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Nonparametric Resampling Methods for Testing Multiplicative Terms in AMMI and GGE Models for Multienvironment Trials

Malik, W. A. and Hadasch, Steffen and Forkman, Johannes and Piepho, H-P (2018). Nonparametric Resampling Methods for Testing Multiplicative Terms in AMMI and GGE Models for Multienvironment Trials. Crop science. 58 , 752-761
[Journal article]

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Official URL: http://dx.doi.org/10.2135/cropsci2017.10.0615

Abstract

The additive main effects and multiplicative interaction (AMMI) and genotype and genotype 'environment interaction (GGE) models have been extensively used for the analysis of genotype 'environment experiments in plant breeding and variety testing. Since their introduction, several tests have been proposed for testing the significance of the multiplicative terms, including a parametric bootstrap procedure. However, all of these tests are based on the assumptions of normality and homogeneity variance of the errors. In this paper, we propose tests based on nonparametric bootstrap and permutation methods. The proposed tests do not require any strong distributional assumptions. We also propose a test that can handle heterogeneity of variance between environments. The robustness of the proposed tests is compared with the robustness of other competing tests. The simulation study shows that the proposed tests always perform better than the parametric bootstrap method when the distributional assumptions of normality and homogeneity of variance are violated. The stratified permutation test can be recommended in case of heterogeneity of variance between environments.

Authors/Creators:Malik, W. A. and Hadasch, Steffen and Forkman, Johannes and Piepho, H-P
Title:Nonparametric Resampling Methods for Testing Multiplicative Terms in AMMI and GGE Models for Multienvironment Trials
Series/Journal:Crop science (1435-0653)
Year of publishing :2018
Volume:58
Page range:752-761
Number of Pages:10
Publisher:The Crop Science Society of America, Inc.
ISSN:1435-0653
Language:English
Publication Type:Journal article
Refereed:Yes
Article category:Scientific peer reviewed
Version:Accepted version
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 1 Natural sciences > 101 Mathematics > 10106 Probability Theory and Statistics
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 405 Other Agricultural Sciences > Other Agricultural Sciences not elsewhere specified
Agrovoc terms:plant breeding, genotype environment interaction, simulation models
Keywords:genotypes, environment, plant breeding, simulation studies, genotype environment interaction
URN:NBN:urn:nbn:se:slu:epsilon-e-4904
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-e-4904
Additional ID:
Type of IDID
DOI10.2135/cropsci2017.10.0615
Web of Science (WoS)000429460300027
ID Code:15472
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Department of Plant Biology (from 140101)
Deposited By: SLUpub Connector
Deposited On:28 May 2018 12:16
Metadata Last Modified:09 Sep 2020 14:17

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