The stability of tolerance of Sorghum spp to Striga asiatica L. Kuntze under diverse conditions and existence of pre- attachment resistance
Mandumbu Ronald (201317414)
A Thesis Submitted to the Faculty of Science and Agriculture in Fulfillment of the Requirements of the Degree of Doctor of Philosophy
Department of Agronomy
Faculty of Science and Agriculture
University of Fort Hare
July 2017
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DECLARATION I Ronald Mandumbu, declare that the work contained in this thesis is entirely my own work and that all reference materials contained in this thesis have been duly acknowledged. This thesis has not been previously submitted to this or any other University for the award of a degree.
Signature………………………………………………
Date…………………………………………………….
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PUBLICATIONS
1. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2016). Existence of different physiological strains of Striga asiatica (L.) Kuntze on Sorghum spp [Sorghum bicolor and Sorghum arundinaceum (Desv) Stapf) in Zimbabwe. Research on Crops 17 (3): 468 – 478. DOI10.5958/2348-7542.2016.00077.2
2. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2017) The effect of witchweed (Striga asiatica) infestation and moisture stress on selected morpho-physiological traits of sorghum in Zimbabwe. Journal of Agronomy 16 (2): 65 - 75.
3. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2017) determination of resistance to Striga asiatica (L.) Kuntze using agar jel analysis and sand culture in Sorghum bicolor and Sorghum arundinaceum in Zimbabwe. Accepted by the Asian Journal of Crop Science.
4. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2017) Response of Sorghum bicolor (L) Moench and Sorghum arundinaceum (Desv) Stapf to Striga asiatica (L) Kuntze infestation under mulch. Accepted by Tropical Agriculture .
5. Mandumbu R, Mutengwa C, Mabasa S and Mwenje E (2017). The Striga scourge under changing climate in southern Africa: A perspective. Accpeted by Journal of Biological Science.
6. Mandumbu R, Mutengwa C, Mabasa S, Mwenje E (2017). Factors affecting the success of resistance as a management strategy in Striga management: A review. Under review with the Asian Journal of Plant Science.
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PREFACE This thesis is presented in a form of a General Introduction (Chapter 1) and Literature
Review (Chapter 2) which introduces the reader to sorghum and Striga issues in Zimbabwe and elsewhere in the world. Chapter three deals with the simultaneous effect of reduced water availability and Striga asiatica infestation on the morpho-physiological attributes of sorghum. Chapter four investigates the effect of mulching as a cultural practice on the stability of tolerance by Sorghum spp to Striga asiatica. Chapter five focuses on the variable effects of two Striga asiatica strains sourced from two distant places in Zimbabwe on sorghum productivity and the stability of tolerance. Chapter 6 deals with the quantification of strigolactones in Sorghum bicolor and Sorghum arundinaceaum and determines the relationship between strigolactone quantities and sorghum tillering. Finally, the general discussion, conclusions and recommendations are reported in the last chapter (Chapter 7).
This thesis was written in paper format and there is therefore unavoidable repetition of some information, including references.
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ABSTRACT
Sorghum is the fifth most important cereal in the world and a staple food for humans. It is also a source of food and fodder for animals. In addition to the abiotic stresses such as drought, parasitic weeds of the genus Striga cause losses in sorghum production in sub
Saharan Africa. Striga asiatica is a parasitic weed that attacks cereals in low input agricultural systems and is distributed throughout semi- arid regions of Africa. Most sorghum producing farmers rely on tolerance for their harvests in Striga infested fields yet the stability of tolerance in the face of a changing climate (recurrent droughts), new farming systems
(mulch based agriculture) and existence of various Striga strains needs further investigation.
Reduced strigolactones production was also studied as a resistance mechanism.
The first study was focused on the determination of tolerance of Striga asiatica infested sorghum under drought in a pot study. Five sorghum lines were subjected to infestation with
Striga and some were not infested while watering was done at 50 % field capacity (FC) and
100% FC. The results showed that the five sorghum lines differed significantly in chlorophyll content and Normalised Differential Vegetation Index (NDVI). Infection did not lower chlorophyll content when it co-occurred with drought across all sorghum lines. Drought and infestation had mutually exclusive effects on chlorophyll content and NDVI. Under infestation, internode length was similar both at 100 % FC and at 50 % FC while under uninfested conditions, 100 % FC gave the longer internode compared to 50 % FC. Both infestation and irrigation regime reduced the sorghum head weight, illustrating that the two effects have synergistic effects on sorghum head weight.
The second study sought to determine the effects of mulching and infestation on sorghum spp tolerance to Striga asiatica. The experiments were carried out in the seasons 2013/14 and
2014/15 summer seasons. The results indicated that mulching increased chlorophyll content
v in the 2014/15 season which was a drier season compared to 2013/14. In the 2014/15 season, mulching increased chlorophyll content in all varieties except Ruzangwaya, Mukadziusaende and SC Sila. When the same varieties were infested under mulch and infested without mulch, the results showed that mulching overcomes the effects of infestation in some varieties.
Mulch also negates the effect of Striga parasitism and results in yield maintenance in sorghum varieties.
The third study sought to determine the stability of sorghum lines when exposed to two
Striga asiatica lines sourced from two places which are 500 km apart in Zimbabwe. The two strains were termed the Chiundura and Rushinga strains, based on where they were sourced.
The experiments were conducted at Henderson Research Station (HRS) at Mazoe and at
Bindura University of Science Education (BUSE). The results showed differential virulence for some traits while the two strains were equally virulent for some traits. The two strains were equally virulent on all sorghum lines with respect to chlorophyll content. The different sorghum lines responded differently to the effects of the two strains. The effects of the two strains were generally similar for head index, root index, and leaf index at all sites. Generally the Chiundura strain was more virulent to sorghum lines compared to Rushinga strain, confirming the existence of physiological strains of Striga in Zimbabwe. Therefore physiological speciation of Striga asiatica exists and this adds a further dimension to the complexity of Striga management in the smallholder sector.
Quantification of strigolactone production by different sorghum genotypes was conducted in the laboratory using the agar gel assay. The genotype Mukadziusaende produced significantly the least (P<0.01) quantities of strigolactones, as inferred from the maximum germination distance (MGD) from the sorghum root. The MGD was negatively correlated to tiller numbers illustrating that the more the strigolactones the less the tillering capacity. Tiller numbers and MGD can therefore be used to select for reduced strigolactones production.
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Key words
Sorghum bicolor, Sorghum arundinaceum, Striga asiatica, resistance, tolerance, drought, mulch, physiological speciation, strigolactones.
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DEDICATION This study is dedicated to my wife, Virginia, my children, Praise, Gladiness, Anesu and Ruth, my parents Ndedza and Enita Mandumbu.
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ACKNOWLEDGEMENTS In a doctoral study, one is indebted to so many sources of assistance that it is practically impossible to list them all. At the risk of omission, I would like particularly to thank the people and institutions listed below.
I would like to thank my supervisors: Professor C.S. Mutengwa, Dr Stanford Mabasa and Professor Eddie Mwenje for their guidance throughout the course of this work. This work was made possible by the financial assistance from the Zimbabwe Manpower Development Fund (ZIMDEF), the Research Council of Zimbabwe (RCZ) and the Research and Post Graduate Centre of the Bindura University of Science Education (BUSE).
I want to thank Mr Chikaka, Mr Gochera, Zengeza Tapiwa, Chitaukire Charity and Maramba Komborero, Mr Kufa Mutsengi and Munyati Vincent for the assistance of setting the experiments and data collection. Mr Senga and Mr Kamhapa for the assistance in laboratory work. Mr Parwada and Mr Mafuse for assembling at our reading hub as we had the same challenges of coming up with a thesis. The Weed Research Team at Henderson Research station is acknowledged for their assistance with space and data collection for the experiments which were carried out there. I also want to thank the Mafirenyika family for hosting me in East London every time I was in South Africa. They made my stay a memorable experience with great dinners, break fast and sight seeing. I also want to thank my brothers and sisters who include Tongai, Pesanai, Georgina, Tawanda, Solomon, Ruvarashe and Chiedza and their families for inspiration. I also thank Diriri Simbarashe and family for their support. My brother Zvamaida Gumbo is acknowledged for teaching me to read, I am sure you also did not know it was coming to this. To Effort Macheza, Noel Gumbo and Model Macheza, the button is now in your hands and the tracklines are open.
Never should I forget the Lord Jesus Christ for His unwarranted favour, for giving me strength and wisdom to complete this study. Last but definitely not least I want to thank Prophet Emmanuel Makandiwa, Prophetess Ruth Makandiwa and the whole United Family International Church for the teachings, motivation and inspiration I got which have kept me going and grounded in the word of God. And He said I give unto you POWER.
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Table of Contents
PREFACE ...... iv
ABSTRACT ...... v
DEDICATION ...... viii
ACKNOWLEDGEMENTS ...... ix
1.1 Statement of the problem ...... 1
1.2 Justification of the study ...... 5
1.3 Main objective ...... 7
1.4 Specific objectives...... 7
References ...... 9
CHAPTER TWO: LITERATURE REVIEW ...... 15
2.1. Introduction to literature review ...... 15
2.2 Sorghum production in Zimbabwe ...... 15
2.3 The genus Striga...... 16
2.3.1 Striga hermonthica ...... 17
2.3.2 Striga asiatica ...... 17
2.3.3 Striga gesneroides ...... 18
2.4 Extent of the Striga problem in sub-Saharan Africa ...... 19
2.5 Striga problem in the smallholder sector of Zimbabwe ...... 20
2.6 History and distribution of Striga asiatica in Zimbabwe ...... 24
2.7 Striga asiatica research in Zimbabwe ...... 24
2.8 Striga asiatica lifecycle ...... 27
2.8.1 Dormancy and conditioning ...... 27
2.8.2 Germination ...... 28
2.8.3 Haustorium development ...... 28
2.8.5 Establishment of parasitism and flowering ...... 30
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2.9. Strigolactones in plants ...... 31
2.10 The parasite as a sink ...... 33
2.11 Mechanisms of sorghum tolerance to Striga asiatica ...... 33
2.11.1 Host photosynthesis ...... 33
2.11.2 Sorghum tillering as Striga tolerance mechanism ...... 35
2.11.3 Environmental regulation of tillering ...... 36
2.12.1 Propensity to tiller ...... 36
2.13 Host plant resistance against Striga ...... 37
2.13.1 Reduced host stimulant production ...... 37
2.13.2 Reduced haustorium inducing factors (Low haustorial factor) ...... 38
2.13.3 Parasite establishment resistance ...... 39
2.13.4 Post-attachment resistance ...... 39
2.13.5 Incompatible response (IR) ...... 39
2.13.6 Hypersensitive response ...... 40
2.14 Managing Striga asiatica in sub-Saharan Africa ...... 40
2.15. Sorghum response to drought stress ...... 42
2.16 Existence of Striga physiological speciation and differential virulence ...... 43
2.17 Mulch effects on Striga asiatica incidence ...... 44
2.18 Photosynthesis in a Striga-infested plant ...... 46
2.18.1 Stomatal conductance ...... 47
Chapter Three: ...... 68
The effect of witchweed (Striga asiatica L. Kuntze) and moisture stress on selected morpho- physiological traits which impart tolerance to Sorghum spp ...... 68
3.1 Abstract ...... 68
3.2 Introduction ...... 69
3.3 Methodology ...... 73
3.3.1 Experimental site ...... 73
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3.3.3 Experimental design and treatments ...... 73
3.3.5 Irrigation ...... 74
3.3.6 Data collection ...... 74
3.4 Results ...... 75
3.4.1 Chlorophyll concentration and NDVI ...... 75
3.4.2 Dry matter traits ...... 81
3.5 Discussion ...... 89
References ...... 94
CHAPTER FOUR:...... 103
The response of tolerance traits of Sorghum bicolor (L) Moench and Sorghum arundinaceum (Desv) Stapf to Striga asiatica (L) Kuntze infestation under mulch ...... 103
4.1 Abstract ...... 103
4.3 Materials and methods ...... 106
4.3.1 Experimental site ...... 106
4.3.2 Experimental design and pot layout ...... 106
4.3.4 Source of Seeds ...... 107
4.4 Results ...... 108
4.4.4 Plant height ...... 114
4.4.5 Grain yield ...... 119
4.5 Discussion ...... 121
6.0 References ...... 126
The existence of different physiological ‘strains’ of Striga asiatica (L.) kuntze on Sorghum bicolor (L.) Moench and Sorghum arundinaceum (desv) Stapf in Zimbabwe ...... 131
5.1 Abstract ...... 131
5.2 Introduction ...... 132
5.3 Materials and Methods ...... 134
5.3.1 Experimental sites...... 134
5.3.4 Experimental details ...... 135
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5.3.5 Data Collection ...... 136
5.4 Results ...... 136
5.4.1 Sorghum plant height...... 136
5.4.3 Sorghum tillering ...... 143
5.4.4 Sorghum dry matter traits ...... 145
5.4.5 Sorghum head weight ...... 148
5.4.6 Total dry weight...... 150
5.5 Discussion ...... 152
5.7 References ...... 156
CHAPTER SIX ...... 161
Sorghum response to Striga asiatica based on maximum germination distance, Striga counts and sorghum tillering in Zimbabwe ...... 161
6.1 Abstract ...... 161
6.2 Introduction ...... 162
6.3 Materials and methods ...... 165
6.3.1 Experiment 1: Agar jel assays ...... 165
6.3.2 Sorghum germplasm and Striga asiatica seed sources ...... 165
6.3.3 Experimental design ...... 165
6.3.4 Surface Sterilisation and sorghum seed germination ...... 165
6.3.5 Conditioning of Striga seed ...... 166
6.3.6 The assay set up ...... 166
6.5 Results ...... 167
6.5.1 Maximum germination distance (MGD) ...... 167
6.5.2 Tillering ...... 168
6.5.3 Striga counts ...... 169
6.5.3 Correlations between maximum germination distance, tillering and Striga counts . 170
6.6 Discussion ...... 171
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6.7 Conclusion ...... 173
6.8 References ...... 173
CHAPTER SEVEN: GENERAL DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS ...... 178
7.1 Introduction ...... 178
7.2 Discussion ...... 178
7.3 Conclusions ...... 180
7.4. Recommendations for further research ...... 181
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List of tables
Table 2.1: Zimbabwe sorghum production by year from 2010 - 2014 ...... 16
Table 2.2: The distribution and occurrence of Striga spp in sub-Saharan Africa ...... 18
Table 2.3: Agro-ecological regions of Zimbabwe and agricultural activities carried out in the various regions...... 22
Table 2.4: Different methods of controlling Striga asiatica ...... 40
Table 3.1: Sorghum genotypes effects on chlorophyll content at 6 and 10 WACE ...... 76
Table 3.2: Moisture stress effects on NDVI at 6 and 10 WACE ...... 77
Table 3.3: Effect of S. asiatica infection on chlorophyll content of sorghum ...... 79
Table 3.5: Effect of sorghum genotypes on head weight and head index ...... 82
Table 3.6: The effect of infection on head weight and head index ...... 83
Table 3.6: The effect of water availability on head weight and head index across the two experiments ...... 83
Table 3.7: Effect of sorghum genotypes on leaf dry matter, leaf index, stem weight and index and total dry matter in both experiments ...... 86
Table 3.8: The effect of infection on leaf weight and index, stem weight and index and total dry matter in both experiments...... 86
Table 3.9: The effects of water availability on leaf weight and index, stem weight and index and total dry matter...... 87
Table 4.1: Sorghum genotypes tested for tolerance to Striga in the 2013/14 and 2014/15 seasons ...... 107
Table 4.2: Effect of mulching on chlorophyll concentration for the 2013/14 and 2014/15 summer seasons ...... 109
Table 4.6: Effect of sorghum variety on Striga counts ...... 113
Table 4.7: Effects of infestation on plant height at 8 and 12 WACE in the year 2013/14 and 2014/15 seasons...... 117
Table 5.4: Effect of sorghum genotypes on head index, root index, stem index and leaf index at BUSE and Henderson sites...... 146
Table 5.5: Effect of Striga strains on head, root, stem and leaf index at BUSE and Henderson...... 147
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List of figures
Figure 2.1: The Natural Farming Regions of Zimbabwe ...... 21
Figure 2.2: The life cycle of S. asiatica (Rich and Ejeta, 2007)...... 27
Figure 3.1: Interaction effects of sorghum genotype and moisture availability on NDVI at 10 WACE in Experiment II...... 78
Figure 3.2: Interaction effects of sorghum genotypes and water availability on chlorophyll concentration at 6 WACE in Experiment II...... 79
Figure 3.3: Effect of Striga infestation on internode length...... 80
Figure 3.4: Interaction effects of Striga infestation and water availability on sorghum internode length...... 81
Figure 3.3: The response of sorghum genotypes yield to moisture availability...... 84
Figure3.6: Interaction effects of water availability and Striga infestation on leaf index...... 88
Figure 3.7: Interaction effects of sorghum genotypes and Striga asiatica infestation on stem weight ...... 89
Figure 4.1: Effect of infestation on chlorophyll concentration at 6 WACE during the 2014/ 15 season...... 109
Figure 4.2: Interaction between variety and Striga infestation a) 6 WACE andvariety and mulch b) 8 WACE on chlorophyll concentration ...... 110
Figure 4.3: Effect of infestation status on stomatal conductance for the sorghum genotypes during the 2013/14 season...... 111
Figure 4.4: Effect of season on tiller numbers over two seasons...... 112
Figure 4.6: Interaction effects of sorghum genotype and S. asiatica infection on sorghum height in the 2014/15 season at 8 and 12 WACE...... 115
Figure 4.7: Interaction effects of sorghum genotype, mulching and infestation on plant height in the 2014/15 season...... 116
Figure 4.8: Interaction effects of sorghum variety and infestation on plant height at 4, 8 and 12 WACE during the 2013 season...... 118
Figure 4.9: Interaction effects of sorghum genotypes and infestation on sorghum yield for the 2013/14 season ...... 119
Figure 4.10: Effect of sorghum genotypes, infestation and mulching on sorghum yield in the 2014/15 season ...... 120
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Figure 5.1: Interaction effects of sorghum genotypes and Striga strain on sorghum height at 6, 8 and 12 WACE at Henderson research station...... 138
Figure 5.2: Interaction effects of sorghum genotype and Striga strains at 12 WACE at BUSE ...... 139
Figure 5.3: Interaction effects of sorghum genotype and Striga strains on chlorophyll content at 10 WACE at both sites ...... 143
Figure 5.4: Effect of sorghum variety on tiller number at 12 WACE at both sites ...... 144
Figure 5.5: Effect of Striga strains on tiller number...... 145
Figure 5.7: Interaction effects of sorghum genotypes and Striga strain at BUSE and Henderson ...... 149
Figure 5.8: Total dry matter of sorghum genotypes for BUSE and Henderson ...... 150
Figure 5.9: Interaction effects of sorghum genotype and Striga strain on total dry mass at BUSE ...... 151
Figure 6.1: Maximumgermination distances for various sorghum genotypes……….….....168
Figure 6.2: Effect of Striga asiatica on tillering of sorghum genotypes ...... 169
Figure 6.3: Effect of Sorghum genotypes on Striga counts ...... 169
Figure 6.4 : The relationship between germination distance and tiller numbers in sorghum...... 170
Figure 6.5: Relationship between sorghum yield and tiller numbers………..…………..…171
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List of Acronyms
WACE – Weeks after crop emergence
FC – Field capacity
NDVI—Normalised vegetation difference index
BUSE – Bindura University of Science Education
HRS—Henderson research Station
MGD—Maximum germination distance
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CHAPTER ONE: INTRODUCTION
1.1 Statement of the problem
Sorghum (Sorghum bicolor L. Moench) is an important crop in traditional farming systems and in the diet of millions of people in the semi-arid tropics (Haussmann et al., 2001). It is an annual C4 crop commonly consumed as human food and livestock feed and it feeds more than
500 million people in 98 countries in Africa, Asia and America (Pennissi, 2009). It is one of the top five cereal grains produced worldwide (Burdette, 2007). In Zimbabwe, it is ranked the third most important cereal after maize and wheat (FAO, 1996). It can maintain remarkable yield potential in environments that are normally too extreme for other C4 plants (Tari et al.,
2013).One of the remarkable characteristics of sorghum is its drought tolerance, which has made it an important cereal grown for food and beverages by resource poor farmers in sub-
Saharan Africa. . Sorghum represents a large proportion of the calorie intake of the people in sub-Saharan Africa. White sorghum is ground into flour mostly for making sadza (a stiff dumpling), beverages and porridge (Mutengwa, 2004). It can be popped like popcorn to create a delicious snack food.
Among a myriad of factors constraining sorghum production, Striga is the major biological constraint that hinders increased sorghum production in the small-holder sector of sub-
Saharan Africa. Striga species are a major parasitic weedy pest throughout the semi-arid sub-
Saharan Africa and many parts of Asia (Rubiales et al., 2009). Many cropping fields in
African countries including, Tanzania, Kenya, Malawi, Madagascar, Botswana, Zimbabwe,
Gabon, Nigeria, Ethiopia, Niger, Togo, Benin and Burkina Faso are highly infested with
Striga causing serious yield losses that are as high as 100 % at some sites (Lagoke et al.,
1988; Badu-Apraku et al., 2014; Bozkurt et al., 2014). In Kenya, crop losses have been reported to be as high as 100 % in sorghum. For maize, losses of 50 % under ‘moderate’
1 infestation and 87 % under heavy infestation have also been reported (Manyong et al., 2007).
In Zimbabwe, complete crop failure has been reported by Mabasa (2003). The parasite is a major constraint to subsistence agriculture in Africa such that resource poor farmers are sometimes forced to abandon their fields with grave consequences to their families (Berner et al., 1995; Ejeta, 2007). In particular, major crops that supply the bulk of the energy and protein needs of the poor in the African savannah, namely maize, sorghum, millets, upland rice and cowpeas have been severely vulnerable (Ejeta, 2005).
Losses from Striga are compounded because of the tendency of crops grown under severe moisture and poor fertility conditions to show significant predisposition to Striga. According to Timko et al., (2012), two thirds of the farmland under cultivation in sub-Saharan Africa is infested with one or more Striga spp directly affecting livelihoods of more than 300 million people in 25 countries. According to Scholes and Press (2008) and Ejeta (2007), over 50 million hectares of arable farmland under cultivation with cereals and legumes in sub-
Saharan Africa are infested with one or more Striga species. In many of these places, the
Striga has reached epidemic proportions presenting a desperate situation in subsistence agriculture (Ejeta and Butler, 1993). The weed causes annual losses of yield estimated to be in excess of US$10 billion (Ejeta, 2007). Striga spp affects the welfare and livelihoods of over 100 million people in Africa (Rubiales et al., 2009). According to Parker (2009), the weed has impacted on the sub-region’s economy. Striga spp stand as a major constraint that prevents attainment of household food security for some of the world’s poorly resourced people.
The Striga problem in sub-Saharan Africa is made worse by its exquisite adaptation to the climatic conditions of the semi-arid tropics, its high fecundity and longevity of its seed reserves in the tropical soils (Ejeta, 2007). The problem is tending to increase rather than decrease as intensive land use and lack of fertilizers leads to continued decline in soil fertility
2 which greatly favours Striga (Parker, 2012). The climatic conditions of sub-Saharan Africa permit timely break down of seed dormancy and conditioning of Striga seeds. Striga asiatica has a high reproductive capacity, producing 10 000 to 20 000 seeds per plant (Hearne, 2009).
Striga seeds have very small dimensions (0.3 nm * 0.15 nm) and are light (4 – 7 ug) such that they are easily dispersed by wind, water and animals. The viability of Striga seed goes beyond 20 years in the soil and this creates seed banks that are difficult to manage.
The life cycle of the noxious cereal weed S.asiatica is complex and has co-evolved with many hosts to comprise a series of discrete steps that are tightly coupled with the host’s biochemistry, life cycle and genotype (Bouwmeester et al., 2003). The parasitic plant grows underground for 4 – 7 weeks prior to emergence and utilizes host water, nutrients and photosynthates (Jamil et al., 2012). Yoneyama et al., (2010) reported that seeds of parasitic
Striga only germinate after perceiving a germination stimulant (strigolactones) from their host. The concentration of the stimulant required to initiate germination are as low as 10-18M soil solution (Stewart and Press, 1990, Yoneyama et al., 2007).
No single completely effective and practical method to eliminate Striga is known (Bozkurt et al., 2014). Over the years, many promising Striga control strategies have been suggested in various formats, with some suggestions appearing in multiple incarnations (Hearne, 2009).
Inspite of all this valuable work, adoption and utility of control methods is limited. The control measures are neither fully effective nor easy to apply. Only marginal successes have been obtained to date (Joel et al., 2006). As a result, yield loss attributable to Striga is acute, as noted before (De Groote et al., 2008). Hence Striga continues to present a challenge for the forseable future, not only in the areas already affected but also in terms of introduction into new areas (Parker, 2012).
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Host plant defense against Striga spp is the only sustainable route for Striga control. It constitutes two complimentary mechanisms and these are resistance and tolerance. According to Kim (1994) and Badu-Apraku et al., (2006) resistance to Striga refers to the ability of a host plant to stimulate the germination of Striga seeds but prevent the attachment of the parasite to its roots or kill the attached parasite. Host resistance is multi-dimensional with both general and specific defence mechanisms that can disrupt critical steps throughout the parasite’s life. Kim (1994) and Rodenburg and Bastiaans (2011) reported that a Striga tolerant genotype germinates and supports many Striga plants as the intolerant ones, but produces more grain and stover and shows fewer damage symptoms. Different cultivars may differ in their capacity to tolerate the physiological and pathological effects caused by Striga parasitism, finally resulting in milder or stronger impacts on crop yield (Cardoso et al., 2011).
There is only a marginal role of tolerance in the exploitation of host plant defense in sorghum against Striga asiatica. Resistance is neither complete nor everlasting. The high level of genetic variation in Striga populations, combined with typical high seed production rates threatens the durability of resistance. The loss of resistance can be disastrous as the parasite depends on the staple crops of rural farmers. Tolerance will act as a ‘safety net’ that prevents a sudden and unforeseen collapse in food supply (Rodenburg and Bastiaans, 2011).
According to Gurney et al., (2003), the control of Striga has proved challenging, mostly as a result of intricate life cycle of the parasite with the host. Much research has therefore focused on the development of cereals resistant to infection as a sustainable long term solution.
Complete resistance has not been identified in sorghum although varieties differ in their sensitivity to infection (Gurney et al., 1995). Therefore, the traits that reduce fitness impacts of damage such as increased photosynthesis, compensatory growth, architecture of auxillary buds and carbon storage organs are very critical in varietal selection under Striga infestation.
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Understanding the mechanisms that plants use to defend themselves and the ecological drivers thereof has been a major research problem (Hartmann, 2008; Agrawal, 2011).
1.2 Justification of the study
Despite cultivating the sorghum crop in S. asiatica infested fields, some level of yield has been maintained in sorghum due to tolerance. Tolerance gives the ability to produce yield despite Striga infestation. The stability of tolerance may be affected by exogeneous environmental drivers such as athropogenically induced climate change, changes of farming systems or cultural practices, or the existence of genetic variance in Striga asiatica virulence.
According to Stringer et al., (2009), agricultural systems face the increasing risk of water stress and that can affect the nature of parasitism between Striga and its host. The stability of tolerance may vary across genotypes and ecological contexts. The most common scenario is for Sorghum to deal with both water stress and S. asiatica infestation. Given that global change involves modification of a series of environmental factors concurrently and changes in the severity of different stress factors, knowledge on how plants acclimate to multiple successive or multiple combined stresses is of key significance in understanding the effects of future climates on the parasite. A combination of two or more stresses such as drought and
Striga infestation is a common occurence to many agricultural areas around the world and impacts negatively on crop productivity. According to Suzuki et al., (2014) there is an urgent need to generate crops with enhanced tolerance to stress combinations. Information is limited in literature on the stability of sorghum tolerance under both drought and Striga asiatica stresses.
Additionally, human interventions to curb the effects of climate change can modify the agricultural landscape to the demise or promotion of the parasite. Mulch based farming systems being promoted as a component of conservation agriculture in sub Saharan Africa may affect the expression of tolerance traits in some sorghum genotypes. Mulch increases
5 soil moisture and fertility, decreases soil temperature, light transmittance and these are antagonistic to weed development (Carsky et al., 1994; Oswald et al., 2002). Information is not available for Zimbabwe on the effects of this practice on the Striga epidemic and whether it enhances the expression of tolerance in sorghum. Weed responses to such cultural practices are usually species and genotype specific.
Sorghum arundinaceum (wild sorghum) is increasing in Zimbabwe’s cropping systems as a weed and occurs in all crops, even where sorghum has never been grown. Near relatives of cereals could provide new sources of tolerance and resistance (Ejeta et al., 2000, Gurney et al., 2001, 2002). Studies done by Gurney et al., (2002) indicated that the Sorghum arundinaceum strain they used demonstrated tolerance to infections by S. asiatica in terms of growth, biomass accumulation and grain production and this contrasted with Sorghum bicolor, in which infestations had deleterious effects. Such genotypes can be sources of resistance and tolerance traits which can be exploited in breeding for elite genotypes. Mwenje
(2006) reported high cross compatibility between cultivated Sorghum spp and their wild relatives. This provides the opportunity for gene flow between S. arundinaceaum and cultivated sorghums. Rich et al., (2004) found wild sorghum lines that rarely stimulated the development of haustoria in Striga. Currently it is not known whether the Zimbabwean wild sorghum ecotypes are resistant, tolerant or susceptible to Striga species such that their role in the spread of Striga species is unknown.
Genetic variation for virulence can enable the parasite to adapt to new host resistance alleles.
Hence a better understanding of the virulence variability of S. asiatica populations is essential for deployment of resistant varieties in integrated Striga control. According to Bozkurt et al.,
(2014), geographic distance plays a more important role in population differentiation than specialization to a host species. The high evolutionary potential of the parasite populations was also reported by Karltz and Shykoff (1998). Information on the existence of
6 physiological speciation and the stability of tolerance to various S. asiatica accessions is unavailable Zimbabwe but can enhance efforts to breed elite sorghum varieties with broad spectrum and durable resistance through better understanding of the host parasite interactions.
