Asset Details
Do you wish to reserve the book?
Modeling spatial trends and selecting tropical wheat genotypes in multi-environment trials
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Modeling spatial trends and selecting tropical wheat genotypes in multi-environment trials
Do you wish to request the book?
Modeling spatial trends and selecting tropical wheat genotypes in multi-environment trials
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Modeling spatial trends and selecting tropical wheat genotypes in multi-environment trials
2024
Overview
In many cases, traditional analysis of breeding trials based on analysis of variance (ANOVA) do not allow a suitable genetic evaluation. Alternatively, mixed model-based approaches create the possibility of dealing with unbalanced data and modeling spatial trends. The aims of this study were to compare the goodness-of-fit of the model and the genotype ranking through different residual modeling approaches and to select the best performing tropical wheat genotypes based on the best-fitting model. A panel of tropical wheat genotypes was evaluated in three field trials conducted between 2020 and 2021 for grain yield. Linear mixed model analyses were used on the data to estimate the genetic parameters and to predict the genotypic values in analyses of single- and multi-environment trials. Accounting for spatial trends in the analyses of single-and multi-environment trials provides better outcomes than the compound symmetry model does.
Publisher
Crop Breeding and Applied Biotechnology,Brazilian Society of Plant Breeding
Subject
