Tag: farm management
An Introduction to the Climate-Smart Agriculture Papers
Over the last decade, international concerns about climate change have stimulated broad investment in the pursuit of agriculture that is more climate-smart. These concerns are particularly pressing in Africa, where most farmers remain severely impoverished and dependent on rain-fed production systems. This volume collates some of the latest research from agricultural scientists working to speed up the development and adoption of more climate-smart farming systems in eastern and southern Africa. These 25 papers highlight ongoing efforts to better characterise climate risks, develop and disseminate climate-smart varieties and farm management practices, and integrate these technologies into well-functioning value chains. The papers emphasise the additional research efforts needed to improve the understanding and response to climate risk. The expert authors also make suggestions for strengthening the responsiveness of agricultural research and extension systems to future climate changes.
Land tenure and farm management efficiency: The case of smallholder rubber production in customary land areas of Sumatra
This study assesses the impact of land tenure institutions on the efficiency of farm management based on a case study of rubber production in customary land areas of Sumatra, Indonesia. Using the modes of land acquisition as measures of land tenure institutions, we estimated tree planting, revenue, income, and short-run profit functions, and internal rates of return to tree planting on smallholder rubber fields. We find generally insignificant differences in the incidence of tree planting and management efficiency (defined as residual profits) of rubber production between newly emerging private ownership and customary ownership. This is consistent with our hypothesis that tree planting confers stronger individual rights, if land rights are initially weak (as in the case of family land under customary land tenure systems). On the other hand, short-term profits are higher on land that is rented through share tenancy. This result indicates that rubber trees are over-exploited under renting arrangements due partly to the short-run nature of the land tenancy contracts and partly to the difficulty landowners face in supervising tapping activities of tenants in spatially dispersed rubber fields.
Tree establishment and management on farms in the drylands: Evaluation of different systems adopted by small-scale farmers in Mutomo District, Kenya
Agroforestry systems in Sub-Saharan African drylands are complex and heterogeneous in nature even under similar biophysical conditions. This can be attributed to household needs and socioeconomic status which influence the species and utility of the adopted trees. This has an impact on the trees establishment and management system through planting or Farmer Managed Natural Regeneration (FMNR). This study evaluates how trees for different utilities are managed and which socioeconomic factors influence these decisions. The study used primary data collected in Mutomo District, Kenya through a household survey based on a structured questionnaire. A paired sample t-test was done to assess the preferred mode of adopting trees for different utilities while factor analysis was used to characterize the households as either planting trees or practicing FMNR. Multiple linear regression using household regression factor scores as independent variables and socioeconomic indicators as dependent variables was done to ascertain which socioeconomic factors affect tree adoption. The results show that trees planted were mostly exotic species valued for their nutrition and commercial value, while FMNR was used for subsistence products and environmental services. Household size, livestock levels and mobility had a positive correlation with tree planting, while income, access to markets and roads had an inverse correlation. Access to natural woodland, distance to the nearest motorable road and land size had a positive correlation with tree protection. It is hoped that this knowledge will act as a reference point when designing agroforestry projects in similar areas to ensure they are more aligned to specific site and household conditions.
Exploring optimal farm resources management strategy for Quncho-teff (Eragrostis tef (Zucc.) Trotter) using AquaCrop model
Teff is a major staple food crop in Ethiopia. Moisture and soil fertility are the two major factors limiting teff yield. Studies were conducted across three sites in Ethiopa [Mekelle (MK) in 2012 and 2016, Ilala (IL) in 2012 and Debrezeit (DZ) in 2009 and 2010]. The objectives of these studies were (1) to assess the response of Quncho-teff to different fertilizer and irrigation levels; 2) to quantify irrigation water productivity (IWP), and (3) to collect data to calibrate and validate AquaCrop model for simulating yield and evaluate optimal irrigation and sowing date strategy for Quncho-teff at different locations in Ethiopia. The different fertilizer levels were: 1) 64 kg N and 46 kg P/ha (N2P2); 2); 32 kg N and 23 kg P/ha (N1P1); 3) 0 kg N and 0 kg P/ha (N0P0) and 4) 52 kg N and 46 kg P/ha (N3P3). The four irrigation treatments were: zero (rainfed), two, four and full irrigation applications. Findings showed that full irrigation in combination with high fertilizer (N2P2) could give better yield. However, during abnormal rainfall, spreading the available fertilizer at a rate of 32 kg N and 23 kg P/ha may be preferable to applying 64 kg N and 46 kg P/ha. This study also indicated that the regional fertilizer recommendations for teff need to be revised taking in to account the soil characteristics, climate and irrigation water availability. The AquaCrop model was able to simulate the observed canopy cover, soil water, biomass and yield of teff satisfactorily. Canopy cover was simulated with normalized root mean square error (NRMSE), index of agreement (I) and R2 of 7%, 0.5 and 0.8, respectively. Soil moisture during the season was simulated with NRMSE of 11.4–15.7%, I of 0.99 and R2 of 0.85–0.9. Simulated final aboveground biomass values were in close agreement with the measured (NRMSE, 7.8%, I, 0.89 and R2, 0.66). There was also good agreement between simulated and measured grain yield with NRMSE, I and R2 values of 10.9%, 0.93, 0.80, respectively. Scenario analysis indicated that early sowing was the best option to maximize teff yield with the least amount of irrigation. Scenario analysis also showed that one irrigation during flowering stage could substantially improve irrigation water productivity (IWP) of teff and minimize the yield loses which could occur due to shifting of sowing date from early to normal. Two irrigation applications also substantially improved the yield and IWP of late sown teff. However, to get high yield, a late sown teff should receive at least four irrigation applications during the mid-growth stage of the crop. These results suggest that AquaCrop model can be used to identify optimal farm resource management strategies for teff production. © 2016
Agricultural economics and marketing in the tropics
Abstract not found
Policymaker perceptions of COVID-19 impacts, opportunities and challenges for sustainable wildlife farm management in Vietnam
This paper uses Vietnam – where overexploitation of wildlife resources is a major threat to biodiversity conservation – as a case study to examine how government officials perceive the impacts of COVID-19 on wildlife farming, as well as the opportunities and challenges presented for sustainable wildlife management. Findings show Vietnamese government officials perceive COVID-19 to have had mixed impacts on wildlife conservation policies and practice. While the pandemic strengthened the legal framework on wildlife conservation, implementation and outcomes have been poor, as existing policies are unclear, contradictory, and poorly enforced. Our paper also shows policymakers in Vietnam are not in favor of banning wildlife trade. As our paper documents the immediate impacts of the pandemic on wildlife farming, more research is necessary to analyse longer-term impacts.