Prediction of peanut protein solubility based on the evaluation model established by supervised principal component regression

doi:10.1016/j.foodchem.2016.09.091

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	Prediction of peanut protein solubility based on the evaluation model established by supervised principal component regression
	Wang, Li 1; Liu, Hongzhi 2; Liu, Li 2; Wang, Qiang 2; Li, Shurong 1; Li, Qizhai3
	2017-03-01
发表期刊	FOOD CHEMISTRY
ISSN	0308-8146
卷号	218 页码:553-560
摘要	Supervised principal component regression (SPCR) analysis was adopted to establish the evaluation model of peanut protein solubility. Sixty-six peanut varieties were analysed in the present study. Results showed there was intimate correlation between protein solubility and other indexes. At 0.05 level, these 11 indexes, namely crude fat, crude protein, total sugar, cystine, arginine, conarachin I, 37.5 kDa, 23.5 kDa, 15.5 kDa, protein extraction rate, and kernel ratio, were correlated with protein solubility and were extracted to for establishing the SPCR model. At 0.01 level, a simper model was built between the four indexes (crude protein, cystine, conarachin I, and 15.5 kDa) and protein solubility. Verification results showed that the coefficients between theoretical and experimental values were 0.815 (p < 0.05) and 0.699 (p < 0.01), respectively, which indicated both models can forecast the protein solubility effectively. The application of models was more convenient and efficient than traditional determination method. (C) 2016 Elsevier Ltd. All rights reserved.
关键词	Prediction Peanut protein solubility Supervised principal component analysis Evaluation model
DOI	10.1016/j.foodchem.2016.09.091
语种	英语
资助项目	Special National Key Research and Development Plan[2016YFD0400205] ; Special National Key Research and Development Plan[2016YFD0400201]
WOS研究方向	Chemistry ; Food Science & Technology ; Nutrition & Dietetics
WOS类目	Chemistry, Applied ; Food Science & Technology ; Nutrition & Dietetics
WOS记录号	WOS:000386409700072
出版者	ELSEVIER SCI LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/23864
专题	系统科学研究所
通讯作者	Wang, Qiang
作者单位	1.Beijing Vocat Coll Agr, Dept Food & Biol Engn, Beijing 102442, Peoples R China 2.Chinese Acad Agr Sci, Inst Food Sci & Technol, Comprehens Key Lab Agr Prod Proc & Qual Control, Minist Agr, Beijing 100193, Peoples R China 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Wang, Li,Liu, Hongzhi,Liu, Li,et al. Prediction of peanut protein solubility based on the evaluation model established by supervised principal component regression[J]. FOOD CHEMISTRY,2017,218:553-560.
APA	Wang, Li,Liu, Hongzhi,Liu, Li,Wang, Qiang,Li, Shurong,&Li, Qizhai.(2017).Prediction of peanut protein solubility based on the evaluation model established by supervised principal component regression.FOOD CHEMISTRY,218,553-560.
MLA	Wang, Li,et al."Prediction of peanut protein solubility based on the evaluation model established by supervised principal component regression".FOOD CHEMISTRY 218(2017):553-560.