Determinants of Stevia (stevia rebaudiana) Adoption by Small Scale Farmers in Kericho District, Kenya

The aim of this study was to determine the socio-economic and institutional factors influencing Stevia adoption in Kericho District Kenya. A structured questionnaire was used to collect data from farmers both adopters and non adopters of Stevia through face to face interviews where purposive sampling methods were employed respectively and 150 respondents were contacted in total. Heckman two-step regression analysis was used to determine factors affecting Stevia adoption as well as the extent of adoption. The results showed that group membership, gender, education extension services and individual land ownership significantly and positively affected the adoption of Stevia while age was significant with negative effect.  Household size, farm size, revenue from Stevia and access to extension services significantly and positively influenced the extent of adoption. In conclusion, there is need for more effort in terms of extension service so as to encourage farmers to adopt improved crop varieties through demonstrations on farmers' fields, field days, farm visits and agricultural shows and also development of institutional strategies to support farmers. Therefore policy interventions is recommended to enhance access to credit, reduce illiteracy levels among farmers through training and extension services. Keywords: Stevia, adoption, socioeconomic factor

Factors Influencing Commercialization of Horticultural Crops Among Smallholder Farmers in Juba, South Sudan

This paper aims at analyzing socio-economic and institutional factors influencing the commercialization of horticultural crops among smallholder farm households in Juba, South Sudan. The study adopted a multi-stage sampling technique to select a sample of 151 respondents. The survey was conducted using semi-structured questionnaires to collect primary data. The data collected were analyzed using descriptive statistics and a Tobit regression model by STATA analytical software. The results from descriptive statistics indicated that 77.48% of the farmers are female, 36.65% have access to land, 37.09% have access to education at the primary level, 96.69% have no access to market information, 74.17% do not have group membership and only 54.97% have access to irrigation facilities. The findings further revealed that the mean household commercialization index (HCI) was 74.81% and the specific HCI for the selected vegetable crops; tomato, okra and cowpeas were 74.92%, 72.96%, and 74.84% respectively. The results from the Tobit regression model revealed that commercialization of horticultural crops is influenced by the age of the farmer, farming experience, type of land acquisition, the quantity of crop produced, group membership, total variable costs, total farm revenue, and access to irrigation facilities. The finding revealed that the age of a farmer, types of crop produced, type of land acquisition, and group membership are negatively significant whereas, farming experience, total variable costs, total farm revenue, and access to irrigation facilities are positively significant. The study suggests that further evaluation of the factors influencing the commercialization of indigenous and exotic vegetables would be required in rural and peri-urban settings of South Sudan. This study provides an insight for policymakers to formulate appropriate policies that can promote domestic production and accelerate the transition of smallholder farmers from subsistence to the market-oriented production system. Keywords: Commercialization, Horticultural crops, Peri-urban areas, smallholder, Tobit regression model DOI: 10.7176/JESD/12-14-05 Publication date:July 31st 202

Land Use Change and Determinants of Agricultural Land Conversion Due to Urbanization: Case of Smallholder Farmers in Njoro Sub-County, Kenya

Urbanization process stands out amongst the most imperative drivers of financial, physical and societal change. However, the drivers of agricultural land conversion due to urbanization in Africa specifically, Njoro Sub-County in Kenya are still not clear. This paper looks at the factors impacting decision to convert land used for agricultural purposes and the degree of conversion to non-agricultural purposes. Data for this study was collected from 384 randomly selected smallholder farmers, by the use of semi-structured questionnaires and key witness interviews. The study employed Craggit (Double-Hurdle Model) to examine the drivers of conversion and analyze the amount of land converted. The results from the study show that decision to convert and extent of land conversion were influenced by; age, gender, education, productive farm assets, distance to town, tenure system, risk attitude, soil fertility and land rented out. The study concluded that despite the threat urbanization has on food security, much of peri-urban agricultural land is still being converted to non-agrarian purposes. This study recommends coherent policies that take into account farmer socio-economic and bio-physical characteristics that could stimulate behavioral change towards land conversion. This could be complemented by adopting strategies that align all shareholders from different segments of the economy, provide secure rights to land and incentivize solutions for sustainable agriculture by making agribusiness more competitive. Keywords: Drivers, urbanization, agricultural land conversion, smallholder, Craggit mode

Importance of Employee Welfare and Performance: The Case of the UASU at Egerton University, Kenya

Trade unions play a key role in enhancing employee welfare and performance in organizations. In Kenya, the Universities’ Academic Staff Union (UASU) is a trade union for academic staff in all the public universities, with a Chapter in every university and whose objects include ensuring better welfare for its members. Through a cross-sectional survey, this study examined the contribution of the UASU to employee welfare and the extent of its effects on employee performance. The study was undertaken at UASU Egerton University Chapter, Njoro, Kenya. A representative group of 82 respondents was obtained by simple random sampling from a sample frame of the 435 general members of the UASU. The respondents provided information regarding the contribution of the activities of the UASU to employee welfare and their influence on employee performance. Results indicated that the UASU had different but positive impacts on the variables affecting employee welfare and, consequently, employee performance. In descending order of importance, maternity, pension, housing and medical schemes were some of the benefits from the activities of the UASU. However, availability of recreational facilities received least attention from the UASU. The UASU should, therefore, be maintained and strengthened to further improve on quality delivery of products and services in the University by its members. Keywords: Employee welfare; Employee performance; UASU; Egerton University, Keny

Determinants of Tea Marketing Channel Choice and Sales Intensity among Smallholder Farmers in Kericho District, Kenya

