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Optimization of conventional extraction and multivariate metabolite profiling of soybean seeds (Glycine max L. Merrill) for enhanced isoflavones and antioxidant properties

Authors
Park, Dong HyunKwak, Youn-SigChoi, KihyuckChung, Eui-HwanKim, Jeong-SeonPark, Jong-HwanKim, Du HyunLee, Jin Hwan
Issue Date
Apr-2026
Publisher
Elsevier BV
Keywords
Soybean; Isoflavone; Optimal conventional extraction; Antioxidant activity; UPLC-Q-TOF-MS/MS; Metabolite; Multivariate analysis
Citation
Food Chemistry, v.507
Indexed
SCIE
SCOPUS
Journal Title
Food Chemistry
Volume
507
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/82396
DOI
10.1016/j.foodchem.2026.148237
ISSN
0308-8146
1873-7072
Abstract
This study presents a comprehensive investigation of fluctuations in isoflavone contents and antioxidant properties of soybean seeds under various conventional extraction parameters, including solvent, time, temperature, and pH. Both individual and total isoflavones varied considerably throughout different extraction conditions. The optimal method was established using 50% methanol (pH 7) at 50 degrees C for 30 h, yielding 3078.4 mu g/g, with the following composition: glucosides (1559.1 mu g/g, 50.6%) > malonylglucosides (1426.3 mu g/g, 46.3%) > acetylglucosides (86.6 mu g/g, 2.8%) > aglycones (6.4 mu g/g, 0.2%). Moreover, multivariate analyses (PCA and heatmap) confirmed that solvent and temperature predominantly influenced isoflavone clustering. Isoflavone glucosides showed higher levels with increasing temperature (25 -> 65 degrees C; 414.1 -> 1878.6 mu g/g) and pH (1 -> 7; 1138.6 -> 1559.1 mu g/g), whereas malonylglucosides were more abundant with increasing solvent concentrations (10 -> 50% methanol; 301.6 -> 2117.1 mu g/g) and times (6 -> 30 h; 1994.8 -> 2358.3 mu g/g). The optimized extract exhibited potent, dose-dependent antioxidant abilities, ranked as follows: DNA protection (91.6% at 75 mu g/mL) > ABTS (95.8% at 500 mu g/mL) > DPPH (53.8% at 1000 mu g/mL) > FRAP (0.45 OD593nm at 2000 mu g/mL). Specifically, metabolite profiling of this extract using UPLC-Q-TOF-MS/MS identified 33 metabolites (isoflavone, soyasaponin, alkaloid, lipid, terpene, and flavonoid derivatives). These findings suggest that metabolite composition plays an important role in determining the bifunctional properties of soybean, highlighting the integration of multivariate analysis and UPLC-Q-TOF-MS/MS profiling under varied conditions.
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