Diversity Analysis and Comprehensive Evaluation of 101 Soybean (Glycine max L.) Germplasms Based on Sprout Quality Characteristics.

IF 4.7 2区 农林科学 Q1 FOOD SCIENCE & TECHNOLOGY
Foods Pub Date : 2024-11-04 DOI:10.3390/foods13213524
Xiaoyan Zhang, Gufeng Wu, Yuhe Wu, Ning Tang, Lu Huang, Dongqing Dai, Xingxing Yuan, Chenchen Xue, Xin Chen
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引用次数: 0

Abstract

Soybean sprouts are a common culinary vegetable due to their high nutrition and tasty flavors. To select soybean varieties with excellent sprout quality, 101 soybean materials were collected from different regions of China, and eight sprout quality parameters were determined for overall evaluation. The results showed that eight sprout quality parameters achieved varying degrees of difference and correlation. Based on the principal component analysis (PCA), three principal components were extracted, with a cumulative contribution rate of 78.314%. Further, the comprehensive evaluation value (D) of soybean sprout quality was calculated by membership function analysis based on PCA, and the quality of soybean sprouts was ranked accordingly. Subsequently, a regression equation for the prediction of soybean sprout quality was established using a stepwise regression analysis, and the model showed a good prediction performance (correlation coefficient of prediction > 0.8; residual predictive deviation > 2.0). On these grounds, it was proposed that the quality of soybean sprouts could be comprehensively predicted by four parameters: hypocotyl length, edible rate, 100-seed weight, and total isoflavone content and saponin content. In conclusion, this study provides excellent varieties for soybean sprout production and new variety breeding, and it provides an important reference for the prediction of soybean sprout quality.

基于萌芽质量特性的 101 个大豆(Glycine max L. )种质的多样性分析和综合评价。
黄豆芽营养丰富、味道鲜美,是一种常见的烹饪蔬菜。为选育出芽质优良的大豆品种,从中国不同地区收集了 101 份大豆材料,并测定了 8 个芽质参数进行综合评价。结果表明,8 个芽质参数存在不同程度的差异和相关性。根据主成分分析(PCA),提取出三个主成分,累计贡献率为 78.314%。然后,基于 PCA,通过成员函数分析计算出黄豆芽质量的综合评价值(D),并据此对黄豆芽的质量进行排序。随后,利用逐步回归分析法建立了预测黄豆芽质量的回归方程,该模型显示出良好的预测性能(预测相关系数大于 0.8;残差预测偏差大于 2.0)。据此,提出可以通过下胚轴长度、可食率、百粒重、总异黄酮含量和皂苷含量这四个参数来综合预测大豆芽的品质。总之,本研究为大豆芽菜生产和新品种选育提供了优良品种,为预测大豆芽菜品质提供了重要参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Foods
Foods Immunology and Microbiology-Microbiology
CiteScore
7.40
自引率
15.40%
发文量
3516
审稿时长
15.83 days
期刊介绍: Foods (ISSN 2304-8158) is an international, peer-reviewed scientific open access journal which provides an advanced forum for studies related to all aspects of food research. It publishes reviews, regular research papers and short communications. Our aim is to encourage scientists, researchers, and other food professionals to publish their experimental and theoretical results in as much detail as possible or share their knowledge with as much readers unlimitedly as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, unique features of this journal: Ÿ manuscripts regarding research proposals and research ideas will be particularly welcomed Ÿ electronic files or software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material Ÿ we also accept manuscripts communicating to a broader audience with regard to research projects financed with public funds
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