Musimwa et al., (2001) observed wide genetic distance among S.asiatica strains sourced in
Zimbabwe.
Production of low germination stimulants results in low numbers of Striga asiatica attachments, thus producing a resistant phenotype. Jamil et al., (2011) found significant variation in strigolactones production in New Rice for Africa (NERICA) and the low producers gave resistant phenotypes. Information is not available for Zimbabwe on the resistance through reduced strigolactones production and the link between strigolactones and tillering.
1.3 Main objective
The overall objective of this research was to examine the stability of tolerance of Striga asiatica infested Sorghum spp under drought, mulch and different Striga strains. Also to determine the existence of reduced strigolactones production as a resistance mechanism, and establish its link to sorghum tillering.
1.4 Specific objectives
The objectives of this research were:
1. to determine the effect of drought stress and Striga asiatica infection on the stability
of morpho-physiological traits which impart tolerance to Sorghum bicolor and
Sorghum arundinaceum;
2. to determine the effect of mulching on Striga infected sorghum growth, tillering and
dry matter partitioning;
7
3. to determine the variable effects of two Striga asiatica strains on the stability of
tolerance of S. bicolor varieties and S. arundinaceaum; and
4. to quantify strigolactones produced in Sorghum bicolor and Sorghum arundinaceaum
and correlate it to sorghum tillering.
1.5 Alternate Hypothesis
1. Reduced water availability and Striga asiatica infestation have an effect on the
morpho-physiological traits of Sorghum bicolor and Sorghum arundinaceaum.
2. Mulch reduces S. asiatica incidence on S. bicolor and S. arundinaceaum and
enhances the expression of tolerance traits in sorghum.
3. There are variable effects of S. asiatica strains sourced from geographically distant
places on sorghum varieties and sorghum is able to maintain its tolerance in the face
of physiological speciation of S. asiatica.
4. There is pre-attachment resistance through reduced strigolactones production in
Sorghum bicolor varieties and Sorghum arundinaceaum.
8
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14
CHAPTER TWO: LITERATURE REVIEW
2.1. Introduction to literature review
The literature review provides a detailed background to the issues studied in this thesis. The major aim of this study was determination of the stability of tolerance traits of Striga asiatica infested Sorghum bicolor and Sorghum arundinaceaum under drought conditions, under mulch, and under two different Striga asiatica strains sourced in Zimbabwe. The study also sought to quantify strigolactones produced by sorghum varieties as a resistance mechanism and also to find the relationship between strigolactones quantities and sorghum tillering. It was thus necessary to explore literature on sorghum production in Zimbabwe, the genus
Striga, the extent of the S. asiatica problem in sub Saharan Africa and Zimbabwe, Striga research in Zimbabwe, Striga life cycle and management and functions of strigolactones. The mechanisms of resistance and tolerance were also explored, including Striga management, sorghum response to stress and mulching. The discussions on Striga management were biased towards subsistence agriculture as it was an important goal of this study to enhance productivity in this agricultural sector.
2.2 Sorghum production in Zimbabwe
Sorghum bicolor is an important staple crop in Africa, Asia and central America. It is the fifth major cereal crop after wheat, rice, maize and barley. Sorghum is adapted to tropical and subtropical climates but the greatest area of the crop is cultivated in drought prone semi-arid tropical environments with 400 – 600 mm rainfall that are too dry for maize (Mwenje, 2006).
Sorghum bicolor is one of the most drought tolerant small cereal grain crop grown under the smallholder sector in Zimbabwe’s natural farming region III, IV and V (Mutengwa, 2004) which covers more than 70 % of the area in Zimbabwe. These regions are the driest in
Zimbabwe, receiving less than 500 mm of rainfall per year. The crop is grown traditionally in
15
Zimbabwe to ensure food security even in drought years. Sorghum is therefore a calorie source for the millions who reside in Zimbabwe’s semi-arid areas. The major producing areas are Matebeleland North, Matebeleland South and Masvingo provinces. The Mashonaland province produces only 10 % of the total tonnage in Zimbabwe. The production of sorghum in Zimbabwe has been on the increase since 2010 for about five years (Table 2.1) with the exception of 2012 when there was a decrease caused by reduced sorghum prices by the Grain
Marketing Board.
Table 2.1: Zimbabwe sorghum production by year from 2010 - 2014
Year Tonnage (MT) Growth rate (%)
2010 74 000 5.71
2011 95 000 28.38
2012 65 000 -31.58
2013 69 000 6.15
2014 95 000 37.68
Source: FAOSTAT 2015
2.3 The genus Striga
Striga is a latin word for ‘witch’ presumably because plants infested by Striga display stunted growth and an overall drought like phenotype long before the weed appears. The genus was previously grouped within the family Scrophulariaceae but more recent analysis has placed
Striga under the family Orobanchaceae (Ejeta, 2007; Spallek et al., 2013). Striga possibly originates from a region between Semien mountains of Ethiopia and the Nubian Hills of
Sudan (Atera and Itoh, 2011). The same is the centre of cultivated sorghum which is the major host species for several Striga spp (Spallek et al., 2013).
16
The main agriculturally important Striga spp in cereal crops are S. hermonthica (Del) benth and S. asiatica (L.) Kuntze, while S. gesneroides (Willd) Vatke is a major pest in cowpeas.
Striga aspera (Willd) Benth and S. forbesii are also significant problems in cereals in limited locations (Parker, 2009). The distribution of various Striga spp across the African continent is shown on Table 2.2.
2.3.1 Striga hermonthica
This is the most damaging of all Striga spp affecting most staple cereal crops grown in
Africa. It has purple flowers. It is found mainly in the tropical and northern sub tropical regions from Gambia to western Kenya, Tanzania and Ethiopia in the East (Parker, 2009).
According to Mohammed et al., (2001) S. hermonthica is widespread in sub Saharan Africa and is found throughout west Africa to Ethiopia and east Africa.S. hermonthica is particularly harmful to sorghum, maize and millet but is also found in sugarcane and rice fields (Atera and Itoh, 2011).
2.3.2 Striga asiatica
Striga asiatica has red flowers and occurs sporadically across west Africa but becomes pre- dominant species towards the east African coast, southwards to southern Africa (Parker,
2009). This is the Striga spp that wrecks havoc in Zimbabwe. Kroschel (1999) reported that a countrywide survey in Malawi found 63 % of maize fields to be infested with this species. De
Groote et al., (2008) reported that 10 % and 25 % of the maize crop in Namibia and in
Angola, respectively, was infested with this species. A survey by Mabasa (1994) in
Zimbabwe found that 79 % of the farmers reported that this Striga species was present in their fields.
17
2.3.3 Striga gesneroides
Striga gesneroides occur widely in Africa mainly on wild plants only although it has been found in cowpeas in west Africa (Parker, 2009). It has been found in northern Zimbabwe infesting cowpeas and weeds.
Table 2.2: The distribution and occurrence of Striga spp in sub-Saharan Africa
Striga spp Host Plants Distribution
Striga Rice, Sorghum and Angola, Lesotho, Malawi, Mozambique, Namibia,
asiatica maize Tanzania, Madagascar, South Africa, Zanzibar,
Zambia, Botswana, Burundi, DRC, Zimbabwe
Striga aspera Rice, maize, sorghum, Burkina Faso, Cameroun, Central African republic,
finger millet, wild Ethiopia, Gambia, Guinea, Cote’divoire, Nigeria,
grasses and sugarcane Niger, Mali, Ghana, Senegal and Sudan
Striga Sorghum, sugarcane, Angola, Botswana, DRC, Ethiopia, Kenya, Malawi,
forbesii maize, rice Mozambique, South Africa, Sudan, Swaziland,
Tanzania, Uganda, Zambia, Zimbabwe
Striga Cowpeas, and legumes, Angola, Botswana, Burkina Faso, Cameroun,
gesneroides Nicotiana spp, Central Africa Republic, DRC, Ethiopia, Sierra
Eurphobia spp and Leone, Senegal, South Africa, Tanzania,
Ipomoea spp Zimbabwe, Gambia, Ghana, Kenya, Malawi, Mali,
Mozambique, Somalia, Nigeria, Rwanda, Uganda,
Zambia.
Striga Maize, millet, rice, Angola, Cameroun, Central Africa Republic,
hermonthica sorghum,Pearl millet, Djibouti, Eritrea, Gambia, Guinnea Bissau,
Fingermillet, sugarcane Ethiopia, Nigeria
18
2.4 Extent of the Striga problem in sub-Saharan Africa
Parasitic weeds are fast becoming a major constraint to many crops in sub Saharan Africa and yet the efficacy of available means to control them are minimal. Parasitic weeds have become one of the greatest biological constraints to food production in the drier parts of Africa, probably a more serious problem than insects, birds or plant diseases. The C4 cereals consisting of maize, sorghum and millet are the preferred hosts and the infection of these plants by Striga spp can result in severe grain losses. S hermonthica causes up to 100 % grain yield losses. Losses associated with this pest are estimated to be more than US$7 billion in sub Saharan Africa only (Berner et al., 1995) with most affected being the resource poor subsistence farmers (Gurney et al., 2006). According to Rubiales et al., (2009), typical yield losses vary from 15 to 20 % at a regional level, but can be more severe at local scales, sometimes resulting in total crop failure. The losses largely depend on the level of infection, stage of crop growth when infestation occurs, crop variety, soil fertility and rainfall (Menkir and Kling, 2007).
In addition to the yield losses estimated to exceed US$7 billion in value, the weed also causes adverse effects on the welfare and livelihoods of over 100 million people in Africa (Rubiales et al., 2009). The most affected are the resource poor, small scale subsistence farmers and severe infestations cause serious food shortages. There are contrasting statistics on the extent of the Striga infestations by individual species but according to Mwakaboko (2003), 40 % of arable land in sub Saharan Africa and 67 % of the 73 million hectares in cereal zones is infested by Striga. Harsh conditions mean that few alternative crops can be grown, and the use of high-cost inputs such as herbicides is generally not affordable to the resource poor farmers. Sorghum is generally grown by small scale farmers whose cash investments in crop production are low. According to Webb and Smith (1996), inputs are low, rainfall is erratic and soils are poor. These conditions are likely to be the most suitable for the Striga epidemic.
19
In other areas, the weed has reached epidemic proportions, presenting a desperate scenario to small scale farmers. Where the scenario has worsened to these proportions, the farmers are left with no option except to abandon the land. According to Evans et al., (2012), demographic pressure has led to monocropping, thus increasing the frequency of Striga spp host crops in the cropping system, an ideal condition for Striga to thrive.
Ahmed et al., (2001) reported that research in Africa on the control of Striga has been going on for >70 years and despite these efforts, limited success has been achieved. Effective control of Striga has been elusive due to the fact that the weed produces thousands of seeds that can remain viable in the soil for a long time, combined with the complicated mode of parasitism where vascular connections occur underground (Midega et al., 2013). This is partly due to the complex life cycle of Striga, which is intimately linked to its host and depends on the response to chemical and tactile cues, posing a challenge to control both before and after attachment to the host.
2.5 Striga problem in the smallholder sector of Zimbabwe
Zimbabwe is a land locked country which lies entirely in the tropics. It is situated between
15o30I and 30o05I east longitudes. It has been divided into five agro-ecological zones- I, II.
III, IV and V defined largely by rainfall distribution (Figure 2.1) (Vincent and Thomas,
1961). The agricultural regions are therefore an indication of the agricultural potential of the various regions in Zimbabwe (Table 2.2) (Rambakudzibga, 2000). A summary of the rainfall characteristics of the five agro-ecological zones of Zimbabwe and the suitable agricultural activities are shown in Table 2.3.
20
Figure 2.1: The Natural Farming Regions of Zimbabwe
21
Table 2.3: Agro-ecological regions of Zimbabwe and agricultural activities carried out in the various regions.
Agro- Area % of Rainfall characteristics Agricultural activities ecological (Km2) total region
I 7.000 2 More than 1050 mm per Specialized diversified farming region.
annum with some rain in all Suitable for forestry, temperate fruit
months production and intensive livestock
production
II 58. 15 700 – 1050 mm confined to Flue–cured tobacco, maize, soyabean, cotton,
600 summer. Infrequent heavy sugar beans and coffee can be grown.
rainfall. Subject to seasonal Sorghum, groundnuts, seed maize, wheat and
droughts barley can be grown. Wheat and barley are
grown in winter under irrigation. Mixed
cropping with poultry, beef and dairy
production very common in the region.
III 72. 18 500 – 7000 mm per annum. A semi-intensive farming area. Smallholder
900 Infrequent heavy rainfall. farmers occupied 39 % of this prior to land
Subject to periodic seasonal reform and most of the land was used for
droughts, prolonged mid intensive ranching. Maize production
season dry spells and dominated commercial production. Irrigation
unreliable starts of the season. played an important role in sustaining crop
production in commercial farming areas
IV 147. 38 450- 600 mm per annum Suitable for intensive ranching and wild life
800 management. Too dry for successful crop
production and most crops suitable are
22
sorghum and millets and other drought
tolerant crops. Maize is commonly grown
under smallholder farmers. Sugarcane and
cotton are produced under irrigation in large
estates
V 104. 27 Normally less than 500 mm per Extensive ranching and wildlife management
400 annum are the most suitable activities
TOTAL 390. 100
700
Source: Rambakudzibga, 2000.
Zimbabwe is considered an agricultural country because the majority of the population indirectly or directly depends on agriculture (Jasi and Mabasa, 2001). Prior to the land reform program, most of the large scale commercial farmers were located in Natural Regions I and II which are high potential areas for crop production. At independence, nearly 75 % of the communal farmers were located in natural regions IV and V (Whitlow, 1980) and up to now most of the communal areas are located in these regions. Crop production in these low rainfall areas is risky, yields are low and they experience periodic crop failure.
Soils in the communal areas are mainly light sands with low fertility because they contain low levels of nitrogen and phosphorus (Mashiringwani, 1983). Farmers in these areas have limited access to capital for the purchase of inorganic fertilisers, pesticides and seed.
Agriculture in the small scale farming area is, therefore, characterized by unfavourable soil and rainfall as well as constraints in input procurements. Striga is a problem mainly in this farming sector.
23
2.6 History and distribution of Striga asiatica in Zimbabwe
Striga asiatica was first recorded in Zimbabwe in 1916 when it was found in farms around
Mazowe District (Weinmann 1972). Weinmann (1975) reported that 22 % of the total land area in Mazowe District was infested between 1929 – 1930. A weed survey conducted in
1970 in the commercial farms showed that Striga asiatica was only a problem in isolated areas in Mazowe (Thomas, 1970). Subsequent surveys done showed that Striga asiatica was a problem in both the commercial sector (Chivinge, 1983) and the smallholder sector
(Chivinge, 1988; Mabasa, 1993).
In Zimbabwe, the weed is mostly found in the low rainfall areas where 75 % of the rural farmers reside (Mabasa, 1993). In a survey done by Chivinge (1988), Striga asiatica was found infesting maize, sorghum, pearl millet and finger millet in all the then eight provinces of Zimbabwe. Chivinge (1988) reported the weed as the second most aggressive weed in
Mashonaland Central and third most aggressive in the Midlands and Masvingo Provinces in the large scale commercial farms.
Another survey by Mabasa (1994) showed that 79 % of the farmers reported that Striga was present in their fields. Mabasa (1993) noted that Striga is a significant production constraint in three of the five agro-ecological regions (III, IV and V) where nearly 75 % of the communal farmers are based. Efforts to combat the Striga should therefore be intensified to come up with sustainable means of combating the weed.
2.7 Striga asiatica research in Zimbabwe
According to Timson (1945), Striga asiatica research in Zimbabwe dates back to the 1930s and 1940s. After realizing the threat of Striga in the 1920s, an experimental farm was set up in the Concession-Glendale area in the Mazowe valley in the 1930s with the aim of carrying out both experimental and demonstrative work on Striga asiatica control (Anon, 1938).
24
Between 1945 and 1980, there was no research that was done on Striga because it was assumed that the problem had been solved (Mabasa, 1993). This could be because research by then targeted mostly white commercial farmers and neglected the black farmers who might have been suffering due to the effects of the weed.
In 1986-87, the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT) initiated Striga research and they specifically looked at the screening of sorghum cultivars for resistance and tolerance to Striga forbesii (Mabasa, 1993). A survey done in 1988 by the
Weed Research Team (Agronomy Research Institute) found that 79 % of the interviewed farmers reported that Striga was in their fields with the highest infestations in Zaka and
Chiwundura (Jasi and Mabasa, 2001).
Research was initiated on the management of Striga and agronomic trials were conducted by the Weed Research Team on the effects of planting dates, herbicides (Dicamba), manure and fertiliser on Striga in maize sorghum and millet. Early planted crops had the highest Striga infestations than late crops and maize was found to tolerate Striga when manure was applied at 30 tonsha-1 and nitrogen at 90 – 140 kgha-1 (Agronomy Institute, 1988/89). The level of manure and fertiliser was found to be beyond the reach of Zimbabwe’s smallholder farmers.
The tested herbicide was Dicamba (3,6 dichloromethoxybenzoic acid) and it was found to be effective in the control of Striga but it was unaffordable to the small scale farmers and the numeracy that was needed for calibration made it complex for the smallholder farmers.
Maize cultivars that were tested for resistance were found to be susceptible. For sorghum, cultivars SAR29, SAR33, SAR35, SAR37 and SAR16 supported low Striga asiatica counts compared to SV1 and SV2 (Mabasa, 1996). However, their yields were very low. There was therefore a need to improve the yielding capability of the resistant varieties which were otherwise the least preferred by farmers.
25
A comprehensive study by Musambasi (1997) compared herbicide 2.4 dichlorophenoxyacetic acids (2.4 D) and 3.6 dichloromethoxybenzoic acid (dicamba) to hand weeding at 2 and 5 weeks after crop emergence and found that dicamba resulted in the best control of Striga asiatica and 2.4 D was effective in suppressing the weed at 12 weeks after crop emergence and that hand weeding was uneconomic. In the same study, intercropping with Vigna subterranean and Vigna unguiculata, field beans (Phaseolus vulgaris) and groundnut
(Arachis hypogeal) resulted in reduced Striga asiatica numbers. Another study by Mabasa
(2003) revealed that the source and timing of nitrogen application did not influence Striga asiatica tolerance in maize and recommended supportive hand weeding to prevent build up of seeds in the weed seed bank.
There are various constraints in the use of available technologies which should be taken into account when working with smallholder farmers. Most technologies will need 3 – 4 years before there is any appreciable reduction in Striga infestation. No technology has been able to eliminate Striga hence research continues. Consequently, some farmers have come to accept the problem as something they have to live with.
26
2.8 Striga asiatica lifecycle
Figure 2.2: The life cycle of S. asiatica (Rich and Ejeta, 2007).
2.8.1 Dormancy and conditioning
Striga seeds must go through a phase of conditioning before they can be able to germinate
(Spallek et al., 2013). If no strigolactone is received during this time, the Striga seeds will eventually fall into secondary dormancy (Cardoso et al., 2011). Germination is linked to the presence of the host that is nearby as the endosperm of Striga can sustain growth for only 3 –
7 days (Berner et al., 1995).
After ripened Striga seeds may not germinate until they have passed through a pre- conditioning process (Figure 2.2). According to Ejeta and Butler (1993), peak germination of
S asiatica seed occurs in vitro after 10 – 15 days of soaking in water at a temperature of 28 oC. According to Sun et al., (2008), preconditioning strongly affects the responsiveness of
27 seeds to the stimulants. Pre-conditioning at 30oC releases the dormancy within 2 – 3 weeks and increases the sensitivity to strigolactones by several orders of magnitude.
2.8.2 Germination
The biology of Striga parasitism at its various stages is a series of signal exchanges between the host and the parasite that leads to successful establishment (Rich and Ejeta, 2008). The germination of Striga is tightly defined by spatial relations with potential hosts. Striga seed germination is reflected by the distance from the host root where strigolactones are still active, that is, concentrated enough to elicit germination (Fate et al., 1990). Striga seeds can not germinate without specific germination stimulants released by the potential host (Shen et al., 2006). The strigolactone concentrations required to stimulate germination are in the concentration range of 10-10 – 10-15 MoleM3 (Cechin and Press, 1994). Strigolactones have been shown to induce germination of Striga at concentrations that are as low as 10-16M
(Mussellman, 1980). Hearne et al., (2008) reported that the concentration dependent spatial limitation of Striga seed germination ensures nearness to a potential host. This is critical because once germinated, the seedlings will lose their capacity to form competent haustoria within 3 – 7 days (Berner et al., 1995). This is because Striga seed has small amounts of food reserves which can only support limited growth and the Striga would die in a few days without attaching to the host (Shen et al. 2006).
2.8.3 Haustorium development
After seed germination has been triggered, the radicle of the germinating seed penetrates the host root and forms haustoria to establish a xylem to xylem connection with the host to withdraw water and nutrients (Jamil et al., 2011). A haustorium is a multifunctional organ that attaches to a host, establishes a xylem and/or phloem continuum, a physiological bridge between the parasite and its host, directs the unidirectional flow of resources to the parasite and functions at multiple stages in the parasitism (Estabrook and Yoder, 1998). Generally,
28 haustorium formation consists of three phases, initiation (formation of the haustorium primordial), invasion (the penetration of haustorium primordial) and maturation (the establishment of xylem continuum linking the host to the parasite vacular systems
(Musselman and Dickison, 1975). The radicle tip grows chemotropically towards potential host roots after germination.
Haustoria are the invasive structures that develop at the tips of Striga radicle in response to a host root contact. Certain phenolics, flavonoids and quinines have been identified that induce haustorium development when added to the parasite in vitro (Riopel and Timko, 1995).
Chang and Lynn (1986) reported that the only haustorium inducing factor isolated directly from the host root is 2.4-dimethoxy-p-benzoquinone (DMBQ). DMBQ is a product of lignin oxidation and decarboxylation of phenolic acids found in plant cell walls (Spallek et al.,
(2013). Within hours after the parasite roots come into contact with haustorial initiation factors, the growth and division of cortical cells is altered, resulting in localized swelling that develops into haustorium (Yoder, 1999). Xylem formation only occurs upon contact with the host stele (Yoder, 1998). Striga therefore elicits the host to produce a signal necessary for parasite development in the process called semagenesis (Keyes et al., 2007). A synthetic haustorium initiation factor known as syringic acid has been made in the laboratory. Within
24 hours after contact, rapid cell division of the radical tip stops and a hypertrophic growth phase begins (Hood et al., 1998). Penetration of the host epidermis is mediated by the elongation of distal cells in the protoderm or epidermis and the underlying tissue, followed by rounds of periclinal and anticlinal divisions of the cells leading to the growth into the cortex of the host plants (Spallek et al., 2013).
The haustorium is a physical and physiological connection between the parasite and its host and its interaction with host tissues is important in the translocation of molecules (Aly, 2013).
The haustoria initially adheres to the host root by a secreted, mucilaginous substance (Joel
29 and Kesner-Gashen, 1974) and penetrates by pushing between the host cells. Penetration is aided by digestive enzymes secreted by the parasite that include pectin methylesterase, polygalacturonase and endocellulase (Benhod et al., 1993, Losner-goshen et al., 1998). In general, penetration is completed 40 – 72 hours after contact with a host root (Hood et al.,
1998). Molecular translocation between host and parasite ranges from the movement of sugar
(Aber et al., 1983), herbicides (Joel et al., 1995, Nandular et al., 1999) to movement of proteins (Hamamouch et al., 2005; Aly, 2007).
2.8.4 Nutrient transfer
Hibberd and Jeschke (2001) reported that most of the parasitic plants make a beeline for their host’s vascular system and they are able to tap into a large flux of amino acids, organic sugars, ions and water in the host’s xylem vessels or sugars, ions or amino acids in the host’s phloem. Press and Whittaker (1993) found that most of the hemi-parasites have very high transpiration rates and that can be double that of their host especially under low moisture availability. This then creates a strong mass flow that facilitates transfer of water, carbon, nitrogen and mineral nutrients from the host plant. Shen et al., (2006) reported that the stomata of the parasite remains more open than that of the host and results in higher transpiration rates and lower water potentials in the parasite than the host. This was also confirmed by Press (1995). Low water potentials are maintained by the biosynthesis of polyhydric alcohols like mannitol (Press and Graves, 1995) in the parasite.
2.8.5 Establishment of parasitism and flowering
Once xylem to xylem connections are established, the cotyledons of Striga enlarge and break free from the seed coat within 24 hours (Hood et al., 1998). The Striga grows adventitious roots and are able to form secondary haustoria on the same host. Once a strong sink has developed between the host and the parasite, water and nutrients begin to flow and this
30 damages the crops’ development by reducing crop yield. When the Striga plant starts to photosynthesise, the low carbon dioxide fixation and high dark respiration rates of Striga asiatica result in negative carbon gain over a 24 hour period, thus making the weed dependent on the host when growing above ground (Press et al., 1987). Striga leaves are characterised by degenerated palisade cell layers and a relatively small number of chloroplasts per cell (Spallek et al., 2013). This leads to lower photosynthetic rates by Striga.
A stem develops and emerges above ground to flower and disseminate seed after approximately 4 – 7 weeks of growth (Aly, 2013). Flowers of Striga asiatica are red and after pollination, seeds mature within 4 weeks in seed pods, which contain 250 – 500 of dust-like seeds of 200 – 300 µm in size. According to Berner et al., (1995) under optimal conditions each Striga plant can produce between 50 000- 500 000 seeds. Eventually the seed pods open up and the seeds spread on the soil adding to the seed bank.
2.9. Strigolactones in plants
The frequently asked question is why plants exude strigolactones that enables their
locationby parasitic plants. Xie et al., (2010) concluded that the strigolactones may
have other roles that outweigh the risks of parasitism. According to Akiyama et al.,
(2005), Akiyama and Hayashi (2006) and Akiyama et al., (2007) strigolactones
function as branching factors for the symbiotic abuscular mycorrhizae (AM) fungi
from which plants benefit. The AM fungi are soil inhabiting microorganisms that
form symbiotic associations with plants. The fungi penetrate and colonise plant roots
where they develop highly branched arbuscules which serve as nutrient exchange
sites. According to Xie et al., (2010) the fungi supply their host with water and
nutrients, especially nitrogen and phosphorus that are obtained through the hyphae
that is found on the outside in the soil.
31
In the absence of the host, the AM hyphae differentiate into morphological structures characterized by extensive branching (Buee et al., 2000). Strigolactones therefore appear to trigger a cascade of molecular and cellular events necessary for hyphae to become more effective. In host plants, production of strigolactones is stimulated by phosphate shortages
(Yoneyama et al., 2007a). This demonstrates that strigolactones are molecules for use in the successful establishment of plants with hyphal fungi- plant symbiosis.
Strigolactones have also been implicated in fungal/host shoot branching (Umehara et al.,
2008). When there is a host plant root in the vicinity of the germinating spores, signaling molecules are released by the roots into the rhizosphere and they reach the hyphae and the fungus responds to this with increased growth and intensive hyphal branching.
During symbiosis, the AM fungi obtain carbohydrates from the host plant and at the same time the host obtains water and minerals from their fungal partners enabling them to perform better under stressful conditions (Lopez Raez, et al., 2008a). This probably explains why strigolactones are produced inspite of the risk of infection by parasitic plants. It is likely that the parasitic plant has evolved the capacity to perceive the presence of a host plant by taking advantage of the already existing signaling between plants and AM fungi.
Strigolactones have been classified as a new group of plant hormones that inhibit shoot branching by preventing the outgrowth of leaf auxiliary buds. Like other plant hormones, the strigolactones require a receptor in order to exert their activity; they are active at low concentrations and can be transported over some distance (Umehara et al., 2008). Increased synthesis of strigolactones under low phosphate and nitrogen conditions leads to the proposition that under low inorganic phosphate conditions, plants increase biosynthesis of
32 strigolactones to reduce shoot branching and increase root growth to maximize interactions with AM fungi to facilitate the uptake of mineral nutrients (Lopez Raez et al., 2008b).
2.10 The parasite as a sink
There is evidence that parasitic plants generally obtain carbon and nitrogen from their hosts
(Press, 1989; Press, 1995). However, the level of dependence may differ. For example hemi- parasitic species that are facultative can survive in the absence of a host whilst holo-parasitic angiosperms rely exclusively on their hosts for their carbon and nitrogen supplies (Press,
1995). The Striga parasite has roots and pigmented leaves and that suggests that the root hemi-parasite may receive and incorporate water and solutes from both autotrophic and heterotrophic sources (Press, 1996).
Mabasa (2003) reported that the rates of photosynthesis in hemi-parasites are generally towards the low end as observed in C3 species and are usually lower than those of their hosts.
Lowly concentrated chlorophyll, poorly developed mesophyll cells and fewer air spaces between the spongy mesophyll cells (Press et al., 1988) and low levels of ribulose 1,5- biphosphate carboxylase (Press et al., 1986) in some root hemi-parasite may account for the low rates of carbon dioxide fixation. According to Graves et al., (1989), carbon budget models suggest that S hermonthica would be unable to maintain any appreciable positive carbon balance in the absence of carbon from the host. This makes the parasite a strong sink for the carbohydrates manufactured by the hosts.
2.11 Mechanisms of sorghum tolerance to Striga asiatica
2.11.1 Host photosynthesis
Host responses to infestation cannot be attributed solely to resource competition between the host and the parasite (Gurney et al., 1999). Differences in dry matter accumulation between
33 infested and uninfested plants partly results from the parasite acting as a sink for carbon, inorganic solutes and water, particularly in the later stages of infection, but also lower rates of carbon gain by the infested cereals (Cechin and Press, 1993; Gurney et al., 1995; Smith et al.,
1995).
A study by Gurney et al., (2002) found lower rates of photosynthesis for all parasite-host associations. However, the same study revealed that the tolerant Sorghum arundinaceaum was not affected by the parasite with respect to dry matter accumulation. This demonstrated the uncoupling of photosynthesis and biomass accumulation as was observed by Frost et al.,
(1997) in some sorghum–Striga associations.
