Kenyan maize and beans production is estimated at 2.4 and 0.3 million metric tonnes, against a consumption requirements of about 3.6 and 0.9 million metric tonnes, respectively (World Bank, 2012). A farm profile study conducted in the region revealed that the two crops’ yields are low at 1.2 and 0.5 t ha-1 against the expected 6.0 and 2.3 t ha-1 season-1 for maize and bean, respectively.

The problems are compounded by low adoption of appropriate farming methods due to lack of appropriate local institutional to foster and promote innovative practices; lack of access to extension services, poor state of transport and other  infrastructure ( Nyariki,2004).  It is also attributed to low or too high rainfall coupled with  degradation of land ,reduced tree cover and water resources (Nyariki et al.2004;Simpson et al.,1996)

Of Kenya’s population roughly 80% are involved in agriculture (Kenya National Bureau of Statitics, KNBS, 2017). Approximately 4.8 million households (average household of 7 persons) are smallholders farming on less than two hectares representing 75% of the country’s population.  At any specified period at least 10 million Kenyans are estimated to suffer from chronic food insecurity and poor nutrition. An estimated 98% of 3.5 million small-scale farmers in Kenya grow maize where it accounts for 56% of cultivated land in Kenya (ASDS, 2012; Kilimi 2012). The main cropping system for smallholders is maize-legume system which entail intercropping and crop rotation. There are also incidences of maize mono cropping and relay cropping is also being practiced.

Key risks faced by smallholder farmers include i) variability in markets (prices of produce and inputs), ii) emerging diseases and pests including Maize Lethal Necrosis (MLN) and Fall Army Worm (FAW) , and variability in rainfall causing drought or  floods. Although crop production vary between households, low soil fertility, climate variability, pests and high cost of inputs are among the most common challenges faced by farmers (Ouma and DeGroote., 2011).


SIMLESA undertook on-farm research in different agroecological zones to assess the benefits of CASI and to develop appropriate technological packages for farmers. It increased the range of maize, legume and fodder/forage varieties available to smallholder farmers. Farmers were involved in participatory seed selection trials to identify the seed with qualities that they prefer. SIMLESA helped establish Agricultural innovation platforms (AIPs) to bring members along the value chain together (including farmers, seed producers, agro-dealers, NGOs and extension workers) to better serve farming communities, help mobilize resources, and support scaling. SIMLESA also provided training and capacity strengthening for national agricultural research systems and worked with government, business, and civil society organizations to provide an enabling environment for the benefits of CASI to be realized by farmers.

Strategic Approach

The majority of farmers in Kenya belong to groups. It was cost-effective to reach farmer groups through cluster approaches that evolved to innovation platforms ( also included researchers, extension providers, savings and credits, farmer field schools, church based organizations  and cooperatives) 

Many approaches such as field demonstrations, Participatory Variety Selection(PVS), were used, and many were familiar to farmers, but the AIPs were a relatively new approach.

In Kenya, AIPs were formed and managed at location with majority of members  coming from the same region. However, the initiatives had memberships with regional and national levels of operations. Examples of such members included Equity bank, Crop Insurance Companies and Seed Companies.

Monitoring, Evaluation and Learning

Direct beneficiaries reached through SIMLESA support : 172,621

Innovation Platforms: 13

Farmers reached: 10,000

Researchers trained  651

Adoption target: 130,708

Thematic Area Kenya
Area under dedicated for maize (millions) 1.6
Production per ha (tonnes) 1.8
Baseline reports 1

SIMLESA Impacts in Kenya

  • Scientific Impact

    Through partnership and collaborative research in the target countries, in line with the program design, the SIMLESA program has consistently maintained its focus on generating scientific impacts.

  • Capacity Impact

    SIMLESA has continued to deliberately direct its efforts on trainings in conservation agriculture principles and technologies; sustainable and climate responsive agriculture production systems; agricultural production systems simulations; risk management and systems modelling acknowledging the socioeconomic dynamics of households in different sites.

  • Community Impact

    During the design phase, the program set targets and adoption pathways to achieve scaling out processes in terms of the number of research communities covered, number of farmers reached out and the number of adopters (these being the farmers who have learned, embraced and started practising sustainable intensification technologies).

  • Economic Impact

    SIMLESA has brought increased use of CA-based sustainable intensification options technology in communities which have also led to evident reduction of production costs and increased crop productivity per unit area especially and dietary diversification in farm households where maize and legumes are intercropped.

  • Social Impact

    SIMLESA, on the social dimension side, continues to improve family fabric through the hosting of exploratory trials which promote the participation of men, women and youths thereby making everyone strategic and important participant in household farming activities.

  • Environmental Impact

    Climate change is expected to negatively impact agricultural production in SIMLESA countries. Low-nitrogen stress combined with drought and heat stress will become increasing constraints on maize production, and on growing improved varieties.




        Trial Demonstration Plots

        In Kenya, SIMLESA operated in two regions that represent about 39% of the arable land. In eastern Kenya, the Programme covers three counties: Embu, Meru and Tharaka Nithi (intial Counties). Later outscaled to, Meru, Embu, Nyeri and Kitui Counties (NCCK). In western Kenya, two counties are covered, Siaya and Bungoma (initial Counties) and later outscaled to Vihiga and Busia Counties) (Egerton University)

        Some of our field experimental sites:

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