86 research outputs found

    Low permeability triple-layer plastic bags prevent losses of maize caused by insects in rural on-farm stores

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    Participatory on-farm trials were conducted to assess effectiveness of Purdue Improved Crop Storage (PICS™) bags for storage of maize in small-scale farmers’ stores in rural villages in eastern Kenya. A PICS bag is a three-layered hermetic bag-system that forms a barrier against the influx of oxygen and the escape of carbon dioxide. Jute, woven polypropylene or PICS bags were filled with shelled maize grain, purchased from the participating farmers, and the three sets of bags kept in the farmers’ own stores for 35 weeks. Oxygen and carbon dioxide levels in the PICS bags were monitored, as well as the temperature and relative humidity in all the bags. Grain moisture, live insect population, grain damage and weight loss were examined at intervals of seven weeks. Oxygen and carbon dioxide composition demonstrated that PICS bags are capable of sustaining good air-barrier properties under farmer storage conditions. Moreover, moisture content of maize stored in PICS bags did not change throughout the storage period whereas the moisture content of maize stored in polypropylene and jute bags decreased significantly in the final 14 weeks. Maize stored in PICS bags remained free from insect infestation and the weight loss due to insect damage was below 1 %. On the contrary, polypropylene and jute bags permitted profuse build-up of insect populations. At 35 weeks, grain damage reached 77.6 % and 82.3 % corresponding to 41.2 % and 48.5 % weight loss in the polypropylene and jute bags respectively. These findings demonstrate that PICS bags are effective in controlling losses caused by storage pests under farmer storage conditions

    Socio-Economic and Institutional Constraints to Accessing Credit among Smallholder Farmers in Nyandarua District, Kenya

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    Amongst the challenges faced by smallholder farmers in production is inaccessibility to credit. This study sought to identify household socio-economic and institutional constraints influencing access to credit among smallholder farmers in Nyandarua District. The study used a Logit model. Both quantitative and qualitative data were acquired from primary and secondary sources. Primary data was collected using questionnaires through a survey design. A sample of 164 smallholder farmers was selected using stratified, multi-stage random sampling techniques. Data was analyzed using descriptive statistics and maximum likelihood method using Statistical Package for Social Sciences (SPSS). The study established that socio-economic constraints such as age, gender, household size, farm income, collateral and awareness are critical determinants of access to credit. The study also established that institutional requirements such as costs involved in operating / maintaining bank accounts, loan requirements and transaction costs involved in the credit process influenced access to credit. The study concludes that household socio-economic characteristics and institutional requirements influence access to credit. Key recommendations made include the need by government to deal with bureaucracies involved in land registration to benefit majority of smallholder farmers who remain insecure in the land they use without proof of ownership and also to make easier the registration of lease certificates for those who do not own land and use land on leasehold tenure system. Financial institutions should also put in place less stringent credit requirements and reduce credit costs especially interest rates to make credit more affordable. Keywords: socio-economic and institutional constraints, credit access, smallholder farmers, logit model

    Analysis of Farmers’ Perceptions of the Effects of Climate Change in Kenya: the Case of Kyuso District

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    A cross-sectional analysis was carried out to evaluate how farmers in Kyuso District have perceived climate change. Data was collected from 246 farmers from six locations sampled out through a multistage and simple random sampling procedure. The logistic regression analysis was carried out to assess factors influencing farmers’ perceptions of climate change. The analysis revealed that 94% of farmers in Kyuso District had a perception that climate was changing.  In this regard, age of the household head, gender, education, farming experience, household size, distance to the nearest input/output market, access to irrigation water, local agro-ecology, access to information on climate change, access to extension services, off farm income and change in temperature and precipitation were found to have significant influence on the probability of farmers to perceive climate change. Since the level of perception to climate change revealed by the study was found to be high (94%), the study suggests that more policy efforts should thus be geared towards helping farmers to adapt to climate change. Key words: Climate change, Perceptions, Logistic regression, Kyuso District

    Assessment of Farmers’ Adaptation to the Effects of Climate Change in Kenya: the Case of Kyuso District

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    The study was carried out to assess how farmers in Kyuso District have adapted to the effects of climate change. Survey data was collected from 246 farmers from six locations that were sampled out through a multistage and simple random sampling procedure. The probit regression model was fitted into the data in order to assess factors influencing farmers’ adaptation to the effects of climate change. The analysis revealed that 85% of the farmers had adapted in various ways to the effects of climate change. In this regard, the age of the farmer, gender, education, farming experience, farm income, access to climate information, household size, local agro-ecology, distance to input/output market, access to credit, access to water for irrigation, precipitation and temperature were found to have significant influence on the probability of farmers to adapt to climate change. The study suggests that more policy efforts should thus be geared towards helping all the farmers in the district to adapt to climate change. Key words: climate change, adaptation, probit regression model, Kyuso District

    Enhancing Soil Carbon in East Africa: The biophysical evidence, socio-economic incentives, and policy implications

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    This report provides a summary/sythesis of key research outputs and messages gathered from the four year BMZ-funded project on "Scaling up soil carbon enhancement interventions for food security and climate across complex landscapes in Kenya and Ethiopia.