In a study by Van Aast and Bastiaans (2006), it was found that two sorghum varieties
Tiemarifing and CK60-B had differential response to infection by Striga asiatica.
Tiemarifing’s reduction in panicle weight was proportional to overall reduction in total plant dry weight but for CK60-B panicle weight was much more strongly reduced in total weight than total dry mass. It was then concluded that the ability to maintain a constant harvest index under Striga infestation conditions might be another aspect of tolerance in this cultivar.
According to Haussmann et al., (2001), genetic variation for tolerance to Striga under field conditions exist in cultivated sorghum especially in local African cultivars. The different responses of wild sorghum to infection by S. hermonthica and S. asiatica suggest that these
Striga spp possibly influence host growth through different mechanisms or differential disruption of host metabolism.
Aly (2007) reported export of proteins from the host plant to the parasite. This movement of may lower protein availability hence chlorophyll.Therefore the ability of a genotype to maintain chlorophyll content irrespective of the infection is key to tolerance. Since chlorophyll concentration is connected to nitrogen availability, chlorophyll concentration
34 becomes a key parameter in the measurement of plant canopies and subsequently carbohydrate accumulation.
2.11.2 Sorghum tillering as Striga tolerance mechanism
Tillering is generally recognized as one of the most plastic traits affecting accumulation of biomass and ultimately grain yield in many field crops (Kim et al., 2010a). Tillering is one of the most important agronomic traits in poaceous crops and plays a major role in determining plant architecture and grain yield (Wu et al., 1998). Tillering confers environmental plasticity to grain crops. High tiller production capacity improves the chances of persistence after periods of unfavourable conditions during which a plant may experience biotic and abiotic stress (Assuero and Togretti, 2010). According to Bartholomew (2009), when a tiller dies as a consequence of stress, it is replaced by another tiller in order to keep forage production. The control of tillering is affected by endogeneous factors and environmental supplies (Mcsteen,
2009). According to Hammer et al., (2006), genetic variation in tillering affects the dynamics of canopy development. Yoshida (1976) reported that one of the most critical characteristics of successful high yielding varieties for rice and wheat is a semi-dwarf plant type with high tillering ability.
Although tillering is considerably less in Sorghum bicolor, it nonetheless has a major influence on plant leaf area development (Larfage et al., 2002). Modern sorghum hybrids produce from zero to four fertile tillers under field conditions such that at plant densities below 4 m-2, around 70 – 80 % of the total plant leaf area and grain yield is attributable to tillers. Kim et al., (2010a) asserted that the differences in tillering could be associated with differences in carbon supply-demand balance and the propensity to tiller could possibly be associated with hormonal signaling. Differences in tillering could be caused by differences in hormonal signaling or responsiveness to sugar level. Studies done have found novel hormones that trigger branching and are known to affect tiller growth in sorghum (George-
35
Jaeggli, 2009). Therefore, the capacity of a variety to produce tillers is important when considering tolerance to Striga.
2.11.3 Environmental regulation of tillering
Studies by Kim et al., (2010b) found that the rate of appearance of successive leaf tillers and the leaf appearance rate were similar to the appearance rate of leaves of the main shoot.
Therefore, the environmental effects on plant phenology can be important in explaining tillering dynamics in terms of topological location, appearance and fertility frequency.
Environmental conditions affect tillering through their effects on the carbohydrate supply/demand framework. Environmental effects on sorghum tillering have been reported by Kaitaniemi et al., (1999) and were due to changes in leaf elongation rate in response to temperature, vapour pressure deficit and water availability. In sorghum that is under parasite attack, there is intense nitrogen competition and carbon usage is more prominent. For a variety that uses tillering as a tolerance mechanism, the tillers should therefore appear after the Striga has completed its life cycle. Striga generally takes a total of 10 – 12 weeks to complete its life cycle. Once the Striga is dead and new tillers come up they are likely to result in more yield as there is an extensive root system that will have been established.
Assuero et al., (2000) found that tiller number was reduced by endophyte infection in two
Fastuca arundinacea that had been infested by two fungal endophyte strains Neotyphodium coenophilum strains. The same should be applied to plants parasitised by Striga as they lead to resource competition.
2.12.1 Propensity to tiller
Studies by Kim et al., (2010b) revealed that high tillering was also associated with the propensity to tiller. This is associated with hormonal signaling and responsiveness to sugar level. Umehara et al., (2008) identified the hormone strigolactone that triggers branching.
36
The hormones are known to affect tiller outgrowth in sorghum (George-Jaeggli, 2009).
Research by Jamil et al., (2011) in rice cultivars found that low tillering rice cultivars have lower strigolactones in the root exudates compared to high tillering.
2.13 Host plant resistance against Striga
Host resistance to parasitic plants is a multicomponent process that occurs at different stages of a parasite’s life cycle (Estabrook and Yoder, 1998). Rich and Ejeta (2008) reported that the biology of Striga at its various stages is a series of signal exchanges between host and parasite that leads to successful establishment. Yoder and Scholes (2010) combined the various stages of parasite development into the three general periods: pre-attachment, parasite establishment and post attachment maturation. Parasitic plants use chemical communication in the rhizosphere to trigger certain stages to occur in their life cycle. Therefore any genetic differences in the biosynthesis or release of signaling molecules can reduce parasite viability.
The types of resistance occurring in parasitic plant hosts are classified into reduced host germination stimulant production, reduced haustorium initiation factor production, host resistance to parasite establishment and host resistance after parasite establishment.
2.13.1 Reduced host stimulant production
According to Jamil et al., (2011), there is a promising opportunity to minimize losses through avoiding triggering of Striga seed germination through reduced strigolactone production.
Low production of host plant root exudates compounds that are essential for Striga germination is the understood mechanism for Striga resistance (Lynn and Chang, 1990). In a study by Sun et al., (2008), and Jamil et al., (2011), germination of Striga hermonthica seed was dependent upon the quantity and quality of strigolactone production and any genetic variation in this trait could potentially confer pre-attachment resistance. In a study by Jamil et al., (2011), rice varieties CG14, WAB56-104 and NERICA 1 produced the smallest amounts of strigolactones. The same varieties were shown to have differences in the
37 composition of the strigolactone blend. In another study, Jamil et al., (2011b) found that the concentration of strigolactones in root exudates varied strongly in rice cultivars and that in the study, Super Basmati, TN1, Anakila and Agee produced the least strigolactones. Low germination stimulant genotypes of sorghum have enhanced resistance to Striga because of the reduction in Striga germination (Ejeta, 2007). Low germination stimulant was also implicated in some legume and sunflower accessions that showed enhanced resistance to
Orobanche species.
According to Ejeta et al., (2001) all susceptible Sorghum spp appear to be high stimulant producers. Vogler et al., (1996) found that low germination stimulant (lgs) production of sorghum is controlled by a single recessive gene. According to Ejeta et al., (1997), the lgs gene found in a source germplasm has been transferred into high yielding and broadly adapted sorghum cultivars.
2.13.2 Reduced haustorium inducing factors (Low haustorial factor)
Haustoria are the structures that invade the host root and causes the formation of xylem- xylem connections. Riopel and Timko (1995) identified that phenolics, flavonoids and quinones as compounds that induce haustorial development.
The success of parasitic plants results largely from strategies that tightly couple developmental transitions with host recognition signals. This means in the absence of specific signals by a potential host, successful infestation by the parasite is prevented. Studies by
Gurney et al., (2003) found that Tripscum dactyloides, a wild relative of maize does not produce primary haustorium inducing factors as a small number of parasites initiated haustorial formation. Rich and Ejeta (2004) found sorghum lines that rarely developed haustoria.
38
Low haustorial factor (Lhf) is inherited as one dominant gene. According to Ejeta (2005) the lhf gene found in sorghum has been transferred into improved sorghum cultivars and has been pyramided with other resistant genes.
2.13.3 Parasite establishment resistance
In some cultivars, the parasite penetrates the host root cortex but is unable to form vascular continuity with the host and it dies (Gurney et al., 2005). The same study revealed that by day
9 after infection, the parasite could not form a parasite-host xylem-xylem connection. In many cases, the endophyte passed straight through the root cortex and emerged from the other side of the root. Vascular continuity allows movement of water and nutrients from host to parasite. It also provides factors required for further differentiation of the haustorium.
In a study by Gurney et al., (2006), the haustorium of parasites attached to the sorghum variety Noponbare did not mature and differentiate. Their results indicated that by day 21, 49
% of the attached parasites were either dead or showed signs of necrosis. In other sorghum varieties (Framida and Dobbs), a proportion of the parasites died owing to the onset of the rapid hypersensitive reaction (Mohamed et al., 2003).
2.13.4 Post-attachment resistance
Resistance can occur following successful connection of parasites to the host vascular system
(Yoder and Scholes, 2010). Perez-de-Luque et al., (2006) found that in some pea genotypes, host vascular cells fill with mucilage-like compounds that block the transport of nutrients to the parasite leading to death of tubercules.
2.13.5 Incompatible response (IR)
This response is similar to the hypersensitive response in that it discourages the development of Striga beyond attachment. There is however no apparent necrosis in host root tissue surrounding the attachment site. In the IR based resistance, Striga seedlings that penetrated
39 the host tissue may not develop beyond first emergence of leaf primordia (Ejeta, 2005). Some
Striga appear to develop normally at first but show signs of stunted growth with time.
2.13.6 Hypersensitive response
In some sorghum genotypes, necrotic areas appear on roots at the site of Striga attachment.
Ejeta (2005) reported that necrotic lesions start as red becoming brownish with time and can spread to 2 mm from the centre of attachment but most remain more localized. This discourages further advancement of attached Striga which does not develop normally and eventually dies on the host. Sorghum varieties with this phenomenon have been observed and they include Framida, CK32 and CK33 (Ejeta, 2005). Hypersensitive reaction is conditioned by two complementary dominant genes.
2.14 Managing Striga asiatica in sub-Saharan Africa
Despite the concerted efforts to come up with a sustainable method of Striga asiatica control, there is no sustainable control method available for managing the parasite. It remains as the number one biological constraint limiting the production of cereal grains in sub-Saharan
Africa. Several methods have been studied but have been accompanied by minimum success.
The numerous methods that have been suggested or developed together with their technical limitations are shown in Table 2.4.
Table 2.4: Different methods of controlling Striga asiatica
Control Mechanism Limitation References
strategy
Increased soil Shortage of nitrogen Most of the Williams (1961), Raju et al., (1990)
fertility and phosphorus leads to affected farmers Mabasa (2003), Jamil et al., (2011),
more active production cannot afford the Lopez-Raez et al., (2008),
of strigolactone to levels of fertiliser Yoneyama et al., (2007a, 2007b))
40
attract mychorhizal required to reduce
fungi for increased production of
nutrient absorption. strigolactones
Intercropping The mechanism Jasi and Mabasa (2001), with legumes according to Fernandez- Rambabkudzibga and Mabasa
Aparicio et al., (2011) (1993), Kabambe (1991),
involves smothering by Musambasi (1997), Kasembe
cover crops and (1995), Mbwaga (1995), Adipala et
increase in soil moisture al., (1997), Kuchinda et al., (2003),
and fertility for legumes Carsky et al., (1994), Oswald et al.,
and decrease soil (2002), Khan et al., (2006), Midega
temperature. et al., (2010), Picket et al., (2010),
Khan et al., (2008) Tsanuo et al.,
2003; Hooper et al., 2010.
Trap crops These crops stimulate Trap crops cannot Rao and Gacheru (1998), Oswald et
germination of the exhaust the seed al., (1996), Odhiambo and Ransom
parasitic weed but is not banks and their (1996).
compatible with cultivation may not
subsequent infection be economic.
process
Catch crops These are true hosts that Not economic for Oswald et al., (1997)
promote Striga the farmer
germination but will be
burnt or chopped down
as soon as Striga
germinates
Host Low strigolactone This is a Jamil et al., (2011), Gurney et al., resistance or production, low sustainable (2003), Rich and Ejeta (2008), El
41
tolerance haustorial initiation approach but not Heweris (1987).
factors, plugging of even one sorghum
xylem-xylem cultivar has shown
connection between complete
host and parasite and resistance.
antibiosis.
Herbicide Herbicide coated seed Successful so far Samb and Chamel (1992), Chivinge
seed dressing maize uses germplasm et al., (1999), Odhiambo and
resistant to Ransom (1993), Kanampiu et al.,
Imidazolinone group of (1997), Manyong et al., (2008),
accetolactate synthase Kanampiu et al., (2002)
(ALS) inhibiting family
of herbicides.
2.15. Sorghum response to drought stress
About a third of the world’s agricultural land currently suffers from chronically inadequate water availability (Ghannoun, 2009). Adaptations to drought is a quantitative trait controlled by many genes (Fenta et al., 2012). According to Mitchell et al., (2013), plants exposed to low intensity but long duration droughts may maintain water status above the critical water potential thresholds but deplete stored carbohydrates. High intensity drought and incapability to regulate plant water status above critical thresholds will lead to plant death. The ability of a plant to maintain high rates of photosynthesis is an important determinant of the ability of a crop plant to maintain growth and indicates tolerance of a crop to drought and Striga infections.
Fenta et al., (2012) found differences in root biomass under water replete conditions with one variety showing the greatest biomass accumulation. The same trend was demonstrated for
42 root biomass while no differences were shown in shoot/root biomass. The same study found that tolerance was often concentrated largely on shoot parameters, particularly those associated with photosynthesis. Gilbert et al., (2011) found that considerable genetic differences exist in the ability of soyabeans to maintain high water use efficiency and photosynthesis during drought. Genetic differences in stomatal conductance are considered to exert the greatest effect on the intrinsic water use efficiency (Gilbert et al., 2011). The stability of photosynthesis under conditions of water deprivations is also considered to be an important aspect of drought tolerance.
The sorghum plant has the capability of withstanding drought conditions through adjustments in stomatal aperture, maintenance of cell turgor, hydraulic conductivity and maintenance of cell photosynthesis. However, the introduction of an extra sink from the parasite may alter this delicate balance. Even if sorghum varieties may be tolerant to drought, the occurrence of drought to a host attached to the parasite may aggravate the situation. The ability of a sorghum plant to withstand both the parasite and drought may be compromised.
2.16 Existence of Striga physiological speciation and differential virulence
A lot of Striga management systems have been suggested, including introduction of resistant sorghum varieties. According to Mohammed et al., (2007), crops with some measure of resistance have been integrated into Striga management programmes and the new material gets challenged by the Striga seed bank. The newly introduced sorghum variety must be able to cope with the great potential genetic diversity in the seed bank. One of the major problems in Striga control is the possible existence of physiological speciation within the species of
Striga as was first suggested by Jones (1955). Ten years later, Doggett (1965), was the first one to report varietal differences in sorghum susceptibility to Striga hermonthica in east
Africa. It was observed that varieties of sorghum that were resistant in one location became susceptible in another suggesting the existence of physiological strains of the parasite.
43
According to Bozkurt et al. (2015), genetic variation for virulence can enable the parasite to adapt to new host resistance alleles and several studies have been undertaken to understand the parasite’s genetic diversity and variability for virulence.
Rao and Musselmann (1987) suggested the possible causes of the differential response to be
Striga intensity differences, instability of host resistance or other several soil and environmental factors which affect resistance of the host cultivars. Bebawi (1981) investigated the germination response of eleven Striga hermonthica samples from sorghum and pearl millet exudates of 27 sorghum cultivars and confirmed the suspiscions of physiological speciation in Striga which had been alluded to by Parker and Reid (1979).
Botanga and Timko (2006), suggested that geographical isolation and host driven selection are important factors in the formation of races of Striga gesneriodes in West Africa. In Striga asiatica and Striga hermonthica populations from Kenya, 96.8 % and 84 % of the Amplified fragment length polymorphism (AFLP) bands were polymorphic respectively (Gethi et al.,
2005). The observed polymorphism indicated that different strains were in each of the Striga populations. A study in Benin discovered a high degree of host speciation within the 14 analysed Striga asiatica populations (Botanga et al., 2002). According to Spallek et al.,
(2013), Striga asiatica isolated from wild grasses species were unable to successfully parasitise sorghum and maize plants susceptible to other Striga asiatica collections. The same authors found a significant relationship between genetic and geographic distances in Striga species.
2.17 Mulch effects on Striga asiatica incidence
There is a growing worldwide concern about soil health, usage of fossil fuels and overall economics of field crop production. Conservation agriculture (CA) is being promoted
44 globally as a farming system that can address many of those concerns and increase the overall economic productivity of mechanised agriculture (Norsworthy and Oleivera, 2007; Hobbs et al., 2008; Sanyal et al., 2008). Conservation agriculture is a broad term, which encompasses activities such as minimum and zero tillage, tractor powered, animal powered and manual methods, integrated soil and water management and includes conservation farming. It is generally defined as any tillage sequence that minimises soil and water loss and achieves at least 30 % soil cover by crop residues.
According to Bilalis et al., (2003), the correct use of residues helps to conserve moisture and deal with weeds while improving soil structure. Teasdale and Mohler (1993) indicated that annual weed infestation decreases as crop residues increase on the soil surface offering direct evidence that crop residues control weed emergence. The effect of the surface mulch on weed seedling emergence is controlled by several factors such as quality of residue, weed species, position in the soil, soil type and environmental conditions. According to Liebman et al.,
(2001), the mechanisms for weed suppression include changes in soil moisture, reduced temperatures at the soil surface, physical impedance and allelopathy.
Weed response to residue depends on quality, quantity of residue and biology of a particular weed. Residues of small grains have been shown to inhibit weed emergence and growth in cropping systems (Putnam et al., 1983). Mulch therefore exerts a selection pressure on weeds and the weeds that possess traits that enable them to germinate on the surface will increase in numbers.
Crop residues used as mulch substantially decrease maximum daily soil temperature (Mohler and Teasdale, 1993). Differences in temperature between mulched and unmulched plots can be as great as 14 oC. Mulch shades weed seeds from light and prevents shoot growth. The presence of light might indicate proximity to the soil surface or absence of overstorey canopy
45 and assurance for successful establishments and growth. Mohler and Teasdale (1993) reported that large quantities of residues were needed to effect weed control as total weed emergence paralleled light transmittance through the residues. The ability of mulch to suppress weeds is also correlated to light extinction coefficient of the mulch. However no study has sought to determine the effects of mulch on Striga asiatica establishments.
2.18 Photosynthesis in a Striga-infested plant
According to Gurney et al., (1999), an increased understanding of the parasitic mode of nutrition has demonstrated that host response to infestation cannot be attributed to more competition between the host and the parasite. Reduced photosynthesis may account for the lower rates of host productivity. Graves et al., (1989) found that 80 % of the biomass not accumulated by the host compared with uninfested plants can be accounted for by lower carbon fixation in infested plants compared to controls. Gurney et al., (2002) suggested that an ability to maintain high rate of photosynthesis while infested may be an important factor of tolerance to the parasite.
According to Frost et al., (1997) lower rates of photosynthesis are a consequence of lower stomatal conductance, particularly in the early stages of infection. Increased levels of the plant growth regulator abscissic acid in infested plants cause stomatal closure (Taylor et al.,
1996; Gurney et al., 1997). The effects of plant parasites on their hosts vary from undetectable levels where a plant proceeds to reproduction as if there is no pest to extreme cases where the host dies. Some Striga-cereal associations result in stunting of the internode elongation leading to unpacking of the leaves within the canopy (Walting and Press, 1997,
1998).
46
2.18.1 Stomatal conductance
One of the shoot related physiological traits that may affect stress tolerance is the decline in whole plant water use during soil water deficit events (Manavalan et al., 2009). In most cases, stomatal conductance affects leaf gas and water vapour exchange. According to Liu et al., (2003), drought stress decreases relative leaf expansion rate, stomatal conductance and leaf turgor whereas it increases abscissic acid content in the leaf and xylem. There are obviously genetic differences in the ability to keep stomata open despite the presence of stress in some plants. The control of stomatal conductance under stress is a physiological trait that can be exploited when developing drought resistant materials in sorghum.
Adjustments in stomatal arpeture act to reduce transpiration in response to the declining hydraulic conductance and/or reductions in leaf turgor and help plants to avoid water potentials that can induce hydraulic failure (Sperry, 2000). Phosphorus and potassium are the most essential nutrients. Ruiz-Lozamo et al., (1995) asserted that in particular, potassium plays a key role in plant water stress and has been found to be the cationic solute responsible for stomatal movement. Ge et al., (2012) found that the decline in nutrient uptake especially
P and K was because of low transpiration rate under soil water deficit. This had earlier been observed by Sinha (1978) that stress tolerant wheat varieties can accumulate more potassium than susceptible ones and that plants well supplied with potassium have higher stomatal resistance which resulted in low transpiration rates.
2.19 Conclusions
A comprehensive up-to-date review of literature was conducted. In this review, Striga was found to cause devastating effects on sorghum production. The life cycle of Striga spp was discussed paying attention to its multi-stage nature, and depedance on host signals. The current management methods were reviewed together with the limitations of each of them.
47
Tolerance was determined as central to Striga management since there is no single genotype that has been found to be completely resistant. However, there is limited information on the response of sorghum spp to various ecological factors such as mulching, drought and the existence of physiological speciation in Striga.
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67
Chapter Three:
The effect of witchweed (Striga asiatica L. Kuntze) and moisture stress on selected morpho-physiological traits which impart tolerance to Sorghum spp
3.1 Abstract
Sorghum production is hampered by the parasite Striga asiatica and recurring droughts.
However, the morpho-physiological effects of these combined stresses on tolerance of sorghum traits are poorly understood. Two pot experiments were set up to determine the effects of the two stresses on morpho-physiological traits of sorghum. A 2 * 2 * 5 factorial experiment laid down as a completely randomised design replicated three times was carried out twice at Bindura University of Science Education (BUSE) nursery. The first factor was water availability at two levels: 50 % field capacity (FC) and 100 % FC. Infection was the second factor at two levels: infested and uninfested, and all these were imposed on five sorghum lines, including wild sorghum (Sorghum arundinaceaum). Sorghum chlorophyll content, normalized difference vegetation index (NDVI) and dry matter traits were analysed using Genstat version 14 to compare treatment effects. Watering at 100 % FC gave the higher
(P<0.01) NDVI across all the measured periods compared to 50 % FC. The results indicated that sorghum genotypes differed sharply with respect to chlorophyll content and the NDVI with the genotype Mukadziusaende having the most chlorophyll and NDVI (P<0.05), whilst the least was wild sorghum. Chlorophyll content and NDVI differed significantly among genotypes while limited water availability did not reduce chlorophyll content of
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Mukadziusaende, wild sorghum and Chiredhi. Striga infection when it co-occurred with water stress did not affect chlorophyll content. Mukadziusaende had the highest (P<0.05) head weight and head index. Infestation with Striga significantly reduced (P<0.05) head weight across all treatments. Drought stress and Striga infection had mutually exclusive effects on chlorophyll content and NDVI. However, both infection and drought stress reduced head weight illustrating the two factors were synergistic on their effects on sorghum head weight.
3.2 Introduction
Sorghum is an important cereal crop that feeds more than a third of the population in southern
Africa. One of the remarkable characteristics of sorghum is its drought tolerance, that has made it an important cereal grown for food and beverages in sub-Saharan Africa (SSA).
Among the major constraints of sorghum production are drought and infestation with Striga asiatica. Striga is a parasitic weed that attaches itself to the roots of sorghum from where it draws its moisture and nutrient requirements thus inhibiting host plant growth, reducing yield and in severe cases, causing plant death. Striga affects the major crops that supply the bulk of the carbohydrate and protein needs of the poor who reside in SSA (Ejeta, 2005). Scholes and
Press (2008) and Ejeta (2007) reported that over 50 million hectares of arable farmland under cultivation with cereals and legumes are infested with one or more Striga species in SSA.
About a third of the world’s agricultural land currently suffers from chronically inadequate water availability (Ghanounn et al., 2009) and this situation is predicted to worsen (Jury and
Vaux, 2007) due to climate change. Global warming, changes in rainfall abundance and frequency and severity of rainfall events may exert a significant pressure on agricultural water use, with several regions currently experiencing water deficits likely to face further shortages (Padgam, 2009). Infact, many of the world’s poorest people farm in areas with inadequate and unreliable rainfall. Even in traditionally irrigated areas, water stress is
69 becoming a serious threat to crop production due to water scarcity resulting from the growing and competing demands for water uses. Despite all this, agricultural productivity must be increased to provide food for the world’s ever increasing population. Future food demand for the rapidly increasing population pressures is likely to further aggravate the effects of drought
(Somerville and Briscoe, 2001).
Under natural conditions, a combination of two or more stresses such as drought, salinity and heat are common to many agricultural areas around the world and negatively impacts crop productivity (Suzuki et al., 2014). Information on plant performance under a more complex environment where multiple stresses co-occur is fragmentary (Farooq et al., 2010). Cramer et al., (2011) asserted that the major crops of the world are likely to be exposed to a wide range and a number of abiotic and biotic stress conditions as well as their combinations. Stress combinations represent one of the most critical challenges facing sorghum production today and improved theory and practice are needed for quantification of genotype responses. As an example, studies done elsewhere have revealed that the molecular responses of plants to a combination of heat stress and drought is unique and cannot be directly extrapolated from the response of plants to stresses such as drought or heat when applied individually (Rhizhsky et al., 2002, Suzuki et al., 2005; Mittler et al., 2006).
There has been contrasting responses of different plants to different stress combinations.
Demirevska et al., (2010) found that tobacco showed the same physiological responses to drought and heat and their combinations. In barley, the effect of drought or heat stress reduced plant growth with a more severe effect coming from drought. The combination of drought and heat stress reduced plant growth to a much greater extent than drought or heat applied individually (Suzuki et al., 2014). However, Iyer et al., (2013) reported that
Medicago truncatula showed contrasting responses to a combination of ozone and drought stress. Ozone stress caused development of chlorotic and necrotic tissue and drought alone
70 caused wilting and collapse of leaves but a combination of the two stresses cancelled the effects of both stresses. Drought leads to stomatal closure and reduce the uptake of pollutants via stomata thereby ameliorating the effect of gaseous pollutants like ozone (Olinger et al.,
1997; Low 2006). Actually, Suzuki et al., (2014) posited that some stress combinations might have beneficial effects compared with the occurrence of separate stresses. Understanding the limits of stress tolerance and acclimation to stress is of great importance and practical value in predicting the potential limit of plant productivity (Isebrands et al., 2000).
Wahid and Rasul (2005) found that the major effect of drought is reduction in photosynthetic machinery and pre-mature leaf senescence culminating in reduction of food production.
Drought stress produces changes in photosynthetic pigments and components (Anjom et al.,
2003) and diminishes the activities of the Calvin cycle enzymes which reduce yields (Fu and
Huang, 2001). According to Cramer et al., (2011), the hormones abscisic acid (ABA) and ethylene have been found to be important regulators of plant responses to both abiotic and biotic stresses. Striga has been shown to increase ABA in infested maize and sorghum plants
(Frost et al., 1997; Taylor and Frost, 1997). ABA induces stomatal closure which allows a reduction in water loss and as a consequence, the maintenance of beneficial water potential.
Farooq et al., (2010) reported that the stoma close gradually as drought progresses, followed by the parallel decline in net photosynthesis. Studies done on maize have shown that drought stress leads to morphological, physiological and biochemical changes, including reduced photosynthesis (Pervez et al., 2004; Zhao et al., 2010). Drought stress frequently enhances allocation of dry matter to the roots which enhance water uptake (Leport et al., 2006).
Although the sorghum crop has evolved appropriate stress tolerance strategies, they are largely incompatible with the exploitative root parasitic strategy of Striga species (Tesitel et al., 2015). Given that global change involves a series of environmental factors occurring concurrently and changes in the severity of different stress factors; knowledge on how plants
71 acclimate to multiple stresses is of key importance in understanding the effects of the future climate on crops (Niinemets, 2010). An urgent need to generate crops with enhanced tolerance to stress combinations therefore exists (Suzuki et al., 2014). It is necessary to select for sorghum genotypes with enhanced tolerance to Striga asiatica, drought, and a combination of the stresses. To determine the response of sorghum to a combination of abiotic and biotic stresses applied simultaneously, the effects of Striga asiatica parasite and drought on chlorophyll content, internode length, dry matter traits and productivity of sorghum were studied. A combination of drought and Striga stress represent conditions encountered by many cereal crops growing in the semi-arid environments of the sub tropical regions of Africa. It becomes necessary to select for sorghum genotypes with enhanced tolerance to drought and Striga asiatica and their combinations to ensure food security for the poorly resourced farmers. The objectives of this study were:
i) To determine the effect of Striga infestation and reduced water availability on
normalized difference vegetation index (NDVI), chlorophyll concentration and
sorghum height as tolerance parameters to Striga.
ii) To determine the effects of Striga asiatica infestation and water availability on
sorghum yield and dry matter partitioning of sorghum.
The associated alternate hypotheses were:
i) Striga infestation and reduced water availability, lower chlorophyll content, NDVI
and sorghum height.
ii) Striga infestation and reduced water availability reduces sorghum yield and alters dry
matter partitioning of the host species.
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3.3 Methodology
3.3.1 Experimental site
The pot experiments were carried out at Bindura University of Science Education (BUSE)
Astra Campus nursery, Bindura (17o 181 5811 S and 31o 191 2311 East). Bindura is located 89 km north of the city of Harare. The soil type used was sandy, with 4.3 % clay content and a pH of 4.4. The area receives an annual rainfall of about 700 mm per annum, with an average temperature of 25 oC in the summer months.
3.3.2 Seed sources
Striga asiatica seeds were obtained from Henderson Research Station (Weed Research team) at Mazowe in Zimbabwe. The seeds had been collected from Chiwundura communal lands in the Midlands Province in Zimbabwe from farmers’ fields in the 2009 summer season.
Sorghum seed was obtained from the gene bank at the Department of Research and Specialist
Services in Harare. Wild sorghum seeds were collected from Gwebi Agricultural College fields, 27 km west of Harare.
