Options identified for systems intensification and diversification that reduce risk using systems modeling. Potential technologies, systems, practices, and risk management strategies including conventional and CA systems, and a restricted range of potential legume speciesto increase maize productivity, legume options for system diversification and sustainability will be identified, along with opportunities for balanced gender impact. Legume green manure cover crops may be considered where farmers are not land-constrained.
Functioning local innovation systems which engage 5,000 farmers each in at least ten maize-legume systems scaled out locally. Local groups and stakeholders will be encouraged to participate in innovation system field days, discussion groups and farmer visits from year 1; farmers will be encouraged to adopt, experiment with, and adapt the CA-oriented technologies, varieties and ways to improve market access; the effectiveness of local processes for adapting and spreading program technologies will be assessed using participatory and M&E systems and the most effective processes replicated to foster growth of the local innovation system from approximately 500 farmers per innovation system in year 1 to a target of 5,000 participating farmers per system in at least ten active local innovation systems.
Exploratory trials of current best options for maize/legume smallholder systems evaluated in thirty research sites/communities. Conservation agriculture-oriented management systems and other production technologies will be adapted to the biophysical and socio-economic conditions of innovative farmers via exploratory trials; “best bet” CA options will be tested in each community and compared with current management practices; basic soil, topography and cropping history data will be obtained for each demonstration/validation plot; and observations of problems on these trials will provide inputs into the on-farm research program and management over succeeding years.
Adjustments made to the smallholder systems tested in exploratory trials and farmer experiments and soil quality, system productivity and disease, pest and weed dynamics quantified. This will be achieved through on-farm research and researcher-managed trials that will generate data to enable adequate parameterization of the APSIM model; trials will be established and data collected on crop productivity and water dynamics for crop/soil simulation to address potential effects of technological interventions on soil quality, biological nitrogen fixation (BNF), and disease, pest and weed dynamics, and on system productivity and sustainability.
Appropriate interventions for improving seed and fertilizer delivery and farmer access to technologies and markets field tested. National reports identifying best practices and models for improving farmer access to seeds and technology adoption will be synthesized and business development services supporting this adoption developed; a second report identifying best practices, marketing instruments and models for improving farmer access to output markets; a third report identifying best practices for provision of insurance services to smallholders to manage risks will be prepared; a synthesis of national reports identifying best practices for improving food quality, safety, and household processing will be developed; policy options to enhance markets for maize and legumes will be identified and summarized in policy briefs and communicated to policy makers.
Lessons from active farmer experimentation with CA-oriented systems incorporated into on-farm research and/or demonstration plots. Plots of farmers who plan to install maize/legume CA-oriented experiments will be monitored to record farmer activities and innovations, as well as crop productivity; results of these farmer experiments will also be discussed at the Annual E&P meetings and problems observed as well as farmer innovations discussed to assess the need to incorporate them into the on-farm research process; these data will be fed back into the systems modeling.
Farmer learning through annual facilitated visits of farmers and their local extension agents between the targeted communities. Communities with similar conditions to target communities will be identified and farmer-to-farmer networking will be fostered for scaling out of knowledge and technological innovations; data on new farmer experiments will be made available, permitting an evaluation of the effectiveness of the farmer-to-farmer visits.