Micro-Spatial Analysis of Maize Yield Gap Variability and Production Factors on Smallholder Farms

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Munialo Sussy 1,*, Hall Ola 2, Francisca Archila Bustos Maria 2, Boke-Olén Niklas 3, Onyango M. Cecilia 1, Oluoch-Kosura Willis 4, Marstorp Håkan 5 and Göran Djurfeldt 2

[email protected] (G.D.)
3  Centre for Environmental and Climate research (CEC), Lund University, 22100 Lund, Sweden, [email protected]
4  Department of Agricultural Economics, University of Nairobi, Nairobi P.O. Box 29053-00625, Kenya; [email protected]
5  Department of Soil and Environment, Swedish University of Agricultural Sciences, S-75007 Uppsala, Sweden; [email protected]

* Correspondence: [email protected]; Tel.: +254-7105-81953
Received: 30 July 2019; Accepted: 6 September 2019; Published: 11 October 2019

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

Agriculture 2019, 9, 219; doi:10.3390/agriculture9100219 www.mdpi.com/journal/agriculture

Agriculture 2019, 9, 219 2 of 24

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.

Keywords: spatial arrangements; heterogeneous farms; yield gap patterns; site-specific; land management; unequal resource

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