title: Support vector regression-guided unravelling: antioxidant capacity and quantitative structure-activity relationship predict reduction and promotion effects of flavonoids on acrylamide formation.
abstract: We used the support vector regression (SVR) approach to predict and unravel reduction/promotion effect of characteristic flavonoids on the acrylamide formation under a low-moisture Maillard reaction system. Results demonstrated the reduction/promotion effects by flavonoids at addition levels of 1-10000 μmol/L. The maximal inhibition rates (51.7%, 68.8% and 26.1%) and promote rates (57.7%, 178.8% and 27.5%) caused by flavones, flavonols and isoflavones were observed at addition levels of 100 μmol/L and 10000 μmol/L, respectively. The reduction/promotion effects were closely related to the change of trolox equivalent antioxidant capacity (ΔTEAC) and well predicted by triple ΔTEAC measurements via SVR models (R: 0.633-0.900). Flavonols exhibit stronger effects on the acrylamide formation than flavones and isoflavones as well as their O-glycosides derivatives, which may be attributed to the number and position of phenolic and 3-enolic hydroxyls. The reduction/promotion effects were well predicted by using optimized quantitative structure-activity relationship (QSAR) descriptors and SVR models (R: 0.926-0.994). Compared to artificial neural network and multi-linear regression models, SVR models exhibited better fitting performance for both TEAC-dependent and QSAR descriptor-dependent predicting work. These observations demonstrated that the SVR models are competent for predicting our understanding on the future use of natural antioxidants for decreasing the acrylamide formation.
authors: Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang R &D Center for Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China.|Department of Food Science and Nutrition, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China.
authors: Mengmeng
authors: M
authors: Huang
authors: Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang R &D Center for Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China.|Department of Food Science and Nutrition, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China.
authors: Yan
authors: Y
authors: Wei
authors: Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang R &D Center for Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China.|Department of Food Science and Nutrition, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China.
authors: Jun
authors: J
authors: Wang
authors: Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang R &D Center for Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China.|Department of Food Science and Nutrition, College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, Zhejiang, China.
authors: Yu
authors: Y
authors: Zhang
mesh_terms: D020106:Acrylamide / Q000737:chemistry*; D000975:Antioxidants / Q000737:chemistry*; D005419:Flavonoids / Q000737:chemistry*; D006027:Glycosides / Q000737:chemistry*; D017665:Hydroxyl Radical / Q000737:chemistry; D016014:Linear Models; D015416:Maillard Reaction; D010084:Oxidation-Reduction; D021281:Quantitative Structure-Activity Relationship; D060388:Support Vector Machine
chemical_list: D000975:Antioxidants; D005419:Flavonoids; D006027:Glycosides; D020106:Acrylamide; D017665:Hydroxyl Radical