African Phytosanitary Journal

Volume 2, Issue 1 November, 2020

EDITORIAL MANAGEMENT Managing Editor Prof. Theophilus M. Mutui Managing Director-KEPHIS Editor in Chief Dr. Isaac Macharia Editorial Team Kenya Plant Health Inspectorate Service (KEPHIS) Kenya Agricultural and Livestock Research Organization (KALRO) University of Nairobi (UoN) Kenyatta University (KU) Masinde Muliro University of Science and Technology (MMUST) Centre for Agriculture and Bioscience International (CABI) Editorial Secretariat Dr. Isaac Macharia Mr. Joseph Kigamwa Ms. Pamela Kipyab Dr. Mary Guantai Dr. Moses Oyier Dr. Alexander Muvea Dr. Benard Mukoye Mr. Ivan Obare

Mobile: +254709891000

Kenya Plant Health Inspectorate Service (KEPHIS)

P.O.Box 49592-00100

Nairobi, Kenya

Email: [email protected] , [email protected]

Foreword

The African Phytosanitary Journal is a peer refereed academic journal which is one of its kind. It provides a platform to inform the stakeholders involved in trade in agricultural products. This journal provides a clear understanding of phytosanitary issues in Africa and beyond. Subsequently, it provides a platform for the stakeholders to stay informed of the current and emerging phytosanitary issues. Research Institutes, National Plant Protection Organizations (NPPOs), Universities and industry constantly conduct research and come up with innovations and discoveries that affect plant health in one way or another yet the findings are not disseminated to the intended consumers in time.

With increased globalization, there is imminent increase in trade involving plant and animal products. It is prudent that this trade be conducted with materials free of contaminants. The regulatory protocols developed to actualize this are science based and are in line with sanitary and phytosanitary requirements. The stakeholders involved in this line of trade need to be updated regularly on the requirements inorder to facilitate their activities. Cognizant of this fact, the African Phytosanitary Journal provides a platform for research scientists, academia and industry to share their experiences and innovations. This is an open access journal with a wide scope in sanitary and phytosanitary issues. This issue has focused on pest management, pest surveillance, pest risk analysis, emerging technologies, pest identification and analysis.

The mission of this journal is to foster a deeper understanding of phytosanitary issues in Africa and provide a basis for their management. I would like to take this opportunity to thank the team that worked tirelessly on this journal and made the release of this issue possible. Lots of gratitude to the editorial board, the reviewers and the authors for their time and energy spent towards the production of this journal.

Dr. Isaac Macharia Editor in Chief

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Scope of the journal This journal has been developed to bridge the knowledge and information gap in the following thematic areas: • Pest surveillance • Pest reporting • Phytosanitary measures • Pest Risk Analysis • Pest identification and analysis • Food safety • Quarantine and Biosecurity • Phytosanitary policy and regulation • Phytosanitary treatment • Emerging technologies • Biological agents • Pest Management • Agricultural Chemistry • Emerging phytosanitary issues • Biosafety • Phytosanitary issues on trade • Other relevant phytosanitary issues

Table of Contents

EDITORIAL MANAGEMENT ...... i

Foreword ...... iii

Scope of the journal ...... iv

Table of Contents ...... v

Status of Maize Lethal Necrosis Disease in Zambia...... 1

The Effect of Seed Source and Post-harvest Practices on Quality of Soybean (Glycine max) Seeds in Busia County ...... 17

Abundance and Diversity of Frugivorous Fruit Flies in Kandara, Murang’a County, Kenya ...... 41

Next generation sequencing as a tool in modern pest risk analysis: a case study of groundnuts (Arachis hypogaea) as a potential host of new viruses in western Kenya ...... 51

Maize Head Smut: Pathogenesis, Epidemiology, and Management Options ...... 63

New scale insect country records for Kenya (Hemiptera: Coccomorpha) from old samples in insect collections ...... 72

Pest Incursions Pose a Serious Threat To Food Security and the Kenyan Economy ...... 105

Status of Maize Lethal Necrosis Disease in Zambia Chomba, M. D*., Msiska, K. K., Abass M. S., Mudenda, M., Mukuwa, P.S.C. Zambia Agriculture Research Institute, Plant Quarantine and Phytosanitary Service P/B, 7, Chilanga, Zambia. *Corresponding Author: Doreen Malekano Chomba, Email: [email protected]

Abstract

Maize is a staple food in Zambia and contributes immensely to food security for smallholder farmers. Disease outbreaks such as Maize Lethal Necrosis Disease (MLND) can be a key constraint to maize production. This disease is caused by synergistic co-infection with Maize Chlorotic Mottle Virus (MCMV) and any virus from the family Potyviridae, particularly, Sugarcane Mosaic Virus (SCMV), Maize Dwarf Mosaic Virus (MDMV) or Wheat Streak Mosaic Virus (WSMV). In 2011, an outbreak of MLND affecting almost all of the currently grown commercial varieties posed a challenge to maize production in Kenya and it has since been reported in DR Congo, Ethiopia, Kenya, Rwanda, Tanzania, and Uganda causing yield losses of up to 100%. Despite MLND having been reported in some neighboring countries, there is no information on the status of the disease in Zambia. Additionally, there is a lot of grain and seed trade between Zambia and other countries among which MLND has been reported. The aim of this study was to establish: (a) the status of MCMV; (b) agricultural practices used by farmers and (c) insect vectors associated with MLND. A survey was conducted in nine (9) provinces of Zambia during 2014/2015 and 2015/ 2016 cropping seasons. Farmers’ maize fields were sampled at every five to ten- kilometer interval and tested using rapid diagnostic kits capable of detecting MCMV. Four hundred and nineteen samples collected all tested negative for MCMV. Zambian Agricultural Research Institute (ZARI), with all stakeholders in the maize value chain should continue implementing measures aimed at preventing the introduction of MLND in Zambia.

Key words: Survey, MLND, Losses, food security

INTRODUCTION farmers accounted for 89% of the total Maize (Zea mays L.) is one of the production over this period. principal cereal crops in Sub-Saharan In terms of trade, Zambia has been a Africa (SSA) and is largely produced by hub of seed and grain exports to her smallholder farmers over 35 million neighboring countries. A total of hectares with an estimated production 120,000 MT of seed maize was quantity of over 70 million metric tons exported within the Southern African of grain (Boddupalli et al., 2020). The Development Community (SADC) crop is critical to food security in SSA; region and COMESA member countries Eastern and Southern Africa uses 85% (ACTESA, 2015), implying that maize of the maize produced as food, while has a significant contribution to the Africa as a whole uses 95% as food Zambia’s Gross Domestic Product (Shiferaw et al., 2011). Maize is equally (GDP) and thereby to the National a very important food crop in Zambia economy. and according to (Chapoto et al., 2010) the average consumption of maize Although maize is widely grown, it is grain in Zambia has been estimated at faced with several biotic constraints 133 kg per year making it the most such as weeds, pathogens and insect popular food crop. It is cultivated in all pests thereby affecting its productivity the provinces and its production is (Oerke, 2006). In September 2011, a dominated by small scale farmers who high incidence of a new maize disease constitute an important and invaluable called Maize Lethal Necrosis Disease component of the Zambian economy (MLND) was reported at lower (Chiona et al., 2014). According to the elevations (1,900 m a.s.l) in the Longisa analysis of this study regarding the division of Bomet County, Southern Rift trend of maize production based on the Valley in Kenya. Since then, the disease crop forecasting survey estimates made has spread to many countries of East available by the national Central Africa rapidly due to insufficient Statistical Office (CSO) for the period knowledge on how the disease should 2011 to 2015, the country produced a be managed (Mahuku et al., 2015). cumulative total of 14.37 million MT. MLND is caused by the synergistic co- Zambia’s small to medium holder infection of maize with Maize Chlorotic

Mottle Virus (MCMV) of the genus becoming an emerging threat in Africa Machlomovirus and any of the and Asia (Achon et al., 2017). In Kenya, Potyviruses such as: Maize Dwarf field losses for all commercial maize Mosaic Virus (MDMV), Sugarcane varieties were estimated at 30 to 100% Mosaic Virus (SCMV), and Wheat Streak depending on the stage of disease Mosaic Virus (WSMV) (Achon et al., onset and severity (Mahuku et al., 2017). In Eastern Africa, MLND was 2015). In 2012, MLND affected 77,000 found to have resulted from co- ha in Kenya, translating into an infection of maize with MCMV and estimated yield loss of 126 million MT SCMV, although MCMV alone appeared valued at U.S.$52 million (Wangai et to cause significant crop losses. SCMV al., 2012a; Mahuku et al., 2015). has been known to be distributed Further annual losses due to MLN were widely in Africa since the 1970s estimated at 0.5 million MT/year (22%) (Mahuku et al., 2015). Therefore, this or $187M in Kenya (De Groote et al., makes the detection of MCMV 2016). The transmission of MCMV important as it is the only single virus occurs through insect vectors, needed together with SCMV to cause mechanically, and also via seed at very MLND (Mahuku et al., 2015). The low rates of about 0.04% (Jensen et al., disease is naturally known to affect all 1991). This poses a challenge to detect varieties of maize resulting in chlorotic this virus to prevent its introduction, mottling of the leaves, severe stunting infection and transmission (Liu et al., and necrosis. This subsequently hinders 2015). Infected soil has also been the physiological processes of the plant shown to transmit the viruses that such as photosynthesis, chlorophyll cause MLN (Mahuku et al., 2015). formation as well as denaturing Weeds such as Bermudagrass enzymes necessary for the crop to (Cynodon dactylon) Napier grass produce. This further leads to low (Pennisetum purpureum) have been maize yields or plant death (Wangai et known to be hosts of viruses that al., 2012). MLND is an economically causes MLND. It is further reported that devastating disease in maize growing insects such as thrips, beetles and areas of the world and is currently aphids carry the viruses

from one plant to another in the field MATERIALS AND METHODS (Mahuku et al., 2015). Study Location Despite MLND being reported in some The surveys were conducted from of Zambia’s neighboring countries such 2014/2015 to 2015/2016 cropping as DR Congo and Tanzania, so far, no seasons and covered the following study has been carried out to establish provinces: Copperbelt, Muchinga its status in Zambia. In the light of this, Northern, Lusaka, Luapula, North- a survey was conducted from 2015 to Western, Southern, Central and 2016 in order to investigate and Eastern. Areas along the border establish if there was any occurrence of between Zambia, Tanzania and DR MLND. The objective of this study was Congo covering the Copperbelt, to determine: (1) the presence or Muchinga and Northern Provinces were absence of Maize Chlorotic Mottle Virus targeted in 2014/2015. The survey was (MCMV) in Zambia; (2) some of the later extended to include other agro cultural practices conducted by provinces covering Lusaka, Luapula, farmers which may predispose them to North-Western, Southern, Central and the attack of MLN in the study area in Eastern Provinces in the 2015/2016 an event of an outbreak; (3) the cropping season (Fig. 1). presence or absence of insect vectors and weeds known to be hosts of MLND causing viruses.

Figure 1: Map of Zambia showing areas surveyed.

2.2 Data collection using The global positioning system (GPS) questionnaires latitude, longitude and elevation points were also recorded to help with the The questionnaires used in the survey production of maps. were designed by the International Maize and Wheat Improvement Center The agro cultural practices were (CIMMYT) and adopted to be utilized collected by means of questionnaires. during the survey. The information Farmers were asked to whether they collected included: name and sex of practiced crop rotation, planted local farmer, location, type and source of varieties; and whether they used seed, planting date, field size, variety, recycled seed among other questions. stage of crop, crop rotation history, The farmer’s responses were recorded frequency of visits from extension on questionnaires. The information on agents, pesticides use, type of insects, agro cultural practices was collected type of diseases, symptoms and weeds. because, in countries were MLN has

been reported, research has shown that have a thorough examination of the crop rotation, use of certified seed are field (Muliokela, 1995). A total of six among interventions being used for plants were randomly selected and disease management. Therefore, such inspected for the identification of MLN information would be used by policy virus symptoms along each path within makers and extension staff to intensify the X pattern (Suresh and Mezzalama, the awareness on good agricultural 2016). practices that help to prevent the A total of six flag leaf samples per field disease. Similarly, insects and weeds were cut out using scissors previously such as thrips, aphids and beetles disinfected with bleach targeting both among others have been reported to be the symptomatic and non-symptomatic vectors that aid the transmission of plants for general virus related MLN causing viruses. Consequently, symptoms. Depending on the size of farmers would be advised on the the field the sampling was done as control methods for such pests. follows: for field of 5 ha one X pattern, 2.3 Field leaf sampling 5 to 20 ha two X pattern and over 20 Maize fields were inspected and ha six or more. According to the sampled for detection of MCMV CIMMYT MCMV detection protocol, it is between January and March of each recommended to test using flag leaves cropping season. The plants sampled because these leaves are more were of varying growth stages ranging succulent than the rest of the leaves, from flowering to the dough stages. and more importantly the immunostrips Samples were picked at an interval of are sensitive enough to detect the virus every five to ten (5-10) km distances during the surveillance. Tissue paper between maize fields depending on the towels were used to hold the leaves availability of maize fields in a particular when cutting in order to avoid area. contamination during sampling. Each of the six individual wrapped leaves were 2.4 Sample collection placed in individual paper bags with The survey team followed the X pattern uniquely identified barcodes placed on (Fig. 2) to sample the field crops in each sample. In order to avoid order to maximize coverage and to

6 contamination, the scissors were disinfected in between fields.

Figure 2: Schematic diagram on how sampling of plants was done.

Diagnostic procedure: Testing the and left for 10 to 15 minutes before leaves using the Immunostrips reading the results. Vector Pest Survey With clean gloves, coin size leaf pieces General vector pest surveillance was were cut off from each of the six leaf conducted in order to check for samples collected and placed in a small presence or absence of all vectors size zip lock bags containing 4 mls of associated with MLND such as aphids, extraction buffer before crashing the thrips and stem borers without leaves. One drop of extracted plant sap determining the numbers occurring per using a pipette was collected and host. Pests found were noted and placed in another small clean vial with samples submitted to the entomology three drops of extraction buffer added laboratory for identification. and mixed thoroughly. Thereafter, MCMV immunostrips was inserted into Surveillance of Maize Aphid a test bag on its end marked sample The upper leaves were examined from each plant and a total of 50 plants were

7 sampled per field. Both winged and Surveillance of weeds wingless aphids were collected and The field was checked for the presence preserved in 70% ethyl alcohol and later of weeds occurring using the weed submitted to the Entomology Laboratory identification book. Weed samples were for identification. collected and matched in line with the Surveillance of Maize Thrips descriptors outlined in the weed pocket Observations for the presence of thrips book and identified accordingly. This was done along the path of the X was done in order to check for the pattern on all the internal plant parts, as presence of weeds reported as hosts for well as in sheaths, under cob husks, on MLN causing viruses silk, between kernels, and in tassels, Results including individual spikelet. Plants were Table 1 below indicates results for a cut down, packed into sealed plastic total number of 419 samples obtained bags and transported to the laboratory, from the surveyed provinces of Zambia. where they were inspected under a Sampling sites per province ranged microscope. All the collected thrips were from 31 to 76. Muchinga Province had preserved in 70% alcohol and later the highest number of samples with 76 submitted to the Entomology Laboratory while southern province had the lowest. for identification. The provinces such as Lusaka, Surveillance of Maize Stem Borer Muchinga and Copperbelt had higher

The field was scanned for the presence samples tested because they relatively of the stem borers. All the infested have high interactions with countries plants were dissected and the larvae outside Zambia. Muchinga and found where collected. The collected Copperbelt share borders with Tanzania larvae were preserved in 70% alcohol and the Democratic Republic Congo, and later submitted to the Entomology respectively while Lusaka is the hub for Laboratory for identification. all grain and seed import and export activities. All samples collected and

tested for MCMV were negative.

Table 1: Table of results for rapid diagnostic tests during surveillance for 2014 to 2016.