The aim of this study was to determine the socio-economic and institutional factors influencing smallholder farmers’ choice on tea marketing channel in Kericho District. A semi-structured and pre-tested questionnaire was used to collect data from smallholder tea farmers through face to face interview. Multistage sampling procedure was employed to contact 155 respondents. The study used Heckman two stage model to identify factors that determine tea growers’ choice of marketing channel and sales volume decisions once a marketing channel has been selected. The results showed that age, gender, education in years, farming years and second payments significantly affected the participation in marketing channel. Tea production, farming years, age and second payment significantly affected the intensity of participation.  The results of the study provide an insights to the policy makers on what needs to be done to promote and improve farmer-market linkages hence improve farmers’ incomes from their farming and marketing activities. Keywords: Tea, Marketing channel, socioeconomic factors

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Influence of Agripreneurial Orientation Constructs on Growth of Cassava-Based Small and Medium Enterprises in Migori County, Kenya

The study sought to analyse influence of agripreneurial orientation constructs on growth of cassava based small and medium enterprises in Migori County, Kenya. Data were collected using snow balling sampling method from 171 cassava agripreneurs. Data analysis was done using descriptive statistics and Probit model. The study revealed that the respondents were middle aged (43 years), majority were female (78.4%.), had reached formal education (52%), average age of enterprises was 10years and average quantity of cassava traded per week of 29 Kg, average number of workers employed of 2 persons while the average distance to the market being 3Km. The important and statistically significant variables that influence growth of cassava based small and medium enterprises include: Education level (p<0.05), number of Skilled employees (P<.01), owner experience (P<.1), number of trained employees (P<0.01), enterprise age (P<0.05), competitive aggressiveness (P<.01) and agripreneurial orientation (P<0.05) with Psedudo R2 value (.5946). According to these findings, the study recommends that the government should empower cassava based agripreneurs through training, trade fairs and capacity building to change the mind-set of the agripreneurs while providing incentives in venturing into cassava for the growth of the agrienterprises as well as individual growth. The government of Kenya can achieve these through its agricultural organizations with collaborations with Non-Governmental organizations and other stakeholders

Tropical Africa’s first testbed for high-impact weather forecasting and nowcasting

Testbeds have become integral to advancing the transfer of knowledge and capabilities from research to operational weather forecasting in many parts of the world. The first high-impact weather testbed in tropical Africa was recently carried out through the African SWIFT program, with participation from researchers and forecasters from Senegal, Ghana, Nigeria, Kenya, the United Kingdom, and international and pan-African organizations. The testbed aims were to trial new forecasting and nowcasting products with operational forecasters, to inform future research, and to act as a template for future testbeds in the tropics. The African SWIFT testbed integrated users and researchers throughout the process to facilitate development of impact-based forecasting methods and new research ideas driven both by operations and user input. The new products are primarily satellite-based nowcasting systems and ensemble forecasts at global and regional convection-permitting scales. Neither of these was used operationally in the participating African countries prior to the testbed. The testbed received constructive, positive feedback via intense user interaction including fishery, agriculture, aviation, and electricity sectors. After the testbed, a final set of recommended standard operating procedures for satellite-based nowcasting in tropical Africa have been produced. The testbed brought the attention of funding agencies and organizational directors to the immediate benefit of improved forecasts. Delivering the testbed strengthened the partnership between each country’s participating university and weather forecasting agency and internationally, which is key to ensuring the longevity of the testbed outcomes

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.Funding: the Tri-I Program in Computational Biology and Medicine (CBM) funded by NIH grant 1T32GM083937; GitHub; Philip Blood and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1548562 and NSF award number ACI-1445606; NASA (NNX14AH50G, NNX17AB26G), the NIH (R01AI151059, R25EB020393, R21AI129851, R35GM138152, U01DA053941); STARR Foundation (I13- 0052); LLS (MCL7001-18, LLS 9238-16, LLS-MCL7001-18); the NSF (1840275); the Bill and Melinda Gates Foundation (OPP1151054); the Alfred P. Sloan Foundation (G-2015-13964); Swiss National Science Foundation grant number 407540_167331; NIH award number UL1TR000457; the US Department of Energy Joint Genome Institute under contract number DE-AC02-05CH11231; the National Energy Research Scientific Computing Center, supported by the Office of Science of the US Department of Energy; Stockholm Health Authority grant SLL 20160933; the Institut Pasteur Korea; an NRF Korea grant (NRF-2014K1A4A7A01074645, 2017M3A9G6068246); the CONICYT Fondecyt Iniciación grants 11140666 and 11160905; Keio University Funds for Individual Research; funds from the Yamagata prefectural government and the city of Tsuruoka; JSPS KAKENHI grant number 20K10436; the bilateral AT-UA collaboration fund (WTZ:UA 02/2019; Ministry of Education and Science of Ukraine, UA:M/84-2019, M/126-2020); Kyiv Academic Univeristy; Ministry of Education and Science of Ukraine project numbers 0118U100290 and 0120U101734; Centro de Excelencia Severo Ochoa 2013–2017; the CERCA Programme / Generalitat de Catalunya; the CRG-Novartis-Africa mobility program 2016; research funds from National Cheng Kung University and the Ministry of Science and Technology; Taiwan (MOST grant number 106-2321-B-006-016); we thank all the volunteers who made sampling NYC possible, Minciencias (project no. 639677758300), CNPq (EDN - 309973/2015-5), the Open Research Fund of Key Laboratory of Advanced Theory and Application in Statistics and Data Science – MOE, ECNU, the Research Grants Council of Hong Kong through project 11215017, National Key RD Project of China (2018YFE0201603), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01) (L.S.