISA plate reader. Means followed by the same letter are not significantly different from one another at P = 5%.

Optical density after the specified incubation time

Treatment 1 h 24 h

Buffer 0.122b 0.223b Escherichia coli 0.120b 0.206b Xanthomonas campestris pv. musacearum 0.274a 0.631a

Table 11.2. Anti-Xanthomonas campestris pv. musacearum (Xcm) polyclonal antibodies (PAbs) tested against three concentrations of Xcm and other xanthomonads, using coating buffer as a control and tested by ELISA. Mean optical densities at 405 nm were measured by the ELISA plate reader 1 h post incubation. Means followed by the same letter are not significantly different from one another at P = 5%.

Optical density from ELISA plates for each initial bacterial concentrationa

Treatment 0.1 0.5 1.0

Buffer control 0.076d 0.074e 0.097e X. vasicola pv. vasculorum (maize pathogen) 0.293c 0.182d 0.144c X. vasicola pv. vasculorum (sugarcane pathogen) 0.425b 0.212c 0.182b X. vasicola pv. holcicola (sorghum pathogen) 0.496b 0.339b 0.090d Xanthomonas campestris pv. musacearum 0.941a 0.896a 0.824a aInitial bacterial concentrations given as optical density at 650 nm.

Table 11.3. Means of optical density (at 405 nm) in ELISA tests for reciprocal antiserum and Xanthomonas campestris pv. musacearum (Xcm) dilutions to determine sensitivity. Means followed by the same letter are not significantly different from one another at P = 5%.

Mean optical density for antiserum dilution (v/v)

Pure Xcm dilution 1:10000 1:5000 1:2500 1:1500 1:1000

Buffer control 0.224a 0.220a 0.230a 0.228a 0.238a 1.0 × 10–1 0.349b 0.371b 0.316b 0.348b 0.279b 5.0 × 10–2 0.396b 0.422c 0.346bc 0.388c 0.287b 2.5 × 10–2 0.446c 0.469cd 0.370cd 0.403cd 0.288b 1.25 × 10–2 0.482cd 0.469cd 0.394de 0.435de 0.289b 6.25 × 10–3 0.498d 0.505de 0.409ef 0.461e 0.305b 3.13 × 10–3 0.502d 0.540e 0.413ef 0.472e 0.309b 1.56 × 10–3 0.513d 0.541e 0.445f 0.507f 0.313b ELISA for Detection of Xanthomonas campestris pv. musacearum 97

was detected when 2.5 × 107 or 5 × 107 cells/ml 405 nm was produced, and for the molecular were initially present for PAb dilutions of 1:1 × 10–4 method detection occurred when an observ- and 1:5 × 10–3, respectively. able 650 bp band was amplified using the Xcm 38 primer pair of Adikini et al. (2011).

11.3.3 Antibody sensitivity and detection of X. c. pv. musacearum 11.4 Discussion and Conclusion in diseased, asymptomatic and healthy banana plant material The objective of this study was to develop and evaluate polyclonal antibodies (PAbs) Xcm was detected in symptomatic leaf for ELISA detection of X. campestris pv. samples at all dilution levels, that is, when musacearum (Xcm). The data presented serially diluted once (0.5 × original bacterial indicate that ELISA is a specific and sensitive concentration), thrice (0.125) and six times method and could provide a practical test (0.016) (Fig. 11.1a). Similar results were supplementary to morphological and molec- observed for asymptomatic leaf samples ular methods for detection of Xcm of banana. (Fig. 11.1b). For pseudostem sample dilutions, This is the first time a serological diagnostic Xcm was detected in all antibody dilutions method for Xcm has been developed. PAbs for the symptomatic samples (Fig. 11.1c), were preferred to monoclonal antibodies while for the asymptomatic samples a similar (MAbs) because they are less expensive and result was observed in the 0.5× and 0.125× can be generated much more rapidly, and dilutions (Fig. 11.1d). However, for pseudostem with less technical skill than is required to samples for asymptomatic plants diluted produce MAbs (Yokoyama, 1995; Zola, 1999). sixfold, Xcm was detectable only up to 1:2048 The monospecificity of MAbs may limit their × 10–4 (= 4.88–8) antibody dilution (Fig. 11.1d). usefulness and small changes in the structure of an epitope (e.g. as a consequence of genetic polymorphism, glycosylation or denatura- 11.3.4 Comparison of X. c. pv. tion) markedly affect their function (Neil musacearum diagnostics through et al., 2005). In contrast, because PAbs are het- morphological identification, ELISA erogeneous and recognize a host of antigenic and molecular methods epitopes, the effect of change on a single or small number of epitopes is less likely to be Standard protocols for Xcm detection by cul- significant (Neil et al., 2005). PAbs are also turing, ELISA and PCR were used to detect more stable over a broad range of pH and salt Xcm in infected, asymptomatic and sympto- concentrations, whereas MAbs can be highly matic plant samples; uninfected plant parts susceptible to small changes in both (Neil were included as controls. The only samples et al., 2005). in which Xcm was detected by all three meth- The PAbs tested were specific to Xcm, ods was the symptomatic pseudostem sam- the causative agent of banana Xanthomonas ples (Table 11.4). In the symptomatic leaf wilt (BXW) disease. It is evident that there samples and the asymptomatic leaf and pseu- was no cross-reaction of the anti-Xcm PAbs dostem samples, Xcm was detected by the with E. coli, X. vasicola pv. vasiculorum and culturing method and ELISA only. Xcm was X. vasicola pv. holcicola. Buchwalow and not detected in the uninfected (control) plant Böcker (2010) noted that PAbs frequently parts by any of the three methods (Table 11.4). have better specificity than MAbs because For the cultural morphological method, they are produced by a large number of B-cell detection of Xcm occurred when characteris- clones, each generating antibodies to a spe- tic yellow and mucoid cultures were formed cific epitope, and polyclonal sera are a com- on semi-selective media (Tripathi et al., 2007; posite of antibodies with unique specificities, Mwangi et al., 2007); for ELISA, detection although the concentration and purity levels occurred when an OD of greater than 0.10 at of specific antibody are higher in MAbs. 98 G.V. Nakato et al.

(a) (c) 0.30 0.30

0.25 0.25

0.20 0.20

0.15 0.15

0.10 0.10 Absorbance at 405 nm 0.05 Absorbance at 405 nm 0.05

0.00 0.00 10 1 0.1 0.01 0.001 0.0001 10 1 0.1 0.01 0.001 0.0001 Polyclonal antibody dilution ϫ 10–4 Polyclonal antibody dilution ϫ 10–4

Healthy leaf Healthy pseudostem Leaf dilution 1 Pseudostem dilution 1 Leaf dilution 0.125 Pseudostem dilution 0.125 Leaf dilution 0.016 Pseudostem dilution 0.016

(b) (d) 0.30 0.30

D 0.25 0.25

0.20 0.20

0.15 0.15

0.10 0.10 Absorbance at 405 nm 0.05 Absorbance at 405 nm 0.05

0.00 0.00 10 1 0.1 0.01 0.001 0.0001 10 1 0.1 0.01 0.001 0.0001 Polyclonal antibody dilution ϫ 10–4 Polyclonal antibody dilution ϫ 10–4

Healthy leaf Healthy pseudostem Leaf dilution 1 Pseudostem dilution 1 Leaf dilution 0.125 Pseudostem dilution 0.125 Leaf dilution 0.016 Pseudostem dilution 0.016

Fig. 11.1. Detection of Xanthomonas campestris pv. musacearum (Xcm) in symptomatic ‘Kayinja’ banana plant material at three dilutions (1, 0.125, 0.016) using polyclonal antibodies diluted 12 times and compared with healthy samples. The antibody dilutions are presented on a log axis. To obtain actual dilution values multiply by 10–4. (a) symptomatic ‘Kayinja’ banana leaves; (b) asymptomatic ‘Kayinja’ banana leaves; (c) symptomatic ‘Kayinja’ banana pseudostem sample; and (d) asymptomatic ‘Kayinja’ banana pseudostem sample. ELISA for Detection of Xanthomonas campestris pv. musacearum 99

Table 11.4. Comparison of Xanthomonas campestris pv. musacearum (Xcm) diagnostics through morphological identification in culture, ELISA and molecular methods for healthy (uninfected) banana plant parts, and for asymptomatic and symptomatic banana infected plant parts. (+) indicates detection of Xcm and (−) indicates absence of a positive reaction. For the morphological method, detection of Xcm occurred when characteristic yellow and mucoid cultures were formed on semi-selective media (Mwangi et al., 2007; Tripathi et al., 2007); for ELISA, detection occurred when an optical density (OD) of greater than 0.10 at 405 nm was produced; for the molecular method, detection occurred when an observable 650 bp band was amplified using the Xcm 38 primer pair of Adikini et al. (2011).

Morphology Molecular Plant part in culture ELISA method

Uninfected leaf – 0.067 (–) – Infected symptomatic leaf + 0.384 (+) – Infected asymptomatic leaf + 0.273 (+) – Uninfected pseudostem – 0.079 (–) – Infected symptomatic pseudostem + 0.265 (+) + Infected asymptomatic pseudostem + 0.171 (+) –

Determination of the sensitivity of PAbs and the plant generation from which the sam- is necessary in order to detect infection when ples were picked, it was presumed that Xcm pathogen titres are low in asymptomatic was evenly distributed within the plant parts. plants. The results obtained suggest that It is concluded from the study that anti- ELISA is applicable to the detection of Xcm Xcm PAbs are selective and sensitive and hence in asymptomatic plants. The study also con- offer a practical detection tool compared to cludes that there are no confounding com- morphological and molecular detection pounds that hinder detection of Xcm in the methods. In ELISA, they were specific and different parts of infected plants. sensitive in detecting Xcm but not the other For asymptomatic samples, morphologi- bacteria tested, so this method has the potential cal detection was a more reliable method for to be used as a reliable assay for the detection of detecting Xcm in the pseudostem and leaf the causal agent of bacterial wilt of banana. samples, but this kind of identification is This technique should improve the field slow because the bacterium must first be detection and diagnosis of BXW, thus enabling recovered and then allowed to grow for 72 h rapid intervention to prevent its further spread. on artificial and semi-selective culture media. Molecular detection using PCR was more rapid and precise than the use of semi-selective Acknowledgement media as other xanthomonads may also form yellow mucoid cultures on semi-selective The authors extend appreciation to the media (although they are not expected from Association for Strengthening Agricultural bananas). ELISA succeeded in detecting Xcm Research in East and Central Africa in both symptomatic and asymptomatic plant (ASARECA) for financial support for this samples. Based on the inoculation method work.

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W. Ocimati,1* F. Ssekiwoko,2 M. Buttibwa,3 E. Karamura,1 W. Tinzaara,1 S. Eden-Green4 and G. Blomme1 1Bioversity International, Kampala, Uganda; 2National Banana Research Programme, National Agricultural Research Organisation (NARO), Kampala, Uganda; 3National Crops Resources Research Institute, NARO, Namulonge, Uganda; 4EG Consulting, Larkfield, Kent, UK

Abstract Xanthomonas wilt caused by Xanthomonas campestris pv. musacearum indiscriminately attacks all banana cultivars. Contaminated garden tools are one of the main modes of spread. Cultural practices are so far the most effective ways of controlling Xanthomonas wilt. However, they are laborious and frequently abandoned by farmers. Insight on within-plant spread/systemicity after a garden tool infection will inform existing control strategies. An on-station experiment using plants of East African highland bananas (EAHB, AAA-EA) and ‘Pisang Awak’ (Musa ABB) was established at Kifu Forest, Mukono District, central Uganda. One-year-old and 9.6-month-old vegetative-stage banana plants of both cultivars were inoculated with X. c. pv. musacearum by (i) cutting three leaf petioles (de-leafing) or (ii) cutting one sucker at soil level (de-suckering) using a contaminated knife or machete. Twenty 1-year-old inoculated plants/cultivar and treatment were monitored for disease incubation period and incidence during 13 months after inoculation. Mats of eighty 9.6-month-old plants/treatment and genotype were sampled (4 plants at 3 day intervals) for 60 days and suspensions of cross-sections of the parent plant corm and pseudostem, mat cord roots and lateral shoots were cultured on cellubiose cephalexin agar at 24°C for 72 h. In an additional experiment, three leaves of each of 20 EAHB and 20 ‘Pisang Awak’ plants were inoculated through either the leaf tip or leaf base and symptom development observed over 5 months. Markedly lower incidence and higher incubation period were observed in de-suckered plants than in de-leafed plants. This could be a result of the rather compact nature of corm tissues. The incubation period for de-leafed EAHB plants was longer for taller plants. The movement of X. c. pv. musacearum was systemic but the speed of this differed markedly between de-leafing and de-suckering treatments. The bacteria were observed to have spread throughout the mat long before symptoms appeared in the plants. Time from disease expression to complete leaf yellowing was significantly lower in leaf base (5.7 days) than leaf tip (22 days) inoculations, with uniform yellowing in leaf base treatments and progressive yellowing from the leaf tip in leaf tip treatments. Thus, within a leaf, X. c. pv. musacearum spreads faster in the direction of the xylem flow.

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 101 102 W. Ocimati et al.

12.1 Introduction The systemicity of X. c. pv. musacearum after an insect vector infection has been iden- Xanthomonas wilt of banana caused by tified in ‘Pisang Awak’ plants at four symp- Xanthomonas campestris pv. musacearum indis- tom stages: wilting of male bud bracts, drying criminately attacks all banana cultivars. of the male bud rachis, premature ripening of Xanthomonas wilt was first reported in the bunch, and rotting of the bunch and death bananas in Ethiopia in 1974 (Yirgou and of the plant (Ssekiwoko et al., 2010). No scien- Bradbury, 1974), but its impact on banana cul- tific studies have been carried out on the tivation has been limited to western parts, systemicity of X. c. pv. musacearum after tool where the cultivation of enset (Ensete spp.) infections though, and the spread of this dominates and only a few banana mats are disease from the parent plant to the lateral cultivated per farm. Ethiopia’s main banana shoots or vice versa after tool infection of veg- growing region in Arba Minch has so far etative plants is not well understood. Insight been spared from the disease. In 2001, the on the within-plant and within-mat spread of disease was observed in central Uganda X. c. pv. musacearum after a garden tool infec- (Tushemereirwe et al., 2004) and in North tion will help in the fine-tuning of existing Kivu, eastern Democratic Republic of Congo control methods. (Ndungo et al., 2006). Xanthomonas wilt is cur- The objectives of this study included rently also present in Rwanda (Reeder et al., establishing: (i) Xanthomonas wilt incidence; 2007), Tanzania (Mgenzi et al., 2006), Kenya (ii) Xanthomonas wilt incubation period, and (CRS/USAID/IITA, 2006; Mbaka et al., 2009) (iii) the pattern of X. c. pv. musacearum spread and Burundi (Carter et al., 2010). The disease within the banana mat after tool inoculation causes yield losses of up to 100%, especially in of different parts of vegetative-stage, field- cropping systems based on ABB bananas, established banana plants of both EAHB and leading to reduced home banana consump- ‘Pisang Awak’ cultivars. tion and household incomes, increased banana prices and the possibility that farm households may switch to other enterprises (Kalyebara 12.2 Materials and Methods et al., 2006; Karamura et al., 2006). Xanthomonas wilt has a similar epidemio- Field studies were carried out in an isolated logy to other banana bacterial wilts – Moko, area in Kifu Forest, Mukono District in central blood disease and Bugtok (Buddenhagen and Uganda. This is the only location in Uganda Elsasser, 1962; Eden-Green, 1994; Soguilon that is approved by the National Banana et al., 1995) – that are known to be transmitted Research programme of the National Agri- by insect vectors and garden tools (Yirgou cultural Research Organisation (NARO) and Bradbury, 1974). Studies have so far con- for artificial Xanthomonas wilt inoculation firmed the role of insect vectors in spreading experiments. The study area has a mean daily the disease through the male inflorescence temperature of 25°C, with a maximum (Tinzaara et al., 2006) and the role of contami- temperature of 29°C. The area is moist to nated garden tools via injuries to any part of sub-humid, with a mean annual rainfall of the plant (Eden-Green, 2004; Addis et al., 1100 mm, which is bimodal in distribution 2010). No resistant Musa varieties are yet (March–May and September–November). known (Thwaites et al., 2000, Ssekiwoko et al., Laboratory work was carried out at the National 2006). The cultural practices of roguing and Agricultural Research Laboratories, Kawanda. destroying infected plants, early removal of Suckers of ‘Pisang Awak’ and a mixture male buds, use of clean planting material and of EAHB cultivars (‘Mbwazirume’ and disinfection of farm tools have been the most ‘Nyakinyika’) were obtained from field- effective ways of reducing the inoculum in established parent plants known to be free infested fields (Yirgou and Bradbury, 1968; of Xanthomonas wilt and were planted on Tushemereirwe et al., 2004). However, these 7–8 April 2008 at a spacing of 2 × 2 m. Test measures are laborious and expensive and plants were allowed to grow until they thus are often abandoned by farmers. were 9.6 or 12 months old. At 9.6 months, Xanthomonas campestris pv. musacearum in banana plants 103

80 plants/ cultivar, and at 12 months, 20 plants/ were chopped into small pieces and sus- cultivar, were inoculated with X. c. pv. pended in distilled sterile water. The use of musacearum using a knife or machete contam- transverse cross-sections increases the chance inated between each cut by dipping into a of detecting X. c. pv. musacearum. Ssekiwoko bacterial suspension with an OD (optical den- et al. (2006) observed a larger number of sity) at 600nm adjusted to 0.5, which corre- plants to have X. c. pv. musacearum bacteria in sponds to 1.0 × 108 cfu (colony forming the Mangin layer (cambium ring in the corm) units)/ml. The plants were subjected to two than in the corm’s central cylinder or the cor- treatments: (i) cutting three leaves at the peti- tex layer. This is because X. c. pv. musacearum ole (de-leafing); or (ii) cutting one sucker at mainly infects the vascular system. The ground level (de-suckering). On the day of Mangin layer is a mass of vascular vessels/ inoculation, plant height from soil level to the bundles with a connection to the true stem, crossover of the leaf petioles of the most while the inner cylinder and cortex, in con- recently emerged leaf was measured in all trast, are largely a mass of starchy paren- test plants for both treatments. chyma (Stover and Simmonds, 1987). Thus, The 12-month-old plants (20 plants/ isolating transverse sections ensures that cultivar) were monitored for Xanthomonas the vascular vessels that are mainly infected wilt incidence and incubation period during by X. c. pv. musacearum are represented in 13 months after inoculation (AI). Incidence for the sample for isolation. Samples of 10 ml of both treatments was recognized as yellowing the suspensions were plated on cellubiose and/or wilting of parent plant leaves. A two- cephalexin agar (Mwebaze et al., 2006) and sample (unpaired) t-test of the means of the incubated at 24°C for 72 h. The number of incubation periods with the plant heights as plants with X. c. pv. musacearum in the differ- a factor (replication) were computed using ent parts was recorded and expressed as a GenStat (11th edn) statistical software (VSN percentage of all the plants examined to International, 2008). A simple regression anal- determine the systemic spread of the disease. ysis of time from inoculation to symptom In an additional experiment, three leaves expression, as the response variable, against for each of 20 EAHB and 20 ‘Pisang Awak’ plant height, was conducted using the GenStat plants were inoculated by smearing a suspen- software, while MS Excel was used to draw sion of X. c. pv. musacearum using a small the simple linear regression graphs. paint brush through small cuts either in the Four mats per genotype from the leaf tip (10 plants/genotype) or leaf base 9.6-month-old plants were randomly sampled (10 plants/genotype) and symptom develop- at 3 day intervals for 60 days. The collected ment observed for a period of 5 months. Data plant parts were mat cord roots (5 cm long cord were collected on the incubation period and root sections cut 2 cm away from the corm), time from symptom expression to leaf death. parent plant and sucker corm (approximately The same GenStat software was used to per- 5 cm long portion, including the corm’s central form analysis of variance of these data, while cylinder, Mangin layer and cortex tissue) and means were separated using least signifi- parent plant pseudostem (cross-sectional sam- cance difference at P = 5%. ple of the leaf sheaths 45 cm above the soil). In the laboratory, the corm and root samples were carefully cleaned with tap water to remove 12.3 Results and Discussion soil, subsequently surface sterilized by soak- ing for 3 min in 5.3% NaOCl solution (diluted 12.3.1 Incidence of Xanthomonas wilt at a ratio of 1:5) and then rinsed five times with and incubation period in de-leafed and distilled sterile water. The leaf sheath samples de-suckered plants were surface sterilized by wiping with cotton wool soaked in 95% ethanol. Thirteen months after inoculation, 100% inci- Thin 1 mm thick (approximately 10 g) dence of Xanthomonas wilt was observed in transverse sections were then cut from the de-leafed EAHB plants and 91% incidence in inner portion of the samples, and the sections de-leafed ‘Pisang Awak’ plants. The incidence 104 W. Ocimati et al.

of the wilt was much less in de-suckered was explained by plant height. The regression plants: 35% in EAHB plants and 45% in ‘Pisang coefficient in ‘Pisang Awak’ was 0.06, with a Awak’. The plants with wilt showed the char- standard error of 0.07. The model predicts acteristic symptoms of leaf yellowing and wilt- an increase in disease incubation period of ing (Plate 8), starting in most plants with the 0.07 days with each 1 cm increase in plant tips of the youngest leaves. The incubation height in ‘Pisang Awak’ (Fig. 12.1b). These period in de-leafed plants of EAHB varied results suggest that the incubation period of from 38 to 162 days, and for ‘Pisang Awak’, the disease increased by approximately 2 h from 27 to 163 days. In de-suckered plants, for every 1 cm increase in plant height. The incubation period varied from 46 to 383 days mean incubation period for EAHB (59.0 days) in EAHB and from 70 to 217 days for ‘Pisang was significantly higher than for ‘Pisang Awak’. Incidence was lower and time to symp- Awak’ (43.1 days) (Test statistic t = 5.01 on tom expression was delayed in the de-suckered 26 d.f.; P < 0.001). The mean difference in incu- parent plants compared with the de-leafed bation period between EAHB and ‘Pisang plants. This could be related to the plant recy- Awak’ plants (95% confidence interval, CI) cling nutrients from the leaf sheaths of severed was 9.4–22.4 days for the same plant height. leaves in the de-leafed plants, whereas the decapitated sucker would withdraw nutrients from the parent plant in an attempt to recover. The predominant sap flows may therefore 12.3.2 The pattern of movement of assist or hinder the movement of the bacteria. X. c. pv. musacearum within a banana In addition, the dense corm tissue, especially mat after inoculation through de-leafing for the de-suckering treatment, may also be an and de-suckering obstacle to rapid movement of bacteria. A positive effect of plant height, although In de-leafed plants, bacteria could be detected non-significant, was observed on the length close to the ground in the cut leaf sheaths of of disease incubation for de-leafed plants the parent plant as early as 3 days after inocu- (Fig. 12.1). X. c. pv. musacearum mainly infects lation. Some 98% of plants sampled from the and spreads through the vascular tissue of 3rd to the 60th day had bacteria in the cut leaf banana plants (Ssekiwoko et al., 2006). So the sheaths of both genotypes (Table 12.1); bacte- observed effect of plant height on disease ria were isolated from the corms of 85% of incubation can be attributed to the time the ‘Pisang Awak’ plants sampled 12–60 days bacteria take to move from the point of inocu- after inoculation and 94% of EAHB plants lation in the cut leaf petiole down through the sampled 15–60 days after inoculation. At vascular vessels in the leaf sheath of the inoc- 24 days after inoculation, X. c. pv. musacearum ulated leaf, into the corm tissue, and finally had already colonized the attached suckers into other leaf sheaths that are connected to with incidences of over 84% recorded from the corm. No significant correlation (at P<0.05) 24 to 60 days after inoculation. was observed between Xanthomonas wilt In de-suckered plants, bacteria were incubation period (time to symptom expres- found in the parent plant corms of ‘Pisang sion in non-inoculated leaves) and plant Awak’ 18 days after inoculation and in EAHB height measured at inoculation in either 21 days after (Table 12.1). Over 72% of the EAHB or ‘Pisang Awak’ plants. The regres- plants sampled from the 21st day had the sion coefficient was 0.093, with a standard bacteria in the parent plant corms. Despite error of 0.074. Thus, the model predicts the high incidence of X. c. pv. musacearum in an increase in disease incubation period of corm tissues of both genotypes in both 0.093 days with each 1 cm increase in plant treatments, the attached cord roots had the height at inoculation for EAHB (Fig. 12.1a). lowest incidences. This could be the result of Only 11% of the variation in the incubation the inhibition of colonization by the corky period in EAHB was explained by plant nature of cord root tissues. height. In ‘Pisang Awak’, only 5.6% variation The spread of X. c. pv. musacearum in in the incubation period of Xanthomonas wilt banana mats was systemic, with the bacteria Xanthomonas campestris pv. musacearum in banana plants 105

(a) 90

80 y = 0.0928x + 43.126 R² = 0.1073 70

50 period (days) 40

Xanthomonas wilt incubation Xanthomonas wilt 30

20 100 120 140 160 180 200 220240 Plant height at inoculation (cm)

(b) 90

70 y = 0.059x + 33.165 60 R² = 0.0561

50 period (days) 40

Xanthomonas wilt incubation 30

20 100 120 140 160 180 200 220 Plant height at inoculation (cm)

Fig. 12.1. Simple linear regressions for incubation period of Xanthomonas wilt (days) against plant height (cm) at inoculation in (a) East African highland bananas (AAA-EA) and (b) ‘Pisang Awak’ (Musa AAB) plants. Plant height was measured from soil level to the crossover of the leaf petioles of the most recently emerged leaf. spreading to the entire mat from the point of largely a mass of starchy parenchyma, while infection in either the parent plant or the the Mangin layer is a mass of vascular bun- attached sucker. The speed of spread was dles (Stover and Simmonds, 1987). As such, markedly faster in the de-leafed than in the X. c. pv. musacearum does not seem to spread de-suckered treatments for both genotypes easily in the inner cylinder or the cortex (Table 12.1). This could be attributed to the (Ssekiwoko et al., 2006). predominant direction of sap flow and/or the These results show that in the de-leafed compact nature of the corm tissue that parent plant X. c. pv. musacearum would have the bacteria have to cross before colonizing crossed from the points of inoculation to the the other plant parts in de-suckered mats. The attached suckers in the mat by 24 days, while inner cylinder and the cortex of the corm are in the de-suckered plants the bacteria would 106 W. Ocimati et al.

Table 12.1. Speed of spread of Xanthomonas campestris pv. musacearum from infection point through different plant parts of 9.6-month-old parent plants and the attached lateral shoots following de-leafing (cutting the three oldest leaves) of parent plants or de-suckering (cutting one sucker at soil level) using a contaminated garden knife. T: time (days) after inoculation when X. c. pv. musacearum was first isolated from the plant part.

Cumulative percentage plants with X. c. pv. musacearum in plant part from time of first isolation (T) to 60 days

Days to first Treatment Plant part isolation (T) EAHB ‘Pisang Awak’

De-leafing of parent plants Leaf sheaths of parent 3 98 98 Corm of parent 12 0 85 Corm of parent 15 94 94 Cord roots of parent 30 23 52 Attached sucker 24 86 84 De-suckering of parent plants Inoculated sucker 6 95 95 Corm of parent 18 NCa 75 Corm of parent 21 72 NC Leaf sheaths of parent 27 80 96 Cord roots of parent 54 8 0 aNC, no samples collected at that time.

have crossed to the attached parent plant by the leaf base inoculation. However, the time 21 days. When contrasted with the time for from initial disease expression to complete symptom expression, it is noted that symp- leaf yellowing/wilting was significantly toms are expressed long after the bacteria lower (P < 0.001) in the leaf base inoculation have spread throughout the plant. This study treatments (5.5 days in EAHB and 5.8 days therefore suggests that dependency on the in ‘Pisang Awak’) than in the leaf tip inocula- observation of disease symptoms in plants tions (21.2 days in EAHB and 22.2 days in is not sufficient for the management of ‘Pisang Awak’) (Table 12.2). Yellowing and Xanthomonas wilt in banana and that disin- wilting progressed gradually from the leaf fection of tools and the roguing of diseased tips to the base in the leaf tip treatments mats are still the most effective methods for (Plate 9a), while it progressed uniformly in combating tool transmission of Xanthomonas the leaf base treatments (Plate 9b). This sug- wilt in farmers’ fields. For routine surveil- gests that the disease spreads faster in the lance, for example at village/district level, direction of the xylem flow, and could also the development and deployment of diag- partially explain the low and slow coloniza- nostic kits sensitive to latent infections is also tion of root tissues. recommended for the effective management of the disease. In the leaf tip and leaf base inoculation treatments, the disease incubation period 12.4 Conclusion and did not differ markedly either between or Recommendations within the two genotypes. In EAHB, it was 40.0 days for the leaf inoculation and This study confirms the role of contami- 39.0 days for the leaf base inoculation. In nated garden tools in the perpetuation of ‘Pisang Awak’, the times were 36.6 days for the problem of Xanthomonas wilt in farm- the leaf tip inoculation and 39.8 days for ers’ fields and also confirms the previous Xanthomonas campestris pv. musacearum in banana plants 107

Table 12.2. Disease incubation period and time from first appearance of leaf symptoms to complete leaf yellowing/wilting in Musa plants inoculated with Xanthomonas campestris pv. musacearum through the leaf tip or leaf base (petiole) in East African highland banana (EAHB) and ‘Pisang Awak’ plants.

Time from first sight of leaf symptom to complete leaf Incubation period wilting (days)

Treatment AAA-EA ‘Pisang Awak’ AAA-EA ‘Pisang Awak’

Leaf tip inoculation 40.0 36.6 21.2 22.2 Leaf base inoculation 39.0 39.8 5.5 5.8 CV (%) 28.7 27.2 LSD (5%) 9.9NS 3.5***

NSNot significantly different at P < 0.05; ***Significantly different at P < 0.001. research findings by Addis et al. (2010). Acknowledgements Thus, tools should be sterilized before and after use, especially where Xanthomonas The authors gratefully acknowledge the wilt has been reported to occur. The study Directorate General for Development, Belgium demonstrates the systemic spread of for funding this study through the CIALCA Xanthomonas wilt within banana mats from (Consortium for Improving Agriculture-based the point of infection in either the parent Livelihoods in Central Africa) project. The plant or attached sucker to the entire mat. authors also thank the National Forests It is also evident that, by the time symptoms Resources Research Institute (NaFORRI) of the appear, the disease has already spread National Agricultural Research Organisation throughout the entire mat. As such, the (NARO), Uganda for providing the secluded management of tool infections cannot rely land for the artificial inoculation experiments on the expression of disease symptoms. at Kifu Forest, Mukono District. Also grate- Consequently, it is recommended that fully acknowledged are the contributions of mats of vegetative-stage plants with leaf Mr Mujuni Denis who ably coordinated wilting/yellowing symptoms be completely between this project (Bioversity/CIALCA) uprooted. The deployment of diagnostic and NaFORRI, Mr Frank Turyagenda who kits sensitive to latent infections for routine established the experiments in 2008 and surveillance at, e.g. the village/district Mr Richard Akope (RIP) (NAFORRI) and level, is also recommended for the effective Mr John Nkeza who assisted in field manage- management of the disease. ment and data collection.

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I. Ramathani and F. Beed* International Institute of Tropical Agriculture (IITA), Kampala, Uganda

Abstract Banana Xanthomonas wilt, caused by the bacterium Xanthomonas campestris pv. musacearum, and banana bunchy top virus disease (BBTD), caused by the banana bunchy top virus (BBTV), are two of the most devastating diseases of banana in East and Central Africa, and cause significant losses in food security and income for millions of farmers, traders and consumers. To prevent the establishment and spread of the diseases across the region, control interventions must be rapidly deployed. A first and critical step towards deployment of appropriate disease management strategies is the rapid and precise diagnosis of the causal agent of disease. The diagnosis of Xanthomonas wilt in the field based on disease symptoms is often confused with another disease that causes wilting that is due to the fungus Fusarium oxysporum f.sp. cubense, so diagnostic tools that are easy to use, cost-effective and reliable are required to help field workers. BBTD symptoms can also be confused with nutrient deficiencies or varietal differences. To this end, three types of portable kits were evaluated for their performance in capturing pathogen DNA from the field for use in precise, molecular-based pathogen diagnostics under controlled laboratory conditions. All three prototypes tested – FTA cards, the PhytoPASS kit and two-minute DNA extraction dipsticks – gave excellent results and methods were optimized for sample collection in the field, DNA extraction and PCR- based diagnostics for X. campestris pv. musacearum and BBTV. The benefits of using DNA capture kits included: collection of pathogen DNA in a cheap and practical manner, safe and fast transfer of high- integrity pathogen DNA across country borders, rapid and precise diagnosis using state-of-the-art molecular technologies and direct comparison of results from geographically diverse samples. This is possible because analysis is performed in a uniform manner in terms of method, date, equipment, reagents and technical staff. Technical support was provided to workers in the field to help them differentiate symptoms based on diagnostic results from laboratory analyses; such support could also be provided to regulatory officials at borders to ensure that, for example, planting material is free from disease. Countries involved in testing the DNA capture kits for X. campestris pv. musacearum included Burundi, Democratic Republic of Congo (DR Congo), Kenya, Rwanda, Tanzania and Uganda. The same countries, with Zambia also included, were also tested for BBTV. While no positive results for X. campestris pv. musacearum were obtained from samples originating from surveys in Burundi, subsequent DNA capture kits from samples from Bubanza and Cankuzo provinces did test positive, thus confirming an outbreak of Xanthomonas wilt in this country. BBTV was confirmed in DR Congo, Burundi, Rwanda and Zambia.

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 109 110 I. Ramathani and F. Beed

13.1 Introduction primers and PCR are being employed (López et al., 2009). Banana Xanthomonas wilt (BXW), caused by PCR, with all its variants, is currently a the bacterium Xanthomonas campestris pv. basic tool in diagnosis. It relies on the musacearum, and banana bunchy top disease amplification of pathogen-specific fragments (BBTD), caused by the banana bunchy top virus of DNA or RNA and may be used alone or, (BBTV), are among the most devastating preferably, in combination with other techniques. diseases of banana afflicting sub-Saharan Africa Compared with other techniques such as (SSA). For example, in Uganda, by 2006, it was ELISA (reviewed in Chapter 11), PCR offers estimated that if Xanthomonas wilt was not quick results with the greatest level of accuracy controlled, the country stood to lose an estimated and requires minimum resources, as a single US$295 million worth of banana output, valued fragment of DNA can provide evidence of a at farm gate prices, which is equivalent to an pathogen. There are also many variants of PCR, annual US$200 of food and income per with each new form giving a better degree of household (Kalyebara et al., 2006), while in accuracy and a better understanding of the Malawi, 40% of national banana production is population dynamics of the pathogen under lost to BBTD (FAO, 2011). Presently, diagnoses of study in the ecosystem. PCR gives a clear-cut banana diseases across SSA are based upon deduction of the causal agent, and most recognition of symptoms in the field. However, especially when using gene-specific primers this is not straightforward, as symptoms can be that target the presence of specific DNA confused; for example, Xanthomonas wilt has fragments (Chandler and Jarrell, 2005). similarities with other bacterial wilts of banana To address the need for high-integrity caused by Ralstonia (Pseudomonas) solanacearum, DNA for PCR diagnostics, simple DNA cap- including Moko, blood and Bugtok diseases ture kits were tested for their suitability to (Thwaites et al., 2000). capture pathogen DNA from diseased plants Once a pathogen has become established, in the field for subsequent analysis in the labo- disease control is very difficult and eradica- ratory. The novel DNA capture kits tested tion impossible (Eden-Green, 2004). Thus, included the commercial Whatman FTA cards prevention is essential to avoid the dissemina- and PhytoPASS kit, and two-minute extraction of the pathogen by different means, such tion dipsticks (Plate 10). as contaminated propagative plant material, The FTA card method was developed for vectors, irrigation water and soil (De Boer the collection and storage of biological materi- et al., 2007). Also, preventive measures de- als using a solid matrix. It was first described mand highly sensitive, specific and reliable for blood samples for diagnostics (Guthrie and pathogen detection methods, as many phyto- Susi, 1963), and later for PCR for medical and pathogenic organisms can remain latent in forensic applications (Carducci et al., 1992). ‘subclinical infections’, and/or in low num- The card is named after Flinders Technology bers, and/or in some special physiological Associates (Whatman International Ltd, states in propagative plant material and in Maidstone, Kent, UK) and offers a simple tech- other reservoirs (López et al., 2009). nology that simplifies the steps of DNA collec- Diagnosis of the disease-causing organism tion, transportation, purification and storage; is the first and critical step towards appropriate consequently, it reduces the cost and time disease management. The proper diagnosis of required to process DNA to the final step of the causative pathogen is crucial for any inte- purified DNA ready for downstream applica- grated pest management (IPM) strategy as the tion. FTA cards are impregnated with chemi- risk of disease/inoculum spread necessitates a cals that allow for the breakdown of the cell reduction in levels of pathogen inoculum that wall, and thus immobilize the DNA within the do not cause economic damage. Bearing this in matrix without interfering with its integrity, mind, there is need for rapid and more efficient (Mbogori et al., 2006). The chemicals are safe tools that enable diagnosis of pathogens with to handle and are environmentally friendly. minimum resources. Presently, molecular tech- Hence, the FTA card technology enables sam- niques mediated through the use of specific pling in remote areas without the need for DNA Capture Kits to Collect Xanthomonas campestris pv. musacearum 111

complicated equipment to maintain DNA Democratic Republic of Congo (DR Congo), integrity. Furthermore, it allows for any num- Burundi, Kenya, Tanzania, Rwanda, Uganda ber of samples to be collected as there is no and Zambia, and tested in the laboratory for need to rush back to the lab as the DNA that DNA fragments of X. campestris pv. musacearum has already been collected is kept stable at and BBTV. Beforehand, a training workshop room temperature. Recent studies have shown was organized in Uganda for scientists from that use of FTA cards maintains DNA integrity the respective countries on the utilization of for over 14 years, as successful PCR amplifica- these kits in the field and in the laboratory. tion has been carried out using FTA cards that In actual practice, PhytoPASS kits were only have been stored for this period (Mbogori employed in Uganda and Zambia, while two- et al., 2006). minute DNA dipstick and FTA cards were PhytoPASS (DNAlis sprl, Gembloux, employed in all seven countries. Belgium) is another sampling kit that has a cas- Fields suspected of having plants infected ing containing a sampling strip carrying a sam- with Xanthomonas wilt were targeted, and pling membrane. These are easy to handle and samples of different plant parts (cut pseudo not need refrigeration. This kit has been dostem, rachis, peduncle or male bud) were employed in the collection of begomoviruses imprinted into each kit. To imprint samples from cassava (Busogoro et al., 2008) and in the on FTA cards, a portion of the plant material collection of BBTV (Busogoro et al., 2007). was rolled and pressed hard on to the FTA The third kit addressed in this study is card matrix for about 5 min until the sap the two-minute DNA dipstick developed by penetrated. For two-minute nucleic acid Forsite Technology with the UK Food and extraction dipsticks, a plant sample was cut Environmental Research Agency (FERA, into smaller pieces (0.5 cm2) and dropped Sand Hutton, York, North Yorkshire); this is into a bottle containing the extraction buffer based on immunochromatic (serological) and steel balls to increase sample degrada- strips akin to the lateral flow devices (LFDs) tion when agitated vigorously for 1 min. used, for example, for pregnancy tests and for Extraction dipsticks, with their glass fibre specific pathogen families and even species. release pad section facing downwards, were A small piece of the LFD membrane can be dipped into the sample bottle and allowed used directly in the PCR reaction without fur- to stand for 2 min, followed by brief air dry- ther purification steps. Two-minute nucleic ing before storing. For the PhytoPASS kits, acid extraction dipsticks have been used in the sampling strip was rubbed across sam- the rapid detection of Phytophthora ramorum ples of plant material transversely over the and P. kernoviae (Tomlinson et al., 2007, 2009). fibres for about 10–20 s. The sampling membrane was left to air dry for 30 s and then the kit was closed without touching the sampling surface. 13.2 Materials and Methods

13.2.1 Source of plant samples 13.2.2 Preparation of samples and sampling methods for PCR detection

Samples were collected from plants symp- For the FTA card, the method described by tomatic of Xanthomonas wilt and BBTD, from Dellaporta et al. (1983) and Rowhani et al. plants suspected to have these diseases, and (2000) was adopted to prepare the samples for from asymptomatic plants (i.e. plants sus- PCR. About 1–3 ml of the contents were tested pected to be healthy) using the three DNA cap- as the DNA template in the PCR reaction. For ture kits described in Section 13.1: two-minute the two-minute nucleic acid extraction dip- nucleic acid extraction dipsticks, FTA cards sticks, a 2.0 mm punch was used to obtain a and the PhytoPASS kit. The collections were single disc from the DNA membrane, which made from targeted survey areas in collabor- was then placed in a PCR tube containing the ation with national research organizations in master mix, followed by placing within the 112 I. Ramathani and F. Beed

thermocycler. PhytoPASS kit samples were (Tris-acetate-EDTA) buffer) under a constant prepared according to the method described current of 100 V, running in 1× TAE buffer. by Busogoro et al. (2009). These migrations were followed by visualiza- tion of the amplified bands under UV light using a UV Transilluminator and photo- graphed with Fujifilm instant black and white 13.2.3 Molecular detection of professional film. X. campestris pv. musacearum and BBTV

The detection of X. campestris pv. musacearum 13.3 Results was performed based on the optimized conditions described by Adikini et al. (2011) using In subsequent PCR tests on a subset of FTA X. campestris pv. musacearum-38F (5′CCGCCGG card, PhytoPASS and two-minute DNA TCGCAA TGTGGGTAAT3′) and X. campestris pv. dipstick samples for X. campestris pv. musacearum musacearum-38R (5′CAGCGGCGCCGGTGT and BBTV, amplification with the conventional ATTGAGTG3′) primer pairs. A 20 ml volume PCR primers yielded the expected PCR containing 1× reaction buffer (50 mM KCl, 10 products of 650 and 239 bp (Plates 11 and 12). mM Tris-HCl pH 8.3), 1.5 mM MgCl2, dNTPs (Promega) at 0.25 mM, 0.5 pmol of each primer and 1.0 U of Taq DNA polymerase (Eppendorf) was placed in a thermocycler with the DNA 13.3.1 Detection of X. campestris pv. template. Thermocycler parameters were set musacearum and BBTV across at an initial denaturation of 94°C for 5 min, East and Central Africa followed by 40 cycles of 94°C for 20 s, 60°C for 20 s and 72°C for 1 min, with a final extension Over 50% of all symptomatic samples collected step of 72°C for 10 min. using the kits tested positive for X. campestris The detection of BBTV was based on pv. musacearum and over 87% for BBTV DNA standard protocols developed by Kumar fragments. Further, the DNA capture kits were (Kumar, Ibadan, 2009, personal communi- able to detect X. campestris pv. musacearum/ cation) using two primer pairs: pair 1 for BBTV pathogen DNA among suspected sam- detecting the BBTV fragments BBTV1 ples as well as among those considered to be (5′GCGTGAAACGCACAAAAGGCC3′) and healthy. A smaller percentage (<20%) of sus- BBTV2 (5′GCATACGTTGTCAAACCTTCTC pected samples for X. campestris pv. musacearum CTC3′), and pair 2 for detecting the banana and BBTV tested positive for the respective genome BrepF (5′GATTTTGTAGATTTTGGA DNA fragments. Among the samples consid- CACCG3′) and BrepR (5′GAATAACAAA ered to be healthy, less than 37% of the samples TATGCTCCAATACCC3′) in a multiplex for X.campestris pv. musacearum and BBTV tested PCR. A 25 ml volume containing 1× reaction positive for X. campestris pv. musacearum and buffer (50 mM KCl, 10 mM Tris-HCl pH 8.3), BBTV DNA fragments (Table 13.1). Based on the

4.8 mM MgCl2, dNTPs (Promega) at 0.2 mM, laboratory results, X. campestris pv. musacearum 0.2 mM of each of the two sets of primers and was confirmed to occur in all countries tested 0.6 U of Taq DNA polymerase was used. PCR except Zambia. Initially, samples collected parameters were set at an initial denaturation from Burundi in 2010 did not test positive for temperature of 94°C for 5 min, followed by X. campestris pv. musacearum, but subsequent 35 cycles of 94°C for 45 s, 53°C for 30 s and 72°C samples collected from Bubanza and Cankuzo for 30 s, with a final extension step of 72°C provinces early in 2011 on two-minute DNA dip- for 5 min. Positive controls for BBTV detection sticks did test positive. No positive cases of were obtained from BBTV plasmid DNA. BBTV were identified in Uganda, Kenya or The PCR products for both pathogens Tanzania, although it was established by this were separated by electrophoresis in a 1.5% study that samples collected from Kamanyola, agarose gel containing ethidium bromide Nyangezi and Butembo in DR Congo, close (l g/10 ml or 5 ml of ethidium/100 ml of TAE to the Uganda border, as well as from DNA Capture Kits to Collect Xanthomonas campestris pv. musacearum 113

Table 13.1. Number of samples collected for each of the three DNA capture kits for Xanthomonas campestris pv. musacearum and banana bunchy top virus (BBTV) and positive results (+ve) after molecular diagnosis using conventional PCR for samples collected across East and Central Africa.

2-minute dipsticks FTA cards PhytoPASS kit

Nature of No. samples Tested No. samples Tested No. samples Tested Pathogen sample collected +ve (%) collected +ve (%) collected +ve (%)

Xanthomonas Symptomatic 172 59 159 60 28 93 campestris pv. Suspected 142 18 130 5 0 0 musacearum Healthy 62 37 30 20 13 0 Total 376 40 319 34 41 63

Banana bunchy Symptomatic 99 97 100 87 45 100 top virus (BBTV) Suspected 17 6 8 0 0 0 Healthy 44 0 42 0 45 22 Total 160 61 150 58 90 61

Makamba in Burundi, close to the Tanzania (22%) of samples considered to be healthy and border, were infected with BBTV (Plate 13). sampled using the PhytoPASS kit tested posi- Samples were further tested after being tive for BBTV when compared with a positive stored at room temperature and were found control (BBTV plasmid DNA). This could be to retain pathogen DNA integrity after attributed to latent infection that is not easily 6 months on all three prototype kits, though noticed in the field but can be detected by they declined thereafter, especially for the PCR. Differences in rates of detection for Xan two-minute extraction dipsticks. and BBTV between the three different capture methods have been correlated with symptoms in the field by revisiting those plants from which samples were collected, and will be 13.4 Discussion reported in detail elsewhere. In general, all three DNA sampling kits The aim of this study was to test the potential demonstrated their usefulness in capturing of three simple DNA capture kits for the collec- crude X. campestris pv. musacearum and BBTV tion of X. campestris pv. musacearum and BBTV DNA that could be used for diagnosis and pathogen DNA across targeted survey areas in can therefore be applied in epidemiological East and Central Africa. The results showed studies. This is important, particularly in that all three prototype kits are able to capture endemic areas for both pathogens, as speci- DNA of both of the pathogens from fresh dis- mens suspected to contain either could easily ease samples taken directly in the field. be stored and amplified at any time. The kits Molecular detection by PCR showed that have proved to be simple to use in the field more than 50% of all symptomatic samples and also provided a rapid means of diagnosis and less than 20% among suspected samples using crude DNA, which is contrary to tested positive for X. campestris pv. musacearum. accepted protocols, which require purification Interestingly, a higher proportion of healthy of DNA before PCR amplification (Su et al., samples (20% for FTA cards and 37% for two- 2003) and liquid nitrogen for grinding plant minute DNA dipsticks) than suspected sam- tissue (Furuya et al., 2005). Furthermore, the ples also tested positive for X. campestris pv. greater sensitivity of the kits reported here musacearum. Among the BBTV samples, over means that information can be obtained 80% of all symptomatic samples collected from field samples that have relatively using the three kits tested positive for BBTV, small amounts of bacterial or viral DNA, as as did a few (<10 %) among the suspected observed from the suspected or asympto- samples. It was noted that a high percentage matic samples collected in the field. 114 I. Ramathani and F. Beed

The results presented here are the first and BBTV DNA from both symptomatic and reporting a comparative study of the use of asymptomatic plant samples. DNA capture kits for a viral and a bacterial pathogen, and demonstrate the potential of the kits for wide-scale deployment in sub- Saharan Africa. The kits provide several bene- Acknowledgements fits: they provide an easy means of collection of pathogen DNA directly from the field; they Thanks are owed to the Association for are safe and permit the fast transfer of high- Strengthening Agricultural Research in East integrity pathogen DNA across country bor- and Central Africa (ASARECA); the Food ders, thus obviating the need to comply with and Agriculture Organization of the United time-consuming, bureaucratic and costly sani- Nations (FAO) and the International Plant tary and phytosanitary regulations; they pro- Diagnostic Network - Integrated Pest Manage- vide rapid and precise diagnosis using ment Collaboration Research Support Program molecular methods under laboratory condi- (IPDN-IPM) for funding and guidance; and tions, as well as allowing the direct comparison to key national collaborators: National Agri- of results from geographically diverse samples, cultural Research Organisation (NARO), Uganda; as the analyses use the same diagnostic method Kenya Agricultural Research Institute (KARI) and can be performed on the same date; in and Kenya Plant Health Inspectorate Services addition, they facilitate regional linkages for (KEPHIS); Université Catholique du Graben disease surveillance through sharing and mov- (UCG), Democratic Republic of Congo; the ing samples across borders among research Ministry of Agriculture, Food Security and institutes. Furthermore, the three prototypes Co-operatives (MAFSC) and the Agricultural retained the integrity of both bacterial and Research Institute (ARI), Uyole, of Tanzania; viral DNA after 6 months – far longer than the Institut des Sciences Agronomiques du 4 months reported by Busogoro et al. (2009) when Burundi (ISABU); Institut des Sciences testing the PhytoPASS kit for BBTV detection. Agronomiques du Rwanda (ISAR) and the In conclusion, we have demonstrated that Rwanda Agricultural Development Authority the two-minute DNA test dipstick, the (RADA) – now both part of the Rwanda PhytoPASS kit and Whatman FTA cards can be Agricultural Board (RAB); and the Zambia used to capture X. campestris pv. musacearum Agricultural Research Institute (ZARI).

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A. Rutikanga,1* C. Sivirihauma,2 C. Murekezi,3 U. Anuarite,3 V. Ndungo,4 W. Ocimati,5 J. Ntamwira,6 P. Lepoint7 and G. Blomme5 1Bioversity International, Kigali, Rwanda and Higher Institute for Agriculture and Animal Husbandry (ISAE), Rwanda; 2Bioversity International, Butembo, Democratic Republic of Congo; 3Rwanda Agriculture Board (RAB), Kigali, Rwanda; 4Université Catholique du Graben (UCG), Butembo, Democratic Republic of Congo; 5Bioversity International, Kampala, Uganda; 6Institut National pour l’Etude et la Recherche Agronomique (INERA), Mulungu Research Station, Bukavu, Democratic Republic of Congo; 7Bioversity International, Bujumbura, Burundi

Abstract Xanthomonas campestris pv. musacearum is a bacterium that causes Xanthomonas wilt of banana. It mainly spreads through contaminated garden tools, infected planting materials and insect vectors. Following infection, the bacterium spreads systemically throughout the plant, including the lateral shoots. Cultural practices are the only available management option for controlling the disease. Researcher-led and farmer- implemented experiments were established in Rwanda and eastern Democratic Republic of Congo (DR Congo) to assess the effectiveness of selective uprooting of diseased mats combined with early male bud removal and the prohibition of the use of garden tools for routine field maintenance. Three farmers’ fields, corresponding to initial Xanthomonas wilt incidence levels of 14–29%, 30–35% and 42–45% (proportion of mats with symptoms), were selected in each of four sectors in Rubavu District, western Rwanda, while in North Kivu, eastern DR Congo, two fields were selected with disease levels of 14–29% and 42–45%. Banana plants were monitored on a monthly basis for disease symptoms in both treated and adjacent control plots (with no management of Xanthomonas wilt) for 10 months. A separate experiment in South Kivu, DR Congo, compared the effect of removal of the whole mat with removal of single plants on the expression of the disease. In Rwanda, seven out of 12 farmers attempted to rigorously apply the recommended control options and this increased the proportion of visibly healthy plants fivefold (from 7% to 35%). In DR Congo, when the initial disease level was 14–29%, after 10 months of treatment 57% of plants were visibly healthy compared with only 15% in non-treated plots. At an initial disease level of 42–45%, 32% of plants were visibly healthy after 10 months of treatment compared with only 9% in non-treated plots.