SN Province No of fields Bulk AgriStrip Result surveyed MCMV (+/-)

1 Eastern 51 Negative 2 Central 33 Negative 3 Southern 31 Negative 4 Lusaka 73 Negative 5 Muchinga 76 Negative 6 Copperbelt 69 Negative 8 North -western 41 Negative 9 Northern & Luapula 45 Negative Total 419

All samples showed only one red line, implementing the agro-cultural which implied no presence of MLND in practices are shown in figure 3 below. all the samples tested. Two hundred and twelve farmers were planting local varieties while 164 Information obtained from the farmers were not practicing crop questionnaires. rotation with 85 using recycled seed. Results obtained from the questionnaires regarding farmers not

250 200 212 150 164 100 50 85 Numberfarmers of 0 Not practicing crop Planting local Use of recycled rotation varieties seed

Agro-cultural practices Figure 3: Number of farmers not implementing some agro cultural practices

Observed pests in farmer’s fields insect type present on plants were stalk The insect pests that are known to be borers followed by the combination of associated with MLND were observed in stalk borers and aphids. However, the farmer’s maize fields. Those many farmers’ fields (200 out of the observed were as follows: Aphids, 419) surveyed fields had no insects thrips, stalk borers and beetles, and the observed on plants. Generally, aphids weeds that may act as reservoir for the and beetles occurred on plants which virus: Bermudagrass (Cynodon were from vegetative to tasseling dactylon) and Napier grass stages while stalk borers and thrips (Pennisetum purpureum). In several were mostly observed on cases maize plants in the fields had physiologically matured ears and more than one type insect occurring as stems. shown in Figure 4. The most common

Frequency of insect types per farmer's field

Others 37 Thrips, Leaf beetles, Stalk borer 1 Thrips, Aphids, Stalk borer 1 Stalk borer 76 Leaf beetles, Stalk borer 12 Leaf beetles 5 46

Insect type Aphids, Stalk borer Aphids, Leaf beetles, Stalk borer 5 Aphids, Leaf beetles 1 Aphids 35 No insect present 200

0 50 100 150 200 250 No. of occurence of insect types

Figure 4: Frequency of insect types on maize plants in farmers’ fields

Discussion northern part in Arusha. The fact that in The survey findings revealed that the the same period of 2014, MLN was Maize Chlorotic Mottle Virus (MCMV) detected in two countries confirms its was absent. This implied that all the fast geographical spread. This confirms surveyed areas in Zambia were free the expressed concern in the report from Maize Lethal Necrosis (MLN). It is made by Isabirye and Rwomushana important for Zambia to maintain this (2016) that MLN has the potential to status if it is to continue as the hub of spread and devastate maize production seed and grain exports to the in Africa at a very fast rate. The neighboring countries. According to predictive model on MLN spread shows data on trade by ACTESA (2015) and that countries with the semi-arid and CSO/MAL (2015) Crop Forecast Survey sub humid tropical type of climate in respectively, Zambia has been leading Central and Eastern Africa such as in the export of seed and it has been Ethiopia, Tanzania, and DRC were at performing well with regards to seed risk of losing 662, 924 Km2, 625, 690 and grain production. km2 and 615,940 Km2 potential land of maize production respectively. From Since the first report in Kenya, in 2011, this information, Tanzania and DRC the MLN has spread tremendously fast being Zambia’s immediate neighboring to other parts of Africa as well. The countries implies, that the risk of MLN detection of MCMV and MLN in DRC and introduction to Zambia is very high. This Tanzania the closest neighbors and state of affairs demands for trading partners for Zambia is of strengthening surveillance and putting Concern. According to Lukanda (2014) in place other measures like creating MLND was detected in Kivu province in awareness to prevent further spread DRC in 2013 and the following year (Lukanda, 2014). (2014), it was detected on maize affecting both the local and hybrid The practice of growing maize on a varieties in two provinces of Tanzania yearly basis predisposes farmers to (Bini and Lubero) in and also in the incidences of crop diseases including

MLN. Planting the same crop on the (2015) suggests that the use of same piece of land encourages the resistant hybrids and cultivars, in buildup of diseases and insect pests. combination with improved agronomic Crop rotation, soil tillage, fertilization, practices is likely to be the best solution liming and irrigation are among the in the long run. agronomic practices that play an Weeds such as Bermudagrass important role in preventing or reducing (Cynodon dactylon) Napier grass the risk of diseases (Heitefuss, 1989). (Pennisetum purpureum) were Additionally, Mahuku et al. (2015) detected in the surveyed fields as claims that some research conducted in outlined in section 3.2. Mahuku et al. USA and Kenya showed that (2015) claims that these weeds are interventions such as the insect vector among the hosts of MLN causing control, crop rotation, and crop viruses. Bockelman (1982) diversification are among the recommends that uncontrolled weeds agronomic practices that play an that serve as hosts to the viruses important role in preventing or reducing causing MLN could act as reservoirs for the risk of MLND. Further, in Kenya, the virus infection to the crops. For this effective monitoring, rigorous reason, farmers should keep their fields implementation of maize-free periods weed free. and rotation with non-cereal crops have helped in minimizing MLND incidence. Similarly, some pests known to be vectors for MLN causing viruses such as Furthermore, despite the availability of stalkborers, aphids, thrips, and beetles many certified varieties on the market, were observed in the field during the the study revealed that 50% of farmers survey. These pests are of concern still planted local varieties and a further even though seed transmission for both 20% used recycled seed as presented MCMV as well as SCMV as reported by in Table 2. This type of seed in most (Wangai et al., 2012) is known to take cases results in poor yields and is highly place at very low rates. However, the susceptible to diseases. Mahuku et al. presence of these vectors if not

controlled can spread the disease very Zambia by: continuing with conducting fast resulting in epidemics (Mahuku et detection surveys; revision of maize al., 2015). phytosanitary import conditions; development and review of Conclusion Standard Operating Procedures Findings from this study clearly indicate (SOPs); stakeholder consultations and the absence of MLND in all the 419 sensitizations on strategies to prevent fields of the provinces surveyed, which MLN and development of emergency suggests that MLND is not present in response plan. Zambia. The revelation of the study Acknowledgements that some of the farmers were inclined to certain agro-cultural practices that The surveillance was made possible could encourage the spread and through the financial support provided buildup of diseases in the fields needs by the Agricultural Productivity Program redress as it might increase the risk for for Southern Africa (APPSA) and the introduction of MLND. International Maize and Wheat Improvement Center (CIMMYT). NPPO Recommendation staff, ZARI management and There is need to strengthen extension Department of Agriculture extension services to enable farmers adopt good staff who were involved in the agronomic practices that help to surveillance are also appreciated. We prevent the spread of MLND such as further thank the Farmers for their crop rotation, crop diversification and corporation during the survey. controlling weeds and insects. The

Government needs to continue to be proactive in conducting awareness and training on MLND. Further, the NPPO needs to put in more stringent phytosanitary measures to prevent MLND introduction and spread into

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The Effect of Seed Source and Post-harvest Practices on Quality of Soybean (Glycine max) Seeds in Busia County Ochran, M. K.,1 Narla, R. D.,1 Muthomi J. W1. and Ochuodho J. O.2 1University of Nairobi P.O. Box 30197, GPO. Nairobi, Kenya 2University of Eldoret P. O. Box 1125-30100, Eldoret, Kenya Corresponding Author: [email protected] Abstract Majority of farmers growing legumes use and recycle seeds from informal sources for the next crop. The quality of such seeds is unknown and usually leads to accumulation of pest, diseases and reduced yields. This study was carried out to determine production practices and quality of soybean seeds obtained from informal sources in Busia County. A survey was conducted to collect information on source of soybean seeds, production and post-harvest handling practices. Seed samples were collected from farmers, local market and agro-dealers. The seeds were evaluated for purity, seed coat damage, germination, vigour and fungal infection. Majority (48%) of farmers in Busia County used farm saved seeds, 29% and 23% used seeds from community based organizations and local markets, respectively. Most of the farmers (92%) used inappropriate threshing techniques like beating with sticks and about 80% of the farmers did not treat seed either before storage or during planting. Majority (68%) stored soybean for three months only. Seeds from informal sources had low purity, higher seed coat damage and infection as compared to certified seeds. The physical purity of seeds from the informal sources did not meet the recommended standard of 98% however their germination was comparable to 75% germination standard. Farmers therefore, should be advised to adopt use of certified seeds and appropriate handling techniques. Keywords: Soybean, seed source, seed quality, seed production practices Introduction 100% of the seed dealers handle maize, In Africa, seed that is used is supplied 82% for cowpea and 82% vegetables by formal and informal seed sector. compared to 27% for soybean seeds According to Adetumbi et al. (2011) indicating a limited supply of soybean

seeds compared to other grain crops productivity of other technologies in and vegetables. The informal sector increasing crop productivity. provides the bulk of seed planted by Soybean (Glycine max) is an important farmers in developing countries multipurpose crop utilized for food, (Bishaw, 2004). It operates at the farm livestock feed, industrial raw material level and depends on local knowledge and bio-energy (Myaka et al., 2005). It of plant or seed selection and is also the world leading source of oil management practices. It does not and protein (Fedaku et al., 2009) with involve seed certification procedures 20% oil content, 40% protein and 35% and although the role of the informal of carbohydrates and is cholesterol free sector is recognized, few attempts have with low levels of saturated fatty acids. been made to assess the status of seed The biomass from soybean is an quality. Seed from the formal sector important source of animal feed, green must meet specific quality standards manure and can also be used as mulch prescribed by the national regulations (Chianu et al., 2009). In Kenya soybean and involve certification agency which is being promoted as a cultural source establishes technical, administrative of protein, cooking oil, income to and regulatory frameworks to produce farmers and for soil fertility quality seed that meets specified improvement (Misiko et al., 2008). minimum standards for marketing. Sanginga et al. (2003) estimated that Apart from good crop management soybean can fix 44-103 kg/ha of practices to maintain varietal purity, nitrogen reducing the need for laboratory tests are conducted to expensive nitrogen fertilizers. It adds assess critical seed quality attributes. nitrogen to the soil enriching infertile Seeds carry genetic potential of plants soils and stimulating crops productions and influence the productivity of other in rotation especially with cereals agricultural inputs. Availability of, (Ojiem, 2006). access to and use of quality seeds are determinant of the efficiency and Western region is the leading soybean production area in Kenya accounting for

80% of the total national soybean on quality of soybean seeds in Busia production with the main production County. areas being Butere/Mumias, Bungoma, Materials and Methods Busia, Teso, Kakamega, Mt. Elgon, A purposeful survey was conducted Lugari and Vihiga (Chianu et al., 2008). using a semi-structured questionnaire However, production is still below their to collect information on source of maximum potential due to some soybean seeds, production and post- challenges facing the farmers. Lack of harvest handling practices. Seed adequate and quality seed supply by samples were collected from farmers, the formal system and lack of local market and agro-dealers in Low knowledge on production and post- Midland Zones I, II and IV. The seeds harvest practices of soybeans also were evaluated for purity, seed coat hindered farmers from accessing damage, moisture content, improved quality seeds (Oshone et al., germination, vigour and infection in the 2014). This has led to about 70% of the laboratory. farmers recycling seeds from informal Seed quality tests sources and because seeds from such Determination of physical purity of sources are of poor quality they result soybean seeds in poor yields. A baseline survey Analytical purity was conducted in conducted by Odendo et al. (2008) accordance to ISTA 2015 guidelines. revealed that communities in this region The different components comprising had interest in growing soybeans but the sample were grouped into, pure had no access to improved varieties, seed, inert matter, other crop seeds good quality seeds and resorted to and weed seed. Percentage of each using seeds obtained from informal component was calculated as a fraction sources to raise crops in the following of the initial weight as indicated below: season. This study therefore aimed at Weight of each component fraction X 100 Component (%) = Initial weight of the sample determining the effect of seed source, Determination of moisture content production and post-harvest handling and seed coat damage

Moisture content was determined using boxes lined with absorbent towel. The a moisture meter by filling the meter boxes were arranged in a completely cup with soybean seeds and recording randomized design (CRD) in the the readings. The test was repeated laboratory under room temperature four times. Seed coat damage was conditions. The seed were routinely detected by sodium hypochlorite test as misted with sterile distilled water. Seeds per Van Utrecht et al. (2000). Four were considered germinated when replicates of 100 seeds were soaked in 2mm of the radicals protruded and 1% sodium hypochlorite solution for 10 germination percentage calculated as minutes. Seeds were considered to be shown below (Chirchir et al., 2016). damaged when the seed coat appeared (Number of germinated seeds) x100 (%) = wrinkled, swollen or with loose coats. Total number of seeds 𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆𝐆 Damaged seeds were counted and the Germination rate index was also percentage estimate of seed coat calculated as shown below: No. germ. seeds 1st Germinated final count damage of a sample calculated using = + Days of 1st count Days of final count the formula: 𝐆𝐆𝐆𝐆𝐆𝐆 Seedling vigor was determined after 15

(No. of swollen seeds after test) x100 (%) = days by randomly selecting 10 Total number of seeds used 𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃𝐃 seedlings from each replicate and

Determination of germination and measuring the root and shoot lengths seedling vigour of soybean using a ruler in centimeters. These were Germination test was done according to then used to calculate the seedling ISTA 2015 guidelines on paper towel to vigor index (SVI) using the formula determine the percentage of viable described by Aliloo and Darabinejad, seeds in a sample. Seeds were surface (2013). % sterilized in 2% sodium hypochlorite = Germination x Seedling length solution for five minutes to kill Determination𝐒𝐒𝐒𝐒𝐒𝐒 of100 fungal infection epiphytes followed by three changes of in soybean seeds using agar plate sterile distilled water. Four replications method of 100 seeds each in transparent plastic

Soybean seeds were surface sterilized Survey data was analyzed using IBM in 2% sodium hypochlorite for three Statistical Package for Social Science minutes, followed by rinsing in three (SPSS) version 20. Laboratory tests changes of sterile distilled water and data were subjected to analysis of blot dried on sterile paper towel. Four variance (ANOVA) using GENSTAT 15th replications of 10 seeds per petri dish edition. Means were separated using were plated on Petri dish containing Fischer’s protected Least Significant potato dextrose agar media and Difference (LSD) at 5% level of incubated for 3-7 days at 250c in significance (Steel and Torrie, 1960). alternating dark and light conditions Results (Alemu, 2014). Sodium chloride was added to the media to inhibit Source of soybean seeds and post- harvest practices used by farmers germination and streptomycin sulphate in Busia County to inhibit bacterial growth. The number Most (48%) of the farmers used farm of seeds infected and the individual pathogen types were recorded and saved seeds, 29% and 23% were using results expressed as a percentage. seeds obtained from community based Fungi growing on potato dextrose agar organizations and local markets plates were identified both visually and respectively, across the three zones. Over (60%) of farmers in LM II used under the stereomicroscope by own saved seeds as compared to other observing colony characters and zones while around 45 % sourced from morphology of sporulating fungi (Shovan et al., 2008). community based organizations within their locality (Table 1). Data analysis

Table 1: Percentage of farmers who obtained soybean seeds from different sources in three agro-ecological zones in Busia County.

n=60 Agro-Ecological Zones Source of seed LM I (%) LM II (%) LM IV (%) Mean Farm saved 40±8.3 65±8.3 40±8.3 48.3±7.6 Local market 30±4.4 25±4.4 15±4.4 23.3±7.6 Community based organizations 30±10.1 10±10.1 45±10.1 28.3±7.6 N=Sample size, LM I= Lower Midland Zone I, LM II= Lower Midland Zone II, LM IV = Lower Midland Zone IV

About 92% of farmers threshed using sticks. Threshing inside the sack soybean crop by beating with sticks, with sticks attracted only 5% of the 5% used their hands to remove seeds farmers in LM II and IV. Hand threshing from the pods while 3% put soybean in was practiced by 15% of the farmers in a sack and beat them with sticks. All LM IV (Table 2). the farmers in LM I threshed soybean

Table 2: Percent farmers using different techniques to thresh soybean in three agro- ecological zones in Busia County.

n=60 Agro-Ecological Zones Threshing method LM I (%) LM II (%) LM IV (%) Mean Removing seeds from the pods by hand 0±5.0 0±5.0 15±5.0 5.0±29.2 Beating with stick on the floor 100±6.0 95±6.0 80±6.0 91.7±29.2 Beating pods in a sack with sticks 0±1.7 5±1.7 5±1.7 3.3±29.2

N=Sample size, LM I= Lower Midland Zone I, LM II= Lower Midland Zone II, LM IV = Lower Midland Zone IV practice. In LM II and IV more than About 67% of the farmers in Busia 70% of farmers did not treat the seeds County did not treat soybean seeds. either before storage or planting Around 60% of the farmers in LM I (Figure 1). adopted seed treatment technology

120 n=60 100 Untreated 80 60 40 20 Percentage of of Percentage farmers 0 LM I LM II LM IV Agro-Ecological Zones

Figure 1: Percentage of farmers who did not treat soybean seeds before storage or planting in three zones Busia County.

Farmers stored soybean seeds up to a about 12% of farmers stored for six period of twelve months. However, months which was equivalent to two majority (68%) reported to have stored growing season. Farmers stored seeds seeds for three months. Only 5% as the for only two to six months period in LM smallest group stored their seeds for II. While in zone IV seeds were stored one year. Around 8% stored for one for twelve months (Table 3) month, 7% stored for two months and

Table 3: Percentage of farmers who reported the duration of storage of soybean seeds in three agro-ecological zones in Busia County.

n=60 Agro-Ecological Zones Duration of storage LM I (%) LM II (%) LM IV (%) Mean Up to 1 month 10±4.4 0±4.4 15±4.4 8.3±12.1 1 to 2 months 5±1.7 10±1.7 5±1.7 6.7±12.1 2 to 3 months 75±9.3 80±9.3 50±9.3 68.3±12.1 3 to 6 months 10±1.7 10±1.7 15±1.7 11.7±12.1 Over 12 months 0±5.0 0±5.0 15±5.0 5.0±12.1 N=Sample size, LM I= Lower Midland Zone I, LM II= Lower Midland Zone II, LM IV = Lower Midland Zone IV

Quality status of soybean seeds used in Busia County

The analytical purity components of the meet the recommended physical purity seed samples from different sources standard of 98% (Table 4). The analysis differed significantly. Seeds obtained indicated that seeds from the informal from agro-dealers had the highest sources had damaged seed coats of percentage of pure seed followed by 88% as compared to seed from agro- own saved seeds and lastly by seeds dealer (82%). from the local market. However, all the seeds from the three sources did not Table 4: Analytical purity of soybean seed samples from various sources in different agro- ecological zones in Busia County.

