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Understanding the combining ability of nutritional, agronomic and industrial traits in soybean F2 progenies.

Authors :
das Chagas, Paulo Henrique Menezes
Teodoro, Larissa Pereira Ribeiro
Santana, Dthenifer Cordeiro
Filho, Marcelo Carvalho Minhoto Teixeira
Coradi, Paulo Carteri
Torres, Francisco Eduardo
Bhering, Leonardo Lopes
Teodoro, Paulo Eduardo
Source :
Scientific Reports; 10/20/2023, Vol. 13 Issue 1, p1-15, 15p
Publication Year :
2023

Abstract

Obtaining soybean genotypes that combine better nutrient uptake, higher oil and protein levels in the grains, and high grain yield is one of the major challenges for current breeding programs. To avoid the development of unpromising populations, selecting parents for crossbreeding is a crucial step in the breeding pipeline. Therefore, our objective was to estimate the combining ability of soybean cultivars based on the F<subscript>2</subscript> generation, aiming to identify superior segregating parents and populations for agronomic, nutritional and industrial traits. Field experiments were carried out in two locations in the 2020/2021 crop season. Leaf contents of the following nutrients were evaluated: phosphorus, potassium, calcium, magnesium, sulfur, copper, iron, manganese, and zinc. Agronomic traits assessed were days to maturity (DM) and grain yield (GY), while the industrial traits protein, oil, fiber and ash contents were also measured in the populations studied. There was a significant genotype × environment (G × A) interaction for all nutritional traits, except for P content, DM and all industrial traits. The parent G3 and the segregating populations P20 and P27 can be used aiming to obtain higher nutritional efficiency in new soybean cultivars. The segregating populations P11 and P26 show higher potential for selecting soybean genotypes that combine earliness and higher grain yield. The parent G5 and segregant population P6 are promising for selection seeking improvement of industrial traits in soybean. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20452322
Volume :
13
Issue :
1
Database :
Complementary Index
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
173116154
Full Text :
https://doi.org/10.1038/s41598-023-45271-4