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Projecting results of zoned multi-environment trials to new locations using environmental covariates with random coefficient models: accuracy and precision

Buntaran, Harimurti and Forkman, Johannes and Piepho, Hans-Peter (2021). Projecting results of zoned multi-environment trials to new locations using environmental covariates with random coefficient models: accuracy and precision. Theoretical and Applied Genetics. 134 , 1513-1530
[Research article]

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Abstract

Key message We propose the utilisation of environmental covariates in random coefficient models to predict the genotype performances in new locations. Multi-environment trials (MET) are conducted to assess the performance of a set of genotypes in a target population of environments. From a grower's perspective, MET results must provide high accuracy and precision for predictions of genotype performance in new locations, i.e. the grower's locations, which hardly ever coincide with the locations at which the trials were conducted. Linear mixed modelling can provide predictions for new locations. Moreover, the precision of the predictions is of primary concern and should be assessed. Besides, the precision can be improved when auxiliary information is available to characterize the targeted locations. Thus, in this study, we demonstrate the benefit of using environmental information (covariates) for predicting genotype performance in some new locations for Swedish winter wheat official trials. Swedish MET locations can be stratified into zones, allowing borrowing information between zones when best linear unbiased prediction (BLUP) is used. To account for correlations between zones, as well as for intercepts and slopes for the regression on covariates, we fitted random coefficient (RC) models. The results showed that the RC model with appropriate covariate scaling and model for covariate terms improved the precision of predictions of genotypic performance for new locations. The prediction accuracy of the RC model was competitive compared to the model without covariates. The RC model reduced the standard errors of predictions for individual genotypes and standard errors of predictions of genotype differences in new locations by 30-38% and 12-40%, respectively.

Authors/Creators:Buntaran, Harimurti and Forkman, Johannes and Piepho, Hans-Peter
Title:Projecting results of zoned multi-environment trials to new locations using environmental covariates with random coefficient models: accuracy and precision
Series Name/Journal:Theoretical and Applied Genetics
Year of publishing :2021
Volume:134
Page range:1513-1530
Number of Pages:18
Publisher:SPRINGER
ISSN:0040-5752
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 1 Natural sciences > 105 Earth and Related Environmental Sciences > Environmental Sciences (social aspects to be 507)
URN:NBN:urn:nbn:se:slu:epsilon-p-111752
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-111752
Additional ID:
Type of IDID
DOI10.1007/s00122-021-03786-2
Web of Science (WoS)000638031200003
ID Code:23446
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Dept. of Crop Production Ecology
Deposited By: SLUpub Connector
Deposited On:07 May 2021 10:03
Metadata Last Modified:07 May 2021 10:11

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