Components Source Pure seed Other crop seed Inert matter Agro-dealer 97.2a 0.2b 0.1c Farm-saved 92.5bc 0.3a 1.0a Market 91.1c 0.4a 0.6b Mean 93.6 0.3 0.6 LSD(P≤0.05) 2.1 0.1 0.3 CV 5.0 118.8 120.8

LSD=least significance difference, CV=coefficient of variation.

Moisture content of seeds from the in seeds collected from the informal three sources did not differ outlets and high compared to seed from significantly. Comparable results were formal source (Table 5). recorded on damage caused by insects Table 5: Percent moisture content, seed coat damage and insect damage of soybean seed samples collected from different sources in the three agro-ecological zones in Busia County.

Source Moisture content Seed coat damage Insect damage Agro-dealer 9.1a 81.8b 0.5b Farm-saved 9.1a 88.4a 1.6a Market 9.2a 87.7a 1.6a Mean 9.1 86.0 1.2 LSD(P≤0.05) 0.3 3.0 0.3 CV 7.5 8.0 83.2 LSD=least significance difference, CV=coefficient of variation

Germination percentage of soybean percentage of 90% followed by local seeds from different sources differed market (76%) and farm saved seeds significantly. Germination percentage (75%) respectively. High germination of the seeds from the three sources rate, number of normal seedlings and met the minimum germination seedling vigour index was also standard recommended for soybean observed on seeds from this source seeds of 75%. Agro-dealer seeds (Table 6). recorded the highest germination

Table 6: Percent germination and seedling vigour of soybean seed samples from different sources in three agro-ecological zones in Busia County.

Germination Seedlings Germinati Germination Norma Seedling Seedling Source on% rate l Length vigour index Agro-dealer 90.0a 30.6a 82.5a 8.4a 7.6a Farm-saved 75.2b 23.3b 69.0b 5.5c 4.8c Market 75.9b 23.3b 66.5b 6.8b 5.7b Mean 80.4 25.7 72.7 6.9 6.0 LSD(P≤0.05 7.7 3.4 7.6 1.4 1.4 ) CV 21.8 30.1 23.8 45.7 52.1 LSD=least significance difference, CV=coefficient of variation.

Infection of seeds collected from observed on seeds collected from local different sources and zones differed market. Aspergillus falvus and significantly. High number of seed Aspergillus niger were the most infection was observed on seeds prevalent in seed obtained from the obtained from farmers and local farmers. Seeds collected from the agro- markets. Infection by Cercospora dealer outlets had the least incidence of kikuchii and Penicillium spp. were fungi observed (Table 7). Table 7: Percentage of fungi in soybean seed samples from various sources in different agro-ecological zones in Busia County.

Fungi Source Infected C. kikuchii A. flavus A. niger Penicillium spp. Agro-dealer 10.0b 0.0b 0.0c 0.0b 0.0b Farm-saved 28.6a 1.1ab 7.8a 5.2a 2.3a Market 23.2a 2.2a 3.8b 2.0b 2.8a Mean 20.6 1.1 3.9 2.4 1.7 LSD(P≤0.05) 9.6 2.2 4.7 4.7 2.8 LSD=least significance difference, C-Cercospora, A-Aspergillus, spp.-species.

Discussion The formal seed source supplied

Most of the farmers in Busia County inadequate seed and this was further utilized soybean seeds from the confirmed with similar findings by Anon informal sources with majority of them (2001) which revealed that the formal using farm saved seeds usually sector supplied only 4% of seeds sown obtained from the previous season. by farmers and the remaining 96% was Most of the farmers have opted to save supplied by the informal sources in seeds to replant in the following season most African countries. Similarly, due to financial constraints, inadequate Adetumbi et al. (2011) reported that seeds of good quality and high cost of 100% of the seed industries which is a certified seeds. Informal seed sources representation of formal sector handled readily availed the seed to farmers maize, 82% for cowpea and 82% every season since most of them save vegetables compared to 27% for up for the next planting. Findings soybean seeds. A baseline survey reported by Oshone et al. (2014) conducted by Odendo et al. (2008) similarly indicated that majority of the revealed that most farmers in Western farmers in Ethiopia obtained common region of Kenya had interest in growing bean seed from informal sources a soybean but had a challenge in channel which contributed more than accessing improved varieties and good 95% of the common bean seed supply quality seed during planting. In in Ethiopia. Similarly, Chianu et al. addition, lack of adequate and quality (2009) conducted a survey on soybeans seed supply by the formal system in Kenya and revealed that most hindered farmers from accessing farmers used saved seeds or seeds improved quality seeds (Oshone et al., sourced from the open air markets 2014). The few seed industries in Kenya which at times were of mixed varieties do not produce adequate seeds of to raise crops the following season due soybean to meet the demand and most to their availability. of them have given priority to cereals or high value crops for them to make profits (Lowaars et al., 2012).

Majority of the farmers interviewed planting or before storage. Untreated reported to thresh soybean with sticks seeds act as vehicles of transmitting and as a result farmers experienced a pathogens which cause diseases in challenge of reduced germination and soybean seeds. These pathogens affect vigor in soybeans. The results were in germination and seedling vigor and as agreement with the findings by Surve et a result lower emergence and al. (2015) who reported that hand productivity (Sinclair, 1991). threshing practices usually used by few Treatment provide additional assurance farmers of soybean recorded minimal to crop establishment at reduced cost seed coat damage and high and allows germination of infected germination compared to other seeds by controlling pathogens and techniques practiced by farmers such as protecting seed from fungi (Araujo et stick beating and mechanical threshing. al., 2005) Similarly, Jha et al. (1995) found that The survey revealed that most of the hand threshing resulted in higher respondents stored their seeds for a germination and less deterioration of maximum period of three months and seed than the other techniques. Hand the second best storage period being threshing of soybean significantly six months. Between 0 and 2 months increased seed yield compared with was the period between harvest and stick threshing and mechanical the next season of planting hence few threshing (El-Abady et al., 2012). farmers reported this storage period. Threshing techniques like machine and The period also could be after-ripening stick beating produces more breaks, session of soybean for it to mature fully cracks, bruises and abrasions which thus minimal deterioration. The results in reduced germination and observed reduction in percentage vigor and increase in abnormal germination and vigor over time could seedlings (Reddy et al., 1995). be linked to depletion of reserved food Survey findings indicated that majority for the embryo. This is in line with the of the farmers do not treat seed during findings of Iqbal et al. (2002) and

Demirkaya et al. 2010) that reduction of et al. (2016) found that germination viability and vigor could be attributed to and seed vigor of cowpeas declined a reduction in enzyme activity within with increase in storage duration the seed. In addition, the reduction in irrespective of genotypes or storage seed quality with time could be as a materials. In addition, more decline in result of membrane degradation (Singh germination of soybean stored under and Dadlani, 2003), reduction in conventional condition due to variable enzyme activity or changes in chemical temperature and humidity was also composition of the cell (Verma et al., reported by Balesevic-Tubic et al. 2003). Similarly, Younesi and Azadi (2010). If the seeds are not dried (2013) reported that an increase in properly high moisture content reduces duration of storage caused a decrease seed viability by promoting fungal in the enzyme activity of sorghum growth (Pradhan and Badola, 2012) seeds. which further results in reduction of germination. For oil crops such as Other studies have shown a gradual soybeans and sunflower, increased decrease in germination and vigor of content of fatty acid and auto oxidation soybean cultivars with increasing period of lipids during storage are the main of storage up to six months (El-Abady causes of rapid deterioration of oil crops et al., 2012) and extending storage seeds (Balasevic-Tubic et al., 2005). period intensified deterioration hence low productivity of soybean (Adoba et Analytical purity of seeds from different al., 2016). Belesevic et al. (2010) found sources varied significantly but did not that storage conditions and durations meet the minimum recommended affected germination but adversely purity standard of 98%. Seeds collected affected seed vigor. According to Arif et from agro-dealers were more pure as al. (2006) seed viability decreased compared to seed from local market gradually from 64.5% to 39.2% as and farmers. Similar observations were duration of storage increased from 2 made by Rahman et al. (2017) that okra months to 12 months. Similarly, Sadia seeds obtained from seed companies

were more pure followed by those from sector is due to poor handling and post- government organizations and then the harvest techniques which in turn farmer’s seeds. Bishaw et al. (2012) reduced seed quality. Similar findings working on barley also observed that were reported by Reddy et al. (1995) seeds obtained from the formal sector that seed damage occurred during had the highest analytical purity as threshing in soybean and resulted in compared to those collected from the shorter storage life of seeds. Costa et farmers and local markets. Fujisaka et al. (2005) studies on zoning soybean al. (1993) found that rice seeds samples crop found out that the spoilage caused that were obtained from farmers who by physical injury and moisture content used manual harvesting and threshing were the main factors that contributed had higher analytical purity compared to reduced quality of soybean seeds. with those that were machine Similarly, mechanical damage was harvested. The use of non-cemented considered the most common reason floors during threshing in the rural for poor quality in most legumes setting resulted in accumulation of especially when threshed at unsuitable foreign materials in farm saved seeds. seed moisture content (Greven et al., Sarker et al. (2015) on quality of okra 2001). Pacheco et al. (2015) pointed seeds from different sources and out that physiological quality, vigor and locations cited lack of careful attention performance of soybean seeds was during cleaning operations contributed highly influenced by seed coat injury. to high percentage of reduced purity in Soybean seeds obtained from informal farm saved seeds. sources had more physical injuries because the farmers had poor The present findings indicated that knowledge on how to handle them seeds obtained from the informal soybean seeds which have a sensitive sources recorded higher percentage of seed coat. Minimal injuries on seeds damaged seeds compared to seeds obtained from the formal sources may from the formal sector. The extensive be attributed to improved and planned damage of seeds from the informal processing technology and knowledge

of handling soybean (Araujo et al., reported that percentage germination 2008). Cracks on the seeds may also of certified seed from the formal sector become entry points of microorganisms was higher compared with seed and become susceptible to insect attack obtained from other farmers, local which reduces the storage potential and markets and own saved seeds. Al- the general quality of the seeds (Marcos Faqeeh (1997) in his studies also found Filho, 2005). that certified seed had significantly higher germination in Lentils compared Percentage germination in seeds from with seeds from other sources. the agro-dealer a formal sector was Germination percentage of seeds from higher as compared to those from the farmers was comparable to the informal sources. The high quality of minimum standard. This can be seeds from the formal sector may be attributed to the fact that most farmers due to the fact that they have do selection of quality seeds for equipment and knowledge of handling planting though using informal seeds. According to Adetumbi et al. procedures which may vary from farmer (2010), the formal sector is well to farmer. Similar results were also equipped with sophisticated reported in Ethiopia where almost all equipments and skills of handling seeds samples collected from the to ensure that the quality of seed is farmersreached the minimum maintained all through. One major germination standards for wheat quality control mechanism that has (Ensermu et al., 1998) and sorghum been instituted in the formal seed (Mekbib, 2008). sector is regular seed inspection at different levels from seed field to Seeds obtained from the local market distribution channels. This has ensured and own saved were more infected as that the quality of the seed is compared those from the agro-dealers. maintained from the field all the way to This is due to lack of standard the hands of the final consumer, the procedures and regulations govern farmer. Bishaw et al. (2012) also production of pathogen free seeds.

Cercospora kikuchii, Penicillium spp., rots and post emergence decays Aspergillus niger and flavus (Bhale et (Koning et al., 1995). al., 2004) were recorded as the most Seeds from the formal source common fungal pathogens that infected registered low infection as compared to soybean in Busia County. Most seed from the informal sector due to pathogens that are seed-borne are unhygienic storage conditions at the difficult to detect by most farmers and farmer’s level (Utoba et al., 2011). may assume that seeds are healthy Variation in fungal incidence was while they are not in reality. Our attributed to variations in climatic findings relate with those of Bhale et al. conditions during the crop cycle (2004); Wu et al. (1964) who isolated especially the prevailing humidity which Fusarium oxysporum, Aspergillus niger favor the growth of the pathogens and Aspergillus flavus, Cercospora (Naqvi et al., 2013). The formal sector kikuchii, Penicillium sp., Phoma also practices seed treatment using medicaginis, Macrophomina phaseolina fungicide, insecticides or combination Alternaria alternate as seed-borne of different chemicals which protect the pathogens which are most predominant seed from infections. Seed dressing fungi in pre and post harvested soybean protects the growing seedling for a seeds. Presence of these fungal specific period helping it escape pathogens reduces physiological infection (Ellis et al., 2011). This potential of soybean seeds (Galli et al., technique has shown significant 2007). Singh and Agrawal (1986) improvement in field emergence, seed reported 30% loss in seed viability and yield and reduced mycoflora association germination because of purple stain (Anuja et al., 2000). caused by Cercospora kikuchii, while, Aspergillus flavus, Aspergillus niger, Fusarium spp were responsible for seed Conclusion seeds for the following season from Majority of farmers from the different informal seed sources. These seeds agro-ecological zones in Busia obtained were found to be of poor quality having

low germination and vigor, high unguiculata L. Walp) seed infection incidence and physical quality germination indices and yield as that is below the ISTA recommended affected by length of storage. Seed standard of 98%. Most of the farmers Science and Biotechnology. 5 (1), also did not treat soybean seeds and pp. 11-14. had limited knowledge on post-harvest Odoba, A., Odiaka, N. I., Gbanguba, A. handling and sensitivity of soybeans. U., & Bashiru, M. (2016).

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Abundance and Diversity of Frugivorous Fruit Flies in Kandara, Murang’a County, Kenya Muriuki C.1,2, Guantai M.3, Samita N.1, Mulwa J.4, Nyamai M.4 and Kasina M2 1School of Agriculture and Enterprise Development, Kenyatta University, P.O Box 43844 - 00100, Nairobi. 2National Sericulture Research Centre, Industrial Crops Research Institute, Kenya Agricultural and Livestock Research Organization, P.O. Box 7816 - 01000 Thika.

3Kenya Plant Health Inspectorate Service, P.O Box 49592 - 00100, Nairobi.

4National Agricultural Research Labs, Food Crops Research Institute, Kenya Agricultural and Livestock Research Organization, P.O. Box 14733 - 00800 Nairobi.

Corresponding Author: [email protected]

Abstract

Fruits and vegetables are important source of livelihood to farmers and major horticulture sub sector with high contribution to agricultural GDP in Kenya. This study was conducted to determine diversity and abundance of frugivorous fruit flies in Kandara sub county, Murang’a County in 2018, at a place where first area of low pest population was created in Kenya for Bactrocera dorsalis. Three sets of pheromone traps (Methyl-Eugenol, Cuelure and Trimedlure) were set in six trap stations within farmers’ orchards in four agro-ecological zones (LH1 (Lower Highland Zone), UM1 (Upper Mid-land Zone), UM2, and UM3). The trap catch data was collected fortnightly and data analyzed. Six fruit flies species namely; Bactrocera dorsalis, Ceratitis cosyra, Ceratitis capitata, Zeugodacus cucurbitae, Dacus bivittatus and Perilampsis sp were identified. Bactrocera dorsalis population was significantly (P<.001) different across the four agro-ecologies with lowest densities at LH1 and highest at UM3. Likewise, C. capitata recorded significant (P=0.042) difference densities across the agro-ecological zones, but no significant (P=0.386) difference was recorded for C. cosyra across the agro-ecological zones. Further, there was significant (P=0.012) difference in the number of Perilampsis sp across the agro-ecologies with the highest number recorded in UM1. Both Z. cucurbitae (P=0.061) and D. bivittatus (P=0.056) had low abundance across the agro-ecologies. The peak infestation period differed across the various fruit fly species, whereby B. dorsalis peaked in May, C. capitata in February and C. cosyra

in January. The study shows that abundance for the fruit flies is probably related to their preferred hostplant and the weather patterns. We recommend continuous monitoring and intensifying trapping activities during peak periods in order to control the pest and protect fruits from damage. Farmers should be trained on the use of pheromone traps to reduce over-reliance on pesticides.