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 116 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Banana Xanthomonas Wilt Management 117

A significantly higher number (57%) of visibly healthy plants was recorded under conditions of low initial disease incidence (14–29%) in DR Congo, while in Rwanda a higher number of asymptomatic plants occurred in plots where farmers attempted to adhere to the recommended management options for Xanthomonas wilt. Although selective uprooting under conditions of low initial infection, in combination with the rigorous application of management options that reduce disease transmission, resulted in a higher number of visibly healthy plants (35% in Rwanda and 57% in eastern DR Congo), farmers reported that new infections were still observed after the experimental period. We are thus inclined to recommend the complete removal of diseased fields and subsequent fallowing/establishment of break crops when disease incidence is above 14%. The experiment in South Kivu indicated that complete mat or single plant removal does not lead to the quick removal of the disease from a field in a small-scale farming context.

14.1 Introduction tools (Eden-Green, 2006; Addis et al., 2010) and by insect species, mainly stingless bees, Xanthomonas wilt of banana is a bacterial fruit flies and grass flies (Tinzaara et al., disease caused by Xanthomonas campestris 2006). Following flower infection, the bacte- pv. musacearum that currently occurs only in rium spreads in a systemic manner through- Africa. It was initially observed in Ethiopia out the plant and physically attached lateral in the 1930s (Castellani, 1939) and con- shoots (Ssekiwoko et al., 2006). In the ‘Pisang firmed by Yirgou and Bradbury (1968, Awak’ (Musa spp. ABB) cultivar, cutting 1974). The disease was first observed in down parent plants at the male bud wilting central Uganda in 2001 (Tushemereirwe stage (i.e. symptom stage one after insect et al., 2003, 2004; Karamura et al., 2006). In vector transmission) may stop the bacteria the same year, farmers also reported it on a from reaching the corm and eventually mov- few plants at Bwere Hill, in the Bashali ing into the lateral shoots (suckers) Mokoto collective in Masisi Territory, 72 km (Ssekiwoko et al., 2010). In plants of the north-west of Goma in North Kivu Province ‘Matooke’ (AAA-EA) cultivar though, the in the Democratic Republic of Congo bacteria seem to move faster, making this (DR Congo) (Ndungo et al., 2004, 2006). In method less effective. Therefore, it has been Rwanda, the disease was officially recorded recommended that whole mats should be in three sectors (Cyanzarwe, Gisenyi and completely uprooted or killed by herbicides Kanama) in the northern part of the country in cases where ‘Pisang Awak’ parent plants in June 2005, although farmer reports show inflorescence symptoms beyond stage suggest that the disease may have been one (male bud wilting), and at all symptom present as early as 2002 around Gisenyi in stages for the inflorescence in ‘Matooke’ northern Rwanda (Reeder et al., 2007) where (Ssekiwoko et al., 2010). bananas are extensively grown on the hills All screened banana and plantain overlooking Lake Kivu. The disease may cultivars are susceptible to the disease have spread from DR Congo when (Welde-Michael et al., 2006; Tripathi et al., Congolese people fled to the former 2008). In addition, Musa ABB genome types Ruhengeri and Gisenyi provinces of Rwanda are highly susceptible to insect vector trans- following the eruption of the volcano mission (Shimelash et al., 2008) with 70% Nyiragongo in January 2002. In addition, devastation of ‘Pisang Awak’ fields observed there is a daily movement of people and in central Uganda (Karamura et al., 2006). goods across the Rwanda–DR Congo border. In Rwanda, in the early years of the epidemic, In all countries affected by Xanthomonas the highest Xanthomonas wilt incidence wilt of banana, studies have been conducted (86%) was recorded in Rubavu District in a bid to understand disease transmission (Nakato and Muhinyuza, 2007). Similarly, in and epidemiology and to draw up recom- eastern DR Congo, Xanthomonas wilt has mendations for its management. It is now been severely damaging banana plantations established that the wilt is mainly transmit- since its appearance in 2001 (Ndungo et al., ted through the use of contaminated garden 2004, 2006). 118 A. Rutikanga et al.

Cultural practices (e.g. early de-budding of plants in the population that show using a forked wooden stick, uprooting of symptoms), were selected in each of four diseased mats and disinfection of metal sectors (Cyanzarwe, Rugerero, Rubavu and garden tools) are the only recommended Nyamyumba) in Rubavu District, Rwanda. management options for controlling the dis- In parallel, two fields were selected for disease (Blomme et al., 2005a, 2005b; Brandt ease incidence levels 14–29% and 42–45% in et al., 1997). However, knowledge is lacking Kisungu, DR Congo. In both countries, the fol- of the level of disease incidence that war- lowing Xanthomonas wilt control package was rants complete removal/uprooting of a field evaluated, as well as the degree of adherence as opposed to selective uprooting of infected to it: continuous and selective uprooting of dis- plants/mats. (In this context, it should be eased mats (a mat containing at least one symp- noted that a ‘plant’ is a component of a mat tomatic plant was considered to be infected) in and may include parents or suckers, each of combination with early male bud removal which may be selectively removed, leaving using a forked stick; prohibition of the use of the mat to produce further ‘plants’ or garden tools for activities such as de-leafing, de- shoots.) In order to investigate the appropri- trashing, de-suckering and weeding; no inter- ate approach, researcher-led and farmer- cropping; and prevention of browsing animals implemented experiments were established from entering the experimental area. Monthly in western Rwanda and eastern DR Congo monitoring of banana fields for disease symp- to assess the effectiveness of selective plant/ toms in both treated plots and adjacent control mat uprooting in combination with cultural plots (with no management of Xanthomonas control options in relation to different levels wilt) was conducted for 10 months. of initial disease incidence. In addition, a second experiment was conducted at a site close to the Institut National des Etudes et de la Recherche Agricole (INERA), Mulungu Research Station 14.2 Materials and Methods in South Kivu, eastern DR Congo, to assess the effect of selective uprooting of either sin- On-farm experiments were established in gle diseased plants or complete mats. Three Rubavu District, Western Province, Rwanda plots, each containing 100 mats, were selected and in Kisungu locality, North Kivu, eastern in February 2011 for each of the following DR Congo. Rubavu District is located at an initial disease incidence ranges: 7–10%, average altitude of 1600 m above sea level 11–14% and 21–38%. Complete diseased mats (masl), at latitude 1°41¢20¢¢S and longitude (containing at least one diseased plant) were 29°17¢33¢¢E. The average annual temperature uprooted in the plots with 21–38% disease is 21°C, and the annual rainfall ranges from incidence, while single diseased plants with 1200 to 1350 mm, distributed over two rainy their corms were removed in the plots with seasons (September–December and February– 11–14% disease incidence and single diseased April). A highly fertile, volcanic-derived soil plants were cut off at ground level in the (Andosol) is dominant in Rubavu (FAO, 1998). plots with 7–10% disease incidence. The In contrast, Kisungu is located at latitude removal of single diseased plants is not only 00°14¢38¢¢N and longitude 029°15¢05¢¢E, and less demanding of labour, it is also far more the altitude ranges from 1670 to 1750 masl. easily accepted by farmers, who will not be The average annual temperature is 19°C inclined to remove a complete mat when only and annual rainfall ranges from 1300 to one plant is visibly infected. The experiment 1800 mm, distributed over two rainy seasons was conducted for a period of 17 months, (September–December and March–June). The during which all diseased mats or single soil is clayey, well drained and with uniformly plants were continuously removed. Legume distributed organic matter. intercropping was practised during the rainy Three farmers’ fields, corresponding to seasons (i.e. February–May and September– initial Xanthomonas wilt incidence levels of December) and free-ranging small ruminants 14–29%, 30–35% and 42–45% (the proportion were omnipresent at the experimental sites. Banana Xanthomonas Wilt Management 119

14.3 Results and Discussion 12 farmers rigorously applied the recommended management options and, on average, In Rwanda, the level of compliance with the 35% of these mats remained visibly healthy in recommended package for managing the dis- the treated plots versus a meagre 7% in the ease varied across farms. Seven out of the adjacent control plots (Tables 14.1 and 14.2).

Table 14.1. Effect of management of Xanthomonas wilt of bananas in western Rwanda on the proportion of mats showing symptoms at 1 and 10 months after the experiment began in relation to initial disease level and the adherence of farmers to the cultural practices required to manage the disease. Also shown is the time required for all mats to show symptoms, and the proportion of mats remaining free of symptoms at the end of the experiment (10 months).

Xanthomonas management applied Control – no treatment Months from start 1 10 10 1 10 10

Months for Initial Months for all Free of all mats to Free of disease mats to show symptoms show symptoms level (%) Symptoms (%) symptoms (%) Symptoms (%) symptoms (%)

Farmers who adhered to the cultural practices 14–29 22 68 >10 32 1 81 >10 19 14–29 28 66 >10 33 10 90 >10 10 30–35 30 65 >10 35 48 100 4 0 30–35 30 54 >10 46 4 100 9 0 30–35 35 64 >10 36 20 100 8 0 42–45 42 67 >10 33 46 100 4 0 42–45 42 68 >10 32 4 79 >10 21 Mean 35 7 Farmers who did not completely adhere to the cultural practices 14–29 14 100 5 0 93 100 4 0 14–29 21 100 7 0 5 100 7 0 30–35 33 100 6 0 50 100 5 0 42–45 42 100 6 0 80 100 5 0 42–45 45 100 10 0 40 100 8 0 Mean 7 0 6 0

Table 14.2. Effect of adherence to cultural practices for managing Xanthomonas wilt in bananas on the proportion (%) of plants without symptoms over the 10 month period during which the management techniques were applied in western Rwanda. Means followed by the same letter in a column are not significantly different; ***, significant at P < 0.001.

Time after start of treatment (months) Adherence to cultural practices 12345678910

Yes 67.2a 64.3a 60.3a 56.3a 52.7a 48.9a 45.5a 40.1a 37.8a 35.3a Not completely 69.1a 60.9a 51.5a 37.8b 17.5b 11.5b 4.3b 3.6b 2.5b 0.0b LSD 13.4 14.2 13.6 15.5 13.3 15.5 11.2 8.9 6.7 4.8 Probability 0.77 0.60 0.18 0.02 *** *** *** *** *** *** 120 A. Rutikanga et al.

All mats became infected during the A significantly higher proportion of 10 month treatment period for farmers who visibly healthy plants were recorded in the did not completely adhere to the recom- treated plots in North Kivu, DR Congo mended control package (Tables 14.1 and (Fig. 14.1) compared with those in Rwanda 14.2). Indeed, in their control plots, on average, (Tables 14.1 and 14.2). This difference is all plants showed symptoms by 6 months, attributed to the non-adherence to the full and partial adherence only extended this by control package by a large proportion of the another month (Table 14.1). Hence, the results farmers in Rwanda. showed that maintaining a relatively higher In the second experiment, in South percentage of banana mats in a visibly healthy Kivu, despite the continuous and complete state after 10 months can only be achieved removal of diseased mats in the plots through adherence to the complete control with the highest initial disease incidence package that was advocated (Tables 14.2 (21–38%) over 17 months, the increase in the and 14.3). percentage of new diseased mats was nearly Early detection and destruction of dis- double that in the plots with the lowest eased mats is a key step in preventing dis- initial disease incidence (7–10% plots), ease spread (Blomme et al., 2005b; Karamura which were treated by cutting off single et al., 2005). The farmers who adhered to the diseased plants at ground level (Table 14.4). treatment package regularly used a forked Nevertheless, an additional 30% of mats stick to remove male buds, thus reducing became infected in the 7–10% plots during the incidence of insect vector transmission. the experiment (Table 14.4). The differences De-budding carried out as soon as the last in the percentages of diseased mats in the hand of the bunch appears prevents flower three treatments were significant (P < 0.05) infection and results in bigger, more evenly at the beginning of the experiment, but filled fruits (Blomme et al., 2005a). In highly significant (P < 0.01) after 17 months, DR Congo, all farmers adhered to the rec- suggesting a possible positive effect of the ommended Xanthomonas wilt manage- cultural practices on the incidence of the disease ment package. Consequently, at an initial (Table 14.4). The movement of the disease disease incidence of 14–29% a higher per- within the mats was reflected in the number centage (57%) of visibly healthy plants of mats that had more than one diseased remained in the treated plots compared plant. An average of 15 mats had more than with the adjacent control plots (15%). When one diseased plant in the 11–14% plots and the initial disease incidence was higher an average of ten mats in the 7–10% plots. (42–45%), then 32% of plants were visibly The interval between consecutive infections healthy compared with 9% in the control on a mat was on average around 2 months plots (Fig. 14.1). (Table 14.4).

Table 14.3. Proportion of asymptomatic mats (%) in treated plots in western Rwanda according to initial incidence level (%) of Xanthomonas wilt in bananas. Means followed by the same letter in a column are not significantly different from each other, according to Tukey’s HSD test (P < 0.05).

Time after start of treatment (months) Initial disease incidence 12345678910

14–29 79a 74a 66a 59a 38a 35a 23a 20a 19a 16a 30–35 68b 63b 57ab 48a 41a 35a 33a 32a 31a 29a 42–45 57c 52c 48b 41a 35a 30a 29a 23a 20a 16a LSD (P = 0.05) 6 7 14 23 36 39 39 34 32 31 Probability <0.001 <0.001 0.05 0.34 0.94 0.96 0.84 0.71 0.67 0.57 Banana Xanthomonas Wilt Management 121

Remaining asymptomatic mats (%) 10

0 14–29 42–45 Proportion of mats showing symptoms at start of experiment (%) Management package Adjacent control plot applied Fig. 14.1. Percentage of visibly healthy plants by initial incidence level of Xanthomonas wilt in bananas 10 months after the start of an experiment to use cultural control practices in North Kivu, eastern Democratic Republic of Congo. The control package comprised selective uprooting of diseased mats in combination with early male bud removal and the prohibition of garden tools for de-leafing, de-trashing, de-suckering and weeding.

Legume intercropping was practised with the rigorous application of manage- in the experimental plots in the South ment options that reduce disease inocu- Kivu trial during the rainy seasons (Fig. 14.2), lum, resulted in the highest number of with the legumes planted in February and asymptomatic mats (35% in Rwanda and September. The occurrence of new infections 57% in North Kivu, eastern DR Congo). seemed to be linked to the practice of New infections were, however, still intercropping, as a large number of new observed up to the tenth month after the Xanthomonas wilt infections was observed establishment of treatments in both 2–3 months after land preparation activities countries. This is obviously not very for bean intercropping (Fig. 14.3). These encouraging for farmers. Non-adherence land prepara tions included the removal of to the full package of cultural control dead banana leaves to reduce shading of options significantly reduced the num- the legume crop and rigorous weeding, ber of asymptomatic mats. Farmers who which may damage banana roots. Both rigorously adhered to the appropriate practices favour the transmission of the disease management practices com- disease. plained of the high time and labour requirements needed to effectively implement this package. The timely and complete uprooting of infected mats was 14.4 Conclusion reported as time-consuming and labour intensive. We are thus inclined to recom- Selective mat uprooting under conditions mend the removal of diseased fields and of low initial infection (14–29%), combined subsequent fallowing/establishment of 122 A. Rutikanga et al.

Table 14.4. Results from a trial in South Kivu, Democratic Republic of Congo on the cultural control of Xanthomonas wilt in bananas. Mean disease incidence level at the onset and at 17 months after trial initiation according to initial disease incidence range and corresponding mat/plant removal treatment. Means followed by the same letter (a–c) in a row are not significantly different according to Tukey’s HSD test (P < 0.05).

Treatment

Removal of single diseased plant

Cutting at Digging Removal of LSD CV Parameter soil level out corm complete mat (P = 0.05) (%)

At beginning of experiment Initial disease incidence (%) 7–10 11–14 21–38 Mat number 100 100 100 Diseased mats (%) 8.7a 12.7a 27.0b 11.3* 35 17 months after experiment began Diseased mats (%) 38.3a 48.3a 82.0b 18.1** 16 Increase in diseased mats 29.7a 35.7a 55.0b 16.0* 20 over 17 months (%) Mats with more than one 10 15 NDa diseased plant present Time between two observed 68 61 ND infected plants on a mat (days) No. of plants present on all mats 259a 194b 78c 63*** 18 No. of plants removed during 78a 81a 220b 74** 29 experiment Diseased plants removed (%) 23a 30a 73b 16*** 19

*Significant at P < 0.05; **Significant at P < 0.01; ***Significant at P < 0.001; a ND, not determined.

250

200

150

100 Rainfall (mm)

0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Month

Fig. 14.2. Rainfall distribution in South Kivu, Democratic Republic of Congo, in 2011 (collected at the Institut National des Etudes et de la Recherche Agricole (INERA), Mulungu Research Station). break crops when initial disease incidence applied on a wider scale, thus reducing is above 14% and when adjacent farmers the sources of inoculum, the pattern of are not implementing control measures. infection might be far less dramatic in the Of course, if control measures were first place. Banana Xanthomonas Wilt Management 123

30 No. plants removed

0 Jul Oct Apr Apr Jun Jun Jan Mar Mar Feb Feb Aug Nov Sep Dec May May Month 7–10% 11–14% 21–38%

Fig. 14.3. Results from a 17 month trial in South Kivu, Democratic Republic of Congo on the cultural control of Xanthomonas wilt in bananas intercropped with beans (planted in February and/or September). Mean disease incidence levels at trial onset were 7–10%, 11–14% and 21–38%. Control involved complete removal of diseased mats (with at least one diseased plant) in the 11–14% plots, cutting at ground level of diseased plants in the 7–10% plots, and removal of diseased plants + corms in the 21–38% plots. The number of infected plants removed each month is shown for each of the three initial disease incidence levels.

The results from the South Kivu, Acknowledgements DR Congo, experiment indicate that complete mat or single plant removal does not lead to We would like to thank the Directorate General the quick removal of the disease from a field for Development, Belgium for funding this in a small-scale farming context. Also, tradi- research through the Consortium for Improv- tional intercropping practices, coupled with ing Agriculture-based Livelihoods in Central the omnipresence of free-ranging small- Africa (CIALCA). In addition, the contributions ruminants may perpetuate the disease. More of the Rwanda Agriculture Board (RAB), the in-depth experiments on single plant removal Université Catholique du Graben (UCG), North across a wide range of initial disease inci- Kivu, DR Congo and the Institut National dence levels are needed to further elucidate des Etudes et de la Recherche Agricole (INERA), the potential of this method in controlling Mulungu Research Station, South Kivu, Xanthomonas wilt. eastern DR Congo are highly appreciated.

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Available at: http://c3project.iita.org/ Doc/A11-BXWSurveyRwanda.pdf (accessed 24 April 2013). Ndungo, V., Bakelana, K., Eden-Green, S. and Blomme, G. (2004) An outbreak of banana Xanthomonas wilt (Xanthomonas campestris pv. musacearum) in the Democratic Republic of Congo. InfoMusa 13(2), 43–44. Ndungo, V., Eden-Green, S., Blomme, G., Crozier, J. and Smith, J. (2006) Presence of banana Xanthomonas wilt (Xanthomonas campestris pv. musacearum) in the Democratic Republic of Congo (DRC). Plant Pathology 55, 294. Reeder, R.H., Muhinyuza, J.B., Opolot, O., Aritua, V., Crozier, J. and Smith, J. (2007) Presence of banana bacterial wilt (Xanthomonas campestris pv. musacearum) in Rwanda. Plant Pathology 56, 1038. Shimelash, D., Alemu, T., Addis, T., Turyagyenda, F.L. and Blomme, G. (2008) Banana Xanthomonas wilt in Ethiopia: occurrence and insect vector transmission. African Crop Science Journal 16, 75–87. Ssekiwoko, F., Turyagyenda, L.F., Mukasa, H., Eden-Green, S. and Blomme, G. (2006) Systemicity of Xanthomonas campestris pv. musacearum (Xcm) in flower-infected banana plants. In: Saddler, G., Elphinstone, J. and Smith, J. (eds) Programme and Abstract Book of the 4th International Bacterial Wilt Symposium, 17–20 July 2006, The Lakeside Conference Centre, Central Science Laboratory, York, UK, p. 61. Ssekiwoko, F., Turyagyenda, L.F., Mukasa, H., Eden-Green, S. and Blomme, G. (2010) Spread of Xanthomonas campestris pv. musacearum in banana (Musa spp.) plants following infection of the male inflorescence. Acta Horticulturae 879, 349–356. Tinzaara, W., Gold, C.S., Tushemereirwe, W., Bandyopadhyay, R. and Eden-Green, S.J. (2006) Possible role of insects in the transmission of banana Xanthomonas wilt. In: Saddler, G., Elphinstone, J. and Smith, J. (eds) Programme and Abstract Book of the 4th International Bacterial Wilt Symposium, 17–20 July 2006, The Lakeside Conference Centre, Central Science Laboratory, York, UK, p. 60. Tripathi, L., Odipio, J., Tripathi, J.N. and Tusiime, G. (2008) A rapid technique for screening banana cultivars for resistance to Xanthomonas wilt. European Journal of Plant Pathology 121, 9–19. Tushemereirwe, W.K., Kangire, A., Smith, J., Ssekiwoko, F., Nakyanzi, M., Kataama, D., Musiitwa, C. and Karyaija, R. (2003) An outbreak of bacterial wilt on banana in Uganda. InfoMusa 12(2), 6–8. Tushemereirwe, W., Kangire, A., Ssekiwoko, F., Offord, L.C., Crozier, J., Boa, E., Rutherford, M. and Smith, J.J. (2004) First report of Xanthomonas campestris pv. musacearum on banana in Uganda. Plant Pathology 53, 802. Welde-Michael, G., Bobosha, K., Blomme, G., Addis, T., Mekonnen, S. and Mengesha, T. (2006) Screening banana cultivars for resistance to bacterial Xanthomonas wilt. InfoMusa 15(1–2), 10–12. Yirgou, D. and Bradbury, J.F. (1968) Bacterial wilt of enset (Ensete ventricosum) incited by Xanthomonas musacearum sp. n. Phytopathology 58, 111–112. Yirgou, D. and Bradbury, J.F. (1974) A note on wilt of banana caused by the enset wilt organism Xanthomonas musacearum. East African Agricultural and Forestry Journal 40, 111–114. 15 Effect of Length of Fallow Period after Total Uprooting of a Xanthomonas Wilt-infected Banana Field on Infection of Newly Established Planting Materials: Case Studies from Rwanda and Eastern Democratic Republic of Congo

C. Sivirihauma,1* A. Rutikanga,2 C. Murekezi,3 G. Blomme,4 U. Anuarite,3 W. Ocimati,4 P. Lepoint5 and V. Ndungo6 1Bioversity International, Butembo, Democratic Republic of Congo; 2Bioversity International, Kigali, Rwanda and Higher Institute for Agriculture and Animal Husbandry (ISAE), Rwanda; 3Rwanda Agriculture Board (RAB), Kigali, Rwanda; 4Bioversity International, Kampala, Uganda; 5Bioversity International, Bujumbura, Burundi; 6Université Catholique du Graben, Butembo, Democratic Republic of Congo

Abstract Xanthomonas wilt of banana, caused by Xanthomonas campestris pv. musacearum, is a devastating bacterial disease that can cause up to 100% yield loss when appropriate control measures are not implemented. Currently, cultural practices are the only recommended means for managing Xanthomonas wilt. No cultivar is reported as resistant, nor can the disease be controlled using chemicals. On-farm experiments were established at three sites (eastern and western Rwanda, and North Kivu in Democratic Republic of Congo (DR Congo)), with the main objective of determining the most effective fallow period for eliminating Xanthomonas wilt from a highly infected banana field. At each site, three banana fields with an initial disease incidence of at least 70% were selected. All banana mats and most debris were removed before the experiment began. Thereafter, suckers that were free of Xanthomonas wilt of the cultivars ‘Kamaramasenge’ (Musa AAB group) and ‘Injagi’ (AAA-EA) in Rwanda, and ‘Kamaramasenge’, the plantain ‘Musilongo’ (AAB) and ‘Vulambya’ (AAA-EA) in DR Congo, were planted in experimental plots at monthly intervals, following increasingly long fallow periods, over 10 months. In Rwanda, ten plants per variety were planted each month in parallel rows in each field. In DR Congo, ten plants of each variety were randomly planted across the three experiment plots in single rows of ten plants per plot. In both countries, disease incidence was monitored for 15 months (i.e. up to 15 months after the first planting). In Rwanda, 13–15 months after planting, Xanthomonas wilt incidence in ‘Injagi’ was 22% for the planting in month 1, 27% for month 2 and 9% for month 3, whereas in ‘Kamaramasenge’ it was below 2% for the first 3 months of replanting. In ‘Injagi’, disease incidence declined sharply from months 4 (2.4%) and 5 (1.7%), i.e. less than 11 months from planting. Healthy suckers of the two cultivars planted from month 6 onwards did not

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 125 126 C. Sivirihauma et al.

become infected. In DR Congo, a steady decrease in Xanthomonas wilt incidence from month 1 (up to 70%) to month 10 (10%) was observed in the experimental fields. The prolonged appearance of disease symptoms (i.e. beyond replanting month 5) could be linked to the extremely high (>80%) disease incidence of, and close proximity to, diseased fields. Possible transmission of the disease into the experiment by foraging small ruminants and larger birds could have occurred. In contrast, diseased mats were continuously uprooted in adjacent farmers’ fields in Rwanda. Results suggest that under Rwandan conditions, the bacterium is likely to survive for up to 5 months in soil and/or remaining plant debris. Therefore, it is proposed that replanting of previously Xanthomonas wilt-infected fields should be carried out 6 months after thorough uprooting of bananas infected with X. c. pv. musacearum. The DR Congo study also indicates that there is need for rigorous application of preventive control measures in adjacent farms to avoid possible transmission by foraging animals, large birds or runoff water. Hence, in both Rwanda and eastern DR Congo, disease management efforts should be carried out by farmers in a concerted manner.

15.1 Introduction removal of infected mats and fallowing are considered the only viable control measures Banana (Musa spp.) is an important crop in (Brandt et al., 1997). both the Democratic Republic of Congo Turyagyenda et al. (2008, 2009) assessed (DR Congo) and Rwanda. Some 70% of appropriate replanting times in an on-farm bananas in DR Congo are produced in the experiment in central Uganda and indicated eastern provinces, with a staggering 24% pro- that plantlets established after a 1 month fallow duced in North Kivu Province (Bakelana and had a 25% survival rate, while plants established Ndungo, 2004). In Rwanda, a quarter of ara- after 7–8 months of fallow all survived. This study ble land is allocated to banana production suggested that cleared, Xanthomonas wilt- (Mpyisi et al., 2000). Annual Musa production infected farms need a fallow of at least 6 months is estimated at 1.57 million metric tonnes under central Ugandan agro- ecological condi- (MT) in the DR Congo and 2.75 million MT in tions. To make recommendations to farmers in Rwanda (FAOSTAT, 2010). Rwanda and eastern DR Congo, knowledge on However, banana yield is seriously the required length of fallow period for their affected by the bacterial disease Xanthomonas specific agro-ecological conditions needs to be wilt, among other production constraints. generated. Hence, a study was conducted in This disease is caused by Xanthomonas camp- Rwanda and eastern DR Congo to assess how estris pv. musacearum and was first officially length of fallow after total uprooting of banana reported in Ethiopia in 1968 (Yirgou and fields with a high incidence of Xanthomonas Bradbury, 1968). In 2001, it was observed in wilt influenced the infection of plants growing both central Uganda (Tushemereirwe et al., from newly established and clean (uninfected) 2004) and eastern DR Congo (Ndungo et al., planting material. 2004, 2006). It was first officially reported in Rwanda in 2005 (Reeder et al., 2007), although farmer reports indicate that the disease may 15.2 Materials and Methods have been present in Gisenyi Province since 2002. Following the first reports of the disease On-farm experiments were established at in both Rwanda and DR Congo, it has three sites – eastern and western Rwanda, and emerged as a crucial factor in limiting banana North Kivu in the DR Congo – to determine the production (Beed et al., 2010). The bacteria most effective fallow period for eliminating spread systemically throughout the entire Xanthomonas wilt from a highly infected mat, so all attached lateral shoots can poten- (>70% disease incidence) banana field. In tially be infected (Ssekiwoko et al., 2010). Rwanda, the experiment was established in Currently, no cultivar is reported to be resist- Rubavu District (western Rwanda), and ant to the disease (Tripathi et al., 2008). Nyagatare and Gatsibo districts (eastern Cultural control practices, including early Rwanda). Rubavu District is located at an alti- disbudding, disinfection of garden tools, tude of around 1600 m above sea level (masl), Effect of Fallow Length after Uprooting of Infected Bananas 127

at latitude 1°41¢20S and longitude 29°17¢33E. 15.3 Results and Discussion The average annual temperature is 21°C, and the annual rainfall ranges from 1200 to In Rwanda, 15 months after the initial plant- 1350 mm, distributed over two rainy seasons ing, the highland cooking banana ‘Injagi’ (September–December and February–April). (AAA-EA) had a mean disease incidence of The predominant soil is a highly fertile 22% for plants established after 1 month of volcanic-derived soil (Andosol) (FAO, 1998). fallow, 27% after 2 months of fallow and 9% The biophysical conditions in eastern Rwanda after 3 months of fallow. A sharp decline in are quite similar to those of western Rwanda. disease incidence was, however, observed Altitudes range from 1000 to 1450 masl. Annual for subsequent planting months: 2.4% for rainfall is estimated at around 831 mm and 4 months of fallow and 1.7% for 5 months of follows the same distribution as in Rubavu fallow (Fig. 15.1). In contrast, the cultivar District (i.e. two rainy seasons). The soil is ‘Kamaramasenge’ (AAB) had a disease inci- dominantly silty clay. In DR Congo, the study dence of less than 2% for up to 3 months of was conducted in North Kivu, Beni Territory, fallow (Fig. 15.1). The highland cooking culti- Kisungu locality, at latitude 0°14¢38N and var ‘Injagi’ is clearly far more susceptible to longitude 29°15¢05E. The altitude ranges from the disease than ‘Kamaramasenge’. No new 1670 to 1750 masl with an average annual tem- infections were observed after 3 months of fal- perature of 19°C. Annual rainfall ranges from low for ‘Kamaramasenge’ and after 5 months 1300 to 1800 mm and is distributed over two of fallow for ‘Injagi’ (Fig. 15.1). rainy seasons (September–December and March– A similar study conducted in Uganda by June). The soil is mainly clayey (ENRA, 2010). Turyagyenda et al. (2008) also recorded a Three banana fields with an initial higher infection rate for the AAA-EA cultivar disease incidence of at least 70% were ‘Mporogoma’ than for the ABB cultivar ‘Pisang selected at each site. All banana mats and Awak’. As already mentioned, Turyagyenda most debris were removed before the exper- et al. (2008, 2009) indicated that plantlets estab- iment began. In Rwanda, the varieties used lished after a 1 month fallow had a 25% survival were the dessert banana ‘Kamaramasenge’ rate, while plants established after 7–8 months (Musa AAB group) and the highland banana of fallow had a 100% survival rate. Their study ‘Injagi’ (AAA-EA); in DR Congo, the varie- suggested that the cleared Xanthomonas wilt- ties were ‘Kamaramasenge’, the plantain infected farms need a fallow of at least 6 months ‘Musilongo’ (AAB) and the highland cooking under central Ugandan agro-ecological condi- banana ‘Vulambya’ (AAA-EA). Clean tions. Also in line with our observations, X. c. pv. suckers of each variety were planted in the musacearum is reported to have limited survival experimental plots at monthly intervals, in the soil in the absence of suitable host tissue. following increasingly long fallows, for up to The bacterium can survive in the soil for less 10 months. In both countries, the first than 3 months under laboratory conditions replanting was done in October during the (Mwebaze et al., 2006), and in Ethiopia, it is rainy season. In Rwanda, ten plants per vari- reported that it can survive in detached enset ety were planted each month in parallel (Ensete ventricosum) leaf petioles and leaf rows in each field. In DR Congo, ten plants of sheaths for up to 3 months (Welde-Michael each variety were randomly planted across et al., 2008). the three experimental plots per month in In eastern DR Congo, there was a general single rows of ten plants per plot. In both decreasing trend in new infections with countries, Xanthomonas wilt symptoms on increase in the length of fallow (Fig. 15.2). banana plants in the experimental plots was Nevertheless, new infections were obser ved monitored monthly for a period of 15 months over up to 10 months of fallow for (i.e. up to 5 months after the last planting). ‘Kamaramasenge’ (AAB), up to 9 months for All mats that became infected during the the plantain ‘Musilongo’ (AAB) and up to observation period were systematically 8 months for the highland cooking variety uprooted to remove all secondary sources of ‘Vulambya’ (AAA-EA) (Fig. 15.2). The inoculum. prolonged appearance of disease symptoms 128 C. Sivirihauma et al.

10 Plants infected with Xanthomonas wilt (%) 5

0 12345678910 Month of replanting

‘Injagi’ ‘Kamaramasenge’

Fig. 15.1. Percentage of banana plants of two cultivars (the highland banana ‘Injagi’, AAA-EA, and the dessert banana ‘Kamaramasenge’, AAB) infected with Xanthomonas wilt in Rwanda. Clean suckers were established 1–10 months after clearing an infected field, and disease incidence assessed at 15 months after the first planting (in month 1). Error bars indicate the SED.

40 wilt (%) 30

10 Plants infected with Xanthomonas 0 12345678910 Month of replanting

‘Vulambya’ ‘Kamaramasenge’ ‘Musilongo’

Fig. 15.2. Percentage of banana plants infected with Xanthomonas wilt of three cultivars, for each replanting time (i.e. from one to ten months after clearing the diseased field), at 15 months after the planting in month 1 in eastern Democratic Republic of Congo. Error bars indicate the SED. in the experiment in eastern DR Congo (i.e. mats in adjacent fields were continuously beyond the 5 months of fallow observed in uprooted and debris buried in pits at the the Rwandan trial) could be linked to the extremities of neighbouring farmers’ fields. very high disease incidence (>80%) of, and close proximity to, neighbouring diseased fields. A possible transmission of the disease 15.4 Conclusion into the experiment by foraging small ruminants or larger birds could have Based on the results presented here, X. c. pv. occurred. In contrast, in Rwanda, diseased musacearum is likely to survive for up to Effect of Fallow Length after Uprooting of Infected Bananas 129

5 months in soil and/or remaining banana cultivar ‘Kamaramasenge’ under Rwandan plant debris under the conditions in Rwanda. conditions. However, a clear cultivar effect on Therefore, replanting of previously infected disease incidence was not observed in eastern fields should be carried out no less than DR Congo (Fig. 15.2). 6 months after a thorough uprooting of diseased bananas. Turyagyenda et al. (2008) also suggested that, under central Ugandan agro- Acknowledgements ecological conditions, a fallow period of at least 6 months is required to restore health to We would like to thank the Directorate farms after infection with Xanthomonas wilt. General for Development, Belgium, for The study in eastern DR Congo suggests that funding this research through the Consortium continuous transmission might have for Improving Agriculture-based Livelihoods occurred from neighbouring infected fields in Central Africa (CIALCA) project. In (located at 2–10 m from the on-farm experi- addition, the Rwanda Agriculture Board ments), thus highlighting the need for con- (RAB) and the Université Catholique du certed eradication efforts. The study also Graben (UCG), North Kivu, DR Congo are suggests a reduced susceptibility of the AAB acknowledged for facilitating the study.

References

Bakelana, K. and Ndungo, V. (2004) La Maladie de Bwere: Une Bactériose Dévastatrice de la Culture de la Banane dans la Province du Nord Kivu en République Démocratique du Congo, Rapport de Mission, FAO (Food and Agriculture Organization of the United Nations), Rome. Beed, F., Fiaboe, K., Ouma, E., Ndungo, V., Tinzaara, W. and Koury, W. (2010) L’Ampleur des Problèmes Lies au Flétrissement Bactérien de la Banane (BXW) à l’Est de la RDC (Nord – Sud Kivu et Province Orientale): Une Évaluation d’Experts sur les Informations Existantes, Kinshasa, RD Congo du 05–09 Juin 2010. Brandt, S.A., Spring, A., Hiebsch, C., McCabe, J.T., Tabogie, E., Diro, M., Wolde-Michael, G., Yntiso, G., Shigeta, M. and Tesfaye, S. (1997) The Tree Against Hunger: Ensete-based Agricultural Systems in Ethiopia. American Association for the Advancement of Science, Washington, DC.. ENRA (2010) Rapport Synthèse Annuelle d’Observation Météorologique pour les Années 2009 et 2010. Enzyme Refiners Association, Beni, Democratic Republic of Congo. FAO (1998) World Reference Base for Soil Resources. International Soil Reference and Information Centre (ISRIC) and International Society of Soil Science (ISSS), Food and Agriculture Organization of the United Nations, Rome. FAOSTAT (2010) Online statistical database. Food and Agriculture Organization of the United Nations, Rome. Available at: http://faostat.fao.org/ (accessed 24 April 2013). Mpyisi, E., Nyarwaya, J.B. and Shingiro, E. (2000) Statistiques Agricoles: Production Agricole, Élevage, Superficies et Utilisation des Terres, Année Agricole 2000. MINAGRI/DSA (Ministry of Agriculture and Animal Resources/Agricultural Statistics Division), Kigali, Rwanda. Mwebaze, J.M., Tusiime, G., Tushemereirwe, W.K. and Kubiriba, J. (2006) The survival of Xanthomonas campestris pv. musacearum in soil and plant debris. African Crop Science Journal 14, 121–127. Ndungo, V., Bakelana, K., Eden-Green, S. and Blomme, G. (2004) An outbreak of banana Xanthomonas wilt (Xanthomonas campestris pv. musacearum) in the Democratic Republic of Congo. InfoMusa 13(2), 43–44. Ndungo, V., Eden-Green, S., Blomme, G., Crozier, J. and Smith, J. (2006) Presence of banana Xanthomonas wilt (Xanthomonas campestris pv. musacearum) in the Democratic Republic of Congo (DRC). Plant Pathology 55, 294. Reeder, R.H., Muhinyuza, J.B., Opolot, O., Aritua, V., Crozier, J. and Smith, J. (2007) Presence of banana bacterial wilt (Xanthomonas campestris pv. musacearum) in Rwanda. Plant Pathology 56, 1038. Ssekiwoko, F., Turyagyenda, L.F., Mukasa, H., Eden-Green, S. and Blomme, G. (2010) Spread of Xanthomonas campestris pv. musacearum in banana (Musa spp.) plants following infection of the male inflorescence. Acta Horticulturae 879, 349–356. Tripathi, L., Odipio, J., Tripathi, J.N. and Tusiime, G. (2008) A rapid technique for screening banana cultivars for resistance to Xanthomonas wilt. European Journal of Plant Pathology 121, 9–19. 130 C. Sivirihauma et al.

Turyagyenda, L.F., Blomme, G., Ssekiwoko, F., Karamura, E., Mpiira, S. and Eden-Green, S. (2008) Rehabilitation of banana farms destroyed by Xanthomonas wilt in Uganda. Journal of Applied Biosciences 8, 230–235. Turyagyenda, L.F., Blomme, G., Karamura, E., Ssekiwoko, F., Tinzaara, W., Mpiira, S. and Eden-Green, S. (2009) Cultural practices for management of Xanthomonas in Uganda. In: Karamura, E.B. and Tinzaara, W. (eds). Management of Banana Xanthomonas Wilt in East and Central Africa: Proceedings of the Workshop on Review of the Strategy for the Management of Banana Xanthomonas Wilt, 23–27 July, 2007, Hotel la Palisse, Kigali, Rwanda. Bioversity International, Kampala, Uganda, pp. 69–73. Tushemereirwe, W.K., Kangire, A., Ssekiwoko, F., Offord, L.C., Crozier, J., Boa, E., Rutherford, M. and Smith, J.J. (2004) First report of Xanthomonas campestris pv. musacearum on banana in Uganda. Plant Pathology 53, 802. Welde-Michael, G., Bobosha, K., Addis, T., Blomme, G., Mekonnen, S. and Mengesha, T. (2008) Mechanical transmission and survival of bacterial wilt on enset. African Crop Science Journal 16, 97–102. Yirgou, D. and Bradbury, J.F. (1968) Bacterial wilt of enset (Ensete vertricosum) incited by Xanthomonas museacearum sp. n. Phytopathology 58, 111–112. 16 Distribution, Incidence and Farmer Knowledge of Banana Xanthomonas Wilt in Rwanda

G. Night,1* S.V. Gaidashova,1 A. Nyirigira,1 Theodomir Mugiraneza,2 A. Rutikanga,3 C. Murekezi,1 A. Nduwayezu,1 E. Rurangwa,1 Thierry Mugiraneza,1 F. Mukase,1 O. Ndayitegeye,1 W. Tinzaara,4 E. Karamura,4 W. Jogo,4 I. Rwomushana,5 F. Opio5 and D. Gahakwa1 1Rwanda Agriculture Board (RAB), Kigali, Rwanda; 2National University of Rwanda (NUR), Huye, Rwanda; 3Bioversity International, Kigali, Rwanda and Higher Institute for Agriculture and Animal Husbandry (ISAE), Rwanda; 4Bioversity International, Kampala, Uganda; 5Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), Entebbe, Uganda

Abstract Banana Xanthomonas wilt was reported in Rwanda in 2005. The present study was conducted to determine the distribution and incidence of the disease and farmer knowledge of disease symptoms, modes of spread and control. A survey was conducted in Rwanda in 2009–2010 in 12 major banana-growing districts of the country. One hundred and eight banana growers were interviewed using a structured questionnaire. Farmers were asked about knowledge of disease symptoms, spread, control and use of control methods. They were also asked about their sources of information on Xanthomonas wilt. Direct field observations were made of the distribution and incidence of the disease as well. The proportion of fields with Xanthomonas wilt was highest in Rutsiro (89%) and lowest in Kayonza and Ruhango (11%). The disease was not found in Gakenke, Kicukiro or Ngoma. Within-farm incidence was highest in Rutsiro (average 36%) and lowest in Kayonza (1%). The awareness of disease symptoms ranged from 53% (discoloured fruit pulp) to 84% (wilting leaves). For modes of spread, the highest proportion of farmers (73%) was aware of the role of contaminated tools while the least known mode was spread via soil and water (24%). Some 72% of famers were aware of uprooting plants as a control measure. There were large differences between awareness and use of tool disinfection and destruction of infected plants as control measures. There is a need to develop user-friendly methods of disease control. The creation of awareness in newly affected and Xanthomonas wilt-free areas is advocated. Participatory approaches are encouraged as they may reduce the gap between knowledge and adoption of control measures.

16.1 Introduction by several symptoms: wilting leaves; yellow ooze from severed pseudostems, fingers Banana Xanthomonas wilt caused by Xatho monas and other plant parts; premature ripening; campestris pv. musacearum is characterized discoloration of fruit pulp; and rotting of

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 131 132 G. Night et al.

male buds (Smith et al., 2008). Recently, Aritua Xanthomonas wilt among farmers are key in et al., (2008) suggested reclassification of the the implementation of disease management pathogen as X. vasicola pv. musacearum. The programmes (Bagamba et al., 2006). disease causes plant death and total loss of The present study had the specific objec- yield as the infected fruit cannot be consumed tives of establishing and updating informa- by humans or livestock. It is transmitted tion on: (i) distribution and incidence of through infected plant material, contaminated Xantho monas wilt in Rwanda; (ii) farmers’ tools, insects visiting male buds and animals knowledge of disease symptoms and mecha- coming into contact with infected material, as nisms of spread; (iii) knowledge and use of well as via soil and water (Tinzaara et al., 2006; control methods by farmers. Biruma et al., 2007). Methods recommended for management of the disease are the destruction of infected plant material, early disbudding (removal of the male bud), disinfection 16.2 Methods of tools and quarantine (Muhangi et al., 2006; Biruma et al., 2007). A survey was conducted to determine disease Xanthomonas wilt first existed only in status in areas where the disease has been Ethiopia on enset (Ensete ventricosum) and reported, to assess disease advance in report- banana (Musa spp.) (Yirgou and Bradbury, edly free areas and to investigate farmer knowl- 1968, 1974). The disease currently affects edge of the disease. The survey was carried out banana in several countries of eastern, central in districts where Xanthomonas wilt has been and southern Africa. Banana Xanthomonas wilt reported (existing or contained) and in those was first reported in Rwanda in 2005 (Reeder where it has not been reported, and was con- et al., 2007) in the district of Rubavu, Western ducted from December 2009 to January 2010. Province, but farmers reported symptoms as Twelve districts were surveyed (Plate 14). Three having appeared in their fields in 2002. sectors were randomly selected and surveyed When Xanthomonas wilt was reported in in each district, with the exception of Kicukiro Rwanda, a National Task Force was set up to District, in which the sole sector where banana combat it and this drew up a management is grown (Masaka) was selected. Three fields strategy with a focus on raising awareness were randomly selected in each sector, from at (through meetings, mass media, posters and least two different cellules. In Kicukiro District, pamphlets), eradication of infected plants however, sites were selected from six different through community work (‘umuganda’) as cellules of one sector (Masaka). The criterion well as individual initiatives, training and local used for site selection was a banana field having quarantine. Further interventions included a at least 20 mats (stools). Distance between fields campaign to eradicate infected plants by was at least 5 km. In total, 108 farmers, nine uprooting, training of trainers and the forma- from each district, were interviewed using a tion of task forces at district, sector and cellule structured questionnaire. Questions addressed levels (administrative divisions in order of to farmers included knowledge of disease decreasing size). In spite of these efforts, symptoms, spread and control, and use of con- Xanthomonas wilt has continued to spread. trol methods. Direct field observations were The status of Xanthomonas wilt in differ- also made of the incidence of Xanthomonas ent areas of Rwanda ranges from contained wilt. Twenty stools selected along two diago- outbreaks to endemic. Furthermore, resur- nals (ten stools on each diagonal) were observed gence has occurred in some of the areas for absence or presence of symptoms of where the disease was thought to have Xanthomonas wilt. Stools were scored as ‘0’ been contained. There is, therefore, a need to when symptom free and ‘1’ when they pre- determine the current status of the disease. sented symptoms of the disease. Moreover, control interventions depend on The farms that were investigated were the status of the disease, differing in endemic, spatially located using handheld global posi- front-line, threatened or disease-free areas tioning system (GPS) units with at least 3 m (Smith et al., 2008). Levels of awareness of accuracy. Incidence of banana Xanthomonas Banana Xanthomonas Wilt in Rwanda 133

wilt (BXW) was determined by calculating the Rutsiro in 2007, but limited interventions in proportion of affected mats among those terms of disease control have been made there. selected. Incidence data were joined to GPS The other three districts (Nyamasheke, coordinates plotted and mapped using ArcGIS Musanze and Karongi) have newer infections. (Version 9.3). Symbols of proportional size Rulindo had a low incidence of the disease, were used for illustrating the spatial patterns although it was the second district where it of wilt incidence at farm level. Data were ana- was reported. This may be attributed to the fact lysed using the Statistical Analysis System that the district is not a major banana-growing (SAS, Version 9.1). Descriptive statistics (per- area. Gakenke, Kicukiro and Ngoma districts centages of respondents) were calculated to were free of Xanthomonas wilt. determine the proportions of farmers having Some 37% of respondents indicated that knowledge of a given subject (different symp- they had Xanthomonas wilt on their farms at toms, methods of spread and control) or using the time of the survey, and 63% said that it a particular technique to control Xanthomonas was absent from their farms. The survey wilt. Fisher’s Exact Test was used to deter- observations indicated that 33% of the farms mine whether there was an effect of aware- had mats with symptoms of Xanthomonas ness of symptoms (know or do not know) on wilt. These incidences underline the impor- the correct estimation of disease incidence tance that the disease has assumed over the within the field (correct or incorrect). last 5 years. Disease incidences of 10–40% were found in 51% of the farms, and incidences of 40–70% 16.3 Results and Discussion were found on 16% of farms. The highest mean within-farm Xanthomonas wilt inci- 16.3.1 Status of Xanthomonas dences were observed in the districts of wilt on farms Rutsiro, Rubavu and Nyamasheke (Table 16.1; Plate 15). These levels are high and suggest The districts of Rutsiro, Rubavu, Nyamasheke, large potential economic losses. Kalyebara Musanze and Karongi had the highest propor- et al. (2006) estimated annual losses of tions of sites/farms infected with Xanthomonas US$200/household if Xanthomonas wilt was wilt (Fig. 16.1). None of them has received not controlled in Uganda, where incidence as much attention to disease management as varied from 10% to 71%. Further studies are Rubavu. Banana Xanthomonas wilt arrived in required to determine the economic losses

100

40 Incidence (%) 20

0 Rutsiro Ngoma Rulindo Gatsibo Rubavu Karongi Kicukiro Kayonza Gakenke Musanze Ruhango Nyamasheke District

Fig. 16.1. Proportion of sites/farms with Xanthomonas wilt infection in different districts of Rwanda surveyed in 2009–2010. 134 G. Night et al.

Table 16.1. Proportion of plants (mean ± SE) stems (c2= 0.21; P = 1.00), premature fruit rip- infected by Xanthomonas wilt within farms/sites ening (c2 = 0.87; P = 1.00) or rotting of the fruit (n = 9) in Rwanda, 2009–2010. Means followed (c2 = 0.07; P = 1.00). by the same letter are not significantly different at P = 0.05.

District % infected plants 16.3.2 Awareness of Xanthomonas wilt symptoms Gakenke 0.0 ± 0.0b Gatsibo 3.9 ± 2.9b Karongi 7.8 ± 3.3b Some 97% of respondents had heard of Kayonza 1.1 ± 1.1b Xanthomonas wilt before the survey; only Kicukiro 0.0 ± 0.0b 3% had not, and having heard of Musanze 11.8 ± 5.8bc Xanthomonas wilt was independent of dis- Ngoma 0.0 ± 0.0b trict (Fisher’s exact test P £ 0.85). Awareness Nyamasheke 16.2 ± 4.8ac of Xanthomonas wilt symptoms was high Rubavu 26.1 ± 8.2ac (Table 16.3). Most farmers were aware of Ruhango 3.9 ± 3.3b wilting leaves (84%), premature ripening Rulindo 12.0 ± 7.7ac (71%) and yellow ooze from cut plant parts Rutsiro 35.9 ± 8.6a (67%) as symptoms of Xanthomonas wilt. Discoloration of fruit pulp and rotting of Table 16.2. Incidence of Xanthomonas wilt within the male bud were less well known as fields reported by farmers and observed by symptoms, and significantly so compared interviewers on farms with the disease in Rwanda, with the previously mentioned three symp- 2009–2010. toms, although at least half of the respond- Proportion (%) of plants with ents were aware of these other two symptoms symptoms. Knowledge of all Xanthomonas wilt symptoms except for rotting of male Farmer Interviewer buds was influenced by district. In general, Incidence estimates observations awareness of the different symptoms varied range (%) (n = 42) (n = 37) by district, with knowledge of one symptom <10 47.6 27.0 not automatically implying knowledge 10–40 23.8 51.4 of other symptoms. Notably low levels of 40–70 7.1 16.2 knowledge were noted in the districts of >70 21.4 5.4 Gakenke (25% for discoloration of pulp, premature ripening and rotting of male bud to 63% for wilting leaves), Ngoma (22% for due to Xanthomonas wilt in Rwanda. Some pulp discoloration to 67% for wilting leaves) 60% of respondents indicated that Xantho- and Ruhango (25% for all symptoms). monas wilt was increasing on their farms, while 36% thought that it was decreasing; only 4% thought that it was constant. Banana Xanthomonas wilt incidence 16.3.3 Awareness of modes of spread within fields, as estimated by farmers and as observed by interviewers, differed (Table 16.2). Farmers were most aware of contaminated Farmers tended to overestimate extreme inci- tools, insects, infected planting material and dence levels (<10% and >70%) and underesti- infected plant parts as means of spread of mate moderate levels (10–70%). However, the Xanthomonas wilt (Table 16.4). Awareness farmers’ ability to accurately determine inci- of disease spread by water and soil, domes- dence levels was not related to whether they tic animals and flying animals was signifi- were able to recognize disease symptoms in cantly lower (P = 0.05), while knowledge of terms of discoloration of fruit pulp (c2 = 0.89; spread by infected plant parts was moder- P = 0.61), wilting leaves (all farmers who had ate. Low levels of awareness for these modes Xantho monas wilt knew), yellow ooze from of spread were not influenced by district Banana Xanthomonas Wilt in Rwanda 135

Table 16.3. Awareness of farmers of the symptoms of Xanthomonas wilt in the 12 districts of Rwanda surveyed in 2009–2010. Means followed by the same letter are not significantly different at P = 0.05.

