Sustainable development of crop-livestock farms in Africa

Crop-livestock farms across Africa are highly variable due to in agroecological and socioeconomic factors, the latter shaping the demand and supply of livestock products. Crop-livestock farms in Africa in the 20-first century are very different from most mixed farms elsewhere in the world. African crop-livestock farms are smaller in size, have fewer livestock, lower productivity and less dependency on imported feed than farms in most countries of Europe, the Americas and the intensive agricultural systems of Asia. This paper discusses the role African crop-livestock farms have in the broader socio-agricultural economy, and how these are likely to change adapting to pressures brought on by the intensification of food systems. This intensification implies increasing land productivity (more food per hectare), often leading to more livestock heads per farm, producing fertilized feeds in croplands and importing feed supplements from the market. This discussion includes (1) the links between crop yields, soil fertility and crop-livestock integration, (2) the increasing demand for livestock products and the land resources required to meet to this demand, and (3) the opportunities to integrate broader societal goals into the development of crop-livestock farms. There is ample room for development of crop-livestock farms in Africa, and keeping integration as part of the development will help prevent many of the mistakes and environmental problems related to the intensification of livestock production observed elsewhere in the world. This development can integrate biodiversity, climate change adaptation and mitigation to the current goals of increasing productivity and food security. The inclusion of broader goals could help farmers access the level of finance required to implement changes

Perceptions and outlook on intercropping coffee with banana as an opportunity for smallholder coffee farmers in Uganda

Coffee and banana are important cash and food crops in Uganda and the surrounding East African highland region. Production is dominated by smallholders that have limited arable land and often coffee and banana are intercropped. No significant research and development efforts have been undertaken over the last few decades on this coffee/banana intercropping system. Because recent studies suggest that this system could be a practice with high benefits to the farmers, we decided to study the perceptions of stakeholders along the coffee value chain starting with farmers. Perception analysis based on open-ended interviews following interview guides revealed that a major limitation for the sustainability of this system was poor soil fertility conditions. Perceptions on the benefits of intercropping differed little among coffee actors; that is, banana intercropping provides additional food and income from smallholders’ limited land and helps farmers reduce risks related to drought, pest/disease attacks and coffee price volatility. However, farmers’ desire to minimize risks does not match the objective of stakeholders higher up the coffee value chain to maximize coffee production. Furthermore, research by public institutes, both national and international, is primarily organized for single crops and not systems. We conclude that the institutional setting of the coffee sector hampers the promotion of intercropping, despite the benefits for the farmer

Land use, land use history and soil type affect greenhouse gas fluxes from intact soil cores sampled across agricultural landscapes of the East African highlands

Data on greenhouse gas (GHG) fluxes from smallholder based systems in East Africa is limited. Estimation of GHG fluxes in smallholder farming systems is further constrained by the diversity of drivers of GHG fluxes such as land use, soil types, management intensities, climatic variables, and this renders field GHG fluxes measurements costly in terms of time and resources. Use of intact soil core incubation approach can be used as a priori of field measurement to get an understating of the drivers of GHG fluxes in search complex systems. We carried out this work in a 10 x10 km block of Rakai, in southern Uganda (O°40.124’ S 31°26.283’E). Rakai block is one of benchmark sites for CCAFS that represents the Perennial-annual crop farming system, which is widely practiced in the East African highlands. A preliminary study in reference to possible biophysical drivers of GHG fluxes pointed at land use, topographic positions and soil textural classes as likely drivers of GHG fluxes at the landscapes. We also identified a small patch of remaining degraded forests, surrounded by converted land uses to agriculture 3 and 50 years ago. This study therefore aimed at assessing the effects of soil textural class, topography, land use, and land use history on potential soil GHG fluxes (carbon dioxide- CO2 and nitrous oxide- N2O) in the Lake Victoria region. This work aimed at addressing two research questions; 1. To what extent do slope position, soil textural class, and topography and their interaction affect the soil GHG flux potential in the study area? 2. Does time since conversion (from natural forests to agricultural land-use) affect the soil GHG flux potential? Intact soil cores were sampled from randomly selected plots at 0-0.05m soil depth together with soil samples for analysis of soil texture, pH, total nitrogen and carbon and bulk density. Gas samples were first taken from air dried samples after which they were subjected to the different water holding capacities (WHC) .Individual soil cores were subjected to 30, 55 and 80% (WHC) and incubated at 21°C for a period of 48 hours. Gas samples were taken on the first day (three hours after adding deionized water), after 24 hours and at 48 hours. Cumulative fluxes (CO2 and N2O ) for the 48 hours were calculated by integrating the area of all measurement points for the 48-hour period following rewetting. We used cumulative 48hr after re-wetting to study the effect of land use, soil textural classes, slope positions and time of conversion. This dataset consists of cumulative CO2 and N2O at %WHC of 30, 55 and 80, and auxiliary data of soil properties (soil texture, pH, total nitrogen and carbon, C:N ratio and bulk density)