3.3.3 Experimental design and treatments
The experiment was a 2 * 2 * 5 factorial experiment laid down as a randomized complete block design replicated three times. The first factor was sorghum genotype at five levels, the second factor was infestation at two levels, infested and uninfested. The third factor was irrigation at two levels, 50 % and 100 % of field capacity. The moisture level of 50 % Field
Capacity (FC) was included to mimic the low rainfall areas in SSA where total rainfall is usually below 400 mm and that is where Striga has deleterious effects. Irrigation scheduling was done using the 100 % field capacity application. The experiment was repeated twice over time, and denoted as experiments I and II.
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3.3.4 Experimental procedures
Plastic pots with a height of 27 cm and diameters of 25 cm and 17.5 cm for the top and bottom, respectively, were filled with 8 kg of soil. All pots had six drainage holes at the bottom. Half the pots were infested with 1 gram of Striga asiatica seeds and mixed with the top 10 cm of the soil. Fertilizer was applied at a rate of 5 g maizefert (8 N: 14 P2O5: 7 K2O) per pot. Top dressing was done at 4 weeks after crop emergence (WACE) by applying 2.5 grammes of ammonium nitrate (34.5 % N). Ten sorghum seeds were planted and germinated after 6 days and were thinned to one plant per pot at 2 WACE. Weeds other than Striga were hand pulled as soon as they emerged.
3.3.5 Irrigation
The soil had its water holding capacity determined and half the pots were watered with water that gave the field capacity (FC) and the other by half that amount. To determine field capacity, five pots with the same oven dried soil were weighed and gradually filled with water until the addition of any extra water created a tiny flood layer. The pots were then left to drain freely for 48 hours and weighed again. This method was according to Kabiri et al.,
(2014). The amount required to reach field capacity was 1.5 litres per pot. The pots were irrigated to a moisture content of 100 % and 50 % field capacity according to Webster and
Grey (2008) and Chauhan and Johnson (2010).
3.3.6 Data collection
Data collected during crop growth were: normalized difference vegetation index (NDVI), chlorophyll content and sorghum internode length. The NDVI was measured using a handheld green-seeker optical sensor unit (NTech industries, Inc, USA). Chlorophyll content was measured using a chlorophyll meter (SPAD 502, KONICA MINOLTA Incl) starting
74 from 6 WACE. At the end of the experiment, head weight and total dry matter were determined using a sensitive scale. At crop maturity, the sorghum plants were harvested and partitioned into roots, leaves and stems. They were put in the drier at 104 oC for 48 hours for dry matter determination using a sensitive weight scale. Total dry matter constituted the total weights of roots, leaves, stems and head for each treatment. Head, stem, leaf and root indices were computed as follows:
Part (e.g. roots, leaves stems) Index = Part weight/Total dry weight.
3.3.7 Statistical analysis
Data was assessed by analysis of variance using Genstat version 14. Means that were significantly different were separated using LSD at 0.05 probability level.Barlett’s test was applied and variances for the two experiments were not homogeneous, hence the data were analysed separately.
3.4 Results
3.4.1 Chlorophyll concentration and NDVI
Sorghum varieties differed sharply with respect to chlorophyll concentration (P<0.01).
Across all the measured periods (6 and 10 WACE) in both experiments, the sorghum genotype Mukadziusaende gave the highest chlorophyll content and the least was recorded for wild sorghum (Table 3.1).
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Table 3.1: Sorghum genotypes effects on chlorophyll content at 6 and 10 WACE
Experiment I Experiment II
Chlorophyll concentration Chlorophyll concentration
(mmolcm-2) (mmolcm-2)
Sorghum 6 WACE 10 WACE 6 WACE 10 WACE genotype
SC Sila 40.21±2.14a 40.5±2.025a 38.39±2.035a 31.04±3.152a
Mukadziusaende 43.00±2.14a 47.23±2.025b 42.33±2.035b 33.55±3.152a
Wild Sorghum 34.9±2.14b 36.3±2.025c 32.39±2.035c 29.78±3.152a
Chiredhi 40.07±2.14a 42.09±2.025a 38.49±2.035a 32.95±3.152a
Isifumbathe 43.77±2.14a 41.46±2.025a 39.8±2.035a 31.97±3.152a
At increased moisture availability, there were significantly higher (P<0.005) NDVI values compared to 50 % FC across the measured periods in both experiments (Table 3.2).
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Table 3.2: Moisture stress effects on NDVI at 6 and 10 WACE
Experiment I Experiment II
6 WACE 10 WACE 6 WACE 10 WACE
100 % FC 0.525±0.067a 0.594±0.0242a 0.59±0.0242a 0.528±0.0267a
50 % FC 0.464±0.067b 0.523±0.0242b 0.523±0.0242b 0.464±0.0267b
At 10 WACE in experiment II, there was a significant interaction of genotype and water availability on NDVI (Figure 3.1). For the genotype Chiredhi, higher NDVI were found at
100 % FC compared to 50 % FC. All the other genotypes had similar NDVI despite different moisture availabilities (Figure 3.1).
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0.7 100 % 50 % 0.6
0.5
0.4
NDVI 0.3
0.2
0.1
0.0
SC Sila Chiredhi Isifumbathe Wild Sorghum Mukadziusaende
Sorghum varieties
Figure 3.1: Interaction effects of sorghum genotype and moisture availability on NDVI at 10 WACE in Experiment II.
Chlorophyll content was not significantly affected by infection except at 6 WACE in
Experiment II (Table 3.3). Infection did not affect chlorophyll content in Experiment I and at
10 WACE in Experiment II. At 6 WACE, uninfested sorghum had a significantly higher chlorophyll content compared to infested (Table 3.3).
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Table 3.3: Effect of S. asiatica infection on chlorophyll content of sorghum
Chlorophyll content (mmolcm-2)
Experiment I Experiment II
6 WACE 10 WACE 6 WACE 10 WACE
Infected 40.99±1.359a 41.54±1.295a 36.73±1.458a 31.35±1.994a
Uninfected 39.79±1.359a 41.59±1.295a 39.8±1.458b 32.37±1.994a
Figure 3.2: Interaction effects of sorghum genotypes and water availability on chlorophyll concentration at 6 WACE in Experiment II.
The genotypes Mukadziusaende, Wild sorghum and Chiredhi maintained their chlorophyll content despite variations in moisture availability. The chlorophyll concentration of genotypes Isifumbathe and SC Sila was significantly (P<0.05) lowered by reduced moisture availability (Figure 3.2).
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60
100 % FC 50 % FC 50
)
-2
40
30
20
Chlorophyll content (mmolcm content Chlorophyll 10
0
Sc Sila Chiredhi Isifumbathe Wild Sorghum Mukadziusaende
Sorghum genotypes
Figure 3.2: Interaction effects of sorghum genotypes and water availability on chlorophyll concentration at 6 WACE in experiment II.
3.4.2 Internode length
Sorghum internode length was significantly lowered by infection (P<0.01). The uninfested sorghum genotypes gave longer internode lengths compared to infested ones (Figure 3.3).
10
8
6
4
Internode length (cm)
2
0 Infested Uninfested Infestation status
Figure 3.3: Effect of Striga infestation on internode length.
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A significant interaction of infection and drought (P<0.01) showed that under Striga infestation, internode length was the same both for 100 % FC and 50 % FC, whilst under non infested conditions, 100 % FC increased sorghum internode compared to 50 % FC (Figure
3.4)
12
100 % FC 50 % FC 10
8
6
4
Internode (cm) length
2
0 Infested Uninfested Infection status
Figure 3.4: Interaction effects of Striga infestation and water availability on sorghum internode length.
3.4.2 Dry matter traits
Striga infested sorghum significantly (P<0.05) increased both root weight and root index in experiment I. In experiment II, infestation did not affect either root weight or root index
(Table 3.4). In both experiments, irrigation at 100 % FC increased root weight compared to
50 % FC.
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Table 3.4: Effect of infestation and moisture availability on root weight and root index
Experiment I Experiment II
Root weight (g) Root Index Root weight Root index
Striga infested 39.6±4.53a 0.489±0.029a 34±3.99a 0.479±0.028a
Uninfested 29.4±4.53b 0.429±0.029b 28.8±3.99a 0.426±0.028a
100 % FC 41.4±4.53a 0.464±0.029a 37.4±2.28a 0.448±0.028a
50 % FC 27.6±4.53b 0.453±0.029a 25.4±2.28b 0.457±0.028a
Head weight and head index were significantly affected by sorghum genotype across the two experiments (Table 3.4).
Table 3.5: Effect of sorghum genotypes on head weight and head index
Experiment I Experiment II
Sorghum Head weight (g) Head index Head weight (g) Head index genotype
SC Sila 4.04±1.304a 0.056±0.0266a 5.52±1.228a 0.0659±0.0211a
Mukadziusaende 8.12±1.304b 0.165±0.0266b 8.05±1.228b 0.1446±0.0211b
Wild Sorghum 0.44±1.304c 0.005±0.0266a 1.96±1.228c 0.0207±0.0211c
Chiredhi 3.22±1.304a 0.0544±0.0266a 3.4±1.228c 0.0486±0.0211ac
Isifumbathe 1.85±1.304ac 0.0339±0.0266a 1.94±1.228c 0.0268±0.0211dc
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Head weight was highest on the genotype Mukadziusaende, which had head indices of 0.16 and 0.45 in experiment I and II respectively. The least head weight and head index were recorded for wild sorghum in both experiments (Table 3.5).
Table 3.6: The effect of infection on head weight and head index
Experiment I Experiment II
Head weight (g) Head index Head weight (g) Head index
Infested 2.31±0.825a 0.0385±0.0168a 2.83±0.777a 0.0432±0.0134a
Uninfested 4.76±0.825b 0.0874±0.0168b 5.52±0.777b 0.0795±0.0134b
The results revealed that infestation significantly reduced head weight and head index in both experiments. Non infestation led to increase in head weight and head index in both experiments (Table 3.6).
Table 3.6: The effect of water availability on head weight and head index across the two experiments
Experiment I Experiment II
Head weight (g) Head index Head weight (g) Head index
100 % FC 4.93±0.825a 0.0755±0.034a 6.14±0.777a 0.777±0.0133a
50 % FC 2.14±0.825b 0.0504±0.034a 2.21±0.777b 0.045±0.0133b
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Increased water availability significantly increased head weight and head index in both experiments except head index in experiment I (Table 3.6). Increased moisture availability significantly increased (P<0.05) head weight for SC Sila and Mukadziusaende, whilst the rest of the sorghum genotypes did not respond to moisture availability (Figure 3.3).
16
14 100 % FC 12 50 % FC
10
8
6
Sorghum (g) yield
4
2
0
Sc Sila Chiredhi Isifumbathe Wild Sorghum Mukadziusaende
Sorghum genotypes
Figure 3.3: The response of sorghum genotypes yield to moisture availability.
The yields of wild sorghum, Chiredhi and Isifumbathe were not affected by water availability. However, yields of SC Sila and Mukadziusaende were lowered by reduced moisture availability although they remained higher than the other genotypes (Figure 3.5).
The yield of Mukadziusaende at 50 % water availability was still higher compared to wild sorghum at 100 % FC (Figure 3.5).
In experiment II, leaf index, stem weight and stem indices were significantly affected by sorghum genotypes (Table 3.7). However, SC Sila had a significantly (P<0.01) higher dry weight and the least was Mukadziusaende. This trend was repeated for Experiment 11 (Table
84
3.7). Infestation did not affect leaf weight, leaf index, stem weight and stem index and total dry matter for both experiments (Table 3.8). However, irrigation at 100 % field capacity gave a significantly higher leaf weight, leaf index, stem weight, stem index and total dry matter in both experiments (Table 3.9).
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Table 3.7: Effect of sorghum genotypes on leaf dry matter, leaf index, stem weight and index and total dry matter in both experiments
Experiment I Experiment II
Sorghum genotype Leaf Index Leaf dry matter Stem weight Stem index Total dry Leaf weight (g) Leaf index Stem weight Stem index Total dry matter
(g) (g) matter (g) (g) (g)
Sc Sila 0.197±0.028a 14.54±1.754a 21.2±3.2a 0.284±0.032a 78.4±9.21a 14.92±1.684a 0.2055±0.024a 19.0±2.91a 0.262±0.034a 75.8±7.83a
Mukadziusaende 0.1888±0.028a 9.20±1.754b 15.9±3.2a 0.312±0.032a 49.7±9.21b 8.85±1.684b 0.1767±0.024a 14.84±2.91a 0.291±0.034a 49.8±7.83b
Wild sorghum 0.2028±0.028a 16.81±1.754a 18.4±3.2a 0.248±0.032a 76.3±9.21a 15.7±1.684a 0.2314±0.024a 17.12±2.91a 0.238±0.034a 71.5±7.83a
Chiredhi 0.1972±0.028a 14.62±1.754a 22.9±3.2a 0.293±0.032a 77.9±9.21a 13.32±1.684a 0.1954±0.024a 21.27±2.91a 0.303±0.034a 71.4±7.83a
Isifumbathe 0.222±0.028a 15.94±1.754a 18.4±3.2a 0.248±0.032a 74.1±9.21a 12.91±1.684a 0.1925±0.024a 19.3±2.91a 0.292±0.034a 66.7±7.83a
Table 3.8: The effect of infection on leaf weight and index, stem weight and index and total dry matter in both experiments.
Experiment I Experiment II
Leaf weight (g) Leaf index Stem weight (g) Stem index Total dry matter Leaf weight (g) Leaf index Stem weight (g) Stem Index Total dry matter
(g) (g)
Infested 14.63 0.205±0.018a 19.4±2.03a 0.267±0.014a 75.9±5.82a 13.48±1.06a 0.2028±0.015a 17.99±1.84a 0.269±0.02a 68.3±4.95a
Uninfested 13.82 0.197±0.018a 19.3±2.03a 0.287±0.014a 66.7±5.82a 12.8±1.06a 0.1978±0.015a 18.62±1.84a 0.285±0.02a 65.7±4.95a
86
Table 3.9: The effects of water availability on leaf weight and index, stem weight and index and total dry matter.
Experiment I Experiment II
Water Leaf weight (g) Leaf index Stem weight (g) Stem Index Total dry Leaf weight (g) Leaf Index Stem weight (g) Stem index Total dry availability matter (g) matter (g)
100 % FC 15.81±1.109a 0.1947±0.0176a 22.1±2.03a 0.266±0.302a 84.2±5.82a 15.08±1.065a 0.1943±0.015a 21.3±1.842a 0.269±0.02a 79.9±4.95a
50 % FC 12.64±1.109b 0.1922±0.0176a 16.6±2.03b 0.287±0.302b 58.4±5.82b 11.20±1.065b 0.2063±0.015a 15.32±1.842b 0.285±0.02a 54.1±4.95b
87
There was a significant effect of infection and drought on leaf index (P<0.05) (Figure 3.7)
0.30 100 % irrigation 50 % Irrigation 0.25
0.20
0.15
Leaf index
0.10
0.05
0.00 Infested Uninfested Infestation status
Figure3.6: Interaction effects of water availability and Striga infestation on leaf index.
Under infestation, 100 % irrigation had a lower leaf index compared to 50 % and under infestation there were no significant differences (Figure 3.7). There was a significant interaction of variety and infection on stem dry matter (P <0.05). Stem weight of wild sorghum was reduced by Striga infestation (P<0.05) whilst it was vice versa for Chiredhi
(Figure 3.7).
88
35
30 Infested Uninfested
25
20
15
Stem weight (g)Stem
10
5
0
Sc Sila Chiredhi Wild sorghum Isifumbathe Mukadziusaende
Sorghum genotypes
Figure 3.7: Interaction effects of sorghum genotypes and Striga asiatica infestation on stem weight
3.5 Discussion
The objective of the study was to determine the effects of Striga asiatica and water stress occurring simultaneously on sorghum productivity. The sorghum genotype Mukadziusaende had the highest chlorophyll concentration of 47.33 mmolcm-2, and the least was recorded for wild sorghum, with 29.78 mmolcm-2. This trend for chlorophyll concentration was the same for both experiments. These values are in the range commensurate with Gurney et al.,
(2002)’s findings, where a maximum of 47.44 and a minimum of 32.33 mmolcm-2 were reported.
Chlorophyll concentration was lowered by moisture deficit when irrigated at 50 % FC compared to 100 % FC (Table 3.2) but was not affected by infection (Table 3.4). This contrasts with the findings of Gurney et al., (2002), where Striga asiatica infection alone
89 reduced chlorophyll concentration. Similar results were also found by Wahid and Rasul
(2005) and Fu and Huang (2001) who reported that drought impaired the photosynthetic machinery of the plant which eventually reduces food production. Likewise, Anjum et al.
(2003) also reported changes in photosynthetic pigments and their components as a result of drought. According to Niinemets et al., (2010), measurements of chlorophyll provides an important tool to gaining insight into modifications of foliage physiological activity. The sensitivity of photosynthesis to both biotic and abiotic stresses varies with plant genotype tolerance. This study revealed that sorghum genotypes vary greatly with respect to chlorophyll concentration when exposed to the same environmental limitations. Palta et al.,
(1994) and Zhang et al., (1998) reported that water deficits result in early senescence which results in reduced chlorophyll concentrations. The results of this study suggested that drought stress takes precedence over Striga asiatica stress when they co-occur in sorghum. This may be attributed to the fact that water has to be available prior to Striga asiatica infection in sorghum. The results may also suggest that the two are mutually exclusive on their effects on chlorophyll concentration in sorghum.
The responses of sorghum genotypes to chlorophyll content under 50 and 100 % FC tended to differ (Figure 3.2). The genotypes Mukadziusaende, wild sorghum and Chiredhi had similar chlorophyll content at both irrigation regimes. However, reduced water availability lowered the chlorophyll content of genotypes SC Sila and Isifumbathe. Similar results were found by Gurney et al., (2002) who reported a maize variety, ‘Staha’, whose foliar chlorophyll concentration was unaffected by the parasite. In the current study, it was hypothesized that the genotypes Mukadziusaende, wild sorghum and Chiredhi showed resilience to both stresses hence photosynthesis was maintained in these genotypes despite the presence of both stresses, which may help maintain sorghum productivity. This may be due to the limited sensitivity of the genotypes towards drought. According to Cameron et al.,
90
(2006), it is known that the responses of the genotypes to reduced water availability might be high osmotic adjustments that help maintain leaf water potential. Bloom et al., (1985) reported that even in limited supply of resources, plants have to maintain a balanced investment such that all functions and organs are limited to the same degree. Across all the two experiments, NDVI was higher at 100% compared to 50 %. NDVI is a measurement of amalgamated plant growth that reflects the effects of various plant growth factors and is highly correlated with plant available soil moisture (Verhulst and Govaerts, 2010). For the genotypes SC Sila, Mukadziusaende, wild sorghum and Isifumbathe, NDVI was lowered by drought treatments. Bjorkman and Powles (1984) reported that the effect of S. asiatica on both photosynthetic performance and photo-inhibition of maize plants under light conditions is similar to the effects observed when abiotic factors such as water shortage are imposed. For the genotype Chiredhi, NDVI was higher at 100 % moisture compared to 50 %, whilst the rest of the genotypes were not affected. Irrigation at 50 % of field capacity could have limited nitrogen assimilation and consequently lowered chlorophyll concentration in the affected genotypes.
Under infested conditions, moisture availability did not affect internode length. However, 100
% FC under uninfested conditions increased internode length (Figure 3.4). The fact that drought reduced internode length in sorghum is in tandem with Deligoz and Gur (2015)’s findings who reported that drought stress causes physiological and metabolic changes which negatively affects growth and development of plants. Actually, Farooq et al., (2009) reported that growth is accomplished by cell division, enlargement and differentiation. Nonami (1998) posited that under water deficient conditions, cell elongation can be inhibited by interruption of water flow from xylem vessels to surrounding cells. This study revealed that in relation to internode length, the effect of reduced water availability is equal to the effect of Striga.
91
Under 50 % FC, non infested sorghum had limited growth and it only grew when water was made available at 100 % FC.
Striga infestation increased dry matter allocated to the roots in Experiment I, but had no effect on experiment II. This agrees with Poorter et al., (2011), who reported that plants allocate more dry matter to the roots as the limiting factor is below the ground. Similar results were also found by Farooq et al., (2009 and Liu et al., (2011). The results indicated that root dry mass decreased under drought, which was also reported by Luttschwager et al., (2016), who found decreased root mass under drought in Populus tremula.
Head weight and head index were lowered by S. asiatica infestation and drought (Tables 6 and 7). The results are in tandem with the findings of Baker et al., (1996) and Vasey et al.,
(2005) in which infestation reduced dry matter allocated to the head. Similar results were found by Pandey et al., (2000) who found that the harvest index was lowered by increased water stress. Groene (2008) concurs with the assertions and reported that drought has an effect on pollen viability, pollen tube germination and increases in ovule abortion rates as a result of reduction in assimilate supplies which are required for grain development.
According to Ober et al., (1991), water stress resulted in diminished grain set and kernel growth in wheat and decreased rate of endosperm cell division. Striga asiatica causes increases in abscissic acid (Taylor et al., 1996; Frost et al., 1997). Also, increases in ABA concentration as a result of drought had been previously documented by Aldesuquy and
Ibrahim, (2001) and Gniazdowska et al., (2007). Cramer et al., (2011) asserted that ABA is an important regulator of plant responses to both abiotic and biotic stresses. Both drought and
Striga infestation have been reported to lead to an increase in ABA production and consequently cause stomatal closure reducing carbon dioxide entrance into the leaf, hence reduced productivity.
92
Leaf and stem indices were not affected by sorghum genotypes (Table 3.8) and infestation
(Table 3.9) whereas they were both reduced by irrigation at 50 % of field capacity. These results are in disagreement with the findings of Aflakpui et al., (1998), who found that Striga infestation reduced leaf and stem indices. However, their study on maize was subjected to
Striga only whereas in this study, drought was also a factor that was added to S. asiatica infection. Taken together, these results indicated that the response of sorghum to S. asiatica and drought is complex and cannot be extrapolated from the results of each stress applied singly. This confirms the assertion by Mittler (2005) that two or more stresses may require a unique response on the hosts and that the responses may have synergistic or antagonistic effects on each other. From the results, drought effects got preference when they co-existed with Striga infestation. The simultaneous occurrence of different biotic and abiotic stresses was shown to result in a high degree of complexity in plant responses as the responses to these combined stresses are largely controlled by different signaling pathways that may interact or inhibit one another (Artkinson and Urwin, 2012; Rasmussen et al., 2013).
Consequently, the fact that drought only had a significant influence on leaf and stem biomass indicated that its influence was greater than that of S. asiatica or the response pathways to drought suppresses the effects of S. asiatica. The effects of S. asiatica are inhibited when it co-exists with drought in sorghum. Results from this study confirmed the findings of
Artkinson and Urwin (2012), who reported that plants respond in a specific manner when they have to face more than one stress simultaneously, and the response cannot be predicted based on the plant’s response to the individual stresses.
Leaf index was higher under infested conditions at 50 % irrigation compared to uninfested conditions (Figure 3.4). This demonstrated that the two stresses resulted in more dry matter
93 being channeled to the leaves. These results confirmed the assertion by Suzuki et al., (2014) that stress combinations might have beneficial effects on plants compared to each stress applied separately.
Stem weight was not significantly affected by infections for all varieties except for wild sorghum where infection lowered stem weight but increased stem weight for Chiredhi.
Reduced allocation of dry matter to the stems combined with increased allocation to the roots was reported by Frost et al., (1995) and Graves et al., (1990). It is now known that the parasite acts as a sink for carbon, inorganic solutes and water and also because of the reduced carbon gain in infested hosts as reported by Smith et al., (1995) and Cechin and Press (1993).
Under infestation, reduced water availability increased leaf index and this is likely an issue of overcompensation.
3.5 Conclusions
The study found that with respect to chlorophyll content, reduced water availability and infestation were mutually exclusive. With respect to sorghum internode length, the resilience of sorghum to Striga asiatica is reduced when sorghum is affected by drought which shows synergistic effects of drought and S. asiatica infestation..
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CHAPTER FOUR:
The response of tolerance traits of Sorghum bicolor (L) Moench and Sorghum arundinaceum (Desv) Stapf to Striga asiatica (L)
Kuntze infestation under mulch
4.1 Abstract
The production of sorghum is hampered by the parasitic weed Striga asiatica. Studies are lacking on the effect of cultural techniques of managing the weed such as mulching.
Mulching is promoted as a component of the conservation agriculture systems in sub Saharan
Africa. Nine Sorghum bicolor cultivars and one Sorghum arundinaceum line were evaluated under Striga infestation and under Striga free conditions with half being mulched and the other half unmulched for two years at Bindura University of Science Education (BUSE) nursery in Zimbabwe. The objective was to assess the effects of mulching and infestation on the tolerance of Sorghum bicolor and Sorghum arundinaceum to Striga asiatica. The experiment was a 2*2*10 factorial, replicated three times in both seasons and arranged as a completely randomized design. Results indicated that mulching increased chlorophyll content in the 2014/15 season compared to 2013/14. Infestation reduced chlorophyll content in both seasons. For the 2014 season, mulching increased chlorophyll content in all varieties except
Ruzangwaya, Mukadziusaende and SC Sila. Stomatal conductance and tiller numbers were higher (P<0.01) in uninfested sorghum compared to infested in both seasons. The varieties
Mukadziusaende, Chiredhi and Hlubi were able to maintain height despite infestation by
Striga. When the same varieties were infested under mulch and infested without mulch, the
103 results showed that mulching overcomes the effect of infestation in some varieties. Varieties
Chiredhi, Mukadziusaende and Mashava were able to maintain yield despite infestation by
Striga in the 2013 season. Wild sorghum was highly susceptible to Striga. Mulching negates the effect of Striga parasitism in the drier season compared to wetter season and results in yield maintenance in some varieties.
4.2 Introduction
Sorghum (Sorghum bicolor L) is a multipurpose crop belonging to the Poaceae family, which are C4 carbon cycle plants with high photosynthetic efficiency and productivity (Tari et al.,
2013). Sorghum is a preferred crop in sub tropical Africa as it can maintain yields in environments normally regarded as too hostile for other crops such as maize. Many people in
Southern Africa live in chronic food deficit regions including the semi-arid zones where rainfall shortage causes recurring food shortages and consequent malnutrition. In these regions, sorghum is a critical strategic grain crop for a vast number of farmers. It is an essential component of sustainable agricultural systems in the region’s extensive semi-arid areas. Improvement of sorghum productivity is an immediate priority in these areas.
Striga species are obligate hemi-parasitic plants that attach to the root of the host to obtain water, nutrients and carbohydrates (Parker and Riches, 1993). The life cycle of Striga asiatica is complex, and co-evolved with many hosts to comprise a series of discrete steps that are tightly coupled to the host’s biochemistry and life cycle (Bouwmeester et al., 2003).
The parasite grows underground for 4 – 8 weeks prior to emergence (Jamil et al., 2013). The severe infestations appear to render African farmers helpless even though they are otherwise very resilient and adaptive (Ejeta, 2007). The extent and intensity of Striga species infestations has rapidly increased and become a threat to food production in practically the entire semi-arid region farming systems of southern Africa.
104
Effective control of S asiatica has proved challenging, mostly as a result of the intricate life cycle of the parasite (Gurney et al., 2003). Complete resistance has not been identified in sorghum although varieties vary in their sensitivity to the parasite (Gurney et al., 1995).
Therefore, the traits that reduce fitness impacts of damage such as maintenance of chlorophyll, increased photosynthesis, compensatory growth and tiller production despite infection are very critical in varietal selection under Striga infestations. Also, any cultural practice that negates Striga parasitism is critical to sorghum productivity.
Cultural practices like mulching may enable expression of tolerance since the parasite affects the water economy of the plant. Mulch tends to develop and strengthen the top soil structure through soil protection, microfauna activities and the incorporation of organic matter which usually provides a high infiltration rate (Rao et al., 1998, Scopel et al., 1998). Mulch reduces surface runoff due to increased roughness (Gilley et al., 1991; Gilley and Kottwitz, 1992).
Adekalu et al., (2007) reported increased water infiltration with increasing levels of mulch.
The same mulch has low thermal conductivity such that soil temperature is reduced sometimes with consequent decrease in root development (Riddle et al., 1996). Generally mulching is known to reduce weeds through physical effects and allelopathy. However, this information relates to non-parasitic weeds and there is limited information on the effects of mulching on Striga incidence and parasitism.
Sorghum arundinaceum is increasing in Zimbabwe’s cropping systems as a weed and occurs in all crops. Studies by Gurney et al., (2002) and Rich et al., (2004) found a Sorghum arundinaceum strain that was tolerant to Striga. In Zimbabwe, Mwenje (2006) reported high compatibility between cultivated sorghum and its wild relatives. Therefore, the objectives of this study were:
105
i) To determine the effect of mulching and Striga infestation on sorghum chlorophyll
concentration, stomatal conductance, sorghum height and Striga counts.
ii) To determine the effect of mulching and Striga infestation on sorghum grain yield and
dry matter traits.
The corresponding alternative hypothesis were
i) Mulching and Striga infestation affect the expression of tolerance traits of sorghum
genotypes with respect to chlorophyll concentrations, stomatal conductance,
sorghum height and Striga counts.
ii) Mulching and Striga infestation affect the expression of tolerance traits in sorghum
with respect to sorghum grain yield and dry matter partitioning.
4.3 Materials and methods
4.3.1 Experimental site
The pot experiments were carried out at Bindura University of Science Education (BUSE)
Astra Campus nursery, Bindura (GPS coordinates: 17o 181 5811 S and 31o 191 2311 East) during the 2013/14 and 2014/15 summer seasons. The area is located in agro-ecological region 11b according to the Zimbabwean classification system (Vincent and Thomas, 1961) and it receives a total of 800 mm of rainfall per season from November to April. The pot experiment was done in medium grained sands with a pH of 4.2.
4.3.2 Experimental design and pot layout
For both seasons, the experiment was 2*2*10 factorial experiment. The first factor was mulch at two levels: mulched at a rate equivalent to 3 t ha-1 and 0 t ha-1. The second factor was infestation at two levels: infested and uninfested. The third factor was sorghum genotype
106 at 10 levels (Table 4.1). The experiment was laid down as a completely randomized design replicated three times.