Key words: Agro-ecologies, Bactrocera dorsalis, Ceratitis sp, fruit fly density, Pheromone,

Introduction points for pathogens, fruit decay occurs and then falls to the ground, which Fruits are an important source of contribute to high farm losses. Exported livelihood for farmers and they further fruit have been intercepted due to contribute immensely to the agricultural presence of fruit flies by the importing GDP for the country. They also improve countries (Bissdorf & Weber, 2005; diet by providing nutrients and essential Follett & Neven, 2006). For example, vitamins (Thomas, 2008). Majority of since 2015 to date, 19 interceptions households living in Kandara is have been received from EU due to composed of farmers who grow Tephritidae flies in Mango, Capsicum, mangoes, avocados, and guavas as Eryngium and Cucurbits (EC, 2020). commercial fruits which unfortunately are among the main host plants for fruit Pest management practices by farmers flies. Therefore, the productivity and in Kandara include use of pesticides quality of these fruit crops is highly that has resulted in their over-reliance affected by fruit flies (Tephritidae) control, increased cost of production which cause damage directly by and economic losses due to rejection of puncturing the fruits to lay eggs, the fruits as a result of maximum residue hatched maggots feed on the fruit levels, increased pollution, health creating galleries that serve as entry problems, (USDA-APHIS, 2008).

Poor farmer knowledge on fruit fly development, possible practical pest development in relation to host management options have resulted into

over-reliance on pesticides. Earlier The purpose of this study was to studies indicate that lack of training and determine the diversity and activity technical support to fruit farmers has density trends of fruit flies across the contributed immensely to low adoption agro ecological zones in Kandara from of Integrated Pest Management (IPM) January to May 2018. technologies in developing countries MATERIALS AND METHODS (Parsa et al., 2014). The use of insect development and reproductive Study site behaviour such as their activity density The study was carried out in Kandara trends in the farmland is a major step sub-County in Murang’a County in towards their successful management. 2018. Kandara Sub County covers an Earlier studies indicated that the activity area of about 236 km2 and is located at density and distribution of Tephritid latitude 0° 53’59.99”N and longitude fruit flies is affected by biotic factors 37° 00’0.00”E and an altitude of such as temperature and humidity between 1520-1880 m above sea level. (Vayssières et al., 2008). For example, Kandara is composed of four agro studies carried out in Thailand, ecological zones; Lower Highland Zone indicated that the developmental time (LH1) - Tea and dairy zone, First Upper for the immature stages of Bactrocera Mid-land Zone (UM1) - Coffee and tea carambolae and Bactrocera papayae zone, Second Upper Mid-land Zone increased with decrease in temperature (UM2) - Main coffee zone, Third Upper (Danjuma et al., 2014) whereas the Mid-land Zone (UM3) - Marginal coffee optimum temperature for fruitflies zone (Fig 1). The average annual development has been reported to lie rainfall of the area studied ranges between 20° and 30°C for B. dorsalis between 1,400 to 2,000mm and the (Rwomushana et al., 2008) and annual mean temperature is between between 26 and 30°C for B. cucurbitae,. 18°c to 21°c (Jaetzold et al., 2006).

Figure 1. Map of the study sites

Data collection used to attract both Bactrocera

Three sets of pheromone traps (Methyl- cucurbitae and Dacus bivittatus. Trap Eugenol, Cuelure and Trimedlure) were catch data was collected on a fortnight set in six trap stations within mango, basis and servicing of the monitoring avocado and guava farms in the four traps done every 6 weeks. Samples of agro-ecological zones (LH1 (Lower collected trap catches were put in Highland Zone), UM1 (Upper Mid-land diffrent vials and taken to the Zone), UM2 (second Upper Midland laboratory at the Kenya Agricultural and Zone) and UM3 (third Upper Midland Livestock Research Organization Zone) in the sub-county in 2018. Methyl (KALRO) Sericulture, for further –Eugenol was used to attract identification and counting. The ANOVA Bactrocera dorsalis, TrimediLure was of the trap catch data was done using th used to attract Ceratitis cosyra and Genstat 17 edition. Significant means Ceratitis capitata, While Cuelure was were separated using Fishers Protected

Least Significance Difference Test However, there was no significant (LSD). difference in the number of C. cosyra (P=0.386), D. bivittatus (P=0.056) and Results B. cucurbitae (P=0.061) across the agro Six species of fruit flies were identified ecologies. Perilampsis sp recorded the across the four agro-ecological zones. least activity density across all the agro These were Bactrocera dorsalis Ceratitis ecologies, possibly due to low cosyra, Ceratitis capitata, Bactrocera sensitivity of the lures towards this fruit cucurbitae, Dacus bivittatus and fly. Generally, UM3 had the highest Perilampsis sp. (Table 1). A significant number of fruit flies (45.28%), followed difference in the number B. dorsalis by UM1 (24.77%), UM2 (22.40%) and (P<0.001), C. capitata (P=0.042) and the least was LH1 (7.55%). However, a Perilampsis sp. (P=0.012) was recorded significant number of D. bivittatus was across the agro-ecological zones. recorded in LH1 (Table 1).

Table 1: Fruit fly densities across the agro-ecological zones.

Agro B. B. D. Perilampsis Ecology dorsalis C. cosyra C capitata cucurbitae bivittatus sp LH1 3.64b 17.7a 27.21a 4.267a 7.752a 0.2b UM1 65.69b 41.25ab 80.38b 5.286a 4.848b 1.7905a UM2 106.9b 25.54ab 36.87c 6.202a 4.865b 0.7212ab UM3 231.68a 45.3b 72.42b 11.048b 3.333b 0.4762ab P value <.001 0.386 0.042 0.061 0.056 0.012 s.e. 32.44 12.88 15.62 1.91 1.16 0.36

Abundance of C. capitata increased almost flattened in April. A gradual gradually from January peaking in increase in B. dorsalis was recorded February after which a gradual drop from January to March and thereafter was recorded. In contrast, C. cosyra the population increased exponentially decreased gradually from January and till the end of May (Fig 2).

B. dorsalis C. cosyra C. capitata B. cucurbitae D. bivittatus Perilampsis sp 300 250 200 150 100 50

Mean trap catch of fruit flies fruit of catch trap Mean 0 January February March April May -50 Month, 2018

Figure 2: Fruit fly trap catch trend (Jan-May, 2018).

Discussion LH1 and UM1 had significantly lower pest population compared to UM2 due Activity density of fruit flies differed to cool weather LH1 (Kasina et al., across the four agro ecological zones 2019). Earlier studies by Vayssières et probably due to variation in climatic al. (2008) indicated that Tephritid conditions across the zones. The LH1, distribution and abundance depend on which is at a higher altitude and records several abiotic factors (e.g., lower temperatures explains why few temperature, relative humidity, rainfall) fruit flies were recorded in this region. and biotic factors (e.g., host plants, Further, fruit diversity is low in this natural enemies). Low temperature was zone. Temperature levels increase found to increase developmental time towards UM3 and this is likewise for of immature stages of Bactrocera fruit crop diversity and intensity of carambolae and Bactrocera papaya production. Previous studies on (Danjuma et al., 2014) with the oriental fly (B. dorsalis) distribution in optimum temperature found to range Kenya in the same area indicated that

between 25 and 30°C for B. invadens Africa (José et al., 2013). Earlier studies (Rwomushana et al., 2008). on preferred hosts in Zimbabwe indicate that availability of cultivated The difference in the level of infestation and wild fruit varieties throughout the of fruit fly species across the months year results in increased population of (January to May 2018) is associated to fruit flies making it difficult to manage the availability of suitable fruits for egg them (Musasa et al., 2019). A previous laying and multiplication. In Kandara, review on status of data from mangoes matured between February Afrotropical countries indicated that and April while avocadoes matured host availability and ecological niches from March. This ensured sufficient affected the occurrence and impact of food supply for multiplication of the fruit Z. cucurbitae (De meyer et al., 2015). flies, especially B. dorsalis throughout Other fruit fly species are more host the study period. B. dorsalis is known to specific explaining why their numbers attack at least 46 host plants, including may have remained relatively low in many commercially grown fruit crops absence of their hosts. Our results such as mango, oranges, guava, shows that abundance for the fruit flies cucurbit, papaya and avocado, as well is probably related to their preferred as many other species indigenous to hostplant and the weather patterns.

Recommendations farmers on how to use pheromone traps with specific lures to reduce the There is need to carry out continuous pest population. A year round fruit fly monitoring of fruit flies in Kandara management in the farmland is the only throughout the growing season for their assurance for long term reduction and timely management to reduce fruit control of the diverse fruit fly pest in the damage and meet phytosanitary locality. requirements. There is need to train

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Next generation sequencing as a tool in modern pest risk analysis: a case study of groundnuts (Arachis hypogaea) as a potential host of new viruses in western Kenya Mukoye B1*., Mangeni B. C2., Sue J3., Mabele A. S2. and Were H. K2. 1 Kenya Plant Health Inspectorate Service (KEPHIS), Nairobi, Kenya. 2 Department of Biological Sciences, Masinde Muliro University of Science and Technology (MMUST), Kakamega, Kenya. 3 Cell and Molecular Biology Sciences, The James Hutton Institute (JHI), Dundee, UK. *Corresponding Author: [email protected] Abstract Groundnut (Arachis hypogaea, L.) is grown in diverse environments throughout the semi-arid and sub-tropical regions of the world. Poor yields of 500-800kg/ha are attributed to poor agronomic practices, pests and diseases. The major disease reported in Kenya is Groundnut rosette disease (GRD). But recent observations in the field showed that the crop has varied and severe symptoms in addition to those caused by GRD. This required deeper analysis to establish the causal agents. Groundnut samples with virus-like symptoms were collected from western Kenya in 2016. Total RNA was extracted using All Prep RNA Mini Kit. Five mRNA libraries were prepared using the Illumina TrueSeq stranded mRNA library Prep Kit and pooled for multiplexed sequencing using an Illumina HiSeq 2500 to generate paired end reads (FastQ Sanger). The reads were analysed in the Galaxy project platform (customized). Quality reads were first mapped onto plant genome Refseq and unmapped reads isolated and mapped onto virus Refseq using Bowtie 2 (v2.2.3). Groundnut rosette virus satellite RNA, Groundnut rosette virus, Groundnut rosette assistor virus, Ethiopian tobacco bushy top virus, Cowpea polerovirus 2, Chickpea chlorotic stunt virus, Melon aphid- borne yellow virus, Phasey bean mild yellow virus, Beet mild yellowing virus, White clover mottle virus and Cotton leafroll dwarf virus were identified in four libraries. Other viruses (with less than 100 reads) including Bean common mosaic virus, Bean common mosaic necrosis virus, Cowpea chlorotic mottle virus RNA 3, Broad bean mottle virus RNA 3, Passion fruit woodiness virus among others were also mapped. Some of the viruses common in western Kenya were confirmed by PCR. The presence

of at least three viruses in groundnuts in Western Kenya highlights the importance of starting a germplasm clean-up program of the plant material used as seed in this crop.

Key words: Groundnuts, NGS, RefSeq, Viruses. pathogenic viruses, fungi, bacteria and Introduction nematodes (Mabele et al., 2020; Mutegi Virus infection is prevalent across many et al., 2010;). About 31 viruses have types of plants, and is of specific been reported to naturally infect importance in crops cultivated for food, groundnuts around the world (Kumar et where they cause significant yield and al., 2007). These viruses belong to quality losses. Groundnuts (Arachis various genera including Potyvirus, hypogaea L.), belongs to the family Tospovirus, Cucumovirus, Pecluvirus, Fabaceae, and is the only domesticated Soymovirus Umbravirus, Begomovirus, species in the genus (Usman et al., Bromovirus, Carlavirus, Ilarvirus, 2013). Groundnut production is an Luteovirus, Potexvirus, Rhabdovirus enterprise of economic and nutritional and Tymovirus. Nineteen of these value for farmers in east Africa (Okello viruses were first isolated from et al., 2010). Resource poor smallholder groundnuts, while the rest from other farmers grow nearly 75 - 80% of the hosts, but they commonly occur on world’s groundnuts in developing groundnuts. The most economically countries obtaining yields of 500- important viruses of groundnuts are: 800kg/ha, as opposed to the potential Groundnut rosette virus (GRV), yield of >2.5t/ha (Kayondo et al., Cucumber Mosaic Virus (CMV), Peanut 2014). In western Kenya, an average of mottle virus (PeMoV), Groundnut bud 600 – 700 kg/ha is achieved which is necrosis virus (GBNV), Indian peanut less than 30-50% of the potential yield. clump virus (IPCV), Groundnut rosette The low yields are mainly attributed to assistor virus (GRAV), Peanut stripe poor quality seeds, drought, poor virus (PStV), Peanut clump virus (PCV), agronomic practices, numerous pests Tomato spotted wilt virus (TSWV), and diseases caused by numerous Tobacco streak virus (TSV) (Okello et

52 al., 2014) and Cowpea mild mottle virus and DNA extractions (Adams et al., (CPMMV) (Mukoye et al., 2015). The 2009). This study utilized NGS to observations made on groundnuts in establish viruses that could be causing western Kenya showed severe and the observed varied symptoms in highly variable virus-like symptoms groundnuts. which could be due to multiple infection Materials and methods of any of the groundnut viruses (Mukoye et al., 2020). Groundnut leaf samples showing virus- like symptoms of green mosaic, leaf Proper diagnosis of plant viruses is the distortion, downward curling, mottling, first step to the development of their chlorotic areas, necrotic spots, local management strategies in addition to lesions, stunting or a combination of preventing their introduction and these were collected in RNAlater® RNA spread. New viruses are identified on a Stabilization Solution and kept at 4oC regular basis and more are yet to be until further analysis. The leaves were uncovered in some hosts or in other collected in fields from Bungoma, Busia, geographical regions where they have Homabay, Kakamega, Siaya and Vihiga not been reported. Therefore, there is Counties through systematic sampling need for a robust tool to identify new during the 2016-2017 short rains and viruses that have not been identified in long rains seasons. new geographical areas, and in new hosts or new recombinants. Next Total RNA was extracted using All Prep generation sequencing (NGS) RNA Mini Kit in the pooled samples. Five technologies are fast becoming a mRNA libraries were prepared using the popular method to obtain whole plant Illumina TrueSeq stranded mRNA virus genomes in a relatively short library Prep Kit and pooled for period of time (Boonham et al., 2014). multiplexed sequencing using an NGS sequences complete genomes of Illumina HiSeq 2500 to generate paired plant viruses and still obtains excellent end reads (FastQ Sanger). The reads results due to its ability to use total RNA were analysed in the Galaxy project

53 platform (customized). Quality control proteins from known virus genomes of the raw reads was conducted using [extracted from GenBank (Benson et Trimmomatic (Bolger et al., 2014) with al., 2013) release 225] by selecting parameters: LEADING: 20 TRAILING: entries classified as ‘virus’ (VRL 20 SLIDINGWINDOW: 4:20 and a partition) and ‘complete genome’ using minimum read length of 50. To remove the NCBI’s Assembly database (Kitts et host reads, trimmed reads were al., 2016). The alignment was mapped to the concatenated genome conducted using BlastX® (Altschul et sequences of two diploid ancestors of A. al., 1990), and aligned contigs (e- hypogaea, A. duranensis (Genbank values<10−6) denoted as virus GCA_000817695.2) and A. ipaensis sequences. The BlastX® alignments for (Genbank GCA_000816755.2) (Bertioli virus-derived contigs were then et al., 2016) and the chloroplast checked manually to confirm virus genome of A. hypogaea (Genbank sequence identification. KX257487.1) (Prabhudas et al., 2016) Verification of some of the common (as there is currently no sequenced viruses detected by NGS (with less than genome for A. hypogaea). Mapping was 100 reads) was done by RT-PCR conducted using Bowtie2 (Langmead, according to Naidu et al., (1998a). This 2013) (score-min value“L,0,-0.2″). The was done on some of the groundnut un-mapped reads, designated as non- samples returned after sequencing (1, host reads were then assembled into 2, 3, 4 and 5). The target viruses were contigs using Trinity (Grabherr et al., Cowpea aphid-borne mosaic virus 2011) with a minimum contig length of (CABMV), Bean common mosaic virus 200bps. The contigs were mapped to (BCMV), Bean common mosaic necrosis the concatenated host ancestor virus (BCMNV), Cowpea mild mottle genome using Bowtie2 (Langmead, virus (CPMMV) and Cucumber mosaic 2013), and the unmapped contigs virus (CMV). designated as non-host contigs. The non-host contigs (≥300 bp) were then Total RNA was extracted using RNeasy aligned against a dataset of 691 K Plant Mini Kit (Qiagen) following the 54 manufacturer’s instructions. For Pathogroup V (Mangeni et al., 2014) samples 1, 2, 3 and 4, the leaf tissue and CABMV (accession X82873) was homogenized in liquid nitrogen Zimbabwe isolate (Mlotswa et al., while for sample 5, (which was split into 2002). 3 sets –A, B and C based on the fact Results that each leaf was from a different plant) the tissue was homogenized in Raw reads obtained ranged from 3.2 – lysis buffer provided in the kit. Coat 7.2 million. After trimming, the yield protein primers for BCMV, BCMNV and ranged from 2.8 – 6.3 million of which CABMV were chosen using Primer3 between 50 – 70% mapped to host software with reference to known genome. About 0.2 – 11% of the non- accessions, namely; BCMNV NL-3 host reads mapped to the virus genome (accession Z17203.21) Pathogroup V1, (VRL) (Table 1). BCMV NL-2 (accession L19472.1)

Table 1: Reads and contig counts information for each library RNA-seq dataset.

