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Four-way data analysis within the linear mixed modelling framework Scientia Agricola
Studnicki,Marcin; Mądry,Wiesław; Derejko,Adriana; Noras,Kinga; Wójcik-Gront,Elżbieta.
Cultivars have to be evaluated under different crop management systems across agro-ecosystems and years using multi-environment trials (MET) before releasing them to the market. Frequently, data collected in METs are arranged according to cultivar (G), management (M), location, (L) and year (Y) combinations in a four-way G x M x L x Y data table that is highly unbalanced for cultivars across locations and time. Therefore, we present the restricted maximum likelihood method (REML) for linear mixed models (LMM) with a factor analytic variance-covariance matrix for assessing cultivar adaptation to crop management systems and environments based on unbalanced datasets. Such a multi-environmental trial system has been in operation in Poland for winter wheat...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Crop management; Restricted maximum likelihood methods; Unbalanced data; Winter wheat.
Ano: 2015 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162015000500411
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Adaptation patterns of winter wheat cultivars in agro-ecological regions Scientia Agricola
Studnicki,Marcin; Derejko,Adriana; Wójcik-Gront,Elżbieta; Kosma,Michał.
ABSTRACT: Multi-environment trials are commonly used to assess cultivar adaptation patterns under different environmental conditions and to help make effective cultivar recommendations for growers. An example of a multi-environment trial system used for cultivar recommendations is the Polish Post-registration Variety Testing System. A common approach in cultivar recommendations is to evaluate the adaptability of cultivars across, or for, specific trial locations. However, the locations of the trials and the fields where a farmer will grow a crop are hardly ever in the same place. Therefore, it would be better to group the trial locations into regions and give recommendations for the whole region. The aim of this study is to evaluate the grain yield...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Crop management intensity; Covariance structure; Cultivar recommendation; Superior genotypes; Yield ranking.
Ano: 2019 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162019001200148
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