School of Agriculture, Veterinary Science and Technology

EPIDEMIOLOGY AND CHARACTERISATION OF Groundnut Ringspot Virus (GRSV) INFECTING GROUNDNUTS AND OTHER PLANTS IN WESTERN KENYA

Sun, 01 Jan 2023 00:00:00 GMT

EPIDEMIOLOGY AND CHARACTERISATION OF Groundnut Ringspot Virus (GRSV) INFECTING GROUNDNUTS AND OTHER PLANTS IN WESTERN KENYA Murere, Lubao Wanyonyi Groundnut (Arachis hypogaea L.) is an annual oilseed legume crop grown by small holder farmers in Kenya for its economic and nutritive value. However, its yield has declined upto 680 kg ha-1 than its genetic potential of 1690 kg ha-1 attributed to abiotic and biotic stressors. Viruses are among biotic stressors for yield reduction globally. These include; Groundnut ringspot virus (GRSV), Tomato spotted wilt virus (TSWV), among others. GRSV was reported in South Africa, Ghana, Brazil and USA infecting groundnuts, soybeans and others. GRSV and TSWV have similar biological symptoms but differentiated using serological tests. Typical Symptoms for GRSV appears on groundnuts and other plants in western Kenya but no report had been documented on the occurrence of the virus nor its management strategies Kenya. The general objective of this study was to determine the occurrence, distribution and characterisation of GRSV on groundnuts and other host plants in western Kenya. Survey on prevalence of GRSV, was conducted in short and long rain seasons of the years 2019 and 2020 in western Kenya. Simple random sampling (SRS) used in selecting farms visited in groundnut growing regions and disease incidence/ severity recorded and data collected analyzed using post-hoc analysisANOVA. Serological analysis was done on samples collected using polyclonal and monoclonal antisera against GRSV and TSWV respectively. Field trials on the effect of intercropping other legumes with groundnuts on GRSV incidences were laid on a randomized complete block design (RCBD) and replicated three times. Viral incidence and severity recorded and symptomatic leaf samples collected for GRSV ELISA tests. Health tested seeds to GRSV of groundnut varieties and other plant species were planted in plastic pots of a mixture of sterilized loam, sand and organic manure at a ratio of 2:1:1 respectively in greenhouse to screen for their response and host range to GRSV and inoculated with GRSV inoculum. Plants symptomatic development observed at an interval of 5 days for 8 weeks and plant samples for each variety/species collected for GRSV ELISA Tests. Total RNA of Kenyan plant isolates extracted using CTAB and purified by DCC™-5 purification kit then amplified using target primers GRSVnR (5’-GCGGTCTACAGTGTTGCACTT3’)andGRSVnF(5’TCTTGTGCATCATCCATTGT-3’) using Rt-PCR at 614-bp fragment of the nucleocapsid gene of GRSV corresponding to the part of the nucleocapsid (N) gene. The RT-PCR product taken for Sanger sequencing. Sequence readings trimmed using Bio-edit software and phylogenetic analysis done in MEGA-X. New primers from GRSV sequences of western Kenya was designed using primer3plus software, synthesized and validated using PCR tests. GRSV occurs in surveyed regions with variant incidence; Chwele having the highest incidence (45.04 %) while Kapkateny having the lowest incidence (17.75 %) with significant difference of (P < 0.05). Groundnuts planted in pure stand had lowest disease incidence (4%) while intercropped groundnuts had the highest (28%). Screened groundnuts showed Homabay variety being more susceptible with incidence of 31 %, followed by ICGV-9991 with incidence of 28 %. SM99568 variety was tolerant to the virus. Varieties ICGV-90704, ICGV-99048 and ICGV-99019 were resistant to the virus.Screened plants; Pigeon peas, Bambara nut, peas, Chenopodium album, Galinsoga parviflora among others, revealed being as host range for the virus. Kenyan GRSV isolates clustered with USA, Ghanaian and South African isolates in GenBank. One of developed primers formed clear bands in a PCR tests with positive samples of western Kenya. GRSV occurs in surveyed counties of western Kenya, which should be a big concern to all stakeholders. Introgression of resistant genes into local groundnuts to gain resistance to the virus with urgency. Farmers should avoid intercropping groundnuts with alternative hosts to reduce transmission of the virus.

PERCEPTIONS OF SUGAR SUBSECTOR ACTORS ON THE IMPACT OF POLICY ISSUES ON REVIVAL OF SUGARCANE FARMIN IN THE WESTERN KENYA SUGARBEL

Wed, 01 Nov 2023 00:00:00 GMT

PERCEPTIONS OF SUGAR SUBSECTOR ACTORS ON THE IMPACT OF POLICY ISSUES ON REVIVAL OF SUGARCANE FARMIN IN THE WESTERN KENYA SUGARBEL KOMBO, JOSEPHAT BARASA