Table 4.1: Sorghum genotypes tested for tolerance to Striga in the 2013/14 and 2014/15 seasons
Sorghum variety/code* Region Collected/grown Local name
1551 Matebeleland Isifumbathe
1773 Chiredzi Chiredhi
1836 Mrewa Mashava
1555 Matebeleland Tswetha
1556 Matebeleland Hlubi
1697 Masvingo Mukadziusaende
1669 Matebeleland Zambia
4487 Masvingo Ruzangwaya
SC Sila Zimbabwe
Wild sorghum Mashonaland West
*Codes refer to accession numbers at the Department of Research and Specialist Services, gene bank in Harare, Zimbabwe
4.3.4 Source of Seeds
Sorghum and S. asiatica seeds were obtained from a source as stated in Section 3.3.2.
4.3.5 Experimental details
The soil was obtained from a farmer’s field where no Striga was reported before. The pots were filled with soil and the top 10 cm of the soil was thoroughly mixed with 5.7 g of maize fert (7N: 14 P2O5: 7 K2O) compound fertiliser and 1 g of conditioned S. asiatica seed. The soil/S. asiatica mixture was placed back into the bucket after mixing thoroughly. Ten
107 sorghum seeds were planted in the bucket at a depth of 0.5 cm. The pot filling and planting process was started on the uninfested pots to avoid contamination. The experiment was rain- fed and the sorghum seedlings were thinned to one plant per pot at two weeks after crop emergence (WACE). Sorghum plants were top-dressed by applying 3 grams of ammonium nitrate (34.5 % N) per pot representing 90 kg ha-2 at 4 WACE. Non Striga weeds which emerged were manually pulled and this was done continuously throughout the experimental period.
4.3.6 Data collection
Height of the plants was measured and tiller number counted at 8 and 12 weeks after crop emergence. Chlorophyll content was measured by a chlorophyll meter (SPAD-502 KONICA
MINOLTA INCL) at 6, 8 and 12 WACE. Sorghum yield was estimated by harvesting the head when the sorghum plant had reached maturity and was weighed using a sensitive scale.
Stomatal conductance was measured using a porometer (DECAGON INCL).
4.3.7 Data analysis
Analysis of variance was performed to examine the effects of treatments and their interactions on chlorophyll content, stomatal conductance, plant height and yield. The
Bartlett’s test for homogeneity of variance procedure showed that variances were not homogeneous and hence, the data were analysed separately. The analysis was performed using Genstat statistical software, Version 14. S. asiatica counts were subjected to square root transformation prior to analysis.
4.4 Results
4.4.1 Chlorophyll content
108
Mulching increased (P<0.001) chlorophyll concentration at 6, 8 and 12 WACE for the
2014/15 season while it had no significant effect (P>0.05) during the 2013/14 season (Table
4.2).
Table 4.2: Effect of mulching on chlorophyll concentration for the 2013/14 and 2014/15 summer seasons
Condition Chlorophyll content for the 2013/2014 Chlorophyll content (mmolcm-2) for 2014/2015 summer
summer season season
6 WACE 8 WACE 12 WACE 6 WACE 8 WACE 12 WACE
Mulched 19.83a 31.62a 41.06a 20.69±0.883a 46.25±1.014a 37.69±1.376a
Unmulched 20.3a 31.55a 39.87a 17.11±0.883b 39.23±1.014b 31.09±1.376b
Infestation also lowered chlorophyll concentration at 6 WACE in the 2014/15 season but was not significant at 8 and 12 WACE during the same season (Figure 4.1).
Figure 4.1: Effect of infestation on chlorophyll concentration at 6 WACE during the 2014/ 15 season.
109
35 Infested
) Uninfested -2 30
25
20
15
10
Chlorophyllconcentration (mmolcm
5 Hlubi Chiredhi Mashava Zambia Sc Sila Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
60 Mulched Unmulched 8 WACE in 2014 season
) 55
-2
50
45
40
35
30
Chlorophyllconcentration (mmolcm 25
20 Hlubi Chiredhi Mashava Zambia Sc Sila Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
Figure 4.2: Interaction between variety and Striga infestation a) 6 WACE andvariety and mulch b) 8 WACE on chlorophyll concentration
There was a significant interaction of variety and mulching on chlorophyll content in the
2013/14 season (P<0.01) (Figure 2) and variety and Striga infestation (P<0.001).
110
At 6 WACE in the 2013, infestation significantly (P<0.05) lowered chlorophyll content of SC
Sila whilst all the other varieties were not affected. At 6 WACE in the 2014/15 season,
Isifumbathe, Chiredhi, Zambia and Wild sorghum had their chlorophyll concentration significantly lowered by infection. Mulching significantly increased (P<0.01) chlorophyll content in all varieties except Ruzangwaya, Mukadziusaende, Mashava and SC Sila. At 8
WACE, infestation lowered chlorophyll content (P<0.05) of wild sorghum whilst the content for Tshwetha was not affected.
Figure 4.3: Effect of infestation status on stomatal conductance for the sorghum genotypes during the 2013/14 season.
There was a significant effect of infection on stomatal conductance (P<0.001) (Figure 4.3).
The results revealed lowered stomatal conductance due to infestation compared to uninfested conditions.
4.4.2 Tillering
111
The results showed that Mukadziusaende, Mashava and Isifumbathe had the highest tillers in the 2013/14 summer season. The same varieties had the highest tiller numbers in the 2014/15 season. The 2013/14 season had less tillers for Chiredhi than 2013/14 season while 2014/15 had more tillers for Mukadziusaende and the same was true for Tshwetha (Figure 4.4).
5
2014 -15 season 2013 - 14 season 4
3
2
Tiller numbers
1
0 Hlubi Chiredhi Mashava Zambia SC Sila Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotype
Figure 4.4: Effect of season on tiller numbers over two seasons.
4
3
2
Tiller number Tiller
1
0 Infested Uninfested Infestation status Figure 4.5: Effect of infestation status on tiller numbers
112
For the variety Mukadziusaende and Tswetha, tiller number was significantly higher in the
2013/14 season compared to the 2014/15. Also infestation significantly (P<0.001) lowered tillering across all the sorghum genotypes (Figure 4.5).
Sorghum genotypes differed significantly (P <0.05) at 10 WACE with regard to S. asiatica incidence. The sorghum genotype Hlubi supported the highest number of S. asiatica plants while Isifumbathe and Mukadziusaende supported the lowest at 10 WACE during both seasons (Table 4.6).
Table 4.6: Effect of sorghum variety on Striga counts
Sorghum variety Striga counts at 10 WACE in 2013- Striga counts at 10 WACE in 2014-
14 season 15 season
Hlubi 3.4 (12.88)±0.632d 5.08 (29.5)±0.71e
Isifumbathe 1.28 (3.5)±0.632a 2.59 (8.2)±0.71ab
Ruzangwaya 1.85 (4.67)±0.632abc 4.11 (21.7)±0.71cde
Chiredhi 1.73 (4.33)±0.632abc 2.34 (6.8)±0.71a
Mukadziusaenda 1.49 (3.67)±0.632ab 2.29 (5.5)±0.71a
Mashava 2.81 (8.67)±0.632cd 3.54 (13.7)±0.71abcd
Zambia 2.02 (4.17)±0.632abc 2.77 (8.5)±0.71abc
Tswetha 2.19 (5.87)±0.632abc 4.68 (23.2)±0.71de
SC Sila 2.66 (7.5)±0.632bcd 3.82 (14.8)±0.71bcde
Wild Sorghum 1.72 (5)±0.632abc 3.65 (13.5)±0.71abcd
The numbers in brackets represent the actual counts and those not in brackets are figures after square root transformation.
113
4.4.4 Plant height
The effects of Striga infection on sorghum height are shown in Figure 4.6. At 6 WACE,
Striga infection significantly reduced the height of some sorghum varieties. It was clear that the impact of Striga infection on sorghum height was different among sorghum varieties at 12
WACE. It was interesting to note that Striga infection did not significantly reduce the heights of Isifumbathe, Mukadziusaende and Chiredhi. In contrast, Striga infection reduced the height of other sorghum cultivars (Figure 4.6).
90 8 wace in 2014 - 15 season Infested 80 Uninfested
70
60
50
Sorghum height (cm)Sorghumheight 40
30
20 Hlubi Chiredhi Mashava Zambia SC Sila Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotype
114
140 Infested Uninfested 120
100
80
60
Sorghum height (cm) height Sorghum 40
20
0
N.a.N. Hlubi Chiredhi MashavaZambia SC Sila Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
Figure 4.6: Interaction effects of sorghum genotype and S. asiatica infection on sorghum height in the 2014/15 season at 8 and 12 WACE.
The interaction revealed that all varieties, except Tshwetha, maintained their plant height when infested pots were compared with uninfested ones. There was a significant interaction of variety, mulching and infestation. Sorghum varieties responded differently to mulching and infestation. Variety Isifumbathe had the least height under unmulched and infested treatments (Figure 4.7). For SC Sila, plant height under mulched and infested pots was significantly (P<0.05) taller than under unmulched uninfested plants (Figure 4.7).
115
180
Mulched infested 160 Mulched uninfested Unmulched infested 140 Unmulched uninfested
120
100
80
Plant height (cm) height Plant 60
40
20
0 Hlubi Chiredhi Mashava Zambia SC Sila Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
Figure 4.7: Interaction effects of sorghum genotype, mulching and infestation on plant height in the 2014/15 season.
For the varieties Ruzangwaya, Tshwetha and SC Sila, mulched and infested pots gave taller plants compared to unmulched and infested pots (Figure 4.7). For the variety Isifumbathe, mulched and infested pots were taller better compared to infested but unmulched pots in the
2014/15 season (Table 4.7).
In the 2013/14 season infestation significantly (P<0.001) reduced affected plant height.
116
Table 4.7: Effects of infestation on plant height at 8 and 12 WACE in the year 2013/14 and 2014/15 seasons.
Infestation 2013/14 8 WACE 12 WACE 2014/15 8 WACE 12WACE
Infested 53.24±1.995a 97.3±6.61a 48.94±1.955a 79.5a
Uninfested 60.68±1.995b 125.4±6.61b 54.5±1.955b 78.1a
In the 2013/14 season there were significant interactions between variety and infestation at 6,
8 and 12 WACE.
60 Infested Uninfested 50
40
30
20
Sorghum height(cm)
10
0
Hlubi Zambia SC Sila Sc Sila Chiredhi Mashava Tshwetha IsifumbatheRuzangwaya Mukadziusaende
Sorghum genotypes
117
100 Infested Uninfested
80
60
40
Sorghum height (cm) height Sorghum
20
0
Hlubi Sc Sila Chiredhi Mashava ZambiaTshwetha SC Sila IsifumbatheRuzangwaya Mukadziusaende
Sorghum genotypes
200 Infested Uninfested
150
100
Sorghum height (cm) height Sorghum 50
0
Hlubi Sc Sila Chiredhi Mashava ZambiaTshwetha SC Sila IsifumbatheRuzangwaya Mukadziusaende Sorghum genotypes
Figure 4.8: Interaction effects of sorghum variety and infestation on plant height at 4, 8 and 12 WACE during the 2013 season. At 6 WACE, uninfested pots of Hlubi, Chiredhi, Mukadziusaende, Zambia and Tshwetha had taller plants compared to infested ones. The results showed that infestation lowered plant height for the majority of the sorghum genotypes except for Chiredhi, Mukadziusaende,
Zambia and Tshwetha at 8 WACE. At 8 WACE, Ruzangwaya, Chiredhi, Mukadziusaende
118 and SC Sila were not significantly affected by infestation (Figure 4.8). Isifumbathe,
Mukadziusaende and SC Sila resisted the dwarfing effects of Striga at 12 WACE.
4.4.5 Grain yield
The interaction of sorghum variety and Striga infection was significant (P<0.01) on sorghum grain yield (P < 0.05). Striga infection significantly reduced the grain yield for most of the sorghum varieties with the exception of Chiredhi, Mukadziusaenda and Mashava (Fig 4.9). In fact, Mukadziusaende had significantly higher grain yield in the Striga infected plants compared to uninfected plants (P < 0.05) for the 2013/14 season (Figure 4.9).
100
Infested 80 Uninfested
)
-1
60
40
Sorghum yield (gplant yield Sorghum 20
0
Hlubi Chiredhi MashavaZambiaTswethaSC Sila Isifumbathe Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum varieties
Figure 4.9: Interaction effects of sorghum genotypes and infestation on sorghum yield for the 2013/14 season Uninfested pots had a higher head weight (P<0.05) compared to infested pots for Hlubi,
Isifumbathe, Ruzangwaya, Zambia, Tswetha and wild sorghum (Figure 4.10). Chiredhi and
Mashava maintained their yield despite infection. For the 2014/15 season head weight was
119 significantly affected by sorghum variety (P<0.001), infestation (P<0.001) and mulch (P=
0.001) (Figure 4.10).
40 sorghum yield in 2014 - 15 season 50
2014 - 15 season 30 40
30 20
20
Yield (g/plant)
Sorghum yield (g/plant) 10
10
0 0 Infested Uninfested Mulched Unmulched Infestation Mulching status
60 Yield for the 2014 - 15 season
50
40
30
20
Sorghum (g/plant) yield
10
0 Hlubi Chiredhi Mashava Zambia SC Sila Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende Sorghum varieties
Figure 4.10: Effect of sorghum genotypes, infestation and mulching on sorghum yield in the 2014/15 season It was noted that whilst there were no significant interactions on yield, infestation reduced yield while mulching increased yield (Figure 4.10). The sorghum genotypes Isifumbathe and
SC Sila had the highest yield. Mulching significantly (P<0.001) increased yield in the
2014/15 season.
120
4.5 Discussion
In this study, chlorophyll concentration was reduced by infection with S. asiatica.
Chlorophyll concentration is indicative of photosynthetic functioning and potential maximum carbon dioxide assimilation rates. The fact that chlorophyll concentration was reduced by infection is in agreement with the findings of Gurney et al., (2011) who found lower chlorophyll content in Striga infested maize than uninfested susceptible maize genotypes.
Mulching increased chlorophyll concentrations at 6, 8 and 12 WACE for the 2014/15 season which was not the case for 2013/14 season. The 2013/14 season was a wet season whilst the
2014/15 season had less rainfall with a lot of mid-season droughts. According to Chakraborty et al., (2008), mulching is a suitable agronomic practice for conserving soil and water and controlling soil temperature regimes. Mupangwa et al., (2012); Rao et al. (1998); Scopel et al., (1998); and Adekalu et al., (2007) reported that the presence of mulch residue at the soil atmosphere interface has a direct influence on infiltration of rainwater into the soil and evaporation from the soil leading to improved water supply for crops. The advantage of mulching with respect to chlorophyll content was apparent in the 2014/15 season which had erratic rainfall.
Chlorophyll concentration is connected to nitrogen availability and is a key parameter in measurement of plant canopies (Gitelson et al., 2003). Any perturbations in nitrogen assimilation as a result of water limitations could in turn lower chlorophyll content as reflected by the results of this study. The rest of the varieties whose chlorophyll content was not affected by mulching may have high osmotic adjustment that helps maintain higher leaf water potential. Blum (2005) reported that osmotic adjustment helps to sustain growth while the plant is meeting transpirational demand by reducing its leaf water potential.
121
Stomatal conductance was lower in infested compared to uninfested sorghum genotypes. The reduced stomatal conductance was probably caused by changes in the concentrations of growth regulators in the host which are stimulated by Striga infestations (Frost et al., 1997).
Taylor and Frost (1997) revealed that increased levels of abscissic acid (ABA) in infested plants resulted in stomatal closure. The wide variations of stomatal conductance following infection across different varieties were probably a reflection of variable responses to ABA accumulation in the plant.
The genotypes that maintain higher stomatal conductance are likely going to maintain photosynthesis despite Striga infection. The varieties Chiredhi, Zambia and Wild sorghum for the 2013/14 season and Hlubi, SC Sila and Tshwetha for the 2014/15 season maintained opening of stoma under infestation and this is a useful trait for maintenance of photosynthesis. It therefore enhances tolerance of the genotype to Striga infestations.
The genotypes that had the highest tiller numbers were Mukadziusaende, Mashava,
Isifumbathe and Ruzangwaya for both seasons. Tillers were more in infested sorghum cultivars compared to uninfested ones. Tillering is one of the most important agronomic traits in poaceous crops and plays a major role in determining plant architecture and grain yield
(Wu et al., 1998). According to Assuero and Tognetti (2010), high tiller production capacity improves the chances of persistence after periods of unfavourable environmental conditions during which a plant can experience biotic or abiotic stress. It means that there are higher chances of survival after a biotic stress as one or more tillers can take over after stress has affected the initial stems.
Strigolactones are involved in the regulation of above ground plant architecture by inhibiting tiller development or shoot branching (Umehara et al., 2010). Jamil et al., (2011) found an inverse relationship between number of tillers per plant and strigolactone production. This
122 may mean that high tillering varieties are producers of low strigolactones which gives an advantage of supporting a lower number of S. asiatica parasites. Tillering therefore becomes a useful trait that can be incorporated into other cultivars. According to Khush et al., (1999), tillering increased the widespread adoption of wheat and rice varieties in the 1960s because the altered plant architecture averted severe food shortages and was an essential component of the green revolution. Jahn et al., (2011) found that continuous tillering is associated with high grain yield and is characteristically selected for in advanced varieties in most crops. This study showed that tillering was higher in uninfested pots than infested ones. This coincides with the findings of Cruz and Boval (2000) who found a positive effect of nitrogen availability on tillering in Lolium perenne. In this study, it could be possible that the nitrogen levels in the Striga infested pots were not sufficient to sustain the direct demands of the parasite and the tillering processes of the sorghum plants.
The germination of S. asiatica is elicited by strigolactones from the hosts. Therefore the number of Striga attached is a reflection to some extent of the quantity of strigolactones produced by the host. In a study by Jamil et al., (2011), the germination of Striga was dependent on the quantity and quality of strigolactones produced by the host. As a result, any genetic variation in this trait could potentially confer pre-attachment resistance. Varieties
Hlubi, Mashava, Ruzangwaya and Tshwetha are likely to be high strigolactone producers as they stimulated a lot of seeds to germinate. Mukadziusaende and Chiredhi are likely to be low strigolactone producers as they elicited the germination of a few parasites.
The heights of varieties Chiredhi, Mukadziusaende and Isifumbate were not significantly lowered by Striga infestation. Mukadziusaende and Chiredhi resisted the dwarfing effects of
S. asiatica. Reduction in plant growth rate is caused by changes in the growth regulators in the host (Frost et al., 1997). Taylor et al., (1996) reported that the increased levels of the plant growth regulator, ABA in infested plants may result in stomatal closure. The reduction
123 in photosynthesis and ultimately growth would explain the reduction in height of infested plants that was observed in this study.
The differences in plant height observed between infested and uninfested genotypes for some varieties reflected that the parasite acted as a sink for carbon, inorganic solutes and water.
This was confirmed by Gurney et al., (2002), Cechin and Press (1993), and Gurney et al.,
(1995). The sorghum genotypes that maintained plant height irrespective of infestation demonstrated tolerance. The results showed that at 6, 8 and 12 WACE for the 2013/14 season, the varieties Mukadziusaende, Chiredhi and Isifumbathe maintained their plant height. The same genotypes were able to maintain high chlorophyll content, were independent of mulch and infection with respect to chlorophyll content, maintained high stomatal conductance and supported low Striga numbers. The first two parameters constitute the photosynthetic machinery, implying that photosynthesis was not affected by infection in those genotypes and hence they were able to maintain plant height despite the parasite load.
For the varieties Tshwetha, SC Sila and Ruzangwaya, mulched and infested pots had taller plants than unmulched and uninfested ones demonstrating that in drier seasons, moisture availability can negate the effects of infestation. The absence of mulch caused the plant to be affected more than by infection alone. Despite the fact that sorghum is a drought tolerant crop, absence of mulch which regulates soil temperature and conserve soil moisture had deleterious effects on plant height. This is supported by Chakraborty et al., (2008) and
Mupangwa et al., (2012) who reported the merits of mulching in moisture conservation and temperature regulation in hot and dry environments.
The ability of the varieties to maintain grain yield when infested by Striga asiatica may result from the ability of the cultivars to maintain higher rates of photosynthesis (Gurney et al.,
2002). Striga asiatica therefore has little effect on the physiology of these varieties. Infact,
124
Mukadziusaende had higher yields in infested than uninfested pots, a phenomenon that was attributed to profuse tillering. Jahn et al., (2011) reported on rice varieties that continued to tiller after the main stem begins senescence. Striga spends about 7 weeks underground and about 3 weeks above ground, after which it sets seed and dies. Mukadziusaende and Chiredhi matured early and the main stem dried, many tillers formed and these matured very early which lead to increased yield. Tillering seems to be the major parameter for tolerance under infested conditions. Mukadziusaende had the highest number of tillers and chlorophyll content and all these added together may provide a suite that overcompensates for Striga infestation to the extent that yield becomes higher under infested than uninfested conditions.
The ability to tiller when the main stem approaches senescence therefore becomes a beneficial trait in response to Striga infestation.
Varieties Isifumbathe, Mukadziusaende and Mashava had the highest number of tillers. The same varieties supported the least number of S. asiatica. The data showed that there was an inverse relationship between the number of tillers per plant and S. asiatica parasitism. Similar results were found by Jamil et al., (2011) in rice cultivars where there was an inverse relationship between number of tillers in rice and the number of Striga supported. Their study quantified strigolactones and found that they were also inversely related to tillering in rice cultivars. This research did not quantify strigolactones but their quantities can be inferred from the Striga asiatica attached together with tillering of sorghum. The results imply that
Mukadziusaende is a low strigolactone producer which is why it had the highest tiller number. Hlubi, Ruzangwaya and SC Sila supported the highest number of Striga asiatica and had lower number of tillers so they are likely to be producers of low quantities of strigolactones. The tillering of sorghum can therefore be used as a measure of sorghum tolerance when selecting genotypes for use. Chlorophyll content and growth rate can be used
125 as parameters for tolerance to Striga. When all these traits are combined, they can characterise a sorghum variety in terms of its ability to resist and tolerate Striga.
This study demonstrated substantial sorghum genetic variation for chlorophyll content, Striga number, tillering, stem height, internode length and grain yield in response to mulching. The sorghum varieties Mukadziusaende and Chiredhi were Striga tolerant, because of their ability to maintain high chlorophyll content, stem height, high internode length values, high grain yields and supporting low Striga attachments. The other two sorghum varieties were
Ruzangwaya with high chlorophyll content and maintenance of stem heights under Striga infection, and Mashava with high tillering ability and high grain yield production. The results clearly indicated that varieties Mukadziusaende and Chiredhi were able to perform well in parasite infested pots.
4.6 Conclusions
Mulching increased chlorophyll content and sorghum height in the drier season of 2014/15 compared to the 2013/14 wetter season. Yield and dry matter traits were maintained under S. asiatica infestation in the drier season of 2014/15. Therefore, mulching negated the effects of drought spells in the drier seasons. In the wetter season the effects of mulching were not apparent.
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International, Wallingford, UK.
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CHAPTER FIVE
The existence of different physiological ‘strains’ of Striga asiatica
(L.) kuntze on Sorghum bicolor (L.) Moench and Sorghum arundinaceum (desv) Stapf in Zimbabwe
5.1 Abstract
A better understanding of the virulence variability of S. asiatica populations and host parasite interactions is essential for more efficient resistant material deployment. This study was stimulated by the observation that sorghum that is tolerant to Striga asiatica in a particular area could still lack the same tolerance to a strain native to remote areas.Therefore an experiment was designed with the objective of determining the stability of Sorghum spp tolerance to two Striga strains. Nine Sorghum bicolor and one Sorghum arundinaceaum
(Wild sorghum) genotypes were subjected to two Striga asiatica strains sourced from
Rushinga and Chiundura, which are 500 km apart, and a control. A 3*10 factorial experiment was set up, arranged in a completely randomized design with three replications at two sites.
The data collected were sorghum height, chlorophyll content, tiller number and dry matter traits. The results showed that sorghum genotypes differed significantly (P<0.05) in their response to the stunting effects of Striga strains at both sites. The Chiundura strain was more virulent to Isifumbathe, Zambia, Wild sorghum and Mashava at Henderson research station whilst at BUSE, the Chiundura strain was more virulent on wild sorghum and Mashava. The two Striga strains were generally similar on their effects on chlorophyll content. At
Henderson, the Chiundura strain reduced chlorophyll content of Chiredhi, Zambia, Tshwetha and SC Sila. At BUSE both strains were not significantly different (P<0.01) from each other
131 at 10 weeks after crop emergence (WACE). The effects of the two strains were similar for head index, root index, stem index and leaf index at both sites. The Chiundura strain reduced the total dry weight at BUSE but not at Henderson. Overally, the Chiundura strain had more deleterious effects on sorghum traits compared to the Rushinga strain confirming the existence of physiological speciation on Striga asiatica in Zimbabwe.
Key words: Striga asiatica, sorghum, Striga strains, dry matter partitioning
5.2 Introduction
Sorghum (Sorghum bicolor) is an important food crop in sub Saharan Africa where plant available water is often a limiting factor for crop production. Sorghum allows for maintenance of yield stability in arid environments. Despite cultivating the crop in more than
60 % of the world hectarage, African sorghum constitutes 37 % of the world’s production and the average yield in most African countries is about 0.9 tha-1 which is substantially lower than the world average of 1.4 t ha-1(Jamil et al., 2012). The major biotic constraint to sorghum production in the southern Africa sub-region is Striga asiatica, a hemi-parasitic weed. Striga competes effectively with the host for carbon, nitrogen and inorganic solutes (Gurney et al.,
1999) and also causes phytotoxic effects on the host plants within days of attachment (Frost et al., 2005; Frost et al., 1997). The witchweeds are obligate hemi-parasites and although they contain some photosynthetic capacity, Striga species have an absolute requirement for the host in order to develop and complete their life cycle (Aly, 2007).
Host resistance to Striga has been proposed as the best method of control. According to
Mohammed et al., (2007), crops with some measure of resistance have been integrated into
Striga management programmes and the new material got challenged by the Striga seed bank. The newly introduced sorghum genotype must be able to cope with the great potential genetic diversity in the seed bank. Lewin (1939) was the first to observe the possible
132 existence of biological strains in Striga to explain the differential damage and distribution of
Striga on wild and cultivated hosts in sub Saharan Africa. Jones (1955) reported that the major problem in Striga control is the possible existence of physiological speciation within the species. Ten years later, Doggett (1965), reported varietal differences in sorghum susceptibility to Striga hermonthica sourced from different places in east Africa. It was observed that varieties of sorghum resistant in one location became susceptible in another location thus suggesting the existence of physiological strains of the parasite.
Some workers have reported that resistance could be dependent on the virulence of the Striga strains (Parker and Reid, 1979; Ramaiah, 1987). A study by Riches et al., (1992) on cowpeas found occurrence of distinct varietal specificity among races of the S. gesneroides. This meant existence of genetic divergence in Striga. Reda et al., (2010) found that there were populations of Striga that represented a threat to resistant varieties. Virulence could depend on the history of agriculture and specific characteristics of the source environment
(Polniaszek et al., 1991).
Botanga and Timko (2006) suggested that geographical isolation and host driven selection are important factors in the formation of races of Striga gesneriodes in West Africa. S. asiatica and S. hermonthica populations from Kenya were respectively polymorphic for 96.8 % and
84 % of the amplified fragment length polymorphic (AFLP) bands that were assessed (Gethi et al., 2005). A study in Benin discovered a high degree of host speciation within the 14 S. asiatica populations that were analysed (Botanga et al., 2002). According to Spallek et al.,
(2013), S. asiatica isolated from wild grasses spp were unable to successfully parasitise sorghum and maize plants susceptible to other Striga asiatica collections.
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In Zimbabwe, studies conducted by Musimwa et al. (2001) using RAPD-PCR markers found great genetic distances among Striga from three places which are sparsed from one another by about 400 kilometres.
The objective of this study were
i) to determine the differential virulence effects of two srains of S. asiatica to sorghum
genotypes with respect to growth and dry matter traits in sorghum.
ii) to establish the existence of different strains of S. asiatica in Zimbabwe
There the alternative hypothesis were
i) the two S. asiatica strains were differentially virulent on sorghum growth and
dry matter parameters.
ii) there exists physiological strains in S. asiatica in Zimbabwe
5.3 Materials and Methods
5.3.1 Experimental sites
Two experiments were carried out at Henderson Research Station in Mazowe and the other one at Bindura University of Science Education (BUSE) nursery. Henderson Research station is located at latitude17.340S and longitude 30.580E. BUSE is located at the coordinates: 17o
18I 58II S and 31o 19I 23IIE. The two sites are located in agro-ecological region IIa of
Zimbabwe (Vincent and Thomas, 1961) and receive about 800 mm rainfall per annum. The average temperature for both areas was 25oC. The experiments were conducted in the 2013 -
14 cropping season. The soil used at both sites was medium grained sands with a pH of 4.1
(CaCl2) and with a phosphorus content of 20 parts per million (ppm), 4 ppm nitrogen.
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Exchangeable cations in milligram equivalent per 100 g of soil were 0.06 for potassium, 0.67 calcium and 0.48 magnesium.
5.3.2 Source of sorghum genotypes and Striga asiatica strains
Sorghum bicolor genotypes were sourced from the gene bank at the Department of Research and specialist services, Harare research station, Zimbabwe. The Chiundura S. asiatica strain was sourced from the Midlands province of Zimbabwe, which is 500 km from Rushinga in
Mashonaland province where the Rushinga strain was sourced. Sorghum arundinaceum seed was collected in arable lands at Gwebi Agricultural College, 27 km west of Harare.
5.3.3 Experimental design
The experiments were conducted in pots with a 3*10 factorial treatment structure. The sorghum genotypes that were used are shown in Section 4.3.2.