Library E5 E7 E8 E9 Raw Reads 3,329,984 3,238,295 7,263,305 4,316,937 Reads after trimming 2,957,536 2,888,001 6,361,618 3,830,698 Reads after host mapping 996,404 1,472,648 3,019,197 2,139,196 Reads mapped to host 69.9% 54.5% 57.5% 50.2% Reads mapped to Gb-VRL-cg (%) 0.88% 5.6% 11.6% 0.23% Reads un-mapped to Gb-VRL-cg 989,041 1,407,511 2,713,214 2,136,764 Contigs assembled 15,183 79,111 24,346 10,658 Contigs mapping to host 210 756 1146 202 Contigs mapped to Gb-VRL-cg 1197 1769 1707 805 Unmapped contigs >= 1000bps 115 522 436 225

(GRAV) were the common viruses Groundnut rosette virus (GRV), its detected in most of the libraries. Other associated satellite RNA (sat-RNA) and viruses detected include Ethiopian Groundnut rosettes assistor virus tobacco bushy top virus, cowpea

55 polerovirus 2, chickpea chlorotic stunt mild yellowing virus, White clover virus, Melon aphid-borne yellow virus, mottle virus, Cotton leafroll dwarf virus Phasey bean mild yellow virus, Beet (Table 2).

Table 2: Viruses identified in the 4 libraries using the bioinformatics workflow. Viruses are only reported if they have ≥ 100 reads or ≥ 5 contigs mapped and 20% coverage.

The fifth library (E6) revealed some of common mosaic necrosis virus, Broad the common viruses in western Kenya bean mottle virus RNA 3, Passion fruit but with less than 100 reads. These woodiness virus and Cowpea aphid- were Bean common mosaic virus, Bean borne mosaic virus.

56 Table 3: Library E6 matched viruses with <100 reads.

RefSeq Reads Genome match annotation* ref|NC_002738.1| 23 Groundnut rosette virus satellite RNA, complete genome ref|NC_030236.1| 7 Impatiens flower break potyvirus isolate Asan, complete genome ref|NC_003397.1| 5 Bean common mosaic virus, complete genome ref|NC_003603.1| 2 Groundnut rosette virus complete genome, strain MC1 ref|NC_004047.1| 2 Bean common mosaic necrosis virus, complete genome ref|NC_014790.2| 2 Passion fruit woodiness virus, complete genome ref|NC_004013.1| 1 Cowpea aphid-borne mosaic virus, complete genome *Bolded refers to common viruses in western Kenya.

RT-PCR verification 5, portions A and C were negative for CABMV, BCMV and BCMNV. Portion B Samples 1, 2 and 4 had BCMNV, BCMV was positive for all these viruses (Figure and CABMV. Leaf sample 3 was free of 2). these viruses (Figure 1). In sample

Figure 1: Gel electrophoresis view of Figure 2: A gel electrophoresis view of RT-PCR results for samples 1-4. RT-PCR results for sample 5 – A, B and C.

57 The challenge to be addressed is proper Discussion analysis, interpretation and utilization Next generation sequencing (NGS) of the huge data generated using NGS offers a great opportunity in diagnosis technology. Platforms to handle some of plant viruses especially in the of these challenges have been identification of new viruses. Detection developed and still under constant of viral RNA and DNA genomes in improvement. The Galaxy platform is infected plant material by NGS (Kreuze one of the effective one with proper et al., 2009) is possible through the tools in manipulation of NGS data. extraction and sequencing of total RNA However, it needs a deeper and DNA (Eichmeier et al., 2016). NGS understanding of the parameters has the ability to sequence whole involved in each tool contained. genomes of known and unknown viruses and the ability to detect multiple The use of PCR and other serological viruses from a mixed infection, thus virus detection methods are key in providing a very sensitive diagnostic verification of the identified viruses method for the rapid and routine using the NGS platform. This is key detection of viruses. NGS being non- specifically when the technology is specific, can be used to detect all utilized by National Plant Protection known and unknown viruses present in Organizations (NPPOs) in virus a host irrespective of their diagnostics. The challenge will be in the pathogenicity. In this study, common detection of new/novel viruses whose groundnut viruses namely: GRV, GRAV quarantine status has not yet been and sat-RNA were detected in almost all established and therefore, this will the libraries. In addition, several other require proper pest risk analysis (PRA) new viruses were detected some of to be conducted. which have never been reported in Conclusion groundnuts before. This confirms that NGS can be utilized in detection of The NGS technology is a modern tool known and unknown plant viruses. that is able to detect new viruses in

58 plants, and therefore useful in Plant Pathology. 10, pp. 537– enhancing phytosanitary operations 545. in trade. Its use in determining Altschul, S. F., Gish, W., Miller, W., the groundnut virome revealed Myers, E. W. & Lipmon, D. J. that the crop is a host of many (1990). Basic local alignment viruses. The challenge lies in the search tool. Journal of Molecular proper analysis of huge data Biology. 215, pp. 403–410. generated and verification of the detected plant viruses. Boonham, N., Kreuze, J., Winter, S., Recommendation van der Vlugt, R., Bergervoet, J., Utilization of new technologies like the Tomlinson, J., & Mumford, R. Next generation sequencing in pest (2014). Methods in virus diagnosis is recommended since it has diagnostics: from ELISA to next the potential of eliminating ambiguity. generation sequencing. Virus Virus containment in areas of detection research. 186, pp. 20-31. is encouraged. Benson, D. A., Cavanaugh, M., Clark,

Acknowledgement K., Karsch-Mizrachi, I., Lipman, This work was funded by The royal D.J., Ostell, J. & Sayers, E.W. society of UK. The sequencing was (2013). GenBank. Nucleic Acids done at FERA Science (UK) and analysis Research. 41, pp. 36–42. done at James Hutton Institute (JHI). Bertioli, D. J., Cannon, S. B., Froenicke,

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Maize Head Smut: Pathogenesis, Epidemiology, and Management Options Chemeltorit, P.1* and Suresh, L.M2.

1Kenya Plant Health Inspectorate Service (KEPHIS)

2International Maize and Wheat Improvement Center (CIMMYT), P.O. Box 1041 Village Market-00621, Nairobi.

*Corresponding Author: [email protected]

Abstract

Maize (Zea mays) head smut caused by Sphacelotheca reiliana, a basidiomycete with worldwide distribution, can cause devastating crop losses that pose a food security threat. While Kenya has experienced high incidences of the disease in the recent years, the seed certification regulation has a zero tolerance on S. reiliana. The spores of S. reiliana remain viable in soil for many years and serve as the main inoculum source as they germinate when the conditions are favourable and infect the host in the early stages of growth after germination. After penetration, the fungus grows systemically as the plant matures eventually transforming part or all of the inflorescence (ears and tassels) tissues into smut galls. The symptoms develop because the inflorescences have increased levels of reactive oxygen species, auxin, and misregulation of floral regulatory transcription factors. The most practical control strategy for maize head smut encompasses the use of resistant/tolerant cultivars, fungicide treatment (of seed or drenching of rows immediately after seeding), and field hygiene/ sanitation. Crop rotation may help when host crops are not planted for between 2-3 years or even more. Resistance genes, including ZmWAK, found in the major quantitative trait locus qHSR1/qHS2.09 regulate resistance of maize to head smut. The objective of this review paper is to provide an understanding of the head smut disease pathogenesis, epidemiology, and effective management options.

Key words: Sphacelotheca reiliana, basidiomycete, seed certification, smut galls, resistance gene

Introduction

Being the most important cereal crop in in maize and sorghum determine sub-Saharan Africa, Maize (Zea mays) specificity of host (Poloni & Schirawski, is Kenya’s staple crop with annual 2016; Zuther et al., 2012). S. reiliana production steadily increasing over the reproduces sexually. One study last ten years, despite the area under (Schirawski et al., 2005) described two production not changing significantly mating type loci of S. reiliana as triallelic (FAOSTAT, 2018). Pest and diseases ‘a’ and multiallelic ‘b’. Each of the ‘a’ loci remain the main challenge to maize is composed of two pheromone genes production and yield. Maize is affected where only one mating partner by two types of smut diseases: head specifically recognizes each smut caused by Sphacelotheca reiliana pheromone. (J. G. Kühn) G. P. Clinton [syn. In severe cases, maize head smut can Sporisorium reilianum], and common cause up to 80% yield loss smut caused by Ustilago maydis (DC.) (Frederiksen, 1977). The severity Corda. The head smut pathogen, S. depends on the incidence since no reiliana, is a destructive soil borne viable kernels are produced by maize basidiomycete of the ustilaginaceae plants that are infected (Jackson-Ziems, family and has a worldwide distribution. 2014). This is why maize head smut S. reiliana is biotrophic (Martinez et al., needs to be urgently and effectively 2002; Mohan et al., 2013) with systemic managed. infection occurring in the very early stages of growth while the plant is in The Kenyan Seed and Plant Varieties the seedling phase (Kosiada, 2011). S. Act (Cap 326) lists S. reiliana as a reiliana has two formae speciales which significant pathogen in seed production are host specific, one infecting maize systems and places a zero tolerance on only while the other infecting sorghum it during the final inspection of a maize (Martinez et al., 1999; Poloni & seed crop that is due for seed Schirawski, 2016). Distinct mechanisms certification. In August 2016, four counties of Kenya (Nandi, Elgeyo 64

Marakwet, Trans Nzoia, and Uasin Most of the affected counties have the Gishu) reported high incidences of head favourable climatic conditions (average smut in maize. According to a soil temperatures of 28 °C and surveillance (report unpublished) moderate to low soil moisture) for carried out by the Nakuru County Early seedling infection. Figure 1 represents Warning and Rapid Response Team, led the situation of infection in one of the by KEPHIS, in September 2019, Nakuru visited farmers’ fields during the County reported increased cases of the surveillance. disease, especially in Njoro sub-county.

Smutted tassels

Figure 1: - High incidences of head smut in a maize field in Njoro, Nakuru County (September 10, 2019). All the infected plants are unproductive.

One of the findings of the surveillance farmyard manure were used in the was that in the previous cropping following season. Such practices may seasons, most farmers had fed infected have contributed to the increased maize debris to cows and the resulting disease epidemics in the following

seasons. With maize being Kenya’s objective of this review paper is, staple food crop, outbreaks of head therefore, to provide a concise outline smut can spell a food security crisis of head smut pathogenesis, hence the need to understand the epidemiology, and management pathogen and disease dynamics. The options.

Disease cycle and symptoms and the maize root entails the formation of a fungal sheath around the root Spores from smutted inflorescence are tissue (Martinez et al., 2000) which easily dispersed by wind and rain and facilitates penetration whereas the can remain viable in soil for up to four initial infection of seedling is promoted years (Mohan et al., 2013) hence by delayed rains (Jackson-Ziems, serving as the main source of inoculum. 2014). Following an infection of a maize The germination of the S. reiliana seedling, the fungus passes through the spores in soil tend to be high in acidic host cell wall by lysis and mechanical soils. Under favourable conditions pressure (Martinez et al., 1999). The (acidic soils, moderate to low soil infective hyphae mainly grow moisture, and warm temperatures of intracellularly and systemically between 23-30°C), the spores advances through the plant tissues, germinate into infective hyphae which eventually transforming part or all of penetrate the roots of seedlings before the inflorescence tissues into smut they reach the six-leaf growth stage galls. Head smut then portrays on (Jackson-Ziems, 2014; Martinez et al., maize ears and tassels as galls, which 2002; Mohan et al., 2013). The initial later mature and sporulate to restart contact between the infective hyphae another disease cycle.

Figure 2. Symptoms of head smut disease on maize; (a) sori with teliospores and finger or wire-like proliferations on maize ear, (b) black mass of fungal teliospores on tassel, (c) malformation of the tassel and ear lacking silks.

Infected ears have rounded or pear- though infected, the vegetative tissues shaped smuts and lack silks whereas of maize do not show any symptoms infected tassels turn into leafy and may appear healthy (Martinez et structures with smutted spikelets al., 1999) and thus mycelia in crop (Jackson-Ziems, 2014; Mohan et al., residue can serve as inoculum source in 2013). In the early stages of ear the following crop season (Anderson et development, these galls have a thin al., 2016). membrane that ruptures to expose dry, Disease Management powdery, dark brown to black masses of teliospores (Mohan et al., 2013). The The increase in maize head smut presence of fine, thread-like strands occurrence and incidences over the within the galls are remnants of the years can be attributed to the infected and damaged vascular tissue continuous mono-cropping, use of of the plant (Mohan et al., 2013). The susceptible varieties, misuse of seed symptoms develop because maize coating agents and change in weather inflorescences (ears and tassels) that patterns (Li et al., 2015). These factors are infected by S. reiliana have have contributed to the availability of increased levels of ROS (reactive favourable conditions (acidic soils, oxygen species) and auxin, and moderate to low soil moisture, and misregulation of floral regulatory warm temperatures of between 23- transcription factors (Ghareeb et al., 30°C) for infection and disease 2011). It is important to note that even proliferation. It is important to point out

that there are no curative measures for may not have a direct connection with maize head smut and thus the only the quality of the seed, as long as the available options are preventive as seed is certified. described in the following paragraphs. Fungicide treatment – This is achieved The use of resistant varieties - The by either seed dressing or by soil resistance of maize to S. reiliana has drenching, before or after seeding. received some remarkable attention Because S. reiliana is biotrophic in through studies in the recent years and behaviour, systemic fungicide has been found to be quantitative and treatment will be effective if their mode mostly additive (Anderson et al., 2016). of action will inhibit mycelial growth Two quantitative trait loci, and/or sporogenesis, at least until floral qHSR1/qHS2.09/q2.09HR (Konlasuk et induction occurs (Martinez et al., 1999). al., 2015; Li et al., 2015; Weng et al., Some of the active ingredients that are 2012) and q5.03HR (Li et al., 2015), effective in reducing S. reiliana have been described as responsible for infection, even at low application rates, head smut resistance and is useful in are tebuconazole, fludioxonil, sedaxane marker assisted resistance for breeding (Anderson et al., 2015), propiconazole, programs. The resistance is conferred and fiutriafol combined with imazalil by the ZmWAK gene which is found in sulphate (Wright et al., 2006). Most of the qHSR1 locus (Konlasuk et al., 2015; these molecules belong to the azole Zhao et al., 2012; Zuo et al., 2015). The group to which resistance development genome-wide association study by fungi is rare and whose mode of (GWAS) by Wang et al., (2012) action is inhibition of the synthesis of illustrated that resistance to head smut ergosterol hence loss of cell membrane entails complex molecular interactions. integrity. In Kenya, two maize varieties, KH500- Cultural methods – This is best 21A and PAN3M05, have been listed as achieved by deep ploughing and resistant to head smut whereas WH699 rotation with non-host crops to reduce is recorded as tolerant to smut, S. reiliana inoculum in soil and although the causative agent of the consequently lower disease incidences. referred smut is not specified. Farmers For effective application, the rotation must use certified seed in order to cycle should be at least 2-3 years utilize the variety resistance. Whenever (Mohan et al., 2013) without maize, there are high head smut disease sorghum, and any other grasses that incidences in Kenya, farmers always serve as alternative sources of blame the seed they used. This could inoculum. Additionally, rogueing of be true because the cultivar they infected plants and ensuring field planted is susceptible to S. reiliana but

sanitation to rid the field of crop residue by ensuring a clear understanding of will reduce inoculum load and thus a the disease pathogenesis (biology, good management strategy. infection mechanisms, and symptoms) and epidemiology (spread in time and Conclusion space). The maize head smut disease has a References worldwide distribution. Disease incidences occur sporadically especially Anderson, S. J., Simmons, H. E., in high altitude areas and is associated French-Monar, R. D., & Munkvold, with soils with nitrogen deficiency G. P. (2016). Susceptibility of (Mohan et al., 2013), which means that maize inbreds and incidence of it is difficult to predict its occurrence symptomless infection by the head during a cropping season. Whereas smut pathogen, Sphacelotheca head smut disease incidence reiliana. Plant Health Progress. 17 (percentage of infected plants in a crop (1), pp. 1–5. field) can reach 80%, disease severity Anderson, S. J., Simmons, H. E., & in terms of yield loss is 100% because Munkvold, G. P. (2015). Real-time infected plants are not productive. PCR assay for detection of Infections are favoured by acidic soils, Sphacelotheca reiliana infection in moderate to low soil moisture, and Maize (Zea mays) seedlings and warm temperatures. The most practical evaluation of seed treatment management strategy for maize head efficacy. Plant Disease. 99 (12), pp. smut, therefore, integrates the use of 1847–1852. resistant/tolerant cultivars, seed treatment and/or drenching of sown Frederiksen, R. A. (1977). Head smuts rows and observing field of corn and sorghum. Proceedings hygiene/sanitation. It is important to of Corn Sorghum Resesearch note that while cultural methods such Conference. 32, pp. 89–104. as crop rotation are useful, they cannot limit disease incidence because spores Ghareeb, H., Becker, A., Iven, T., remain viable for long periods. Feussner, I., & Schirawski, J. (2011). Sporisorium reilianum Recommendation infection changes inflorescence and branching architectures of Even though maize head smut can maize. Plant Physiology. 156 (4), cause massive crop losses, there are pp. 2037–2052. practical options for its management. Phytosanitary challenges associated Jackson-Ziems, T. A. (2014). Smut with maize head smut can be reduced Diseases of Corn. NebGuide.

