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Implications of intra-plot heterogeneity for yield estimation accuracy: evidence from smallholder maize systems in Ethiopia

Creator: Sida, T.S.
Creator: Chamberlin, J.
Creator: Hailemariam Ayalew
Creator: Kosmowski, F.
Creator: Craufurd, P.
Year: 2021
URI: https://hdl.handle.net/10883/21374
Language: English
Publisher: Elsevier
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
Type: Article
Country focus: Ethiopia
Place of Publication: Amsterdam (Netherlands)
Volume: 267
DOI: 10.1016/j.fcr.2021.108147
Keywords: Yield Variability
Keywords: Within Plot Variation
Keywords: Agronomic Decision
Keywords: Farm Intensification
Keywords: Inter-Plot Heterogeneity
Description: Intra-plot heterogeneity in yield is often observed in smallholder farming systems, although its implications for yield measurement remain under-investigated. Using a unique dataset on smallholder maize production in Ethiopia, we quantify the magnitude of inter- and intra-plot heterogeneity, describe the relationship between intra-plot heterogeneity and maize productivity, and document the implications of intra-field heterogeneity on the accuracy of alternative yield estimation protocols. Our data include five common yield estimation protocols, as well as full plot harvests of 230 smallholder maize fields. We surveyed agronomic decisions, biophysical variables, and accessibility characteristics of the surveyed fields. We quantify intra-plot heterogeneity using the coefficient of variation (CV) of stand density, cob weight, and maize grain yield. A generalized linear mixed model is used to explore the relationship between these variables and the method- and heterogeneity-dependence of yield estimation accuracy. We find inter-plot CV values ranging from 32 to 56 %, 22 to 73 % and 39 to 49 % in population density, cob weight and grain yield, respectively. Intra-plot heterogeneity constituted most of this variation, with across-method mean CV values of 41 %, 82 % and 63 %, respectively, of the total variability in population density, cob weight and grain yield. A rise in intra-plot heterogeneity of 0.5 % to 0.8 % is associated with a significant increase in yield estimation error under alternative yield estimation protocols. Regression analysis shows that interactions in agronomic decisions, input intensity and plot accessibility factors dictate intra-plot heterogeneity and method accuracy in smallholder systems. Intra-plot heterogeneity is larger than inter-plot heterogeneity in the current study area. Our analysis shows that the effect of intra-plot heterogeneity on yield estimation accuracies is method-dependent and yield estimation methods that fail to capture true intra-plot heterogeneity are more error-prone. Results of such estimations should be considered with caution when used as the basis of decision-making.
Agrovoc: YIELDS
Agrovoc: DECISION MAKING
Agrovoc: PARCELS
Agrovoc: INTENSIFICATION
Related Datasets: https://www.sciencedirect.com/science/article/pii/S0378429021000939?via%3Dihub#sec0150
ISSN: 0378-4290
Journal: Field Crops Research
Article number: 108147


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  • Socioeconomics
    Including topics such as farming systems, markets, impact & targeting, innovations, and GIS
  • Sustainable Intensification
    Sustainable intensification agriculture including topics on cropping systems, agronomy, soil, mechanization, precision agriculture, etc.

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