OCCURRENCE OF GROUNDNUT ROSETTE DISEASE AND DIVERSITY OF ITS CAUSAL AGENTS IN WESTERN KENYA

Mon, 01 Jan 2018 00:00:00 GMT

OCCURRENCE OF GROUNDNUT ROSETTE DISEASE AND DIVERSITY OF ITS CAUSAL AGENTS IN WESTERN KENYA Mukoye, Benard Groundnut (Arachis hypogaea L.) is an economically important edible oilseed legume in Sub-Saharan Africa (SSA). Nearly 75% to 80% of the world’s groundnut is grown by resource poor smallholder farmers in developing countries, who routinely obtain yields of 500-800kg/ha, as opposed to the potential yield of >2.5t/ha. Groundnut rosette disease (GRD) is a major constraint in SSA, which can cause 100% yield losses in a devastating severe epidemic situation, to the extent of abandoning the fields. The disease is caused by two synergistic viruses; groundnut rosette assistor virus (GRAV, genus Luteovirus) and groundnut rosette virus (GRV, genus Umbravirus) associated with a satellite-ribonucleic acid (Sat-RNA). The complex etiology and lack of sensitive and specific diagnostic tools, are major limitations in understanding the epidemiology of GRD viruses, and developing appropriate management strategies for the disease. Simultaneous detection of the GRD causal agents is possible by multiplex RT-PCR but this depends on the availability of specific primers to known agents that occur in a specific area. This information is limited for GRD causal agents in western Kenya. This requires a robust detection method which can single out all the GRD agents and their variants. To date, lack of sufficient research on the occurrence, distribution and diversity of GRD causal agents has resulted in continued and increased yield losses amongst groundnut farmers. Recent observations made in groundnut farms in western Kenya have shown that GRD is very severe and highly variable in symptoms appearance. The causes of this is not well documented. This study will determine the occurrence of GRD and characterize GRD causal agents in western Kenya. Disease diagnostic surveys will be conducted in six counties; Bungoma, Busia, Homabay, Kakamega, Siaya and Vihiga. Disease incidence and severity will be scored on the disease score sheet. Symptomatic and asymptomatic groundnut leafy samples will be collected and preserved for laboratory analysis. Total RNA will be extracted by RNeasy Mini Kit (Qiagen), and sequenced using next generation sequencing technologies (NGS). Biological characterization of GRD will be done through mechanical inoculation on leguminous hosts and further vector and seed transmission studied. The data collected on incidence and severity will be subjected to analysis of variance (ANOVA), using Statistical Analysis Software (SAS) program (SAS Institute lnc.). Pairwise comparison of means will be done using Least Significance Difference (LSD) at P 0.05 confidence level. Sequence reads will be analyzed using an in-house, customized version of the Galaxy project bioinformatics pipeline. The reads will be mapped to a custom database of plant virus sequences using Bowtie2 2.2.3+, and further analysis done to establish diversity and other molecular characteristics. This research will provide comprehensive knowledge of GRD viruses, rosette symptoms, better crop protection technologies and acceptable agronomic farming practices, for considerable increased groundnut production. Doctor of Philosophy in Crop Protection

APPLICATION OF SOCIAL NETWORK ANALYSIS TOOL TO INFORMATION FLOW AND ITS INFLUENCE ON THE ADOPTION OF SUSTAINABLE AGRICULTURAL INNOVATIONS IN BUSIA COUNTY, KENYA

Mon, 01 Oct 2018 00:00:00 GMT

APPLICATION OF SOCIAL NETWORK ANALYSIS TOOL TO INFORMATION FLOW AND ITS INFLUENCE ON THE ADOPTION OF SUSTAINABLE AGRICULTURAL INNOVATIONS IN BUSIA COUNTY, KENYA MBAKAHYA, GEORGE MICHAELS The growth of Agricultural productivity in Western Kenya has lagged behind largely due to low adoption of agricultural innovations. The low adoption is attributed to deficiencies in the existing agricultural extension system. The system for a long time has embraced the linear top-down model of information generation and dissemination. In this model, farmers are regarded as spectators of the innovation development process yet; a lot of information is shared through interpersonal channels within social networks. To help address the issue, Social Network Analysis (SNA) was used to map, measure and analyze social relationships among farmers, agricultural extension service providers and researchers who act as channels for the transfer of information. The study was conducted in 4 villages randomly selected in Nambale Sub-county namely; Elwanikha, Ibanda, Budokomi and Ekisumo. The specific objectives of the study were; to determine flow of agricultural information among the farmers through their social networks, to document relational and structural factors that influence flow of agricultural information within the social networks, to describe the formal and informal communication and their influence on adoption of agricultural innovations and to provide recommendations how extension service providers can make use of social networks to increase the of adoption of agricultural innovations. The study adopted ethnographic research design which comprised of social mapping and in-depth interviews. Initial respondents in each village were purposively identified followed by snowballing to generate subsequent respondents. Data was collected using sociometric technique, semi-structures interviews and in-depth interviews to investigate flow of agricultural information and adoption of three selected agricultural innovations within social networks; 1.) Use of Desmodium (Desmodium uncinatum) to smoother Striga (Striga hermonthica) 2.) Use of lime to control soil acidity 3.) Use of hermetic bags in post-harvest storage of maize. Socio-metric analysis was done using UCINET VI version 6.624. Net draw version 2. 160 an interphase program was used to create illustrative maps. The socio-metric analysis of the villages produced 716 nodes (actors) with 1,952 ties (relationships). The socio-grams showed a mixture of weak and strong and weak ties with a minimum and maximum clustering co-efficient of 0.214 and 0.612 respectively. The study established that the social networks of Nambale Sub-county are characterized by both weak and strong ties which are traits in network structure that are significant in sharing of information on sustainable agricultural innovations. However, agricultural extension workers have failed to take advantage of these existing social networks to disseminate agricultural information because the adoption of the selected innovations was low in all the three villages. By leveraging on the power of social networks, the extension service providers can use the method to map information networks which can be used to disseminate agricultural information that would stimulate adoption of innovations among farmers. Doctor of Philosophy in Sustainable Agricultural Systems