5.3.4 Experimental details
Medium grained sandy soil was obtained from the top 15 cm of a farmer’s field where Striga has never been reported. Six litre plastic pots with six drainage holes at the bottom were filled with the soil, and the top 10 cm of the soil were thoroughly mixed with 5.7 g of Compound D fertilizer (8%N, 14% P2O5, 7 K2O) and 1 g of Striga asiatica seed. Ten sorghum seeds were planted in the plastic pots at a depth of 0.5 cm and watered. The two strains were each used to infest a third of the buckets and the other third was uninfested. The pot filling and planting process started with the uninfested pots to avoid contamination. The sorghum seedlings were thinned to one plant/pot at two WACE. The sorghum plants were topdressed at a rate of 3 g per pot using ammonium nitrate (34.5 %N) at 4 WACE.
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5.3.5 Data Collection
Height of the sorghum plants was measured using a metre ruler from the soil level to the growing point. Tiller number was counted on each plant. Chlorophyll content was measured by a chlorophyll meter (SPAD-502 KONICA MINOLTA INCL) at 6, 8 and 12 WACE.
Striga numbers were determined by counting the number of Striga plants that emerged from the pots. The whole sorghum plant was carefully uprooted at maturity and the total dry matter was separated into roots, leaves and stems. Head weight was determined by drying the sorghum head in the sun until moisture content was 14 %. Roots, leaves and stems were dried in an oven at 78oC for 48 hours for dry mass determination. Various indices were calculated by dividing mass of the part, like leaf mass, by total mass.
5.3.6 Data Analysis
Barlett’s test for homogeneity of variance was done and the variances were not homogeneous. Hence, the data from the two sites were analysed separately. Data was subjected to analysis of variance (ANOVA) to determine the treatment effects using Genstat release 14 (VSN International, UK).
5.4 Results
5.4.1 Sorghum plant height
Sorghum genotypes differed significantly (P< 0.01) in plant height in response to the two different Striga strains. There was a significant interaction (P<0.05) of Striga strain and sorghum genotype. The Chiundura strain lowered the height of Isifumbathe, Zambia and wild sorghum 6 WACE at Henderson research station (Figure 5.1).
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50 Henderson plant height at 6 WACE Rushinga Chiundura 45 Uninfested
40
35
30
Sorghum height(cm) 25
20
15 Hlubi Chiredhi Zambia SC Sila Mashava Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
137
90
Rushinga 80 Chiundura Uninfested 70
60
50
40
Plant height (cm) height Plant
30
20
10 Hlubi Chiredhi Zambia SC Sila Mashava Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
220 Rushinga 200 Chiundura 180 Uninfested
160
140
120
100
80
Plant height (cm) height Plant 60
40
20
0 Hlubi Chiredhi Zambia SC Sila Mashava Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
Figure 5.1: Interaction effects of sorghum genotypes and Striga strain on sorghum height at 6, 8 and 12 WACE at Henderson research station.
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At 8 WACE, the Chiundura strain significantly lowered the height of genotype Isifumbathe.
At 12 WACE, the same strain significantly lowered the height of Zambia, Wild sorghum and
Mashava genotypes compared to Rushinga strain and uninfested genotypes. The Rushinga strain significantly (P<0.05) dwarfed Tshwetha compared to Chiundura and uninfested pots
(Figure 5.1). Mukadziusaende and Ruzangwaya genotypes resisted the dwarfing effects of the
Striga strains. The two strains had similar effects on Chiredhi and Isifumbathe genotypes
(Figure 5.1).
250
Rushinga Chiundura 200 Uninfested
150
100
Plant height (cm) height Plant 50
0
-50
Hlubi Chiredhi Zambia SC Sila Mashava Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotype
Figure 5.2: Interaction effects of sorghum genotype and Striga strains at 12 WACE at BUSE
A significant interaction (P<0.05) of sorghum genotype and Striga strains was observed for plant height. The Chiundura strain dwarfed wild sorghum and Mashava genotypes compared to Rushinga and the control at BUSE. Rushinga lowered the height of Tshwetha genotype compared to Chiundura strain (Figure 5.2).
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Table 5.2: Effect of Striga strain on plant height at 6 and 12 WACE at Henderson and
BUSE
6 WACE 12 WACE
Henderson BUSE Henderson BUSE
Rushinga 32.67±1.029a 32.51a 114.6±2.461a 101.4±9.58a
Chiundura 28.00±1.029b 30.62a 111.6±2.461a 98.9±9.58a
Uninfested 34.23±1.029c 33.86a 138.3±2.461b 122.9±9.58b
Values followed by different superscripts are significantly different at P<0.05
Across the measured periods Chiundura elicited the lowest sorghum height at all sites (Table
5.2).
5.4.2 Chlorophyll concentration
Chlorophyll content was significantly affected (P<0.001) by Striga strains at 8 and 12 WACE
(Table 5.3). The results revealed that the two strains were equally virulent on chlorophyll content but were significantly lower compared to uninfested pots at both sites at 8 and 12
WACE (Table 5.3)
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Table 5.3: Effect of Striga strains on chlorophyll content at 8 and 12 WACE
Chlorophyll content (mmolcm-2)
Accesions 8WACE 12 WACE
BUSE Henderson BUSE Henderson
Rushinga 26.48±0.749a 35.67±0.815a 29.54±0.784a 30.66±0.975a
Chiundura 26.56±0.749a 34.53±0.815a 30.74±0.784a 31.21±0.975a
Uninfested 29.45±0.749b 40.16±0.815b 33.01±0.784b 37.45±0.975b
Values followed by different superscripts are significantly different at P<0.001
The genotype Mukadziusaende resisted the effects of the two strains with respect to chlorophyll content (Figure 5.3). The two strains were equally virulent on Hlubi, SC Sila,
Mashava and Ruzangwaya (Figure 5.3) and the results were similar at both sites. The
Rushinga strain elicited the lowest chlorophyll content (Figure 5.3) across all sorghum genotypes.
141
60 Rushinga Chiundura Uninfested 50
)
-2
40
30
20
Chlorophyll content (mmolcm content Chlorophyll 10
0
Hlubi Chiredhi Zambia SC Sila Mashava Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
142
50 Rushinga Chiundura Uninfested
)
-2 40
30
20
10
Chlorophyll content (mmolcm content Chlorophyll
0
Hlubi Chiredhi Zambia SC Sila Mashava Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
Figure 5.3: Interaction effects of sorghum genotype and Striga strains on chlorophyll content at 10 WACE at both sites
5.4.3 Sorghum tillering
At 8 WACE, tiller number was significantly (P<0.001) affected by sorghum genotype and by
Striga strain (P<0.05) (Figure 5.4). The genotypes Chiredhi, Ruzangwaya and Mashava had the biggest tiller numbers, while Hlubi, Zambia and SC Sila had the least.
143
10
8
6
Tiller number 4
2
0
Hlubi Chiredhi ZambiaTswetha SC Sila Mashava Isifumbathe Ruzangwaya Wild Sorghum Makadziusaende
Sorghum varieties
12
10
8
6
Tiller number 4
2
0
Hlubi Chiredhi ZambiaTswetha SC Sila Mashava Isifumbathe Ruzangwaya Wild Sorghum Makadziusaende
Sorghum varieties
Figure 5.4: Effect of sorghum variety on tiller number at 12 WACE at both sites At Henderson research Station, the sorghum genotypes with the highest tiller numbers were
Chiredhi, Ruzangwaya, Mashava and Wild sorghum. At BUSE, Wild sorghum, Mashava and
Ruzangwaya had the highest tiller numbers. At both sites the lowest tillers were on genotypes
Zambia and SC Sila. The Chiundura strain elicited the highest number of tillers compared to infestation using Rushinga strain and uninfested sorghum genotypes (Figure 5.5).
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3.0
2.5
2.0
1.5
Tiller number Tiller 1.0
0.5
0.0 Rushinga Chiwundura Uninfested Striga strains
Figure 5.5: Effect of Striga strains on tiller number.
5.4.4 Sorghum dry matter traits
Sorghum genotype had a significant (P<0.001) effect on head, root, stem and leaf indices at both sites (Table 5.4)
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Table 5.4: Effect of sorghum genotypes on head index, root index, stem index and leaf index at BUSE and Henderson sites.
Head Index Root Index Stem Index Leaf Index Sorghum Henders BUSE Henders BUSE Henders BUS Henders BUSE variety or on on on E on landrace Chiredhi 0.31d 0.40e 0.19a 0.29a 0.42c 0.23bc 0.074a 0.073b c Hlubi 0.18b 0.21c 0.29bcd 0.48cd 0.458cd 0.24bc 0.069a 0.074b c Isifumbathe 0.24c 0.319d 0.287abcd 0.413b 0.412bc 0.216 0.057a 0.051a bc Zambia 0.208bc 0.239c 0.207ab 0.367a 0.497cd 0.289 0.088b 0.104e c Tshwetha 0.089a 0.142a 0.315cd 0.531d 0.527d 0.244 0.068a 0.082c bc d Mukadziusaen 0.232bc 0.315 0.287abcd 0.409b 0.394bc 0.215 0.066a 0.06ab de 5d bc Ruzangwaya 0.171b 0.200c 0.342d 0.498b 0.392b 0.207 0.094b 0.094d cd b e SC Sila 0.1881b 0.185b 0.285abcd 0.514c 0.408bc 0.176 0.118c 0.1230 d d e Wild Sorghum 0.077a 0.082 0.493ef 0.676e 0.32b 0.161 0.108bc 0.079b 7a a cd Mashava 0.168b 0.119a 0.518f 0.688e 0.213a 0.118 0.10b 0.074b a c Sed 0.023 0.037 0.05 0.048 0.053 0.037 0.009 0.01
Means followed by different superscripts in the same column are significantly different at P<0.001.
Head index was significantly higher on Chiredhi, Isifumbathe, Zambia and Mukadziusaende while the lowest indices were recorded for Tshwetha and wild sorghum genotypes at both sites. Root index was highest on Tshwetha, Mashava and wild sorghum genotypes (Table 5.4) whilst the lowest were Chiredhi, Mukadziusaende, Zambia and SC Sila genotypes (Table
5.4). Stem index was lowest on Mukadziusaende, Ruzangwaya and Wild sorghum genotypes.
The Striga strains significantly affected the four indices at Henderson but not at BUSE (Table
5.5).
146
Table 5.5: Effect of Striga strains on head, root, stem and leaf index at BUSE and
Henderson.
Head Index Root index Stem index Leaf index
Striga Henderson BUSE Henderson BUSE Henderson BUSE Henderson BUSE strain
Rushinga 0.1658±0.0123a 0.1785±0.02a 0.388±0.027a 0.566±0.027a 0.37a 0.181±0.029a 0.076±0.005a 0.0741a
Chiundura 0.1861±0.0123a 0.213±0.02a 0.349±0.027a 0.516±0.027a 0.366a 0.185±0.029a 0.1±0.005b 0.0856a
Uninfested 0.2151±0.0123b 0.272±0.02b 0.229±0.027b 0.377±0.027b 0.477b 0.2646±0.029b 0.078±0.005a 0.0857a
Means followed by different letters are significantly different at P<0.001
Both strains led to more dry matter being allocated to the root at both sites. The two Striga strains reduced the biomass allocated to the stems at both sites compared to uninfested hosts.
Head index was also lowered by Striga infestations. Leaf index was independent of Striga strain at BUSE but it increased significantly (P<0.001) under the Chiundura strain compared to Rushinga strain and uninfested genotypes.
There was a significant interaction (P<0.05) of sorghum genotype and Striga strain on leaf index at the Henderson site (Figure 5.6).
147
0.20
0.18 Rushinga 0.16 Chiundura Uninfested 0.14
0.12
0.10
Leaf index Leaf 0.08
0.06
0.04
0.02
0.00
Hlubi Chiredhi Zambia SC Sila Mashava Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
. Sorghum genotypes
Figure 5.6: Interaction effects of sorghum genotype and Striga strains at Henderson.
Leaf indices were similar for Chiredhi, Hlubi, Isifumbathe, Zambia, Mukadziusaende and
Ruzangwaya genotypes. The genotypes SC Sila, Wild sorghum and Mashava increased their leaf indices under infestation by Chiundura strain compared to uninfested sorghum genotypes. The Chiundura strain stimulated formation of more leaf tissue in wild sorghum and SC Sila because of the higher leaf indices observed for these genotypes (Figure 5.6).
5.4.5 Sorghum head weight
There was a significant (P<0.05) interaction of Striga strain and sorghum genotype on sorghum head weight at Henderson research Station and at BUSE (P<0.05) (Figure 5.7).
148
70 Rushinga Chiundura 60 Uninfested
50
40
30
Head weight(g) 20
10
0
Hlubi Chiredhi Zambia SC Sila Mashava Isifumbathe Tshwetha Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
70 Head weight at BUSE Rushinga 60 Chiundura Uninfested
50
40
30
20
Sorghumhead weight (g)
10
0 Hlubi Chiredhi ZambiaTswetha SC Sila Mashava Isifumbathe Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotypes
Figure 5.7: Interaction effects of sorghum genotypes and Striga strain at BUSE and Henderson
149
At both sites, the head weight of Hlubi, Mukadziusaende and Wild sorghum genotypes were not affected by the Striga strains. The effects of Rushinga and Chiundura strains were similar for Ruzangwaya and SC Sila genotypes and they were lower than uninfested genotypes
(Figure 5.7).
5.4.6 Total dry weight
The total dry weight was significantly affected by Striga strain (P<0.05) at BUSE, but was not affected at Henderson Research Station (Figure 5.8). The Rushinga strain gave the highest total dry weight at BUSE compared to the Chiundura strain and uninfested genotypes.
At Henderson, the total dry weight was not affected by the Striga strains (Figure 5.8).
250
BUSE Henderson 200
150
100
Total dry matter (g) matter dry Total
50
0 Rushinga Chiundura Uninfested Striga strains
Figure 5.8: Total dry matter of sorghum genotypes for BUSE and Henderson
150
350 Rushinga total dry mass at BUSE Chiundura 300 Uninfested
250
200
150
Total dry mass (g) dry Total 100
50
0 Hlubi Chiredhi ZambiaTswetha SC Sila Mashava Isifumbathe Ruzangwaya Wild Sorghum Mukadziusaende
Sorghum genotype
Figure 5.9: Interaction effects of sorghum genotype and Striga strain on total dry mass at BUSE
There was a significant interaction (P <0.05) between variety and Striga strain for total dry matter. Uninfested Isifumbathe, Zambia, Ruzangwaya, SC Sila and Mashava genotypes had significantly higher (P<0.05) head weight compared to infested genotypes. The Chiwundura strain had higher virulence on head weight for the varieties Mashava, Zambia and Chiredhi.
The head weight of genotypes Hlubi, Tshwetha, Mukadziusaende, Ruzangwaya and wild sorghum was not significantly reduced by the Striga strains (Figure 5.9).
Total dry matter was not significantly (P >0.05) affected by both Striga strains for the genotypes Chiredhi, Hlubi, Isifumbathe, Zambia, Tshwetha, Hlubi, Isifumbathe,
151
Mukadziusaende, Ruzangwaya and SC Sila. The Chiwundura strain significantly (P<0.05) lowered the total dry matter of the genotypes wild sorghum and Mashava.
5.5 Discussion
The objective of this study was to determine the stability of sorghum tolerance when infested with two Striga asiatica strains. The ability to express tolerance in a wider range of environments indicates plasticity which is an important component for yield maintenance.
According to Poorter et al., (2012), the plant has to balance the allocation of dry matter to leaves, stems and roots in a way that matches the physiological activities and functions performed by these organs.
Generally, the Chiundura strain was more virulent in dwarfing the sorghum genotypes compared to the Rushinga strain. The sorghum genotypes which resisted the dwarfing effects of the Striga were Hlubi, Zambia, Mukadziusaende, and Ruzangwaya. The two strains differed in their effects on sorghum lines. The results concur with the findings of Campos et al., (2004) who reported that the response of plants to stress is genotype specific. Other studies by Taylor et al., (1996) found that the plant growth regulator abscissic acid (ABA) increases in Striga infested plants and this leads to a reduction of stomatal conductance which consequently reduced carbon assimilation. In tolerant maize genotypes, Gurney et al., (2002) found two maize varieties in which Striga had limited effect on photosynthesis despite infection. In this study, failure by the Striga strains to dwarf Zambia, Mukadziusaende and
Ruzangwaya may be a demonstration that the genotypes are less responsive to ABA hence may be labelled as tolerant with respect to height. In sorghum genotypes such as Mashava, wild sorghum, SC Sila and Chiredhi, differential effects of the Striga strains were observed.
Flexas et al., (2006) attributed reduction in plant growth from imposition of stress to changes in the partitioning of assimilates between different organs and the balance between photosynthesis and respiration.
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The differential effects of the Striga strains on plant height was demonstrated in this study.
In this case, the Chiundura strain was the more virulent than the Rushinga strain. However,
Richards et al., (2006) asserted that a given host genotype may be plastic for a certain trait in a certain set of environments but not plastic for other traits in the same environments.
The effects of the two strains on chlorophyll content was not significantly different but all were significantly less than the uninfested genotypes. The chlorophyll content of the genotypes Ruzangwaya, Mukadziusaende and Mashava was not affected by the Striga strains at both sites. These results were similar to observations by Gurney et al., (2002), who reported that a tolerant maize variety was able to maintain high chlorophyll content levels despite being infested. Chlorophylls are the light harvesting complexes and tolerant genotypes should adjust chlorophyll content to be independent to keep photosynthesis at optimal rate. Aly (2007) reported that the host proteins are exported to the parasite. The ability of a genotype to maintain chlorophyll content irrespective of infection is key to tolerance. Chlorophyll content is a key parameter in tolerant genotypes as it depicts the extent of plant canopies and the subsequent carbon assimilation.
The varieties which lacked tolerance could have been caused by perturbations in host carbon assimilation that could also limit nitrogen assimilation and in-turn lower chlorophyll synthesis. This may explain the lower chlorophyll content of the infested Tshwetha,
Isifumbathe, Hlubi and SC Sila genotypes.
Across all genotypes, the root index for Rushinga was 0.388 at Henderson and 0.566 at
BUSE. Chiundura produced 0.349 at Henderson and 0.516 at BUSE against 0.22 and 0.377 for uninfested genotypes at Henderson and BUSE respectively. This indicated that sorghum genotypes allocated more dry matter to roots in response to Striga infestations. This behaviour coincides with that established by Poorter and Nagel (2000) and, Shipley and
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Meziane (2002) who reported a proportional increase in root fraction as soil available moisture decreases. A study by Acciaressi and Guiamet (2010) on Sorghum halepense found that the witchweeds incite a host to increase the amount of biomass allocated to roots when they are stressed. The root parameter is important because the spatial deployment of roots determines the ability of a plant to secure edaphic resources. According to Campos et al.,
(2004) and Reynolds et al., (2007), there is evidence to suggest that adverse effects of stress can successfully be avoided by changing the carbon allocation patterns to allow formation of a deep root system before the onset of a growth limiting stress. In this study, the sorghum genotypes differed in the allocation of dry matter to the roots. The lowest root indices were recorded for genotypes Chiredhi, Zambia, Isifumbathe and Mukadziusaende. The highest performing genotype was Mashava with 0.518 and wild sorghum with 0.493. The varieties that respond to Striga infestations by allocating more dry matter to roots at the expense of yield are non tolerant to Striga in terms of grain yield. The genotypes which show plasticity to Striga infestation and do not alter the allocated carbohydrates to the roots show plasticity to yield. Therefore, the varieties Chiredhi, Zambia, Mukadziusaende, Isifumbathe and SC
Sila are plastic to Striga infestations in terms of dry matter allocated to roots.
Striga strain did not lower sorghum head weight compared to uninfested sorghum for genotypes Chiredhi, Hlubi, Tswetha, Mukadziusaende, wild sorghum and Mashava at both sites. However, Tswetha and wild sorghum had low yields. This is expected for wild sorghum as it has not undergone any improvement to increase its yield. The genotypes have the capacity to diminish the consequences of infection. According to Swabrick et al., (2008), different cultivars differ in their capacity to tolerate the physiological and pathological effects of Striga parasitism finally resulting in milder or stronger impacts on crop yield. Despite the fact that several studies (Gurney et al., 2002; Rodenburg et al., 2005), have shown a reduction in yield after Striga infestation, it may be that these varieties uncouple the process
154 of photosynthesis and dry matter allocation. Similar results were found by Frost et al., (1997) in sorghum: Striga hermonthica associations. The results confirm the assertion by
Haussmann et al., (2001) that genetic variation for tolerance to Striga under field conditions exists in cultivated sorghums especially in local African cultivars. This may mean that Striga does not cause serious changes in the metabolism of some hosts.
Genotypes Isifumbathe, Zambia, Ruzangwaya and SC Sila had their head weight depressed by Striga. The results showed a depression in the dry matter allocated to the head. The reduced head weight index may partly result from the parasite acting as a sink of carbon, inorganic solutes and water and also lower rates of carbon gain by infested cereals (Cechin and Press, 1993). According to Joel (2000), the parasite develops as a strong metabolic sink, relative to the host and channels the flow of water and nutrients to itself thereby damaging the crops’ development. In this study, the stems made up the bulk of the biomass. The same results were found by Jahn et al., (2010) in rice cultivars.
The Chiundura and Rushinga strains had similar effects on head, root, and stem indices, and stem weight. This is in agreement with the findings of Dube and Belzile (2010) who found very low levels of genetic diversity among Striga gesneroides and this was attributed to a high degree of selfing. The results point to the fact that there are minor genetic variations in the virulence of S. asiatica strains on the stated sorghum traits. According to Loveless and
Hamrick (1984), S. asiatica is mainly autogamous and this can limit genetic diversity. Studies done in Kenya by Gethi et al., (2005) showed very low genetic diversity and the reason that was advanced was that the parasitic weed had recently been introduced in Kenya. In Benin,
Botanga et al., (2002) showed host speciation of Striga asiatica. In our study, the results indicated that there are particular processes and parameters of sorghum which were affected more by a particular strain in a particular genotype. These results may indicate that the strain seriously reduce dry matter accumulation in the affected varieties. When the same varieties
155 are grown in areas in which the Rushinga strain dominates the genotypes may be labelled as resistant only to lose resistance when grown where the Chiwundura strain dominates. It can therefore be inferred that the Striga strains each has physiological processes that it affects more in a particular genotype. In some sorghum genotypes, particular strains affected chlorophyll content, in some height; in some they caused allocation of dry matter to be more to the roots than the harvestable part.
5.6 Conclusion
It can therefore be concluded that there was differential virulence of Striga asiatica strains on plant height, chlorophyll content, tiller production, different sorghum indices and yield. This study confirms the variable virulence and the existence of physiological strains of Striga asiatica in Sorghum species in Zimbabwe.
5.7 References
Acciaresi HA, Guiamet JJ (2010).Below and above ground growth and biomass allocation in maize and Sorghum halepense in response to water competition. Weed Research 50: 481 –
492.
Aly R (2007) Conventional and biotechnological approaches for control of parasitic weeds.
In vitro cell Dev Biology Plant 43: 304 – 317
Bebawi FF (1981). Interspecific physiological variants of Striga hermonthica. Experimental
Agriculture 17: 419 - 423
Botanga C, Kling J, Berner D,Timko M (2002). Genetic variability of Striga asiatica L.
Kuntze based on AFLP analysis and host parasite interactions. Euphytica 128: 375 – 388
Botanga CJ,Timko MP (2006) Phenetic relationship among different races of Striga gesneroides (Willd) vatke from West Africa. Genome 49: 1351 1365
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Campos H, Cooper A, Halburn JE, Edmead GO, Schussler J.R. (2004). Improving drought tolerance in maize: view from industry. Field Crops Research 90: 19 – 34.
Cechin I and Press M.C (1993). Nitrogen relations of the Striga hermonthica host parasite associations: growth and photosynthesis. Plant cell and environment 16: 237 - 247
Doggett H (1965). Striga hermonthica on Sorghum in East Africa. Journal of Agricultural
Science 65: 183 – 194.
Dube M-P and Belzile FJ (2010). Low genetic variability of Striga gesneroides population on cowpeas might be explained by recent origin. Weed Research 50: 493 - 502
Flexas J, Bota J, Galmes J, Medrano H, Ribus-Carbo M (2006). Keeping a positive carbon balance under adverse conditions: response of photosynthesis and respiration to water stress.PhysiologiaPlantarum 127: 343 - 352
Frost DL; Gurney AL., Press MC, Scholes JD (1997). Striga hermonthica reduces photosynthesis in sorghum: the importance of stomatal limitations and potential role of ABA.
Plant cell and environment 20: 4873 – 4492
Gethi JG Smith ME Mitchell SE and Kresovich S (2005).Genetic Structure of Striga hermonthica and Striga asiatica population of Kenya. Weed Research 45: 64 – 73.
Gurney, AL, Press M.C and Scholes J.D (1999).Infection time and density influence the response of Sorghum to the parasitic angiosperm, Striga hermonthica. New Phytologist 143:
573 – 580
Gurney, A.L, taylor A, Mbwaga A, Scholes J.D, Press M.C. (2002). Do maize cultivars demonstrate tolerance to the parasitic weed Striga asiatica. Weed research 42: 299- 306
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Gurney, A.L, Slate J, Press M.C and Scholes J.D. (2006). A novel form of resistance in rice to the angiosperm parasite Striga hermonthica. New Phytologist 169: 199 – 208.
Hausmann B.I.G, Hess, D.E’ Welz H.G, Geiger, H.H (2000). Improved technologies for breeding Striga resistant sorghums. Field crops Research 66: 195 - 211
Jamil M, Charnikhova T, Houshyani B, van Ast, A, Bouwmesster, H (2012), Genetic variation in strigolactones production and tillering in rice and its effects on Striga hermonthica infection. Planta. DOI10.1007/s00425-011-1520-y
Jahn C.E, McKay J.K, Mauleon R, Stephens J, McNally K.L, Bush D.R, Leung H and Leach
J.E (2011). Genetic variation in biomass traits among 20 diverse rice varieties. Plant physiology 155 (1): 157-168
Joel D.M (2000). The long term approach to parasitic weed control: manipulation of specific developmental mechanisms of the parasite. Crop protection 19: 753 – 758
Jones W (1955). Further experiments in witch weed control 11 Existence of strans of Striga hermonthica. Empire Journal of Exp Agric 23: 206
Lewin C.H. (1939). Witchweeds (Striga lutea, Lour, Var Bicolor, O. Kuntze. Northern
Rhodesia Department of Agriculture Bulletin 2: 51 – 52
Lichtenhaler A.K and Wellburn L.R. (1983). Determination of total carotenoids and chlorophyll a and b of leaf extracts in different solvents. Biochemical Society Transactions
11: 591 - 592
Loveless M.D and Hamrick J.K (1984). Annual Reviews of Ecological systems 15: 65 - 73
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Musimwa C, Tongoona P, Mutengwa C.S. and Chivinge O.A (2001). Genetic variations in the witch weed inferred from RADP-PCR markers. African crop Science Proceedings 5: 51 –
55.
Pinheiro C and Chaves M.M (2011). Photosynthesis and drought: can we make metabolic connections from available data. Journal of Experimental Botany 62: 869 – 882.
Polniazek T.I, Parker C, Riches C.R (1991). Variation in virulence of Alectra vogelii populations in cowpeas. Tropical Pest Management 37: 152 - 154
Poorter H and Nagel O (2000). The role of biomass allocation in the growth response of plants to different levels of light, carbon dioxide, nutrients and water: a quantitative review.
Australian journal of Plant Physiology 27: 595 – 607
Poorter H, Niklas K.J, Reich P.B, Olekysyn J, Poot P and mommer L (2012). Biomass allocation to leaves, stems and roots: meta analysis of interspecific variation and environmental control. New Phytologist 193: 30 - 50
Ramaiah K.V (1987). Breeding cereals grains for resistance to wicthweeds. In Parasitic weeds in agriculture ed Musselman L.J .CRC Press. Pages 227 - 242
Reda F, DierickA,andVerkleij J.A.C (2010). Virulence study of Striga hermonthica populations from the Tigray Region (northern Ethiopia). World Journal of Agricultural
Sciences 6 (6): 676 - 682
Reynolds, M., Calderini, D., Condon, A. & Vargas, M., 2007. Association of source-sink traits with yield, biomass and radiation use efficiency among random sister lines from three wheat crosses in a high yield environment. Journal of Agricultural Science, 145: .3-16.
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Richard C.L, Bossdorf O, Muth N.Z, gurevitch J and Pigliucci (2006).Jack of all trades, master of some?On the role of phenotypic plasticity in plant invasions. Ecology letters 9: 981
- 993
Riches C.R, Hamilton K.A, Parker C (1992). Parasitism in grain legumes by Alectra spp.
Annals of Applied biology 121: 362 - 370
Parker C and Reid D.C (1979).Host specificity in striga spp, some preliminary observation.
Supplement to the proceedings of the second International Symposium on Parasitic weeds.
Pages 79 - 90
Rodenburg J, Bastiaans L, Weltzien E and Hess D (2005. How can field selection of for
Striga resistance and tolerance in Sorghum be improved. Field Crops Research 93: 34 – 50
Spallek T, Mutuku J.M and Shirasu K (2013). The genus Striga: a witch profile. Molecular
Plant Pathology.DOI10.1111.mpp.12058.
Swarbrick P.J; Huang K and Liu G (2008). Global patterns of gene expression in rice cultivars undergoing a susceptible or resistant interaction with the parasitic Striga hermonthica. New Phytologist 179: 515 – 529.
Taylor A, Martin J, Seel W.E, (1996). Physiology of parasitic associations between maize and witchweed (Striga hermonthica): Is ABA involved. Journal of Experimental botany 47:
1057 – 1065.
Vincent V and Thomas R.G (1961). An Agricultura survey of southern Rhodesia: agricultural regions survey. Salisbury, Rhodesia. Ministry of agriculture.