http://extensionpublications.unl.e 253. du/assets/pdf/g2223.pdf Martinez, C., Roux, C., Jauneau, A., & Konlasuk, S., Xing, Y., Zhang, N., Zuo, Dargent, R. (2002). The Biological W., Zhang, B., Tan, G., & Xu, M. Cycle of Sporisorium reilianum f.sp. (2015). ZmWAK, a quantitative zeae: An Overview Using resistance gene to head smut in Microscopy. Mycologia. 94, pp. maize, improves yield performance 505–514. by reducing the endophytic Mohan, S. K., Hamm, P. B., Clough, G. pathogen Sporisorium H., & Toit, L. J. (2013). Corn reiliana. Molecular Breeding. 35 Smuts. (8), pp. 174. Poloni, A., & Schirawski, J. (2016). Host Kosiada, T. (2011). In vitro influence of specificity in Sporisorium reilianum selected fungicides on is determined by distinct Sphacelotheca reiliana and mechanisms in maize and Ustilago maydis. Journal of Plant sorghum. Molecular Plant Protection Research. 51 (4), pp. Pathology. 17 (5), pp. 741–754. 342–348. Schirawski, J., Heinze, B., Li, Y., Wu, X., Jaqueth, J., Zhang, D., Wagenknecht, M., & Kahmann, R. Cui, D., Li, C., Hu, G., Dong, H., (2005). Mating type loci of Song, Y., Shi, Y., Wang, T., Li, B., Sporisorium reilianum: Novel & Li, Y. (2015). The Identification pattern with three a and multiple b of Two Head Smut Resistance- specificities. Eukaryotic Cell. 4 (8), Related QTL in Maize by the Joint pp. 1317–1327. Approach of Linkage Mapping and Association Analysis. Plos One. 10 Wang, M., Yan, J., Zhao, J., Song, W., (12), e0145549. Zhang, X., Xiao, Y., & Zheng, Y. (2012). Genome-wide association Martinez, C., Jauneau, A., Roux, C., study (GWAS) of resistance to Savy, C., & Dargent, R. (2000). head smut in maize. Plant Science. Early infection of maize roots by 196, pp. 125–131. Sporisorium reilianum f. sp. zeae. Protoplasma. 213(1-2), pp. 83–92. Weng, J., Liu, X., Wang, Z., Wang, J., Zhang, L., Hao, Z., Xie, C., Li, M., Martinez, C., Roux, C., & Dargent, R. Zhang, D., Bai, L., Liu, C., Zhang, (1999). Biotrophic development of S., & Li, X. (2012). Molecular Sporisorium reilianum f. sp. zeae in mapping of the major resistance vegetative shoot apex of maize. quantitative trait locus qHS2.09 Phytopathology. 89 (3), pp. 247– 70

with simple sequence repeat and Tan, G., Li, B., Xing, Y., Zhang, B., single nucleotide polymorphism Liu, H., Fengler, K. A., Zhao, J., markers in Maize. Phytopathology. Zhao, X., Chen, Y., Lai, J., Yan, J., 102 (7), pp. 692–699. & Xu, M. (2015). A maize wall- associated kinase confers Wright, P. J., Fullerton, R. A., & quantitative resistance to head Koolaard, J. P. (2006). Fungicide smut. Nature Genetics. 47 (2), pp. control of head smut (Sporisorium 151–157. reilianum) of sweetcorn (Zea mays). New Zealand Journal of Zuther, K., Kahnt, J., Utermark, J., Crop and Horticultural Science. 34 Imkampe, J., Uhse, S., & (1), pp. 23–26. Schirawski, J. (2012). Host specificity of Sporisorium reilianum Zhao, X., Tan, G., Xing, Y., Wei, L., is tightly linked to generation of the Chao, Q., Zuo, W., Lübberstedt, T., phytoalexin luteolinidin by & Xu, M. (2012). Marker-assisted sorghum bicolor. Molecular Plant- introgression of qHSR1 to improve Microbe Interactions, 25 (9), pp. maize resistance to head smut. 1230–1237. Molecular Breeding, 30(2), pp. 1077–1088.

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New scale insect country records for Kenya (Hemiptera: Coccomorpha) from old samples in insect collections Watson G. W. 1*, Ouvrard D.2, Kasina M.3, Achieng J.C.4, Githae M.M.5, Mulwa J.3, Kinuthia W.4, Macharia I.6, Heya H.M6, Polaszek A.1 1Department of Life Sciences, the Natural History Museum, Cromwell Road, London SW7 5BD, U.K. 2Anses, Laboratoire de la Santé des Végétaux, 755 avenue du campus Agropolis CS 30016, FR-34988 Montferrier-sur-Lez Cedex, France. 3Kenya Agriculture and Livestock Research Organisation, P.O. Box 57811-00200, Nairobi, Kenya. 4National Museums of Kenya, P.O. Box 40658-00100, Nairobi, Kenya. 5School of Biological Sciences, College of Biological and Physical Sciences, University of Nairobi, P.O. Box 30197-00100, Nairobi, Kenya. 6Kenya Plant Health Inspectorate Service, P.O. Box 49592-00100, Nairobi, Kenya. *Corresponding author: Email: [email protected]

Abstract Scale insects (Hemiptera: Sternorrhyncha: Coccomorpha) are some of the least understood insects, particularly in agriculture, even though they can cause high crop losses. Due to their small size and cryptic habits they are rarely noticed at the onset of an infestation. In Kenya, efforts have been initiated to understand these pests better. Scale insects from Kenya, found in samples between 13 and 107 years old, were studied in the insect collections of the Natural History Museum, London, U.K. and the Kenya Agriculture and Livestock Research Organisation, Nairobi, Kenya. The study identified 51 new country records of scale insects including one new continental record for Africa, Ferrisia dasylirii (Cockerell) (Pseudococcidae). Of the new records, 35 species (68.6%) are native to Africa and 16 (31.4%) have been introduced from elsewhere. Six of the 51 species (11.8%) are pests in Kenya today. Amongst the introduced species, at least one (Aonidiella comperei McKenzie) could cause plant quarantine issues in trade, and four (25.0%) are pests, more than four times the frequency of pests amongst the African species (5.7%). The remaining 45 species have been present in Kenya for at least 13 years and many have not been collected again since the original samples, suggesting that either they have not survived or they

are rare because they are under good natural control. Most of the introduced species listed (75.0%) have not caused economic problems in Kenya to date, so it is thought unlikely that they will do so in the future.

Key words: Scale insects, introduced species, native species Introduction As part of the Darwin Initiative-funded Specimens in old insect collections project 25-032: “Agriculture and provide evidence of the species that biodiversity: addressing scale insect were established in a country or region threats in Kenya”, old scale insect slide at a specific date. Review of historic mounts in two important insect insect collections can reveal new collections were studied. The collection country records and early distribution at the Kenya Agriculture and Livestock records of species that have never been Research Organisation (KALRO) recorded in the literature: for example, National Agricultural Research study of the Wirjati collection in Laboratory (KALRO-NARL) at Kabete, Indonesia (containing material collected Nairobi, Kenya contains samples mostly 1916-1960) revealed three new collected between 1920 and 1970. Indonesian country records of Giovani De Lotto worked at this mealybug species (Sartiami et al., laboratory between 1950 and 1963 2016), and study of Takahashi slides (Ben-Dov & Russo, 1991) and greatly from Malaysia (containing material enlarged the scale insect slide collected 1943-1944) revealed the collection; the 3,597 slides were re- earliest known Malaysian records of two curated and databased during this mealybug species (Sartiami et al., work. The collection at the Natural 2017). Such baseline information History Museum, London, U.K. provides clarification of which non- (NHMUK) contains samples mostly native species have been accidentally collected between 1910 and 2000, introduced in more recent times including the type material of many (Sartiami et al., 2016, 2017). species. Study of Kenyan material in these collections has revealed multiple

unpublished first country records for collections of some of the species as Kenya and one new continental record evidence that they are still present in for Africa. Here we document these new the country. records, and provide data on recent

Materials and methods followed by data from recently collected Old samples of scale insects on slide- material where available. Species likely mounts in the KALRO-NARL and NHMUK to have been introduced from outside collections were studied using a Zeiss continental Africa are marked with an Axiophot compound light microscope asterisk (*); those known to be native with phase contrast illumination and to Africa are marked with a dagger (†). magnifications of 25x-800x. Species New host-plant records are indicated by identities were checked using the most N. Collectors’ names are provided where recently published identification keys known. Recent samples from the available (listed in Table 1), together present Darwin Initiative project are with unpublished keys being developed represented by slides that will be by the first author (GW) as part of the deposited in both the KALRO-NARL and Darwin Initiative project. Specimens NHMUK collections. Some recent were also compared to type material material will be deposited also in the when it was available. To assess which collections at the National Museums of of the species identified had never been Kenya, Nairobi, Kenya (NMK); recorded from Kenya in the literature, a University of Nairobi, Nairobi, Kenya list compiled from the old collections (UoN); and Kenya Plant Health was compared with a list searched Inspectorate Service, Muguga, Kenya online from the ScaleNet database (KEPHIS). (García Morales et al., 2016), which is based on the literature, particularly De Lotto’s publications. For each species, collection data are given for the historic samples first,

Table 1. References used for identification of scale insect slide mounts from Kenya in the collections at KALRO and NHMUK. The references are in chronological order so that it is evident which is the most up-to-date.

Scale insect Identification aid resources family Aclerdidae Howell & Williams (1976), Ben-Dov (1977), Gill (1993), Hodgson & Millar (2002), Miller et al. (2014) Asterolecaniidae Russell (1941), Giliomee & Munting (1968), Howell & Williams (1976), Kosztarab & Kozár (1988), Williams & Watson (1990), Gill (1993), Kosztarab (1996), Stumpf & Lambdin (2001, 2006), Giliomee & Kozár (2008), Miller et al. (2014) Cerococcidae Howell & Williams (1976), Lambdin & Kosztarab (1977), Williams & Watson (1990), Gill (1993), Kosztarab (1996), Miller et al. (2014), Hodgson & Williams (2016) Coccidae Hall (1925), Laing (1929), De Lotto (1954a, 1955, 1956a, 1956b, 1957a, 1957b, 1958a, 1958b, 1959a, 1960, 1961b, 1962, 1963, 1964b, 1965, 1966a, 1966b, 1966c, 1967b, 1969a, 1970, 1971, 1974a, 1975b, 1978, 1979), Hodgson (1967a, 1994), Howell & Williams (1976), Nakahara & Gill (1985), Kosztarab & Kozár (1988), Williams & Watson (1990), Gill (1988, 1993), Kosztarab (1996), Hodgson & Henderson (2000), Miller et al. (2014), Łagowska & Hodgson (2019) Conchaspididae Mamet (1954), Hodgson (1967b), Howell & Williams (1976), Ben-Dov (1981), Williams & Watson (1990), Gill (1993), Miller et al. (2014) Dactylopiidae Karny (1972), De Lotto (1974b), Howell & Williams (1976), Williams & Watson (1990), Gill (1993), Miller et al. (2014) Diaspididae Ferris (1937, 1938, 1941, 1942), Hall (1946), Balachowsky (1956, 1958), Mamet (1958), Williams (1963), Howell & Williams (1976), Tang (1986), Kosztarab & Kozár (1988), Ben-Dov (1988), Williams & Watson (1988a), Danzig (1993), Gill (1993, 1997), Kosztarab (1996), Watson (2002), Miller & Davidson (2005), Miller et al. (2014), Schneider et al. (2019) Eriococcidae Howell & Williams (1976), Kosztarab & Kozár (1988), Williams & Watson (1990), Gill (1993), Kosztarab (1996), Kozár et al. (2013), Miller et al. (2014) Halimococcidae Stickney (1934), Williams & Watson (1990), Miller et al. (2014) Kermesidae Howell & Williams (1976), Bullington & Kosztarab (1985), Gill (1993), Miller et al. (2014) Kerriidae Howell & Williams (1976), Varshney (1984, 1990), Williams & Watson (1990), Gill (1993), Kondo et al. (2011), Miller et al. (2014) Kuwaniidae Morrison (1928), De Lotto (1959b), Gill (1993), Hodgson & Foldi (2006), Miller et al. (2014)

Lecanodiaspididae De Lotto (1955), Hodgson (1973), Howell & Williams (1976), Williams & Watson (1990), Gill (1993), Miller et al. (2014) Table 1: Continued from previus page Scale insect Identification aid resources family Margarodidae Morrison (1928), de Klerk (1982a, 1982b, 1983), Foldi (2005a), Vahedi & Hodgson (2007) Matsucoccidae Boratynsky (1952a, 1952b), Gill (1993), Foldi (2005b), Miller et al. (2014) Micrococcidae Miller & Williams (1995), Miller et al. (2014) Monophlebidae Morrison (1928), De Lotto (1959b), Gill (1993), Kosztarab (1996), Kosztarab & Kozár (1988), Unruh & Gullan (2008), Foldi (2010), Miller et al. (2014) Ortheziidae Morrison (1925, 1952), Howell & Williams (1976), Kosztarab & Kozár (1988), Williams & Watson (1990), Gill (1993), Kosztarab (1996), Kozár & Konczné Benedicty (2000, 2001), Kozár et al. (2002), Miller & Kozár (2002), Kozár (2004), Kondo et al. (2013), Miller et al. (2014) Phoenicococcidae Howell & Williams (1976), Gill (1993), Miller et al. (2014) Pseudococcidae James (1935), Ferris (1950, 1953), De Lotto (1954b, 1955, 1957c, 1958c, 1961a, 1964a, 1964c, 1967a, 1969a, 1969b, 1974c, 1975a), Ezzat & McConnell (1956), Williams (1958a, 1958b, 1961, 1970, 1986, 1996, 1998, 2001, 2004), Ezzat (1960, 1962), Balachowsky & Matile-Ferrero (1966), McKenzie (1967), Matile-Ferrero (1970), Howell & Williams (1976), Cox (1987, 1989), Kosztarab & Kozár (1988), Williams & Watson (1988b), Watson & Cox (1990), Williams & Granara de Willink (1992), Kosztarab (1996), Williams & Matile-Ferrero (1999, 2005), Granara de Willink & Szumik (2007), Schneider & LaPolla (2011), Miller & Giliomee (2011), Kaydan & Gullan (2012), Miller et al. (2014) Putoidae Gill (1993), Miller et al. (2014) Rhizoecidae Hambleton (1976), Kosztarab (1996), Kozár & Konczné Benedicty (2007), Miller et al. (2014) Stictococcidae Richard (1976), Williams et al. (2010), Miller et al. (2014)

Results oppositaN, 20.v.1988, coll. J.H.

The scale insect species below Martin (NHMUK). were found in the KALRO-NARL, †A soft scale, Coccus sp. near cajani NHMUK and NMK collections. According (Newstead): Kenya: Kiambu Co., to the ScaleNet database (García Kikuyu, on Acacia mearnsii, v.1974 Morales et al., 2016) they have not (NHMUK); Nairobi County, been recorded from Kenya in the Waithaka, on Cajanus sp., coll. literature before. Alice, 19.vi.1977 (NHMUK). †A soft scale, Coccus milanjianus Family Coccidae (13 species) Hodgson: Kenya, Kikuyu, on †A wax scale, Ceroplastes ficus Elaeodendron (=Cassine) N Newstead: Kenya, Nairobi, buchananii , v.1974 (NHMUK). National Museums of Kenya, †A soft scale, Inglisia theobromae Biodiversity Centre, on shrubs and Newstead: Kenya: Limuru, on N trees, coll. G.W. Watson, 5.x.1996 Pelargonium sp., 16.i.1963, coll. (NHMUK). G. De Lotto (NHMUK); Kikuyu, on N †A wax scale, Ceroplastes Acacia mearnsii , v.1964 N quadrilineatus (Newstead): (NHMUK); Kikuyu, on Abutilon Kenya, Nairobi, on Ficus sp., coll. sp., v. 1974 (NHMUK); Nairobi, W.J. Hall, 26.iii.1949 (NHMUK). N.A.L., on cotton, 4.vii.1977, coll. †A wax scale, Ceroplastes P. Nderi (NHMUK). ?sinoiae (Hall): Kenya, on †A soft scale, Lagosinia vayssierei Coffea sp., coll. H.C. James, (Castel-Branco): Kenya, N [probably in the 1930s] (NHMUK). Kisumu, on Grewia sp., †A soft scale, Ceroplastodes 23.xi.1953 (NHMUK). zavattarii Belio: Kenya: Yatta †A soft scale, Pulvinaria merwei Plateau, Katangi, on ?Malvaceae, Joubert: Kenya, Kiambu Co., 6.viii.1977, coll. J.H. Martin Ruiru, on Ipomoea batatas, (NHMUK); Malindi, on Hoslundia 20.viii.1957 (NHMUK).

