How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia

Agricultural statistics and applied analyses have benefitted from moving from farmer estimates of yield to crop cut based estimates, now regarded as a gold standard. However, in practice, crop cuts and other sample-based protocols vary widely in the details of their implementations and little empiri...

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Autores principales: Kosmowski, Frederic, Chamberlin, Jordan, Ayalew, Hailemariam, Sida, Tesfaye, Abay, Kibrom A., Craufurd, Peter
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://hdl.handle.net/10568/142563
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author Kosmowski, Frederic
Chamberlin, Jordan
Ayalew, Hailemariam
Sida, Tesfaye
Abay, Kibrom A.
Craufurd, Peter
author_browse Abay, Kibrom A.
Ayalew, Hailemariam
Chamberlin, Jordan
Craufurd, Peter
Kosmowski, Frederic
Sida, Tesfaye
author_facet Kosmowski, Frederic
Chamberlin, Jordan
Ayalew, Hailemariam
Sida, Tesfaye
Abay, Kibrom A.
Craufurd, Peter
author_sort Kosmowski, Frederic
collection Repository of Agricultural Research Outputs (CGSpace)
description Agricultural statistics and applied analyses have benefitted from moving from farmer estimates of yield to crop cut based estimates, now regarded as a gold standard. However, in practice, crop cuts and other sample-based protocols vary widely in the details of their implementations and little empirical work has documented how alternative yield estimation methods perform. Here, we undertake a well-measured experiment of multiple yield estimation methods on 237 smallholder maize plots in Amhara region, Ethiopia. We compare yield from a full plot harvest with farmer assessments and with estimates from a variety of field sampling protocols: W-walk, transect, random quadrant, random octant, center quadrant, and 3 diagonal quadrants. We find that protocol choices are important: alternative protocols vary considerably in their accuracy relative to the whole plot, with absolute mean errors ranging from 23 (farmer estimates) to 10.6 (random octant). Furthermore, while most methods approximate the sample mean reasonably well, the divergence of individual measures from true plot-level values can be considerable. We find that randomly positioned quadrants outperform systematic sampling schemes: the random octant had the best accuracy and was the most cost-effective. The nature of bias is non-classical: bias is correlated with plot size as well as with plot management characteristics. In summary, our results advocate that even “gold standard” crop cut measures should be interpreted cautiously, and more empirical work should be carried out to validate and extend our conclusions.
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spelling CGSpace1425632024-10-25T08:03:50Z How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia Kosmowski, Frederic Chamberlin, Jordan Ayalew, Hailemariam Sida, Tesfaye Abay, Kibrom A. Craufurd, Peter sampling methods sampling surveys maize measurement crop yield crop production smallholders farms agricultural systems farming systems errors Agricultural statistics and applied analyses have benefitted from moving from farmer estimates of yield to crop cut based estimates, now regarded as a gold standard. However, in practice, crop cuts and other sample-based protocols vary widely in the details of their implementations and little empirical work has documented how alternative yield estimation methods perform. Here, we undertake a well-measured experiment of multiple yield estimation methods on 237 smallholder maize plots in Amhara region, Ethiopia. We compare yield from a full plot harvest with farmer assessments and with estimates from a variety of field sampling protocols: W-walk, transect, random quadrant, random octant, center quadrant, and 3 diagonal quadrants. We find that protocol choices are important: alternative protocols vary considerably in their accuracy relative to the whole plot, with absolute mean errors ranging from 23 (farmer estimates) to 10.6 (random octant). Furthermore, while most methods approximate the sample mean reasonably well, the divergence of individual measures from true plot-level values can be considerable. We find that randomly positioned quadrants outperform systematic sampling schemes: the random octant had the best accuracy and was the most cost-effective. The nature of bias is non-classical: bias is correlated with plot size as well as with plot management characteristics. In summary, our results advocate that even “gold standard” crop cut measures should be interpreted cautiously, and more empirical work should be carried out to validate and extend our conclusions. 2021-07-09 2024-05-22T12:10:41Z 2024-05-22T12:10:41Z Journal Article https://hdl.handle.net/10568/142563 en Open Access Elsevier Kosmowski, Frederic; Chamberlin, Jordan; Ayalew, Hailemariam; Sida, Tesfaye; Abay, Kibrom A.; and Craufurd, Peter. 2021. How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia. Food 102(July 2021): 102122. https://doi.org/10.1016/j.foodpol.2021.102122
spellingShingle sampling methods
sampling
surveys
maize
measurement
crop yield
crop production
smallholders
farms
agricultural systems
farming systems
errors
Kosmowski, Frederic
Chamberlin, Jordan
Ayalew, Hailemariam
Sida, Tesfaye
Abay, Kibrom A.
Craufurd, Peter
How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia
title How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia
title_full How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia
title_fullStr How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia
title_full_unstemmed How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia
title_short How accurate are yield estimates from crop cuts? Evidence from smallholder maize farms in Ethiopia
title_sort how accurate are yield estimates from crop cuts evidence from smallholder maize farms in ethiopia
topic sampling methods
sampling
surveys
maize
measurement
crop yield
crop production
smallholders
farms
agricultural systems
farming systems
errors
url https://hdl.handle.net/10568/142563
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