Proportion (%, mean ± SE) of Symptom respondents aware of symptoms No. respondents

Wilting leaves 83.2 ± 6.7a 88 Premature ripening 70.4 ± 8.0ab 74 Yellow ooze 66.3 ± 7.4ab 70 Rotting male bud 55.0 ± 6.2b 57 Discoloration of fruit pulp 53.9 ± 9.3b 55

Table 16.4. Awareness of farmers of the mode of spread of Xanthomonas wilt in the 12 districts of Rwanda surveyed in 2009–2010. Means followed by the same letter (a, b) are not significantly different at P = 0.05.

Proportion (%, mean ± SE) of Mode of spread respondents aware of mode of spread No. respondents

Contaminated tools 71.7 ± 7.9a 74 Insects 63.7 ± 6.5a 64 Infected planting material 61.2 ± 7.2a 62 Infected plant parts 55.1 ± 6.8ab 56 Flying animals 37.8 ± 6.3b 38 Cattle and goats 26.8 ± 5.8b 27 Water and soil 23.4 ± 6.7b 24

(i.e. they were low regardless of district). Awareness of contaminated tools as a means 16.3.4 Awareness and use of control of disease spread was uniformly high across methods of Xanthomonas wilt districts. In contrast, awareness of infected planting material as means of Xanthomonas The awareness of different methods of wilt spread was strongly influenced by dis- Xanthomonas wilt control varied among trict. Several districts had low levels of farmers (Table 16.5). Awareness of the awareness of various means of disease destruction of plants by uprooting, removal spread compared with others: Gakenke, 0% of male buds, cutting or burying plants and for transmission by water and soil or cattle tool disinfection as control measures was and goats, up to 29% for transmission by very high. The removal of male buds, while insects or tools; Ngoma, 0% for transmission a method of Xanthomonas wilt control, is by cattle and goats, up to 33% for transmis- also a common agronomic practice among sion by tools or infected planting material; banana growers. However, in Uganda, and Ruhango, 13% for transmission by farmers do not commonly remove male water and soil or cattle and goats, up to 38% buds of beer bananas (AAA-EA), and this for transmission by tools. has facilitated spread of Xanthomonas wilt These levels of awareness are higher (Bagamba et al., 2006; Kagezi et al., 2006). than those reported by Bagamba et al. (2006) Farmers in Uganda cite reduction of beer in Uganda. In their study, the highest levels of quality and labour requirements as reasons awareness of means of disease transmission for not removing male buds from beer were 39% for flying insects, followed by 27% bananas, although in Rwanda, levels of for contaminated tools; the lowest levels of awareness of the removal of male buds for awareness were for flying and walking ani- wilt control and the practice of this method mals (2%), soil (3%) and water (4%). were similar. 136 G. Night et al.

Table 16.5. Awareness of farmers of methods for control of Xanthomonas wilt and their use in the 12 districts of Rwanda surveyed in 2009–2010. Means followed by letters a–c in a column or x, y in a row are not significantly different at P = 0.05.

Proportion (%, mean ± SE) and number of respondents

% aware of control No. % currently using Method of control method respondents control method No. respondents

Uprooting plants 70.4 ± 8.9ax 68 37.1 ± 9.2aby 32 Removal of male buds 68.2 ± 8.8ax 66 55.2 ± 7.3ax 48 Cutting plants 63.5 ± 7.5ax 59 17.9 ± 6.6bcy 27 Burying plants 63.2 ± 9.2ax 62 31.0 ± 9.1aby 28 Tool disinfection 56.8 ± 7.6abx 58 30.2 ± 5.5by 24 Use of pruning knife 34.6 ± 7.3bx 31 30.1 ± 6.5bx 31 Use of forked stick 23.5 ± 6.9bcx 23 15.5 ± 4.9bcx 31 Use of clean planting 20.9 ± 4.5bcx 18 12.9 ± 3.5cx 8 material Breaking with hand 10.2 ± 3.0cx 9 7.4 ± 3.4cx 5 Burning plants 8.8 ± 3.7cx 8 0.0dy 0 Quarantine 8.1 ± 3.1cx 7 6.6 ± 2.9cx 1

Early removal of male buds is recom- (2006) also observed low levels of use of mended for Xanthomonas wilt control as a bleach for tool disinfection in Uganda. The means of preventing insect transmission. destruction of infected plants is labour Use of a pruning knife to do this is not rec- intensive, and lack of labour was cited by ommended as sap on the knife can easily farmers in Uganda as a major reason for not contaminate healthy plants if disinfection is carrying out Xanthomonas wilt control not carried out. Therefore, removal of male practices (Muhangi et al., 2006). For the buds using a (forked) stick or breaking by other methods of Xanthomonas wilt control hand is recommended. In this study, use of (removal of male buds, use of a pruning a pruning knife was practised by 30% of the knife or forked stick, use of clean planting farmers. These observations demonstrate material, breaking by hand and quaran- the importance of communicating clear tine), the proportion of respondents aware messages to farmers. Moreover, as Muhangi of the method was not significantly differ- et al. (2006) pointed out, farmers may not ent from those who were using it. readily relate modes of spread (for example through contaminated tools) to methods of control. 16.4 Conclusion Levels of current usage of control methods were generally less than levels of Banana Xanthomonas wilt has spread widely awareness of the methods. The use of tool in Rwanda. Farmers’ awareness of disease disinfection, destruction of infected plants symptoms, modes of spread and control was by cutting, uprooting, burying and burning appreciable. However, launching awareness were significantly (P = 0.05) lower than the campaigns to enhance these levels would be levels of awareness (Table 16.5). For tool beneficial. There was often a discrepancy disinfection or destruction of infected between awareness of control methods and plants, only about half of the respondents actual practice, especially for tool disinfec- who were aware of the method actually tion and the destruction of infected plants, used it. Tool disinfection using fire is not and there is a need to develop more user- user friendly (i.e. convenient) and house- friendly methods. Moreover, future studies hold bleach (sodium hypochlorite) is not should investigate the factors that influence affordable for most farmers. Muhangi et al. the adoption of Xanthomonas wilt control Banana Xanthomonas Wilt in Rwanda 137

technologies. While awareness of Xantho- Acknowledgements monas wilt symptoms, spread and control was high, there is a need to increase aware- Funding was provided by the Association ness in newly infected and disease-free areas. for Strengthening Agricultural Research in Previous methods of disseminating informa- Eastern and Central Africa through the project tion pertaining to Xanthomonas wilt were ‘Enhanced management of Xanthomonas wilt top-down. Participatory approaches would for sustainable banana productivity in East enhance training and dissemination of con- and Central Africa’. The cooperation of trol technologies and decrease the gap Rwandan banana farmers in furnishing infor- between knowledge and use. mation requested is acknowledged.

References

Aritua, V., Parkinson, N., Thwaites, R., Heeney, J.V., Jones, D.R., Tushemereirwe, W., Crozier J., Reeder, R., Stead, D.E. and Smith J. (2008) Characterization of the Xanthomonas sp. causing wilt of enset and banana and its proposed reclassification as a strain of X. vasicola. Plant Pathology 57, 170–177. Bagamba, F., Kikulwe, E., Tushemereirwe, W.K., Ngambeki, D., Muhangi, J., Kagezi, G.H., Ragama, P.E. and Eden-Green, S. (2006) Awareness of banana bacterial wilt control in Uganda: 1. Farmers’ perspective. African Crop Science Journal 14, 157–164. Biruma, M., Pillay, M., Tripathi, L., Blomme, G., Abele, S., Mwangi, M., Bandyopadhyay, R., Muchunguzi, P., Kassim, S., Nyine, M., Turyagyenda, L. and Eden-Green, S. (2007) Banana Xanthomonas wilt: a review of the disease, management strategies and future research directions. African Journal of Biotechnology 6, 953–962. Kagezi, G.H., Kangire, A., Tushemereirwe, W., Bagamba, F., Kikulwe, E., Muhangi, J., Gold, C.S. and Ragama, P. (2006) Banana bacterial wilt incidence in Uganda. African Crop Science Journal 14, 83–91. Kalyebara, M.R., Ragama, P.E., Kagezi, G.H., Kubiriba, J., Bagamba, F., Nankinga, K.C. and Tushemereirwe, W. (2006) Economic importance of the banana bacterial wilt in Uganda. African Crop Science Journal 14, 93–103. Muhangi, J., Nankinga, C., Tushemereirwe, W.K., Rutherford, M., Ragama, P., Nowakunda, K. and Abeyasekera, S. (2006) Impact of awareness campaigns for banana bacterial wilt control in Uganda. African Crop Science Journal 14, 175–183. Reeder, R., Opolot, O., Muhinyuza, J., Aritua, A., Crozier, J. and Smith, J. (2007) Presence of banana bacterial wilt (Xanthomonas campestris pv. musacearum) in Rwanda. New Disease Reports 14, 52. Smith, J.J., Jones, D.R., Karamura, E., Blomme, G. and Turyagyenda, F.L. (2008) An analysis of the risk from Xanthomonas campestris pv. musacearum to banana cultivation in Eastern, Central and Southern Africa, Bioversity International, Montpellier, France. Tinzaara, W., Gold, C.S., Ssekiwoko, F., Tushemereirwe, W., Bandyopadhyay, R., Abera, A. and Eden- Green, S.J. (2006) Role of insects in the transmission of banana bacterial wilt. African Crop Science Journal 14, 105–110. Yirgou, D. and Bradbury, J.F. (1968) Bacterial wilt of enset (Ensete ventricosum) incited by Xanthomonas musacearum sp. Phytopathology 58, 111–112. Yirgou, D. and Bradbury, J.F. (1974) A note on wilt of banana caused by the enset wilt organism Xanthomonas musacearum. East African Agriculture and Forestry Journal 40, 111–114. 17 Xanthomonas Wilt Incidence in Banana Plots Planted with Asymptomatic Suckers from a Diseased Field Compared with Plots Using Suckers from a Disease-free Zone in North Kivu, Eastern Democratic Republic of Congo

C. Sivirihauma,1* N. Ndungo,1 W. Ocimati2 and G. Blomme2 1Bioversity International, Butembo, Democratic Republic of Congo; 2Bioversity International, Kampala, Uganda

Abstract Xanthomonas wilt has the potential to infect each and every mat in a field. The disease can spread by insect vector transmission, from planting material or through the use of contaminated garden tools. A fallow period of at least 6 months, or the cultivation of a non-host crop, is advised after the removal of a heavily infected banana field. Subsequent replanting needs to be done using clean planting material. Such a strategy is not, however, easily applicable in villages were land is a limiting factor and seeds of non-host crops are not readily available. This study assessed the use of asymptomatic lateral shoots of two Musa genotypes, ‘Vulambya’ (AAA-EA) and ‘Kamaramasenge’ (AAB), obtained from heavily infected fields as a source of planting material. This approach depends on the observation that incomplete systemicity has been observed in mats where the mother plant became infected through the inflorescence, meaning that not all lateral shoots necessarily acquire the infection. Suckers obtained in a disease-free region were used as a control. Disease incidences in plots established with asymptomatic suckers obtained from diseased fields were 44% for ‘Vulambya’ and 47% for ‘Kamaramasenge’, while slightly higher incidences (66% for ‘Vulambya’ and 59% for ‘Kamaramasenge’) were observed for plots established with suckers obtained from a disease-free zone. The results from this experiment were not very encouraging and demonstrate that controlling this disease under small-scale farmer settings in central Africa needs a multifaceted, coordinated and concerted effort.

17.1 Introduction been restricted to Ethiopia up to the turn of the century (Yirgou and Bradbury, 1968, 1974), but Xanthomonas wilt of banana (Musa spp.) in 2001, the disease appeared in central and enset (Ensete ventricosum) caused by Uganda and in North Kivu, eastern Democratic Xanthomonas campestris pv. musacearum had Republic of Congo (DR Congo) (Tushemereirwe

* E-mail: [email protected]; c. [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 138 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Xanthomonas Wilt in Plots with Asymptomatic Suckers 139

et al., 2003, 2004; Ndungo et al., 2004, 2006). It remotely located and poor in resources. has since spread to Tanzania, where it was Further, all banana plots can be infected reported in 2006 (Karamura et al., 2008; Carter across whole villages and farmers cannot et al., 2010), Kenya (2007) (Mbaka et al., 2007; easily leave their land under fallow or do not Carter et al., 2010), Rwanda (2006) (Reeder et al., have the required seeds to use break crops. 2007; Karamura et al., 2008) and Burundi (2010) (Carter et al., 2010). The disease is mainly transmitted 17.2 Materials and Methods through planting materials, contaminated garden tools (e.g. during de-leafing and de- On-farm experiments were established in Beni suckering) and insect vectors (Yirgou and Territory, North Kivu in eastern DR Congo to Bradbury, 1974; Eden-Green, 2004; Gold and assess Xanthomonas wilt incidence in plots Bandyopadhyay, 2005; Tinzaara et al., 2006; planted with asymptomatic suckers obtained Karamura et al., 2008; Addis et al., 2010). Disease from a heavily diseased field. Plots planted transmission may also occur through brows- with healthy suckers obtained from a disease- ing domestic animals, which are omnipresent free zone served as controls. in small-scale central African farms, large The on-farm experiments were estab- birds, e.g. hornbills (Bucerotidae), that forage lished at three sites: Kisungu at 1743 m above in the plantations and fruit bats (Pteropodidae) sea level (masl) and 2.5973°N, 29.25216°E; (Buddenhagen, 2006; Karamura et al., 2008). Kisungu, Communauté Baptiste au Centre Planting materials, i.e. suckers, are de l’Afrique (Kisungu CBCA) at 1716 masl mainly obtained from farmers’ own and and 2.5973°N, 29.25216°E; and Vuhatsia at neighbouring fields in central African small- 1715 masl and 2.6014°N, 29.25168°E. The scale farmer settings (Ndungo et al., 2008). average annual temperature at these sites The use of tissue-cultured plants is not com- was 19°C, while the average annual rainfall mon (Ndungo and Lubanga, 2006; Ndungo was 1038 mm (from 2009 to 2011) and distrib- et al., 2008). The complete uprooting of dis- uted over two rainy seasons, i.e. September– eased fields has been advocated when inci- December and March–June; the soil was dence levels of Xanthomonas wilt are higher clayey (ENRA, 2012). than 20% (see Chapter 14, this volume). In A field with an initial disease incidence of addition, a fallow period or a rotation cycle at least 65% was selected at each site. The main with a non-host substitute crop for at least Musa cultivars found across the experimental 6 months has been advocated before clean fields were the highland cooking banana banana suckers can be planted without risk ‘Vulambya’ (Musa AAA-EA, 47%), the dessert of infection by the disease (Brandt et al., 1997; banana ‘Kamaramasenge’ (AAB, 21%), the Mwebaze et al., 2006; Turyagyenda et al., plantain ‘Musilongo’ (AAB, 12%), the dessert 2008). This strategy, however, becomes diffi- banana ‘Kitika sukari’ (AAA, 9%), the highland cult to implement in regions where banana is banana ‘Kiware’ (AAA-EA, 6%) and the plan- the main staple food and banana farms across tain ‘Kotina’ (AAB, 5%). Asymptomatic suckers whole villages are infected. of the popular cultivars ‘Vulambya’ (AAA-EA) This study, therefore, assessed the use of and ‘Kamaramasenge’ (AAB) were selected for asymptomatic lateral shoots obtained from the experiment. These suckers were marked heavily infected fields as a source of plant- and carefully uprooted using clean garden ing material. Incomplete systemicity has tools, i.e. hoes and machetes. A fire was estab- been observed in mats where the mother lished at each of the experiments to disinfect plant became infected through the inflores- the tools after each sucker was uprooted. Addi- cence, in which case not all lateral shoots tional paring, i.e. cutting off the cord roots and necessarily become infected (Ocimati et al., paring back the corm surface with a knife, was 2013). Suckers were planted within days of carried out using disinfected machetes. uprooting a heavily diseased field. This Twenty eight asymptomatic suckers experiment mimics a worst case scenario in per cultivar were obtained in the diseased small-scale banana farming systems that are experimental plot at Kisungu, 20 per 140 C. Sivirihauma et al.

cultivar in Kisungu CBCA and 20 per May 2010 to May 2011. All observed sympto- cultivar in Vuhatsia. All mats (both symp- matic mats were systematically uprooted to tomatic and asymptomatic) were subse- remove all sources of inoculum. quently uprooted in the three experimental fields. Every corm was carefully uprooted to remove all sources of inoculum from the 17.3 Results and Discussion soil. Plant/mat debris was left in between the rows, as mulch, in the experimental Relatively few diseased plants were fields. As controls, 68 healthy suckers of the observed during the first 6 months after same two cultivars were obtained from the establishing the experiment, but from the Université Catholique du Graben (UCG) seventh month onwards disease incidence Musa collection in Butembo (1815 masl, increased steadily for all treatments (Fig. 17.1). 0.11786°N, 29.2587°E), North Kivu, a disease- At 13 months after the experiment was free zone. A total of 28 plants per cultivar established, disease incidence in plots were established in Kisungu, 20 in Kisungu established with asymptomatic suckers CBCA and 20 in Vuhatsia. All of the suckers obtained from diseased fields were 44% for were planted within 2 days of the field ‘Vulambya’ and 47% for ‘Kamaramasenge’; bring uprooted. The experimental fields slightly higher incidences, 66% and 59%, were located in undulating terrain (slope respectively, were observed for plots estab- of 15%), and each was divided in two across lished with suckers obtained from a disease- altitude lines. Asymptomatic suckers free zone (Table 17.1). However, there were obtained from the diseased field were planted no significant differences (P < 0.05) in disin one half, while the suckers obtained from a ease incidence between either the two treat- disease-free zone were planted in the other ments or the two cultivars. half. The halves were randomly assigned. The The asymptomatic planting material cultivars were planted in rows (along altitude obtained from the heavily infected fields lines) of 14 plants at Kisungu and 10 plants at is obviously a possible source of infection Kisungu CBCA and Vuhatsia. in the experimental fields. The infections No disease control was carried out in on plants derived from clean suckers in neighbouring banana fields, which all had disease-free zones could also have origi- disease incidence levels of >65%. However, nated from banana plant debris that was all experimental fields were fenced off to spread between banana rows. Wounds on prevent the entry of the browsing small the pared corms are possible entry routes ruminants that are omnipresent in the for soil-borne infections. The disease could Kisungu area and could transmit the disease also have been transferred by large birds, (Karamura et al., 2008). Hand/hoe weeding e.g. hornbills, which eat ripe fruits. Their was practised by the farmers who were sharp claws can penetrate leaf or petiole responsible for the experimental fields and tissue while foraging in the plantations. only dead/dried out banana leaves were Transmission through small ruminants can pruned to prevent any infection through this be excluded as all experimental fields were practice. On the bunches, early male bud tightly fenced off, but the omnipresence removal was carried out using a forked of the disease in adjacent fields and the wooden stick. No intercropping was done in non-implementation of control actions by the experimental fields as land preparation neighbouring farmers kept inoculum activities for annual crops at the onset of the levels in the experimental zones at very rainy seasons, e.g. weeding and banana leaf high levels. removal to reduce shade levels, could trans- Regular weeding was carried out by the mit the disease. farmers who were responsible for the experi- All plants/mats were monitored at mental plots. Although farmers were advised weekly intervals for Xanthomonas wilt to carry out superficial hand weeding, some symptoms for a period of 13 months, from of the banana roots could nevertheless Xanthomonas Wilt in Plots with Asymptomatic Suckers 141

30 disease incidence (%) disease incidence 20

10 Cumulative Cumulative 0 1234 5678910111213 Month of observation

‘Vulambya’ asymptomatic suckers, diseased field ‘Kamaramasenge’ asymptomatic suckers, diseased field ‘Vulambya’ suckers, disease-free zone ‘Kamaramasenge’ suckers, disease-free zone

Fig. 17.1. Cumulative disease incidence in plots established with asymptomatic suckers obtained from diseased fields and suckers obtained from a disease-free zone. Experiments were established using two cultivars: the highland cooking banana ‘Vulambya’ and the dessert banana ‘Kamaramasenge’.

Table 17.1. Proportion of symptomatic mats (%) for the cultivars ‘Vulambya’ and ‘Kamaramasenge’ according to source of planting material at 13 months after planting.

Source of planting material Cultivar Proportion of infected mats (%)

Asymptomatic suckers obtained from the ‘Vulambya’ 44.3 diseased field ‘Kamaramasenge’ 46.9 Suckers obtained from a disease-free zone ‘Vulambya’ 65.5 ‘Kamaramasenge’ 59.3 LSD (P = 0.05) 25.4a CV (%) 23.6 aNot significant at P = 0.05. have been damaged through the occasional days after field uprooting. The pathogen is use of hoes, and infections could have also reported to survive in the soil (or occurred by this means. debris) for up to 4 weeks, during which it Although the initial mat uprooting was could serve as primary inoculum (Mwebaze carefully carried out, some re-sprouting was et al., 2006; Karamura et al., 2008). Unster- nevertheless observed, indicating that some ilized soil (containing bacterial ooze) in corm pieces were still present in the soil plant nurseries has been observed to cause when the suckers were planted. Complete death of seedlings within weeks of infection mat uprooting is especially difficult in the (Karamura et al., 2008). clayey/hard soils around Kisungu. The The results from this experiment were experimental plots were established on hilly not very encouraging, all the more so given terrain and bacterial ooze could have been that 13 months after establishment of the washed down the slope during the initial experiment the disease incidence was still on 142 C. Sivirihauma et al.

the rise. This clearly demonstrated that the Acknowledgements control of Xanthomonas wilt is a multifaceted endeavour under small-scale farmer The authors would like to thank the Directorate conditions in eastern DR Congo, and a con- General for Development (DGD, Belgium) certed and coordinated rigorous implemen- through the Consortium for Improving tation of control packages is needed across Agriculture-based Livelihoods in Central whole villages. Africa (CIALCA) project for funding this work.

References

Addis, T., Turyagyenda, L.F., Alemu, T., Karamura, E. and Blomme, G. (2010) Garden tool transmission of Xanthomonas campestris pv. musacearum on banana (Musa spp.) and enset in Ethiopia. Acta Horticulturae 879, 367–372. Brandt, S.A., Spring, A., Hiebsch, C., McCabe, J.T., Tabogie, E., Diro, M., Wolde-Michael, G., Yntiso, G., Shigeta, M. and Tesfaye, S. (1997) The Tree Against Hunger: Ensete-based Agricultural Systems in Ethiopia. American Association for the Advancement of Science, Washington, DC. Buddenhagen, I. (2006) Managing banana bacterial wilts in Latin America. In: Karamura, E., Osiru, M., Blomme, G., Lusty, C. and Picq, C. (eds) Developing a Regional Strategy to Address the Outbreak of Xanthomonas Wilt in East and Central Africa. Proceedings of the Banana Xanthomonas Wilt Regional Preparedness and Strategy Development Workshop, Kampala, Uganda, 14–18 February 2005. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France, pp. 23–25. Carter, B.A. et al. (2010) Identification of Xanthomonas vasicola (formerly X. campestris pv. musacearum), causative organism of banana Xanthomonas wilt, in Tanzania, Kenya and Burundi. Plant Pathology 59, 403. Eden-Green, S. (2004) How can the advance of banana Xanthomonas wilt be halted? InfoMusa 13(2), 38–41. ENRA (2012) Rapport Synthèse Annuelle d’Observation Météorologique pour les Années 2009 et 2011. Enzyme Refiners Association, Beni, Democratic Republic of Congo. Gold, S.G. and Bandyopadhyay, R. (2005) Identifying Insect Vectors and Transmission Mechanisms for Banana Xanthomonas Wilt. R8484 (ZA0695 and ZA0714), Final Technical Report, 1 April 2005–31 December 2005. Crop Protection Programme, Department for International Development (DFID), London, UK. Available at: http://researchintouse.com/nrk/RIUinfo/outputs/R8484_FTR.pdf (accessed 25 April 2013). Karamura, E.B., Turyagyenda, F.L., Tinzaara, W., Blomme, G., Molina, A. and Markham, R. (2008) Xanthomonas Wilt (Xanthomonas campestris pv. musacearum) of Bananas in East and Central Africa. Diagnostic and Management Guide. Fountain Publishers, Kampala, Uganda. Mbaka, J., Ndungo, V. and Mwangi, M. (2007) Outbreak of Xanthomonas wilt (Xanthomonas campestris pv. musacearum) on banana in Kenya. In: Recent Advances in Banana Crop Protection for Sustainable Production and Improved Livelihoods. Programme and Abstracts, ISHS/ProMusa Symposium, Greenway Woods Resort, White River, 10–14 September 2007. Bioversity International, Montpellier, France, p. 58. Mwebaze, J.M., Tusiime, G., Tushemereirwe, W.K. and Kubiriba, J. (2006) The survival of Xanthomonas campestris pv. musacearum in soil and plant debris. African Crop Science Journal 14, 121–127. Ndungo, V. and Lubanga, D.L. (2006) Banana Xanthomonas wilt in DR-Congo. In: Karamura, E., Osiru, M., Blomme, G., Lusty, C. and Picq, C. (eds) Developing a Regional Strategy to Address the Outbreak of Xanthomonas Wilt in East and Central Africa. Proceedings of the Banana Xanthomonas Wilt Regional Preparedness and Strategy Development Workshop, Kampala, Uganda, 14–18 February 2005. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France, 17–18. Ndungo, V., Bakelana, K., Eden-Green, S. and Blomme, G. (2004) An outbreak of banana Xanthomonas wilt (Xanthomonas campestris pv. musacearum) in the Democratic Republic of Congo. InfoMusa 13(2), 43–44. Xanthomonas Wilt in Plots with Asymptomatic Suckers 143

Ndungo, V., Eden-Green, S., Blomme, G., Crozier, J. and Smith, J. (2006) Presence of banana Xanthomonas wilt (Xanthomonas campestris pv. musacearum) in the Democratic Republic of Congo (DRC). Plant Pathology 55, 294. Ndungo, V., Fiaboe, K.K.M. and Mwangi, M. (2008) Banana Xanthomonas wilt in the DR Congo: impact, spread and management. Journal of Applied Biosciences 1, 1–7. Ocimati, W., Ssekiwoko, F., Karamura, E., Tinzaara, W., Eden-Green, S. and Blomme, G. (2013) Systemicity of Xanthomonas campestris pv. musacearum and time to disease expression after inflorescence infection in East African highland and Pisang Awak bananas in Uganda. Plant Pathology 62, 777–785. Reeder, R.H., Muhinyuza, J.B., Opolot, O., Aritua, V., Crozier, J. and Smith, J. (2007) Presence of banana bacterial wilt (Xanthomonas campestris pv. musacearum) in Rwanda. Plant Pathology 56, 1038. Tinzaara, W., Gold, C.S., Tushemereirwe, W., Bandyopadhyay, R. and Eden-Green, S.J. (2006) Possible role of insects in the transmission of banana Xanthomonas wilt. In: Saddler, G., Elphinstone, J. and Smith, J. (eds) Programme and Abstract Book of the 4th International Bacterial Wilt Symposium, 17–20 July 2006, The Lakeside Conference Centre, Central Science Laboratory, York, UK, p. 60. Turyagyenda, L.F., Blomme, G., Ssekiwoko, F., Karamura, E., Mpiira, S. and Eden-Green, S. (2008) Rehabilitation of banana farms destroyed by Xanthomonas wilt in Uganda. Journal of Applied Biosciences 8, 230–235. Tushemereirwe, W.K., Kangire, A., Smith, J., Ssekiwoko, F., Nakyanzi, M., Kataama, D., Musiitwa, C. and Karyaija, R. (2003) An outbreak of bacterial wilt on banana in Uganda. InfoMusa 12(2), 6–8. Tushemereirwe, W., Kangire, A., Ssekiwoko, F., Offord, L.C., Crozier, J., Boa, E., Rutherford, M. and Smith, J.J. (2004) First report of Xanthomonas campestris pv. musacearum on banana in Uganda. Plant Pathology 53, 802. Yirgou, D. and Bradbury, J.F. (1968) Bacterial wilt of enset (Ensete ventricosum) incited by Xanthomonas musacearum. Phytopathology 58, 111–112. Yirgou, D. and Bradbury, J.F. (1974) A note on wilt of banana caused by the enset wilt organism Xanthomonas musacearum. East African Agricultural and Forestry Journal 40, 111–114. 18 Coffee/Banana Intercropping as an Opportunity for Smallholder Coffee Farmers in Uganda, Rwanda and Burundi

L. Jassogne,1,2 * A. Nibasumba,1,2,3 L. Wairegi,1,4 P.V. Baret,2 J. Deraeck,2 D. Mukasa,1 I. Wanyama,1 G. Bongers1 and P.J.A. van Asten1 1International Institute of Tropical Agriculture (IITA), Kampala, Uganda; 2Université Catholique de Louvain (UCL), Louvain-le-Neuve, Belgium; 3Institut des Sciences Agronomiques du Burundi (ISABU), Bujumbura, Burundi; 4CAB International, Nairobi, Kenya

Abstract Coffee is a primary cash crop and banana a primary food crop in the East African highlands region, including Rwanda, Burundi, north-west Tanzania, west and central Kenya and eastern Democratic Republic of Congo. These two crops often occur on the same smallholder farms, either planted on separate plots or intercropped. In certain countries, intercropping coffee and banana is voluntarily practised, while in others governments recommend growing these crops on separate plots. Even if intercropping coffee and banana leads to a decrease in coffee yields under certain conditions, it gives certain advantages to smallholder farmers. Intercropping offers higher returns per unit of land compared with coffee alone. Farmers increasingly resort to intercropping as a result of declining farm sizes, and in an effort to reduce risks related to income and food security. Researchers have identified the potential opportunity for intercropping coffee and banana for smallholder farmers, but many public and private development partners have not yet fully embraced this technology. The benefits and constraints of intercropping coffee and banana are discussed based on results from Burundi, Rwanda and Uganda. The aim is to understand the drivers of this system in Uganda, where intercropping is a common practice, so that a framework can be suggested to develop research and recommendations for intercropping coffee and bananas in Burundi and Rwanda, where intercropping is under experimentation and has high potential.

18.1 Introduction predominantly on smallholder farmers. For example, in Uganda there are officially Coffee is an important export product, with 1.3 million smallholder coffee farmers, with revenues of US$262 million in Uganda, 90% whose average farm size ranges from US$56 million in Rwanda and US$16.7 mil- <0.5 ha to 2.5 ha (UCDA, 2011). Furthermore, lion in Burundi in 2009/10 (Government of the coffee industry employs over 3.5 million Rwanda, 2011; AEO, 2012). In these three families through coffee-related activities countries, the production of coffee relies (UCDA, 2011).

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 144 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Coffee/Banana Intercropping for Coffee Farmers 145

A large proportion of smallholder farm- intercropping is a cropping system that is ers growing coffee also grow bananas. Banana spontaneously practised by farmers and is an important food and cash crop in the research has shown that it can provide region. In Uganda it is the most important many benefits to smallholder farmers (van staple crop, with a production of 9,512,000 t Asten et al., 2011). It gives food for the in 2009 (FAOSTAT, 2012). In Rwanda, banana farmer through banana production, shade production was 2,993,480 t and in Burundi to the coffee from the banana plants and 620,028 t in 2009 (FAOSTAT, 2012). Bananas an income to the farmer. With this knowl- provide food throughout the year and the edge, research in Uganda, Rwanda and surplus is sold, resulting in a continuous Burundi was started to characterize popu- small income. lar coffee/banana intercropped systems. In In this region, coffee and bananas on this chapter, a summary is given of the smallholder farms can be found both mono- recent results from various studies done on cropped and intercropped. Intercropped cof- coffee/banana intercropping in the region. fee and banana fields are common in Uganda, but can also be found sparsely in Rwanda and Burundi, although monocropping is widely recommended in the latter two coun- 18.2 Materials and Methods tries. Even though extension material in Uganda still recommends monocropping for The chapter is based on data collected during coffee, the benefits of intercropping coffee a survey carried out in Uganda and Rwanda, with bananas are recognized. A study by van perception studies in Uganda and Rwanda, Asten et al. (2011) found good marginal rates and field experiments in Burundi. of return when banana was added to mono- To characterize the perceptions of cof- cropped coffee systems in Uganda, which fee/banana intercropping by coffee small- suggests that intercropping is more profitable holder farmers and other stakeholders (in terms of total productivity) than along the coffee value chain, in-depth, semi- monocropping. structured interviews were held in Uganda When coffee was introduced by colo- and Rwanda (Deraeck, 2011; Jassogne et al., nists, it became the most important cash crop 2013). Forty interviews were done in Uganda in Uganda, Rwanda and Burundi, and it con- (eight managers, eight extension staff and tributed significantly to those national econo- 24 smallholder coffee farmers). In Rwanda, mies. The aim of governments at that time 46 interviews were done (eight managers, was sustaining and increasing coffee produc- eight extension staff and 30 farmers). tion and quality, and research then showed In addition to the two perception studies, that the best systems to achieve these goals the chapter also draws on a study done in were high-input monocropped coffee sys- south, west and east Uganda by van Asten tems in full sun. However, the conditions in et al. (2011). During this study, 152 coffee plots smallholder farming systems do not favour were surveyed. The data were collected high-input supply and management and through structured interviews, field measure- numerous studies have shown that under ments and observations. The study quanti- suboptimal conditions, shaded coffee sys- fied the agronomic productivity of banana tems are more sustainable, even if yields can and coffee monocropping and intercropping, be lower (DaMatta, 2004). None the less, to with the aim of assessing the profitability of make sure that the goals were met, govern- intercropping in smallholder systems in ments were highly involved in coffee produc- regions growing Arabica (east Uganda) and tion and promoted full-sun monocropped Robusta (south and west) cultivars. systems. For Burundi, the results given in the In Uganda, coffee/banana intercrop- chapter are based on an ongoing study by ping became common practice in the 1980s Nibasumba. The first experiment compared when food security was low, and thereafter, plant performance and yield of coffee mono- when coffee prices declined. Coffee/banana crop plots, both near to and far from bananas, 146 L. Jassogne et al.

to quantify the influence that each crop had bananas throughout the year, as well as a on the other (Nibasumba et al., 2011), based small continuous income from the surplus. on field measurements and observations. Furthermore, once or twice a year, depending on the location in Uganda, the smallholder farmer gets a ‘cash boom’ from the coffee. The study by van Asten et al. (2011) showed that 18.3 Results and Discussion for Robusta and Arabica farmers in Uganda, intercropping coffee with banana was more In Uganda and Rwanda, during a perception profitable than either monocrop. This was the study on intercropping coffee and banana, case even though the bananas in a Robusta– Jassogne et al. (2013) and Deraeck (2011) banana intercropped field suffered and their found that farmers would intercrop for six yield value decreased – while the opposite major reasons. These reasons, in decreasing occurred in an Arabica–banana intercropped order of importance, are: (i) cash and food are field (Fig. 18.1). These contrasting effects of provided from the same piece of land under intercropping on banana yields are because conditions of land scarcity, and there is Robusta coffee trees are more demanding in increased income; (ii) coffee in banana shade terms of space than Arabica trees and so are is more resilient to drought; (iii) banana pro- more competitive when intercropped with vides in situ mulching material for both crops; bananas. Intercropping had no significant (iv) bananas in the intercrop provide motiva- effect on coffee yields. tion to manage coffee well when it is too The second reason for intercropping young to produce; (v) coffee under shade mentioned by farmers was that coffee would gives larger berries; and (vi) additional ani- be more resilient to drought when grown mal feed is supplied from bananas grown in under banana shade. Farmers explained that coffee fields. It seems that any differences when coffee trees are under banana shade between Rwanda and Uganda do not lie at they look greener, even during a drought the level of the perceptions of smallholder period, than do coffee trees in full sun. This farmers, but at the level of the perceptions of will become more important as drought stakeholders higher up the coffee value chain. events become more prevalent (van Rikxoort The first reason for intercropping indi- et al., 2011). cates that intercropping coffee and banana The third reason for intercropping was increases food security of the farmer. In a situ- that banana would provide in situ mulching ation where land becomes scarce, intercrop- material for the coffee. In Rwanda, Burundi ping cash and food crops is a way to manage and Uganda, mulching material has increas- risks. The farmer gets food from his or her ingly become scarce and expensive. In the

5000 5000 4500 4500 /ha) /ha) $ $ 4000 4000

US 3500 3500 3000 3000 2500 2500 2000 2000 1500 1500 1000 1000 500 500 Annual yield value (US Annual yield value ( 0 0 Coffee monocrop Intercrop Banana monocrop Coffee monocrop Intercrop Banana monocrop Arabica, east Uganda Robusta, south-west Uganda Banana Coffee

Fig. 18.1. Annual yield value (based on 2006/7 coffee prices) of coffee and banana from intercropped and monocropped systems in Uganda. Separate data are given for Arabica systems (Mt Elgon, east Uganda) and Robusta systems (south and west Uganda). (Source: van Asten et al., 2011) Coffee/Banana Intercropping for Coffee Farmers 147

past, mulch material could be found in wet- with coffee, the farmer gets food and money lands, but at present, due to increasing popu- from the field much more quickly and is lation pressure, this land is becoming more motivated to manage the bananas. Indirectly, populated and exploited. What is more, in the coffee benefits from this management. Rwanda and Burundi, there was a policy, still Fifthly, the thickness of berries can be an largely in place, that all the banana mulch indicator of coffee quality, and when coffee had to be exported to the coffee fields to make grows under shade, as in intercropping, the sure of sustaining coffee production of the coffee berries have more time to fill and the farm. In the long term then, banana fields quality of coffee increases. This is especially would produce less and less while coffee the case under suboptimal management con- fields would benefit due to the recycling of ditions, as is the case for most smallholder the nutrients from the banana fields. Putting farmers (DaMatta, 2004). A study done by coffee and banana together on one field Nibasumba et al. (2011) in Burundi shows that would decrease the labour needed to get the coffee, when shaded by bananas, produces mulch from one field to another, or from any heavier berries (Fig. 18.2). wetland to the coffee field. When grown The last reason, farmers explained, was together, coffee and banana will benefit from that when bananas are intercropped with cof- the banana mulch, which has a higher bio- fee, they provide additional animal feed for mass than the mulch from coffee. the farm in the form of banana pseudostems. The fourth reason for intercropping indi- This was mentioned in the Mt Elgon area in cates that when coffee is not yet productive, Uganda, where grazing land is scarce and the farmer is motivated to take care of the cof- livestock tends to be stall-fed. In this case, the fee field if banana is intercropped. Depending farmer trades off the benefits of mulching on the cultivar, coffee can be fully productive against the benefits of feeding livestock. 3–5 years after planting. During these years, Even though many farmers recognize even if the farmer does not get any returns the benefits from intercropping coffee and from the coffee, the field must still be man- banana, not all coffee farmers intercrop aged to make sure that it can grow. However, bananas. From the interviews, it seemed that a smallholder also needs to attend to other competition for light, water and nutrients crops on the farm and, due to time or labour were the most limiting factors in the inter- shortage, tends to neglect crops that are not cropped system. Too much shade will be productive. When banana is intercropped counterproductive for the coffee plants and

200 a 180 b a 160 a 140 120 100 80 60 40 Weight of 100 berries (g) 20 0 Buyenzi Kirimiro Close to banana Far from banana

Fig. 18.2. Weight of 100 berries in two coffee growing regions in Burundi picked from coffee trees close to bananas (shaded) and far from bananas (full sun). The weight of 100 berries is an indicator of coffee quality, where large berries indicate better quality. Bars with the same letter within growing regions are not significantly different at P = 0.05. 148 L. Jassogne et al.

the first practice that was perceived to be quality. Uganda liberalized its coffee market necessary to sustainably intercrop coffee and around 1991, Rwanda around 1998 and banana was maintaining the correct densities Burundi around 2008. Before those dates, for both crops. In addition, suckers of governments were responsible for the whole bananas need to be managed continuously coffee value chain, and there were strict rules (de-suckering) to minimize competition. on how to manage the crop for maximum Secondly, banana cultivars that are tall and production. Smallholder farmers would be produce a small amount of suckers should be fined if they did not follow the recommended chosen. Thirdly, soil fertility has to be man- practices and so many smallholder farmers aged constantly through the use of mulch, considered coffee to be a government crop adding manure and/or fertilizers. In the per- and did not feel any ownership of it, even if it ception study done in Uganda, 91% of the was growing on their farm. Because they did farmers used manure but explained that they not have any ownership over the crop, they did not have enough of it. In the same study, tended to neglect it and not manage it 58% of the farmers explained that they had properly unless they saw the benefits in used fertilizer in the past but that they lacked terms of income security. When the coffee the capital to continue this practice. Finally, sector was liberalized, government involve- to reduce competition, good crop management decreased and farmers had more free- ment practices are necessary, such as weed- dom in how to manage their crops. In Uganda, ing, water harvesting and pruning. So even because liberalization of the coffee sector though coffee/banana intercropping seems happened in the early 1990s, and because the to have a lot of advantages for the farmer, it prices of coffee are increasing at present, also has a lot of constraints and limiting fac- smallholder farmers see the benefits of grow- tors at field and farm level. Other external ing coffee and are motivated. In Burundi, the factors also play an important role for the sus- liberalization of the coffee sector only hap- tainable practice of this system. pened recently and so farmers do not yet feel The studies in Uganda and Rwanda ownership of their coffee. The situation in showed that there were many disincentives Rwanda lies in between those of Uganda and to intercropping coffee and banana at the Burundi. institutional level. First of all, research and Burundi is also one of the most food- extension programmes are largely operating insecure countries on the African continent. separately, so there is no clear agreement on Consequently, smallholder farmers want to who should be doing the research on inter- invest more in food crops than in cash crops. cropped systems. Moreover, budgets are Because of this food insecurity and also because limited. For the most part, research on the of the lack of ownership that is felt towards cof- two crops is done independently, yet they are fee, the Burundian government is concerned grown together in the majority of cases. that coffee production will be dramatically Research on the coffee/banana intercrop sys- affected, which could have a large negative tem is, then, minimal. impact on the national economy. Therefore, the Monocropping and the intercropping of extension service still highly recommends coffee and banana are widespread in Uganda. monocropping coffee. Its perception is that if In Rwanda and Burundi, the monocropping coffee and banana intercropping is allowed, of coffee is the dominant practice. When look- farmers will associate banana with coffee with- ing at research and extension outputs, coffee out taking into consideration management monocropping is strongly recommended in practices such as planting at the appropriate all three countries, except for young planta- densities, the need for de-suckering of bananas, tions in Uganda, where intercropping with weeding, pruning and soil fertility manage- food crops can be recommended. ment. Under such conditions, competition Coffee contributes significantly to between the two crops will increase and coffee national economies. Hence, the governments production will suffer (Plate 16). of these countries want to increase, sustain However, even though coffee mono- and protect their coffee production and cropping in Rwanda and Burundi is still Coffee/Banana Intercropping for Coffee Farmers 149

recommended, national programmes have are challenges that also need to be tackled at decided to start their own research on international level. To successfully intercrop coffee cropping coffee and banana as this system and banana, competition for light, water and seems to be so beneficial for smallholder nutrients between crops needs to be man- farmers. aged. This can be done by adapting crop densities, choosing the appropriate banana cultivar, managing banana suckers and using optimal crop practices such as weeding and 18.4 Conclusion pruning. In addition, management of soil fertility through optimal nutrient recycling, Coffee/banana intercropping has many ben- mulching and adding manure and fertilizers efits for the smallholder farmer that could be is required. At the national level, research and beneficial at national level as well. Increasing policies need to be revised to create condi- food security and adapting to climate change tions for coffee/banana intercropping.

References

AEO (2012) African Economic Outlook: Uganda. Available at: http://www.africaneconomicoutlook.org/en/ countries/east-africa/uganda/ (accessed 22 January 2012). DaMatta, F.M. (2004) Ecophysiological constraints on the production of shaded and unshaded coffee: a review. Field Crops Research 86, 99–114. Deraeck, J. (2011) Le potentiel de l’association banane–café au Rwanda: une analyse systémique. MSc thesis, Université Catholique de Louvain, Louvain-la-Neuve, Belgium. FAOSTAT (2012) Online statistical database. Food and Agriculture Organization of the United Nations, Rome. Available at: http://faostat.fao.org/ (accessed 22 January 2012). Government of Rwanda (2011) Rwanda National Export Strategy (NES), March 2011. Ministry of Trade and Industry, Government of Rwanda, Kigali, Rwanda. Available at: http://www.minicom.gov.rw/IMG/ pdf/National_Export_Strategy.pdf (accessed 25 April 2013). Jassogne, L., van Asten, P., Wanyama, I. and Baret, P.V. (2013) Perceptions and outlook on intercropping coffee with banana as an opportunity for smallholder coffee farmers in Uganda. International Journal of Agricultural Sustainability 11, 144–158. Nibasumba, A., Jassogne, L., van Asten, P. and Baret, P. (2011) Plant and soil interactions between adjunct coffee and banana plots in Burundi: preliminary assessments in farmer field conditions. In: Conference Abstracts. Challenges and Opportunities for Agricultural Intensification of the Humid Highland Systems of sub-Saharan Africa, CIALCA Conference, Kigali, Rwanda, 24–27 October 2011, p, 146, abstract 122. Available at: http://es.slideshare.net/petelinckova/intensif-afr (accessed 25 April 2013). UCDA (2011) Uganda Coffee Development Authority: Production. Kampala, Uganda. Available at: http:// www.ugandacoffee.org/index.php?page&a=15 (accessed 16 March 2011). van Asten, P.J.A., Wairegi, L.W.I., Mukasa, D. and Uringi, N.O. (2011) Agronomic and economic benefits of coffee–banana intercropping in Uganda’s smallholder farming systems. Agricultural Systems 104, 326–334. van Rikxoort, H., Jassogne, L., Laderach, P. and van Asten, P. (2011) Building “climate smart” East African coffee production systems. In: Challenges and Opportunities for Agricultural Intensification of the Humid Highland Systems of sub-Saharan Africa. CIALCA Conference, Kigali, Rwanda, 24–27 October 2011, p. 29, abstract 16. Available at: http://es.slideshare.net/petelinckova/intensif-afr (accessed 25 April 2013). 19 The Use of Trees and Shrubs to Improve Banana Productivity and Production in Central Uganda: An Analysis of the Current Situation

S. Mpiira,1* C. Staver,2 G.H. Kagezi,1 J. Wesiga,3 C. Nakyeyune,4 G. Ssebulime,5 J. Kabirizi,1 K. Nowakunda,1 E. Karamura,6 and W.K. Tushemereirwe1 1National Agricultural Research Organisation (NARO), Kampala, Uganda; 2Bioversity International, Montpellier, France; 3Volunteer Efforts for Development Concern (VEDCO), Kampala, Uganda; 4SSC-Vi Agroforestry, Kampala, Uganda; 5Kyankwanzi District Local Government, Kiboga, Uganda; 6Bioversity International, Kampala, Uganda

Abstract In central Uganda, in spite of poor soils and high pest pressure, bananas are a primary source of household food and income. Farmers are increasingly challenged by the need to maintain banana productivity and to expand production for nearby markets. Traditional inputs – grass mulch, crop residue and animal manure – have become scarce and expensive. We posed the question of whether on-farm trees and shrubs can be used as a source of fodder and mulch, and for improved soil and microclimate could be harnessed to improve banana productivity. A survey was conducted in three districts of the Central Region of Uganda – Kiboga, Sembabule and Nakaseke – to characterize bananas, livestock, trees and shrubs on farms, and the linkages among these components in farm productivity. In each district, 70 households were interviewed and field sampling was conducted on the farms of 30 of these. Across the three districts, farms varied in their land area, in the numbers of banana mats, trees and shrubs they contained, and in ownership of ruminant animals. They also differed in their hiring or selling of labour, the use of mulch on the banana crop and whether or not the crop was grown under tree shade. A total of 49 tree species was counted, with Ficus natalensis, Albizia coriaria, Markhamia lutea, Mangifera indica and Persea americana being the most common. Farmers readily identified good neighbour trees for banana (Ficus natalensis and Albizia coriaria), tree-friendly banana cultivars – which included ‘Kibuzi’, ‘Ndibwabalangira’ ‘Nakitembe’, ‘Mbwazirume’ and ‘Nakabululu’ East African Highland Bananas (EAHB; AAA-EA group), and numerous trees and shrubs that are useful as fodder. From the survey, we concluded that banana crops and trees coexist on the same farm. However, few households make systematic use of trees and shrubs as mulch or animal fodder to increase manure supplies, and neither do they manage tree canopies to improve the microclimate for bananas. Certain households are endowed with more land, livestock and on-farm trees with which to undertake agroforestry strategies to improve banana productivity. A technology innovation approach to develop options for less resource-endowed households should draw on three elements: participatory experimentation incorporating current farmer knowledge and practice in a science-based agro-ecological framework; field studies on management principles for banana agroforestry; and models to understand medium-term biological interactions and farm household technology choices.

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 150 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Trees and Shrubs to Improve Productivity and Production 151

animal feeds, with the increased on-farm 19.1 Introduction manure applied to bananas and other crops; (iv) increased on-farm planting and use of Central Uganda was at one time among the trees and shrubs, both as mulch for bananas major banana-growing areas of Uganda and as feed for increased animal and manure (Gold et al., 1999; Bagamba et al., 2010), but in production. In this chapter, we explore the recent decades, several factors have contrib- current status of on-farm trees and shrubs in uted to the decline in importance of bananas central Uganda and their potential contribu- as a food and cash crop. During the political tion to banana production and productivity. instability of the 1970s to the 1980s, commu- Recent studies on land and soil produc- nities were dislocated, which led to a collapse tivity in Uganda have left out the possible of production systems as farmers ceased the contribution of trees and shrubs. In their traditional production practices they had study of organic matter resources in south used to control weevils and nematodes and central Uganda, Bekunda and Woomer (1996) maintain soil and crop productivity (Gold did not include trees. Ellis and Bahiigwa et al., 1999). The spread of banana black (2003), in their study of livelihoods in three leaf streak (caused by the fungal pathogen districts in southern Uganda, made no men- Mycosphaerella fijiensis), which reached tion of trees. Briggs and Twomlow (2002) Uganda in 1989 (Tushemereirwe and Waller, reported no role for trees and shrubs in their 1993), had an especially severe impact in cen- study of organic material flows in south- tral Uganda, which is at a lower elevation western Uganda, although this region may than other production areas in the country have fewer trees compared with central (Tushemereirwe et al., 2000). Farms have Uganda. Other studies have documented the become smaller as land is divided among role of trees in maintaining productivity and new generations, and Uganda’s average farm farm income (Nielsen et al., 1995). Throughout size is now in the range of 0.5 to 2.5 ha (IFAD, Uganda, bark cloth trees (Ficus natalensis, 2007). Grazing lands and swamp, the tradi- F. thonningii and F. ovata), so called because tional sources of mulch and manure, have they were (and are) used to make bark cloth, also declined in area as more land is con- have many traditional functions in village life verted to crops. Concomitant with the expan- (Ipulet, 1993). Studies in central Uganda have sion of crop areas has been an increased listed a wide range of trees and shrubs used demand for manure. At the same time as tra- for fruit production and sale, firewood, conditional measures to increase fertility have struction and fodder (Nielsen et al., 1995; become more difficult, farmers are growing Mugabi, 2002). Exploratory visits and inter- bananas to supply the Kampala market, views in the region have indicated the pres- which has an annual population growth of ence of large trees such as Ficus spp., Albizia 5.6% (UBOS, 2002). Further, this increased spp., Artocarpus heterophyllus and Maesopsis production for market represents an increas- eminii, coppiced trees such as Markhamia lutea, ing export of soil nutrients. and shrubs such as Vernonia amygdalina. For farmers of central Uganda and for To guide the formulation of a question- other more distant production areas of the naire and field survey, we proposed possible country, a central issue then is how to main- links between trees and shrubs, banana and tain and increase banana production and pro- land productivity (Fig. 19.1). We hypothesized ductivity. A number of approaches can be that trees/shrubs can be linked to banana postulated: (i) the use of chemical fertilizers and land productivity in four ways: (i) bananas directly on bananas; (ii) the application of growing directly under trees with contribu- chemical fertilizers on annual crops such as tions both as mulch, improved nutrient maize and beans to increase the transfer of status of soil and positive microenvironment; crop residues to bananas, a practice that is (ii) trees/shrubs as the source of fodder for used traditionally; (iii) intensive animal rais- animals which produce manure for bananas; ing (chickens, pigs, zero-grazed dairy cows) (iii) trees/shrubs as source of mulch for bananas, based on the purchase of high-nutrient although they have no direct interaction with 152 S. Mpiira et al.