*Cottony citrus scale, Pulvinaria native to Africa; it is polyphagous polygonata (Cockerell): Kenya: and can cause significant Mombasa, on Mangifera indica, defoliation of woody hosts. 10.viii.1958 (NHMUK); Malindi, on Pulvinaria urbicola has a history of Mangifera indica, 25.iii.1961, coll. damaging native forests on small J.F. Graham (NHMUK). Recent: islands in the Pacific Ocean, Kilifi Co., Mtwapa, KALRO orchard, particularly if ants are present to S 3º 56’ 12”, E 39º 44’ 32”, 10 m attend it (Smith et al., 2004; Peck alt, on Mangifera indica, et al., 2014; Neumann et al., 10.vii.2019, coll. Extension officers 2014, 2016). (NHMUK, KALRO-NARL); Kwale *Iceplant scale, Pulvinariella Co., Lunga Lunga, S 4º 33’, E 39º mesembryanthemi (Vallot): 52’, 52 m alt., on Citrus sinensis, Kenya, Nairobi, on 28.viii.2019, Michael Githae Mesembryanthemum sp., (UoN). The species originated in 6.ix.1951 (NHMUK). The insect is southern Asia and is known to be native to South Africa; in California a pest of citrus. In the coastal in the absence of its natural counties of Kenya it is a pest on enemies, it can kill large areas of citrus, causing serious honeydew highway ice plant (Aizoaceae: and sooty mould fouling of leaves Carpobrotus edulis (L.) N.E. Br.) and fruits, impacting fruit quality. ground cover beside roads (Gill, *Urbicola soft scale, Pulvinaria 1993). No such damage has been urbicola (Cockerell): Kenya: recorded in Kenya in the literature Kwale, on roots of Capsicum sp., but ice plant is not widely used in 11.vi.1956 (NHMUK); Mombasa, amenity plantings there, possibly on roots of Solanum tuberosumN, because the scale makes them 8.xi.1956 (NHMUK); Mombasa, on unsightly. Capsicum sp., 10.vii.1957 †Giant soft scale, Pulvinarisca (NHMUK). The species is of inopheron (Laing): Kenya: unknown origin but probably is not Chogoria, on Cajanus indicusN,

4.x.1937, coll. A.R.M. (NHMUK); 39ᵒ 44' 32", 10 m alt., on Citrus Nairobi, on Croton manostachys, sp. leaf undersides, coll. Extension 16.ix.1951 (NHMUK); Nairobi, on Officers, 10.vii.2019, 2 samples; Chaetacme aristataN, 29.x.1953 Mtwapa, S 3.93717˚, E 39.7424, (NHMUK); Nairobi, on Salvia sp., 169 m alt., on Citrus sinensis, coll. 7.vi.1954 (NHMUK). Recent: M.M. Githae, 12.xii.2019 and Kenya, Central Province, Muguga, 13.xii.2019; Malindi, S 3.27643˚, on small farm, on Caliandra E 40.01251˚, 139 m alt., on C. carobensisN, 15.vii.2018, coll. G. sinensis, coll. M.M. Githae, Opondo (NHMUK, KALRO-NARL). 12.x.2019; Malindi, S 3.27442˚, E In Kenya, this species forms very 40.04494˚, 166 m alt., on C. heavy infestations on Calliandra sinensis, coll. M.M. Githae, grown for animal fodder. Each 12.x.2019; Kwale County: adult female may be up to two cm Matunga, S 4.27996˚, E long and produces a conspicuous 39.56794˚, 68 m alt., on C. large white ovisac. sinensis, coll. M.M. Githae, 25.viii.2019; Ukunda, S 4.28601˚, Family Diaspididae (23species) E 39.5284˚, 63 m alt., on C. †An armoured scale, Africaspis sinensis, coll. M.M. Githae, communis (Hall): Kenya, 14.xii.2019; Njego, S 4.65341˚, E Nairobi, on fig, 26.iii.1949, coll. 39.1998˚, 53 m alt., on C. W.J. Hall; Eldoma Ravine, on sinensis, coll. M.M. Githae, stems of shrub, 25.ii.1970, coll. 16.xii.2019; Botela, S 4.5809˚, E E.S. Brown (NHMUK). 39.10918˚, 45 m alt., on C. limon, *False yellow scale, Aonidiella coll. M.M. Githae, 16.xii.2019. comperei McKenzie: Kenya: Worldwide, this species has been Pemba Island, host not noted, recorded on host-plants in 12 coll. Anderson, pre-1962. families including species of Recent: Kilifi County, Mtwapa, Citrus, Annona and other fruit KALRO orchard, S 3˚ 56' 12", E trees, Cocos nucifera, Carica

papaya, Musa sp. and Vitis vinifera Balachowsky (1958) recorded it and may have a wider host range previously from Tanzania and (Williams & Watson, 1988; remarked that it has a preference Watson, 2002; García Morales et for citrus. In Kenya it was found al., 2020). Aonidiella comperei on citrus and may have the secretes a circular, flat, yellow- potential to become a citrus pest. brown scale cover that is often Its presence on exported fruit closely attached to the insect could cause plant quarantine beneath. The anterior part of the issues in trade. adult female expands with *Aglaonema scale, Aspidiotus maturity to become kidney- ?excisus Green: Kenya, Siaya shaped, forming postero-lateral County, on Lantana camara, coll. lobes that lie alongside the smaller Prof. Odihambo, 6.iv.1990. These abdomen, and becomes hard and specimens differ from typical A. brown (like A. aurantiae excisus by having median lobes (Maskell)). Mounted on a with basal scleroses. Recent: microscope slide, the adult female Mombasa Co., Likoni, S 4.0948ᵒ, E A. comperei has the pygidial 39.64874ᵒ, 142 ft alt., on venter with one small group of Capsicum frutescens leaf, coll. W. perivulvar pores on either side of Kinuthia, J. Achieng, 20.ii.2020. the vulva, and lacks prevulvar CHECK for scleroses Aglaonema scleroses and apophyses scale has been intercepted from (whereas A. aurantiae lacks Africa (Mozambique) at plant perivulvar pores but has paired quarantine in South Korea (Suh, prevulvar scleroses and 2016). The species is considered apophyses). Aonidiella comperei to be a pest of ornamental plants probably originated from tropical (Davidson & Miller, 1990). Asia, but has been spread to other †Fried egg scale, Aspidiotus continents through the movement ?ruandensis Balachowsky: of infested live plant material. Kenya, Kericho County: Kericho,

on Camellia sinensisN, 2.iii.1967; number of submarginal Nakuru, on Camellia sinensis, coll. prepygidial macroducts. Molecular G.W. Oloo, 30.x.1972; Kericho, on analysis of material representing Ca. sinensis, coll. V. Sudoi, these two scale-cover colours iv.1986; Kiambu County: Kiambu, would resolve whether there is on Coffea arabicaN, coll. J.W. more than one species involved. Waikwe, 10.vii.1978; Kiambu, Fried egg scale may have been Makana Estate, on Co. arabica, introduced to Kenya from further coll. R.H. Markham, 18.iv.1983; west; it has been present in the Ruiru, on Co. arabica leaves, country since at least 1967. It ?1991; Ruiru, Ruara Estate, on Co. occurs on shade trees in Kenyan arabica, coll. G.W. Watson, beverage crop plantations; in dry viii.1993; Ruiru, Ruara Estate, conditions it spreads onto the 1500 m asl,, on Co. arabica, coll. foliage of coffee bushes, T.J. Crowe, 29.iv.1994; Kwale sometimes becoming a pest (T.J. County: Diani forest, on Diospyros Crowe, pers. comm. 1994). The squarosaN, 17.x.1983 (NHMUK). sample data above and in García This is a native African species; Morales et al. (2016) indicate that there is some uncertainty about its it is relatively polyphagous on tree identity because when A. foliage, including fruit trees. ruandensis was described from *Cactus scale, Diaspis echinocacti Rwanda (Balachowsky, 1955), the (Bouché): Kenya, Nairobi, on scale cover was described as light Diospyros abyssinicaN, coll. G. De grey-brown with a yellowish cast, Lotto, 28.iii.1956 (KALRO-NARL). and with dark exuviae; whereas †Mango scale, Duplachionaspis specimens in Kenya have white natalensis (Maskell): Kenya, scale covers with yellow exuviae. Machakos, on Panicum However, the morphology coloratumN, 9.v.1950 (KALRO- supports the material representing NARL). a single species with a variable

†An armoured scale, Hemiberlesia Odonaspis, and has been recorded mammillaris (Lindinger): damaging lawn grass in Egypt and Kenya, Magadi, on Aloe sp., Israel, and forage and turf grasses 29.vii.1956 (KALRO-NARL). in the southern U.S.A. and Chile † An armoured scale, Hulaspis (Watson, 2002). dombeyae (Hall): Kenya, *Paragrass scale, Odonaspis Kikuyu, on Dombeya goetzenii, saccharicaulis (Zehntner): v.1974 (NHMUK). Kenya, on roots of lemon grass, †An armoured scale, Lindingaspis coll. F.S. Notley, 28.v.1935; British musae (Laing): Kenya, Ruiru, on East Africa, Kenya, on roots of Syzygium cordatumN, 31.x.1953 lemon grass (Andropogon sp.), no (KALRO-NARL). date; Ramisi, on sugarcane, †An armoured scale, Morganella 8.xi.1971, coll. G.W. Oloo conspicua (Brain): Kenya, (NHMUK). The species can be a Kajiado, on CommiphoraN sp., pest of sugarcane in India. 10.vi.1956 (KALRO-NARL). *Parlatoria date scale, Parlatoria †An armoured scale, Morganella blanchardi (Targioni spinigera (Lindinger): Kenya, Tozzetti): Kenya, Turkana, on Nairobi, on Gelonium procerumN, date palm, coll. Smead, 8.xi.1971 18.iv.1953 (KALRO-NARL). (NHMUK). The scale is not native †Reed scale, Odonaspis phragmitis to Africa but probably originated in Hall: Kenya, Ruiru, on roots of the Middle East; it is a well-known Paspalum scrobiculatumN, pest of date palms. There are no 7.ii.1956 (KALRO-NARL). recent records, probably due to *Bermuda grass scale, Odonaspis lack of sampling in northern ruthae Kotinsky: Kenya, Nairobi, Kenya. on roots of Rhychelytrum repensN, *Boxwood scale, Pinnaspis buxi coll. G. De Lotto, 20.iv.1954 (Bouché): Kenya, Nairobi, Scott (KALRO-NARL). This is the most Agricultural Laboratory, on polyphagous species in Bauhinia purpurea, 26.ii.1951

(NHMUK); Nairobi, on Musa Kenya, on unknown plant, enseteN, 25.ix.1951 (KALRO- 7.x.2019, coll. J. Achieng (NMK). NARL). Ebeling (1959) recorded this †An armoured scale, Pseudaonidia species as a pest of lychee (Litchi baikeae Newstead: Kenya: chinensis, Sapindaceae) in Florida. Nairobi, on Chaetachme aristataN, There is no record of it causing 24.vi.1951 (KALRO-NARL); Thika, damage in Kenya. on Rawstonia usambaruensisN, †An armoured scale, Sclopetaspis 24.viii.1952 (KALRO-NARL). ?malawica Munting: Kenya, †An armoured scale, Kikuyu, on ‘Rwegethia’ [=Zehneria Pseudotargionia glandulosa scabra], v.1974 (NHMUK). (Newstead): Kenya, Magadi, on †An armoured scale, Umbaspis Acacia senegal, coll. R.W. Le spatulata (Hall): Kenya, Nairobi, Pelley, 6.viii.1951 (NHMUK); on Tulia simplicifoliaN, 10.iv.1953 Magadi, on Acacia sp., coll. G. De (KALRO-NARL). Lotto, 29.vii.1956 (KALRO-NARL). †An armoured scale, Rolaspis Family Eriococcidae (1 species) polypora Munting: Kenya, †A felt scale, Acanthococcus Sultan Hamud, 19.viii.1956 ?etbaicus (De Lotto): Kenya, N 01º (KALRO-NARL). 07’, E 35º 51’, on Acacia nilotica, †An armoured scale, Rolaspis 1.i.1987 (NHMUK). syrinx Williams: Kenya, Naivasha, on Acokanthera Family Kerriidae (1 species) schimperiN, 1.i.1953 (NHMUK). †A lac insect, Tachardina *Lychee bark scale, Rutherfordia ?brachystegiae (Hall): Kenya, major (Cockerell): Kenya, Buchuma N.W. of Mombasa, on Nairobi, on Ehretia sylvaticaN, twigs of Acacia nilotica, 16.v.1986 4.xi.1951, coll. G. de Lotto (NHMUK). (KALRO-NARL). Recent: Kenya, Nairobi, National Museums of

Family Lecanodiaspididae (1 Naromoru, on Asteraceae species) (=Compositae), 26.viii.1977, coll. †A false pit scale, Lecanodiaspis J.H. Martin (NHMUK). mimosae (Maskell): Kenya, †Podocarpus mealybug, Eastia Naivasha, on Acacia jouberti De Lotto: Kenya, Nyeri xanthaphloeaN, 9.viii.1970, coll. H. Province, on Podocarpus Schmutterer (NHMUK). ?gracilea, 27.ix.1982 (NHMUK). *A mealybug, Ferrisia dasylirii Family Monophlebidae (2 species) (Cockerell): Kenya: Kiambu, on †Spiny monophlebid, coffee, iv.1926, coll. T.W. Aspidoproctus ?tricornis Kirkpatrick (NHMUK); Central (Newstead): Kenya, Marigat, Province, Mitungu, 1,500 m alt., Loruk, on Acacia nilotica ssp. on TephrosiaN sp., viii.2007, coll. subalata, 6.vi.1990, coll. J. Dudutech 030907F (NHMUK). Marohasy (NHMUK). New continental record. The †A monophlebid, mealybug is of South American Pseudaspidoproctus fulleri origin. It is polyphagous and was (Cockerell): Kenya, Chiromo, on only identified recently because grass, 2.ii.1971, coll. H. Kaydan & Gullan’s (2012) revision Schmutterer (NHMUK). of the genus provided an identification key. Like F. virgata Family Pseudococcidae (10 species) (Cockerell), also present in Kenya, †Acacia mealybug, Acaciacoccus heavy infestations can cause hockingi Williams & Matile- honeydew and sooty mould Ferrero: Kenya, Lake Naivasha, fouling of foliage. lakeside, on whistling thorn *A mealybug, Ferrisia malvastra Acacia, 27.v.1988, coll. J.H. Martin (McDaniel): Kenya, Namanga, (NHMUK). on Abutilon mauritienseN, †A mealybug, Delottococcus 21.i.1961, coll. G. de Lotto phylicus (De Lotto): Kenya, (KALRO-NARL). The species is of

South American origin. Like the Arboretum, on buds of related species F. virgata CallistemonN sp. with ants, (Cockerell), also present in Kenya, 31.viii.1988, coll. J.H. Martin heavy infestations can cause (NHMUK); Nairobi Arboretum, on honeydew and sooty mould Clausena anisataN, 2.v.1988, coll. fouling of foliage. J.H. Martin (NHMUK). Recent: †A mealybug, Heliococcus sp. near Kilifi Co., Mtwapa, KALRO orchard, osborni Sanders: Kenya, Mt S 3º 56' 11", E 39ᵒ 44' 28", 14 m Kenya, on grass, coll. H. alt, on Psidium guajava, Schmutterer, 14.ii.1971 (NHMUK). 10.vii.2019, coll. Extension officers *Hall’s mealybug, Planococcus (NHMUK, KALRO-NARL). halli Ezzat & McConnell: Kenya, Planococcus minor is possibly of Nanyuki, on PistaciaN sp., Pacific origin and is highly 30.ix.1977, coll. O. Barton polyphagous, attacking many (NHMUK). The origin of this economically important plants; it polyphagous species is unknown; is sometimes ant attended. The hosts include yams, groundnuts, species is a fairly common pest on cassava, pigeon pea, sugarcane, crops including citrus in the coffee and citrus. The mealybug is coastal counties of Kenya, where it often intercepted at plant occurs much more frequently than quarantine inspection in the U.S.A. P. citri (Risso). on yam tubers from Nigeria (Cox, *Obscure mealybug, Pseudococcus 1989). viburni (Signoret): NHMUK: *Passionvine mealybug, Kiambu Co., on DaturaN sp., coll. Planococcus minor (Maskell): R.H. Le Pelley, 20.x.1929 Kenya: Kikuyu, on Jacaranda (NHMUK). Of unknown origin, this mimosifoliaN, v.1974 (NHMUK); species is highly polyphagous and Malindi, Msabaha Ag. Res. Station, there are many literature records on potato in storage, 5.iii.1987, of it being a pest on tree, field and coll. B.L. Parker (NHMUK); Nairobi glasshouse crops (García Morales

et al. 2016). No recent samples above are based on samples between have been seen from Kenya. 13 and 107 years old. While 35 †Short-legged mealybug, (68.6%) of these species are native to Vryburgia brevicruris Africa, 16 (31.4%) have been (McKenzie): Kenya, on roots of introduced accidentally from outside Bidens pilosaN, 5.iv.1930, coll. the continent (Table 2). Most of the H.C. James (NHMUK). introduced species had been recorded previously from some other part of Discussion Africa but there is one new continental The 51 new country records of scale record: Ferrisia dasylirii insect species for Kenya recorded (Pseudococcidae). Table 2. A breakdown of taxonomic, geographic origin and economic data for the new Kenya species records found in old samples.

