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Global sensitivity analysis for calculating the contribution of genetic parameters to the variance of crop model prediction

David Makowski, Naud, Cédric, Jeuffroy, Marie-Hélène, Aude Barbottin and Monod, Hervé

Reliability Engineering and System Safety, 2006, vol. 91, issue 10, 1142-1147

Abstract: Dynamic models are often used to predict the effects of farmers’ practices on crop yield, crop quality, and environment. These models usually include many parameters that must be estimated from experimental data before practical use. Parameter estimation is a difficult problem especially when some of the parameters vary across genotypes. These genetic parameters may be estimated from plant breeding experiments but this is very costly and requires a lot of experimental work. Moreover, some of the genetic parameters may account for only a very small part of the output variance and, so, do not deserve an accurate determination. This paper shows how methods of global sensitivity analysis can be used to evaluate the contributions of the genetic parameters to the variance of model prediction. Two methods are applied to a complex crop model for estimating the sensitivity indices associated to 13 genetic parameters. The results show that only five genetic parameters have a significant effect on crop yield and grain quality.

Keywords: Crop model; Extended fast; Genetic parameter; Global sensitivity analysis; Winding stairs (search for similar items in EconPapers)
Date: 2006
References: View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:91:y:2006:i:10:p:1142-1147

DOI: 10.1016/j.ress.2005.11.015

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