(b) Musa Manure gardens with (a) trees

(b) Musa (c) Livestock gardens Fodder

Other crop (d) land Trees/Shrubs near Musa Trees/Shrubs

Fallow land Mulch

Fig. 19.1. Potential linkages among bananas, trees and livestock via manure, mulch and land use changes. Flow (a): leaf litter and other tree interactions with banana (Musa) when growing on the same piece of land. Flow (b): manure collected from livestock fed on crop residues and tree/shrub fodder, and grazing off farm and on fallow and cropped land. Flow (c): mulch from diverse sources. Flow (d): the establishment of new banana fields through the conversion of land with different levels of potential productivity. bananas; (iv) trees/shrubs which improve of banana plants, ground cover and other the productivity of land which is brought into crops, including coffee, trees and shrubs, new production with bananas. were measured. In each district, 70 households were interviewed and field sampling was conducted on the farms of 30 of these. 19.2 Materials and Methods Means and standard deviations were calculated for descriptive statistics. To group households by wealth status, a principal com- The study was conducted in two parts in ponents analysis was done. Of the 13 varia- three districts of the Central Region of bles, quantitative variables were land area Uganda – Kiboga, Sembabule and Nakaseke. and livestock units (LUs) (Chilonda and Otte, A pretested survey questionnaire was used to 2006). Indicator variables included motorcy- gather information on household and farm cle ownership, wall, floor and roof materials, characteristics, land holding, household labour hire and work off farm (both full and assets, livestock ownership, manure sources part time). Indices were generated with and uses, crop resources (including a profile STATA software (StataCorp, 2011) to identify of crops grown), trees on the farm and their the significant variables and the values were uses, and social capital in terms of access to plotted in Microsoft Excel. The resulting scat- information. A field sampling tool was devel- ter plots were used to identify wealth-based oped and also pretested. For the field sam- groups of households. pling, the farmer first drew a map of his or her land. The farmer and the researchers then walked the farm profiling the characteristics of the shrubs and all of the trees taller than 19.3 Results 3 m. Measurements of girth, height, crown diameter, distance to the nearest tree and 19.3.1 Household resources extent of pruning of the tree canopy were recorded. A 25 × 6 m banana subplot was For Kiboga, Nakaseke and Sembabule, marked and within the subplot the densities respectively, land holding was, on average, Trees and Shrubs to Improve Productivity and Production 153

2.6, 4.4 and 3.4 ha, with 291, 355 and The majority of households, 78%, were in the 517 banana mats, and 15, 23 and 11 trees and struggling and medium categories. The asset- shrubs per farm, with 69, 71 and 32 % of farms poor and struggling households were found owning no ruminants. Of the households, 24, in a greater proportion in Kiboga. 57 and 56% hired labour, while 31, 46 and 52% sold their labour (Table 19.1). The main sources of income in the three districts were 19.3.2 Trees and bananas on farm sales of bananas, coffee and maize. For Sembabule and Kiboga, bananas were the Just over 3420 trees taller than 3 m were main source, while in Nakaseke, coffee was recorded from the count of all trees on farms, the main cash crop. Over 65% of households representing a total of 49 tree species. There in Nakaseke owned cattle, while only 35% were more trees in Nakaseke (1592) and owned cattle in Sembabule and 24% in Kiboga. Kiboga (1083) than in Sembabule (748). The For those households with cattle, the average average number of trees per farm was 53 in numbers owned were 2.4 in Nakaseke, 3.2 in Nakaseke, 36 in Kiboga and 25 in Sembabule. Sembabule and 1.6 in Kiboga. In general, The most common trees across the three dis- goats were held by fewer households and in tricts were: Artocarpus heterophyllus (jackfruit) fewer numbers. Only in Kiboga was goat and Mangifera indica (mango), followed holding more common, with 30% of house- by Albizia coriaria (mugavu), F. natalensis holds having at least one goat. (mutuba), Markhamia lutea (musambya) and Based on the analysis of resources, four Maesopsis eminii (musizi). By district, the most groups of households were proposed: very important trees on farm were jackfruit, poor, struggling, medium and better off. The A. coriaria and M. lutea for Nakaseke, F. natal- most important characteristics in the group- ensis, jackfruit and mango for Sembabule, and ings were labour hiring, full-time off-farm jackfruit, F. natalensis and A. coriaria for work, type of house construction material Kiboga. There were no Eucalyptus or Moringa and ownership of a motorcycle (Table 19.2). oleifera (moringa) trees in Kiboga among the Although differences were not statistically sampled farmers and no F. mucoso (mukunyu) significant, the poorest households on aver- trees in Sembabule. The land use under trees age had less land and fewer livestock than the was primarily banana, cocoyam and coffee other groups. Asset-poor (very poor) house- cropping; Kiboga had the highest percentage holds made up 5% of all households, while of trees associated with these crops (56%), fol- better-resourced households made up 17%. lowed by Nakaseke (43%) and Sembabule (40%). Shrub fallow vegetation was found under only 13% of trees in Nakaseke, 9% in Table 19.1. Selected household resources in Kiboga and 5% in Sembabule. Uganda by district. Farmers readily identified good neigh- District bour trees for banana (F. natalensis and Albizia coriaria), tree-friendly banana cultivars – Variables Kiboga Nakaseke Sembabule which included ‘Kibuzi’, ‘Ndibwabalangira’ ‘Nakitembe’, ‘Mbwazirume’ and ‘Nakabululu’ Average 2.63 4.41 3.39 landholding East African Highland Bananas (EAHB; (ha) AAA-EA group), and numerous trees and Average 1.3 1.3 1.9 shrubs that are useful as fodder. In the number of 90 banana subplots sampled in the three plots districts, 5333 banana mats were counted in a Renting 19 15 12 total subplot area of 14,850 m2, representing a land (%) density of 1161 mats/ha in Sembabule, Renting out 12 4 10 892 mats/ha in Nakaseke and 845 mats/ha in land (%) Kiboga. The most common banana cultivars Hiring 24 57 56 on farm were ‘Mpologoma’ and ‘Nakitembe’ labour (%) in Sembabule, ‘Musakala’ and ‘Mpologoma’ 154 S. Mpiira et al.

Table 19.2. Characteristics of household wealth identified through principal components analysis. Values represent averages (mean ± SE) of quantitative variables or percentage of the wealth group for indicator variables.

Wealth groupings

Variables measured Very poor Struggling Medium Better off Significance

Land (ha) 3.3 ± 3.5 7.3 ± 17.7 7.5 ± 14.1 6.5 ± 5.6 NSa Motorcycle value 7.5 ± 0.44 5.0 ± 1.2 4.8 ± 1.2 1.1 ± 1.4 ** (million Uganda shillings) Animals (livestock units) 0.00 0.27 ± 0.44 0.19 ± 0.39 0.06 ± 0.39 NS House walls made of bricks (%) 3.4 28.4 45.7 22.4 ** House walls made of mud (%) 44.4 48.3 29.8 14.3 *** House floor made of concrete (%) 11.1 22.5 34.5 45.7 * House floor made of mud (%) 88.9 77.3 63.1 54.3 * House roof made of iron sheets (%) 100.0 94.7 94.6 94.3 NS House roof made of grass (%) 0.0 5.3 6.0 5.0 NS Labour hiring full time (%) 5.3 47.4 42.1 5.3 NS Labour hiring part time (%) 4.7 37.6 45.6 12.1 * Off-farm work full time (%) 4.1 30.6 44.7 20.6 *** Off-farm work part time (%) 11.1 16.0 13.1 8.6 NS aNS, not significant; *, Significant at P = 0.05; ** Significant at P = 0.01;, *** Significant at P = 0.001. in Nakaseke, and ‘Ndibwabalangira’ and wastes. Although 29% of respondents in ‘Kayinja’ (ABB) in Kiboga. Kiboga, 51% in Sembabule and 55% in Some 71 trees were counted in the Nakaseke indicated that they planted trees marked banana subplots, comprising 18 spe- and shrubs which could be used as fodder, cies, with F. natalensis and A. coriara being the only 30% fed tree and shrub fodder to their most common. Kiboga (32) and Nakaseke animals on a regular basis, more so in (30) had more trees than Sembabule (10). Nakaseke and Sembabule than in Kiboga. In Of these 18 tree species, farmers indicated addition to F. natalensis, Calliandra calothyrsus, that A. coriara and F. natalensis were the most moringa, Leucaena leucocephala and Sesbania banana friendly trees, a term indicating that sesban are usually planted, with V. amygdalina close physical proximity had the least effect and Tithonia diversifolia commonly found in on banana growth and productivity. Of the fields and by the roadside. Erythrina abyssi- 1380 banana plants observed in the three nica is mainly used as a hedge on farms. districts, Nakaseke had the most bananas under a tree canopy, with 124 mats, followed by Kiboga with 118 and Sembabule with 29. 19.3.4 Use of manure and mulch These data indicate few trees in banana plots in banana plots and few bananas under trees. The survey showed that most trees were not pruned – Manure and mulch are considered the tradi- 72% in Kiboga, 68% in Nakaseke and 59% in tional techniques for maintaining banana plot Sembabule, and that little mulch was gener- productivity, but are not widely used in cen- ated for the bananas except through leaf fall. tral Uganda. In Nakaseke, more households (63%) were using manure than in Sembabule (38%) and Kiboga (21%). More households in 19.3.3 Fodder sources for livestock Nakaseke have cattle and many are under controlled or zero grazing (Ministry of Cattle and goats owned by households were Agriculture District Production Officer, primarily free grazed or tethered with occa- Nakaseke, 2011, personal communication). sional feed supplementation by household This makes manure easier to collect and Trees and Shrubs to Improve Productivity and Production 155

apply than in Sembabule and Kiboga, where not the main household plot. Farmers readily livestock are fewer and grazed free range. identify both tree-friendly banana cultivars In Sembabule and Kiboga, households applied and banana-friendly trees, primarily Ficus purchased manure, while in Nakaseke only and Albizia spp. However, most tree canopies 16% of households purchased manure. are not managed to improve the microclimate A minority of households, 16% in Nakaseke, for bananas. 19% in Kiboga and 30% in Sembabule, In terms of manure supplies derived reported applying mulch to their banana from tree and shrub fodder (flow ‘b’ in Fig. plots, primarily swamp grass and bean and 19.1), few households make systematic use maize crop residues. The data collected on of trees and shrubs as animal fodder to ground cover in the banana subplots showed increase manure supplies. Of species with that this was primarily banana residue (37%), fodder potential, F. natalensis, C. calothyrsus, weeds (19%) and bare ground (18%), with moringa, L. leucocephala and S. sesban were very limited grass/crop residue mulch (15%) usually planted, with V. amygdalina and and tree/coffee leaf mulch (10%). T. diversifolia commonly found in fields and by the roadside. E. abyssinica was mainly used as a hedge on farms, but was not recognized by farmers as a fodder, 19.4 Discussion and Conclusion although it is included in manuals of fodder shrubs of East Africa (Aucha et al., 2005). In this last section, we evaluate the potential The main animal feed from trees that is for the use of trees and shrubs to maintain and actually used appears to be jackfruits. Only improve banana productivity, identify the a minority of households own cattle in changes needed on farm and propose appro- Sembabule and Kiboga, although over 60% priate technology generation strategies. in Nakaseke own cattle. Cattle and goats are A review of the evidence presented from tethered or free grazed, often off the farm, the survey, based on the linkages outlined in except in Nakaseke, where zero-grazed the Introduction (Section 19.1) and the flows dairy cows are kept for milk sales to a nearby shown in Fig. 19.1, is a first step in determin- large dairy farm and processing plant. Only ing the feasibility of the agroforestry approach a minority of households apply manure to to improving banana productivity. Trees pop- bananas, although all households recognize ulate the landscape in central Uganda, but in its importance for banana productivity. terms of direct tree–banana interplanting However, trees and shrubs with fodder uses (flow (a) in Fig. 19.1), based on data for the show little evidence of frequent pruning and number of banana mats under trees and farmers also indicated that tree and shrub within the influence of the tree canopy within pruning is infrequent. the banana gardens, there were 11 trees/ha The evidence for the use of mulch from (6.5% canopy cover) in Kiboga, 8 trees/ha (4.8% trees and shrubs not directly planted with cover) in Sembabule and 14 trees/ha (6.5% bananas (flow ‘c’ in Fig. 19.1) indicates that cover) in Nakaseke. Jackfruit and mango, fol- this practice is not common. Overall, few lowed by A. coriaria, F. natalensis, M. lutea and farmers mulch their bananas, except with Maeopsis emini were the most common trees banana trash, in spite of a widespread belief found on farm. These trees were also found to that mulching is important. This is also evi- be the most common by Zziwa et al. (2006). denced by the low pruning rate of trees and Households estimated their total banana shrubs. The sampling of ground cover mats at 219 in Kiboga, 628 in Sembabule and showed that mulch with grass and crop resi- 460 in Nakaseke, but only 19.6% of bananas in due covered only 15% of the soil, and tree and the sampled subplots were found under tree coffee leaves covered only 10%. canopies. In contrast, over half of the trees on The potential role of trees and shrubs in farm were found to have crops, either coffee, maintaining land productivity through rota- banana or cocoyam, within the canopy. For tions and fallowing before establishing banana, this may represent a few mats, but bananas did not emerge from the farmer 156 S. Mpiira et al.

and field sampling, although this was bananas grown with mulch/green-manure- reported by Nielsen et al. (1995). In most generating shrubs and possibly young trees, cases, new banana gardens are interplanted an approach requiring the balancing of with annual crops such as beans, peanuts and plant–plant competition with labour costs; sweet potatoes on land converted from grass (iii) tree-friendly bananas grown with and weed fallows following other annual mulch/green manure-generating shrubs crops. Shrub fallows were found primarily on exploited as fodder for zero-grazed, manure- farms of above average size, although most producing livestock, and possibly young farmers recognize the value of fallowing with trees as well, an approach that needs live- shrubs for building land productivity. stock acquisition opportunities for asset- We conclude that bananas, trees and poor households; and (iv) bananas grown livestock coexist on farm, but are not strongly based on mulch and manure produced off linked in practice through the flows of plot from mulch/green manure-generating resources (Fig. 19.1). Mulch and manure are shrubs exploited to generate manure from perceived as important inputs for banana zero-grazed livestock, an approach that is productivity, but are not widely used. dependent on livestock acquisition and Farmers have many observations about excess land. appropriate species or cultivars for banana To test the viability of these approaches agroforestry and about the palatability of in biological, economic and logistical terms, trees and shrubs for animal feeding. The and to generate practical decision guidelines study suggests that changes in farm prac- for their use, a three-pronged approach is tices would be needed for the greater use of needed, as proposed by Doré et al. (2011). The trees and shrubs, either directly or through first prong is participatory technology gen- livestock feeding, to increase banana pro- eration with groups of farm households tap- ductivity or expand the area under produc- ping into farmer knowledge, observational tion. Trees and shrubs and their products are skills and adaptation capacity under a viewed primarily as spontaneous rather diverse set of household resource and man- than managed by the farmer. Livestock are agement objectives. Researchers contribute tended as a highly valued resource, but feed knowledge generated in other regions, prin- supplies are opportunistic by season and ciples derived from biology and ecology, and from both off- and on-farm sources. A change a capacity for synthesis of more general man- is needed from this consideration of trees agement practices. Farmers need to have and shrubs as spontaneous vegetation to access to planting materials, livestock and their managed planting, thinning and prun- an ongoing process for planning, experimen- ing for specific and planned outputs in pre- tation and analysis. The second prong is chosen niches on farm. These niches should formal studies, which are useful for under- be defined by labour efficiency, reduced standing resource partitioning at the plot competitive effects on preferred crops such level in the mixed systems, particularly as banana, coffee and food crops, and poten- water use, nutrient cycling and light. Such tial synergies directly or through livestock. studies could also look at household decision- Some households are endowed with more making approaches based on the interests of land, livestock and on-farm trees to under- men, women and the next generation, with take agroforestry strategies to improve perceived marginal returns to investment in banana productivity, while others are lim- different on-farm and off-farm activities, ited primarily by a lack of resources for live- especially as tree planting is a medium-term stock acquisition. investment. The third prong is model formu- A number of agroforestry models can lation to account for biological interactions, be envisioned: (i) hardy beer bananas and natural resource quality and the effect of tree-friendly matooke bananas growing changing conditions (including climate, food under occasionally pruned large trees, an and input prices), and to project the viability approach that is currently limited by the of proposed technologies for the next genera- availability of large trees; (ii) tree-friendly tion of asset-poor rural households. Trees and Shrubs to Improve Productivity and Production 157

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J. Ntamwira,1* P. Pypers,2 P.J.A. van Asten,3 B. Vanlauwe,4 B. Ruhigwa,5 P. Lepoint6 and G. Blomme7 1Institut National pour l’Etude et la Recherche Agronomiques (INERA), Mulungu Research Station, Bukavu, Democratic Republic of Congo; 2Tropical Soil Biology and Fertility Institute, International Center for Tropical Agriculture (TSBF-CIAT), Nairobi, Kenya; 3International Institute of Tropical Agriculture (IITA), Kampala, Uganda; 4IITA, Nairobi, Kenya; 5Institut Facultaire des Sciences Agronomiques (IFA-Yangambi), Kisangani, Democratic Republic of Congo; 6Bioversity International, Bujumbura, Burundi; 7Bioversity International, Kampala, Uganda

Abstract As a result of declining farm/plot size and increasing food security needs, intercropping is practised by the majority of small-scale farmers in eastern Democratic Republic of Congo. A banana–legume intercropping experiment was conducted at the Mulungu Research Station in South Kivu Province to evaluate whether banana leaf pruning improves legume biomass and grain yield without reducing banana production. Treatments consisted of combinations of three different levels of banana leaf pruning (maintain four or seven functional leaves, or all leaves) with three bio-fortified leguminous crops (bush bean, climbing bean and soybean). Plots with sole banana or leguminous crops were also included, resulting in a full factorial design with 15 treatments. The banana genotype was an East African highland cooking banana ‘Barhabesha’ (Musa spp., AAA-EA). The legume crops were planted in the established banana fields and observations were taken during two consecutive cropping seasons. Few significant differences were observed in legume biomass or grain yield between the four- and seven-banana leaf treatments for bush beans during both cropping seasons. However, with climbing beans, and especially soybeans, a significant difference was observed in biomass and grain yield between the four- and seven- leaf treatments during the second cropping season, when a more mature banana leaf canopy had developed. We recommend keeping seven green leaves on a banana plant when cultivating bush beans, as this treatment will improve light penetration but may not significantly affect banana growth and yield. In contrast, for climbing beans and especially soybeans, a more severe banana leaf pruning treatment is needed to obtain a reasonable legume biomass and grain yield. Banana landraces or hybrids with more erect leaves could also be envisaged for intercropping purposes, as they will create less shade for the legume crop, although rigorous de-suckering will need to be practised. Alternatively, cultivars with a regulated suckering (i.e. only two to three suckers develop) could be envisaged.

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 158 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Effect of Banana Leaf Pruning on Legume Yield 159

20.1 Introduction In eastern DR Congo, banana–legume intercropping is widely practised (Dowiya Intercropping is a widespread agronomic et al., 2009). Some farmers practise banana practice on subsistence farms in developing leaf cutting when planting beans (Katungu, countries of the tropics (Liu et al., 1997). 2011). This practice enhances light penetra- Small-scale African farmers that suffer from tion to ground level and hence positively the reduced availability of arable land influences legume growth and yield. There depend almost entirely on intercropping to are, however, no quantitative data available produce enough food to satisfy their dietary on the effect of banana leaf pruning during and cash requirements. Intercropping aims the months of legume intercropping on the to maximize productivity and minimize the growth and yield of either the banana or the risks related to, for example, climate change, legume. The objective of this study was to pests and diseases (Nyabyenda, 2006), and evaluate whether banana leaf pruning gives a more stable farm yield compared improves legume biomass and grain yield with monoculture. Furthermore, it often pro- without reducing banana growth. vides a higher economic and monetary return and total production per hectare compared with monoculture and ensures greater 20.2 Materials and Methods resource use efficiency (Ouma, 2009). Land use efficiency of smallholder farms in East An experiment was established at the Institut and Central Africa can be increased by incor- National pour l’Etude et la Recherche porating food and/or fodder legumes into Agronomiques (INERA) Mulungu Research banana cropping systems (Sileshi et al., 2007). Station, which is located at 02°20.042¢S In addition, intercropping with legumes may 028°47.311¢E and at an altitude of 1707 m also be a strategy to offset the depletion of above sea level (masl). The soil is a volcanic- soil fertility (Chakeredza et al., 2007). derived Andosol with the following charac- The intercropping of either banana or teristics: pH, 8.5; organic matter content plantain (Musa spp., AAB) with legumes is (OM%), 4.9; N (%), 0.25; P (mg/kg), 126; practised in both South America and Africa K (cmolc/kg), 1.92; Ca (cmolc/kg), 23.85; and

(Liu et al., 1999). Plantain in West Africa is Mg (cmolc/kg), 1.41. The average annual usually grown in association with food rainfall is 1500 mm distributed over two rainy crops such as melon, soybean, maize and seasons (February–May and September– sweet potato (Sunday and Hassan, 1999). December). The field had been under banana Banana–bean intercropping is widespread cultivation for 3 years. All banana mats were across eastern and central Africa, including uprooted and plant debris was spread out as Uganda, Rwanda, Burundi, the Democratic mulch across the field 1 week before estab- Republic of Congo (DR Congo) and north- lishing the intercropping experiment. western Tanzania (Wortmann and The treatments consisted of combinations Sengooba, 1993). of three different levels of banana leaf pruning Crop production is primarily the conver- (maintaining four or seven or all leaves on sion of solar energy to stored food energy each plant) with three leguminous crops: bush (Pimentel and Pimentel, 2008), and a reduc- bean cv. MLB49 (Phaseolus vulgaris L.); climb- tion in intercepted sunlight reduces producing bean cv. AND10 (Phaseolus vulgaris L.); tion (Nyambo et al., 1982). Light competition and soybean cv. SB24 (Glycine max (L.) Merr.). is an important factor influencing the yield Plots with sole banana or leguminous crops of smaller-sized plants in an intercropping were also included. This resulted in a full system, and it is clear that large plants factorial design with 15 treatments. The (e.g. banana) will provide substantial levels banana genotype was an East African high- of shade and could thus influence the growth land cooking banana ‘Barhabesha’ (Musa spp., and yield of smaller-sized intercropped crops AAA-EA) and the plants were established in (Davis et al., 1987). December 2009. The legume crops were 160 J. Ntamwira et al.

planted among the bananas at 3 and 4 months weight or yield as no plant had flowered at after planting the bananas and observations 12 months after the experiment began. were taken during two consecutive legume An ACCUPAR photometer probe cropping seasons (2010B, March–June 2010; (Model LP-80, Decagon Devices, Pullman, and 2011A, September 2010–January 2011). Washington, USA) was used to measure the The treatments were arranged in a rand- photosynthetically active radiation (PAR) omized complete block design with four rep- received by the leguminous crops under the lications, giving a total of 60 plots. Each plot different shading levels obtained through (120 m²) contained 30 banana plants, planted banana de-leafing. The light measurements in five rows of six plants each, with a plant were taken when: (i) 50% of plants had flow- spacing of 2 × 2 m. Legumes were planted in ered; (ii) 50% of plants had formed pods; and lines 50 cm apart, giving 20 lines of legumes (iii) 50% of plants had reached the grain per plot. Each line of legumes was 12 m long maturity stage. Data were taken on clear and intra-line spacing was 20 cm for bush days between midday and 2 p.m. and just bean, 25 cm for climbing bean and 10 cm for above the legume crop. Twelve light meas- soybean plants. Legumes were sown as seed. urements were taken for each legume treat- Banana leaf pruning was carried out weekly ment and at each of the three legume from legume planting until legume harvest physiological stages. (i.e. during the bean cropping season). Legume disease severity (score 1–9) was Weeding was carried out monthly, while de- recorded during both legume cropping sea- suckering was practised on a case-by-case sons when 50% of plants had formed pods basis. No mineral fertilizer was applied. (van Schoonhoven and Pastor-Corrales, Banana and legume data were collected 1992; Allen et al., 1996). Angular leaf spot in centrally located net plots, which com- fungal disease (Phaeoisariopsis griseola) was prised 12 banana plants and a 6 × 4 m section assessed on bush and climbing beans, while of legume crop. Legume traits were assessed brown spot (Septoria glycines) was assessed using the van Schoonhoven and Pastor- on soybean. All data were subjected to anal- Corrales (1992) protocols and included the ysis of variance using the GenStat software number of days from planting to the date package (GenStat, 2008). when 50% of plants flowered, 50% of plants formed pods and 50% of plants reached grain maturity (the physiological dates). In addition, legume dry weight was assessed at the 20.3 Results and Discussion time of 50% pod formation in a 1 × 1 m section located in the equivalent corner of each 20.3.1 Legume crop cycle legume net plot. Legume dry grain weight was obtained by drying harvested grains Banana leaf pruning did not significantly in the sun until grain weight stabilized. influence the physiological dates for any of Subsequently, the grains were oven dried the bean crops, with the least variation seen (at 90°C) for 24 h. in the crops planted at 9 months after banana Banana growth parameters were field planting. Further, the number of days assessed in the net plots at 4, 8 and 12 months from planting to 50% flowering, 50% pod after the experiment began (on 12 plants); formation and 50% grain maturity of the measurements included plant height and intercropped beans were not significantly pseudostem circumference at soil level and at different from those under monoculture 1 m above soil level. The number of func- (Table 20.1). During the two legume cropping tional banana leaves in the all-leaves treat- seasons, bush bean had the shortest produc- ment was counted at 3 and 9 months after tion cycle, followed by climbing bean and banana planting (i.e. at the onset of the leg- soybean (Table 20.1). The number of days to ume season) to calculate the leaf area index reach 50% grain maturity stage was higher (LAI) using the formula of Nyombi et al. during the second season (2011A), especially (2009). No data were collected on bunch for soy bean: the soybean monocrop took Effect of Banana Leaf Pruning on Legume Yield 161

Table 20.1. Legume crop cycle duration under monocropping and intercropped with banana. Variation is shown in relation to banana leaf pruning (4, 7 or all leaves retained) and cropping season. For season 2010B, legumes were planted 3 months after bananas; for 2011A, legumes were planted 9 months after bananas. Treatment 0, legume monocrop. Means followed by the same letter in a column are not significantly different, according to Tukey’s HSD test (P < 0.05).

2010B 2011A

Days from legume planting to 50% Days from legume planting to 50% Banana leaves Grain Grain Legume retained Flowers Pods maturity Flowers Pods maturity

Soybean 0 54.3a 62 0a 91.3b 59.0a 68.2a 107.8a 4 54.3a 62 0a 91.2b 59.3a 68.7a 107.5a 7 54.3a 61.3ab 93.2a 59.0a 67.0a 107.8a All 54.5a 60.3ab 91.5b 59.3a 65.3a 104.8a Climbing 0 47.3b 60.0ab 90.8b 47.8b 57.8b 93.0b bean 4 47.5b 59.5ab 90.0b 47.5b 57.8b 93.0b 7 48.0b 58.8bc 91.0b 47.8b 58.8b 96.0b All 48.3b 56.3c 90.5b 47.8b 58.8b 96.0b Bush bean 0 42.3c 51.5d 77.0c 43.5c 48.5c 77.5c 4 42.5c 50 0d 77.0c 43.5c 48.5c 77.5c 7 42.2c 50.3d 77.0c 43.5c 48.5c 77.5c All 43.3c 50.3d 77.0c 43.5c 48.5c 77.5c LSD 3.6 3.0 1.5 1.2 3.6 4.6 CV(%) 5.1 4.0 1.2 1.7 4.3 3.4

108 days to reach 50% grain maturity stage, treatment, 0.2–0.4 for the seven-leaves treat- while bush bean only took 78 days. ment and by 0.2–0.3 for the four-leaves treatment. This increase in LAI resulted in a significant negative effect on legume yield, 20.3.2 Legume yield especially for the seven of all leaves treatments and for soybean (Table 20.2). PAR Legume dry matter and grain yield were measurements taken just above the legume higher under monocropping than under crop with the ACCUPAR Model LP-80 intercropping during both legume cropping light meter were strongly and negatively seasons (Table 20.2). Under intercropping, related to the banana LAI values (exponential banana leaf pruning did not affect (the already regress ion model: – = 2080.7e–0.783x, R² = 0.95). reduced) legume yield during the first leg- Soybean yield during the second legume ume cropping season as the banana plants cropping ranged from 1181 kg/ha under mono- were only 3 months old with a pseudostem cropping to 168 kg/ha for the all-leaves treatment height of around 1 m and a limited leaf (Table 20.2). The effect of banana leaf pruning was canopy cover (LAI < 1.1). Nyombi et al. (2009) less pronounced on bush and climbing bean reported that 55% of the solar radiation is yields than on soybean. Yields of bush bean intercepted when the banana LAI is 1.1. This increased from 121, 205, 216 to 389 kg/ha as more corresponds to a significant drop in the light leaves were removed from the bananas; for resource, but even so had little consequence climbing bean, the increases were from 161, 340, for the legumes during the first season. The 715 to 1752 kg/ha as more leaves were removed. banana LAI during the second legume crop- The highest yields were in the legume mono- ping season (at 9 months after banana crop treatments. Mbah et al. (2007) observed a planting) increased by 0.5–0.6 for the all-leaves significant reduction of soybean yield (27%) in 162 J. Ntamwira et al.

Table 20.2. Legume yield under monocropping and intercropped with banana. The effect is shown of banana leaf pruning (4, 7 or all leaves retained) on legume yield and dry matter, and banana leaf area index (LAI, calculated for one banana plant) for two legume cropping seasons. For season 2010B, legumes were planted 3 months after bananas; for 2011A, legumes were planted 9 months after bananas. The photosynthetically active radiation (PAR) is given for season 2011A. Treatment 0, legume monocrop. Means followed by the same letter in a column are not significantly different from each other, according to Tukey’s HSD test (P < 0.05). The statistical analysis was carried out for soybean independently of climbing and bush beans.

2010B 2011A

Banana Legume Legume Legume Legume PAR leaves grain yield dry weight Banana grain yield dry weight Banana (μmole Legume retained (kg/ha) (kg/ha) LAI (kg/ha) (kg/ha) LAI m–2s–1)

Soybean 0 994a 3028a 1181a 6235a 2070a 4 609b 2130a 0.4e 1023a 2845b 0.6f 1324b 7 610b 2590a 0.8d 414b 1370c 1.0d 832c All 544b 2975a 1.0b 168b 872c 1.6a 573e LSD 240 1524 0.1 358 1088 0.2 202 CV(%) 22 36 20 32 24 33 38 Climbing 0 1043b 3030a 1752a 4232a 2122a bean 4 805bc 1748b 0.4e 715b 3362b 0.7ef 1194b 7 680c 2068b 0.9c 340cd 1955c 1.2c 808cd All 928bc 1940b 1.1a 161cd 1422cd 1.7a 675de Bush 0 1528a 2070b 389c 3542b 2062a bean 4 699c 2170ab 0.4e 216cd 1362cd 0.7e 1318b 7 759c 2442ab 0.7d 205cd 1100d 1.1c 965c All 629c 1365b 0.9c 121d 955d 1.4b 552e LSD 272 911 0.1 233 684 0.6 202 CV(%) 21 29 20 33 21 33 38

soybean–maize intercropping due to the the first legume season and the advanced shade effect of maize. Akyeampong et al. (1999) decomposition of banana debris/mulch from showed that a 27% decrease in PAR did not banana mats that were uprooted before the affect beans, although a further decrease to establishment of the intercropping experiment. 42% of total PAR decreased dry bean grain For legume diseases, angular leaf spot yield by 27% compared with the control. was observed during both cropping seasons Legume dry matter production followed a on bush and climbing beans, whereas brown similar trend to grain yield (Table 20.2), with the spot was only observed on soybean (Table 20.3). highest dry matter yield recorded for the leg- The average disease severity scores were below ume monocrop. Dry matter under monocrop- 5.15, indicating that there were numerous small ping was 3542 kg/ha for bush bean, 4232 kg/ha lesions that covered less than 5% of leaves or for climbing beans and 6235 kg/ha for soybean. pods, and so had limited economic impact. In the second cropping season (2011A) dry weights for the all-leaf banana intercropping treatment were 955 kg/ha for bush bean, 20.3.3 Banana growth traits 1422 kg/ha for climbing bean and 872 kg/ha for soybean. The increase in biomass produc- Banana leaf pruning reduced both banana tion during the 2011A season for legumes plant height and pseudostem circumference, under monocropping could be explained by and the decreases increased from 4 to 12 months the nitrogen fixation that had occurred during after banana field establishment (Table 20.4). Effect of Banana Leaf Pruning on Legume Yield 163

Table 20.3. Legume leaf fungal diseases (angular leaf and brown spot) under monocropping and intercropped with banana during two cropping seasons. For season 2010B, legumes were planted 3 months after bananas; for 2011A, legumes were planted 9 months after bananas. Banana plants were leaf pruned to 4 or 7 leaves, or all leaves were retained. Disease severity was scored at 50% podding stage on 10 plants per treatment using a scale from 1 (least severe) to 9 (most severe). Means followed by the same letter in a column are not significantly different according to Tukey’s HSD test (P<0.05). Treatment 0, legume monocrop.

Disease severity score

Angular leaf spot Brown spot

Season Banana leaves retained Climbing bean Bush bean Soybean

2010B 0 4.38a 5.00ab 2.15a 4 3.78a 5.15a 1.73a 7 3.88a 4.30bc 1.65a All 3.65a 3.62c 1.93a LSD 0.87 0.70 0.75 CV(%) 14 22 25 2011A 0 3.52ab 4.48a 1.88b 4 3.90a 3.56b 1.90ab 7 3.10b 3.45b 2.03a All 3.42ab 3.48b 1.95ab LSD 0.53 0.53 0.14 CV(%) 32 32 16

Table 20.4. Effect of banana leaf pruning (4, 7 or all leaves retained) on banana growth parameters under monocropping and under intercropping with legumes. Means followed by the same letter in a column are not significantly different, according to Tukey’s HSD test (P<0.05).

Pseudostem circumference Plant height (cm) at soil level (cm)

Banana Months after planting Months after planting Legume leaves type retained 4 8 12 4 8 12

Soybean 4 100d 156d 241f 34.9d 49.8e 64.3d 7 117b 185c 282d 38.5c 55.8cd 69.9c All 128ab 210b 319ab 43.3a 61.5b 75.7a Climbing 4 115c 186c 265e 38.4c 53.6d 65.1d bean 7 133a 208b 305bc 42.8a 58.7b 73.8b All 142a 225a 330a 41.9b 61.5b 77.5a Bush bean 4 113c 184c 279d 38.0cd 57.0c 69.8c 7 110c 188c 301bc 37.1cd 56.0cd 72.9b All 119bc 197c 302bc 39.7b 58.0c 73.5b Banana 4 115c 202b 296c 41.2b 60.3b 71.0c monocrop 7 135a 222a 311b 45.4a 64.2a 73.3b All 132a 227a 330a 45.4a 65.0a 77.9a

LSD 9.3 12.9 13.9 3.3 3.2 2.6 CV(%) 19.1 16.1 11.7 20.5 13.7 8.9 164 J. Ntamwira et al.

The leaf pruning had a significant negative canopy had developed. We would therefore effect on banana plant height at 12 months, recommend keeping about seven green especially for banana plants intercropped with leaves on a banana plant when cultivating soybean, in which case, increasing leaf removal bush beans, as this treatment will improve reduced height by almost 80 cm, from 319 cm to light penetration, but may not significantly 241 cm (Table 20.4). Because of the strong allo- affect banana growth and yield. In contrast, metric growth relationships of East Africa high- for climbing bean and especially soybean, land bananas (Nyombi et al., 2009), we can a more severe banana leaf pruning treatment assume that banana leaf pruning will nega- is needed to obtain a reasonable legume dry tively influence banana yield. weight and grain yield. Banana landraces or hybrids with more erect leaves could also be envisaged for intercropping purposes as they 20.4 Conclusion will create less shade for the legume crop. However, rigorous de-suckering will need to be practised. Alternatively, the use of cultivars For bush bean, few significant differences with a regulated suckering (i.e. only two to were observed in legume dry matter and three suckers develop) could be envisaged. grain yield when banana leaves were pruned so that four or seven leaves were retained during cropping seasons in which the legumes were planted either 3 or 9 months after Acknowledgements bananas. However, with climbing bean, and especially soybean, there was a signi- We are grateful for financial support from the ficant difference in dry weight and grain Belgian Directorate General for Development yield between the four- and seven-leaf through the Consortium for Improving treatments during the second cropping Agriculture-based Livelihoods in Central season, when a more mature banana leaf Africa.

References

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Liu, L.C., Montalvo-Zapata, R., Ortiz-Lopez, J., Rodriguez, J.A. and Aponte, J. (1999) Effect of planting dates and intercropping frequencies on income and yield of bean and banana. Journal of Agriculture of the University of Puerto Rico 83, 209–213. Mbah, E.U., Muoneke, C.O. and Okepara, D.A. (2007) Effect of compound fertilizer on the yields and productivity of soybean and maize in soybean/maize intercrop in south western Nigeria. Tropical and Subtropical Agrosystems 7, 87–95. Nyabyenda, P. (2006) Les Plantes Cultivées en Régions Tropicales d’Altitude d’Afrique. Les Presses Agronomiques de Gembloux, Gembloux, Belgium. Nyambo, D.B., Matimati, T., Komba, A.L. and Jana, R.K. (1982) Influence of plant combinations and planting configurations on three cereals (maize, sorghum, millet) intercropped with two legumes (soybean, green-gram). In: Keswani, C.L. and Ndunguru, B.J. (eds) Proceedings of the Second Symposium on Intercropping in Semi-arid Areas, Morogoro, Tanzania, 4–7 August, 1980. IDRC Publication No. 186e, International Development Research Centre, Ottawa, Ontario, Canada, pp. 56–62. Nyombi, K., van Asten, P.J.A., Leffelaar, P.A., Corbeels, M., Kaizzi, C.K. and Giller, K.E. (2009) Allometric growth relationships of East Africa highland bananas (Musa AAA-EAHB) cv. Kisansa and Mbwazirume. Annals of Applied Biology 155, 403–418. Ouma, G. (2009) Intercropping and its application to banana production in East Africa: a review. Journal of Plant Breeding and Crop Science 1, 13–15. Pimentel, D. and Pimentel, M.H. (2008) Food, Energy, and Society, 3rd ed. CRC Press, Baton Rouge, Florida. Sileshi, G., Akinnifesi, F.K., Ajayi, O.C., Chakeredza, S., Kaonga., M. and Matakala, P.W. (2007) Contributions of agroforestry to ecosystem services in the miombo eco-region of eastern and southern Africa. African Journal of Environmental Science and Technology 1, 68–80. Sunday, O.S.A. and Hassan, T. (1999) Effect of cassava density on productivity of plantain and cassava in intercropping systems. Fruits 55, 23. van Schoonhoven, A. and Pastor-Corrales, M.A. (1992) Système Standard pour l’Evaluation du Germoplasme du Haricot. Publication du CIAT No. 207, International Center for Tropical Agriculture, Cali, Colombia. Wortmann, C.S. and Sengooba, T. (1993) The banana–bean intercropping systems – bean genotype × cropping systems interactions. Field Crops Research 31, 19–25. 21 A Comparative and Systems Approach to Banana Cropping Systems in the Great Lakes Region

J. Van Damme,1* D. De Bouver,1 M. Dupriez,1 P.J.A. van Asten2 and P.V. Baret1 1Earth and Life Institute, Université Catholique de Louvain (UCL), Louvain-le-Neuve, Belgium; 2International Institute of Tropical Agriculture (IITA), Kampala, Uganda

Abstract To explore the diversity and efficiency of smallholder farms, we developed an approach based on a comparative framework and a systems analysis. Five sites in three countries (Rwanda, Burundi and Democratic Republic of Congo) were studied in parallel to take account of variations in agro-ecological and institutional conditions. In a systems-based perspective, we used a combination of quantitative (field measurements, economic valuation) and qualitative methods (semi-directed interviews) to capture the diverse nature of smallholder cropping systems. The novelty of the approach is that qualitative dimensions are included in the farm-level diagnostics, while maintaining a comprehensive and reproducible tool for systems analysis in terms of performance, constraints and drivers. The highest productivity in terms of annual revenue/ha was observed in the medium-sized farms (0.7–1.0 ha). It was also in this category that the number of crops cultivated was the greatest. Our hypothesis is that this high efficiency is the outcome of a system where productivity and risk management are optimized.

21.1 Introduction (Chappell and LaValle, 2009). The aim of this paper is to contribute to a characterization of Recent reports suggest that an agriculture these agricultural systems based on a systems based on smallholders is more sustainable approach, i.e. a multidisciplinary description environmentally and socially (McIntyre et al., focusing on the interactions between drivers, 2009; De Schutter and Vanloqueren, 2011) than constraints and practices. To do so, we con- industrial agricultural systems. At the end of ducted a characterization of these agricultural the 20th century, 85% of the world’s farms systems in a comparative framework. were smaller than 2 ha (von Braun, 2005). Smallholder farming systems are diverse These small farms have higher land producti- and complex. This complexity contributes to vity than larger farms due to multiple cropping system resilience, but may also impede the and a lower dependency on external inputs transition of agricultural systems in an area

* [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 166 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Comparative and Systems Approach to Banana Cropping 167

where a high and rapidly increasing popu- demographic conditions (Cochet, 2001). The lation density needs to be fed from a limited focus of our study is to consider this small- amount of land. In addition, the complexity of holder system to understand the various these farming systems: (i) makes it difficult to dimensions that determine farm productivity. assess their performance; and (ii) requires insights into the trade-offs that there may be between innovations for increasing productivity 21.2 Materials and Methods and any risks and loss of system resilience. Smallholder systems are very diverse The study focused on five sites in Rwanda, owing to the large variability in agro-ecological Burundi and Democratic Republic of Congo and socio-economic conditions in which they (DR Congo). Three sites in Rwanda were operate. The variety of the farmers’ motiva- selected along an agro-ecological gradient tions and abilities is another factor contribut- (in terms of altitude, rainfall, soil fertility, and ing to the observed diversity. To encompass pest and disease pressure): Gatore sector in this complexity, innovations in smallholder the east, Musenyi in the south and Nzahaha systems should be based on a systemic diagno- in the west. The two sites in the other coun- sis of the agro-ecological potential, the socio- tries were Muyange in Burundi and Burhale economic context and the objectives of the farm in DR Congo, and these take into account the households (Hall and Clark, 1995), and specific diversity of institutional organization in attention should be paid to the multifunction- terms of agricultural policy and extension. ality of agriculture (McIntyre et al., 2009). The choice of the five study sites was based Most of the published results in agro- on covering the widest possible range in nomy are quantitative and collected off farm agro-ecological and sociopolitical conditions (Le Gal et al., 2011). They often focus on annual in a relatively small region (± 13,000 km2) that crops cultivated in monoculture and market- may appear quite homogeneous at first view. oriented systems (Scoones and Thompson, This range of site selection should allow us to 2011). To take into account dim ensions such as better understand the drivers of farm diver- food and income security, div ersity and risk sity in banana-based systems. avoidance, complementary approaches using For the sake of homogeneity, we limited additional indicators should be proposed. the scope of our study to the banana-based These will include assessing the multifunct- cropping system. Indeed, the banana crop is ionality of agricultural systems, e.g. including an ideal entry point into the agricultural sys- ecosystem services, while measuring the agri- tems of the Great Lakes region, as banana has cultural productivity (food and income per unit a role in food, income and the social life of the resource invested), and also including impor- population. This explains why most small- tant social dimensions and off-farm linkages, holders have a banana plantation around i.e. how farmers are linked to markets and net- their compounds. works of innovation. Our approach focuses on From 2009 to 2011, we conducted regular the farm level and aims to encompass all dimen- field surveys in each study site. During this sions of production in smallholder systems. period, the first author conducted six field In the banana-growing areas of the trips that varied in duration from 2 weeks East African highlands (Uganda, Rwanda, to 3 months. Each visit was an opportunity Burundi, eastern Democratic Republic of for contact with farmers. In this chapter, we Congo, north-west Tanzania and west Kenya), focus on two survey phases: an individual bananas occupy up to 30% of the cultivated survey conducted in 2009 and a complemen- land (van Asten et al., 2004) and banana pro- tary survey undertaken in 2011. During these duction plays a key role in the food security surveys, we used a combination of qualitative and revenue of rural households (Gaidashova (semi-structured interviews) and quantitative et al., 2005; Ouma et al., 2010). From a historical (field measurements, economic valuation) perspective, banana-based systems are at methods to characterize, diagnose and com- the heart of the adaptation of small-scale prehensively understand the practices and agricultural systems to environmental and strategies of smallholder farmers. 168 J. Van Damme et al.

21.2.1 Qualitative component number who were either low, medium or high in terms of welfare. The socio-economic clas- During 2009, we carried out an individual sification was based on observations of farm- survey to: (i) identify any system constraints ers and perceptions by local key informants perceived by the farmers; (ii) characterize the and interviewed farmers, i.e. the reputational diversity of farm management practices; and method (Blanchet and Gotman, 2010). (iii) understand farmers’ strategies and the Data were collected on: (i) crop types, driving forces behind these choices. Given e.g bananas, beans, maize, and distribution; the time-consuming constraint of this type (ii) crop management practices; (iii) crop of data collection, we sampled 30 farmers production and its value; (iv) livestock (six per site) with the purpose of capturing owned and managed; (v) destination and maximum diversity. prices of farm products; and (vi) farm Comprehensive interviews were the income and expenditure. Most of the infor- main tool used to collect the data. They allow mation was obtained through the interviews. researchers to gather information on the Georeferenced measurements were used to ‘why’ of farmer decision making. We used an assess the total size of the farm and the area interview guide on key topics to tackle dur- of each individual plot. ing the interview, instead of a questionnaire Quantitative data were processed with a with fixed question and answer options. Such complex algorithm to compare the farm per- semi-structured interviews provide an atmos- formances at both the inter-regional and phere of open conversation. We systemati- intra-site level. The first step of this algorithm cally cross-checked the information provided produced a complete economic balance for by the interviewee with a field visit to vali- each farm by calculating its economic compo- date the data. The mode of interaction and nents from the quantitative data collected in the regular personal contacts generated a the field. In the second step, any missing relationship of trust that guaranteed a high information about the production of the dif- reliability of the collected information. ferent crops was estimated using the average The type of information collected was crop yield at the site. variable but substantial. To analyse the data, In this chapter, we will focus on outcomes we sorted and classified it. Then we tran- from descriptive variables of the farming scribed the interviews and compiled sum- system (farm size, type and area of crops, pro- mary tables that were combined with key ducts and flows), plus variables related to quantitative information (e.g. field measure- the gross income calculation (production and ments, production estimation, prices). Finally, prices of crops/products). Within the initial we coded the transcription with a set of key sample of 53 farmers, we discarded nine farm- words. This allowed us to analyse the inter- ers for whom more than 50% of the production view data, for example by extracting inter- had to be estimated by average values. In addi- viewee statements on specific keywords. In tion, a tenth farmer was discarded as a result of this way, the qualitative material can be easily a lack of information about the area of plots. retrieved throughout the research process. The final processed sample comprised 43 farmers: ten in Gatore, seven in Musenyi, seven in Nzahaha, ten in Muyange and nine in Burhale. 21.2.2 Quantitative component The qualitative and quantitative parts of the method were linked throughout the From February to April 2011, we conducted a process of research. The method is intrinsi- complementary survey to diagnose the pro- cally iterative. duction systems. The aim was to analyse the technical functioning of the farming systems and assess their economic performance. 21.3 Results Between nine and 12 farmers were selected in each site, resulting in a total of 53 farms. The structure of the banana plantations dif- Among these farmers, there was an equal fered among sites. Beer bananas were dominant Comparative and Systems Approach to Banana Cropping 169

in Burundi and DR Congo, while the pro- with residues of banana, crops and weeds. portion of banana for beer, cooking or des- All these mulch types were used in east and sert was more even in the Rwandan sites. in south Rwanda, whereas plantations in the Cooking bananas were predominant in the other sites relied heavily on self-mulching east Rwandan site. Plantains were only and weed residue only. In Burundi, a part of significantly present in the DR Congo site. the banana wastes from juice/beer produc- Intercropping in banana was widely tion was used for the mulching of coffee observed in the Burundi sites (especially plantations (Plate 17). with beans and maize), was intermediate Farm size ranged from 0.05 ha to 5.53 ha in Rwandan sites and uncommon in the (Fig. 21.1). The farms were smallest in the DR Congo site. Plant density increased from DR Congo site, with a median of 0.2 ha. The east to west in line with the gradual increase Burundi and west Rwanda sites had inter- of rainfall from eastern Rwanda to the mediate farm sizes (medians of 0.61 and Albertine Rift in the west. The source of fer- 0.77 ha, respectively), while the median sizes tilization was essentially organic: compost of the farms in south Rwanda were 1.01 ha in all sites, cow manure in east and south and in east Rwanda 1.07 ha. The inter- Rwanda and goat manure in west Rwanda quartile range of farm sizes was greater in and DR Congo, but no use of manures in the Rwandan sites than at other sites, par- Burundi. Wastes from the production of ticularly in the east. juice/beer were used in sites where banana Annual productivity (US$/ha) was was processed. Mulching sources were vari- related to farm size (Fig. 21.2). Even if ous: mulching with grass and self-mulching each site had a specific distribution, the

2 Farm size (ha) by site/region

0 DR Congo East West Burundi South Burhale Rwanda Rwanda Muyange Rwanda Gatore Nzahaha Musenyi

Fig. 21.1. Box plots representing for each study region the median farm size (thick horizontal lines), the 25% and 75% percentiles (bottom and top of boxes) and the values corresponding to 1.5 times the interquartile distance (lower and upper bars). The individual point is an outlier. DR Congo, Democratic Republic of Congo. 170 J. Van Damme et al.