Families No. No. No. No. Pests No. (in size gene spp. spp. spp. of Introduc species order) ra of from African ed pest with pest Africa outsid origin species potential n e origin Africa Diaspididae 18 23 15 8 1 2 3 Pseudococcidae 8 10 5 5 0 1 3 Coccidae 8 13 10 3 1 1 1 Monophlebidae 2 2 2 0 0 0 0 Eriococcidae 1 1 1 0 0 0 0 Lecanodiaspidi dae 1 1 1 0 0 0 0 Kerriidae 1 1 1 0 0 0 0 Totals 39 51 35 16 2 4 7

Six of the 51 species (11.8%) are trade, and four (25.0%) are pests pests in Kenya today (Tables 2 and (Aonidiella comperei, Odonaspis 3). Amongst the 16 introduced ruthae, Planococcus minor and species, at least one (Aonidiella Pulvinaria polygonata). This is more comperei) could cause plant than four times more than the quarantine issues in plant produce frequency of pests amongst the

African species (5.7%). Only two species lack specialist natural native African species recorded from enemies from their areas of origin. Kenya for the first time are pests: This may make them suitable for Pulvinarisca inopheron (Coccidae) classical biological control, since and Aspidiotus ?ruandensis many scale insects have host-specific (Diaspididae). The difference in pest parasitoids (Hymenoptera: frequency between these two groups Chacidoidea) in their native ranges. is probably because the introduced

Table 3. Newly recorded species in Kenya in this work, of economic importance or with pest potential: * = introduced, †=originating from Africa.

Family Pest species Potential pests Coccidae *Pulvinaria polygonata *Pulvinaria urbicola †Pulvinarisca inopheron Diaspididae *Aonidiella comperei *Odonaspis saccharicaulis †Aspidiotus ?ruandensis *Parlatoria blanchardi *Odonaspis ruthae *Rutherfordia major Pseudococcidae *Planococcus minor *Ferrisia dasylirii

since the original samples, suggesting The remaining 45 non-pest species (12 that either they have not survived or (26.7%) of them introduced) have been they are rare because they are under present in Kenya for at least 13 years. good natural control. Many have not been collected again Recommendations be suitable for classical biological In this small sample, introduced species control using specialist natural enemies were found to be almost three times from their areas of origin. There is need more likely to become agricultural pests for continued monitoring, awareness than native African species, probably creation on the biology, spread and due to the absence of specialist natural management of the pest in the enemies from their areas of origin. Once surveyed counties. identified, such introduced pests may

Acknowledgements possible by funding provided by the The authors would like to thank the United Kingdom’s Darwin Initiative Director General, KALRO, Nairobi, scheme, project 25-032, supported by Kenya, and Prof. Kenneth Norris, Head Department for Environment Food & of Life Sciences, the Natural History Rural Affairs (Defra), Department for Museum, London, U.K. for permission to International Development (DFID) and study the collections at their the Foreign and Commonwealth Office institutions. The study was made (FCO).

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Pest Incursions Pose a Serious Threat To Food Security and the Kenyan Economy

Macharia I.1, Koome F.1, Kosiom T.1, Munguti F.,1 Mukoye B.1, Kimani E1, Kimenju J.W.2 1 Kenya Plant Health Inspectorate Service (KEPHIS)-P.O BOX 49592, Nairobi

2 University of Nairobi Faculty of Agriculture, Department of Crop Production and Plant Protection, P.O. Box 29053, Nairobi.

Corresponding Author: [email protected]

Abstract

Although Kenya has a well-developed phytosanitary system to regulate introduction of plant and plant products, several pest incursions have been reported in the last two decades. The incursions have culminated in devastating impact on agriculture, biodiversity and the entire Kenyan economy. The objective of this review is to consolidate information on the pests involved, their distribution, estimate the economic losses associated with them and management measures in place. A total of 11 major pests and diseases namely Asian citrus psyllid (ACP), Bactrocera dorsalis, Banana xanthomonas wilt (BXW), Cassava brown streak disease (CBSD), Cassava mosaic disease (CMD), Fall army worm (FAW), Maize lethal necrosis disease (MLND), Papaya mealybug (PMB), Parthenium hysterophorus, potato cyst nematode (PCN) and tomato leaf miners (Tuta absoluta) have been reported in the last two decades. Some of the pests are persistent, invasive, vicious and fast spreading. For instance, the FAW has now spread to nearly all maize growing areas in Kenya in one year after the pest was first reported in 2017. The incursion pests are a major threat to food security, expensive to control and are a barrier to international market access. Integrated measures including improvement of diagnostic potential, increased pest and disease surveillance, improvement in rapid response and pest containment are needed in view of the dangers posed by incursion pests to the entire Kenyan economy whose mainstay is agriculture.

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Key words: Bactrocera dorsalis, maize lethal necrosis disease, Parthenium hysterophorus, Tuta absoluta

Introduction Agriculture is the backbone of the environment. Pest incursions has led to economies of many African countries development of international contributing over 30% of the GDP. phytosanitary measures which are Production has been significantly currently being used to prevent affected by pest and diseases some of introduction of quarantine pests or limit which have been introduced through the entry of regulated non-quarantine trade. International movement of plant pests while promoting international and plant produce has always been trade. regulated due to the risk of introduction Kenya, like any other African countries of pests and diseases. As a result of has not been spared from the effect of several serious pests having been introduction of new harmful pests and introduced in different countries in the diseases. Inadequate phytosanitary late 1800s, it was clear that there is need capacity in many African countries has to undertake action to prevent further been cited as important factors which introductions. For instance, the late could be contributing to introduction and blight in Ireland which left over 2 million spread of new pests and diseases. death due to starvation, the coffee leaf Additionally, lack of capacity in rust in Srinlanka introduced from Africa diagnostics has sometimes delayed seriously affected coffee production, In responses to emerging and endemic Africa, the outbreak of coconut yellow pathogens. Diagnostic tools might be lethal necrosis in Madagascar, and available for some diseases and pests, fusarium wilt of banana caused by strain but may not be applied in time to be TR4 in Mozambique are some of the effective. The widespread lack of examples of pests which have been equipment, supplies, reference materials reported to cause serious economic and opportunities for training hamper the damage to the agricultural sector and the

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ability of African scientists to provide before 1998 include Cassava mosaic these basic services and, further, to disease, Prostephanus truncates (Larger document the presence of dangerous grain borer-LGB), Fusarium oxysporum f. pathogens and pests within their sp. cubense (Panama disease), borders. Globalization, climate change, Salviniamolesta (Salvinia) and porous borders, financial constraints, and Eichhorniacrassipes (Water hyacinth). lack of awareness among farmers, These pests are still serious pests in importers, exporters and research Kenya with enormous resources being scientists have been shown to be a channeled to their management .The challenge in preventing introduction and LGB which is native to Central and South spread of harmful pests. America was introduced in Africa in early 1970s. The pest has spread into Kenya Although Kenya has developed a and other African countries through stringent phytosanitary system which movement of infested grain. Water regulates movement of plant and plant hyacinth infested Kenyan waterways in products, there has been several pest mid 1980s. It quickly spread and attained incursions which have negatively an estimated peak of 17,230 ha coverage impacted on crop production, on the Kenyan side of the Lake Victoria biodiversity, and human development. by 1998. Some of the previous incursions reported worm (FAW), Maize lethal necrosis Foreign pests that have been reported disease (MLND), Papaya mealybug on crops in Kenya since 1998 (PMB), Parthenium hysterophorus, In the last two decades, Kenya has potato cyst nematode (PCN) and tomato encountered several major pest leaf miners (Tuta absoluta), among incursions which include Asian citrus others which have significantly affected psyllid (ACP), Bactrocera dorsalis, food security, the environment and Banana xanthomonas wilt (BXW), international trade (Table 1). A recent Cassava brown streak disease (CBSD), example is the invasive fall army worm Cassava mosaic disease (CMD), Fall army which has been extensively damaging on

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maize and other crops in Sub-Saharan Chlorotic Mottle Virus (MCMV) and Sugar Africa. Cane Mosaic Virus (SCMV) or with other cereal potyviridae viruses like the Wheat The fall army worm (FAW) Spodoptera Streak Mosaic Virus (WSMV) or Maize frugiperda, a native to the tropical Dwarf Mosaic Virus (MDMV).The disease regions of the western hemisphere from was first reported in Bomet County in the United States to Argentina, has Kenya in 2011 and is currently spread caused heavy losses to cereal farmers in across several maize production areas Africa since its introduction in the West (Wangai et al., 2012). Estimated maize African region in 2016. FAW was reported yield loss due to MLND varies from region for the first time in Kenya in Trans Nzoia to region, maize variety and season of County in March 2017 in an offseason the year. In Kenya, up to 100% yield irrigated maize crop after which it spread losses have been reported in areas where first to all the maize production areas the disease was very severe (Wangai et (KARLO, 2017). The pest has continued al., 2012). MLND causing viruses are to cause serious losses in maize transmitted by several vectors including production and is threating horticultural thrips (Frankliniella Williamsi), and cereal export. In view of the importance of this leaf beetles (Oulemame lanopus).The pest, the government has instituted a disease is also seed transmitted. Several multi-institutional technical team which measures have been put in place to has develop strategies for management mitigate the negative effect caused by of the pest. the viruses which include up-scaled seed Maize lethal necrosis is a serious viral certification system, use of systemic disease affecting maize in Kenya. The pesticide and breading for resistance. disease is caused by co-infection of Maize

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Table 1. Foreign pests that have been reported on crops in Kenya since 1998.

Name of pest Year first Status Current Yield loss References reported Distribution or disease Potential

Spodoptera frugiperda 2017 Widespread All maize growing 73% CABI, 2018 (Fall army worm) areas in Kenya

Diaphorina citri (Asian 2016 Restricted Coast Kenya 100% by Rwomushana et citrus psyllid). greening al., 2017 disease

Paracoccus marginatus 2016 Regulated Coast Kenya 100% Macharia et al., (Papaya mealybug) 2017

Globodera rostochiensis 2015 Regulated Potato production 80% Mwangi et al., (Potato cyst nematode) areas 2015

Tuta absoluta (Tomato 2014 Widespread All tomato producing 100% Duressa, 2018 leaf miner) areas in Kenya

Maize lethal necrosis 2011 Regulated Maize production 90% Wangai et al., areas 2012

Parthenium 2010 Noxious Most open farming High Guyana, P., & hysterophorus weed lands Paraguay, S. (Parthenium weed) 2014

Cassava brown streak 2006 Restricted Coastal and Western 70% Were et al., disease Kenya 2016

Xanthomonas 2006 Restricted Western Kenya 100% Kwach et al., campestris pv. 2013 Musacearum (Banana xanthomonas wilt)

Bactrocera (dorsalis) 2003 Invasive All host crops 70% Luc et al .,2003; invades(Mango fruit fly) producing areas in Ekesi et al., 2011 Kenya

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Bactrocera dorsalis (formerly Bactrocera Wilt (BXW) is best managed by use of invades) is an invasive fruit fly species of clean planting materials and removing of Asian origin which was first reported in male flower buds, and sterilization of Kenya in 2003 (Lux et al., 2003). The tools. The disease has been reported in pest has been reported to cause yield banana growing areas in Western Kenya losses of up to 70% in mangoes (Ekesi et and Nyanza (Kwach et al., 2013). al., 2011). Apart from the huge loss, Tomato (Lycopersicon esculentum Mill) is introduction of B. dorsalis significantly one of the most important vegetable affected international market for crops whose production has been horticultural produce in Kenya. The most threatened by Tuta absoluta (tomato leaf notable example is loss of the European miner) which was introduced in Kenya in Union (EU) market for mangoes and 2014. The pest has been reported to South Africa market for avocados cause yield loss upto100% (Duressa, coupled with inability to access other 2018). Chemical control and use of traps market such as USA, Australia among are the main management measures that others. Use of pheromone traps and have been used since the pest was post-harvest treatments have been used reported. in the management of the pest (Ekesi et al., 2011) Cassava Mosaic Disease (CMD) was reported in the 1980 as one of the most Banana, a major fruit crop, has been important viral disease affecting cassava threatened by Xanthomonus Wilt (BXW) in Kenya. Despite the effort through caused by a bacterium Xanthomonas breeding for diseases resistance, vasicola.pv. musacearum (Xvm), introduction of cassava brown streak formerly known as Xanthomonas disease (CBSD) in 2006 rendered the campestris, which has been shown to effort made futile and breeders were cause up to 100% yield loss (Kwach et forced to start all over again as all CMD al., 2013). The disease was introduced resistant varieties were susceptible to from Uganda and has been shown to CBSD. CBSD and CMD causing viruses affect all banana cultivars. Xanthomonus are transmitted by Bemisia tabaci and

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have the potential of causing up to 100% its introduction is still not clear. PCN has yield losses. In Kenya, among the CMD been reported to cause yield losses of up causal viruses, EACMV-Ug has recently to 80%. been reported to be the most prevalent Prevention and management followed by EACMV and ACMV contrary strategies of pest incursions in to previous reports where ACMV was the Kenya most prevalent in Kenya (Were et al., Although introduction of pests still 2016). It is not yet clear what factors remains a challenge in Kenya and other have contributed to this change. African countries, Kenyan government Breeding for resistance is the most through KEPHIS and other institutions reliable means of control. has invested heavily on technology and Other pest that have been introduced in policy to support phytosanitary Kenya include: P. marginatus, native of regulation in the effort to prevent pest Central America and was first observed introduction and spread in the country. on the Africa in Ghana in 2010 from Regulating importation of plant and plant where it spread to other African product plays an important role in countries. The pest was reported in minimizing introduction of harmful pest. Kenya in 2016 (Macharia et al., 2017). Other measures instituted to reduce The pest is highly polyphagous, with introduction of pest and diseases hosts recorded from 84 plant species includes pest risk analysis which provide causing yield loss of up to 100%; risks associated with importation and Diaphorina citri, is native in Asia, and was possible mitigation measures. Pest first reported in Kenya in 2016. It causes surveillance to establish occurrence and up to 80% yield loss in citrus (Khan et al., distribution of pests, pest identification, 2014); Potato cyst Nematode (PCN) is a containment of materials likely to serious pest of potato that was first introduce pests in quarantine facilities reported in Kenya in 2014 in most potato among others. production areas (Mwangi et al., 2015). Although the pest is native of in Europe,

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KEPHIS Plant Quarantine and Biosecurity Dickeya spp, Alternaria padwickii, PVYNTN Station where most of the plant health and several others fungal, bacterial and facilities are located, is responsible for viral diseases. handling imported high risk plant Conclusion materials. The imported material are Various pest of economic importance grown under containment and monitored have gained entry into the country and for pests and diseases for a period of are posing as threats to food security and time based on the pest before they are the general well-being of the people. The released to the importer. This reduces pests come in the form of plant the chances of introduction and spread of pathogens, arthropod pests and invasive harmful pests and diseases in the plant species. country. Importers are also allowed to Recommendation establish quarantine facilities in their There is need to conduct surveillance in farms under strict regulation, monitoring all parts of the country for early detection and control from KEPHIS. All materials which is important for management of under quarantine are monitored and pests. It is also important to strengthen tested for quarantine pests before they phytosanitary measures and create are released. At the boarder points and awareness on pest management point of entry and exit inspection, strategies for the county to attain the sampling grading of all imported required food security. A surveillance consignment is undertaken. database for the pests to be updated for ease of retrieval and build up on In the last two decades several pests information. were identified in imported materials and appropriate measures undertaken to Acknowledgment prevent their introduction. Among the The authors are grateful to the pests detected were coconut case management of The Kenya Plant Health caterpillar Mahasena corbetti, Inspectorate Service and The University Curtobacterium flaccumfaciens pv. of Nairobi for supporting the flaccumfaciens, Pectobacterium spp, collaboration that led to this paper.

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