Selection of superior sweet potato genotypes for human consumption via mixed models

IF 1.2 4区农林科学 Q2 AGRICULTURE, MULTIDISCIPLINARY

Bragantia Pub Date : 2022-01-01 DOI:10.1590/1678-4499.20220075

Ariana da Silva Costa, V. C. A. Andrade Júnior, André Boscolo Nogueira da Gama, E. A. D. Silva, O. G. Brito, J. C. O. Silva, J. B. Bueno Filho

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Abstract

: The growing consumer demand for sweet potato roots results in the need for genotypes with higher yields and better root quality. Thus, the objective of this study was to agronomically evaluate sweet potato genotypes via mixed models to select superior genotypes for human consumption and predict their selection gains. The study had a partially balanced triple lattice design with three replicates. As treatments, 92 sweet potato genotypes from the Universidade Federal de Lavras germplasm bank selected in the first selection cycle were evaluated along with eight controls, namely, Brazlândia Roxa, Princesa, Uruguaiana, BRS Amélia, Beauregard, UFVJM-57, UFVJM-58, and UFVJM-61. The treatments were ranked by the mixed linear model via restricted maximum likelihood (REML) and best linear unbiased prediction (BLUP). We highlighted the 15 best genotypes for each agronomic trait, then identified the best ones overall considering all quantitative and qualitative traits. High heritability was found for the trait commercial root yield (56.31%). For all traits, there were selection gains relative to the population mean. The use of mixed models was efficient for the selection of superior sweet potato genotypes. The genotypes 2018-19-464, 2018-72-1409, 2018-72-1428, 2018-19-443, 2018-36-807, 2018-72-1418, 2018-19-455, 2018-72-1376, 2018-54-1137, 2018-54-1114, 2018-65-1249, and 2018-28-556 have good traits related to commercial root yield and root quality and may be recommended for human consumption.

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通过混合模型选择供人类食用的优质甘薯基因型

消费者对红薯根的需求日益增长，因此需要产量更高、根质量更好的基因型。因此，本研究的目的是通过混合模型对甘薯基因型进行农艺学评价，以选择供人类食用的优良基因型，并预测其选择收益。本研究采用部分平衡三重晶格设计，共3个重复。以第一个筛选周期中从拉夫拉斯联邦大学种质库中筛选出的92个甘薯基因型为对照，分别为brazl ndia Roxa、Princesa、Uruguaiana、BRS amsamlia、Beauregard、UFVJM-57、UFVJM-58和UFVJM-61。通过限制最大似然(REML)和最佳线性无偏预测(BLUP)的混合线性模型对处理进行排序。我们对每个农艺性状突出了15个最佳基因型，然后综合考虑所有数量和质量性状，确定了最佳基因型。商品根产量遗传力高(56.31%)。对于所有性状，都有相对于种群均值的选择增益。采用混合模型对甘薯优良基因型的选择是有效的。基因型2018-19-464、2018-72-1409、2018-72-1428、2018-19-443、2018-36-807、2018-72-1418、2018-19-455、2018-72-1376、2018-54-1137、2018-54-1114、2018-65-1249和2018-28-556具有与商品根产量和根品质相关的良好性状，可推荐供人类食用。

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来源期刊

Bragantia AGRICULTURE, MULTIDISCIPLINARY-

CiteScore

2.40

自引率

8.30%

发文量

审稿时长

4 weeks

期刊介绍： Bragantia é uma revista de ciências agronômicas editada pelo Instituto Agronômico da Agência Paulista de Tecnologia dos Agronegócios, da Secretaria de Agricultura e Abastecimento do Estado de São Paulo, com o objetivo de publicar trabalhos científicos originais que contribuam para o desenvolvimento das ciências agronômicas. A revista é publicada desde 1941, tornando-se semestral em 1984, quadrimestral em 2001 e trimestral em 2005. É filiada à Associação Brasileira de Editores Científicos (ABEC).