主成分分析
风味
化学
偏最小二乘回归
电子鼻
葡萄酒
泰勒瓦
食品科学
色谱法
统计
数学
人工智能
计算机科学
作者
Xin Ren,Sixuan Li,Min Zhang,Lina Guan,Wenxin Han
摘要
Abstract Background and Objectives The eating quality of fresh instant rice differ significantly owing to its geographical origins. However, the method of geographical discrimination is still lacking. In this study, the determination of flavor profiles and multivariate statistical analysis have been applied for discriminating the geographical origins of 18 fresh instant rice from three provinces in Northeast China. Findings The principal component analysis (PCA) of electronic nose (E‐nose) data could rapidly distinguish the samples from three different provinces. The solid phase microextraction‐gas chromatograph‐mass spectrometer (SPME‐GC‐MS) results of samples from different provinces were clearly distinguished in PCA and hierarchical cluster analysis (HCA). The orthogonal partial least squares discriminant analysis (OPLS‐DA) model showed good discriminating ability ( R 2 = 0.894, Q 2 = 0.845, and accuracy = 1.0). Nonanal, 2,4‐di‐tert‐butylphenol, 2,3‐dihydro‐benzofuran, 2‐pentylfuran, indole, pentadecane, 2‐pentadecanone, trans‐farnesol, isopropyl palmitate, and farnesyl acetone were identified as 10 marker compounds. Moreover, their good discrimination was verified in an additional nine samples. Conclusions The strategy of applying flavor profiles for discriminating the geographical origin of fresh instant rice has been proven to be an efficient and non‐destructive method. Significance and Novelty Our study is helpful to control the quality of fresh instant rice and provides a methodological reference for the geographical discrimination of foods.
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