Abstract
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.
Highlights
Smallholder farmers contribute approximately 75% of agricultural productivity and employment in many parts across the world [1]
The results demonstrated the potential use of spatial arrangements on smallholder farms to show yield gap variability and field-specific utilization spatial arrangements on smallholder farms to show yield gap variability and field-specific utilization of factors of production—management, socio-economic and biophysical factors
The study demonstrated the use of spatial arrangements found on smallholder farms as a unique approach to identify patterns of yield gap variability and survey data to reveal field-specific utilization of management, socio-economic and biophysical factors as a scope for enhancing site-specific land management
Summary
Smallholder farmers contribute approximately 75% of agricultural productivity and employment in many parts across the world [1] These farmers live on farms that are less than 2 hectares which are highly heterogeneous with regard to soil quality, productive assets and technology [2]. These diversities contribute to significantly higher maize yield gaps There is limited understanding of the causes of yield gaps at a micro-level This is because studies on analysis of yield gaps at a local level have used methods such as surveys and field experimentation to understand factors limiting crop yields [5,6]. These methods have spatial data limitation where only few randomly sampled units are used and fail to provide a comprehensive understanding of yield gaps at micro-level considering diversity which exists even within fields and plots [7]
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