    Understanding the potential impact of different drug properties on SARS-CoV-2 transmission and disease burden : a modelling analysis

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    Q1Q1Background The unprecedented public health impact of the COVID-19 pandemic has motivated a rapid search for potential therapeutics, with some key successes. However, the potential impact of different treatments, and consequently research and procurement priorities, have not been clear. Methods and Findings develop a mathematical model of SARS-CoV-2 transmission, COVID-19 disease and clinical care to explore the potential public-health impact of a range of different potential therapeutics, under a range of different scenarios varying: i) healthcare capacity, ii) epidemic trajectories; and iii) drug efficacy in the absence of supportive care. In each case, the outcome of interest was the number of COVID-19 deaths averted in scenarios with the therapeutic compared to scenarios without. We find the impact of drugs like dexamethasone (which are delivered to the most critically-ill in hospital and whose therapeutic benefit is expected to depend on the availability of supportive care such as oxygen and mechanical ventilation) is likely to be limited in settings where healthcare capacity is lowest or where uncontrolled epidemics result in hospitals being overwhelmed. As such, it may avert 22% of deaths in highincome countries but only 8% in low-income countries (assuming R=1.35). Therapeutics for different patient populations (those not in hospital, early in the course of infection) and types of benefit (reducing disease severity or infectiousness, preventing hospitalisation) could have much greater benefits, particularly in resource-poor settings facing large epidemics. Conclusions There is a global asymmetry in who is likely to benefit from advances in the treatment of COVID-19 to date, which have been focussed on hospitalised-patients and predicated on an assumption of adequate access to supportive care. Therapeutics that can feasibly be delivered to those earlier in the course of infection that reduce the need for healthcare or reduce infectiousness could have significant impact, and research into their efficacy and means of delivery should be a priorityRevista Internacional - Indexad

    Revealing the extent of the first wave of the COVID-19 pandemic in Kenya based on serological and PCR-test data.

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    Policymakers in Africa need robust estimates of the current and future spread of SARS-CoV-2. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya up to the end of September 2020, which encompasses the first wave of SARS-CoV-2 transmission in the country. We estimate that the first wave of the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 30-50% of residents infected. Our analysis suggests, first, that the reported low COVID-19 disease burden in Kenya cannot be explained solely by limited spread of the virus, and second, that a 30-50% attack rate was not sufficient to avoid a further wave of transmission

    Revealing the extent of the first wave of the COVID-19 pandemic in Kenya based on serological and PCR-test data

    Get PDF
    Policymakers in Africa need robust estimates of the current and future spread of SARS-CoV-2. We used national surveillance PCR test, serological survey and mobility data to develop and fit a county-specific transmission model for Kenya up to the end of September 2020, which encompasses the first wave of SARS-CoV-2 transmission in the country. We estimate that the first wave of the SARS-CoV-2 pandemic peaked before the end of July 2020 in the major urban counties, with 30-50% of residents infected. Our analysis suggests, first, that the reported low COVID-19 disease burden in Kenya cannot be explained solely by limited spread of the virus, and second, that a 30-50% attack rate was not sufficient to avoid a further wave of transmission.</ns4:p

    Population structure and evolutionary history of the greater cane rat (Thryonomys swinderianus) from the Guinean Forests of West Africa

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    Grasscutter (Thryonomys swinderianus) is a large-body old world rodent found in sub-Saharan Africa. The body size and the unique taste of the meat of this major crop pest have made it a target of intense hunting and a potential consideration as a micro-livestock. However, there is insufficient knowledge on the genetic diversity of its populations across African Guinean forests. Herein, we investigated the genetic diversity, population structures and evolutionary history of seven Nigerian wild grasscutter populations together with individuals from Cameroon, Republic of Benin, and Ghana, using five mitochondrial fragments, including D-loop and cytochrome b (CYTB). D-loop haplotype diversity ranged from 0.571 (± 0.149) in Republic of Benin to 0.921 (± 0.013) in Ghana. Within Nigeria, the haplotype diversity ranged from 0.659 (± 0.059) in Cross River to 0.837 (± 0.075) in Ondo subpopulation. The fixation index (FST), haplotype frequency distribution and analysis of molecular variance revealed varying levels of population structures across populations. No significant signature of population contraction was detected in the grasscutter populations. Evolutionary analyses of CYTB suggests that South African population might have diverged from other populations about 6.1 (2.6–10.18, 95% CI) MYA. Taken together, this study reveals the population status and evolutionary history of grasscutter populations in the region
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