P. H. Facchinello, I. Carvalho, E. A. Streck, G. A. Aguiar, Janaína Goveia, Michele Feijó, Roberto Ramos Pereira, P. R. R. Fagundes, Murilo Vieira Loro, L. C. Maia, A. M. Júnior
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Evaluation of intrinsic physical quality attributes with the aid of S21 grain statistical analyzer, as well as grain yield and mill yield (whole and broken grains). Performance of analysis of variance, genetic parameters and Scott Knott cluster test, linear correlation, canonical correlations, cluster analysis via generalized Mahalanobis distance, using the Toucher method, in addition to BIPLOT principal component analysis. The results showed that PH18502 and PH18701 strains presented better agronomic performance for the studied characters, by univariate analysis. The linear and canonical correlations presented demonstrate potential in the direction of selection of multiple characters and point to the possibility of indirect selection among the relevant agronomic characters for the production chain of irrigated rice.","PeriodicalId":297313,"journal":{"name":"Agronomy Science and Biotechnology","volume":"137 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Genetic trends and multivariate interrelationships for grain quality of irrigated rice genotypes\",\"authors\":\"P. H. Facchinello, I. Carvalho, E. A. Streck, G. A. Aguiar, Janaína Goveia, Michele Feijó, Roberto Ramos Pereira, P. R. R. Fagundes, Murilo Vieira Loro, L. C. Maia, A. M. 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引用次数: 1
摘要
对于水稻的遗传改良项目,多变量方法的研究是基础,以确定遗传趋势,集群和农艺性状的相关性,共同帮助选择程序。本研究旨在揭示水稻优良品系的农艺性状、籽粒品质的变化趋势及遗传相互关系。该实验在2017/2018年的收获季节进行,在Embrapa Clima Temperado的esta o Experimental Terras Baixas (ETB)举行。本研究采用随机区组设计,共3个重复。F6系15个,对照品种4个。利用S21谷物统计分析仪评价内在物理品质属性,以及籽粒产量和磨粒产量(整粒和碎粒)。性能方差分析,遗传参数和Scott Knott聚类检验,线性相关,典型相关,聚类分析通过广义马氏距离,使用Toucher方法,除BIPLOT主成分分析。单因素分析结果表明,PH18502和PH18701菌株的农艺性能较好。线性相关性和典型相关性显示了在多性状选择方向上的潜力,并指出了灌溉水稻生产链中相关农艺性状间间接选择的可能性。
Genetic trends and multivariate interrelationships for grain quality of irrigated rice genotypes
For genetic improvement programs, researches with multivariate approaches in rice are fundamental, to define genetic trends, clusters and correlations of agronomic characters that together help selection procedures. This work aimed to reveal the agronomic performance, trends and genetic interrelationships of grain quality based on multivariate models applied to elite lines of irrigated rice. The experiment took place in the 2017/2018 harvest, held at Estação Experimental Terras Baixas (ETB), of Embrapa Clima Temperado. The study used randomized blocks design, with three replications. There were fifteen F6 lines and four control cultivars. Evaluation of intrinsic physical quality attributes with the aid of S21 grain statistical analyzer, as well as grain yield and mill yield (whole and broken grains). Performance of analysis of variance, genetic parameters and Scott Knott cluster test, linear correlation, canonical correlations, cluster analysis via generalized Mahalanobis distance, using the Toucher method, in addition to BIPLOT principal component analysis. The results showed that PH18502 and PH18701 strains presented better agronomic performance for the studied characters, by univariate analysis. The linear and canonical correlations presented demonstrate potential in the direction of selection of multiple characters and point to the possibility of indirect selection among the relevant agronomic characters for the production chain of irrigated rice.