The solution to reducing existing yield gaps on smallholder farms lies in understanding factors limiting yield in areas with agricultural intensification potential. This study applied an integrated analysis approach comprising Classification and Regression Tree (CART), generalized linear mixed model (GLMM), and factor analysis (FA), to explain soil and management‐related factors influencing maize yield gaps, in order to enhance yields. The study was conducted in Mukuyu and Shikomoli in western Kenya, sites with, respectively, high and low agroecological potential regarding soil fertility. Maize yield gaps were quantified by comparing yields on the 90th percentile of farms to yields determined in 189 fields on 70 randomly sampled smallholdings. Soil and management‐related factors were determined at early and late maize development stages. Maize yield on the 90th percentile of farms in Mukuyu and Shikomoli was 5.1 and 4.8 t/ha, respectively, and the average yield gap was 1.8 and 2.6 t/ha, representing 35% and 54% unachieved yield for Mukuyu and Shikomoli, respectively. In FA, soil was revealed to be the main factor influencing maize yield gaps at both sites, rather than management‐related variables. The CART method identified maize density, chlorophyll values, maize height, and depth to compact layer as consistent factors affecting yield at both sites, while GLMM identified soil texture (silt content) as important. According to CART, weed cover at early stages and maize density at late stages were the most limiting factor in maize production in Mukuyu and Shikomoli, respectively. Generalized linear mixed model analysis identified agroecology‐specific factors influencing maize yield gaps as soil‐available phosphorus and zinc, plus weed pressure at early maize stages in Mukuyu, and plus soil cation exchange capacity and exchangeable magnesium in Shikomoli. Through an integrated approach, it was possible to identify both consistent and agroecology‐specific factors limiting crop yields. This can increase the applicability of the findings to smallholder farms.

Site-specific land management practice taking into account variability in maize yield gaps (the difference between yields in the 90th percentiles and other yields on smallholder farmers’ fields) could improve resource use efficiency and enhance yields. However, the applicability of the practice is constrained by inability to identify patterns of resource utilization to target application of resources to more responsive fields. The study focus was to map yield gaps on smallholder fields based on identified spatial arrangements differentiated by distance from the smallholder homestead and understand field-specific utilization of production factors. This was aimed at understanding field variability based on yield gap mapping patterns in order to enhance resource use efficiency on smallholder farms. The study was done in two villages, Mukuyu and Shikomoli, with high and low agroecology regarding soil fertility in Western Kenya. Identification of spatial arrangements at 40 m, 80 m, 150 m and 300 m distance from the homestead on smallholder farms for 70 households was done. The spatial arrangements were then classified into near house, mid farm and far farm basing on distance from the homestead. For each spatial arrangement, Landsat sensors acquired via satellite imagery were processed to generate yield gap maps. The focal statistics analysis method using the neighborhoods function was then applied to generate yield gap maps at the different spatial arrangements identified above. Socio-economic, management and biophysical factors were determined, and maize yields estimated at each spatial arrangement. Heterogeneous patterns of high, average and low yield gaps were found in spatial arrangements at the 40 m and 80 m distances. Nearly homogenous patterns tending towards median yield gap values were found in spatial arrangements that were located at the 150 m and 300 m. These patterns correspondingly depicted field-specific utilization of management and socio-economic factors. Field level management practices and socio-economic factors such as application of inorganic fertilizer, high frequency of weed control, early land preparation, high proportion of hired and family labor use and allocation of large land sizes were utilized in spatial arrangements at 150 and 300 m distances. High proportions of organic fertilizer and family labor use were utilized in spatial arrangements at 40 and 80 m distances. The findings thus show that smallholder farmers preferentially manage the application of socio-economic and management factors in spatial arrangements further from the homestead compared to fields closer to the homestead which could be exacerbating maize yield gaps. Delineating management zones based on yield gap patterns at the different spatial arrangements on smallholder farms could contribute to site-specific land management and enhance yields. Investigating the value smallholder farmers attach to each spatial arrangement is further needed to enhance the spatial understanding of yield gap variation on smallholder farms.

Land subdivision has reduced land for agricultural production resulting in its intensive cultivation. This has lowered soil fertility which has contributed to reduction in the diversity of African Leafy Vegetables thus restricting the otherwise traditional dietary diversity that was once beneficial to smallholder farmers. As land continues to decline, there needs to be some impetus in place that can retain the diversity of African Leafy Vegetables. This study therefore recognized the need to niche the African Leafy Vegetables to a none-competing, specially constructed raised cropping bed referred to us the Premium Influenced Land Agro-usage structure (PILA). A study to investigate the viability of the PILA structure for production of vegetable crops was undertaken in Vihiga and Jinja. The objective of the study was to evaluate the benefits of the PILA structures. PILA structures were constructed on 20 smallholder farms in Vihiga and Jinja. Vegetable crops Solanum scabrum, Cleome gynandra, Amaranthus hybridus) and exotic vegetables (Daucas carota) were grown on these structures. The same procedure was done on farmers' conventional plots (Flat beds). Analysis to compare the performance of vegetable crops between the PILA and Flat beds was done using Genstat. The net present value was used to assess the viability of the structure for long term use. Results indicated high significant differences (p≤0.001) in yield and height of vegetables crops grown on PILA and flat beds, (PILA yield (kg/ha) was 42254 versus 27772 for flat beds, PILA height in (cm) was 14.8 versus 10.8 for flat beds). Comparisons in vegetable performance between seasons showed better performance of vegetable crops in the Long Rains than the Short Rains seasons for both sites with significant difference (p=0.001) in yield (kg/ha) for the Long Rain (LR) was 36064 against 33962 for the Short Rain (SR), mean height (cm) for LR was 13 against 12.5 for SR, mean branching (score out of 3) for LR was 2.5 against 2.4 for SR. Also significant differences in vegetable performance were detected between Vihiga and Jinja in height and yield; mean yield (kg/ha) for Vihiga was 34962 and 36064 for Jinja, mean height (cm) for Vihiga was 12.8 and 16.6 for Jinja. The PILAs had a high net present value (KSH191390) compared to flats beds (KSH122087). Vegetable crops on PILA structure performed better than on Flat beds, the PILA structure can be promoted for production of vegetables in areas with small land sizes like the urban and peri-urban. However, there is need to increase the acceptability and adoption of the structure through awareness.