12000

10000

8000

6000

Productiivity (US$/ha) 4000

2000

0 0.01 0.1 1 10 Farm size (ha) (log scale)

Burundi DR Congo East Rwanda South Rwanda West Rwanda

Fig. 21.2. Productivity by farm size for each study region, measured as annual gross income in US$/ha.

optimum productivity for all sites was Rwanda) and Burhale (DR Congo) recorded reached at 0.72–1.07 ha, with the exception the highest number of crops per farm, of the DR Congo site, where farm sizes whereas the Burundi site had the lowest were generally smaller and the highest number, with a median of seven. However, productivity was observed at 0.2 ha. in Burundi – as with east Rwanda and The farms were grouped into three cat- DR Congo sites – the widest range of crop egories based on the shifts of the distribu- number per farm was recorded, ranging tion of the number of crop types by farm from five to 14. It is also noteworthy that the (Fig. 21.3). In the first category, the farm medium-sized intermediate farm category 2 size (0.05–0.13 ha) and the number of crops presents a larger range of crop types than (3–7) in the farms were very limited. The the other two (small and large) categories second category, with medium farm sizes (Fig. 21.4b). (0.17–1.50 ha), presents a large range of possible number of crop types (5–16). The third category is characterized by larger farms (1.71–6.32 ha) with a high number of 21.4 Discussion crops (10–14). The mean productivity in the medium size category is almost 1.5 times Our findings are valid for the small-scale the average of the other two categories sample that we analysed. They are the first (Table 21.1). attempt to characterize the diversity and On average, ten different crops were complexity of banana-based systems at the cultivated per region (Fig. 21.4a). With a village scale; extrapolation to the country median of 11 crops, Musenyi (south level should be avoided. Comparative and Systems Approach to Banana Cropping 171

The qualitative representation of the less important than the frequency with which diversity of farm management practices they are produced, while in east Rwanda, (Plate 17) provides the framework within food bananas are predominant and give which to explore why farmers adopt these bigger bunches with a low density of plant- practices. In Burundi, for example, even if ing. Understanding the perceptions and the cow manure is available, farmers do not use mechanism of decision making is a prere- this source of organic matter because they quisite to building and implementing more consider it to be the source of disease for suitable recommendations and innovations banana. The high density of plantations in (Hall and Clark, 1995). DR Congo compared with east Rwanda was Our results confirm the small-scale char- linked to the choice of banana type and to acteristic of banana-based farming systems rainfall. In DR Congo, farmers favour beer (Fig. 21.1). With a mean area of 1.04 ha, the bananas, for which the weight of bunches is sizes of the sampled sites of the Great Lakes

8 No. of crops 6

0 0.01 0.1 1 10 Farm size (ha) (log scale)

East Rwanda South Rwanda West Rwanda Burundi DR Congo

Fig. 21.3. The number of crops per farm in relation to farm size (log scale) across the five study sites. The boxes on the left and right indicate the four category 1 farms and the eight category 3 farms (see Table 21.1). DR Congo, Democratic Republic of Congo.

Table 21.1. Classification of farms on the basis of the farm size (mean ± standard deviation).

Category 1 Category 2 Category 3

Number 4 31 8 Mean size (ha) 0.09 ± 0.03 0.63 ± 0.36 3.14 ± 1.20 Median size (ha) 0.10 0.56 2.9 Mean annual productivity (US$/ha) 1534 ± 1162 2785 ± 2170 1416 ± 477 Median productivity 1489 2227 1236 Mean number of crop types 5.0 ± 1.8 9.4 ± 2.7 12.8 ± 1.5 172 J. Van Damme et al.

(a) 16

No. of crops by site/region 4

0 DR Congo East West Burundi South Burhale Rwanda Rwanda Muyange Rwanda Gatore Nzahaha Musenyi

(b) 16

8 No. of crops

0 Small Medium Large Farm Size

Fig. 21.4. Box plots representing the number of crop types in a farm: (a) per site/region; and (b) per size of farm. The plots show the median values (thick horizontal lines), the 25% and 75% percentiles (bottom and top of boxes) and the values corresponding to 1.5 times the interquartile distance (lower and upper bars). The individual point is an outlier. region are above the estimates for Rwanda Rwanda site, was interesting. Recent agricul- (0.71 ha) (Jayne et al., 2003). The relatively tural/rural policies in Rwanda, e.g. the mod- large inter-quartile range of Rwandan farm ernization and professionalization of the sizes (Fig. 21.1), particularly at the east rural population, land consolidation and Comparative and Systems Approach to Banana Cropping 173

the allocation of land to refugees, particularly systems in the Great Lakes region. On the in east Rwanda, may have contributed to a one hand, the quantitative analysis provides widening of the range of farm size. Earlier, a diagnostic of farming systems in character- Ansoms and McKay (2010) observed a large izing their diversity and appraising their heterogeneity in the distribution of income agro-ecological and economic potentialities. in the rural populations of Rwanda, but a On the other hand, a qualitative approach similar negative correlation between farm is necessary to understand the systemic size and productivity. aspects: to understand farmers’ choices and The whole-farm productivity per unit practices, to acknowledge their complexity of land highlights the efficiency of small- and decipher their vision of the process of holder farmers. Whereas productivity incre- innovation. This synergy is clear with the ases with farm size in the lower half of the example for Burundi in the (non-)use of distribution, beyond a threshold of around manure. 1 ha a decrease is observed. In addition, very small farms (0.05–0.13 ha) seem more efficient than the largest farms of the sample (1.70–5.53 ha). The higher productivity of 21.5 Conclusion small than large farms is widely documented in the literature (Lipton, 2010). We Smallholder farming systems are diverse, intend to proceed with further analyses of complex and efficient in land use. Their data to reach an understanding of the main assessment requires interdisciplinary app- factors driving this relationship between roaches and a relationship of trust. This farm size and productivity. study illustrated the large diversity of The agrarian systems in the Great farming systems in an area that may seem Lakes region are not only land use efficient, homogeneous at first hand. Our study they are also complex: an average of nine confirms the relatively high efficiency in different crops were cultivated on a farm terms of land productivity of small-scale size of 1 ha. While the range of number of compared with large-scale farms. A com- crops cultivated is narrow for small and prehensive diagnostic, including causal large farms, the range in the medium size dimensions, is a first requirement in under- category – the most represented category – standing the processes of innovation. It will is wide. This may reflect a specific strategy pave the way for open-minded exploration for minimizing risk in the medium size of the options for the development of rural category. Another indicator of coping with areas in Central Africa. risk (not developed in this study) is the intensity of intercropping, particularly in south Rwanda and DR Congo, where the number of crop types is high despite small Acknowledgements farm size. Both indicators (number of crops and intercropping) were put forward by We acknowledge the support of Belgium Cochet (1998, 2001) as the result of a his- Fonds de la Recherche Scientifique (FNRS)- torically complex process of intensification Fonds pour la Formation à la Recherche dans of the agrarian systems of the region. He l’Industrie et dans l’Agriculture (FRIA), the explained most of the dynamics of intensi- CIALCA (Consortium for Improving fication by intercropping and an increase in Agriculture-based Livelihoods in Central the number of crop cycles and crop types Africa) staff and Belgian cooperation. The (Cochet, 2001). comments and suggestions of an external The quantitative and qualitative dimen- reviewer and editor were appreciated. A spe- sions of the study are complementary in fol- cial thanks to the farmers interviewed and the lowing the diversity of the banana-based translators. 174 J. Van Damme et al.

References

Ansoms, A. and McKay, A. (2010) A quantitative analysis of poverty and livelihood profiles: the case of rural Rwanda. Food Policy 35, 584–598. Blanchet A. and Gotman, A. (2010) L’Enquête et ses Méthodes: L’Entretien, 2nd edn. Armand Colin, Paris. Chappell, M.J. and LaValle, L.A. (2009) Food security and biodiversity: can we have both? An agroecological analysis. Agriculture and Human Values 28, 3–26. Cochet, H. (1998) Burundi: quelques questions sur l’origine et la différenciation d’un système agraire. African Economic History 26, 15–62. Cochet, H. (2001) Crises et Révolutions Agricoles au Burundi. Karthala Editions, Paris. De Schutter, O. and Vanloqueren, G. (2011) The new green revolution: how twenty-first-century science can feed the world. Solutions 2, 33–44. Gaidashova, S., Okech, S., Gold, C. and Nyagahungu, I. (2005) Why beer bananas: the case for Rwanda. InfoMusa 14(1), 2–6. Hall, A. and Clark, N. (1995) Coping with change, complexity and diversity in agriculture – the case of rhizobium inoculants in Thailand. World Development 23, 1601–1614. Jayne, T.S., Yamano, T., Weber, M.T., Tschirley, D., Benfica, R., Chapoto, A. and Zulu, B. (2003) Smallholder in come and land distribution in Africa: implications for poverty reduction strategies. Food Policy 28, 253–275. Le Gal, P.Y., Dugué, P., Faure, G. and Novak, S. (2011) How does research address the design of innovative agricultural production systems at the farm level? A review. Agricultural Systems 104, 714–728. Lipton, M. (2010) From policy aims and small-farm characteristics to farm science needs. World Development 38, 1399–1412. McIntyre, B.D., Herren, H.R., Wakhungu, J. and Watson, R.T. (eds) (2009) International Assessment of Agricultural Knowledge, Science and Technology for Development, Volume 1: The Global Report: Agriculture at a Crossroads. Island Press, Washington, DC. Ouma, E., Jagwe, J., Obare, G.A. and Abele, S. (2010) Determinants of smallholder farmers’ participation in banana markets in Central Africa: the role of transaction costs. Agricultural Economics 41, 111–122. Scoones, I. and Thompson, J. (2011) The politics of seed in Africa’s Green Revolution: alternative narratives and competing pathways. IDS Bulletin 42, 1–23. van Asten, P., Gold, C., Okech, S., Gaidashova, S., Tushemereirwe, W. and De Waele, D. (2004) Soil quality problems in East African banana systems and their relation with other yield loss factors. InfoMusa, 13(2), 20–24. von Braun, J. (2005) Small-scale farmers in liberalised trade environment In: Huvio, T., Kola, J. and Lundström, T. (eds) Small-scale Farmers in Liberalised Trade Environment, Proceedings of the Seminar on October 2004 in Haikko, Finland. Department of Economics and Management, University of Helsinki, Finland. Publication 38, pp 21–52. 22 Agronomic Practices for Musa across Different Agro-ecological Zones in Burundi, Eastern Democratic Republic of Congo and Rwanda

W. Ocimati,1* D. Karamura,1 A. Rutikanga,2 C. Sivirihauma,3 V. Ndungo,4 J. Ntamwira,5 M. Kamira,5 J.-P. Kanyaruguru6 and G. Blomme1 1Bioversity International, Kampala, Uganda; 2Bioversity International, Kigali, Rwanda and Higher Institute for Agriculture and Animal Husbandry (ISAE), Rwanda; 3Bioversity International, Butembo, North Kivu, Democratic Republic of Congo; 4Université Catholique du Graben (UCG), Butembo, DR Congo; 5Institut National pour l’Etude et la Recherche Agronomique (INERA), Mulungu Research Station, Bukavu, Democratic Republic of Congo; 6Bioversity International, Bujumbura, Burundi

Abstract The Great Lakes countries of East and Central Africa, including Rwanda, Burundi and the Democratic Republic of Congo (DR Congo) are a secondary centre of Musa diversity, especially for East African highland bananas (Musa AAA-EA group) and plantains (ABB). Musa cultivation in this region is characterized by low annual productions (5–30 t/ha). This is caused by biotic (pests and diseases) and abiotic (soil fertility and drought) factors. The impacts of these factors are, however, influenced by the different agronomic practices that are applied on farm. This study assessed the use of some key agronomic practices by Musa farmers across districts of Rwanda and Burundi, and the South and North Kivu provinces of eastern DR Congo. Farms in North Kivu were less intensively managed than those in Burundi, Rwanda and South Kivu. For example, farms in North Kivu were the least de-trashed (removal of dead leaves from the pseudostem, 66%) and de-suckered (63%) compared with 88% and 100% in Burundi, 93% and 99% in Rwanda and 89% and 100% in South Kivu, respectively. Agronomic practices such as seed selection and source, pseudostem splitting for mulch and weeding (mainly using the hand hoe) were similarly practised across the study sites. Suckers obtained from neighbourhood (76–100%) and own fields (0–39%) were the only source of planting material used by farmers at the time of this study. This has negative implications for the management of key plant pests and diseases. The use of hand hoes for weeding, though helpful for intercropping, could perpetuate the spread of Xanthomonas wilt disease, which is currently prevalent on farms. De-budding was practised more in Burundi (98%) and South Kivu (96%) than in Rwanda (52%) and North Kivu (62%), although more farmers in South Kivu (68%, compared with <20% in other sites) de-budded on time (3 weeks after flowering, after appearance of the last hand). Agroforestry and fallowing, which are helpful for revitalizing soil fertility, were not popular in Burundi or Rwanda, possibly due to the high population density in these sites. Fallowing could also be obsolete because most farms in this region are over 50 years old. The study revealed the need to strengthen

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 175 176 W. Ocimati et al.

the extension of knowledge to farmers, especially in North Kivu where the farms are not intensively managed. Some of the recommended agronomic practices, such as de-trashing, de-suckering, de-budding and weeding need to be revised in the light of new emerging challenges, especially diseases such as Xanthomonas wilt, and high population density.

22.1 Introduction yields have primarily been attributed to poor and declining soil fertility and drought, The Great Lakes region of East and Central a high and sometimes increasing pressure of Africa is among the largest banana and plan- pathogens and pest damage, and suboptimal tain producing and consuming regions in crop management practices (Bekunda and Africa (Smale and De Groote, 2003). Annual Woomer, 1996; Gold et al., 1999; Karamura Musa (banana and plantain) production is et al., 1999; Stover, 2000; Bagamba, 2007; estimated at 2.75 million t (Mt) in Rwanda, Gaidashova et al., 2009; Wairegi et al., 2010; 0.13 Mt in Burundi and 1.57 Mt in the van Asten et al., 2011). Democratic Republic of Congo (DR Congo) The key biotic constraints include pests, (FAOSTAT, 2010). In addition, the crop ranks such as plant parasitic nematodes (Pratylenchus first in overall production in Rwanda, and goodeyi, Helicotylencus multicinctus, Radopholus second in Burundi and DR Congo (FAOSTAT, similis and Meloidogyne spp.) and the banana 2010). These three countries are also a second- weevil (Cosmo polites sordidus), and diseases ary centre of Musa diversity, especially for such as banana Xanthomonas wilt (caused East African highland bananas (Musa by Xanthomonas campestris pv. musacearum) AAA-EA) and plantains (Musa AAB) Fusarium wilt (caused Fusarium oxysporum (Swennen et al., 1995; Karamura et al., 2004; f.sp. cubense), black leaf streak (caused by Dhed’a et al., 2011). The Musa crop covers 23% Mycosphaerella fijiensis/Pseudocercospora fijiensis) of the total cultivated landscape (Mpyisi et al., and banana bunchy top disease (caused by 2000) and is grown by 90% of households banana bunchy top virus (BBTV), Babuvirus, (Lassoudière, 1989) in Rwanda, whereas in Nanoviridae). Burundi approximately 17% of the landscape The agronomic practices employed by is devoted to Musa production and it contrib- farmers influence the extent of the yield utes about 40% of the total food production in gap caused by the different biotic and abi- the country (Nkurunziza, 1991). In DR Congo, otic factors. For example, mulch obtained 70% of the banana and plantain crop is from old banana leaves and harvested produced in the eastern provinces, with a annual crops protects the soil against staggering 24% produced in North Kivu erosion (Baragengana, 1985). Early de-budding Province (Bakelana and Ndungo, 2004). (immediately after the appearance of the The large canopy of the Musa crop and last female hand on the bunch) has been its superficial root system protect the soil reported to prevent the spread of insect- against erosion (Baragengana, 1985), and thus mediated bacterial and fungal infections and lower soil erosion levels have been reported to result in bigger and more evenly filled in plots with banana compared with plots fruits (Stover and Simmonds, 1987; Blomme containing annual crops (Lufafa et al., 2003). et al., 2005). In addition, split pseudostems The crop is mainly cultivated by smallholder can be used as traps for capturing banana farmers whose farm sizes are <2 ha, and weevils (Gold et al., 1998; Gold, 2000). annual yields in the East and Central African The diagnostic survey reported here region are low (5–30 t/ha) (Wairegi et al., therefore determined the agronomic practices 2010; Okumu et al., 2011) compared with the employed by farmers across banana produc- yields of >70/t/ha that are observed at some tion zones in Burundi, Rwanda and the east- research stations (van Asten et al., 2004) and ern DR Congo (North and South Kivu in some farmer fields in high rainfall areas provinces). The results of the study will be (>1500 mm/year). The predominantly low used to determine priorities in regional Musa Agronomic Practices for Musa 177

research and extension for improving banana standing pseudostem), de-budding (removal and plantain production in these countries. of the male section of the inflorescence) and weeding practices. Data were compiled and analysed to generate tables and figures using 22.2 Materials and Methods the SPSS Statistics software package and Microsoft Excel software. The Musa diagnostic survey was carried out in different agro-ecologies of Rwanda, Burundi and eastern DR Congo (North Kivu 22.3 Results and Discussion and South Kivu) in 2007. In Rwanda, five districts representing different agro-ecologies were selected along a transect from Rusizi, 22.3.1 Selection of planting material bordering Lake Kivu (Western Province), to Kirehe District (Eastern Province) at the The responsibility for selection of planting border with Tanzania. In Burundi, three materials was entirely that of the head of the provinces were selected, namely Cibitoke in household (Table 22.1), except in North Kivu the north-west, Kirundo in the north and and Burundi, where in 10% of households Gitega in the central region. In eastern any household member could select materi- DR Congo, four representative and key als to plant. There were five possible sources banana-growing localities were selected in of planting material of banana and plantain. both North and South Kivu; the sampled local- These included suckers from fields that were ities included Maboya, Mangodomu, Munoli in production, suckers from field sucker mul- and Mutwanga in North Kivu, and Burhale, tiplication plots, plantlets obtained from Kabamba, Luhihi and Lurhala in South Kivu. micro-corms grown out in nurseries, plantlets The study site selection criteria included obtained from full corms placed in a substrate biophysical and socio-economic characteris- in a humidity chamber and subsequently tics (e.g. wealth status and land holding size), transplanted to a seedbed/nursery, and tis- access to markets and the presence of local sue culture plants grown in two-phase nurs- farmers’ organizations and non-government eries (FAO, 2010). Of these sources, suckers organizations (NGOs) that have an interest in obtained from fields that are in production, banana production and the capacity to use either from neighbours (76–100%) or from the the knowledge generated. farmers’ own farms (0–39%) was the only This diagnostic survey built on the par- source of planting material across the study ticipatory rural appraisal and baseline sur- sites (Table 22.1). Reliance on suckers from veys that were conducted in the framework farmers’ own and neighbours’ farms was due of the Consortium for the Improvement of to the lack of capacity in the study regions for Agriculture-based Livelihoods in Central the production of propagation material Africa (CIALCA) project across the same through other methods. provinces in 2006 (CIALCA, 2008). This on- The type and source of planting materials farm diagnostic survey quantified farming have great implications for the control of key systems through individual household inter- pests and diseases (Table 22.2) (FAO, 2010) views. In Rwanda, a total of 118 farmers/ and farm yields. The main Musa pests com- farms were sampled, while a total of 132 farms prise the banana weevil and nematodes, while were sampled in Burundi. In the North and the key diseases are banana Xanthomonas South Kivu provinces, 30 farms were ran- wilt, Fusarium wilt, banana bunchy top dis- domly sampled per locality, giving a total of ease (BBTV) and the banana streak virus 120 farmers/farms per province. Data were (BSV). Cropping systems reliant on suckers collected on key agronomic practices, such are characterized by a high pest and disease as selection and type of planting materials, incidence that builds up over subsequent fallowing, agroforestry and de-suckering cropping cycles and contributes to low yields. (removal of unwanted lateral shoots), de- Dependency on suckers results in a high risk trashing (removal of dead leaves from the of pest and disease transmission, especially 178 W. Ocimati et al.

Table 22.1. Frequency (%) of Musa planting material selection practices (i.e. responsibility for selection, type and source of planting materials) across the four study regions. Data were collected during a Musa diagnostic survey in 2007.

North Kivu, South Kivu, Burundi Rwanda DR Congob DR Congo (n = 129)a (n = 118) (n = 120) (n = 120)

Selection, type and source of planting materials Proportion (%) of farmers/farms

Responsibility for Head of household 86.0 99.0 90.0 100.0 selecting planting Any family member 8.0 1.0 10.0 0.0 materials Labourer 2.0 0.0 0.0 0.0 Spouse 2.0 0.0 0.0 0.0 Head of household 2.0 0.0 0.0 0.0 and spouse Total 100.0 100.0 100.0 100.0 Type of planting Suckers 100.0 100.0 100.0 100.0 material used Tissue cultured plantlets 0.0 0.0 0.0 0.0 Macropropagated plants 0.0 0.0 0.0 0.0 Corm bits 0.0 0.0 0.0 0.0 Total 100.0 100.0 100.0 100.0 Source of planting Neighbour 76.2 82.2 99.2 100.0 materials Own garden 39.2 22.0 34.5 0.0 Research institute 0.8 0.0 0.0 0.0 Other districts 1.5 0.0 0.0 0.0 Neighbouring country 0.0 0.0 0.8 0.0 Total mrqc mrq mrq mrq an, no. farms/farmers sampled; bDR Congo, Democratic Republic of Congo; cmrq, the question is a multiple response question and therefore the totals do not equal 100%.

Table 22.2. Risk of transmission of pests and diseases for five Musa multiplication methods when accompanied by rigorous application of recommended cultural practices. The latter include seed selection and preparation practices, e.g. use healthy suckers (free of pests and diseases) obtained from mother gardens established with tissue cultured plantlets of desired varieties, corm paring and boiling water treatment of suckers. Transmission risk is assessed as: 0, zero risk; 1, low risk; 2, moderate risk; and 3, high risk; numbers in parentheses indicate risk with limited use of good multiplication practices. If the pest or disease is not present in the region or country, the risk is substantially lower. Source: FAO, 2010.

Pest or disease/ Suckers selected Suckers grown method of from field in a multiplication multiplication in production plot Micro-corms Macropropagation Tissue culture

Bacterial diseases 2 (3) 1.5 (2.5) 1 (2) 2 (2) 0.5 (1) Banana bunchy top 2 (3) 1.5 (2.5) 1 (2) 2 (2) 0 (3) virus (BBTV) Banana streak 1 (2) 1 (2.5) 1 (2) 2 (2) 2 (3) virus (BSV) (Plantain) Other viruses 2 (3) 1.5 (2.5) 1 (2) 2 (2) 0.5 (0.5) Fusarium wilt 2 (3) 1.5 (2.5) 1 (2) 2 (2) 0.5 (0.5) Nematodes 1 (3) 1 (2) 0 (2) 0 (2) 0 (2) Weevils 1 (3) 1 (2) 0 (2) 0 (0) 0 (0) when other recommended cultural practices paring and/or boiling water treatment for are not applied (e.g. the selection of healthy the removal of weevil larvae and plant suckers from mother gardens established parasitic nematodes) (Table 22.2) (FAO, with clean tissue cultured plantlets, corm 2010). The dependency on suckers obtained Agronomic Practices for Musa 179

from farmers’ own and neighbouring fields which is growing at a rate of about 3.6% in Central African small-scale farmer set- per annum – one of the highest population tings has been reported to greatly contri- growth rates in the world. Similarly, Burundi bute to the Xanthomonas wilt problem in is densely populated (about 232 people/km2) the region (Ndungo and Lubanga, 2006; with the average arable agricultural land Ndungo et al., 2008). holding per household in 1995 at 0.85 ha (Rishirumuhirwa and Roose, 1998). Farmers in these regions have therefore abandoned 22.3.2 Agroforestry and fallowing the traditional methods of shifting cultivation and fallowing. Growing trees within banana farms is an Fallowing was not a popular practice important agro-ecological intensification across the study region. Some 67% of Musa practice. Agroforestry was more commonly farmers in North Kivu and 98% in South practised in North Kivu (61%) and South Kivu did not fallow their banana/plantain Kivu (52%), with only 30% of Musa farmers in fields (Table 22.3). This was mainly Rwanda and 1% in Burundi practising agro- attributed to small-sized land holdings forestry on their banana farms (Table 22.3). (Table 22.3). It should be noted, however, The low levels of agroforestry practice in that the Musa crop is perennial, with most Burundi and Rwanda could be due to the plantations in this region being over 50 years high population density and correspondingly old, thus making the practice of fallowing small land holdings compared with those in less practical. Moreover, the large banana eastern DR Congo. Voortman et al. (2003) leaves and canopy, the widespread superfi- report the East African highlands as one of cial root system and mulch obtained from the most densely populated and intensively old banana leaves and harvested annual cultivated agricultural zones in Africa. The crops improve the fertility of the soil and rapid growth in population has resulted in protect it against erosion (Baragengana, increase in land pressure (Fermont et al., 1985), thereby minimizing the need for 2008). For example, Rwanda currently has the fallowing. Nevertheless, the few farmers that highest population density (359 people/km2) fallowed their land aimed to improve the in Africa, with a population of 8.5 million, fertility of their soil (Table 22.3). A negligible

Table 22.3. Frequency (%) of Musa farmers practising agroforestry and fallowing across the four study regions. Data were collected during a Musa diagnostic survey in 2007.

North Kivu, South Kivu, Burundi Rwanda DR Congob DR Congo (n = 129)a (n = 118) (n = 120) (n = 120)

Question Response Proportion (%) of farmers/farms

Practice agroforestry Yes 0.8 29.7 60.8 51.7 No 99.2 70.3 39.2 48.3 Total 100.0 100.0 100.0 100.0 Practice fallowing Yes 14.3 4.2 32.8 1.7 No 85.7 95.8 67.2 98.3 Total 100.0 100.0 100.0 100.0 Reasons for fallowing Control diseases 0.0 0.0 0.0 0.8 Improve soil fertility 12.4 3.4 38 0.8 A lot of land 0.0 0.8 0.0 0.0 Reasons for Small land size 83.7 95.8 50.8 97.5 not fallowing Soils are fertile 0.8 0.0 9.2 0.0 an, no. farms/farmers sampled; bDR Congo, Democratic Republic of Congo. 180 W. Ocimati et al.

(0.8%) fraction of farmers in South Kivu The main incentive behind de-suckering fallowed their land to control diseases. across the study sites was to improve crop vig- Xanthomonas wilt was not yet widespread our and yields (bunch size and weight) (from in South Kivu during the time of the 63% of farmers in North Kivu up to 93% in diagnostic survey, although this disease has Rwanda). A very small number of farmers spread widely over the past years across (2–3%) de-suckered to create space for annual both of the Kivu provinces. One of the intercrops (Table 22.4). In Burundi and North recommended practices for controlling this Kivu, 100% of the farmers had no clear pattern disease is the use of a fallow or break crop for de-suckering, while in Rwanda and South period of at least 6 months after the Kivu, circular and linear patterns were used by removal of diseased banana plants in various proportions of farmers (Table 22.4). heavily infected fields, which allows risk- Most of the farmers in Rwanda (98%) and free re-establishment of banana fields using North Kivu (96%) de-suckered at the onset of clean banana plantlets (Brandt et al., 1997; the rains, after weeding their plantations, so as Turyagyenda et al., 2008). to create space for intercropping with annual crops, especially beans. In contrast, most farmers in Burundi and South Kivu de-suckered either midway through the rainy season or 22.3.3 De-suckering when they found it necessary (Table 22.4). Most of the farmers (51% in Burundi and 78% De-suckering is a key agronomic practice in in South Kivu) that de-suckered when they banana plantations and is aimed at maintain- found it necessary fell into the category of ing appropriate plant density and ensuring farmers that maintained between two to four that the number of bunch-bearing plants is suckers per mat. The number of suckers maintained at a level that reduces com- maintained per mat varied from one to ten, petition for available resources (water, light, with most farmers maintaining two to four nutrients) (Tushemereirwe et al., 2001). suckers per mat (Table 22.4). De- suckering Across the study sites, the proportion of the banana mat to three plants at various farmers who did not de-sucker their planta- growth stages (mother, daughter and grand- tions varied between 4% in Rwanda and daughter) is recommended to increase bunch 35% in North Kivu (Table 22.4). In Burundi size (Tushemereirwe et al., 2001). and South Kivu, 11% of the farmers did not de-sucker their plantations. The extent of de-suckering is a direct indication of the intensity with which farmers manage their 22.3.4 Removal of old banana plantations. For example, in North Kivu, leaves (de-trashing) which has the highest number of farmers who did not de-sucker their plantations, De-trashing involves the removal of old farmers have been reported to put low effort banana leaves and functional leaves. Across into the management of their banana plan- the study sites, nearly 100% of farmers de- tations (Ndungo et al., 2008). Farmers in this trashed their plants, except in North Kivu region are reported to only de-sucker when where 34% of farmers did not de-trash they need suckers for establishing new (Table 22.5). The timing of the practice also plantations, because of their fear of reduc- varied across the regions, with most farmers ing the plants and number of bunches har- in Burundi (69%) and South Kivu (95%) vested from a mat (C. Sivirihauma, North de-trashing only when necessary. In contrast, Kivu, DR Congo, 2012, personal communi- 100% of the farmers in Rwanda, and 94% in cation). This (lack of) practice could be sus- North Kivu de-trashed their banana plants at tained by the high soil fertility in this the onset of the rainy season, a practice that region, which can support a large number of they combined with weeding. De-trashing and plants per mat without severely affecting rigorous weeding are carried out at the onset of the yield per unit area. the rainy season for annual crop establishment Agronomic Practices for Musa 181

Table 22.4. De-suckering practices: reasons, methods and timing of de-suckering, and number of suckers maintained after de-suckering, across the four study regions. Data were collected during a Musa diagnostic survey in 2007.

North Kivu, South Kivu, Burundi Rwanda DR Congob DR Congo (n = 132)a (n = 118) (n = 120) (n = 120)

De-suckering practices Proportion (%) of farmers/farms

Practice de-suckering/ Not practised 10.6 4.2 35.0 10.7 reason for de-suckering Improve vigour of 87.8 93.2 63.3 89.1 selected suckers and yield (bunch size and weight) Create space for 1.5 2.5 1.7 0.0 intercropping with bananas Total 100.0 100.0 100.0 100.0 Method of de-suckering n for this question 118 113 78 107 Circular 0.0 18.6 0.0 4.7 Linear 0.0 39.8 0.0 63.6 Other (no clear pattern) 100.0 41.6 100.0 31.8 Total 100.0 100.0 100.0 100.0 When to de-sucker n for this question 118 113 78 107 Beginning of rainy 32.1 98.2 96.2 4.7 season to create space for intercropping (after weeding) When needed 54.0 1.8 0.0 82.2 Middle of rainy season 13.9 0.0 0.0 13.1 Dry season 0.0 0.0 3.8 0.0 Total 100.0 100.0 100.0 100.0 No. suckers left on a mat n for this question 114 113 76 100 1 0.0 0.0 0.0 2.0 2 0.0 31.9 2.6 55.0 3 24.6 45.1 10.5 36.0 4 52.6 18.6 25.0 6.0 5 15.8 3.5 21.1 1.0 6 1.8 0.9 23.7 0.0 7 0.9 0.0 9.2 0.0 8 2.6 –c 5.3 – 10 1.8 – 2.6 – Total 100.0 100.0 100.0 100.0 an, no. farms/farmers sampled; bDR Congo, Democratic Republic of Congo; c‘–’, not applicable.

(mainly of beans). The removal of old leaves is leaves also reduce air movement around recommended for the management of Sigatoka plants, thus encouraging high humidity leaf spot, as it limits its spread to young leaves build-up (Tushemereirwe et al., 2001). It should and plants, while the removal of old sheaths be noted, however, that with the high eliminates hiding places for adult banana prevalence of Xanthomonas wilt disease in weevils. In addition, old leaves shield the this region, only leaves that are completely dry young plants from sunlight (Tushemereirwe should be removed, so that transmission of the et al., 2001; Ssebunya, 2011). The non-functional disease by tools is prevented. 182 W. Ocimati et al.

Table 22.5. De-trashing of banana plants by Musa farmers, and the timing of de-trashing, across the four study regions. Data were collected during a Musa diagnostic survey in 2007.

North Kivu, South Kivu, Burundi Rwanda DR Congob DR Congo (n = 132)a (n = 117) (n = 116) (n = 120)

De-trashing practices Proportion (%) of farmers/farms

De-trashing Yes 100.0 99.1 66.4 100.0 No 0.0 0.9 33.6 0.0 Total 100.0 100.0 100.0 100.0 When to de-trash n for this question 132 117 77 120 Beginning of rainy 17.5 100.0 93.5 1.7 season (following weeding) When needed 68.9 0.0 0.0 95.0 Middle of the rainy 13.6 0.0 2.6 3.3 season During the dry season 0.0 0.0 3.9 0.0 Total 100.0 100.0 100.0 100.0 an, no. farms/farmers sampled; bDR Congo, Democratic Republic of Congo.

22.3.5 De-budding Gloeosporium musarum ( Tushemereirwe et al., 2001; Blomme et al., 2005; Molina, 2006; De-budding is the removal of the male bud. Ssekiwoko et al., 2006). This was more practised in Burundi (99% of Other motivations for de-budding inclu- farmers) and South Kivu (96%) than in North ded the prevention of lodging/pseudostem Kivu (62%) and Rwanda (52%) (Table 22.6). snapping (attributed to the additional weight Of those farmers who disbud, 95% in North of male buds) and inheritance of the practice Kivu, 89% in Burundi, 76% in South Kivu and from forefathers. Up to 8% of the farmers who 41% in Rwanda were driven by the objective de-budded did not know why it was done. of increasing the finger and/or bunch size. In The timing of de-budding varied across the addition, 46% of farmers in Rwanda, 8% in study sites. In South Kivu, most of the farmers Burundi and 3% in South Kivu claimed that (68%) de-budded 3 weeks after the app- de-budding accelerated bunch maturity. earance of the last female hand (i.e. 3 weeks De-budding immediately after the appearance after flowering), compared with only 19% in of the last female hand has been reported to Rwanda and 3% in Burundi (Table 22.6). increase the partitioning of assimilates to the In Burundi, most of the farmers (31%) remaining banana fingers (fruit) and thereby de-budded 1 month after flowering, or when increase fruit and bunch size (Tushemereirwe the fingers were fully filled (also 31%). Most et al., 2001). This could also have been of the Rwandan farmers de-budded 2 months conceived by farmers as an accelerated after flowering (48%), while those in North maturity. Kivu de-budded after bunches were fully Only 2–8% of farmers de-budded to prevent filled (67%). The timing of the de-budding insect-transmitted diseases. De-budding as soon practice across these sites, except South Kivu, as the last hand of the female bunch appears is was not ideal for the control of insect- recommended as a first line of defence against transmitted diseases. insect vector transmission of bacterial wilts and fungal diseases, e.g. Bugtok and Moko disease caused by Ralstonia solanacearum; Xanthomonas 22.3.6 Propping of banana plants wilt; blood disease caused by Pseudomonas celebensis; and cigar end rot caused by either Verti- Propping up of banana plants is done to cillium theobromae, Trachsphaera fructigena and/or prevent plants with maturing bunches Agronomic Practices for Musa 183

Table 22.6. De-budding practices of Musa farmers across the four study regions. Data were collected during a Musa diagnostic survey in 2007.

North Kivu, South Kivu, Burundi Rwanda DR Congob DR Congo (n = 132)a (n = 117) (n = 117) (n = 120)

De-budding practices Proportion (%) of farmers/farms

De-budding Yes 98.5 52.1 62.4 95.8 No 1.5 47.9 37.6 4.2 Total 100.0 100.0 100.0 100.0 Reason for n for this question 125 61 76 112 de-budding Increases finger and 88.8 41.0 94.7 75.9 bunch size Accelerates maturity 8.0 45.9 0.0 2.7 Prevents insect-mediated 2.4 4.9 3.9 8.0 diseases Custom of our forefathers 0.8 0.0 0.0 0.0 Prevents lodging 0.0 0.0 0.0 8.9 Don’t know 0.0 8.2 2.2 3.6 Total 100.0 100.0 100.0 100.0 When to de-bud n for this question 118 58 76 113 3 weeks after flowering 3.4 19.0 0.0 68.1 (after the development of the last hand/ cluster) 1 month after flowering 31.4 24.1 0.0 0.0 1.5 months after flowering 0.0 1.7 0.0 0.0 2 months after flowering 16.9 48.3 0.0 4.4 3 months after flowering 0.0 6.9 0.0 0.9 When the fingers are 31.4 0.0 67.1 9.7 sufficiently filled When necessary 16.9 0.0 19.7 11.5 When weeding or doing 0.0 0.0 11.8 5.3 other field operations During the dry season 0.0 0.0 1.3 0.0 Total 100.0 100.0 100.0 100.0 an, no. farms/farmers sampled; bDR Congo, Democratic Republic of Congo. from breaking or toppling (Tushemereirwe to prevent lodging by strong winds and to et al., 2001). The weight of the banana bunch enable the pseudostem to support the heavy bends the bearing plant and can cause the bunch, respectively. Most of the farmers pseudostem to break, snap off (the corm either propped when the need arose or during breaks, leaving a part of it in the ground) or bunch development/fruit filling (post topple (the entire corm, with the roots, comes flowering) (Table 22.7). out of the ground) (Tushemereirwe et al., In Burundi, despite the fact that 41% 2001). Most of the farmers in Burundi (96%), of the farmers propped all cultivars, ‘Igisahira Rwanda (95%), North Kivu (93%) and, to a gisanzwe’, ‘Intuntu’, ‘Igisahira namujuba’, lesser extent, the farmers in South Kivu ‘Igipaca’ (all Musa AAA-EA), ‘Gros Michel’ (27%) propped their plants (Table 22.7). (Musa AAA, dessert) and ‘Igihonyi’ (AAA- All of the farmers in Burundi and Rwanda EA) were the most frequently propped propped to prevent pseudostem breakage/ (Fig. 22.1). In Rwanda, 96% of farmers lodging due to strong winds, while 47% propped all cultivars, with only 3% propping and 53% of those propping in North Kivu, tall varieties (Fig. 22.2). In North Kivu, and 97% and 3% in South Kivu, propped a total of 12 cultivars were propped, 184 W. Ocimati et al.

Table 22.7. Propping of Musa plants by farmers across the four study regions. Data were collected during a Musa diagnostic survey in 2007.

North Kivu, South Kivu, Burundi Rwanda DR Congob DR Congo (n = 132)a (n = 115) (n = 120) (n = 120)

Propping practices Proportion (%) of farmers/farms

Propping Yes 95.5 94.8 92.5 26.7 No 4.5 5.2 7.5 73.3 Total 100.0 100.0 100.0 100.0 Reasons for n for this question 125 106 116 120 propping Prevent wind breakage 100.0 100.0 46.6 96.6 of pseudostems Enable the pseudostem to 0.0 0.0 53.4 3.4 support a heavy bunch Total 100.0 100.0 100.0 100.0 Stage at which n for this question 125 110 116 87 propping done At flowering 0.0 0.9 1.7 0.0 During bunch development 25.6 57.3 47.4 3.4 Just before harvest 0.8 0.0 2.6 0.0 When need arises 73.6 41.8 48.3 96.6 Total 100.0 100.0 100.0 100.0 an, no. farms/farmers sampled; bDR Congo, Democratic Republic of Congo.

20 each/all cultivar/s % farmers propping 10

0 ‘Isha’ ‘Poyo’ ‘Igisubi’ ‘Intuntu’ ‘Ikiyove’ ‘Igiyove’ ‘Igipaca’ ‘Kayinja’ ‘Igihonyi’ ‘Incakara’ ‘Ikimaraya’ All cultivars ‘Inamajuba’ ‘Ikingurube’ ‘Inabukumu’ ‘Inagitembe’ ‘Gros Michel’ ‘Imporogoma’ ‘Mbwazirume’ All but ‘Kayinja’ ‘Yangambi Km5’ ‘Yangambi ‘Kamaramasengi’ ‘Igisahira gisanzwe’ ‘Igisahira namujuba’ ‘Igisahira

Fig. 22.1. Proportion (%) of farmers propping Musa cultivars in Burundi. Data collected during a Musa diagnostic survey in 2007. Vertical bars are 95% confidence intervals. with ‘Kitika sukari kiri’ (AAA, dessert), these cultivars are characterized by long ‘Vulambya’ (Musa AAB), ‘Mukingiro’ pseudostems and large bunch sizes. In South (AAA-EA), ‘Nguma’ (AAB) and ‘Intuntu’ Kivu, the predominantly propped cultivars being most frequently propped (Fig. 22.3); included ‘Ishika’ and ‘Barhabesha’ (both Agronomic Practices for Musa 185

AAA-EA), ‘Malaya’ (AAA, dessert), ‘Intuntu’ Other uses of harvested pseudostems, though and ‘Gros Michel’ (AAA, dessert) (Fig. 22.4). not common across the sites and among farmers, included composting (2%, in Burundi), feeding to animals (3%, in Burundi) and leav- 22.3.7 Use of pseudostems ing them standing in the fields (1%, in North from harvested plants Kivu). The main objective behind splitting and spreading pseudostems in the field was to Splitting pseudostems and spreading out maintain soil fertility, crop vigour and yield the leaf sheath sections in the field as mulch (71–99% of farms) (Table 22.8). An additional was common and practised by 95–100% of 20% of farms in Burundi and 1% in South farmers across the study sites (Table 22.8). Kivu split and spread pseudostems to reduce runoff and control soil erosion. Some farmers at some of the sites did not know why the

100 pseudostems were split and spread within the field despite practising this. The practice 80 is, however, important in the recycling of 60 nutrients, reducing runoff and water loss

cultivars through evaporation and in suppressing 40 weeds, so it could have a positive impact on

% farmers propping 20 productivity of the crop in these regions. The 0 use of pseudostems as a trap for banana wee- All cultivars All but Tall cultivars vils, a common practice in low-altitude areas, ‘Ikinyangurub’ was not noted in any of the farms across the Fig. 22.2. Proportion (%) of farmers propping three region, but it should be noted that most of categories of Musa cultivars in Rwanda. Data were the survey sites were located at high altitudes collected during a Musa diagnostic survey in 2007. (>1500 m above sea level) that do not support Vertical bars are 95% confidence intervals. the survival of banana weevils.

each cultivar 20 % farmers propping 10

0 ‘Kitoke’ ‘Kiware’ ‘Intuntu’ ‘Vuhind’ ‘Nguma’ ‘Mudjuva’ ‘Mukingiro’ ‘Kithavyira’ ‘Vulambya’ ‘Kitika sukari kiri’ ‘Kitika ‘Kamaramasengi’ ‘Kitika sukari kikuhi 2’ sukari kikuhi ‘Kitika

Fig. 22.3. Proportion (%) of farmers propping Musa cultivars in North Kivu. Data were collected during a Musa diagnostic survey in 2007. Vertical bars are 95% confidence intervals. 186 W. Ocimati et al.

35 30 25 20 15 cultivar/s 10 5

% farmers propping each/all 0 ‘Poyo’ ‘Nsha’ ‘Ishika’ ‘Intuntu’ ‘Malaya’ ‘Buhake’ ‘Gisukari’ ‘Cindege’ ‘Musheba’ ‘Kashulye’ ‘Bumpavu’ ‘Bulengere’ All cultivars ‘Kisamunyu’ ‘Gros Michel’ ‘Cibula nana’ ‘‘Nshungurhi’ ‘Barhabesha’ ‘Yangambi Km5’ ‘Yangambi ‘Kamaramasengi’

Fig. 22.4. Proportion (%) of farmers propping Musa cultivars in South Kivu. Data were collected during a Musa diagnostic survey in 2007. Vertical bars are 95% confidence intervals.

Table 22.8. Fate of harvested pseudostems and the reasons for the practice applied to them across the four study regions. Data were collected during a Musa diagnostic survey in 2007.

Reasons for the practice applied to harvested pseudostems

To maintain soil To control soil fertility for improved erosion and To feed Do not crop vigour and yield reduce runoff the cows know Total Fate of harvested pseudostems Proportion (%) of farmers/farms

Burundi Split and spread 71.2 19.7 –c 3.7 94.7 (n = 132)a out in the field (as mulch) Give to animals – – 3.0 0.0 3.0 Compost 2.3 0.0 – 0.0 2.3 Total 73.5 19.7 3.0 3.7 100.0 Rwanda Split and spread 94.9 0.0 0.0 5.1 100.0 (n = 117) out in the field (as mulch) Total 94.9 0.0 0.0 5.1 100.0 North Kivu, Split and spread 89.9 0.0 0.0 9.2 99.2 DR Congob out in the field (n = 119) (as mulch) Leave them 0.8 0.0 0.0 0.0 0.8 standing Total 90.7 0.0 0.0 9.2 100.0 South Kivu, Split and spread 99.2 0.8 0.0 0.0 100.0 DR Congo out in the field (n = 120) (as mulch) Total 99.2 0.8 0.0 0.0 100.0 an, no. farms/farmers sampled; bDR Congo, Democratic Republic of Congo.; c‘–’, not applicable. Agronomic Practices for Musa 187

22.3.8 Weed management current outbreak of Xanthomonas wilt disease, could lead to within-farm spread of The predominant method of weed manage- the disease. ment across the study sites was through the use of a hand hoe (92–100%) (Table 22.9). Other methods used included weed removal 22.4 Conclusion by hand and slashing. The frequency of weeding varied across the region, with most Some of the agronomic practices investigated, of the farmers in Rwanda (66%) and South such as seed selection and source, pseu- Kivu (43%) weeding three times a year, dostem splitting for mulch and hand weed- while those in North Kivu weeded twice a ing were more or less uniformly practised year (38%) slightly more often than they across the study sites/regions, while the weeded three times a year (36%). Mulching other practices varied by site/region. Suckers is commonly practised in the most intensive obtained from neighbourhood and farmers’ banana production systems in East and own fields were the only source of planting Central Africa (e.g. in south-western material used by farms at the time of this Uganda) as a form of weed management. study. This has great implications for the The mulch significantly reduces weed ger- management of plant pests and diseases. mination and growth, and weeds can then The use of hand hoes for weeding, though be easily removed by hand. The reliance on helpful for intercropping in these densely popu- hand hoes across the study sites in Burundi, lated areas, represents a threat for the perpetua- Rwanda and DR Congo could be due to the tion of Xanthomonas wilt disease problems low level of management of farms, although within farms. De-suckering and de-trashing it could also be due to the need to intercrop of plants were practised more in Burundi, banana plants with other crops such as Rwanda and South Kivu than in North Kivu. beans, a common practice in these regions. Farms in North Kivu were reported to be less Weed removal by hoeing can, however, lead intensively managed. De-budding was prac- to the cutting of plant roots and, with the tised more in Burundi and South Kivu than in

Table 22.9. Weed management on banana farms at sites across the four study regions. Data were collected during a Musa diagnostic survey in 2007.

North Kivu, South Kivu, Burundi Rwanda DR Congob DR Congo (n = 132)a (n = 116) (n = 118) (n = 120)

Proportion (%) of farmers/farms

Weed control method Remove by hand 25.8 6.9 0.0 0.0 Remove by hoe 93.2 92.2 98.3 100.0 Slashing 0.0 0.9 11.0 0.0 Frequency of weeding 1× NDc 0.0 13.6 4.2 2× ND 18.1 38.1 19.5 3× ND 65.5 35.6 43.2 4× ND 16.4 11.0 24.6 5× ND 0.0 0.8 4.2 6× ND 0.0 0.8 1.7 10× ND 0.0 0.0 0.8 12× ND 0.0 0.0 1.7 When needed ND 0.0 0.0 0.8 an, no. farms/farmers sampled; bDR Congo, Democratic Republic of Congo.; cND, not determined. 188 W. Ocimati et al.

Rwanda and North Kivu, but the timing of especially those from diseases such as the practice was optimal only in South Kivu. Xanthomonas wilt and the high rate of The propping of banana plants was least population increase. practised in South Kivu. Agroforestry and fallowing, which are helpful in revitalizing soil fertility, were Acknowledgements least practised in Burundi and Rwanda. This can be attributed to the high popula- The Belgian Directorate General for Devel- tion density. Fallowing could also be obso- opment (DGD), which funded this study, is lete in many cases due to the fact that most gratefully acknowledged. In addition, the Musa farms in this region were over 50 years Institut des Sciences Agronomiques du old. Agroforestry and fallowing are thus not Burundi (ISAR), the Rwandan Agricultural practical options for improving soil fertility in Board (RAB), the Université Catholique du these regions. Graben (UCG) in North Kivu, DR Congo and The study revealed the need to strengthen the Institut National pour l’Etude et la the extension of knowledge to farmers, espe- Recherche Agronomique (INERA), Mulungu, cially in North Kivu, where farms are not South Kivu, DR Congo are acknowledged intensively managed. It should also be noted for their crucial role in data collection. The that some of the recommended agronomic authors also gratefully acknowledge the farm- practices – such as de-trashing, de-suckering, ers of the surveyed localities across the three de-budding and weeding – need to be revised countries who provided the information used in the face of new and emerging challenges, in this study.

References

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A.M. Rietveld,1* S. Mpiira,1,2 W. Jogo,1 C. Staver3 and E.B. Karamura1 1Bioversity International, Kampala, Uganda; 2National Agricultural Research Organisation (NARO), Kampala, Uganda; 3Bioversity International, Montpellier, France

Abstract Beer banana farming systems in central Uganda are important for the livelihoods of smallholder farmers, especially for those that process the bananas into beer and spirits, but also for rural retailers that sell the products. We conducted an exploratory study focusing on the different actors involved in the beer banana value chain, on its importance for those actors and on the dynamics within the chain. The value chain of banana beer and spirit is short and local, with most of these products being consumed in the locality. Only small amounts of banana beer and spirit from central Uganda find their way to urban centres such as Kampala. The bacterial disease Xanthomonas wilt has greatly affected the production of beer bananas, and we report production declines of 65% in two of the study sites. Improved linkages between non-brewers and brewers and between brewers and markets could assure supply and increase prices, giving an incentive for both brewers and non-brewers to invest more in disease control and in quality production.