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CHAPTER SIX
Sorghum response to Striga asiatica based on maximum germination distance, Striga counts and sorghum tillering in
Zimbabwe
6.1 Abstract
Resistance through reduced strigolactones is one of the sustainable ways of managing Striga asiatica. To verify the existence of reduced strigolactone production in sorghum genotypes, an agar gel assay was carried out on seven Sorghum bicolor lines and one Sorghum arundinaceaum sourced in Zimbabwe. The eight sorghum genotypes were also grown in sand and Striga attachments and sorghum yield were recorded. The results indicated that sorghum genotypes varied significantly (P<0.05) with respect to maximum germination distance
(MGD) with wild sorghum and SC Sila having the largest MGDs. The genotype
Mukadziusaende had the highest tiller numbers (P<0.05), while SC Sila had the lowest.
Striga counts were highest on Wild Sorghum, Ruzangwaya and Hlubi. There was a negative correlation coefficient (R2 = 0.2225) between Mgd and tiller number, showing that the highest strigolactone producers had low tiller numbers. A positive correlation coefficient (P=
0.843) was found between sorghum yield and tiller numbers and it indicates that the more the tiller numbers the more the yield. It can therefore be concluded that resistance through reduced strigolactones was found in the sorghum genotype Mukadziusaende. The direct relationship between MGD and tillering means that tiller number can be used to select for reduced strigolactone production in the field.
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6.2 Introduction
The average sorghum productivity in the sub-Saharan Africa is low as a result of a myriad of production constraints of which Striga asiatica is a major obstacle. Striga asiatica is an obligate hemi-parasite that attaches to the roots of several crop species leading to severe yield losses (Parker, 1991). Beyond the burden of losing food and water to these parasites, host plants suffer from a characteristic malady resembling the symptoms of severe drought. Striga spp parasitise important food crops such as sorghum, maize, millets and rice. They have functional chloroplasts but their photosynthates provide only part of the energy required for survival, hence are regarded as hemi-parasites (Xie et al. 2010). This hemi-parasite has long been recognized as the greatest biological constraint to food production in sub Saharan
Africa, causing annual losses in excess of US$7 billion (Samejina et al., 2016).
Striga asiatica is geographically the most widespread species with large populations having been reported throughout sub Saharan Africa, south east China and the Indian subcontinent while smaller isolated populations have been reported in Arabia, Indonesia, Phillipines, north and east Carolina (USA) and Australia (Cochrane and Press, 1997). Striga asiatica is the predominant species towards the east African coast and southern Africa (Parker, 2009).
According to Bouwmeester et al., (2003), these parasites infest about two thirds of the 70 million hectares used for cereal production in Africa. Jamil et al., (2011) asserted that about
20 – 80 % yield losses or even complete crop failure can occur due to Striga parasitism.
The life cycle of the noxious cereal weed has co-evolved with many hosts to comprise a series of discrete steps that are closely linked to the host’s biochemistry (Hearne, 2009). The root parasitic weed has developed the ability to germinate only when they are exposed to germination stimulants released from the host roots, thus syncronising their life cycle to those of their potential hosts. Thus, they only germinate when a suitable host seed is in proximity to the Striga seed (Fernandez-Aparacio, et al., 2009). Fernadez-Aparacio et al., (2011) reported
162 that the synchrony is vital for parasitic weed survival because they have an absolute requirement for nutritional support from the host. This complex life cycle also presents opportunities for disruption (Pierce et al. 2003).
According to Bouwmeester et al., (2003) and Akiyama and Hayashi (2006), the first critical step in the life cycle of Striga, the germination of its seed, is regulated by strigolactones. The dependence on strigolactones could be exploited for Striga management through breeding for low strigolactones producing cultivars. The seeds of these parasitic plants will only germinate after perceiving a germination stimulant of their host (Yoneyama et al., 2010). After radicle emergence, the haustoria attaches and penetrates the host roots (Yoder, 2001). Cardoso et al.,
(2011) reported that once germination has been triggered, the radicle protrudes from the testa, elongates towards the root and develops haustorium, an organ that can attach to and penetrate roots of the host plant. The parasitic plant grows underground for 4 – 7 weeks prior to emergence and utilises host water, nutrients and photosynthates (Jamil et al., 2011). Much of the damage will have occurred by the time the Striga emerges above the ground.
Jamil et al., (2011) found significant variation among NERICA rice cultivars and their parents for strigolactones production and Striga germination. Production of low germination stimulants results in low numbers of Striga asiatica attachments thereby producing a resistant phenotype. Low germination stimulant producing genotypes have enhanced resistance to
Striga because of the reduction in Striga germination (Dun et al., 2009). Striga resistance is the mechanism that ensures lower field infestation and allows for satisfactorily high yields than fully susceptible ones (Rodenburg et al., 2005). Studies done in sorghum have also shown that genotypes with low production of germination stimulants have demonstrated resistance to Striga in the field (Ramaiah, 1987; Hess et al., 1992; Ejeta, 2007). In the past decade, several sorghum varieties with Striga resistance based on low germination stimulant production have been introduced such as SRN 39 and IS9830 in Sudan and Gobiye in
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Ethiopia (Tefera et al., 2012). However, resistance alone is not sufficient for adoption of a variety as adaptability to the environment and farmer preference have to be taken into account (Mohemed et al., 2016). This raises the need to identify resistant genotypes among those cultivated by farmers locally. Since the root parasites affect the crop from the time they attach to the root, the development of new control strategies should focus on the initial steps in host parasite interaction (Lopez-Raez et al., 2008).
Ejeta et al., (2000), Wilson et al., (2000), Gurney et al., (2001), and Gurney et al., (2002) demonstrated that the near relatives of cereals could provide new sources of tolerance and or resistance to parasite infection and may provide the way forward for the control of Striga spp.
According to Doggett (1976, 1988) and De Wet (1978), the cultivated sorghums of today primarily originated in Africa from the wild Sorghum bicolor spp arundinaceaum. Southern
Africa has more sorghum landraces and whilst the quest to find a landrace that produces the least strigolactones is still on, there is need to look at the wild sorghum and the vast number of sorghum landraces that are under cultivation in the African savannah. Given the high genetic diversity of the Sorghum spp, including wild sorghum, there is need to quantify strigolactones in most of these cultivated lines as they are grown in Striga infested fields.
According to Ejeta et al., (1993), different sorghum genotypes differed by as much as a billion fold in the amount of germination stimulants they produce. Jamil et al., (2011), asserted that strigolactones have a triple role which is underground communication between the plant, AM fungi, parasitic plants and the regulation of tillering. According to Umehara et al., (2008), and Lopez-Raez et al., (2008), strigolactones inhibit tillering in plants and therefore the ability to tiller could be used as a selection criteria for reduced strigolactones production.Therefore, the objectives of this study were to:
i) identify low strigolactone producing sorghum lines using agar gel analysis.
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ii) establish the relationships between maximum germination distance (MGD), sorghum
tillering, Striga asiatica counts and sorghum yield.
The corresponding alternate hypothese were:
i) the Sorghum genotypes vary in strigolactones production, resulting in variable
resistance to Striga asiatica.
ii) maximum germination distance is inversely related to sorghum tillering, while it is
positively related to Striga asiatica counts.
iii) MGD is inversely related to sorghum yield.
6.3 Materials and methods
6.3.1 Experiment 1: Agar jel assays
6.3.2 Sorghum germplasm and Striga asiatica seed sources
Refer to section 3.2.2
6.3.3 Experimental design
The treatments for this experiment were the sorghum genotypes (Table 3.1). They were arranged in a completely randomized design replicated four times.
6.3.4 Surface Sterilisation and sorghum seed germination
Sorghum seeds were soaked in 1 % sodium hypohlorite solution for 60 minutes and rinsed in double deionised water. The seeds were soaked in an aqeous solution of 10 % captan overnight. Seeds were rinsed with deionised water three times and then incubated in moist filter paper at 27 oC. After 48 hours, germinating seeds were placed in agar plates as outlined by Hess et al.(1992).
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6.3.5 Conditioning of Striga seed
Striga asiatica seeds were placed in 30 ml sample bottles and rinsed three times by adding 3-
5 drops of the detergent tween 20 into 10 ml of distilled water. Sonication was done using an ultra sonic cleaner three minutes during the first rinse (Mutengwa, 2004). The Striga seeds were incubated at 27 oC for three days prior to transferring them into the fresh sterile flasks containing 15 ml of 0.001 % acqeous benomyl solution. The sample bottles were re- incubated at 25 oC for 35 days before they were ready for use in the agar jel assay.
6.3.6 The assay set up
Pre-conditioned Striga seeds were pipetted into petri dishes. Water agar was then poured over the seed. The roots of the germinating sorghum seeds were placed in the solidifying agar with the root tip pointing across the plate. The plates were incubated in the dark for five days. The
MGD (distance between the host root and the furthest germinated Striga seed) were used as indicators of the quantities of strigolactones produced. The MGDs were recorded using a graduated microscope at 120 hours of incubation time at 30oC. .
6.4 Experiment 2: Pot screening
About 1g of S. asiatica seeds were weighed for every treatment and mixed thoroughly with 2
Kg of washed river sand. The sand was sterilized before the start of the experiment by heating in an oven at 120 oC for 48 hours to kill any Striga weed seeds that could be in the sand. The method was adapted from Jamil et al., (2011). Plastic pots of dimensions 18 cm diameter and 20 cm height were used.
6.4.1 Experimental design, planting and data collection
There were 8 genotypes (Table 3.1) and the experiment was replicated four times and laid down as a completely randomized design. Five sorghum seeds were planted in pots at a depth
166 of 0.5 cm. The seedlings were thinned to one plant per pot at 2 WACE. The sorghum plants were allowed to grow in pots for 20 weeks and the Striga that emerged were counted. The number of tillers, maximum germination distance were also recorded. Yield data was also recorded at the end of the experiment.
6.4.2 Data analysis The data was analysed according to the model:
Yij = µ + Ti +eij
Yij was the measured parameter e.g tiller number, µ = general mean, Ti effect of the treatment and eij is the error term. Correlations of the measured parameters were determined using
Satistical Package for Social Sciences and Genstat version 12.
6.5 Results
6.5.1 Maximum germination distance (MGD) The sorghum genotypes differed strongly (P=0.001) with regard to maximum germination distance, which is indicative of the strigolactones quantity produced (Figure 6.1). The minimum germination distance was 1.225 cm and it was for Mukadziusaende whilst the maximum was 2.775 cm for SC Sila (Figure 6.1).
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3.5
3.0
2.5
2.0
1.5
1.0
Germination distance (cm) Germination
0.5
0.0
Hlubi SC Sila Chiredhi Zambia Isifumbathe Wild sorghum Ruzangwaya Mukadziusaende
Sorghum genotypes
Figure 6.1: Maximum germination differences for various sorghum genotypes
6.5.2 Tillering Sorghum genotypes varied strongly (P <0.01) in tillering, and the average number of tillers varied from 2 for SC Sila to 5 for Mukadziusaende (Figure 6.2). The genotypes that had the highest number of tillers were Mukadziusaende and wild sorghum while the lowest were SC Sila and Zambia (Figure
6.2).
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6
5
4
3
Tiller number Tiller 2
1
0
Hlubi SC Sila Chiredhi Zambia Isifumbathe Wild sorghum Ruzangwaya Mukadziusaende
Sorghum genotypes
Figure 6.2: Effect of Striga asiatica on tillering of sorghum genotypes
6.5.3 Striga counts
18
16
14
12
10
8
Striga countsStriga 6
4
2
0 Hlubi SC Sila Chiredhi Zambia Wild sorghum RuzangwayaIsifumbathe Mukadziusaende Sorghum genotypes
Figure 6.3: Effect of Sorghum genotypes on Striga counts
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The sorghum genotypes varied strongly in eliciting Striga germination (P<0.01). The genotypes that had the highest number of Striga counts were Ruzangwaya and Hlubi, while the lowest were Mukadziusaende and Chiredhi (Figure 6.3).
6.5.3 Correlations between maximum germination distance and tillering
The results indicate a negative relationship between MGD and tillering (R2 = 0.2225) (Figure
6.4). The relationship indicates that as MGD increases tillering decreases. A positive relationship between tiller numbers and yield (R2 =0.8436) indicates that as tiller numbers increase yield also increases (Figure 6.5).
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Figure 6.4: The relationship between germination distance and tiller numbers
Figure 6.5: Relationships between sorghum yield and tiller numbers
6.6 Discussion The objectives of this study were to identify sorghum genotypes that produced the lowest strigolactones, and then correlate strigolactones production to tillering, Striga counts and yield. It is noteworthy that, among all the genotypes evaluated n the present study the genotype Mukadziusaende was identified as the resistant genotype producing low amount of strigolactones and sustained lower Striga emergence. The sorghum genotypes with lowest maximum germination distances were Mukadziusaende, Chiredhi and Isifumbathe, whilst wild sorghum and SC Sila had the biggest maximum germination distances. However, the level of susceptibility differed among the genotypes. This is supported by Haussmann et al.,
(2000) who reported that the Striga species negatively affects the growth and yield of crops they infect but the extent of the negative effects is a function of the environment and genetic makeup of the host and the parasite.
These results are consistent with previous observations in cereals like rice (Jamil et al., 2011).
The results confirm the existence of large genetic variation among the sorghum cultivars.
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According to Jamil et al., (2011), up to about 500-fold differences exist in the amounts of strigolactones exuded by rice Germplasm. Ejeta et al., (1993) confirmed the same results in sorghum and reported differences as much as a billion fold in the amounts of stimulants produced by sorghum.
Tillering varied among sorghum genotypes with Mukadziusaende having the highest tiller number whilst the lowest was SC Sila (Figure 6.2). In sorghum, tillering has been proposed to be under genetic and environmental control and according to Kim et al., (2010), tillering has not been comprehensively addressed by the carbohydrate supply and demand framework. In this study the sorghum genotypes were subjected to the same environmental conditions hence the environmental influences were eliminated. Therefore, the differences suggested that sorghum genotypes may also differ in their propensity to tiller which is independent of the carbon supply demand (Kim et al., 2010). The differences could be due to differences in hormonal signaling as the plants were in the same environment. According to Umehara et al.,
(2008), the hormone strigolactone reduces tillering in plants, such that plants that produce less strigolactones have profuse tillering compared to those that produce more. The results of this study support the propensity to tiller hypothesis as the genotypes were grown in the same conditions.
Increase in MGD indicates susceptibility of the genotype to Striga infestations. This means reduced MGD gives a resistant phenotype which inturn gives higher grain yields. The results corroborates previous findings by Mohemed et al., (2016) on the relationship between germination stimulant activity and Striga infestation. Smaller MGDs mean low amounts of active stimulants which confer pre-attachment resistance and accounts for yield mantainance in the sorghum genotypes. There was a significant correlation between MGD and Striga counts. To the contrary, Haussmann et al., (2000) compared the results of pot trials and only weak correlations between germination distance in agar jel assay and the number of emerged
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Striga plants. However, Rodenburg et al., (2005) reported high correlation coefficient between root exudates and infection levels as illustrated by Striga counts.
6.7 Conclusion Among the set of eight sorghum genotypes screened under pot conditions in Zimbabwe, significant differences were found in their levels of resistance. The genotype
Mukadziusaende showed excellent levels of resistance as illustrated by lower MGDs and
Striga counts. The genotypes SC Sila and wild sorghum were the most susceptible. Yield of sorghum was inversely related to germination distance and tiller number increased as sorghum yield.
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177
CHAPTER SEVEN: GENERAL DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS
7.1 Introduction This chapter is a synopsis of the whole study in relation to the objectives and the major findings. The main objectives of the study are presented together with major findings and conclusions. Lastly, a section on recommendations for further research and for farmers who produce sorghum in Striga asiatica infested fields are presented.
7.2 Discussion The ‘niche area’ of the study or the recommendation domain is the small holder sorghum producers in Zimbabwe and the whole of tropical sub Saharan Africa. Literature review showed that communal farmers have serious problems in sorghum production as a result of
Striga infestation sometimes resulting in 100 % losses (Berner et al. 1995, Mabasa, 2003,
Rubiales et al. 2009). Management of Striga still remains a major challenge faced by small holder farmers in Zimbabwe. Results reported elsewhere especially for rice has promising results through resistance and tolerance (Jamil et al., 2012, Sun et al. 2007, Jamil et al. 2011)
Sorghum genotypes were evaluated on their resistance and tolerance to Striga. This study investigated the resilience of Striga infested sorghum under drought, mulch and under various Striga asiatica strains. The study also sought to determine sorghum resistance to S. asiatica with respect to reduced strigolactone production.
When growing sorghum in Striga infested fields which are prone to drought, the drought exacerbates the effects of Striga in sorghum. However, there are genotypic differences on sorghum responses to the two stresses. The sorghum line Mukadziusaende emerged as a better performer when exposed to both stresses. On growth, water availability and Striga infestation had the same effect on sorghum. Reduced water availability on Striga infested sorghum strongly reduced sorghum growth. It is therefore important to subject sorghum
178 varieties to multiple stresses common in the field especially at evaluation stages as simultaneous occurrence of the stress is common in the subtropical sub Saharan Africa.
Mulching at a rate of 3 tons/ha enables expression of tolerance traits in some sorghum genotypes and negates the effects of Striga parasitism. Mulching at 3 ton/ha as promoted in
CA has been reported to suppress weeds through physical impedance and allelopathy. When mulch is aplied, there is increased water penetration into the soil with subsequent prevention of excessive evapo-transpiration losses (Scopel et al. 1998, Rao et al. 1998, Adekalu et al.
2007). Striga affects the water economy of the sorghum plant hence increased moisture availability through mulch protects sorghum from the effects of Striga. Tolerance expression is improved under mulch. Mulching is currently being promoted as a component of conservation agriculture so adoption can cushion the small scale farmers from the effects of
Striga asiatica parasitism. Mulching increased chlorophyll concentration compared to unmulched pots which in-turn maintained sorghum productivity. Mulching was advantageous in the drier season compared to the wetter season. Drier seasons are more common in sub
Saharan Africa due to the effects of climate change. Again, the ability to tiller gave genotypes higher yield as some genotypes continued to produce tillers after being affected by
Striga.
The problem of the existence of Striga asiatica strains was confirmed in Zimbabwe in this study. Differential effects were observed when similar genotypes were subjected to the two strains. This dimension complicates Striga asiatica management in the smallholder sector.
Trials done on supposedly resistant materials should be done all over the country to determine if they can withstand local Striga asiatica diversity. Sorghum genotypes tended to vary in their response to the strains.
179
No genotype was completely resistant to Striga but were differentially sensitive. The genotype Mukadziusaende produced the least strigolactones which in turn produces a resistant phenotype. Wild sorghum and SC Sila (registered variety) were the highest producers of strigolactones. Sorghum tillering was inversely related to strigolactones and this confirmed what is found in literature (Jamil et al. 2012). It implies that farmers may use tillers to predict strigolactone production in the field. The researchers may select for resistant lines using tiller numbers. Higher tillers are lower producers of strigolactones.
7.3 Conclusions
The following conclusions can be made from the results of this study
1. Reduced water availability caused by droughts increase the effects of Striga asiatica
on sorghum although some genotypes may withstand the pressure.
2. Reduced water availability and Striga asiatica infestation had mutually exclusive
effects on chlorophyll concentration and NDVI.
3. The use of mulch benefits small holder farmers who grow their sorghum in Striga
infested fields since the mulch negates the effects of Striga especially under low
rainfall conditions.
4. There is existence of Striga asiatica physiological strains in Zimbabwe and this calls
for widespread trials on any material to be deemed resistant to the parasite.
5. Mukadziusaende had the least MGD and this means it was the least strigolactones
producer and got fewer Striga attachments and hence it produced the resistant
phenotype.
180
6. Higher tiller producers in sorghum indicates reduced strigolactones producers hence
researchers can use it to select for resistant phenotypes.
7. Sorghum arundinaceaum was found to be susceptible to Striga asiatica and may not
be a source of resistant material in sorghum breeding.
7.4. Recommendations for further research
1. More studies are needed on the link between reduced moisture availability to abscissic acid need to be done to gain full understanding of the combined effects of drought on Striga infested sorghum.
2. There is need to quantify the link between mulching, moisture availability and the effects of parasitism.
3. Striga asiatica strains from the major sorghum producing regions in Zimbabwe to be tested on any genotypes deemed resistant.
4. More genotypes from the genebank and from farmers’ fields need to be evaluated for
Striga resistance and tolerance.
181
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183
APPENDIX
APPENDICES
Appendix for Chapter 3: Analysis of variance tables for experiment 1 and 11
Analysis of variance
Variate: Head_DM
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 252.555 63.139 9.07 <.001 Infection 1 83.733 83.733 12.02 0.001 Drought 1 178.124 178.124 25.57 <.001 Variety.Infection 4 5.909 1.477 0.21 0.930 Variety.Drought 4 23.180 5.795 0.83 0.513 Infection.Drought 1 2.481 2.481 0.36 0.554 Variety.Infection.Drought 4 11.714 2.928 0.42 0.793 Residual 40 278.599 6.965 Total 59 836.294
Analysis of variance
Variate: Head_DM_adj
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 328.220 82.055 9.07 <.001 Infection 1 108.819 108.819 12.02 0.001 Drought 1 231.490 231.490 25.57 <.001 Variety.Infection 4 7.679 1.920 0.21 0.930 Variety.Drought 4 30.125 7.531 0.83 0.513 Infection.Drought 1 3.224 3.224 0.36 0.554 Variety.Infection.Drought 4 15.223 3.806 0.42 0.793 Residual 40 362.067 9.052 Total 59 1086.847
Analysis of variance
Variate: Root_dry
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 2850.7 712.7 2.99 0.030 Infection 1 416.0 416.0 1.74 0.194 Drought 1 2163.5 2163.5 9.07 0.004 Variety.Infection 4 408.4 102.1 0.43 0.788 Variety.Drought 4 496.7 124.2 0.52 0.721 Infection.Drought 1 147.7 147.7 0.62 0.436 Variety.Infection.Drought 4 328.4 82.1 0.34 0.847 Residual 40 9544.2 238.6 Total 59 16355.7
184
Analysis of variance
Variate: Rut_index
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.13483 0.03371 2.78 0.040 Infection 1 0.04188 0.04188 3.45 0.071 Drought 1 0.00140 0.00140 0.12 0.735 Variety.Infection 4 0.01746 0.00436 0.36 0.836 Variety.Drought 4 0.03239 0.00810 0.67 0.618 Infection.Drought 1 0.01862 0.01862 1.54 0.223 Variety.Infection.Drought 4 0.02271 0.00568 0.47 0.759 Residual 40 0.48511 0.01213 Total 59 0.75439
185
Analysis of variance for spad in experiment 2 at 10 wace
Variate: Spad_3ex
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 108.45 27.11 0.45 0.768 Infection 1 15.50 15.50 0.26 0.613 Drought 1 41.50 41.50 0.70 0.409 Variety.Infection 4 52.84 13.21 0.22 0.925 Variety.Drought 4 45.59 11.40 0.19 0.942 Infection.Drought 1 28.15 28.15 0.47 0.496 Variety.Infection.Drought 4 151.34 37.83 0.63 0.641 Residual 40 2385.09 59.63 Total 59 2828.47
Analysis of variance
Variate: Total_DM
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 4976.0 1244.0 3.38 0.018 Infection 1 103.4 103.4 0.28 0.599 Drought 1 9986.5 9986.5 27.17 <.001 Variety.Infection 4 2860.0 715.0 1.94 0.122 Variety.Drought 4 231.4 57.9 0.16 0.959 Infection.Drought 1 58.9 58.9 0.16 0.691 Variety.Infection.Drought 4 582.3 145.6 0.40 0.810 Residual 40 14704.8 367.6 Total 59 33503.4
Analysis of variance
Variate: dry_stems
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 283.43 70.86 1.39 0.254 Infection 1 5.94 5.94 0.12 0.734 Drought 1 536.29 536.29 10.53 0.002 Variety.Infection 4 687.27 171.82 3.37 0.018 Variety.Drought 4 101.22 25.31 0.50 0.738 Infection.Drought 1 0.01 0.01 0.00 0.989 Variety.Infection.Drought 4 335.88 83.97 1.65 0.181 Residual 40 2036.62 50.92 Total 59 3986.66
Analysis of variance at 6 wace in experiment 1
Variate: green_1_exp
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.010077 0.002519 0.37 0.829 Infection 1 0.029927 0.029927 4.38 0.043
186
Drought 1 0.390427 0.390427 57.18 <.001 Variety.Infection 4 0.018423 0.004606 0.67 0.614 Variety.Drought 4 0.010123 0.002531 0.37 0.828 Infection.Drought 1 0.023207 0.023207 3.40 0.073 Variety.Infection.Drought 4 0.044577 0.011144 1.63 0.185 Residual 40 0.273133 0.006828 Total 59 0.799893
Analysis of variance
Variate: green_2_exp_2
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.108593 0.027148 4.23 0.006 Infection 1 0.009882 0.009882 1.54 0.222 Drought 1 0.101682 0.101682 15.86 <.001 Variety.Infection 4 0.006060 0.001515 0.24 0.916 Variety.Drought 4 0.031327 0.007832 1.22 0.317 Infection.Drought 1 0.008402 0.008402 1.31 0.259 Variety.Infection.Drought 4 0.027407 0.006852 1.07 0.385 Residual 40 0.256467 0.006412 Total 59 0.549818
Analysis of variance
Variate: head_index
