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Seed phenotype and maturity groups as determinants of protein, oil, and fatty acid composition patterns in diverse soybean germplasm

文献类型： 外文期刊

作者： Abdelghany, Ahmed M. 1 ; Zhang, Shengrui 1 ; Li, Jing 1 ; Li, Bin 1 ; Sun, Junming 1 ;

作者机构： 1.Chinese Acad Agr Sci, State Key Lab Crop Gene Resources & Breeding, MARA Key Lab Soybean Biol Beijing, Natl Engn Lab Crop Mol Breeding,Inst Crop Sci, 12 Zhongguancun South St, Beijing 100081, Peoples R China

2.Damanhour Univ, Fac Agr, Dept Crop Sci, Damanhour, Egypt

关键词： Glycine max; Seed composition; Seed coat color; Seed weight; Maturity groups; Multivariate analysis

期刊名称：BMC PLANT BIOLOGY （ 影响因子：4.8； 五年影响因子：5.4 ）

ISSN： 1471-2229

年卷期： 2025 年 25 卷 1 期

页码：

收录情况： SCI

摘要： Soybean seed physical characteristics are crucial for quality assessment, but the link between these characteristics and biochemical composition across different maturity groups (MGs) remains unclear. This study examined the relationships between seed physical characteristics (color and weight) and biochemical constituents, including oil content (OC), protein content (PC), and fatty acid (FA) composition in 191 diverse soybean accessions across eight MGs (0-VII) at three locations over two years. The results indicated that black-seeded accessions demonstrated a notably higher average of PC (47.33%) and a lower average of OC (15.78%) in contrast to yellow-seeded varieties, which had an average PC and OC of 42.52% and 19.12%, respectively. In addition, larger seeds exhibited increased OC (19.15%) and OA levels (23.27%), whereas smaller seeds revealed higher concentrations of PC (44.23%), LA (55.06%), and LNA (8.53%). Multivariate analyses, including principal component analysis, clustering heatmap, and radar plot, demonstrated distinct clustering patterns, exhibiting unique compositional profiles closely linked to seed physical characteristics. Furthermore, MGs exhibited notable correlations with LNA (R-2 = 0.238) and OC (R-2 = 0.233), especially in black-seeded and large-seeded accessions. These findings elucidate the complex interaction between seed physical traits and biochemical composition, presenting significant implications for soybean breeding programs aimed at specific quality attributes.

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