23.1 Introduction 10% of total land under banana in Uganda. The brewing type – or beer banana – currently With a total production of 1,552,100 t/year most cultivated is the ‘Pisang awak’ (local (FAOSTAT, 2008), banana (Musa spp.) is one name ‘Kayinja’, from the ABB genome of the main crops in Uganda. Four different group), but the dessert banana ‘Kisubi’ types of banana, based on use, can be distin- (AB genome group) and some EAHB AAA guished: cooking, roasting, dessert and brew- cultivars (e.g. ‘Mbidde’) are also used for ing types (Mgenzi et al., 2005). The majority of juice extraction and brewing. bananas produced in Uganda are of the cook- In central Uganda especially, the farming ing type (East African highland banana system is commonly based on the beer banana (EAHB) AAA genome group) locally referred ‘Kayinja’ because of the relative higher suita- to as ‘matooke’. Matooke, which is prepared bility of this crop for the erratic rainfall, low for eating by steaming wrapped in banana soil fertility and high pest and disease pres- leaves, is the preferred staple food in most sure associated with the lower altitudes of regions of Uganda. According to Spilsbury the Central Region in comparison with cook- et al. (2002), the brewing types account for ing (matooke) types. The ‘Kayinja’ system

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 191 192 A.M. Rietveld et al.

traditionally receives little management, integration of trees, fodder crops and goats in which allows for labour allocation elsewhere. banana-based farming systems at three sites The beer bananas are processed on farm into in central Uganda. The project sites were the commercial products banana beer and gin Lwamata in Kiboga District, Kasana in (waragi). Alcohol consumption is high in Nakaseke District and Mateete in Sembabule Uganda (WHO, 2004), and the large majority District. Banana is a main crop at all three of alcohol consumed consists of such home- sites. Baseline and monitoring data from the made brews. With the rapidly increasing pop- project were used in this study, together with ulation and rising incomes, the demand for additional data collected especially for our alcoholic beverages is expected to increase. purpose. That seems good news for banana farmers The baseline household survey was con- who earn a large share of their total income ducted with a total of 208 respondents. The through beer banana production and brew- focus of the survey was on household compo- ing. However, this farming system has come sition and characteristics, the presence of under serious threat from the disease crops, trees and livestock, plot management Xanthomonas wilt caused by the bacterium and land issues, and livelihood strategies. Xanthomonas campestris pv. musacearum. The From the baseline population, 25 farmers disease made its entry into Uganda just over were selected per site (based on the research- a decade ago (in 2001) and is ‘rapid and disas- ers’ and farmers’ own criteria) to form a trous’ in its effects (Tinzaara et al., 2011). As a farmers’ experimentation group. One of the result of the high susceptibility of beer selection criteria was that participants culti- bananas to Xanthomonas wilt and the low vate banana. These farmers’ experimentation levels of plantation management, the produc- groups have frequent meetings in which dif- tivity of beer banana systems has been drasti- ferent topics are discussed, preparations for cally reduced in central Uganda. farm systems interventions are made and In the context of these developments data are collected. (population increase, rising incomes, The additional data that were collected increased availability of industrial alcoholic consisted of answers to five different ques- beverages and Xanthomonas wilt), we asked tionnaires that were developed for specific what the future is for beer banana production actors in the value chain: growers of beer and processing under current circumstances. bananas (42), brewers (48), traders in banana We used a value chain approach to answer beer/waragi (5), bar owners in rural villages this question, and looked at different actors in the project sites (20) and bar owners in the and steps in the beer banana value chain to capital of Kampala (41). Respondents (except assess product flows, incomes derived, chain for the Kampala bar owners) were selected inefficiencies and opportunities. The empha- using ‘snowball’ sampling, which started sis was on rural chain actors, growers of beer from the farmers’ experimentation groups in bananas, brewers and village bar owners. The the three project sites, whose respondents paper examines: (i) how the beer banana identified other respondents, and so on. value chain is constructed; (ii) the importance Traders proved to be hard to reach, as they of the beer banana for the actors involved; are often on the move and the quantities in and (iii) the main constraints encountered by which they trade also differed greatly; so the actors involved and the opportunities that those that trade on a very small scale within exist for them in the beer banana value chain. their own locality were excluded, as they actually overlap to a large degree with what we call a rural bar owner. Bar owners are 23.2 Methodology defined as those people selling alcoholic beverages from a place where customers can The study was conducted within the frame- sit down and drink – this might be their own work of an Austria Development Agency- home or a bar. In Kampala, seven specific funded project, ‘Growing Bananas with Trees areas were targeted and enumerators visited and Livestock’ that was investigating the all bars in this area; the areas were slums The Beer Banana Value Chain in Central Uganda 193

or otherwise residential areas for lower 23.3 Results income citizens (Mulago, Naguru go-down, Kasenga, Ntinda, Makarere kavule, Katanga, 23.3.1 The products Kamwokya). Interviews were only conducted when the bars were actually selling artisanal Broadly, three beer banana products exist: banana beer and/or waragi. juice, beer and the distillate waragi. Juice and The findings were complemented with a beer are traditional products with zero and low literature review, and the beer and waragi alcohol concentrations, respectively, and both processing procedures were documented fol- products have a short shelf life. Waragi has lowing observation of several brewers busy been produced since the Ugandan people in the act of brewing (see Box 23.1). first encountered distillates at the end of the

Box 23.1. Description of the production process for juice, beer and waragi.

Juice and beer 1. Harvesting. Bunches are harvested when still green. 2. Ripening. One method is to bury bananas in a pit and cover with plastic to stimulate ripening. Another method is to wrap bananas in leaves and place them on a rack over the kitchen fire (Davies, 1993). The bananas need to be evenly ripened until they are ‘soft, yellow and sugary’ (Gensi et al., 1994), which takes from 4 to 8 days (Kyamuhangire et al., 1995). 3. Peeling. When ripe, some of the banana types (usually ‘Mbidde’) are peeled. 4. Juice extraction. The bananas are put in a shallow pit covered with plastic and trampled by foot. The juice thus extracted is collected and put in big wooden mortars that look like boats or ‘canoe-shaped wooden vats’, as Davies (1995) calls them. When juice is destined for consumption without further processing, hands (rather than feet) and big pans are often used for a more hygienic/clean juice. Grasses are used to help juice extraction. According to Kyamuhangire et al. (1995), grasses help to separate the juice from the cells without creating a ‘cloudy emulsion’. The juice produced is a clear liquid with a strong banana flavour and high sugar content. This juice can be consumed directly, although it is often diluted with water because of the strong, sweet taste. 5. Second extraction. This often takes place by adding water to the pulp. The juice thus extracted has a higher percentage of solids (Gensi et al., 1994; Kyambuhangire et al., 1995). 6. Mixing. The pure juice and the diluted juice are mixed according to taste preference (Kyamuhangire et al., 1995). 7. Filtering. The juice is filtered before pouring it into wooden mortars. 8. Additives. Coarsely crushed roasted red sorghum is added to the juice to add a slight bitterness to the taste. The role of the sorghum in yeast development is disputed (Davies, 1995; Kyamuhangire et al., 1995). 9. Fermentation. The mortar or vessel is covered with banana leaves or cloths. The temperature builds up inside and evokes fermentation, which takes from 1 to 6 days (Davies, 1995). 10. Packaging. After fermentation, the beer is poured into jerrycans of 20 l and is ready for consumption. Waragi The beer produced as described above can be distilled to make waragi. According to Kyamuhangire et al. (1995), seven to eight jerrycans of beer are needed to produce one 20 l jerrycan of waragi. The brewers that we encountered, however, used an alternative method also described by Kyamuhangire et al. (1995). For this method, banana pulp (no peel) is mixed with water in a large pit and left to ferment. To separate the liquid from the pulp, the pulp is put into a polypropylene bag, closed and trampled by foot until the liquid seeps out through the bag into a shallow hole in the soil that is covered with a plastic sheet. The liquid or beer is collected and distilled in an oil drum over an open fire; the vapour condenses in a copper pipe that leads from the drum through a stream of water or a water body to a jerrycan, in which it is collected. Brewers continuously taste the distillate and adjust the heat of the fire for optimal alcohol levels and taste. 194 A.M. Rietveld et al.

19th century and discovered how to distil fer- bar owners or to neighbours, family and mented beverages (Davies, 1995); it has an friends in the village. Some 25% of brewers alcohol content of above 40%. A fourth prod- also or exclusively sell to traders who either uct, wine, is a new product that has been reside in or visit the village. Only 5% of introduced in various development projects brewers sell (part of) their brew to bar own- especially in the south-western part of ers in Kampala. Of the 41 bar owners in Uganda, but this is mainly made from cook- Kampala interviewed, only three mentioned ing bananas. a district in the Central Region of Uganda Consistent with data from 1996 (Aked as the origin of their waragi. A schematic and Kyahumangire, 1996), the main beer cul- impression of the beer and waragi value tivars in the Central Region of Uganda are chains is given in Plate 18. ‘Kayinja’ and ‘Kisuubi’. ‘Kayinja’ is used by 100% of the brewers in our sample and 44% of them mix it with ‘Kisuubi’. A very few brew- 23.3.3 Beer banana producers ers also mixed small quantities of EAHB cul- and brewers tivars or ‘Mbidde’ into their beverages. Of 208 respondents to the baseline study, 66% cultivated ‘Kayinja’ bananas; percentages 23.3.2 Characterization of the beer varied considerably across the different sites banana value chain (Table 23.1), as did the number of mats per farm, with numbers in Sembabule usually The value chain for beer banana in central lower. Although many beer banana growers Uganda is generally very local and short, process small amounts of beer banana into juice comprising four main kinds of actors. These for home consumption, not all are also brewers are: (i) the farmers that produce beer of beer and waragi. The number of brewers was bananas on their land; (ii) the brewers that not captured in the baseline study but, based process the beer banana into alcoholic bev- on the literature (Aked and Kyahumangire, erages; (iii) the bar owners or traders that 1996) and our own observations, we estimate buy from brewers and sell banana-based the percentage of brewers to be 5–30% of the beverages to customers; and (iv) the con- total farming population, depending on sumers of banana beer and waragi. Most of region and the local prevailing religion. the banana beer and waragi produced in Brewers are men as well as women of central Uganda is consumed in the village of all ages. In our sample of brewers, there were production or in a nearby village. Of the slightly more men than women (23 versus 19) brewers interviewed, 86% sell all or part of and ages ranged from 19 to 87 years, with an their brew, either in 20 l jerrycans to local average of 46 years for men (SD = 16.5) and

Table 23.1. Source of ‘Kayinja’ bananas and brewing and income data for three districts in Central Region of Uganda.

Nakaseke Kiboga Sembabule Mean

Proportion of farmers cultivating ‘Kayinja’ (%) 45 81 65 64 Proportion of brewers buying ‘Kayinja’ (%) 71 31 94 65 Average income per month from beer banana sales (US$)a 6.80 3.00 7.10 5.60 Average income per month for brewers of beer (US$) –b – 31.70 – Average income per month for brewers of waragi (US$) 46.90 74.20 57.00 59.40 Brewers using only family labour for brewing (%) 57 42 16 38 Brewers using exclusively hired labour for brewing (%) 0 6 25 10 Share of income derived from brewing (%) 42 58 49 50 aConversion from Ugandan Shillings (UGX) at 2011 exchange rate of 1 US$ to 2500 UGX. bNo data available. The Beer Banana Value Chain in Central Uganda 195

42 years for women (SD = 17.2). The quanti- who do not brew often sell their bunches, but ties brewed were similar for men and women, they also use the beer banana leaves for the and there was no correlation between age of preparation of matooke or sell them and brewer and the quantities brewed. The length make banana juice for home consumption. of time that the respondent had been brewing Data from 57 farmer group meetings suggest (experience) varied from 2 to 50 years and was that 65% of households make banana juice. positively correlated with the amounts When asked about drinking habits, half of the brewed (significant at P = 5%). For non- group participants said they drink banana brewing beer banana growers, the number of juice regularly. men in the sample was much higher (33 Box 23.2 provides a brief description of a versus nine women) than for brewers. This beer banana producer and brewer from can be explained by the fact that in this survey Kiboga District. the head of household was interviewed, and this is normally a man, whereas for the brewer Income and prices survey the household member in charge of brewing was interviewed, and this was a Bunches of beer banana types are small and woman in approximately half the cases. are sold heaped together, which means that The non-brewing respondents were three to five bunches account for one sellable slightly older than the brewers, with an load. Prices for these heaped bunches range average age of 50.5 years (SD = 17.4). This can between US$0.40 and US$1.60. Beer banana also be explained by the respondent being the growers earn US$6.00/month on average household head and therefore normally one from beer banana sales. The incomes that of the eldest members of the household and brewers earn from the sale of banana beer older than their spouses. and waragi are much higher, especially for Most farmers in the three sites are small- waragi brewers (Table 23.1). However, labour holders, with the total land size averaging investment is high (Box 23.1), and the majority 1.5 ha for brewers and 1.9 ha for non-brewing of brewers hire labourers to execute part or all of beer banana growers. The area allocated to the activities involved in processing (Table 23.1). bananas (all types) was 0.8 and 0.6 ha, respec- Labour costs were estimated at US$0.80/20 l tively, for brewers and non-brewers, indicat- jerrycan of waragi. Sale prices for 20 l ing that brewers allocate larger shares of their jerrycans of waragi are between US$12 and land (both in absolute and relative amounts) US$40. The price varies among the different to banana cultivation. Brewers usually grow sites, but also depends to some extent on beer bananas themselves, but a considerable quality. If the spirit has been double distilled number buy additional beer banana bunches (rather than only once distilled), the double from other producers to increase the raw distillate has a higher alcohol percentage and material they process (Table 23.1). Some 14% is usually sold for at least US$24 per jerrycan. of brewers (the same for different districts) do If the spirit is pure banana based, the price is not grow any beer bananas themselves but higher than if sugarcane has been mixed into instead buy them all. Beer banana growers it. For banana beer, prices are from US$2.00 to

Box 23.2. A beer banana producer and brewer from Kiboga District.

We meet Livingstone while he is trampling on a sack, the 50 kg kind normally used to store maize or onions. Light brown liquid is seeping out on to a plastic sheet. He is sweating and doesn’t stop moving as we talk to him. Livingstone is making waragi from beer bananas. He used to use only beer bananas from his own plantation but since his productivity went down he buys the majority from other farmers and mixes in molasses sugar. To compensate for the extra costs incurred he has increased his production of 20 l jerrycans of waragi from 25 to 40 jerrycans a month. He sells the waragi from his own depot in a nearby trading centre – Lwamata in Kiboga District. His waragi turnover is around US$960/month. 196 A.M. Rietveld et al.

US$4.00 per 20 l jerrycan. The main quality Sales consideration for banana beer is the extent to which the banana juice has been diluted with The majority of bars only sell one or two water before fermentation. ‘Purer’ beer is different alcoholic beverages, usually war- regarded as having a higher quality. agi with either bottled beer or banana beer. For many brewers, brewing is their main Only 10% of the bars sell a wide range of economic activity, accounting for an average different drinks, such as waragi (industrial share of 50% of total household income, but and artisanal), different brands of bottled going up to 100% in individual cases. beer, banana beer and other non-banana- based local brews and industrial liquors. Waragi is sold by 80% of the bars, while 25% 23.3.4 Sales and trade of banana beer sell banana beer and 73% sell bottled beer. and waragi The amounts sold per bar are generally low. Sales of waragi, for example, vary from 2 l to 30 l a week and average 14 l a week. With an Rural bars average profit margin of US$0.50/l waragi, Many bars are present in the different vil- incomes derived from waragi sales are lages of the study sites. Some of these bars modest. Margins for other drinks are are situated in people’s houses or shops, but similar. Still, bar incomes account for 46% most are separate buildings made from of total incomes on average, indicating bricks with iron sheets, or from mud with that for most people involved this is their thatched roofs. Two thirds of the bar owners core business. interviewed were women, and ages ranged from 21 to 76 years, averaging 39 years, of Kampala bars which 80% were aged 26–41 years, all of them mothers. Although not directly asked in The people that we interviewed in Kampala the survey, some of these women indicated bars were in general selling higher volumes that running the bar was easy to combine of waragi or banana beer per time period with raising young children. The bar was than their counterparts in the rural areas. often run from or near the homestead, allow- Those who we interviewed in these bars ing for the necessary cooking and execution were mostly not the owner but the man- of other household chores. One respondent ager. We only interviewed in bars where considered stopping running the bar soon as they sold either artisanal waragi or banana her children were now older, thus allowing beer. As these products are not sold in the her to return to farming again. The ages of the more expensive, upper class bars, our sur- men running bars contrasted strongly with vey was limited to small cheap bars in the those of the women, as the men were either city. The person in charge at these bars was under 26 years old or over 70 years old. on average 32 years old – much younger Box 23.3 gives a brief description of a than in the rural sites, and 60% were rural bar. women. The quantities sold were higher

Box 23.3. A village bar in Kiboga District.

It is early afternoon on Tuesday, when we stop by a row of small one-room buildings in a village in the sub-county of Lwamata in Kiboga District. One of the few buildings has some sort of veranda, open but roofed and with several benches and two low tables. At least five men are seated, talking or just sitting quietly. Some drink from a big glass of banana beer, others have small glasses of waragi in front of them. Outside, some young adults are playing cards; they pass a small glass bottle around. The only woman to be seen is peeling matooke in the bar and serving the men. Her husband is the owner of the bar, although both the building and their home next door are rented; their baby is playing on the floor. The Beer Banana Value Chain in Central Uganda 197

than in the rural bars, with averages per 23.3.5 Consumers week of 22 l for artisanal waragi and 458 bottles of beer (the equivalents in rural Although a consumer survey was not sites being 14 l and 50 bottles, respectively). included in our study, bar owners in rural In the Kampala bars, we distinguished areas and in Kampala provided observations between artisanal and industrial waragi on their customers and customer preferences because a considerable share of the waragi (Table 23.2). Artisanal alcoholic beverages consumed is produced by large factories, such as home-brewed waragi and banana such as East African Breweries, or by beer are more popular in rural sites than in smaller enterprises that either brew from Kampala. In all sites, waragi is more popular raw materials or re-distil and package than banana beer and bottled beer. Of the bar banana beer and/or waragi, which they owners in rural areas, 80% said waragi is the buy from farmers. most popular drink for men; only 15% said All of the 41 owners/managers of the that it is bottled beer and 5% mentioned bars we interviewed in Kampala sold war- banana beer. According to 47% of rural bar agi, while only three sold banana beer as owners and 82% of Kampala bar owners, well. The waragi was purchased mainly in women prefer bottled beer. Young people the city itself, with 13 people buying at local under 25 years old in Kampala tend to prefer urban markets and 19 getting the waragi industrial waragi over artisanal waragi and delivered to the bar. Nine bar owners pur- bottled beer. The only age group that seemed chased waragi directly in a village. When to prefer banana beer, though this was still asked where their waragi was originally only mentioned by 16% of bar owners, were produced, half of the respondents named a people over 61 years old in rural sites. district in the Western Region (Kabarole, Bar owners, in rural sites and Kampala Rukingiri and Kasese districts were all equally, talked of a tendency of their custom- mentioned five times, and Hoima once). ers to switch from banana beer and waragi to Only two respondents mentioned a district bottled beer as their incomes improved. Rural in the Central Region as the place of pro- bar owners in particular often mentioned that duction of their waragi (Kiboga and waragi is popular because it is the cheapest Sembabule). way of getting drunk. Very few bars in Kampala sold banana beer. When asked why, respondents mentioned the scarcity of the product (66% of 23.3.6 Main constraints and respondents) – apparently it is difficult to opportunities in the value chain purchase banana beer. Other reasons mentioned were the low market demand and Different actors in the chain encounter differ- profitability (22% of respondents) and the ent constraints and see different opportunities. short shelf life of the product (22%). The main constraint mentioned by most actors

Table 23.2. Consumer preferences for alcoholic beverages as stated by rural (R) and Kampala (U) bar owners. Figures are the percentage of bar owners identifying each drink as the most popular.

Men Women <25 years 20–60 years >61 years

Beverage R U R U R U R U R U

Artisanal waragi 80 49 47 8 67 25 72 47 67 87 Industrial waragi –a 14 – 0 – 48 – 12 – 0 Banana beer 5 0 0 8 8 2 0 0 16 6 Bottled beer 15 37 47 82 25 25 22 39 16 6 Other brews 0 0 6 2 0 0 6 2 0 0 aNo information on industrial waragi in rural areas. 198 A.M. Rietveld et al.

(especially beer banana growers and brewers) Based on farmers’ estimations, and com- was the bacterial banana disease Xanthomonas paring current yields with those before wilt and the associated unavailability of beer Xanthomonas wilt arrived, we calculated bananas. Other constraints mentioned by beer decreases in productivity of beer banana banana growers and brewers were problems plantations for both Kiboga and Nakaseke with the transport of bunches, availability and districts of an average of 65%. As a result of price of molasses sugar and labour. Bar own- this large decrease in productivity, the avail- ers mentioned lack of capital for investments ability of beer bananas has fallen drastically. in the bar, low margins and variable revenues Most brewers, certainly those in Kiboga and that are dependent on the changing incomes of Nakaseke, are consequently processing customers through the year. Also, the quality smaller amounts of beer bananas than they of waragi and banana beer and the level of did previously. Some of the beer banana dilution were mentioned. farmers we interviewed had stopped brewing altogether because of yield declines or The system under pressure complete losses. Brewers were either trying to maintain production in various ways or had Xanthomonas wilt is now devastating banana decreased their production (Table 23.3). plantations in the whole region (Jogo et al., Strategies for maintaining the quantities pro- 2011). Due to specific characteristics of the cessed were to purchase larger quantities of inflorescence of the beer banana (ABB beer bananas from outside the farm, to stop genome), these bananas are especially sus- beer production and concentrate on waragi ceptible to infection through insect vector production (or vice versa) or, in the case of transmission (Tushemereirwe et al., 2003). waragi, to increase quantity by adding and The plantations of all respondents, both for mixing in molasses sugar. Farmers have also beer banana growers and brewers, in the switched to other crops, such as coffee or Nakaseke and Kiboga district sites were maize, to compensate for income losses due infected with Xanthomonas wilt. to Xanthomonas wilt. Similar strategies were As there are no banana cultivars that observed by Karamura (2006). are resistant to Xanthomonas wilt, the only way to control the disease is to apply a pack- Opportunities age of cultural practices. These practices, however, ask for considerable investment in Banana beer and waragi alike are sold in jer- time and money, both of which farmers rycans by brewers and in recycled bottles and were not previously used to investing in jerrycans by bar owners and traders. their beer banana systems. Although brew- Packaging of the produce would increase ers were applying control measures more costs but would also provide the opportunity often than non-brewers, few farmers have to differentiate more clearly between differ- implemented a set of cultural practices that ent qualities (e.g. level of dilution, ingredi- are necessary to avoid reinfection and ents) and hence to diversify the market. improve yields. Especially for waragi, the market demand is

Table 23.3. Production and income from brewing before and after Xanthomonas wilt outbreak.

Current Average Average Current Average production current production before average income before ranges production Xanthomonas income Xanthomonas wilt Product (l/month) (l/month) wilt (l/month) (US$/month)a (US$/month)a,b

Waragi 7–140 46 88 60.10 118.30 Banana beer 100–960 232 340 31.80 44.00 aConversion from Ugandan Shillings (UGX) at 2011 exchange rate of 1 US$ to 2500 UGX. bCalculation based on 2011 price information. The Beer Banana Value Chain in Central Uganda 199

large, in rural as well as urban areas. activity in which several household members Collective marketing and increased invest- are involved because of the high labour ment are possible pathways for brewers to demand. Older brewers, in particular, depend reach those markets. on young household members for the labori- If growers of beer bananas want to keep ous parts of the production process. Many their plantation free of Xanthomonas wilt brewers also hire in labour to assist in the they will have to invest more time in planta- brewing process. With ongoing urban migra- tion management. Reducing competition for tion, especially of young people, labour avail- water and nutrients through better weeding ability could decrease even more. Conversely, and control measures such as disbudding the brewing industry could also provide could have a favourable effect on the bunch employment for young people and help to size of beer bananas and thereby increase sustain rural livelihoods. returns. The brewing system is very simple/ primitive in most cases, with little attention paid to hygiene and quality control. Only basic equipment is used and no investments 23.4 Discussion in labour-saving machinery are made. Investments in brewing are discouraged 23.4.1 Growers and brewers because distillation is still officially illegal, though this is hardly enforced. Also, few Growers of beer bananas and brewers (who brewers would be able to make such mone- are also usually growers) have different incen- tary investments. Some waragi brewers share tives for the production of beer bananas. For distillation equipment, but no joint process- brewers, production on farm instead of buying groups or cooperation were found. ing the bananas implies lower production Cooperative processing could facilitate finan- costs and thus higher profit margins on cial investments in equipment and even banana-based beverages. As prices for beer transport, organization of labour and quality banana bunches are relatively low (when control. compared with matooke), incentives for non- brewers to produce beer bananas seem to come more from the usage of other beer banana products (juice, leaves) for household 23.4.2 Commercialisation of consumption than from cash income. Our artisanal beverages data show that juice production, while negligible for household income, is important for In Uganda, alcohol consumption is among household consumption. It would be interest- the highest in the world. An estimated 80% of ing to determine its contribution to nutritional this consumption consists of home-made status, especially of children, within those beers and spirits based on fermentation households that regularly consume banana (WHO, 2004). In the banana-growing areas, juice. Although juice is not often commercial- those drinks are mainly based on banana. ized, we did come across some initiatives. With a population growth rate of 3.2% Quality control and shelf life are the major (UBOS, 2002), the absolute amounts of alco- constraints on juice commercialization. hol consumed are expected to grow, implying Higher prices for beer bananas would a growing market for alcoholic beverages. probably have a positive effect on the control Especially in rural areas, home brew is much of Xanthomonas wilt and would give farmers consumed, but industrial alcoholic drinks less reason to switch from beer bananas to such as bottled beer and spirits packed in bags other crops which, in turn, would improve or bottles are also becoming more widely beer banana availability for brewers. available. The question is whether banana- In addition to the unavailability of beer based alcoholic beverages will retain their bananas, labour shortage is also a major con- dominant position in the consumer market cern for brewers. The brewing is often an when confronted with increased competition 200 A.M. Rietveld et al.

from industrial beverages. The position of because of the short shelf life. The waragi and artisanal waragi, both in rural areas and in banana beer that is sold in bars in Kampala Kampala, seems to be strong. In contrast, mainly comes from other regions. Waragi is banana beer seems to be a product in decline, much more popular than banana beer among and very little banana beer is sold, especially consumers, mainly because it allows you to in Kampala. Decreased availability and short get drunk faster, for a lower cost, but bottled shelf life are probably important factors, but beer is gaining in popularity, especially taste and image certainly also play a role. among those that have more money to spend. Banana beer is associated with traditional This situation is the same both for the rural cultural celebrations and in general is seen as study sites and for Kampala, though in a ‘village’ product. City dwellers, in particu- Kampala bottled beer consumption has far lar, seem to give preference to the different exceeded that of waragi and banana beer. kinds of bottled beer brands that are This change in consumer preference could available. have an impact on demand and thus on price. The profile of rural bar owners – mothers However, taking the rapidly growing popu- with young children, young adult men and lation into account, and the resulting con- older people – indicates that running a bar is tinuous growth in the demand for alcohol, especially an option to gain income for those a significant decrease in demand for artisanal who cannot farm for various reasons, such as beverages is not expected in the short to raising small children, household chores, medium term. advanced age or not having access to land. A more serious threat to the production of artisanal beverages and the incomes derived from them is probably the rapidly decreasing availability of the beer banana. 23.5 Conclusion Xanthomonas wilt has severely reduced the productivity of banana plantations in the The production and processing of beer whole banana-growing region of Uganda, bananas is an important economic activity and in beer banana plantations especially, for many people in the rural areas of central farmers often do not make the effort to control Uganda. Brewers brew, not because it is easy Xanthomonas wilt. A significant difference in money – it is a time-consuming and labour- the level of application of control measures intensive process – but because it is one of the exists between brewers and non-brewers, few options available to them for obtaining indicating that brewers are more motivated relatively large amounts of cash throughout than non-brewers to invest in disease control. the year from their crop production. Bars in This is probably because the beer bananas rural sites are often very small scale, but they represent a larger value to them, and is in allow their owners to earn a living from accordance with the findings of Jogo et al. home, to which many of them are bound (2011), who state that the application of con- because of age, domestic chores or the pres- trol measures is higher in EAHB systems than ence of small children. Although sales of for ‘Kayinja’ because EAHB systems make home-processed beer banana beverages a higher contribution to farmers’ livelihoods. account for significant parts of household The results from our study seem to indicate total income in the Central Region, brewing is that this statement applies only to those often not professional and sales are usually farmers that do not brew. very local, implying that profits are not To increase returns from the sales of beer optimized. bananas and derived products, investment The value chain for waragi and banana in the value chain is essential. Collective beer is short, as most of the production is con- production and marketing could be ways sumed in the locality. That is especially true for brewers and producers of beer banana for banana beer, which is more costly to trans- to increase their incomes and allow them to port because of the lower price per volume make the necessary investments to reach and is less popular among bar owners urban and more diversified markets. The Beer Banana Value Chain in Central Uganda 201

References

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B.N. Ekesa,1* J. Kimiywe,2 M. Davey,3 C. Dhuique-Mayer,4 I. Van Den Bergh5 and G. Blomme1 1Bioversity International, Kampala, Uganda; 2Kenyatta University (KU), Nairobi, Kenya; 3Katholieke Universiteit Leuven (KUL), Belgium; 4La Recherche Agronomique pour le Développement/Agricultural Research for Development (CIRAD), Montpellier, France; 5Bioversity International, Montpellier, France

Abstract Bananas and plantains serve as important food crops in much of Africa. In the Democratic Republic of Congo (DR Congo), production of bananas is concentrated in the eastern region and ranges between 75,000 and 80,000 t/year. Bananas rank second in importance after cassava in eastern DR Congo and are good sources of carbohydrates, though recent research has confirmed that they also have substantial levels of provitamin A carotenoids. This study was undertaken to establish the contribution of bananas and plantains to the diet and nutrition of Musa-dependent households within eastern DR Congo. The study sites included Beni Territory (North Kivu) and Bukavu Territory (South Kivu). The localities, villages and specific households were established through multistage sampling. Sample size was calculated using Fisher’s formula, and mothers/caregivers from 371 households with preschool children were interviewed using a structured questionnaire. Regression analysis with an r2 threshold of 0.045 was carried out to establish the relationship between dietary diversity and banana consumption. Findings showed that the food group consisting of roots, tubers and bananas was the most popular in both Beni and Bukavu territories, with more than 90% of the households having consumed a food item from this group. Although cassava root is the most popular starchy staple, bananas, especially East African Highland bananas (EAHB), had been consumed by more than 60% of the households in the 24 h preceding the survey. In addition, >50% of households indicated that they had consumed these bananas twice to four times a week and that they were mostly simply boiled. Bananas have a significant role in the diets of preschool children and potentially meet their energy needs and needs for nutrients such as potassium and vitamin A. It is therefore important that interventions or research activities geared towards alleviation of hunger and malnutrition should use bananas and plantains as a vehicle for addressing these problems, especially among Musa-dependent populations.

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 202 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Bananas, Plantains and Diet and Nutrition 203

24.1 Introduction Mabuku, Kisungu and Rwakhwa were randomly sampled; in Bukavu Territory, the In the Democratic Republic of Congo randomly sampled localities were Kajeje, (DR Congo) bananas and plantains (Musa spp.) Murhesa and Miti. A listing of all households are presumed to play a major role in meet- with preschool children in each locality was ing the dietary needs of the people. Bananas compiled and systematic random sampling and plantains are prepared and consumed was used to select the specific households to in various forms and there is usually an be interviewed. Sample size was calculated affordable banana dish for every income using Fisher’s formula: category (Fungo, 2007). The high produc- n = [t2 p(1 – p)]/m2 (24.1) tion and consumption of bananas and plantains indicates high reliance on this staple where n = required sample size, t = confi- crop, which leads to diets that are monoto- dence level at 95% (standard value of 1.96), nous, and often include few or no animal p = estimated proportion of households products with few other fresh fruits or veg- with preschool children in total households etables (Ruel, 2002). This diet tends to be and m = margin of error at 5% (standard value low in a number of micronutrients, and the of 0.05) (Magnani, 1997). This gave a required micronutrients that they do contain are sample size of 163 households with preschool often in a form that is not easily bioavaila- children from Beni Territory and 208 house- ble, thus resulting in malnutrition (Ruel, holds with preschool children from Bukavu 2002). The effects of malnutrition on human Territory. performance, health and survival have Structured questionnaires were used been the subject of extensive research for to collect data and respondents included several decades; studies have shown that caregivers of the children or any other per- malnutrition affects physical growth, mor- son responsible for food provision and bidity, mortality, cognitive development, preparation at household level. Data on reproduction and physical work capacity. consu mption patterns and dietary diversity Whereas other developing countries are of bananas and plantains and other food experiencing a downward trend in levels items were collected following FAO guide- of malnutrition and food insecurity, these lines (FAO, 2007), and the tools used problems are still the main factors associ- included 24 h recalls to assess preschool ated with the high child morbidity and child and household dietary diversity scores mortality rates in DR Congo (UNICEF, and a food frequency questionnaire over 2008). The objective of this study was to 7 days to establish the frequency of con- assess the contribution of Musa fruits to the sumption of food items across food groups. diets of smallholder Musa-dependent Data were analysed using the software households from Beni Territory (North package SPSS Statistics Version 17. The quanti- Kivu) and Bukavu Territory (South Kivu) in tative data were organized, described and DR Congo. summarized using frequency tables, charts and graphs. Dietary diversity data were further analysed and interpreted in accordance with the guidelines set by FAO, in 24.2 Methodology which the consumption of food items from six or more food groups is considered high There are 26 provinces in DR Congo. Based dietary diversity, consumption from three on secondary data on banana production to five food groups is medium dietary diver- and food insecurity (WFP, 2008), the prov- sity, and consumption from less than three inces of North and South Kivu, both in eastern food groups is low dietary diversity (FAO, DR Congo, were selected. Multistage sam- 2007). Regression analysis with an r2 thresh- pling was used to select the territories of old of 0.045 was carried out to establish the Beni in North Kivu and Bukavu in South relationship between dietary diversity and Kivu. In Beni Territory, the localities of banana consumption. 204 B.N. Ekesa et al.

24.3 Results and Discussion employment. The mean monthly household income was US$20–50/month, but over 80% 24.3.1 Socio-economic aspects of the households had a monthly average income of less than US$30. Of the 371 respondents, from Bukavu and Beni territories, 92% were women, and 83% were monogamously married, with most of 24.3.2 Dietary practices them aged 25–34 years. The majority of households (61%) consisted of five to eight Dietary diversity and consumption of banana members, with an average household size of in relation to other staples is discussed under 6.4 in Beni and 7.1 in Bukavu. The mean num- three headings: consumption patterns across ber of children below 5 years old per house- food groups; household dietary diversity hold was two, although there were 17% of scores; and consumption patterns of bananas, households with three children below 5 years plantains and other starchy staples old in Bukavu and 12% households with three children below 5 years old in Beni. Consumption patterns across food groups Many of the women interviewed (39%) had lost at least one child below the age of 5 years. With reference to the FAO guidelines for Almost half of the respondents (45%) measuring household dietary diversity (FAO, had not received any form of education, 32% 2007), 14 food groups were taken into consider- had received incomplete primary education, ation (Table 24.1); these excluded the sweets 11% had completed primary education and group and the spices, condiments and bever- only 0.5% had gone to a vocational college. ages group that are included by FAO. The group None had any college or university diploma/ consisting of white roots, tubers and bananas degree. Most of the interviewed households reported the highest consumption rate – >95% (76%) depended on agricultural production in both Beni and Bukavu territories (Table 24.1). for food and income, 14% were involved in After white roots, tubers and bananas, casual labour while 5.3% were involved in the second most popular food group was small-scale business and 4.3% in formal dark green leafy vegetables (Table 24.1).

Table 24.1. Consumption patterns across food groups of households in eastern Democratic Republic of Congo. Data are the proportion of households that consumed the relevant food group in the 24 h period before the survey – HH (%) and the standard deviation (SD).

Beni, North Kivu (n = 163)a Bukavu, South Kivu (n = 208)

Food group HH (%) SD HH (%) SD

Cereals and grains 17.5 0.4 24.0 0.4 Eggs 0.0 0.0 0.0 0.0 Fats and oils 74.3 0.4 96.2 0.0 Fish 22.4 0.4 53.8 0.5 Fruits, other 8.6 0.3 3.8 0.2 Fruits rich in vitamin A 3.3 0.2 1.0 0.1 Legumes and pulses 52.0 0.5 54.8 0.5 Meats, flesh 10.5 0.3 3.4 0.2 Meats, organs 0.7 0.1 0.0 0.0 Milk and milk products 0.0 0.0 0.0 0.0 Vegetables, dark green leafy 79.1 0.4 49.0 0.5 Vegetables, other 10.5 0.3 16.3 0.4 Vegetables rich in vitamin A 9.3 0.3 1.4 0.1 White roots/tubers/bananas 96.8 0.2 97.1 0.2 an, number of households surveyed. Bananas, Plantains and Diet and Nutrition 205

The communities could access a wide range into another and all of the meats together; of such vegetables, which include amaranth this was to derive the household dietary leaves, bean leaves, pumpkin leaves, cassava diversity score (HDDS) according to FAO leaves and spinach, but in both South and (2007); as in the consumption patterns analysis North Kivu the most popular dark green above, these ten groups excluded the sweets leafy vegetable was cassava leaves, which group and the spices/condiments/beverages were consumed by 18% of households in group that are included by FAO. Findings South Kivu and 59% in North Kivu. This from the HDDS analysis showed that more popular green leafy vegetable is a major rel- than 50% of the households had consumed ish known locally as ‘sombe’, and usually less than three of the food groups in the 24 h accompanies a hard paste made from cas- preceding the survey (Fig. 24.1). The fraction sava flour known locally as ‘ugali’. Despite of households consuming highly diversified the high consumption of vegetables and diets (more than six food groups) was less especially of cassava leaves, it is likely that than 10% in the two territories. Although the nutrients in the vegetables are lost as a Bukavu Territory had a slightly higher result of the cooking methods employed. proportion of households consuming diets low The leaves are boiled for prolonged periods, in diversity, the difference in HDDS between the water drained and the leaves then Beni and Bukavu was not statistically significant pounded in a mortar. The main aim of this is (P = 0.32). A similar observation was made to break down and get rid of the cyanide in when Ekesa et al. (2011) assessed the diversity the cassava leaves (J. Ntamwira, Bukavu, of diets consumed by households in Butembo South Kivu, DR Congo, 2009, personal Territory (North Kivu, eastern DR Congo); communication). this study found that the diet of the whole The food group consisting of vitamin A household was not different from the diet of rich vegetables was reported as having a very low consumption rate, and there was virtually no consumption of preformed vita- 60 min A (as eggs, milk and milk products, and organ meats) in either territory within the 24 h 50 preceding the survey. Despite this, the consumption of oils and fats was relatively high: 40 a total of 96% of households in Bukavu and 74% in Beni territories had consumed food 30 cooked with local red palm oil in the last 24 h (Table 24.1). Palm oil is readily available in 20 the region (Carrere, 2010), and in 2005, total palm oil production in DR Congo was 10 estimated at 225,000 t, of which only 25,000 t Proportion of households (%) came from the agribusiness sector, with the 0 bulk (200,000 t) from the village plantation Low Medium High sector. Of this, approximately one quarter Diet diversity represented commercial oil sold on the Beni Territory Bukavu Territory consumer market, while the rest went to self- consumption by the producers and their Fig. 24.1. Diversity of diets consumed by families (in the broad sense of the term) households from Bukavu Territory, South Kivu (Carrere, 2010). and Beni Territory, North Kivu, eastern Democratic Republic of Congo. Low diversity diets include less than three food groups, medium diversity diets Household dietary diversity score (HDDS) include four to five food groups and high diversity diets include six or more food groups out of The 14 food groups already considered were 12 food groups defined by FAO (2007) for the further reduced to ten by putting all of the determination of the household dietary diversity vegetables into one group, all of the fruits score (HDDS) as described in the text. 206 B.N. Ekesa et al.

preschool children within the same The observed high consumption of households. Therefore, although moving EAHBs supports results by Jagwe et al. (2009), from a narrow diet to one containing a more who reported EAHB consumption rates of diverse range of foods has been shown to almost 80% in South Kivu, indicating that increase intake of energy as well as micro- EAHBs form a major part of the diets of nutrients in developing countries (Kennedy households in this region. Jagwe et al. (2009) et al., 2007), following the findings of this also reported that the consumption of plan- study, the diets of most households in east- tain bananas was about 36% in South Kivu ern DR Congo, specifically those of pre- and that plantains have traditionally been a school children, are still largely starch starchy staple food of rural populations in the based and have limited diversity. This puts humid lowlands of DR Congo. The low level them at a higher risk of malnutrition and of plantain consumption observed in this especially at a higher risk of micronutrient study in North Kivu (5% in Bukavu and 10% deficiencies. in Beni) could be explained by the fact that plantains now have high market value and Consumption patterns of bananas, farmers are increasingly selling them as a plantains and other starchy staples cash crop to urban consumers. With rapid urbanization and the growing prosperity of Of all the staples considered in this study, the city dwellers, the demand for plantain is out- East African Highland banana (EAHB), stripping supply, so that rural households are a cooking banana, was the second most con- left to depend on either cooking varieties of sumed starchy staple, with more than 60% of Musa or other starchy staples. The consump- the households in both Beni and Bukavu ter- tion of dessert bananas was even lower, with ritories reporting consumption (Table 24.2 none being consumed in Bukavu and a very and Fig. 24.2). Cassava root was the most low rate of 2% consumed in Beni (Fig. 24.2). popular starchy staple. This finding is sup- Dessert bananas are mostly consumed as ported by the fact that 74% of the population snacks and their production is also very low in the region is involved in cassava produc- in eastern DR Congo. tion, and the region (eastern DR Congo) has Bananas are consumed in various forms, the highest annual cassava consumption in mostly boiled, roasted, as dessert, or as beer or the world, with an estimated 390 kg fresh juice. This study showed that in both Beni and root (1100 cal)/person daily. Bukavu territories, bananas are mostly boiled

Table 24.2. Consumption of cooking bananas, plantains and other starchy staples available to communities in eastern Democratic Republic of Congo. Data are frequency of the households reporting consumption with standard errors of the means (± SE mean).

Bukavu, South Kivu (n = 208)a Beni, North Kivu (n =163)

Starchy staples Frequency (%) ± SE mean Frequency (%) ± SE mean

Cassava and products 86.6 ± 0.026 99.4 ± 0.006 Cooking banana 66.5 ± 0.034 64.0 ± 0.038 Maize 17.8 ± 0.027 14.2 ± 0.028 Millet 0.5 ± 0.005 0.0 ± 0.000 Plantain 4.8 ± 0.015 10.0 ± 0.021 Potatoes, Irish 0.5 ± 0.005 0.6 ± 0.006 Potatoes, sweet 0.5 ± 0.005 0.0 ± 0.000 Rice 1.0 ± 0.007 1.8 ± 0.011 Sorghum 5.8 ± 0.016 0.6 ± 0.006 Wheat and products 0.0 ± 0.000 3.1 ± 0.014 Yam/taro 0.0 ± 0.000 1.2 ± 0.009 an, number of households surveyed. Bananas, Plantains and Diet and Nutrition 207

(Table 24.3). Although only households in The relationship between consumption of Bukavu (47%) indicated having consumed bananas, especially the cooking banana, and roasted banana, the consumption of banana dietary diversity was positive and significant beer by 6% of households was reported in (r2 = 0.54), indicating that more than 50% of both territories. The high consumption of the children/households that had consumed boiled banana and banana beer is explained diversified diets had at least consumed the by the high production area under the two cooking bananas. This was expected following most popular cultivars in the two territories: the very high rate (>60%) of banana consump- ‘Nshikazi’ in Bukavu and ‘Vulambya’ in Beni. tion reported in both territories and indicates The data in Table 24.3 show that the main that bananas and plantains form a major part form of utilization of ‘Nshikazi’ is either of the diets of both preschool children and the cooking (mostly boiling) or beer production whole household. It is therefore necessary and (also reported by Dowiya et al., 2009), while the main form of utilization of ‘Vulambya’ is 70 cooking (boiling). Other products with significant con- 60 sumption in Bukavu were banana juice (13% 50 of households) and porridge (4%); in Beni, 40 only 1% of households consumed these two 30 products. The beer banana cultivars were the AAA EAHB ‘Nshikazi’ cultivar in Bukavu 20 (as already noted) and the AB ‘Kisubi’ cultivar 10 Proportion of households (%) in Beni; these were kept until ripening stage 6 0 (all yellow) before use (Table 24.3). A large Cooking Plantain banana Dessert banana banana proportion of the household members (>55%) Musa genotypes from both territories had consumed Musa Bukavu Beni (banana and plantain) fruit and products two to four times in the 7 days before the inter- Fig. 24.2. Consumption of cooking, plantain and view, and there were some households that dessert bananas among households in Bukavu, had consumed Musa fruit every day of the last South Kivu (208) and Beni, North Kivu (163), 7 days preceding the survey (Fig. 24.3). eastern Democratic Republic of Congo.

Table 24.3. Consumption of local banana products among households in Bukavu, South Kivu (208), and Beni, North Kivu (163) in eastern Democratic Republic of Congo. Ripening stages: 1–3, unripe; 5–6, ripe.

Consumption frequency Genomic Ripening Banana product (%) ± SE mean Cultivars commonly used group stage at use

Bukavu, South Kivu Beer/wine 6.0 ± 0.00 ‘Nshikazi’ AAA 6 Boiled 75.0 ± 0.03 ‘Nshikazi’, ‘Barhebesha’ AAA 1–3 Chips/crisps 0.0 ± 0.00 ‘Musheba’ AAB 5 Juice 13.0 ± 0.00 ‘Nshikazi’ AAA 6 Porridge 4.0 ± 0.01 ‘Musheba’ AAB 5 Roasted 47.0 ± 0.04 ‘Nshikazi’, ‘Barhebesha’ AAA 1–3 Steamed 1.2 ± 0.00 ‘Nshikazi’, ‘Barhebesha’ AAA 1–3 Beni, North Kivu Beer/wine 6.0 ± 0.02 ‘Kisubi’ AB 6 Boiled 69.0 ± 0.04 ‘Vulambya’ AAA 1–3 Chips/crisps 0.0 ± 0.00 ‘Musilongo’ AAB 5 Juice 1.0 ± 0.01 ‘Banane’ 6 Porridge 1.0 ± 0.01 ‘Musilongo’ AAB 5 Roasted 0.0 ± 0.00 – – – Steamed 0.0 ± 0.00 – – – 208 B.N. Ekesa et al.

70 diets of preschool children from Musa- 60 dependent households in the eastern Democratic Republic of Congo. 50 Hence, bananas have a significant role 40 in the diets of preschool children and poten- 30 tially meet their needs for energy and nutrients such as potassium and vitamin A. 20 It is then important that interventions or 10 research activities geared towards the alleviation of hunger and malnutrition should Proportion of households (%) Proportion of households 0 Once 2 to 4 times Daily use bananas and plantains as a vehicle for Frequency of consumption in a week addressing these problems. Best bet prac- Bukavu Beni tices for processing, cooking methods and dietary combinations should be established Fig. 24.3. Consumption frequency of bananas and and promoted to ensure that the nutrients banana products among households in Bukavu, contained in the banana fruits are retained South Kivu (208) and Beni, North Kivu (163), and available for use by the body. As the eastern Democratic Republic of Congo. consumption of bananas is already a cultur- ally acceptable practice, cultivars from important for future research and interven- other regions proven to be superior in nutri- tions that are targeting food and nutrient secu- tion could be tested and incorporated into rity to use banana consumption as a vehicle in existing banana systems to enhance dietary the alleviation of both macronutrient and diversity. micronutrient deficiencies. Acknowledgements 24.4 Conclusion The authors acknowledge the Consortium The most popular food group in both Beni for Improving Agriculture-based Live- and Bukavu territories is the group of roots, lihoods in Central Africa (CIALCA) and tubers and bananas, which have a household HarvestPlus through Bioversity International consumption rate of well over 90%. Although for providing the necessary funding to cassava root is the most popular starchy carry out this research. Sincere gratitude staple, bananas – especially the East African and appreciation goes to the team of persons Highland banana (EAHB) – come second who facilitated the data collection from the with a household consumption rate of more study areas; these include Mr Charles than 60%. Over 50% of households consume Lwanga and Professor Ndung’o Vigheri of bananas two to three times a week and most Beni Territory, North Kivu; and Mr Jules of the bananas consumed are simply boiled. Ntamwira and Mr Charles Bisimwa of Therefore, bananas form a major part of the Bukavu Territory, South Kivu.

References

Carrere, R. (2010) Oil palm in the Democratic Republic of Congo (DRC). In: Carrere, R. Oil Palm in Africa: Past, Present and Future Scenarios. WRM Series on Tree Plantations No. 15, World Rainforest Movement, pp. 32–36. Dowiya, N.B., Rweyemamu, C.L. and Maerere, A.P. (2009) Banana (Musa spp. Colla) cropping systems, production constraints and cultivar preferences in eastern Democratic Republic of Congo. Journal of Animal and Plant Sciences 4, 341–356. Ekesa, B.N., Blomme, G. and Garming, H. (2011) Dietary diversity and nutritional status of pre-school children from Musa-dependent households in Gitega (Burundi) and Butembo (Democratic Republic Bananas, Plantains and Diet and Nutrition 209

of Congo). African Journal of Food, Agriculture, Nutrition and Development 11 (4). Available at: www.ajfand.net/Volume11/No4/Ekesa97251.pdf (accessed 1 May 2013). FAO (2007) Guidelines for Measuring Household and Individual Dietary Diversity, Version 3. Food and Agriculture Organization, Rome. Fungo, R. (2007) Potential Impact of Musa and Musa-based Foods on Micronutrient Deficiency in East Africa. Report prepared for HarvestPlus project of Bioversity International, Montpellier, France. Jagwe, J., Ouma, E., van Asten, P. and Abele, S. (2009) Banana Marketing in Rwanda, Burundi and South- Kivu. CIALCA Project Survey Report, Bujumbura, Burundi. Kennedy, G.L., Pedro, M.R., Seghieri, C., Nantel, G. and Brouwer, I. (2007) Dietary diversity score is a useful indicator of micronutrient intake in non-breast-feeding Filipino children. The Journal of Nutrition 137, 472–477. Magnani, R. (1997) Sampling Guide. Food and Nutrition Technical Assistance Project (FANTA), funded by Office of Health and Nutrition, Bureau for Global Programs, US Agency for International Development (USAID), with earlier funding from IMPACT Food Security and Nutrition Monitoring Project, Arlington, Virginia. Available from FANTA, Washington, DC and at: http://www.ais.up.ac.za/health/blocks/ tnm800/EssentialTNM800/DayThree/ExtraSampling/SamplingGuide.pdf (accessed 1 May 2013). Ruel, M.T. (2002) Is Diversity an Indicator of Food Security or Dietary Quality? A Review of Measurement Issues and Research Needs. FCND Discussion Paper No. 140, Food Consumption and Nutrition Division, International Food Policy Research Institute, Washington, DC. Available at: http://www.ifpri. org/sites/default/files/pubs/divs/fcnd/dp/papers/fcnbr140.pdf (accessed 1 May 2013). UNICEF (2008) Malnutrition at emergency levels in Pinga Health Zone, North Kivu, DRC; UNICEF and partners set up emergency nutritional response. UNICEF (United Nations Children’s Fund) Goma, Democratic Republic of Congo. Available at: http://www.unicef.org/media/media_43849.html (accessed 24 August 2011). WFP (2008) Executive Brief: Democratic Republic of Congo: Comprehensive Food Security and Vulnerability Analysis (CFSVA)/2007–2008. United Nations World Food Programme, Rome. Available at: http://home.wfp.org/stellent/groups/public/documents/ena/wfp188266.pdf (accessed 11 September 2011). 25 Processes and Partnerships for Effective Regional Surveillance of Banana Diseases

F. Beed,1* J. Kubiriba,2 A. Mugalula,3 H. Kolowa,4 S. Bulili,5 A. Nduwayezu,6 C. Murekezi,7 E. Sakayoya,8 P. Ndayihanzamaso,9 R. Mulenga,10 M. Abass,11 L. Mathe,11 B. Masheka,12 M. Onyango,13 E. Shitabule,14 V. Nakato,1 I. Ramathani1 and H. Bouwmeester15 1International Institute of Tropical Agriculture (IITA), Kampala, Uganda; 2National Agricultural Research Organisation (NARO), Kampala, Uganda; 3Ministry of Agriculture, Animal Industry and Fisheries (MAAIF), Kampala, Uganda; 4Ministry of Agriculture, Food Security and Cooperatives, Dar es Salaam, Tanzania; 5Maruku Agricultural Research Institute (ARI-Maruku), Bukoba, Tanzania; 6Rwanda Agriculture Development Authority, Kigali, Rwanda; ISAR, Rwanda; 7Département de la Protection des Végéteaux (DPV), Gitega, Burundi; 8Institut des Sciences Agronomique du Burundi (ISABU), Bujumbura, Burundi; 9Zambia Agricultural Research Institute (ZARI), Lusaka, Zambia; 10Ministry of Agriculture and Livestock (MAL), Lusaka, Zambia; 11Université Catholique du Graben (UCG), Butembo, Democratic Republic of Congo; 12Institut National pour l’Etude et la Recherche Agronomique (INERA), Kinshasa, Democratic Republic of Congo; 13Kenya Agricultural Research Institute (KARI), Nairobi, Kenya; 14Kenya Plant Health Inspectorate Services (KEPHIS), Nairobi, Kenya; 15IITA, Dar es Salaam, Tanzania

Abstract Crop diseases do not respect country borders and yet preventive measures to curtail the introduction, establishment and spread of diseases are often coordinated on a country-by-country basis. This is because each country has its own mandate to safeguard food security and trade relations. However, knowledge held by researchers and regulatory officials within each country for any given disease can benefit those in neighbouring countries, and this can be reciprocated for other diseases, depending on aggregated disease distribution and experience of methods for effective diagnosis and management. Based on an appreciation of this common goal, national research and regulatory officials from seven countries networked to prioritize which diseases of banana (Musa spp.) were of critical importance and where to undertake spatially designed surveillance exercises around the Great Lakes region of sub-Saharan Africa. Surveys for banana Xanthomonas wilt and banana bunchy top disease were targeted to zones where outbreaks had been reported but not confirmed, and where invasion risk was high as a consequence of proximity to areas or countries known to contain either disease. To ensure that disease diagnoses were precise, field based visual assessments of symptoms were supported by molecular based diagnostics performed under laboratory

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 210 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Processes and Partnerships for Effective Regional Surveillance 211

conditions. Samples were transferred from plants in the field to the laboratory using pathogen DNA capture kits that could be swiftly and safely moved across country borders for analysis at a centralized laboratory to ensure that results from different surveys could be compared. The accuracy of global positioning system (GPS) coordinates recorded as the origin of samples from surveys was validated by comparing the altitude given by the GPS with altitude data provided by digital elevation models. Geographical information system (GIS) maps could then be generated to clearly show the prevalence of banana Xanthomonas wilt and banana bunchy top disease for the zones surveyed. Furthermore, the GIS maps can be used to interpolate different GPS-linked data sets to highlight factors driving disease establishment and spread, such as conducive environmental conditions, and to determine where to prioritize management strategies based on food insecurity measures. The need to prioritize investments across a region is of particular importance in developing countries where capacities for disease surveillance and diagnostics are limited, resulting in inaccurate pest lists and, as a consequence, limited prospects for sustained agricultural trade. If there is political will for regional communication, harmonized diagnostics and reporting mechanisms, the current scenario of fighting fully blown epidemics with exorbitant funds can be averted by coordinated, pre-emptive and thus cost efficient management interventions.