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.119577 0.029894 11.16 <.001 Infection 1 0.019735 0.019735 7.37 0.010 Drought 1 0.016000 0.016000 5.97 0.019 Variety.Infection 4 0.003059 0.000765 0.29 0.886 Variety.Drought 4 0.002850 0.000713 0.27 0.898 Infection.Drought 1 0.000630 0.000630 0.24 0.630 Variety.Infection.Drought 4 0.002811 0.000703 0.26 0.900 Residual 40 0.107182 0.002680 Total 59 0.271845
Analysis of variance
Variate: leaf_index
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.019685 0.004921 1.45 0.235 Infection 1 0.000386 0.000386 0.11 0.738 Drought 1 0.002152 0.002152 0.63 0.430 Variety.Infection 4 0.015046 0.003761 1.11 0.366 Variety.Drought 4 0.007571 0.001893 0.56 0.694 Infection.Drought 1 0.004273 0.004273 1.26 0.268 Variety.Infection.Drought 4 0.000867 0.000217 0.06 0.992 Residual 40 0.135712 0.003393
187
Total 59 0.185692
Analysis of variance
Variate: leaves_DM
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 338.93 84.73 4.98 0.002 Infection 1 6.98 6.98 0.41 0.525 Drought 1 226.40 226.40 13.30 <.001 Variety.Infection 4 160.65 40.16 2.36 0.070 Variety.Drought 4 4.32 1.08 0.06 0.992 Infection.Drought 1 6.66 6.66 0.39 0.535 Variety.Infection.Drought 4 28.12 7.03 0.41 0.798 Residual 40 680.87 17.02 Total 59 1452.93
Analysis of variance for experiment 1 at 6 wace
Variate: spad1_Exp2
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 641.20 160.30 5.03 0.002 Infection 1 141.53 141.53 4.44 0.041 Drought 1 440.38 440.38 13.81 <.001 Variety.Infection 4 74.74 18.68 0.59 0.675 Variety.Drought 4 351.77 87.94 2.76 0.041 Infection.Drought 1 23.60 23.60 0.74 0.395 Variety.Infection.Drought 4 105.80 26.45 0.83 0.514 Residual 40 1275.09 31.88 Total 59 3054.11
Analysis of variance
Variate: stem_index
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.033732 0.008433 1.38 0.257 Infection 1 0.004114 0.004114 0.68 0.416 Drought 1 0.003641 0.003641 0.60 0.444 Variety.Infection 4 0.024635 0.006159 1.01 0.413 Variety.Drought 4 0.029982 0.007496 1.23 0.313 Infection.Drought 1 0.001804 0.001804 0.30 0.589 Variety.Infection.Drought 4 0.020288 0.005072 0.83 0.513 Residual 40 0.243676 0.006092 Total 59 0.361872
188
Analysis of variance
Variate: Height_1
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 5431.7 1357.9 11.83 <.001 Infection 1 268.8 268.8 2.34 0.134 Drought 1 163.4 163.4 1.42 0.240 Variety.Infection 4 97.6 24.4 0.21 0.930 Variety.Drought 4 403.4 100.9 0.88 0.485 Infection.Drought 1 421.3 421.3 3.67 0.063 Variety.Infection.Drought 4 72.4 18.1 0.16 0.958 Residual 40 4590.0 114.8 Total 59 11448.6
Analysis of variance
Variate: Height_2
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 3903.6 975.9 6.60 <.001 Infection 1 777.6 777.6 5.26 0.027 Drought 1 614.4 614.4 4.16 0.048 Variety.Infection 4 116.2 29.1 0.20 0.939 Variety.Drought 4 759.1 189.8 1.28 0.293 Infection.Drought 1 77.1 77.1 0.52 0.474 Variety.Infection.Drought 4 352.4 88.1 0.60 0.668 Residual 40 5913.3 147.8 Total 59 12513.7
Analysis of variance
Variate: Height_3
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 4 1872.3 468.1 2.15 0.093 Infection 1 908.7 908.7 4.17 0.048 Drought 1 1096.5 1096.5 5.03 0.031 Variety.Infection 4 911.3 227.8 1.05 0.396 Variety.Drought 4 1583.0 395.7 1.82 0.145 Infection.Drought 1 139.5 139.5 0.64 0.428 Variety.Infection.Drought 4 890.6 222.7 1.02 0.408 Residual 39 (1) 8496.5 217.9 Total 58 (1) 15753.5
189
Analysis of variance
Variate: Tillers
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 46.567 11.642 5.87 <.001 Infection 1 5.400 5.400 2.72 0.107 Drought 1 0.067 0.067 0.03 0.855 Variety.Infection 4 11.433 2.858 1.44 0.238 Variety.Drought 4 2.433 0.608 0.31 0.872 Infection.Drought 1 0.267 0.267 0.13 0.716 Variety.Infection.Drought 4 10.900 2.725 1.37 0.260 Residual 40 79.333 1.983 Total 59 156.400
Analysis of variance
Variate: Greeness2
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.090640 0.022660 3.19 0.023 Infection 1 0.003375 0.003375 0.47 0.495 Drought 1 0.001042 0.001042 0.15 0.704 Variety.Infection 4 0.005300 0.001325 0.19 0.944 Variety.Drought 4 0.023133 0.005783 0.81 0.524 Infection.Drought 1 0.004002 0.004002 0.56 0.457 Variety.Infection.Drought 4 0.049140 0.012285 1.73 0.163 Residual 40 0.284333 0.007108 Total 59 0.460965
Analysis of variance
Variate: Spad_1
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 523.73 130.93 4.73 0.003 Infection 1 11.97 11.97 0.43 0.515 Drought 1 17.93 17.93 0.65 0.426 Variety.Infection 4 66.47 16.62 0.60 0.665 Variety.Drought 4 182.16 45.54 1.64 0.182 Infection.Drought 1 10.09 10.09 0.36 0.550 Variety.Infection.Drought 4 36.34 9.08 0.33 0.857 Residual 40 1107.59 27.69 Total 59 1956.27
Analysis of variance
Variate: Spad_2
190
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 4 734.04 183.51 7.29 <.001 Infection 1 0.23 0.23 0.01 0.924 Drought 1 10.46 10.46 0.42 0.523 Variety.Infection 4 10.32 2.58 0.10 0.981 Variety.Drought 4 133.83 33.46 1.33 0.276 Infection.Drought 1 25.94 25.94 1.03 0.316 Variety.Infection.Drought 4 32.42 8.10 0.32 0.861 Residual 39 (1) 981.38 25.16 Total 58 (1) 1922.27
Analysis of variance for experiment 11 at 6wace
Variate: greeness
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.072640 0.018160 2.07 0.103 Infection 1 0.005042 0.005042 0.57 0.453 Drought 1 0.066002 0.066002 7.51 0.009 Variety.Infection 4 0.042333 0.010583 1.20 0.324 Variety.Drought 4 0.019673 0.004918 0.56 0.693 Infection.Drought 1 0.009882 0.009882 1.12 0.295 Variety.Infection.Drought 4 0.041060 0.010265 1.17 0.339 Residual 40 0.351533 0.008788 Total 59 0.608165
191
Analysis of variance at 10 WACE in experiment 11
Variate: greeness_3
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.03739 0.00935 0.88 0.486 Infection 1 0.09048 0.09048 8.49 0.006 Drought 1 0.06080 0.06080 5.71 0.022 Variety.Infection 4 0.05143 0.01286 1.21 0.323 Variety.Drought 4 0.10554 0.02639 2.48 0.060 Infection.Drought 1 0.00160 0.00160 0.15 0.700 Variety.Infection.Drought 4 0.01591 0.00398 0.37 0.826 Residual 40 0.42627 0.01066 Total 59 0.78942
Analysis of variance
Variate: spad_3
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 4 346.18 86.54 1.05 0.395 Infection 1 12.97 12.97 0.16 0.694 Drought 1 843.00 843.00 10.22 0.003 Variety.Infection 4 121.81 30.45 0.37 0.829 Variety.Drought 4 203.81 50.95 0.62 0.653 Infection.Drought 1 36.97 36.97 0.45 0.507 Variety.Infection.Drought 4 246.88 61.72 0.75 0.565 Residual 39 (1) 3217.59 82.50 Total 58 (1) 4845.74
Analysis of variance
Variate: Head_index
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.177163 0.044291 10.37 <.001 Infection 1 0.035755 0.035755 8.37 0.006 Drought 1 0.009396 0.009396 2.20 0.146 Variety.Infection 4 0.014336 0.003584 0.84 0.509 Variety.Drought 4 0.018068 0.004517 1.06 0.390 Infection.Drought 1 0.000334 0.000334 0.08 0.781 Variety.Infection.Drought 4 0.008320 0.002080 0.49 0.745 Residual 40 0.170891 0.004272 Total 59 0.434264
Analysis of variance
Variate: Head_wei
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 404.89 101.22 9.92 <.001
192
Infection 1 90.28 90.28 8.85 0.005 Drought 1 116.82 116.82 11.45 0.002 Variety.Infection 4 32.75 8.19 0.80 0.531 Variety.Drought 4 111.80 27.95 2.74 0.042 Infection.Drought 1 4.98 4.98 0.49 0.489 Variety.Infection.Drought 4 15.97 3.99 0.39 0.814 Residual 40 408.14 10.20 Total 59 1185.64
Analysis of variance
Variate: Internode
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 64.077 16.019 1.66 0.178 Infection 1 75.264 75.264 7.80 0.008 Drought 1 14.017 14.017 1.45 0.235 Variety.Infection 4 37.273 9.318 0.97 0.437 Variety.Drought 4 33.353 8.338 0.86 0.494 Infection.Drought 1 97.283 97.283 10.09 0.003 Variety.Infection.Drought 4 14.067 3.517 0.36 0.832 Residual 40 385.813 9.645 Total 59 721.147
Analysis of variance
Variate: Leaf_index
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.007335 0.001834 0.39 0.812 Infection 1 0.000971 0.000971 0.21 0.650 Drought 1 0.002985 0.002985 0.64 0.428 Variety.Infection 4 0.003511 0.000878 0.19 0.943 Variety.Drought 4 0.003462 0.000866 0.19 0.944 Infection.Drought 1 0.026219 0.026219 5.64 0.022 Variety.Infection.Drought 4 0.004498 0.001124 0.24 0.913 Residual 40 0.186057 0.004651 Total 59 0.235038
Analysis of variance
Variate: LeavesDM
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 4 421.57 105.39 5.71 0.001 Infection 1 9.91 9.91 0.54 0.468 Drought 1 151.02 151.02 8.18 0.007 Variety.Infection 4 180.02 45.00 2.44 0.063 Variety.Drought 4 13.98 3.50 0.19 0.943 Infection.Drought 1 8.19 8.19 0.44 0.509 Variety.Infection.Drought 4 68.25 17.06 0.92 0.460
193
Residual 39 (1) 719.91 18.46 Total 58 (1) 1566.35
Analysis of variance
Variate: Root_dry
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 5019.6 1254.9 4.08 0.007 Infection 1 1567.0 1567.0 5.10 0.029 Drought 1 2840.2 2840.2 9.25 0.004 Variety.Infection 4 535.5 133.9 0.44 0.782 Variety.Drought 4 615.4 153.9 0.50 0.735 Infection.Drought 1 890.5 890.5 2.90 0.096 Variety.Infection.Drought 4 265.4 66.3 0.22 0.928 Residual 40 12288.3 307.2 Total 59 24022.0
Analysis of variance
Variate: Root_index
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.29315 0.07329 5.75 <.001 Infection 1 0.05435 0.05435 4.26 0.045 Drought 1 0.00155 0.00155 0.12 0.729 Variety.Infection 4 0.01544 0.00386 0.30 0.874 Variety.Drought 4 0.01643 0.00411 0.32 0.861 Infection.Drought 1 0.04829 0.04829 3.79 0.059 Variety.Infection.Drought 4 0.02045 0.00511 0.40 0.807 Residual 40 0.50983 0.01275 Total 59 0.95949
Analysis of variance
Variate: Stem_index
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 0.039043 0.009761 1.60 0.193 Infection 1 0.005657 0.005657 0.93 0.341 Drought 1 0.006670 0.006670 1.09 0.302 Variety.Infection 4 0.039305 0.009826 1.61 0.190 Variety.Drought 4 0.029976 0.007494 1.23 0.314 Infection.Drought 1 0.005795 0.005795 0.95 0.335 Variety.Infection.Drought 4 0.012942 0.003235 0.53 0.714 Residual 40 0.243833 0.006096 Total 59 0.383221
Analysis of variance
Variate: Total_DM
194
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 7122.8 1780.7 3.50 0.015 Infection 1 1287.7 1287.7 2.53 0.119 Drought 1 9983.1 9983.1 19.62 <.001 Variety.Infection 4 3449.9 862.5 1.70 0.170 Variety.Drought 4 412.6 103.2 0.20 0.935 Infection.Drought 1 942.5 942.5 1.85 0.181 Variety.Infection.Drought 4 1254.5 313.6 0.62 0.653 Residual 40 20350.3 508.8 Total 59 44803.3
Analysis of variance
Variate: dry_stems
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 4 357.61 89.40 1.45 0.234 Infection 1 0.24 0.24 0.00 0.951 Drought 1 456.34 456.34 7.42 0.010 Variety.Infection 4 850.16 212.54 3.46 0.016 Variety.Drought 4 76.22 19.05 0.31 0.870 Infection.Drought 1 13.34 13.34 0.22 0.644 Variety.Infection.Drought 4 427.87 106.97 1.74 0.160 Residual 40 2460.59 61.51 Total 59 4642.37
APPENDIX 2: Analysis of variance tables for Chapter 4
Analysis of variance
Variate: Chlorophy_I_3
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 1862.54 206.95 5.30 <.001 Mulch 1 0.16 0.16 0.00 0.949 infestati 1 22.06 22.06 0.57 0.454 Variety.Mulch 9 461.28 51.25 1.31 0.244 Variety.infestati 9 440.13 48.90 1.25 0.276 Mulch.infestati 1 109.92 109.92 2.82 0.097 Variety.Mulch.infestati 9 417.35 46.37 1.19 0.315 Residual 79 (1) 3084.37 39.04
195
Total 118 (1) 6314.94
Analysis of variance for chlorophyll content at 6 WACE in 2013- 14 season
Variate: Chlorophyl1
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 343.60 38.18 1.81 0.080 Mulch 1 6.42 6.42 0.30 0.583 infestati 1 46.94 46.94 2.23 0.140 Variety.Mulch 9 201.91 22.43 1.06 0.399 Variety.infestati 9 375.21 41.69 1.98 0.053 Mulch.infestati 1 1.11 1.11 0.05 0.819 Variety.Mulch.infestati 9 172.52 19.17 0.91 0.522 Residual 77 (3) 1623.73 21.09 Total 116 (3) 2740.53
Analysis of variance for chlorophyll content at 8 WACE in the 2013 – 14 season
Variate: Chlorophyl_2
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 488.52 54.28 3.60 <.001 Mulch 1 42.96 42.96 2.85 0.096 infestati 1 3.47 3.47 0.23 0.633 Variety.Mulch 9 108.70 12.08 0.80 0.617 Variety.infestati 9 166.80 18.53 1.23 0.290 Mulch.infestati 1 16.88 16.88 1.12 0.294 Variety.Mulch.infestati 9 130.23 14.47 0.96 0.481 Residual 79 (1) 1192.75 15.10 Total 118 (1) 2145.72
Analysis of variance
Variate: Chlorophyl_4
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 856.97 95.22 1.32 0.242 Mulch 1 51.16 51.16 0.71 0.403 infestati 1 0.16 0.16 0.00 0.963 Variety.Mulch 9 1560.43 173.38 2.40 0.019 Variety.infestati 9 734.54 81.62 1.13 0.353 Mulch.infestati 1 36.14 36.14 0.50 0.482 Variety.Mulch.infestati 9 1033.34 114.82 1.59 0.134 Residual 73 (7) 5270.21 72.19 Total 112 (7) 8981.34
Analysis of variance
Variate: Chlorophyl_5
196
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 842.61 93.62 1.04 0.420 Mulch 1 375.77 375.77 4.16 0.045 infestati 1 81.43 81.43 0.90 0.346 Variety.Mulch 9 660.95 73.44 0.81 0.606 Variety.infestati 9 881.51 97.95 1.08 0.385 Mulch.infestati 1 145.31 145.31 1.61 0.209 Variety.Mulch.infestati 9 984.42 109.38 1.21 0.302 Residual 72 (8) 6505.40 90.35 Total 111 (8) 10367.63
Analysis of variance for stomatal conductance in the 2013 – 14 season
Variate: Conductance_1
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 6839.8 760.0 3.73 <.001 Mulch 1 0.3 0.3 0.00 0.969 infestati 1 793.9 793.9 3.89 0.052 Variety.Mulch 9 1525.5 169.5 0.83 0.590 Variety.infestati 9 2044.1 227.1 1.11 0.364 Mulch.infestati 1 57.8 57.8 0.28 0.596 Variety.Mulch.infestati 9 2063.8 229.3 1.12 0.357 Residual 74 (6) 15095.3 204.0 Total 113 (6) 26690.3
Analysis of variance
Variate: Height_1
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 2586.89 287.43 5.17 <.001 Mulch 1 12.50 12.50 0.22 0.637 infestati 1 191.83 191.83 3.45 0.067 Variety.Mulch 9 770.53 85.61 1.54 0.150 Variety.infestati 9 951.86 105.76 1.90 0.065 Mulch.infestati 1 39.99 39.99 0.72 0.399 Variety.Mulch.infestati 9 540.70 60.08 1.08 0.388 Residual 73 (7) 4059.35 55.61 Total 112 (7) 8943.01
Analysis of variance
Variate: Height_2
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 4060.7 451.2 3.78 <.001 Mulch 1 0.5 0.5 0.00 0.948
197 infestati 1 1658.9 1658.9 13.89 <.001 Variety.Mulch 9 1780.5 197.8 1.66 0.116 Variety.infestati 9 1270.9 141.2 1.18 0.320 Mulch.infestati 1 69.3 69.3 0.58 0.449 Variety.Mulch.infestati 9 605.0 67.2 0.56 0.823 Residual 70 (10) 8360.9 119.4 Total 109 (10) 15730.4
Analysis of variance
Variate: Height_4
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 69831. 7759. 5.92 <.001 Mulch 1 241. 241. 0.18 0.670 infestati 1 23801. 23801. 18.15 <.001 Variety.Mulch 9 7446. 827. 0.63 0.767 Variety.infestati 9 16268. 1808. 1.38 0.214 Mulch.infestati 1 1665. 1665. 1.27 0.264 Variety.Mulch.infestati 9 4834. 537. 0.41 0.926 Residual 71 (9) 93108. 1311. Total 110 (9) 200388.
Analysis of variance
Variate: Leaf_length
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 14022.9 1558.1 15.37 <.001 Mulch 1 7.8 7.8 0.08 0.783 infestati 1 55.4 55.4 0.55 0.462 Variety.Mulch 9 1109.3 123.3 1.22 0.299 Variety.infestati 9 734.0 81.6 0.80 0.614 Mulch.infestati 1 0.1 0.1 0.00 0.975 Variety.Mulch.infestati 9 407.5 45.3 0.45 0.905 Residual 71 (9) 7198.8 101.4 Total 110 (9) 23007.7
Analysis of variance for effect of sorghum genotypes on tiller number in the 2013 – 14 season
Variate: Tiller_1
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 106.135 11.793 6.33 <.001 Mulch 1 5.852 5.852 3.14 0.080 infestati 1 13.002 13.002 6.98 0.010 Variety.Mulch 9 20.335 2.259 1.21 0.299 Variety.infestati 9 29.185 3.243 1.74 0.093 Mulch.infestati 1 1.302 1.302 0.70 0.406
198
Variety.Mulch.infestati 9 31.052 3.450 1.85 0.072 Residual 79 (1) 147.167 1.863 Total 118 (1) 353.933
Analysis of variance
Variate: height_3
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. Variety 9 17558.5 1950.9 3.38 0.002 Mulch 1 218.7 218.7 0.38 0.540 infestati 1 6453.3 6453.3 11.17 0.001 Variety.Mulch 9 4393.1 488.1 0.84 0.578 Variety.infestati 9 2637.4 293.0 0.51 0.865 Mulch.infestati 1 224.1 224.1 0.39 0.535 Variety.Mulch.infestati 9 1299.2 144.4 0.25 0.985 Residual 72 (8) 41597.0 577.7 Total 111 (8) 70805.4
Analysis of variance
Variate: leaves_1
Source of variation d.f. s.s. m.s. v.r. F pr. Variety 9 34.000 3.778 1.76 0.090 Mulch 1 1.200 1.200 0.56 0.457 infestati 1 8.533 8.533 3.97 0.050 Variety.Mulch 9 28.967 3.219 1.50 0.163 Variety.infestati 9 37.300 4.144 1.93 0.060 Mulch.infestati 1 0.833 0.833 0.39 0.535 Variety.Mulch.infestati 9 18.333 2.037 0.95 0.489 Residual 80 172.000 2.150 Total 119 301.167
Analysis of variance for head weight in the 2014 – 15 season
Variate: Headweight_15
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 8424.1 936.0 7.95 <.001 Infestation 1 1780.9 1780.9 15.13 <.001 Mulch 1 4179.7 4179.7 35.50 <.001 variety.Infestation 9 1503.0 167.0 1.42 0.194 variety.Mulch 9 834.7 92.7 0.79 0.628 Infestation.Mulch 1 36.4 36.4 0.31 0.580 variety.Infestation.Mulch 9 554.2 61.6 0.52 0.854 Residual 80 9419.6 117.7 Total 119 26732.5
199
Appendix 3: Analysis of variance table for Chapter 5 experiment 1 and 11
Analysis of variance for head weight at Henderson research station
Variate: HEAD_WEI_g
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 6378.43 708.71 14.86 <.001 Strain 2 1098.93 549.46 11.52 <.001 variety.Strain 18 1541.34 85.63 1.79 0.047 Residual 60 2862.33 47.71 Total 89 11881.03
Analysis of variance
Variate: Head_weight_g
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 7776.93 864.10 16.87 <.001 Strain 2 596.40 298.20 5.82 0.005 variety.Strain 18 2058.11 114.34 2.23 0.011 Residual 60 3074.01 51.23 Total 89 13505.45
Analysis of variance
Variate: LEAF_WEI_g
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 527.380 58.598 7.64 <.001 Strain 2 1.550 0.775 0.10 0.904 variety.Strain 18 216.699 12.039 1.57 0.098 Residual 60 460.220 7.670 Total 89 1205.849
Analysis of variance
Variate: L_LENGTH
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 418.23 46.47 1.36 0.226 Strain 2 16.07 8.03 0.24 0.791 variety.Strain 18 965.93 53.66 1.57 0.097 Residual 60 2046.67 34.11 Total 89 3446.90
Analysis of variance
Variate: Leaf_weight_g
200
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 1425.37 158.37 9.02 <.001 Strain 2 4.31 2.15 0.12 0.885 variety.Strain 18 456.57 25.36 1.44 0.145 Residual 60 1053.60 17.56 Total 89 2939.85
Analysis of variance for sorghum height at Buse at 12 WACE
Variate: P_HEIGHT
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 53351. 5928. 4.30 <.001 Strain 2 10432. 5216. 3.79 0.028 variety.Strain 18 35048. 1947. 1.41 0.159 Residual 60 82631. 1377. Total 89 181463.
Analysis of variance for root weight at BUSE
Variate: Root_weight
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 36290.6 4032.3 5.56 <.001 Strain 2 16331.9 8165.9 11.26 <.001 variety.Strain 18 17350.5 963.9 1.33 0.204 Residual 60 43531.7 725.5 Total 89 113504.6
Analysis of variance for root index at BUSE
Variate: Rutindex
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 1.29520 0.14391 13.68 <.001 Strain 2 0.57482 0.28741 27.32 <.001 variety.Strain 18 0.25376 0.01410 1.34 0.197 Residual 60 0.63115 0.01052 Total 89 2.75493
Analysis of variance
Variate: STEM_WEI_g
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 3080.2 342.2 3.20 0.003 Strain 2 1268.5 634.3 5.93 0.004 variety.Strain 18 3796.0 210.9 1.97 0.026 Residual 60 6413.5 106.9 Total 89 14558.2
Analysis of variance
201
Variate: S_COUNT
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 474.27 52.70 1.19 0.319 Strain 2 424.09 212.04 4.78 0.012 variety.Strain 18 1021.47 56.75 1.28 0.234 Residual 60 2660.00 44.33 Total 89 4579.82
Analysis of variance for stem index at Buse
Variate: Stem_Inde
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 0.188103 0.020900 3.46 0.002 Strain 2 0.133236 0.066618 11.03 <.001 variety.Strain 18 0.171405 0.009522 1.58 0.096 Residual 60 0.362323 0.006039 Total 89 0.855066
Analysis of variance
Variate: Stem_weight_g
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 48728. 5414. 5.35 <.001 Strain 2 8141. 4070. 4.03 0.023 variety.Strain 18 28045. 1558. 1.54 0.108 Residual 60 60675. 1011. Total 89 145589.
Analysis of variance
Variate: Striga_Counts
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 792.90 88.10 1.69 0.111 Strain 2 687.09 343.54 6.59 0.003 variety.Strain 18 809.80 44.99 0.86 0.622 Residual 60 3126.67 52.11 Total 89 5416.46
202
Analysis of variance
Variate: TILLER_No
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 440.267 48.919 5.35 <.001 Strain 2 43.889 21.944 2.40 0.099 variety.Strain 18 103.667 5.759 0.63 0.862 Residual 60 548.667 9.144 Total 89 1136.489
Analysis of variance
Variate: Total
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 28960.4 3217.8 3.32 0.002 Strain 2 8709.5 4354.8 4.49 0.015 variety.Strain 18 27440.5 1524.5 1.57 0.097 Residual 60 58132.2 968.9 Total 89 123242.6
Analysis of variance
Variate: chloro_1
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 1112.223 123.580 12.41 <.001 Strain 2 532.241 266.120 26.71 <.001 variety.Strain 18 712.641 39.591 3.97 <.001 Residual 60 597.693 9.962 Total 89 2954.798
Analysis of variance for chlorophyll content at 8 wace at BUSE
Variate: chloro_2
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 602.738 66.971 7.26 <.001 Strain 2 186.027 93.013 10.08 <.001 variety.Strain 18 454.389 25.244 2.74 0.002 Residual 60 553.773 9.230 Total 89 1796.927
Analysis of variance for chlorophyll content at 12 wace at BUSE
Variate: chloro_3
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 917.362 101.929 12.11 <.001 Strain 2 171.811 85.905 10.21 <.001 variety.Strain 18 412.843 22.936 2.73 0.002 Residual 60 504.973 8.416
203
Total 89 2006.989
Analysis of variance
Source d.f. s.s. m.s. v.r. F pr. variety ignoring Strain 9 359.48 39.94 1.17 0.333 variety eliminating Strain 9 369.94 41.10 1.20 0.312 Strain ignoring variety 2 194.15 97.07 2.84 0.067 Strain eliminating variety 2 204.60 102.30 2.99 0.058 variety.Strain 18 609.21 33.84 0.99 0.485 Residual 58 1984.81 34.22 Total 87 3158.10 36.30
Analysis of variance for head index at BUSE
Variate: headindex
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 0.812826 0.090314 14.78 <.001 Strain 2 0.135071 0.067535 11.05 <.001 variety.Strain 18 0.141500 0.007861 1.29 0.229 Residual 60 0.366666 0.006111 Total 89 1.456063
Analysis of variance for plant height at 6 wace at Buse
Source d.f. s.s. m.s. v.r. F pr. variety ignoring Strain 9 1874.00 208.22 6.99 < 0.001 variety eliminating Strain 9 1907.52 211.95 7.11 < 0.001 Strain ignoring variety 2 112.02 56.01 1.88 0.162 Strain eliminating variety 2 145.54 72.77 2.44 0.096 variety.Strain 18 512.05 28.45 0.95 0.522 Residual 56 1669.17 29.81 Total 85 4200.76 49.42
Analysis of variance for leaf index at BUSE
Variate: lifindex
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 0.0361770 0.0040197 8.15 <.001 Strain 2 0.0026811 0.0013405 2.72 0.074 variety.Strain 18 0.0109778 0.0006099 1.24 0.264 Residual 60 0.0296068 0.0004934 Total 89 0.0794427
204
Analysis of variance
Variate: tiller_num
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 71.833 7.981 6.41 <.001 Strain 2 10.422 5.211 4.19 0.020 variety.Strain 18 15.800 0.878 0.71 0.792 Residual 60 74.667 1.244 Total 89 172.722
Analysis of variance
Variate: HEAD_WEI_g
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. VARIETY 9 8979.0 997.7 9.65 <.001 STRI_STR 2 1055.4 527.7 5.10 0.009 VARIETY.STRI_STR 18 2633.8 146.3 1.41 0.161 Residual 56 (4) 5791.6 103.4 Total 85 (4) 18103.9
Analysis of variance
Variate: LEAF_WEI_g
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. VARIETY 9 523.919 58.213 7.09 <.001 STRI_STR 2 1.806 0.903 0.11 0.896 VARIETY.STRI_STR 18 218.240 12.124 1.48 0.134 Residual 56 (4) 459.493 8.205 Total 85 (4) 1184.259
Analysis of variance
Variate: STEM_WEI_g
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr. VARIETY 9 3432.8 381.4 2.78 0.009 STRI_STR 2 411.5 205.7 1.50 0.231 VARIETY.STRI_STR 18 3839.5 213.3 1.56 0.103 Residual 59 (1) 8086.3 137.1 Total 88 (1) 15765.2
Analysis of variance
Variate: Head_index
Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 0.404695 0.044966 18.37 <.001 STRI_STR 2 0.036723 0.018362 7.50 0.001
205
VARIETY.STRI_STR 18 0.062302 0.003461 1.41 0.159 Residual 60 0.146895 0.002448 Total 89 0.650616
Analysis of variance
Variate: Head_weight_g
Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 6677.58 741.95 16.79 <.001 STRI_STR 2 1329.86 664.93 15.05 <.001 VARIETY.STRI_STR 18 1631.83 90.66 2.05 0.020 Residual 60 2651.25 44.19 Total 89 12290.51
Analysis of variance for leaf index for the Henderson experiment
Variate: Leaf_index
Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 0.0332699 0.0036967 10.10 <.001 STRI_STR 2 0.0092419 0.0046209 12.63 <.001 VARIETY.STRI_STR 18 0.0128970 0.0007165 1.96 0.027 Residual 60 0.0219552 0.0003659 Total 89 0.0773640
Analysis of variance
Variate: Leaf_weight_g
Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 1444.88 160.54 12.59 <.001 STRI_STR 2 23.77 11.89 0.93 0.399 VARIETY.STRI_STR 18 530.42 29.47 2.31 0.008 Residual 60 764.80 12.75 Total 89 2763.87
Analysis of variance for Root index at henderson
Variate: Root_Index
Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 0.92416 0.10268 9.22 <.001 STRI_STR 2 0.40930 0.20465 18.37 <.001 VARIETY.STRI_STR 18 0.24271 0.01348 1.21 0.283 Residual 60 0.66855 0.01114 Total 89 2.24472
Analysis of variance
Variate: Root_weight
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Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 36290.6 4032.3 5.56 <.001 STRI_STR 2 16331.9 8165.9 11.26 <.001 VARIETY.STRI_STR 18 17350.5 963.9 1.33 0.204 Residual 60 43531.7 725.5 Total 89 113504.6
Analysis of variance for stem index for the Henderson experiment.
Variate: Stem_index
Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 0.63802 0.07089 5.52 <.001 STRI_STR 2 0.23920 0.11960 9.32 <.001 VARIETY.STRI_STR 18 0.30578 0.01699 1.32 0.206 Residual 60 0.77000 0.01283 Total 89 1.95300
Analysis of variance
Variate: Stem_weight_g
Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 48626. 5403. 5.34 <.001 STRI_STR 2 8114. 4057. 4.01 0.023 VARIETY.STRI_STR 18 28040. 1558. 1.54 0.108 Residual 60 60677. 1011. Total 89 145458.
Analysis of variance for total dry weight at henderson
Variate: Total_Dry
Source of variation d.f. s.s. m.s. v.r. F pr. VARIETY 9 86549. 9617. 4.70 <.001 STRI_STR 2 10423. 5211. 2.54 0.087 VARIETY.STRI_STR 18 68784. 3821. 1.87 0.037 Residual 60 122889. 2048. Total 89 288645.
Analysis of variance for chlorophyll content at 8 WACE at Henderson
Variate: chloro_1
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 1112.223 123.580 12.41 <.001 Strain 2 532.241 266.120 26.71 <.001 variety.Strain 18 712.641 39.591 3.97 <.001 Residual 60 597.693 9.962
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Total 89 2954.798
Analysis of variance FOR CHLOROPHYLL CONTENT AT buse AT 10 WACE
Variate: chloro_2
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 602.738 66.971 7.26 <.001 Strain 2 186.027 93.013 10.08 <.001 variety.Strain 18 454.389 25.244 2.74 0.002 Residual 60 553.773 9.230 Total 89 1796.927
Analysis of variance
Variate: chloro_3
Source of variation d.f. s.s. m.s. v.r. F pr. variety 9 917.362 101.929 12.11 <.001 Strain 2 171.811 85.905 10.21 <.001 variety.Strain 18 412.843 22.936 2.73 0.002 Residual 60 504.973 8.416 Total 89 2006.989
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Appendix 6: ANOVA tables for Chapter 6
Analysis of variance for tiller number for quantification trial
Variate: Tiller
Source of variation d.f. s.s. m.s. v.r. F pr. treatment 7 24.0000 3.4286 4.70 0.002 Residual 24 17.5000 0.7292 Total 31 41.5000
Analysis of variance for maximum germination distance
Variate: germ_dist
Source of variation d.f. s.s. m.s. v.r. F pr. treatment 7 7.40219 1.05746 14.16 <.001 Residual 24 1.79250 0.07469 Total 31 9.19469
Analysis of variance for Striga counts in the quantification experiments
Variate: stri_counts
Source of variation d.f. s.s. m.s. v.r. F pr. treatment 7 492.969 70.424 19.26 <.001 Residual 24 87.750 3.656 Total 31 580.719
Correlations
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germ distance tiller striga counts
Correlation Coefficient 1.000 -.191 .564**
germ distance Sig. (2-tailed) . .172 .000
N 32 32 32
Correlation Coefficient -.191 1.000 .090
Kendall's tau_b tiller Sig. (2-tailed) .172 . .518
N 32 32 32
Correlation Coefficient .564** .090 1.000
striga counts Sig. (2-tailed) .000 .518 .
N 32 32 32
Correlation Coefficient 1.000 -.258 .741**
germ distance Sig. (2-tailed) . .154 .000
N 32 32 32
Correlation Coefficient -.258 1.000 .062
Spearman's rho tiller Sig. (2-tailed) .154 . .735
N 32 32 32
Correlation Coefficient .741** .062 1.000
striga counts Sig. (2-tailed) .000 .735 .
N 32 32 32
**. Correlation is significant at the 0.01 level (2-tailed).
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