Literature DB >> 24491728

Isoflavones profiling of soybean [Glycine max (L.) Merrill] germplasms and their correlations with metabolic pathways.

Jae Kwang Kim1, Eun-Hye Kim2, Inmyoung Park3, Bo-Ra Yu2, Jung Dae Lim4, Young-Sang Lee5, Joo-Hyun Lee2, Seung-Hyun Kim2, Ill-Min Chung6.   

Abstract

The isoflavone diversity (44 varieties) of the soybean, Glycine max (L.) Merrill, from China, Japan, and Korea was examined by high-performance liquid chromatography. The profiles of 12 isoflavones identified from the grains were subjected to data-mining processes, including partial least-squares discriminant analysis (PLS-DA), Pearson's correlation analysis, and hierarchical clustering analysis (HCA). Although PLS-DA did not reveal significant differences among extracts of soybean from 3 countries, the results clearly show that the variation between varieties was low. The CS02554 variety was separate from the others in the first 2 principal components of PLS-DA. HCA of these phytochemicals resulted in clusters derived from closely related biochemical pathways. Daidzin, genistin, and glycitin contents were significantly correlated with their respective malonyl glycoside contents. Daidzein content correlated positively with genistein content (r=0.8189, P<0.0001). The CS02554 variety appears to be a good candidate for future breeding programs, as it contains high levels of isoflavone compounds. These results demonstrate the use of metabolite profiling combined with chemometrics as a tool for assessing the quality of food and identifying metabolic links in biological systems.
Copyright © 2013 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Chemometrics; Correlation; Glycine max; Isoflavone; Partial least squares discriminant analysis; Soybean

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Substances:

Year:  2013        PMID: 24491728     DOI: 10.1016/j.foodchem.2013.12.066

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  4 in total

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Authors:  Lixin Lin; Yunjia Wang; Jiyao Teng; Xuchen Wang
Journal:  Environ Monit Assess       Date:  2016-01-17       Impact factor: 2.513

Review 2.  Multi-Omics Techniques for Soybean Molecular Breeding.

Authors:  Pan Cao; Ying Zhao; Fengjiao Wu; Dawei Xin; Chunyan Liu; Xiaoxia Wu; Jian Lv; Qingshan Chen; Zhaoming Qi
Journal:  Int J Mol Sci       Date:  2022-04-30       Impact factor: 6.208

3.  Origin, Maturity Group and Seed Coat Color Influence Carotenoid and Chlorophyll Concentrations in Soybean Seeds.

Authors:  Berhane Sibhatu Gebregziabher; Shengrui Zhang; Suprio Ghosh; Abdulwahab S Shaibu; Muhammad Azam; Ahmed M Abdelghany; Jie Qi; Kwadwo G Agyenim-Boateng; Honey T P Htway; Yue Feng; Caiyou Ma; Yecheng Li; Jing Li; Bin Li; Lijuan Qiu; Junming Sun
Journal:  Plants (Basel)       Date:  2022-03-23

Review 4.  Exploiting Phenylpropanoid Derivatives to Enhance the Nutraceutical Values of Cereals and Legumes.

Authors:  Sangam L Dwivedi; Hari D Upadhyaya; Ill-Min Chung; Pasquale De Vita; Silverio García-Lara; Daniel Guajardo-Flores; Janet A Gutiérrez-Uribe; Sergio O Serna-Saldívar; Govindasamy Rajakumar; Kanwar L Sahrawat; Jagdish Kumar; Rodomiro Ortiz
Journal:  Front Plant Sci       Date:  2016-06-03       Impact factor: 5.753

  4 in total

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