25.1 Introduction and Survey their distribution across locations that were Methods of strategic importance to the region. During an inception meeting in Rwanda The first and critical step in managing a (25–29 January 2010) the network reached disease is to diagnose the causal agent/s. consensus on where to prioritize nationally Once this is done, appropriate control meth- implemented disease surveys, based on a ods can be deployed, based on available combination of both national and regional knowledge or on results generated from tar- needs. The zones selected for surveys tended geted research. This chapter draws lessons to be close to country borders or where the from an initiative that defined the factors presence of disease(s) was unknown, but required to create a functioning disease sur- where the invasion risk was high due to close veillance network across a region. The initia- proximity to areas with disease or to areas tive targeted the two most serious threats to where disease outbreaks had been reported banana (Musa spp.) in the Great Lakes region but not confirmed (Plate 20). of sub- Saharan Africa, namely, banana Xantho- Each disease survey was planned to monas wilt caused by the bacterium Xantho- ensure that sites to be visited were spatially monas campestris pv. musacearum (Tripathi representative and not clustered. Global et al., 2009) and banana bunchy top disease positioning system (GPS) units were used to (BBTD), caused by the banana bunchy top facilitate navigation, to make return visits to virus (BBTV) (Kumar et al., 2011). Xantho- monas wilt and BBTD are established in sev- 6 eral countries in sub-Saharan Africa (Plate 19) 5 where banana production is of critical imp- 4 ortance (Fig. 25.1). Countries included in the initiative were Burundi, Democratic Republic 3 of Congo, Kenya, Rwanda, Tanzania, Uganda 2 and Zambia. To strengthen both national Area (millions ha) 1 and regional communication pathways, rep- resentatives from national research organ- 0 Musa spp. Plantain Banana izations and national plant protection organizations agreed to form a network for Fig. 25.1. Total area (white columns) in Africa the regional surveillance of Xanthomonas used to produce all Musa spp., plantain and wilt and BBTD. The specific objectives were banana (FAOSTAT, 2010) and total areas (grey to share information on the diagnosis and columns) in countries where banana bunchy top management of these diseases and to map disease (BBTD) and Xanthomonas wilt exist. 212 F. Beed et al.

interesting findings possible and to allow coordinates. Where this was not possible, for for the development of maps using a geo- example because incorrect GPS coordinates graphical information system (GIS). National had inadvertently been written down, survey staff performed surveys during 2010 and at notes were reviewed to trace the names of the each site recorded the presence or absence village associated with survey sites and pub- of the characteristic disease symptoms of lished maps were used to determine the Xanthomonas wilt and BBTD. Characteristic coordinates. symptoms for Xanthomonas wilt were A comparison was made between the defined as yellowing/browning and wilting presence of disease at survey sites as assessed of younger leaves, early ripening of fruits, by visual symptoms and the results from rotting of male buds and bunches, yellow PCR-based diagnosis of pathogen DNA on ooze from cut pseudostems or bracts and capture kits. For the majority of the survey brown staining of fruits. Characteristic symp- sites, similar results were generated. toms for BBTD were defined as dark dots and However, for 2% of sites there were positive dashes along foliar veins, hooking of veins laboratory results from DNA capture kits close to the midrib, yellow-brown curling while no symptoms were observed in the margins and narrow leaves, and stunted field, presumably because the disease was in plants with bunched leaves. a latent stage of infection, i.e. before symp- In addition, at each field survey site, tom expression but with the pathogen in suf- samples of pathogen DNA were collected from ficient quantity to be detected using the plants assessed visually for disease molecular techniques. This finding demon- symptoms using novel DNA capture kits (see strates the importance of precise diagnostic Ramathani and Beed, Chapter 13, this volume). methods, such as those using PCR, for early Analysis of the DNA capture kits was performed detection of a disease. For a further 3% of under laboratory conditions using PCR-based sites, positive field observations could not be molecular diagnostics and primers specifically confirmed to be BBTD or Xanthomonas wilt designed for the detection of X. campestris pv. through analysis of corresponding DNA cap- musacearum (Adikini et al., 2011) and BBTV ture kits. This was probably as a result of mis- (Mansoor et al., 2005). All DNA capture kits diagnosis of visual symptoms in the field. were analysed at the regional laboratory of the Xanthomonas wilt symptoms can be con- National Banana Research Programme of the fused with those of Fusarium wilt (caused by National Agricultural Research Organisation the fungus Fusarium oxysporum f.sp. cubense), (NARO) in Kampala, Uganda. which also causes wilting of leaves, although more commonly in older leaves, which are more uniformly discoloured, yellow and collapse to form a skirt around the pseu- 25.2 Results dostem. BBTD symptoms can be confused with differences in growth patterns due to Each country implemented the survey, different varieties or factors, such as mineral although not always as planned, because deficiencies. Comparison of visual symptoms sometimes practical constraints such as non- with confirm atory laboratory-based diagno- availability of staff or vehicles prevented tar- ses increases the confidence of fieldworkers geted areas from being surveyed, for example in their ability to differentiate symptoms. in Zambia (Plate 20). To validate the coordi- Where there was a discrepancy, the labora- nates of survey sites, comparisons were made tory results were used to authoritatively with expected altitude values derived using determine whether the disease-causing organ- digital elevation models (Plate 21). When alti- ism was present or absent. The results were tude measurements for any given survey plotted on a map using GIS. An example for location were more than 100 m different from BBTD is shown in Plate 22. the expected value, the people who carried GIS mapping allows for the interpolation out the survey were requested to review their of disease data by overlaying existing spa- survey notes to retrieve the correct location tially linked data sets, such as climate or Processes and Partnerships for Effective Regional Surveillance 213

trade routes, which, when combined, can increased human mobility, globalization of help to explain patterns of disease spread or trade, climate change, intensified farming highlight risk of further spread. In this way, systems and associated pathogen evolution. GIS maps can be used to prioritize invest- As diseases do not respect country borders, ments, in terms of time, staff or money, for it is logical to adopt a regional approach to future surveys or disease intervention cam- detect and curtail them and to disseminate paigns (Plate 23; Bouwmeester et. al, 2008). successful experiences in any given country Despite widespread awareness of the across a region. benefits of using GPS equipment, it was clear This initiative evaluated the partnerships from this initiative that further training was and processes required to increase the capac- required; for example, decimal degree set- ity for disease surveillance for two banana tings on GPS units were not routinely used, diseases in the Great Lakes region of Africa. which prevented the direct entry of data into The first step was to create a network, i.e. a software to produce digital maps, and the distributed group of individuals and organi- reporting of coordinates was often incorrect. zations that exchange information and work A further constraint to the wide adoption of toward a common goal (Miller et al., 2009). GIS maps by the network was the absence of The key partnerships created were between trained GIS specialists in the Great Lakes regulatory officials and research staff, and region. while this appears obvious, the major challenge to overcome is that formal connections within a given country do not exist, let alone between countries across a region. This is 25.3 Discussion because each organization is charged with individual mandates to manage crop diseases Too often, disease epidemics become estab- and they routinely possess fragmented and lished in a country and, due to inadequate discrete information but rarely work together. diagnostics and poor communication between The network employed processes such neighbouring countries, the disease is able to as agreement on which diseases to target and develop without restriction into regional epi- where the survey should be undertaken. This demics (van Halteren, 2000). Historically, in facilitated the sharing of information on how developing countries, such epidemics require to diagnose and manage the diseases tar- the expenditure of large amounts of resources geted. Field-based observations of disease from development partners for the deploy- symptoms were supported by laboratory- ment of mitigation strategies. Although the based diagnostic methods. A benefit of using cost of pathogen surveillance is perceived to DNA capture kits for centralized PCR-based be prohibitive, if it were carried out in an effi- diagnostics was that samples obtained from cient manner it could save millions of dollars across the region could be stored for up to in revenue that would otherwise be lost to 6 months and analysed using uniform meth- crop disease (Pearson, 2008). However, many ods, staff and equipment on the same date/s developing countries are experiencing to generate comparable results. Results from reduced capacity to perform surveillance and regional surveillance activities were plotted to diagnose pathogens, resulting in inaccurate on a visually easy-to-interpret map that could pest lists and, as a consequence, limited pros- be instantly shared across research staff and pects for international trade (Smith et al., 2008, regulatory officials and updated with new Waage et al., 2009). information as it became available. This situation is particularly apparent Common knowledge and increased in Africa, where the number of new disease awareness of the distribution of a disease is reports has decreased over the past century important to target where to deploy manage- in comparison with Europe (Waage et al., 2006). ment strategies to prevent further spread. Further, it is expected that new and emerging At a review workshop (held in Nairobi, from plant diseases will increasingly threaten 13 to 16 December, 2010) the network parti- agriculture in Africa as a consequence of cipants recognized that it (the network) can 214 F. Beed et al.

play a critical role in interpreting and acting of standard operating procedures for diagno- on results from the field and laboratory and stic methods through coordinated efforts, in sharing these nationally and across the such as those mediated by the International region. Increasing awareness of unfamiliar Plant Diagnostic Network (IPDN) and the symptoms of new diseases, for example European and Mediterranean Plant Protection BBTV in Kenya, Tanzania and Uganda, or Organization (EPPO), require sustained sup- Xanthomonas wilt in Zambia, is of particular port for any given region (Zlof et al., 2000; importance to facilitate their early detection Miller et al., 2010). and thus initiate steps to mitigate their estab- The initiative described here resulted in lishment and spread. Incorrect diagnoses a functioning surveillance network that tar- can have significant consequences because geted national surveys in areas considered to control interventions for most diseases are be of strategic importance to the region, using specific. For example, for Xanthomonas and robust diagnostics and sharing of information Fusarium wilts, apart from the destruction of and results. However, there needs to be infected plant material, the control interven- political will and funds to sustain such a tions are different: deployment of resistant network and to link it to other regional germplasm is recommended for Fusarium networks in Africa and beyond. This would wilt, while for Xanthomonas wilt the routine permit more rapid responses to crop disease use of cultural practices such as the steriliza- and the deployment of pre-emptive manage- tion of farm tools and removal of male buds is ment strategies to halt the establishment and recommended. spread of diseases and obviate the current sce- There are several opportunities to fur- nario of managing fully fledged epidemics. ther optimize diagnostic services to suit the Once the value of such networks is recognized, needs of regional disease surveillance net- through realization of the practical costs saved works, with a focus on high impact, low cost, through increased food security and income robust technologies such as handheld lateral generation, it is likely to be sustained through flow devices (akin to test kits for pregnancy a combination of public, development and or malaria that rely on serological diagnos- private funds (Miller et al., 2009). tics) that can be used both in the field and at border points to provide a diagnosis in a matter of a few minutes. Human and physical capacities must be harmonized and available Acknowledgements knowledge housed in common working documents that evolve as new information arises, Funds for this initiative were provided by the such as pest risk analysis for each targeted Food and Agriculture Organization of the disease. Similarly, the development and testing United Nations and USAID IPM-CRSP.

References

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Mansoor, S., Qazi, J., Amin, I., Khatri, A., Khan, I.A., Raza, S., Zafar, Y. and Briddon, R.W. (2005) A PCR- based method with internal control for the detection of banana bunchy top virus in banana. Molecular Biotechnology 30, 167–169. Miller, S.A., Beed, F.D. and Harmon C.L. (2009) Plant disease diagnostic capabilities and networks. Annual Review of Phytopathology 47, 15–38. Miller, S.A., Kinyua, Z.M., Beed, F., Harmon, C.L., Xin, J., Vergot, P., Momol, T., Gilbertson, R. and Garcia, L. (2010) The International Plant Diagnostic Network (IPDN) in Africa: improving capacity for diagnosing diseases of banana (Musa spp.) and other African crops. Acta Horticulturae 879, 341–347. Pearson, A. (2008) An Independent Review of New Zealand’s Biosecurity Surveillance Systems – Plants. Biosecurity in New Zealand, Ministry for Primary Industries (MPI), Wellington, New Zealand. Available at: http://biosecurity.govt.nz/pests-diseases/surveillance-review/plants.htm (accessed 2 May 2013). Smith, J.J., Waage, J., Woodhall, J.W., Bishop, S.J. and Spence, N.J. (2008) The challenge of providing plant pest diagnostic services for Africa. European Journal of Plant Pathology 121, 365–75. Tripathi, L., Mwangi, M., Abele, S., Aritua, V., Tushemereirwe, W.K. and Bandyopadhyay, R. (2009) Xanthomonas wilt: a threat to banana production in East and Central Africa. Plant Disease 93, 440–451. van Halteren, P. (2000) Diagnostics and national plant protection organizations. OEPP/EPPO Bulletin 30, 357–359. Waage, J.K., Woodhall, J.W., Bishop, S.J., Smith, J.J., Jones, D.J. and Spence, N.J. (2006) T15: Patterns of New Plant Disease Spread: A Plant Pathogen Database Analysis. Commissioned as part of the UK Government’s Foresight Project. Foresight. Infectious Diseases: Preparing for the Future, Office of Science and Innovation, London. Available at: http://www.bis.gov.uk/assets/foresight/docs/infectious- diseases/t15.pdf (accessed 2 May 2013) Waage, J.K., Woodhall, J.W., Bishop, S.J., Smith, J.J., Jones, D.J. and Spence, N.J. (2009) Patterns of plant pest introductions in Europe and Africa. Agricultural Systems 99, 1–5. Zlof, V., Smith, I.M. and McNamara, D.G. (2000).Protocols for the diagnosis of quarantine pests. OEPP/ EPPO Bulletin 30, 361–363. 26 Adoption and Impact of Tissue Culture Bananas in Burundi: An Application of a Propensity Score Matching Approach

E. Ouma,1* T. Dubois,2 N. Kabunga,3 S. Nkurunziza,1 M. Qaim4 and P.J.A. van Asten2 1International Institute of Tropical Agriculture (IITA) Bujumbura, Burundi; 2IITA, Kampala, Uganda; 3International Food Policy Research Institute (IFPRI), Kampala, Uganda; 4Georg-August University of Göttingen, Germany

Abstract Pests and diseases are among the main reasons for low banana productivity in smallholder farming systems in the central African highlands, where the crop is an important staple. In parts of Rwanda, Burundi and North and South Kivu provinces of eastern Democratic Republic of Congo, diseases such as banana bunchy top virus and banana Xanthomonas wilt are prevalent, thereby creating a large demand for new planting material and improved varieties that may have higher yield combined with resistance to diseases or nematodes. To improve the productivity of banana (Musa spp.), access by farmers to improved pest- and disease- free planting material is fundamental. Traditional methods of propagating bananas using suckers serve to perpetuate the problem of pests and diseases, thereby reducing production even further. Banana plantlets obtained from tissue culture (TC) technology are potentially disease-free alternatives but remain largely inac- cessible to most smallholder farmers due to the high cost of plantlets. This study employs a propensity score matching technique to examine the adoption and impact of TC banana technology in Burundi using a sample of 313 banana-farming households. In Burundi, TC bananas are subsidized by FAO and non-government organizations (NGOs), thus providing free plantlets to farmers. However, the adoption of TC bananas has not resulted in any significant increment in banana productivity or gross margins compared with traditional propagation using suckers. Improvements in institutional factors related to the delivery of technology and improvements of TC plantlet quality seem to be preconditions for more favourable technology impacts.

26.1 Introduction food security and revenue. The crop occupies about 25% of the cultivated land area and has Banana (Musa spp.) is an essential staple crop a high cultural value. Despite its importance throughout the Great Lakes region of eastern as both a cash and food crop, its annual pro- Africa, contributing to both rural household ductivity remains low in the region – at less

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 216 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Adoption and Impact of Tissue Culture Bananas 217

than 10 t/ha compared with a potential of buyers are international non-governmental over 50 t/ha (CIALCA, 2009). In Rwanda, organizations (NGOs) and the Food and there has been a steady decline in the banana- Agriculture Organization of the United cropped area and large fluctuations in yield Nations (FAO), which then usually distribute since 1986. In Uganda, the pattern of banana the plantlets at no cost to small-scale sub- decline is reflected in an overall 33% decrease sistence farmers. Plantlets are either directly in national yields between 1971 and 1991. distributed as part of wider agricultural The poor productivity of banana is exacer- development projects or through the provin- bated by pests and diseases, especially banana cial divisions of the Ministry of Agriculture bunchy top disease (BBTD), caused by the (Direction Provincial de l’Agriculture et de banana bunchy top virus (BBTV), and banana l’Elevage). It is noteworthy that the free Xanthomonas wilt, caused by Xanthomonas plantlet distribution is largely unaccompa- campestris pv. musacearum. nied by training and/or an input package. To improve banana productivity and Despite business entry barriers, TC banana safeguard sustainable banana production for production appears to be highly lucrative for small-scale farmers, clean, high quality the entrepreneurs, with profit margins esti- planting material is crucial (Gold et al., 2002). mated at up to 100% (T. Dubois, 2011, unpub- In East African smallholder systems, new lished results). The private sector producing banana fields are traditionally planted with TC plantlets is, however, not regulated in suckers. However, the use of tissue culture terms of virus-free certified plantings and (TC) plants is increasing, because they: (i) are proper production standards, thereby leading pest and disease free (with the exception of to high variability in the quality of the plantlets. fastidious bacteria and viruses); (ii) grow Despite a thriving private sector and the more vigorously, allowing for faster and free distribution of TC banana plantlets to higher yields; (iii) are more uniform, allowing the Burundian population, there is only for more efficient marketing; and (iv) can be anecdotal information on the impact of TC produced in large quantities in short periods plantlets on banana yields and household of time, thus permitting faster distribution welfare. This paper examines the impact of of planting material and new cultivars. TC banana technology in Burundi, focusing As such, the use of TC banana plantlets can on yield and gross margin outcomes by support farmers to make the transition from employing non-parametric evaluation tech- subsistence to small-scale commercial farming niques. Specifically, a propensity score (T. Dubois, 2011, unpublished results). In Kenya, model is employed to control for the self- TC banana was recently estimated to consti- selection that normally arises when technol- tute less than 7% of the total banana coverage ogy adoption is not randomly assigned area, while adoption rates in countries like (Rosenbaum and Rubin, 1983; Imbens and Uganda and Burundi are significantly lower Wooldridge, 2009). (Njuguna et al., 2010). A recent impact study for Kenya showed positive yield effects of TC banana adoption, but also pointed out the importance of good extension and proper 26.2 Empirical Specification of plantation management (Kabunga et al., 2012). Technology Choice and Impact TC plantlets require appropriate handling and Evaluation management practices to optimize their benefits. Consequently, this additional effort and The adoption of TC banana can be viewed as the cost of TC plantlets (US$1.20–2.00) pose an a dichotomous choice, where the technology extra cost for the Kenyan farmer. is adopted when the net benefits from doing The TC banana market in Burundi is so are greater than from not adopting. The presently served by two private laboratories difference between farmers’ perceived net and a public university and research organi- benefits from the adoption and non-adoption zation which, together, produce at least of TC may be denoted as I, such that I > 0 500,000 banana plantlets annually. Their main indicates that the net benefit from adoption 218 E. Ouma et al.

exceeds that of non-adoption. I (a dummy but it is a potentially biased estimator of variable) is unobservable, but Ii can be banana TC adoption impact. expressed as a function of observable ele- The propensity score matching (PSM) ments in the latent variable model: model can be employed to account for sample selection bias in the absence of experimental I = bX + m (26.1) i i i data. The PSM is defined as the conditional where Ii is a binary indicator variable that probability that a farmer adopts a new tech- equals 1 for farmer i in case of adoption, or 0 nology, given the pre-adoption characteristics b otherwise (Ii = 1[Ii > 0]); is a vector of (Rosenbaum and Rubin, 1983). The PSM parameters to be estimated; Xi is a vector of model employs the ‘unconfoundedness ass- m explanatory variables and i is an error term umption’, also known as the conditional inde- assumed to be normally distributed. The pendence assumption, which implies that probability (Pr) of TC banana adoption can once ‘X’ is controlled for, technology adop- be represented as: tion is random and uncorrelated with the outcome variables. Following Rosenbaum Pr(I = 1) = Pr(I > 0) = Pr(m > – bX ) i i i i and Rubin (1983), the propensity score can = 1 – F(– bX ) (26.2) i be expressed as: where F is the cumulative distribution func- m PS(X) = Pr(I = 1|X) = E(I|X) (26.4) tion for i. Different models such as logit or probit normally result from the assumptions that are made on the functional form of the where I = 0 or 1 is the indicator for adoption cumulative distribution function F (Maddala, and X is the vector of pre-adoption character- 1983; Wooldridge, 2005). istics. The conditional distribution of X given The adoption of TC bananas is expected Pr(X) is similar for groups of both adopters to have an impact on banana yields, demand and non-adopters. The underlying objective for inputs such as organic and inorganic fer- of PSM is to balance the observed distribution tilizers, and net returns. To link the adoption of the covariates, X, across the group of adop- decision with the potential outcomes, let Y ters and non-adopters. The ATT can then be i1 expressed as: and Yi0 denote potential observed outcomes (banana yield and net returns) for farmer i p = E(Y1 – Y0|I = 1) in case of TC banana adoption (I = 1) and = E[E(Y1 – Y0|I = 1,PS(X))] non-adoption (I = 0), respectively. Therefore, = E[E(Y|I = 1,PS(X)) Δ 1 = Yi1 – Yi0 is the adoption impact of banana – E(Y1|I = 0,PS(X)|I = 0)] (26.5) TC on the ith household, commonly referred to as the ‘treatment effect’. It follows that There are several matching methods the expected treatment effect for the popula- that have been developed to match adopters tion that has adopted TC bananas may be with non-adopters with similar propensity given as: scores. In this study, we employed nearest neighbour matching (NNM) and kernel- E( p|I = 1) = E(Y|I = 1) 1 based matching (KBM) methods, and used – E(Y |I = 1) (26.3) 0 Stata software for estimation (StataCorp, where p is the ‘average treatment effect for 2011). NNM involves choosing individuals the treated’ (ATT) (i.e. the average impact from adopters and non-adopters that are of TC adoption on the population that is closest in terms of propensity scores as exposed to the TC technology), Y1 denotes matching partners. The KBM method uses the value of the outcome for the banana TC the weighted average of the outcome varia- adopters and Y0 is the same outcome variable ble for all individuals in the non-adopter for non-adopters. However, it is impossible group to construct a counterfactual outcome, to observe both the adoption impact and giving more importance to observations that its counterfactual E(Y0|I = 1) for any given provide a better match. The weighted aver- farmer. Ideally, the difference E(p|I = 1) = age is then compared with the outcome in

E(Y1|I = 1) – E(Y0|I = 0) can be estimated, the adopter group. Adoption and Impact of Tissue Culture Bananas 219

26.3 The Data The t-values suggest that there are some differences between TC banana adopters and The data used in this analysis were derived non-adopters with respect to farm level, from a cross-sectional household survey household and social characteristics. In par- using extensive quantitative farm and house- ticular, there appear to be significant differ- hold questionnaires. The survey was con- ences in land ownership, productive assets ducted from November 2009 to January 2010 and livestock holdings, as well as access to in four of the main banana-growing com- agricultural technology and membership of munes of Gitega Province, Burundi, where social organizations. TC banana adopters are TC banana dissemination efforts had been generally wealthier in terms of land, produc- ongoing for several years. Within each com- tive assets and livestock ownership than are mune, banana-growing villages, specifically non-adopters. TC adopters also have easier those where TC activities had taken place in access to agricultural information and are the past, were purposely selected. Within more involved in collective action activities these villages, farm households were ran- through social groupings. These differences domly sampled. Separate village lists of suggest an apparently stable correlation adopters and non-adopters were prepared, between the incidence of adoption and natu- and adopters were over-sampled in order to ral and social capital endowments. There have a sufficient number of observations for was, however, no significant difference robust impact assessment. In total, 313 banana between adopters and non-adopters in terms farmers were sampled, of which 55% were TC of proximity to input and output markets, adopters and 45% non-adopters. Descriptive which ranged from 3 to 6 km. Non-adopters statistics of the adoption status for several of TC bananas are observed to have higher variables are presented in Table 26.1. average yields than TC adopters; although

Table 26.1. Descriptive statistics: mean and (standard deviation) of variables by status of adoption of tissue culture (TC) banana technology.

Adopters Non-adopters Variable (n = 172) (n = 141) Differencea t-values

Age of household (hh) head (years) 50 (11) 49.3 (14) 0.7 0.05 Gender of hh head (dummy) 0.09 (0.28) 0.11 (0.31) 0.02 –0.57 Household size (persons) 6.48 (2.2) 5.84 (2.2) 0.64*** 2.50 Banana farming experience (years) 28.7 (13) 28.4 (14) 0.27 0.17 Time spent farming (person days/month) 76.8 (62) 73.4 (53) 3.41 0.49 Education years of household head 5.6 (2.8) 5.2 (2.7) 0.40 1.24 Social grouping membership (dummy) 0.72 (0.4) 0.49 (0.5) 0.23*** 4.40 Cultivable land area (ha) 2.19 (277) 1.18 (198) 1.02*** 3.38 Log value of assets 3.74 (1.58) 3.14 (1.43) 0.60*** 3.02 Log value of livestock 5.21 (1.87) 3.86 (2.08) 1.36*** 6.01 Log household farm income 1.51 (1.48) 1.37 (1.48) 0.14 0.82 Log household off-farm income 2.18 (2.60) 2.05 (2.23) 0.13 0.44 Access to agricultural information 0.62 (0.49) 0.41 (0.49) 0.21*** 3.66 (1 = easy; 0 = difficult) Distance to the nearest market (km) 3.63 (2.84) 3.34(1.82) 0.29 0.98 Distance to the nearest input stockist (km) 5.77 (6.13) 4.74 (4.73) 1.03 1.54 Location dummies Giheta commune 0.37 (0.48) 0.42 (0.49) –0.06 –1.01 Gitega commune 0.18 (0.38) 0.11 (0.31) 0.07* 1.69 Itaba commune 0.10 (0.30) 0.14 (0.35) –0.04 1.25 Makebuko commune 0.36 (0.48) 0.33 (0.47) 0.03 0.56 Banana yield (t/ha) 6.3 (9.2) 7.5 (9.0) –1.2 –0.96 aSignificance of t-statistics of mean difference: *, P = 0.10; **, P = 0.05 (none in this instance); ***, P = 0.01. 220 E. Ouma et al.

this difference is not statistically significant, it adoption of TC banana. Such group networks is an indicator at this stage that TC bananas play an important role in disseminating do not necessarily improve productivity in banana TC information. The importance of Burundi. social groups, as well as close interactions with neighbours and local institutions, such as churches, in agricultural technology dis- 26.4 Empirical Results semination has been widely documented (Bandiera and Rasul, 2006; Matuschke and The logit model was employed to predict the Qaim, 2009). probability of adopting TC banana technol- The effect of adoption of TC banana tech- ogy (Table 26.2). A number of farm-level and nology on yield and gross margin was esti- institutional variables were found to influ- mated by the NNM and KBM matching ence the likelihood of adopting TC banana methods. The success of propensity score technology. In particular, large farmland and estimation is assessed by the balance between livestock holdings tend to increase the likeli- the treated (adopters) and untreated (non- hood of adoption. As the TC banana plantlets adopters). The common support condition is are given out free, it is possible that farmers imposed in the estimation by matching in the with larger land areas and livestock holdings region of common support (Fig. 26.1). are targeted by development organizations or Generally, there is substantial overlap extension agents for technology dissemina- and similarity between TC adopters and tion. Access to agricultural technology infor- non- adopters (Fig. 26.1). The quality of the mation and membership of social groups also matching estimations relies on the validity of plays an important role in facilitating the the conditional independence assumption,

Table 26.2. Propensity score for adoption of tissue culture (TC) banana technology (logit estimates).

Variable Coefficient Standard error z-valuea

Banana experience 0.055 0.050 1.10 (Banana experience) –0.001 0.001 –1.26 Time spent farming 0.004 0.003 1.17 Household (hh) size –0.045 0.089 –0.50 Gender of hh head 0.715 0.791 0.90 Education of hh head 0.037 0.069 0.53 Log of land size 0.346 0.148 2.33** Log value of assets 0.190 0.121 1.57 Log value of livestock 0.226 0.099 2.29** Log farm income –0.258 0.136 –1.90* Log off farm income –0.098 0.078 –1.25 Access to agric. technology 0.648 0.350 1.85* Distance-nearest road 0.009 0.060 0.15 Distance-nearest input stockist 0.009 0.034 0.26 Distance-nearest output market 0.003 0.083 0.04 Social grouping 0.634 0.364 1.74* Distance-TC nursery 0.426 0.481 0.89 Commune fixed effects Gitega 0.475 0.586 0.81 Itaba -0.639 0.705 –0.91 Makebuko 0.262 0.537 0.49 Constant –3.933 1.307 –3.01*** Number of observations 303 Pseudo R 2 0.171 Log-likelihood function –115.02 aStatistical significance of z-value: *, P = 0.10; **, P = 0.05; ***, P = 0.01. Adoption and Impact of Tissue Culture Bananas 221 No. of individuals

0 0.2 0.4 0.6 0.8 1 Propensity score Untreated: off support Untreated: on support Treated: on support Treated: off support

Fig. 26.1. Propensity score distribution (effect on productivity) and common support for propensity score estimation. Treated on support indicates the individuals in the tissue culture technology adoption group who find a suitable match, whereas treated off support indicates the individuals in the adoption group who did not find a suitable match. Matching of adopters with non-adopters with similar propensity scores was done by nearest neighbour matching (NNM) and kernel-based matching (KBM) methods.

which basically guarantees that groups are as potential reasons could be poor field manage- similar as possible. The pseudo-R2 of covari- ment of the plantlets by farmers and/or poor ate balancing tests dropped significantly from quality of plantlets from the tissue culture 0.17 before matching to about 0.02 after laboratories. As already mentioned, the agen- matching, which is a good indicator of match- cies disseminating TC bananas do not pro- ing quality (Table 26.3). The standardized vide farmers with physical or knowledge mean difference for overall covariates used in inputs to complement the free plantlets. Such the propensity score was also reduced signifi- inputs would include, first and foremost, cantly after matching. This reduces total bias TC-banana-specific field management tech- in the range of 67–73% through matching. niques in addition to, for example, fertilizers. The P-values of the likelihood ratio tests Field evidence in Burundi has revealed high showing the joint significance of the regres- mortality rates of TC plantlets pre-flowering. sors is rejected after matching. These results Dubois (T. Dubois, 2011, unpublished results) indicate that the proposed specification of the has also pointed to quality variability of the propensity score is fairly successful in terms TC banana plantlets, with several cases of of balancing the distribution of covariates ‘off-types’ and mixed cultivars that only between the two groups. As indicated by the become apparent once they are planted in average standardized bias measure, KBM has farmers’ fields. the best matching quality (Table 26.3). No significant banana yield or gross margin effect was observed between TC 26.5 Summary and Conclusion adopters and non-adopters, whether by NNM or KBM algorithms (Table 26.4). This chapter has analysed the factors influ- Though this study does not fully explore encing adoption of TC bananas as well as the the reasons behind such unexpected results, impact of TC bananas on yield and gross 222 E. Ouma et al.

Table 26.3. Matching quality indicators before and after matching tissue culture technology adopters and non-adopters. Matching algorithm: 1 = two nearest neighbour matching (NNM) with replacement, common support; 2 = six nearest neighbour matching with replacement, common support; 3 = kernel based matching (KLM) with band width 0.06, common support; and 4 = kernel based matching with band width 0.03, common support. LR = likelihood ratio.

Pseudo-R 2 for matching LR χ2 P-value for matching Mean standardized bias Matching Bias algorithm Before After Beforea After Before After reduction (%)

1. NNM 0.171 0.014 44.2*** 4.02 22.5 7.42 67 2. NNM 0.171 0.016 44.2*** 4.44 22.5 6.67 70 3. KBM 0.171 0.017 44.2*** 5.86 22.5 6.07 73 4. KBM 0.171 0.017 44.2*** 5.86 22.5 6.07 73 aStatistical significance: ***, P = 0.01.

Table 26.4. Banana productivity measures before and after matching by nearest neighbour matching (NNM) or kernel based matching (KLM). For details of matching algorithm, see Table 26.3. The difference (ATT) is the ‘average treatment effect for the treated’ (i.e. the average impact of TC adoption on the population that is exposed to the TC technology); SE, standard error;

Mean of outcome variables

Matching TC adopters Non-adopters Difference algorithm Outcome (n = 172) (n = 141) (ATT) SE

1. NNM Banana yield (t/ha) 6.02 7.40 –1.38 2.38 aGross margin, US$/100 m2 8.19 6.95 1.24 2.45 2. NNM Banana yield (t/ha) 6.02 6.38 –0.36 1.83 Gross margin, US$/100 m2 8.19 9.03 –0.84 2.45 3. KBM Banana yield (t/ha) 6.08 6.40 –0.31 2.26 Gross margin, US$/100 m2 7.37 7.57 –0.19 2.55 4. KBM Banana yield (t/ha) 6.08 6.40 –0.31 2.26 Gross margin, US$/100 m2 7.37 7.57 –0.19 2.55 a100 m2 = 1 are; 1 US$ = 1230 Burundian Francs as of January 2010.

margin outcomes in Burundi. The TC banana and related technologies in Burundi could be value chain, especially at the production and better targeted by taking account of these distribution level, is entirely subsidized, with criteria. private TC producers selling plants almost With respect to the performance of TC entirely to government and NGOs, which, in bananas, the results showed non-significant turn, supply the plantlets to farmers free, causal effects on banana yield and gross mar- mostly without any training. gin differentials between TC banana adop- Model estimations show that there are a ters and non-adopters. These results were number of factors that influence TC banana surprising because TC bananas have been adoption in Burundi. These include wealth, shown to outperform conventional suckers with particular reference to the value of pro- in field and on-station experiments in terms ductive assets, livestock and land. In addition, of yield. However, the institutional setting farmers with fewer constraints to accessing for promoting TC bananas is different in agricultural information, as well as those who Burundi from that in other countries. The are more affiliated with social groupings, are unexpected results could be attributed to more likely to adopt TC bananas. Future the poor-quality TC plantlets already in the expansion and dissemination of TC bananas field, coupled with poor field management Adoption and Impact of Tissue Culture Bananas 223

practices characteristic of smallholder farmers to purchase the needed complemen- banana farms in the region. Efficient distri- tary inputs. bution systems for TC bananas need to To ensure that the TC laboratories produce deliver the plants as part of a package that plantlets of superior quality that are disease free, includes training in banana husbandry man- plant health and quality regulations, including agement and access to micro-credit to enable virus screening schemes, need to be put in place.

References

Bandiera, O. and Rasul, I. (2006) Social networks and technology adoption in northern Mozambique. The Economic Journal 116, 869–902. CIALCA (2009) Technical Progress Report No. 6, CIALCA-II, January–December 2009. Consortium for Improving Agriculture-based Livelihoods in Central Africa. Available at: http://www.cialca.org/files/ files/TechnicalReport6.pdf (accessed 2 October 2011). Gold, C.S., Kiggundu, A., Abera, A.M.K. and Karamura, D. (2002) Diversity, distribution, and farmer preference of Musa cultivars in Uganda. Experimental Agriculture 38, 39–50. Imbens, G.W. and Wooldridge, J.M. (2009) Recent developments in the econometrics of program evaluation. Journal of Econometric Literature 47, 5–86. Kabunga, N.S., Dubois, T. and Qaim, M. (2012) Yield effects of tissue culture bananas in Kenya: accounting for selection bias and the role of complementary inputs. Journal of Agricultural Economics, 63, 444–464. Maddala, G.S. (1983) Limited-dependent and Qualitative Variables in Econometrics. Econometric Society Monographs, Cambridge University Press, Cambridge, UK. Matuschke, I. and Qaim, M. (2009) The impact of social networks on hybrid seed adoption in India. Agricultural Economics 40, 493–505. Njuguna, M., Wambugu, F., Acharya, S. and Mackey, M. (2010) Socio-economic impact of tissue culture banana (Musa spp.) in Kenya through the whole value chain approach. Acta Horticulturae 879, 77–86. Rosenbaum, P.R. and Rubin, D.B. (1983) The central role of the propensity score in observational studies for causal effects. Biometrika 70, 41–50. StataCorp. (2011) Stata Statistical Software: Release 12. StataCorp LP, College Station, Texas. Wooldridge, J.M. (2005) Violating ignorability of treatment by controlling for too many factors. Econometric Theory 21, 1026–1028. 27 Communication Approaches for Sustainable Management of Banana Xanthomonas Wilt in East and Central Africa

W. Tinzaara,1* E. Karamura,1 G. Blomme,1 W. Jogo,1 W. Ocimati1 and J. Kubiriba2 1Bioversity International, Kampala, Uganda; 2National Agricultural Research Organisation (NARO), Kampala, Uganda

Abstract The East and Central African region has been devastated by a banana Xanthomonas wilt epidemic caused by Xanthomonas campestris pv. musacearum. Xanthomonas wilt is widespread in Uganda, eastern Democratic Republic of Congo (DR Congo), Rwanda, Kenya and Tanzania, and has been confirmed as present in Burundi since late 2010. The disease causes yield losses of up to 80–100%, especially in ABB banana-based production systems in central Uganda and eastern DR Congo. Currently available information indicates that all cultivars in the region succumb to the disease and this, combined with the speed at which the epidemic spreads to new areas, threatens at least 30 million people who depend on the banana crop for their livelihoods. Recommended control measures for the disease include the destruction and disposal of infected plants/mats, disinfecting tools used in the plantation, using clean planting materials, early removal of male buds and quarantine measures. Raising awareness of all stakeholders along the production-to-consumption chain, by empowering them with the knowledge and skills for diagnosis and management of the disease, is seen as an integral component of the intervention strategy to control the epidemic and restore banana productivity. Several communication tools have been used to disseminate information for the management of Xanthomonas wilt. These include conventional tools (radio campaigns, videos, training by institutions, billboards, posters, brochures, newspapers and television) and participatory development communication approaches. While these approaches can contribute to raising awareness among stakeholders, and hence slow down the disease, no single approach can provide a lasting solution. This paper discusses the different communication approaches currently being used in the region to control the disease; and how integration of approaches may be the most effective and sustainable option for the management of Xanthomonas wilt in East and Central Africa.

27.1 Introduction regions. It is a major staple food, supplying up to 25% of carbohydrates for approximately Banana is an important food crop and a 70 million people in tropical and subtropical source of income for farmers in tropical Africa (FAOSTAT, 2006). The East and Central

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands 224 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) Communication Approaches for Sustainable Management 225

African (ECA) subregion alone produces about The economic impact of Xanthomonas wilt is 20 million tonnes annually and average per due to the death of the mother plant which, capita consumption is 250–300 kg (FAOSTAT, otherwise, would contribute to the ratoon 2006). Despite the key position of banana in plant production cycles. The recommended the region’s food security, smallholder farming management practices for Xanthomonas wilt communities engaged in its production derive in ECA include the destruction of diseased inadequate income from it. The crop is threat- plants, removal of male buds and the use of ened by various constraints, including socio- disinfected tools and clean planting material economic problems (poor market access, high (Eden-Green, 2004; Blomme et al., 2005). In crop management costs, limited postharvest ECA, there are cases where the disease has handling/utilization), declining soil fertility, been eradicated, while in other areas it has pests (the banana weevil and nematodes), and reached endemic status. There are also areas diseases (black leaf streak, Fusarium wilt, where the disease has been controlled, only to banana streak disease and banana bunchy resurge a few months later. The endemic top disease) (Gold et al., 2001; Tushemereirwe nature of the disease is partially attributed to et al., 2004; Bagamba et al., 2006). Since 2001, inadequate knowledge and awareness of Xanthomonas wilt of banana caused by farmers, extension people, local leaders and Xanthomonas campestris pv. musacearum has other stakeholders along the banana value become a serious threat to banana production chain about methods of disease diagnosis, in ECA (Tushemereirwe et al., 2004; Ndungo transmission and management. Raising et al., 2006; Tripathi et al., 2009). awareness of all stakeholders along the value Bacterial wilt diseases are known to be chain by empowering them with knowledge destructive to banana production in Indonesia on the spread and management of the dis- (blood disease), the Philippines (Bugtok) and ease, and with the skills for its diagnosis, is Latin America (Moko) (Molina, 1999). In central seen as a major integral component of any Uganda, Xanthomonas wilt was first reported intervention strategy to control the disease on bananas in Mukono and Kayunga districts and restore banana productivity. (Tushemereirwe et al., 2003), while in This chapter discusses the different Democratic Republic of Congo (DR Congo) approaches that can be used to disseminate the disease first appeared in Masisi, North messages on the diagnosis, transmission and Kivu (Ndungo et al., 2006). The disease sub- management of Xanthomonas wilt. An inte- sequently spread to Rwanda (2005), Kenya grated communication approach for effective (2006), Tanzania (2006) (Karamura and management of the disease is suggested. Tinzaara, 2009) and Burundi (2010). All banana germplasm, including endemic highland cooking and brewing cultivars 27.2 Diagnosis, Transmission and (AAA-EA), exotic brewing, dessert and roasting types (AB, AAA, AAB, ABB), and their Control of Xanthomonas Wilt hybrids are susceptible. Some ABB cultivars, such as ‘Pisang Awak’, are particularly sus- 27.2.1 Diagnosis ceptible to insect vector transmission of the disease and are believed to facilitate its Farmers’ knowledge about disease diagnosis rapid spread (Tushemereirwe et al., 2003). is very important in the management of the Some cultivars, such as ‘Dwarf Cavendish’ epidemic. Most farmers in ECA confuse (AAA, a dessert cultivar), which has persis- Xanthomonas wilt with Fusarium wilt and, as tent male bracts and flowers, escape insect a result, control measures are not targeted to transmission (Tushemereirwe et al., 2003; the epidemic. The first symptoms of a floral Addis et al., 2004). infection of Xanthomonas wilt include discol- The impact of Xanthomonas wilt is both oration at the tip of the male bud and wither- rapid and severe, unlike that of other dis- ing of the flower bracts (Tushemereirwe et al., eases, which cause gradually increasing 2004). This is followed by drying of the rachis, losses over years (Karamura et al., 2008). premature fruit ripening, drying and rotting 226 W. Tinzaara et al.

of bunches and, eventually, wilting and death of infected planting material and plant of the whole plant. Foliar symptoms include parts). Understanding the mechanisms of yellowing and wilting of leaves. When the Xanthomonas wilt transmission is very banana pseudostem is cut, yellow ooze in important in the management of the disease, the leaf sheaths or true stem confirms the although some farmers in the region are not presence of the disease. The plant dies within aware of the different modes that there are a month of the first appearance of any of (Jogo et al., 2011). the symptoms (Tushemereirwe et al., 2004).

27.2.3 Management 27.2.2 Transmission The recommended methods of managing Insect and bird transmission is believed to be Xanthomonas wilt that are disseminated behind the epidemic, together with the use of in the region include the destruction and contaminated garden tools and infected disposal of infected plants, the disinfection planting materials. Insects are important of tools used in the plantation, the use of vectors for the short-distance transmission of clean planting material, early removal the disease through floral parts (Tinzaara of male buds, keeping browsing animals et al., 2006). The rate of spread of the disease out of infected fields and quarantine meas- by insects is affected by the suitability of ures. While these measures, if adhered to, the environment for the development of the will undoubtedly slow the spread of the dis- insect vectors (Mwangi et al., 2006). Disease ease, they do not offer promise for long-term spread by insects is also highly affected by control of the disease. Moreover, no single the traits of the Musa cultivar’s inflorescence method seems to provide a ‘silver bullet’ (i.e. quantity of nectar, persistence of male for the management of Xanthomonas wilt bracts and flowers) (F. Komi, Uganda, 2008, in ECA. For long-term impact, an integrated personal communication), but banana culti- approach is needed that is driven by host vars that have persistent male flowers and plant resistance, involves the surveillance of male bracts do not provide an opportunity disease outbreaks and the creation of com- for insect contamination as no open wounds munity structures (such as task forces), and are created on the rachis. creates awareness among all stakeholders Various birds and bats commonly collect along the production-to-consumption chain nectar from male buds and may pose a seri- (Tinzaara et al., 2009). ous threat when it comes to long-distance In spite of the efforts that have been transmission, as their flight range is consider- made to disseminate information on disease ably larger than that of insects (R. Buregyeya, management, the adoption of control tech- Uganda, 2012, personal communication). nologies by farmers has generally been low, Cows, goats and sheep can also transmit the thereby further limiting the potential for disease while browsing on a healthy plant successful control of the disease. Challenges after having browsed on a contaminated to the adoption of control methods for plant. The farm tools that are used during Xanthomonas wilt in ECA include: (i) diffi- harvesting, the removal of old leaves, de- culty in persuading farmers to destroy dis- suckering or corm paring before planting eased plants in a mat; (ii) the labour-intensive are the most important means of transmis- nature of destroying/uprooting diseased sion of Xanthomonas wilt (Bagamba et al., mats; (iii) the requirement for costly disin- 2006). Tool-mediated infection is also very fectants (which are also of limited availability important in the trading system as buyers in remote villages); (iv) negative attitudes pass from field to field using the same tools towards new technologies; and (v) inade- to harvest mature bunches. Transmission quate knowledge and sensitization of farm- over long distances is also believed to be due ers, local leaders, extension people and other to human activities (such as the movement stakeholders. The different communication Communication Approaches for Sustainable Management 227

approaches that are currently being used in 27.3.1 Conventional communication ECA for dissemination of messages about approaches Xanthomonas wilt management technologies are discussed below. These are generally top-down approaches that treat affected communities (or communities at risk) as passive recipients of infor- 27.3 Communication Approaches mation, via methods such as print and electronic media, seminars and workshops Effective extension, education and communi- and farmer training. These are discussed sep- cation services are probably some of the key arately below. strategies for sustaining agricultural growth, strengthening food security and combating Print and mass media hunger and malnutrition. These services are critical for delivering useful information to The mass media communication channels farmers and assisting those farmers to develop most highly-ranked by farmers in ECA in the requisite knowledge, skills and attitudes terms of spreading information on Xantho- to make use of this information or technol- monas wilt and its management are the ogy effectively. However, diverse sociocultural radio and leaflets/pamphlets/posters/man- backgrounds, linguistic barriers, geographical uals (Table 27.1) (Tinzaara et al., 2009). remoteness and differential incentives make Television messages were reported to be the task of information dissemination chal- very expensive but not effective in reaching lenging. As a result of such heterogeneity, the intended communities, possibly because communities have a complex understanding of most farmers in Uganda do not own tele- diseases (Xanthomonas wilt in this case), their visions (Kiiza et al., 2006). In addition, most spread and management, and caution has to be television and radio stations are concen- taken against producing generic communica- trated in urban areas and their transmissions tion messages and templates for managing may not be easily accessed by rural farmers. the diseases. Several communication channels There is a need for community radio stations have been used to disseminate information on that would address the interests of a certain the management of Xanthomonas wilt in ECA; area, broadcasting content that is popular in the following discussion these are cate- with a local audience but may often be gorized into conventional communication overlooked by commercial broadcasters. approaches and participatory communication Similarly, newspaper pull-outs are known approaches (Tushemereirwe et al., 2006). not to be very effective in conveying

Table 27.1. Channels for disseminating information about Xanthomonas wilt in Rwanda, Tanzania and Uganda categorized by effectiveness: *, less effective; **, effective; ***, very effective (Source: Tinzaara et al., 2009).

