In-season plot area loss and implications for yield estimation in smallholder rainfed farming systems at the village level in Sub-Saharan Africa

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Abstract

The shortfalls in the quality, quantity, and reliability of agriculture performance data are neither new nor confined to Sub-Saharan Africa (SSA). It is, however, a more dire challenge given the overwhelming importance of agriculture in the economies of most countries in the region in terms of food security and poverty reduction. While farmers’ self-reported (SR) data on crop outputs and farm sizes remain popular variables for computing plot productivity and yields, especially in SSA, other methods such GPS measurement and remote sensing measurement of crop area, crop cuts (CC) as well as whole plot harvests have been touted as the gold standard methods for yield measurement. All these approaches to yield estimation are insufficient in capturing real agriculture productivity in rainfed farming systems due to the significant area loss that characterizes these farming systems in the course of each cropping season. This paper compares yield data of smallholder maize plots from two farming communities in the Eastern Region of Ghana based on farmer self-reported outputs and crop cuts, as well as GPS and aerial imagery measurement of plot area. The study finds a high level of agreement between GPS-measured plot area and that measured using remote sensing methods (R2 = 0.80) with the minor deviations between the two measures attributable to changes in farmers’ plans in the course of the season with regards to their cultivation extent. More interestingly, the study finds a substantial disparity between measured CC yields and SR yields; 2174 kg/ha for CC yields compared to 651 kg/ha for SR yields. The significant disparity between the two measures of yield is partly attributable to the significant intra-plot variability in crop performance leading to plot area loss in the course of the season. This area loss (ranging from 15 to 30% of the planted area) is usually not taken into account in current yield measurement approaches. Delineating the productive and planted-but-unproductive sections of plots has important implications not only for yield estimation methodologies but also for shedding more light on the factors underlying current poor yields and pathways to improving productivity on smallholder rainfed maize farms.

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Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Other Agricultural Sciences
  • Geology

Keywords

  • Agricultural productivity, Farm yield measurements, Remote sensing, Smallholder farming
Original languageEnglish
JournalGeoJournal
Publication statusE-pub ahead of print - 2019 Jun 28
Publication categoryResearch
Peer-reviewedYes