Environmental stratification and genotype recommendation toward the soybean ideotype: a Bayesian approach

IF 1.5 4区农林科学 Q2 Agricultural and Biological Sciences

Crop Breeding and Applied Biotechnology Pub Date : 2021-05-21 DOI:10.1590/1984-70332021V21N1A11

J. S. P. C. Evangelista, M. A. Peixoto, I. Coelho, R. S. Alves, F. F. Silva, M. Resende, F. L. Silva, L. L. Bhering

{"title":"Environmental stratification and genotype recommendation toward the soybean ideotype: a Bayesian approach","authors":"J. S. P. C. Evangelista, M. A. Peixoto, I. Coelho, R. S. Alves, F. F. Silva, M. Resende, F. L. Silva, L. L. Bhering","doi":"10.1590/1984-70332021V21N1A11","DOIUrl":null,"url":null,"abstract":"Abstract The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genotypes recommendation. Thus, the objectives of this study were: i) propose the Multi-Environment Index Based on Factor Analysis and Ideotype-Design/Markov Chain Monte Carlo (FAI/MCMC index), and ii) apply it for soybean genotypes recommendation. To this end, a data set with 30 soybean genotypes evaluated in 10 environments for grain yield trait was used. Variance components, genetic parameters and genetic values were estimated through MCMC algorithm. Environmental stratification was conducted by factor analyses and the selection of soybean genotypes was performed using the FAI/MCMC index. The results indicated the existence of genotypic variability and G×E interaction. The environments were grouped into three factors. The predicted genetic gains from indirect selection was 4.81%. Thus, our results suggest that the FAI/MCMC index can be successfully used in soybean breeding.","PeriodicalId":10763,"journal":{"name":"Crop Breeding and Applied Biotechnology","volume":"1 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Crop Breeding and Applied Biotechnology","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1590/1984-70332021V21N1A11","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}

引用次数: 4

Abstract

Abstract The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genotypes recommendation. Thus, the objectives of this study were: i) propose the Multi-Environment Index Based on Factor Analysis and Ideotype-Design/Markov Chain Monte Carlo (FAI/MCMC index), and ii) apply it for soybean genotypes recommendation. To this end, a data set with 30 soybean genotypes evaluated in 10 environments for grain yield trait was used. Variance components, genetic parameters and genetic values were estimated through MCMC algorithm. Environmental stratification was conducted by factor analyses and the selection of soybean genotypes was performed using the FAI/MCMC index. The results indicated the existence of genotypic variability and G×E interaction. The environments were grouped into three factors. The predicted genetic gains from indirect selection was 4.81%. Thus, our results suggest that the FAI/MCMC index can be successfully used in soybean breeding.

查看原文本刊更多论文

大豆理想型的环境分层和基因型推荐:贝叶斯方法

基因型×环境（G×E）相互作用在表型表达中起着重要作用，可能导致基因型推荐困难。因此，本研究的目的是：i）提出基于因子分析和Ideotype Design/Markov Chain Monte Carlo的多环境指数（FAI/MMC指数），以及ii）将其应用于大豆基因型推荐。为此，使用了一个包含30个大豆基因型的数据集，在10个环境中评估了粮食产量性状。通过MCMC算法估计方差分量、遗传参数和遗传值。通过因子分析进行环境分层，并使用FAI/MMCC指数进行大豆基因型的选择。结果表明存在基因型变异和G×E相互作用。环境分为三个因素。间接选择的遗传增益预测值为4.81%，表明FAI/MMCC指数可以成功应用于大豆育种。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Crop Breeding and Applied Biotechnology 农林科学-农艺学

CiteScore

2.40

自引率

13.30%

发文量

审稿时长

6-12 weeks

期刊介绍： The CBAB – CROP BREEDING AND APPLIED BIOTECHNOLOGY (ISSN 1984-7033) – is the official quarterly journal of the Brazilian Society of Plant Breeding, abbreviated CROP BREED APPL BIOTECHNOL. It publishes original scientific articles, which contribute to the scientific and technological development of plant breeding and agriculture. Articles should be to do with basic and applied research on improvement of perennial and annual plants, within the fields of genetics, conservation of germplasm, biotechnology, genomics, cytogenetics, experimental statistics, seeds, food quality, biotic and abiotic stress, and correlated areas. The article must be unpublished. Simultaneous submitting to another periodical is ruled out. Authors are held solely responsible for the opinions and ideas expressed, which do not necessarily reflect the view of the Editorial board. However, the Editorial board reserves the right to suggest or ask for any modifications required. The journal adopts the Ithenticate software for identification of plagiarism. Complete or partial reproduction of articles is permitted, provided the source is cited. All content of the journal, except where identified, is licensed under a Creative Commons attribution-type BY. All articles are published free of charge. This is an open access journal.