Communication channel Rwanda Tanzania Uganda

Community-based organization/non-governmental organizations * *** *** (NGOs) Documentary/drama ** ** ** Leaflets/pamphlets/posters/manuals *** *** *** Local leaders/farmers/traders *** *** ** Newspapers and newsletters ** ** ** Participatory development communication – – *** Radio *** *** *** Telephone SMS messaging * * ** Television * * * Training/seminars/workshops *** *** *** 228 W. Tinzaara et al.

messages about Xanthomonas wilt as they The strategy helped to increase farmer are only accessible to the elite who reside in awareness of the disease (Kiiza et al., 2006). towns and cities. For traders, the major sources of information on the detection, con- The mobile phone system trol and spread of Xanthomonas wilt are fellow traders, followed by radio and farmers Solid surveillance mechanisms are crucial (Kiiza et al., 2006). in the control of Xanthomonas wilt disease. The mobile phone (and text messag- Seminars and workshops ing) system has been successfully tested in Uganda by the National Agricultural These are major tools for informing differ- Research Organisation (NARO) for the ent stakeholders about Xanthomonas wilt. purposes of information flow on disease Several seminars and workshops at regional, surveillance and control (Tushemereirwe national and community level have been et al., 2006). This is a bidirectional, imme- conducted in ECA by trained trainers. These diate communication between science events have enabled many local leaders, (disease diagnosis and control) and prac- opinion leaders, non-governmental organi- tice (growers’ observations and needs). zations (NGOs) and interested farmers to The approach involves having compe- join the expanding pool of trainers. This tently trained community knowledge approach was very effective in disseminat- workers who can train the local communi- ing information about Xanthomonas wilt for ties. The local communities then provide targeted trainers in Uganda (Kiiza et al., government and researchers with informa- 2006) and in Rwanda and Tanzania (Tinzaara tion on disease occurrence through text et al., 2009). However, the effectiveness of messaging. This provides opportunities these tools in reaching farmers depends on for obtaining and accumulating surveil- the subsequent effectiveness of the partici- lance data in a cost-effective manner. pants in using the information in their own Mobile phone technology, then, has great outreach efforts. potential in improving the disease and pest surveillance system in ECA, and its wider application for other diseases and Training of trainers pests at community level should be The national agricultural research systems explored. Currently, there is a lack of the (NARS) in the region, in collaboration with national and regional surveillance and international research centres such as Bio- monitoring mechanisms that are necessary versity International and the International for management of the disease. Institute of Tropical Agriculture (IITA) have conducted training of extension workers Publications and scientists drawn from all countries in ECA (notably during the Crop Crisis Control Bioversity International, via the Banana Project (C3P) of 2007–2008); the training Research Network for East and Southern covered disease identification/diagnostics, Africa, has facilitated communication among disease spread and control. Two regional regional partners through the development training sessions were conducted in prepa- and dissemination of a regional Xanthomonas ration for the deployment of trainers in wilt management strategy. In this context, their own countries. These trained exten- it has published a management guide for sion staff then trained over 50,000 stake- Xanthomonas wilt, pest risk analyses, pro- holders to the farm level (Karamura et al., ceedings and technical reports and a special 2008). In Uganda, service providers drawn issue of African Crop Science Journal (2006) on from the Uganda National Farmers’ Xanthomonas wilt. It has also made informa- Federation were trained to support the tion about Xanthomonas wilt available on the extension staff in sensitizing stakeholders at Bioversity web site (http://bananas.bioversi- the farm level (Tushemereirwe et al., 2006). tyinternational.org). Most of the documents Communication Approaches for Sustainable Management 229

that are accessible provide information on Okasaai, 2006). Lessons from public health disease diagnosis, spread and management. management have shown that an outbreak can be brought under control only when communities actively participate in control 27.3.2 Participatory communication and prevention activities and are ready to approaches adopt and sustain preventive and mitigation behaviours (WHO, 2009). Although these Participatory development approaches may lead to sustainable mana- communication (PDC) gement of the disease, they are still localized in only a few areas and there is a need to scale This approach involves members of the com- them up in the region. munity taking part in problem identification and analysis. It enables the community to Farmer field schools (FFS) analyse and explore alternative solutions to the problem, and to identify the best solu- Farmer field schools (FFS) are a community- tions that they are prepared to implement based participatory extension approach for (Nankinga and Okasaai, 2006). By putting the diffusing new science-based knowledge and affected communities at the centre of the pro- information to farmers in the field. The cess, the PDC approach ensures that the approach empowers farmers to make logical needs, preferences and constraints of commu- crop management decisions, exposes them to nities are understood and taken into account new ways of thinking and problem solving, in developing disease management strate- and encourages them to implement and dis- gies. Furthermore, the participation of com- cuss their own solutions (Hakiza et al., 2004). munities in shaping interventions allows the The method also provides a framework integration of indigenous knowledge, so that through which farmers can learn together the technologies developed are effective, through testing and demonstrating technolo- practical and locally adapted, and can be eas- gies on their farms (Okoth, 2006). FFS also ily adopted and sustained by communities. facilitate the building of coherent farmer In Uganda, a concept of PDC was groups able to demand services and promote adopted to better reach out to the public with the diffusion of innovations within the groups messages about control measures for of the community. The FFS operate on the Xanthomonas wilt (Nankinga and Okasaai, principle that farmers need to develop a bet- 2006; Tushemereirwe et al., 2006). The PDC ter understanding of the constraints inhibit- approach in Uganda centred on facilitating ing their efforts if they are to manage their communities to develop action plans to crops effectively. The FFS approach that was address specific problems facing them coordinated by NARO and FAO (Food and (Tushemereirwe et al., 2006). It used visual Agriculture Organization of the United tools such as videos to attract attention in Nations) in Uganda in 2006–2009 worked to public places like markets, churches, school effectively disseminate information and open days and public transport systems in equip farmers with the knowledge to control order to communicate information to the Xanthomonas wilt (Kubiriba et al., 2012). The public on symptoms of the disease, its spread same approach has been recently initiated in and control measures, and to solicit their sup- western Kenya by the Kenya Agricultural port in control campaigns (Nankinga and Research Institute (KARI) and the Rural Okasaai, 2006). Empowerment of stakehold- Electricity and Food Security Organization, ers is greatly boosted if effective communica- with support from the McKnight Foundation tion strategies with clear messages are in through Bioversity International. The place. To reinforce messages about manage- approach has been found to contribute sig- ment of Xanthomonas wilt in Uganda, a pub- nificantly to the effective management of lic awareness approach – ‘going public’ – was Xanthomonas wilt and increased banana pro- borrowed from the HIV/AIDS campaigns to duction in western Kenya. The FFS approach reach out to the public (Nankinga and is, however, a very intensive format, which 230 W. Tinzaara et al.

makes it difficult to work with thousands of Xanthomonas wilt (early male bud removal, farmers. Nevertheless, it is very effective removal of infected plants/mats and heap- when teaching an integrated pest manage- ing the debris, sterilization of garden tools ment strategy over an entire cropping season and use of clean planting materials) was and needs to be scaled up to other banana- increased as a result of the active involve- growing areas in the region. ment of community structures in Tanzania (J. Nkuba, et al., Tanzania, 2012, personal Farmer exchange visits communication). As a result, the incidence of Xanthomonas wilt was significantly Farmer exchange visits, or farmer-to-farmer reduced at two project benchmark sites from visits, are key in promoting awareness among 40% in 2009 to less than 5% in 2011. stakeholders along the value chain. During Community structures generally help in the the C3P, it was realized that different NARS implementation of control options and also were at different levels of capacity to manage in monitoring their impact. Their success Xanthomonas wilt within their borders. depends partly on social cohesion in the Therefore, a decision was made to organize community which, in turn, is influenced by exchange visits for extension/farmer teams the socio-economic and cultural heterogene- to facilitate cross-border exchanges of infor- ity of the community. mation and technologies (Karamura et al., 2008). The countries visited depended on the needs of the visiting teams and the experiences/comparative advantages of the hosting 27.3.3 Success of communication teams. Thus, the Rwandan/Congolese teams channels visited Uganda, targeting farmer-empowering approaches that put the farmers at the fore- Communication initiatives are key to enhanc- front of the fight against wilt. The Ugandan ing rural development by empowering the teams visited Tanzania to acquaint them- rural farmers with new knowledge, up-to- selves with stakeholder mobilization, target- date information and problem-solving skills. ing local councils and other policy makers, Effective communications aims to improve while the Kenyan farmers visited Uganda to the understanding of skills at different learn skills for raising public awareness. levels, which enables the identification of appropriate systems and institutions for the Community structures (task forces) delivery of relevant information. A participatory community-centred communication The formation of community structures such approach can enhance the adoption of infor- as task forces was found to be an effective mation and communication technologies, in channel for disseminating information contrast to receiving information in the form among stakeholders (Tushemereirwe et al., of messages from external sources (Chapman 2006). Task forces were formed from the et al., 2003; Masuki et al., 2008). national level down to the village and com- The choice of communication approach munity level and these were charged with should take into account the capacity (for different roles geared to the management of example, literacy levels, number of radio Xanthomonas wilt. There are also commu- receivers and extension support) available in nity-based structures that are organized to the target area (Table 27.2). Information is manage Xanthomonas wilt in the Kagera important in raising awareness, which is a Region in Tanzania (Fig. 27.1). Through critical element in disease management. these community-based structures, the prob- However, awareness alone is not sufficient to lem of Xanthomonas wilt and its control instigate behavioural change. For instance, strategy are owned by the communities previous research on Xanthomonas wilt (Jogo which, as a result, become highly motivated et al., 2011) showed that a significant number in the implementation of control measures. of farmers with affected plants, who were Farmers’ awareness of options to control aware of the control practices, were not Communication Approaches for Sustainable Management 231

Ministry of Ministry of Local Agriculture Government (Policy, regulation and (Policy, regulation and law law enforcement) enforcement)

Regional Adminstrative Secretary (Steering committee – advisory role)

District Councils Research Institute (Task force – coordination, (Development of dissemination, supervision technology,dissemination and capacity building) and capacity building)

Ward (Task force – coordination and law enforcement)

Village (Task force – coordination and law enforcement)

Sub-village (Task force –coordination and law enforcement)

Farmers (Implementers of Xanthomonas wilt control measures)

Fig. 27.1. Organization of community-based structures for the management of Xanthomonas wilt in Kagera Region, Tanzania. Arrows indicate the direction of information flow. Source: J. Nkuba, Tanzania, 2012, personal communication.

applying them, partly because of insufficient 27.4 Conclusion and in-depth understanding of the technologies Recommendations involved. This conclusion was further supported by evidence from the same study indi- Xanthomonas wilt is now regarded as cating the widespread incorrect application endemic in banana cropping systems in ECA, of recommended methods. By actively engag- although within each agro-ecology there are ing communities, participatory approaches still disease-free (though threatened) areas. can empower them with knowledge and Several methods, such as cultural control, the enhance their capacity to adapt interventions, creation of awareness of disease diagnosis especially those that integrate elements of and management, and quarantine have been indigenous knowledge. recommended to farmers, but adoption of 232 W. Tinzaara et al.

Table 27.2. Strengths and weaknesses of various communication channels employed in East and Central Africa.

Communication channel Strengths Weaknesses

Radio • Relatively cheap technology • Uses only one sense (hearing) • Wide penetration into several affected • Listener does not see communicator communities • Informal (sometimes not taken • Possibility of receiving prompt feedback seriously) • Can be shared by many listeners • Need for regular replacement of simultaneously batteries is a cost to farmers • Portable, easy to move from one place • Message is only available at time of to another broadcast • Niche audiences can be readily targeted Television • Combination of sound and visual • Expensive to acquire (possessed by images is attractive and convincing a few) (seeing is believing) • Low TV network coverage in the country • Possibility of receiving prompt feedback • Restricted portability • Can be shared by many viewers • Message is only available at time of simultaneously broadcast Print media • Visual images make them attractive • Expensive to produce • Can be shared by many readers • Added costs of transportation and successively distribution • Easy to reproduce • High literacy level requirement • Easy to transport • Subjective distribution can reduce their • Can contain all the required details circulation • If properly stored, can be useful for a • Low readership, e.g. the Ugandan long period of time newspapers (New Vision and Monitor) together reach about 100,000 Ugandans compared with a population of more than 12 million banana farmers Farmer training/ • Can use both audio and visual images • Expensive to plan and conduct workshops thereby making them very informative • Poor logistical support (limited transport • Can be attended by many participants and equipment) simultaneously • Low levels of collaboration and • Can furnish all the required details interaction among all service providers • Many stakeholders can play a role • Reaches very few farmers (public and private sector service providers, farmers, international bodies) • Can be conducted in diverse forms (seminars, workshops, demonstrations) • Interactive and allows for prompt feedback (two-way communication) control measures is generally low and the dis- While the different conventional ease is still spreading across the region. communication approaches will contribute to Limited success in disease management is awareness among stakeholders, and hence partially attributed to lack of sustained slow down disease spread, these do not awareness among the different stakeholders provide a long-term effect as they may not lead along the banana value chain, together with to behavioural change among most farmers. inadequate use of participatory communica- Action-oriented communication approaches tion approaches that lead to behavioural are necessary for the adoption of technologies change of farmers within the disease-affected and sustainable management of the disease. communities. The mass media, for example, can be very Communication Approaches for Sustainable Management 233

effective, but are generally not sufficient course (Masuki et al., 2008). An integrated when used alone as they may have a limited approach to adoption and sustainable man- effect on farmers’ behaviour, whereas a more agement of the disease that combines conven- labour-intensive communication strategy tional and participatory methods is therefore based on a group approach (meetings, work- necessary to raise awareness and foster shops, demonstrations) is normally advisa- behavioural change by empowering farmers ble to convince at least the early adopters, to take charge of their lives (through active who will be followed by the majority in due participation).

References

Addis, T., Handoro, F. and Blomme, G. (2004) Bacterial wilt (Xanthomonas campestris pv. musacearum) on enset and banana in Ethiopia. InfoMusa 13(2), 44–45. Bagamba, F., Kikulwe, E., Tushemereirwe, W.K., Ngambeki, D., Muhangi, J., Kagezi, G.H. and Green, S. (2006) Awareness of banana bacterial wilt control in Uganda. Farmers’ perspective. African Crop Science Journal 14, 157–164. Blomme, G., Mukasa, H., Ssekiwoko, F. and Eden-Green, S. (2005) On-farm assessment of banana bacterial wilt control options. In: Tenywa, J.S., Adipala, E., Nampala, P., Tusime, G., Okeri, R. and Kyanuhangire, W. (eds) African Crop Science Conference Proceedings, Volume 7, Part 1, Kampala, Uganda, 5–9 December 2005. African Crop Science Society, pp. 317–320. Available at: http://www. acss.ws/?t=a_conf&s=4 (accessed 3 May 2013). Chapman, R., Slaymaker, T. and Young, J. (2003) Livelihoods Approaches to Information and Communication in Support of Rural Poverty Elimination and Food Security. Food and Agriculture Organization of the United Nations, Rome with Department for International Development (DfID), London. Available at: http://pdf.wri.org/ref/chapman_03_livelihoods.pdf (accessed 3 May 2013). Eden-Green, S. (2004) How can the advance of banana Xanthomonas wilt be halted? InfoMusa 13(2), 38–41. FAOSTAT (2006) Online statistical database. Food and Agriculture Organization of the United Nations, Rome. Available at: http://faostat.fao.org/ (accessed 3 May 2013). Gold, C.S., Pena, J.E. and Karamura, E.B. (2001) Biology and integrated pest management for the banana weevil, Cosmopolites sordidus (Germar) (Coleoptera: Curculionidae). Integrated Pest Management Reviews 6, 79–155. Hakiza, J.J., Odogola, W., Mugisha, J., Semana, A.R., Nalukwago, J., Okoth, J. and Ekwamu, A. (2004) Challenges and prospects of disseminating technologies through farmer field schools: lessons learnt based on experiences from Uganda. Uganda Journal of Agricultural Sciences 9, 196–175. Jogo, W., Karamura, E.K., Kubiriba, J., Tinzaara, W., Rietveld, A., Onyango, M. and Odongo, M. (2011) Farmers’ awareness and application of banana Xanthomonas wilt control options: the case of Uganda and Kenya. Journal of Development and Agricultural Economics 3, 561–571. Karamura, E. and Tinzaara, W. (2009) Management of Banana Xanthomonas Wilt in East and Central Africa. Proceedings of the Workshop on the Review of the Strategy for the Management of Banana Xanthomonas Wilt, 23–27 July 2007, Hotel la Palisse, Kigali, Rwanda. Bioversity International, Kampala, Uganda. Karamura, E., Turyagyenda, F.L., Tinzaara, W., Blomme, G., Molina. A. and Markham, R. (2008) Xanthomonas Wilt (Xanthomonas campestris pv. musacearum) of Bananas in East and Central Africa. Diagnostic and Management Guide. Bioversity International, Kampala, Uganda. Kiiza, B.A., Lwasa, S., Rwomushana, G. and Diiro, G.M. (2006) An Evaluation of the Banana Bacterial Wilt Disease Awareness Campaign in Uganda. A report submitted to United States Agency for International Development (USAID) and the Danish International Development Agency (DANIDA), Kampala, Uganda. Kubiriba, J., Karamura, E.B., Jogo, W., Tushemereirwe, W.K and Tinzaara, W. (2012) Community mobilization: a key to effective control of banana Xanthomonas wilt. Journal of Development and Agricultural Economics, 4, 125–131. Masuki, K.F., Kamugisha, R., Mowo, J.G., Tukahirwa, J.M. and Tanui, J.K. (2008) Improved Access to Information for Development. ACACIA Final technical report submitted to IDRC by African Highlands Initiative (AHI), World Agroforestry Centre (ICRAF). AHI, Kampala, Uganda. 234 W. Tinzaara et al.

Molina, A.B. (1999) Fruit rot disease for cooking banana in South East Asia. InfoMusa 8(1), 29–30. Mwangi, M., Tinzaara, W., Vigheri, N., Namu, F.N., Ragama, P. and Bandyopadhyay, R. (2006) Comparative study of banana Xanthomonas wilt spread in mid and high altitudes of the Great Lakes region of Africa. In: Tropentag 2006, University of Bonn, October 11–13, 2006. Conference on International Agricultural Research for Development. Available at: http://elewa.org/pestdseagric/4BXWspreadmid& highaltitudes.pdf (accessed 3 May 2013). Nankinga, C. and Okaasai, O. (2006) Community approaches used in managing BXW in Uganda. In: Karamura E.B., Osiru, M., Blomme, G., Lusty, C. and Picq, C. (eds) Developing a Regional Strategy to Address the Outbreak of Banana Xanthomonas Wilt in East and Central Africa: Proceedings of the Banana Xanthomonas Wilt Regional Preparedness and Strategy Development Workshop Held in Kampala, Uganda, 14–18 February 2005. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France, pp. 56–60. Ndungo, V., Eden-Green, S., Blomme, G., Crozier, J. and Smith, J. (2006) Presence of banana Xanthomonas wilt (Xanthomonas campestris pv. musacearum) in the Democratic Republic of Congo. Plant Pathology 55, 294. Okoth, J. (2006) Prospects for management of BXW through Farmer Field School approaches. In: Karamura E.B., Osiru, M., Blomme, G., Lusty C. and Picq C. (eds) Developing a Regional Strategy to Address the Outbreak of Banana Xanthomonas Wilt in East and Central Africa: Proceedings of the Banana Xanthomonas Wilt Regional Preparedness and Strategy Development Workshop Held in Kampala, Uganda, 14–18 February 2005. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France, pp. 61–63. Tinzaara, W., Gold, C.S., Ssekiwoko, F., Tushemereirwe, W., Bandyopadhyay. R., Abera, A. and Eden- Green, S.J. (2006) The possible role of insects in the transmission of banana Xanthomonas wilt. African Crop Science Journal 14, 105–110. Tinzaara, W., Karamura, E.B., Kubiriba, J., Byabachwezi, M., Tushemereirwe, W. and Opio, F. (2009) The integrated approach for the management of banana Xanthomonas wilt in east and central Africa. In: Tenywa, J.S., Joubert, G.D., Marais, D., Rubaihayo, P.R. and Nampala, M.P (eds) African Crop Science Conference Proceedings Volume 9, Part 2, Cape Town, South Africa, 28th September to 2nd October, 2009. African Crop Science Society, pp. 691–696. Available at: http://www.acss.ws/?t=a_ conf&s=4 (accessed 3 May 2013). Tripathi, L., Mwangi, M., Abele, S., Aritua, V., Tushemereirwe, W.K. and Bandyopadhyay, R. (2009) Xanthomonas wilt: a threat to banana production in east and central Africa. Plant Disease 93, 422–451. Tushemereirwe, W., Kangire, A., Smith, J., Ssekiwoko, F., Nakyanzi, M., Kataama, D., Musiitwa, C. and Karyeija, R. (2003) An outbreak of bacterial wilt on banana in Uganda. InfoMusa 12(2), 6–8. Tushemereirwe, W., Kangire, A., Ssekiwoko, F., Offord, L. C., Crozier, J., Boa, E., Rutherford, M. and Smith, J.J. (2004) First report of Xanthomonas campestris pv. musacearum on banana in Uganda. Plant Pathology 53, 802–802. Tushemereirwe, W.K., Okaasai, O., Kubiriba, J., Nankinga, C., Muhangi, J., Odoi, N. and Opio, F. (2006) Status of banana bacterial wilt in Uganda. African Crop Science Journal 14, 74–82. WHO (2009) Social Mobilization in Public Health Emergencies: Preparedness, Readiness and Response. Report of an Informal Consultation, Geneva, Switzerland, 10-11 December 2009. Document No. WHO/ HSE/GAR/BDP/2010.1, World Health Organization, Geneva, Switzerland. Available at: http://www.who. int/csr/resources/publications/HSE_GAR_BDP_2010_1/en/index.html (accessed 3 May 2013). 28 A Global Information and Knowledge Sharing Approach to Facilitate the Wider Use of Musa Genetic Resources

N. Roux,* M. Ruas and B. Laliberté Bioversity International, Montpellier, France

Abstract A wider use of the available Musa (banana and plantains) diversity would boost rural livelihoods and food security. A comprehensive understanding of such diversity, and of its potential uses, is crucial to all stakeholders within the Musa value chain, to whom such knowledge needs to be made accessible. A germplasm information management system and stakeholder networks provide a global platform to assure wider and more effective knowledge sharing for this purpose.

28.1 Importance of Musa agricultural production systems more sus- Genetic Diversity tainable, and bananas and plantains are no exception. Growing a mix of cultivars can Bananas and plantains (Musa spp.) are among contribute to safeguarding the crop against the most important basic food crops for an pests and diseases and make it more resilient estimated 400 million people. The world’s under adverse environmental conditions. production of dessert bananas is 97 million t (Mt), In addition, different cultivars can bring and the five largest producing countries are different nutritional benefits to poor popula- India (27 Mt), China (9 Mt), the Philippines tions and offer a broader range of processing (9 Mt), Ecuador (7.6 Mt) and Brazil (6.8 Mt). and marketing opportunities. Global production of plantains and cooking The main challenge in banana cultivation bananas is 36 Mt, with the five largest produc- remains the lack of resistance or tolerance to ing countries being Uganda (9.5 Mt), Ghana the many pests and diseases that threaten its (3.6 Mt), Rwanda (3 Mt), Nigeria (3 Mt) and production. For example, banana bunchy top Colombia (3 Mt). The major part of Musa pro- virus (BBTV)-infected plants were recently duction (87%) is for local consumption and detected in the Democratic Republic of Congo only the remaining 13% comprises exported (Bas Congo Province), where many small vil- Cavendish varieties (FAOSTAT, 2009). lages in that region depend on banana culti- Intraspecific crop diversification is a vation for their income. As a result of this crucial component of any strategy to make viral disease, the production of bananas to be

* E-mail: [email protected]

©CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 235 236 N. Roux et al.

sold on the Kinshasa market dropped from result of intensive oil palm planting in east- two trucks a week to zero in just a year (Vangu ern Sabah (Indonesia; northern Borneo). Paka, Mvuazi, 2008, personal communica- According to the International Union for the tion). Abiotic factors (such as drought) are Conservation of Nature (IUCN) Red list cri- also becoming an issue, because researchers teria, M. beccarii var. beccari is endangered and growers are looking to grow banana (Carré and Lusty, 2007). where the environment is less favourable for These endangered wild species could be the development of pests and diseases. carrying genes such as those that confer Consumer needs and nutritional value are resistance to Fusarium oxysporum f.sp. cubense becoming traits of increased interest as well. (Foc TR4; the fungus that causes Panama dis- For example, there are very encouraging ease), or genes that make plants more drought results for increasing pro-vitamin A content tolerant or encode for higher vitamin A con- across the Musa gene pool. However, incor- tent. So with the loss of genetic diversity we porating such traits into landraces is still chal- are losing potentially unique genes that may lenging, particularly in overcoming breeding confer traits of interest. What we need to do is constraints such as those due to polyploidy to increase productivity while at the same and parthenocarpy (fruit production without time maintaining adequate diversity and fertilization of ovules) in edible (seedless) cul- assuring sustainable production systems. tivars. In addition, it takes several years to Consequently, there is a need to enlarge the obtain hybrids. genetic basis of Musa diversity and to capture There is a common denominator for all all the existing diversity before it disappears. these challenges, and that is the use of genetic However, the safeguarding of Musa genetic diversity in banana and plantain improve- resources and the maximum use of its poten- ment programmes. This will ensure contribu- tial are slowed down by a lack of global col- tions to the sustainability of agricultural laboration in the sharing of resources and the production systems, the safeguarding of the exchange of technologies and information. crop against pests and diseases, and increased resilience under adverse environmental conditions. The use of genetic diversity can also bring different nutritional benefits to poor 28.2 MusaNet: the Global Musa populations and offer a broader range of pro- Genetic Resources Network cessing and marketing opportunities. A comprehensive understanding of the The long-term security of Musa genetic existing Musa diversity, and its potential uses, resources requires the mobilization of all is therefore crucial, not only for gene bank stakeholders to ensure a more efficient and curators, molecular biologists, breeders, phy- effective global system of conservation and topathologists and other Musa researchers, use. A global Musa genetic resources network, but also for the rural households most MusaNet, has recently been launched, coor- dependent on the crop for their food and dinated by Bioversity International. Musa- income. It is thus the responsibility of those Net is providing a collaborative framework working with genetic resources to make this to support the implementation of the Global knowledge accessible. Strategy for the Conservation and Use of Genetic diversity is being lost at a very Musa Genetic Resources (in preparation). rapid rate and we need to act quickly. MusaNet not only strives to improve the Several reports reveal this loss. In Borneo, conservation and safe dissemination of for example, certain species of Musa wild Musa genetic resources, it also seeks to fill relatives, such as M. azizii (Häkkinen, 2005), the gaps in knowledge of the Musa gene M. beccarii var. beccari (Häkkinen et al., 2005, pool through increased characterization and 2007), M. lawitiensis (Häkkinen, 2006) and multi-locational evaluation efforts. It pro- M. monticola (Argent, 2000) (Plate 24) were vides accessible diversity to farmers, thereby found only on one site. It is possible that allowing them more options to grow bananas this unique population will disappear as a and plantains. Facilitating Wider Use of Musa Genetic Resources 237

A first global strategy for the conserva- The wild and cultivated diversity of tion of banana and plantain was developed Musa is at its richest in the Asia-Pacific region, in 2005 and 2006. This focused on the con- as its primary centre of diversity is in South- servation of existing diversity in the differ- east Asia. East Africa is the second centre of ent collections (international, regional and diversity. Little diversity is found in Latin national). The main driver for developing America, apart from few mutations arising in such a strategy was the then newly estab- a vegetatively propagated crop. The goal of lished Global Crop Diversity Trust (the MusaNet is to build upon existing strengths Trust), a public–private partnership raising in the global, regional and national collec- funds to establish an endowment fund that tions by bringing people together to opti- will provide complete and continuous fund- mize the effort to conserve, add value to and ing for key crop collections in perpetuity. promote the use and safe distribution of a In line with the ‘International Treaty on wide range of Musa genetic diversity as the Plant Genetic Resources for Food and Agri- foundation for further breeding or direct use culture’ and the ‘Global Plan of Action for by farmers. The networked structure of the Conservation and Sustainable Utilization MusaNet (Plate 26) consists of a Coordinating of Plant Genetic Resources’, the Trust’s goal Secretariat, an Expert Committee and a num- is to advance an efficient and sustainable ber of Thematic Groups in which experts dis- global system of ex situ conservation by pro- cuss and propose solutions in critical thematic moting the rescue, understanding, use and areas of Musa genetic resources, namely: long-term conservation of valuable plant genetic resources. So the focus of the 2006 • Thematic Group 1: Genetic diversity gap strategy was to bring urgent and critical filling, taxonomy and characterization assistance to unique germplasm and ensure • Thematic Group 2: Germplasm evalua- its sustainable long-term conservation for use. tion and uses The first MusaNet Strategic Meeting was • Thematic Group 3: Germplasm informa- held in Montpellier, France, from 28 February tion and documentation to 3 March 2011. The community of key actors • Thematic Group 4: Conservation and stakeholders was brought together to partnership agree on and review the 2006 Global Strategy for the Conservation and Use of Musa Genetic The strategic framework of MusaNet is Resources, its implementation to date and provided by the Global Strategy for the incentives for participation, and to establish Conservation and Use of Musa Genetic MusaNet as the mechanism to ensure the Resources. Critical links with the four regional efficient coordination and implementation research networks (Banana Asia-Pacific Net- of the strategy and stimulate the involvement work (BAPNET); Banana Research Network for of partners. A total of 47 participants attended East and Southern Africa (BARNESA); Musa the meeting, representing different stake- Network for Latin America and the Caribbean holder groups, from 21 different institutes, (MUSALAC) and the Banana Research located in 15 countries. Participants also Network for West and Central Africa (Innovate represented different areas of expertise, such Plantain)) and with other key initiatives, such as as breeding and crop improvement (8 partici- the Platform for sharing Musa information and pants); germplasm information and docu- knowledge (ProMusa) and the Global Musa mentation (9); molecular biology and Genomics Consortium (GMGC), are ensured genomics (9); phytopathology and posthar- by their representation on the MusaNet Expert vest (11); taxonomy and characterization Committee (Plate 26). It is through partner- (morphological and molecular) (8); and ships with the regional networks that demon- policy issues (3). In addition, 13 Musa genetic stration experiments at the farm level can be resources collections were represented, established – like those that already exist in although we estimate that there are around certain Asian countries within the framework 60 major Musa collections around the world of National Repository, Multiplication and (Plate 25). Dissemination Centres (NRMDCs). 238 N. Roux et al.

The Expert Committee is composed of is ready to donate 16 samples of the following 11 members: improved plant material to the Bioversity International Transit • The MusaNet coordinator Centre (ITC), Belgium as announced • The Chairs of the four Thematic Groups at the 2011 ProMusa symposium • A representative of each of the four (Edson Perito, San Salvador, 2011, regional networks personal communication). • The Coordinator of ProMusa • Thematic Group 3 on information: • The Chair of the Global Musa Genomics To raise awareness with key partners Consortium (GMGC) of the importance of conserving, The Expert Committee guides the overall documenting, exchanging and planning of MusaNet priorities and activities sharing the benefits of using Musa supporting the implementation of the Global genetic resources. The network will Musa Strategy. It reviews work plans and pro- invest further in improving the level vides overall technical and policy guidance to of documentation of accessions held the operations of MusaNet. The Thematic in national collections. The goal is to Groups decide on priorities for collective have each Musa collection sharing actions. They formulate project proposals for information through the global collaborative activities in the thematic areas. Musa Germplasm Information The objective of each Thematic Group and System (MGIS). At the moment, their priority actions are currently: MGIS includes information on only 22 of the estimated 60 collections • Thematic Group 1 on diversity: gap worldwide (Plate 25). filling This group started to use minimum To ensure the secured conservation sets of photographs to more rapidly of the entire Musa gene pool by recognize accessions (Plate 28). These assessing the diversity conserved photographs allow the comparison and filling gaps, with an emphasis of plant material and its behaviour in on threatened material. different regions (Plate 27). One of the priority actions for this • Thematic Group 4 on conservation: group is to collect new plant material Strengthen the capacity of partners in the following areas: Indonesia, to undertake the cost-effective long- the Philippines and the east coast of term conservation and management Africa. of germplasm collections and • Thematic Group 2 on evaluation facilitate access to useful Musa To enhance the value of Musa genetic genetic resources in improvement resources for breeding, through programmes and by other users. effective collaborative characteriza- The two priority actions for this tion, evaluation and pre-breeding group are to be able to order clean efforts. in vitro Musa germplasm from the One of the priority actions is the ITC, Belgium through the MusaNet increased use and capturing of data web site (http://www.musanet.org/) on biotic and abiotic descriptors in and to update the technical the Musa Germplasm Information guidelines on the safe movement of System (MGIS) database (Plate 27). germplasm. This group is also considering implementing a multi-site evalua- MusaNet members are from a wide tion of material coming out from range of Musa genetic resources interests. breeding programmes for testing Membership is on an expertise basis. The useful and interesting plant material network encourages its members to meet through multi-location experiments. regularly during symposia and conferences. The Brazilian breeding programme MusaNet has a new web site to share with Facilitating Wider Use of Musa Genetic Resources 239

the Thematic Groups and develop projects wider and more effective knowledge shar- using workspaces available in each group ing for this purpose. (Plate 29). Global collaboration for the efficient and effective conservation and use of Musa genetic resources requires the full support 28.3 Conclusion and participation from a number of key partners and networks. At the heart of the strat- A wider use of available Musa (banana and egy are the institutes managing Musa plantains) diversity would boost rural live- diversity and the users. A number of net- lihoods and food security. A comprehen- works and global initiatives direct the sup- sive understanding of such diversity and of port of the implementation of the strategy. its potential uses is crucial to all stake- These include the Global Musa Genomics holders within the Musa value chain. Such Consortium (GMGC), the 4 thematic groups knowledge needs to be made accessible to of MusaNet, the three regional Musa net- stakeholders. A germplasm information works, the ProMusa researcher network, and management system and stakeholder net- ITC as well as the facility of the Musa works provide a global platform to assure Germplasm Information System (MGIS).

References

Argent, G. (2000) Two interesting wild Musa species (Musaceae) from Sabah, Malaysia. Garden’s Bulletin Singapore 52, 203–210. Carré, J. and Lusty, C. (2007) Wild relatives of banana under threat. Geneflow ’07. Bioversity International, Rome, p.55. FAOSTAT (2009) Online statistical database. Food and Agriculture Organization of the United Nations, Rome. Available at: http://faostat.fao.org/ (accessed 3 May 2013). Häkkinen, M. (2005) Musa azizii, a new Musa species (Musaceae) from northern Borneo. Acta Phytotaxonomica et Geobotanica 56, 27–31. Häkkinen, M. (2006) Musa lawitiensis Nasution & Supard. (Musaceae) and its intraspecific taxa in Borneo. Adansonia sér. 3, 28, 55–65. Häkkinen, M., Suleiman, M. and Gisil, J. (2005) Musa beccarii (Musaceae) varieties in Sabah, Northern Borneo. Acta Phytotaxonomica et Geobotanica 56, 135–140. Häkkinen, M., Teo, C.H. and Othman, Y. (2007) Genome constitution for Musa beccarii N.W. Simmonds (Musaceae) varieties. Acta Phytotaxonomica Sinica 45, 69–74. This page intentionally left blank Index

Agro-ecological zones, Burundi HSD 40 agroforestry see Agroforestry hybrid cultivar ‘FHIA-17’ 43 annual crops 176 linear mixed-effects modelling 40 biotic constraints 176 macropropagation technology 44–45 CIALCA 177 model selection 40 de-suckering see De-suckering origin, classification and use, cultivars 38, 39 diagnostic survey, Musa 177 performance at flowering 41 disbudding see Disbudding performance at harvest 41–43 Musa crop 176 plant and ratoon crop cycles 40 old banana leaves production constraints 38 adult banana weevils 181 randomized design 39 de-trashing 180, 182 site location, altitude transmission, disease 181 and annual rainfall 38, 39 pseudostems see Pseudostems soil characteristics, sites 38, 39 selection, planting material statistical analysis 40 BBTV and BSV 177 tissue culture plantlets 39 Musa planting 177, 178 Akaike Information Criteria (AIC) 40 suckers 177 Arbuscular mycorrhizal fungi (AMF) transmission, pests and diseases 177, 178 ANOVA 85 Xanthomonas wilt 179 antagonistic relationships 80 soil fertility and drought 176 application at the nursery stage 90 SPSS statistics software package 177 application, genotypes 80 weed management 187 banana systems 84 Agroforestry biological material 73 agricultural zones 179 biological properties, soils 79 banana leaves and canopy 179 cation exchange capacity and nutrient Musa farmers 179 supply 79 South Kivu 180 colonization frequency 79 Agronomic evaluation, dessert banana cultivars data assessment procedures 74–75 agricultural practices 44 effects, plant growth 91 agronomic performance 38 growth and nutrition of banana cultivars 83 de-suckering and de-leafing 39 hardening phase 84 disease resistance traits 38 inoculated TC banana plantlets 86–90 false decapitation technique 45 inoculation process 74 GPS 38 micropropagated banana 83–84

241 242 Index

Arbuscular mycorrhizal fungi (AMF) (continued) GenStat software package 160 MSI 86 intercropping 159 mycorrhizal dependency 79 landraces/hybrids 164 mycorrhization 83 levels, banana leaf pruning 159 natural population 79 banana mat nutritional limitations 80 de-suckered treatments 105 plant care and experimental design 74 disease incubation period and time 106, 107 population density 75 EAHB 106 root characteristics, treatments 77, 78 farmers’ fields 106 root colonization, soils and genotype 75–77 Mangin layer 105 root development 75 Xanthomonas campestris versus root resources 80 musacearum 104, 106 root system 80 yellowing and wilting 106 Rwandan banana plantations 84 Banana productivity and production, shoot growth characteristics, treatments 77, 78 Central Uganda soil fertility, pasteurized and non-pasteurized agroforestry approach 155 soils 75 animal and manure production 151 soil management 72 animal raising 151 soil pasteurization and inoculation 77 asset-poor rural households 156 soil properties 84, 85 chemical fertilizers 151 soil type and genotype 77 descriptive statistics 152 standard fertilizer regimes 83 farmer and field sampling 155–156 statistical data analysis 75 farm income 151 trapping and bulking processes 84 field sampling tool 152 fodder sources, livestock 154 household resources 153 banana bunchy top disease (BBTD) land and soil 151 characteristic disease symptoms 212 linkages, trees and livestock 151, 152 DNA capture kits 111 manure and mulch 154–155 lowlands 59 on-farm planting 151 Banana bunchy top virus (BBTV) 176, 177, 217 participatory technology generation 156 Banana cropping systems, Great Lakes Region tree canopy 152 agrarian systems 173 and trees, farm 153–154 agricultural policy and extension 167 wealth-based groups 152 agro-ecological Banana sampling and collection and economic potentialities 173 carotenoids 28 and socio-economic conditions 167 cassava farming 28 farm management practices 171 clustering and spatial arrangement 27 industrial agricultural systems 166 conservation and identification, genotypes 23 medium farm size 169 cooking types 25 plantations 168 crop improvement 22 plant density and mulching sources 169 farm clusters, Bundibugyo district 25, 26 qualitative component 168 frequency of occurrence, farm clusters 24, 25 quantitative component genetic resources 23 data collection 168 germplasm accessions 25, 26 economic performance 168 GPS 24 farming system 168 local and exotic germplasm 22–23 socio-economic classification 168 local genotype composition 28–29 self-mulching and weed residue 169 Mbarara field genebank 23 smallholder farming systems and land minimum set, descriptors 26, 27 productivity 173 Musa production constraints 24 types 170 national germplasm 24 Banana–legume intercropping systems principal component analysis 24 ACCUPAR photometer probe 160 pseudostem, pigmentation and colour 29 banana growth traits 162–164 respondent-driven snowball sampling 23 crop production 159 sampling design, data collection and sample data collection 160 collection 23, 24 Index 243

snowball sampling technique 23 symptomatic, asymptomatic and healthy type, flour 25 banana plant materials 95 Xanthomonas 28 symptom-based diagnosis 93 Banana streak virus (BSV) 177 visibly healthy plants 120, 121 Banana Xanthomonas Wilt (BXW) working dilution, ELISA tests 96–97 adherence, cultural practices 119 BBTV see banana bunchy top virus (BBTV) antibody sensitivity 97 Beer banana farming systems, Uganda antibody specificity 95–96 alcohol consumption 192 anti-X. c. pv. musacearum polyclonal and brewers see Brewers antibodies 95 brewing type 191 asymptomatic samples 99 characterization 194 bacterial cultures 94 commercialisation, artisanal CCA 94 beverages 199–200 consecutive infections, mat 122 constraints and opportunities control measures 122 opportunities 198–199 control package 120 system under pressure 198 cultural control options 121 consumers 197 DAC-ELISA 95 EAHB AAA cultivars 191 disease management practices 121 and growers 199 disease transmission and epidemiology 117 growers and brewers 199 early detection and destruction, Kayinja 191 diseased mats 120 matooke 191 early disbudding 118 methodology 192–193 ELISA and molecular methods 97 products 193–194 flower infection 117 sales and trade free-ranging small-ruminants 123 kampala bars 196–197 garden tools 118 rural bars 196 inflorescence symptoms 117 sales 196 land preparation activities 121, 123 Brewers legume intercropping 118 beer banana producer, MAbs 97 Kiboga District 195 morphological and molecular detection farming population 194 methods 99 household 195 musacearum diagnostics 97 income and prices 195–196 non-adherence 121 ‘Kayinja’ bananas 194 PAbs 97 land size 195 PCR-based diagnostic assays 93 BSV see Banana streak virus (BSV) plant samples 94 production, polyclonal antibodies 94 proportion, asymptomatic mats 120 CCA see cellobiose cephalexin agar (CCA) rainfall distribution in South Kivu 121, 122 cellobiose cephalexin agar (CCA) 94 Rwanda Coffee awareness, symptoms 134 production and quality 145 characterization 131 smallholder farming systems 145 control methods, awareness and Coffee–banana intercropping use 135–136 agronomic productivity 145 descriptive statistics 133 annual yield value 146 direct field observations 132 Arabica–banana intercropped field 146 disease incidences 133 banana cultivars 148 disease management programmes 132 coffee-related activities 144 GPS 132 description 144 infection, districts 133 food insecurity and insecurity 148 modes of spread, awareness 134–135 grazing land 147 National Task Force 132 in situ mulching material 146 proportion, sites/farms 133 income security 148 reclassification, pathogen 132 monocropped and intercropped 145 symptoms 133, 134 national programmes and researches 149 244 Index

Coffee–banana intercropping (continued) Disbudding 182 pseudostems 147 DNA sampling kits soil fertility management 149 bacterial/viral DNA 113, 114 Communication approaches diagnostic method 114 heterogeneity 227 disease control 110 mobile phone system 228 disease surveillance 114 print and mass media 227–228 FTA card method 110 publications 228–229 high-integrity DNA 110 seminars and workshops 228 IPM 110 training, trainers 228 LFDs 111 Communication channels molecular detection 112 community-centred communication 230 PCR 110 description 230 PhytoPASS 111 strengths and weaknesses 230, 232 population dynamics, pathogen 110 Consortium for Improving Agriculture- preparation of samples for based Livelihoods in Central Africa PCR detection 111 (CIALCA) 44, 177 sampling methods 111 symptomatic and asymptomatic plant samples 114 De-leafed and de-suckered plants X. c. pv. musacearum and BBTV 112–113 banana mat see Banana mat Xanthomonas wilt and incubation period 103–105 EAHB see East African highland bananas (EAHB) Democratic Republic of Congo (DRC) East African highland bananas (EAHB) BXW management see Banana adoption, control strategies 34 Xanthomonas wilt (BXW) banana production zones 35 germplasm diversity see Germplasm Black Sigatoka 30–31 diversity, Musa control measures 31 plantain collection and morphological conventional breeding 31 characterization see Plantain cooking banana 206 cultivation and diversity data collection and analysis 31–32 De-suckering 180 design programmes 34 Diet and nutrition, Musa-dependent households East African highland bananas 32, 33 animal products 203 food qualities 33, 34 dietary practices see Dietary practices household consumption 208 DR Congo 203 ‘Nshikazi’ cultivar 207 FAO guidelines 203 sampling procedure 31 Fisher’s formula 203 in South Kivu 206 malnutrition 203 traditional cooking banana cultivars 34 regression analysis 203 traits, farmers 33, 34 socio-economic aspects 204 verification Dietary practices consumer qualities 35 bananas and plantains, consumption patterns food colour and aroma 33, 34 beer banana cultivars 207 nutritional value, product 35 children/households 207 East African highlands (EAH) consumption, cooking 206, 207 cropping systems 73 EAHB 206 landscape and soil conservation 72 food and nutrient security 208 root system 73 households, Bukavu 206, 207 soil type diversity 73 market value and farmers 206 East and Central African (ECA) region ‘Nshikazi’ and ‘Vulambya’ 207 bacterial wilt diseases 225 consumption patterns, food groups 204–205 communication approaches see HDDS 205–206 Communication approaches direct antigen coating enzyme-linked communication channels see immunosorbent assay (DAC-ELISA) Communication channels enzyme-labelled antibody conjugate 94 description 224–225 morphological and molecular diagnostics 95 diseased plants destruction 225 Index 245

PDC see Participatory development measurements, inflorescence 54, 55 communication (PDC) plantain planting material 49 socio-economic problems 225 plantain suckering 51, 52 Xanthomonas Wilt see Xanthomonas Wilt plant height and time 54, 55 ECA see East and Central African (ECA) region plant spacing 49 enzyme-linked immunosorbent assay (ELISA) pseudostem circumference, plant anti-Xcm PAbs 95 height 50–51 X. c. pv. musacearum 96–97 rainfall patterns (seasons) 49 EPPO see European and Mediterranean Plant soil characteristics 53, 54 Protection Organization (EPPO) temperature and rainfall data, European and Mediterranean Plant Protection Mutwanga 51, 53 Organization (EPPO) 214 volcanic-derived soils 49

Farmer field schools (FFS) 229–230 HDDS see Household dietary diversity score (HDDS) Farmer-preferred traits, Uganda see East African honestly significant difference (HSD) 40 highland bananas (EAHB) Household dietary diversity score farm management practices 168, 171 (HDDS) 205–206 FFS see Farmer field schools (FFS) Household resources Field techniques analysis 153 classification 70 description 153 financial capability 70 HSD see honestly significant difference (HSD) seed production-oriented farmers 70 soil-borne contaminants 70 Fisher’s Exact test 133 IITA see International Institute of Tropical Agriculture (IITA) industrial agricultural systems 166 General linear model (GLM) 85 inoculated TC banana plantlets Germplasm diversity, Musa field performance 89–90 agricultural intensification 19 nursery studies see Nursery studies, agroecologies 19 inoculated TC banana plantlets cultivar richness 11–14 Integrated pest management (IPM) 110 distribution, use 15, 16 International Institute of Tropical Agriculture (IITA) farming systems 10 planting material 67–68 food security 19 three-tier multiplication scheme 70 GenStat 11 International Plant Diagnostic Network Gini–Simpson index 11, 14–15 (IPDN) 214 nomenclature, cultivars 9 International Transit Centre (ITC) 39 on-farm conservation 19 International Union for the Conservation of soil erosion levels 9 Nature (IUCN) 236 synonym names, cultivars 15, 17–19 IPDN see International Plant Diagnostic Gini–Simpson index Network (IPDN) distribution, cultivars 14 IPM see Integrated pest management (IPM) genetic erosion 14 IUCN see International Union for the Conservation management strategy 14–15 of Nature (IUCN) Musa cultivars, germplasm survey 11, 14 GLM see General linear model (GLM) Global Musa Genomics Consortium (GMGC) 238 kernel based matching (KLM) 222 Global positioning system (GPS) 24, 38, 132 KLM see kernel based matching (KLM) GMGC see Global Musa Genomics Consortium (GMGC) GPS see Global positioning system (GPS) lateral flow devices (LFDs) 111 Growth and yield, plantain cultivars Legume bunch size and suckering behaviour 56 crop cycle 160–161 growth traits 50 disease severity 160 insect vector transmission 50 dry matter and grain yield 161–162 mean first crop cycle duration 50, 52 LFDs see lateral flow devices (LFDs) 246 Index

MAbs see Monoclonal antibodies (MAbs) livelihoods and food security 239 Macropropagation technology nutritional benefits 236 agroecologies 60 pests and diseases 236 ANOVA 60 polyploidy and parthenocarpy 236 banana planting material type 67 Musa Germplasm Information banana ‘seed systems’ model 68 System (MGIS) 238 BBTD 59 MusaNet CIALCA 70 breeding and crop improvement 237 cost-effective measures 63 expert committee 238 diseases and pests 69 Global Crop Diversity Trust 237 effect, Musa cultivar 60, 61 GMGC 238 field techniques 68, 70 MGIS 238 food security 58 mobilization, stakeholders 236 GenStat software package 60 networked structure 237 healthy planting material 66, 67, 71 Strategic Meeting 237 horticultural multiplication 59 wild and cultivated diversity 237 humid chamber type effect 61, 62 Musa spp. macropropagation see IITA 67–68 Macropropagation technology initiation substrate effect 61, 62 Mycorrhizal soil infectivity (MSI) test 86 labour requirements 69 low plantlet survival rates 69 NGOs 68 NARO see National Agricultural Research oil-borne pathogens 67 Organisation (NARO) paring and hot/boiling water National Agricultural Research Organisation treatment 69 (NARO) 102, 107 poor sprouting 69 National Museums of Kenya (NMK) 85 premature rotting of corms 69 nearest neighbour matching (NNM) propagators 68 adopters and non-adopters 218 prototype macropropagation 63 and KBM matching methods 220 random and uncontrolled exchange 59 NGOs see non-government randomized block design 60 organizations (NGOs) reduced soil fertility 59 NMK see National Museums of secondary scarification, shoots 60 Kenya (NMK) shoot production data 63 NNM see nearest neighbour small-and medium-scale enterprises 68 matching (NNM) sterilization of initiation media 64 non-government organizations (NGOs) 10 substrate source and type 70 Nursery studies, inoculated three-tier multiplication scheme 70 TC banana plantlets tissue-cultured planting material 71 growth response to AMF 87 tissue culture plantlets 71 LSA 87 variety mix-up 70 ‘Mpologoma’ and warmer climate 60 ‘Kamaramasenge’ 87, 88 MGIS see Musa Germplasm Information mycorrhizal colonization 86–87 System (MGIS) Monoclonal antibodies (MAbs) 97 Musa cultivar richness Participatory development biotic and abiotic constraints 11 communication (PDC) genome groups 11–13 community structures 230 germplasm survey 11, 14 disease management strategies 229 Musa genetic resources empowerment, stakeholders 229 adverse environmental conditions 236 farmer exchange visits 230 agricultural production systems 235 and FFS see Farmer field schools (FFS) banana cultivation 235 HIV/AIDS campaigns 229 germplasm information 239 PDC see Participatory development global collaboration 239 communication (PDC) intraspecific crop diversification 235 Plantain cultivation and diversity IUCN 236 ‘Ambulu’ (‘great banana’) 5 Index 247

civil war 2 TC see Tissue culture (TC) bananas, Burundi food security 2 Tissue culture (TC) bananas, Burundi forest cover 3, 5 adopters and non-adopters 222 ‘French’ plantain 5, 6 BBTD and BBTV 217 germplasm research 3 cash and food crop 216 Musa cultivars 3 data 219–220 name and clone set 3, 4 KLM, NNM and ATT 221, 222 plantain diversity 2 matching quality indicators 221, 222 political instability 2 model estimations 222 production systems 3 NNM and KBM matching methods 220 savannah-type ecology 4 non-parametric evaluation 217 social unrest 2 plantlets 217 Plant density 169, 180 propensity score 220 principal component analysis 24 propensity score distribution 220, 221 Propensity score matching (PSM) approach P-values 221 see Tissue culture (TC) small-scale commercial farming 217 Propping, banana plants technology choice and impact valuation banana bunch weight 183 adoption and non-adoption 217 cultivars 183–185 ATT 218 Musa plants 183, 184 average treatment effect 218 proportion, farmers 183, 184 binary indicator 218 pseudostems and bunch sizes 184 organic and inorganic fertilizer 218 Pseudostems PSM 218 description 185 harvested 185, 186 recycling, nutrients 185 Ugandan National Banana Research survey sites 185 Programme 31

RAB see Rwandan Agricultural Board (RAB) Weed management 187 Regional surveillance, banana diseases disease epidemics 213 farming systems and pathogen Xanthomonas campestris pv. musacearum evolution 213 banana bacterial wilts 102 field-based observations 213 cylinder and cortex 103 IPDN and EPPO 214 de-leafed and de-suckered plants see laboratory-based De-leafed and de-suckered plants diagnostic methods 213 description 102 survey methods distilled sterile water 103 BBTD and BBTV 211 EAHB cultivars 102 functioning disease surveillance ELISA see Banana Xanthomonas network 211 wilt (BXW) GIS mapping 212–213 GenStat software 103 GPS units 211 leaf sheath samples 103 national and regional communication molecular diagnostics see DNA pathways 211 sampling kits National Banana Research NARO 102 Programme 212 ‘Pisang Awak’ plants 102 pathogen DNA 212 treatments 103 PCR-based diagnosis 212 wilt incidence and incubation period 103 Xanthomonas wilt 212 Xanthomonas wilt of banana Rwandan Agricultural Board (RAB) 10 asymptomatic lateral shoots 139 asymptomatic planting material 140 asymptomatic suckers per SAS see Statistical Analysis System (SAS) cultivar 139–140 snowball sampling technique 23 banana plants, two cultivars 127, 128 Statistical Analysis System (SAS) 133 biophysical conditions 127 248 Index

Xanthomonas wilt of banana (continued) management 226–227 control packages 142 mother plant death 225 cultivar effect, disease incidence 128, 129 on-farm experiment 126 diagnosis 225–226 on-farm experiments 139 diseased plants 140 planting materials and contaminated disease-free zone 139 garden tools 139 disease incidence 127 regular weeding 140 disease symptoms 127–128 small-scale banana farming systems 139 experimental fields 140 sources, inoculum 127, 140 garden tools 126 superficial hand weeding 140–141 initial disease incidence 139 transmission 226 initial mat uprooting 141 Ugandan agroecological conditions 129 insect vectors 139 Xanthomonas campestris 225