Prediction of fatty acid composition in camellia oil by 1H NMR combined with PLS regression

被引：63

作者：

Zhu, MengTing ^{[1
]}

Shi, Ting ^{[1
]}

Chen, Yi ^{[1
]}

Luo, ShuHan ^{[1
]}

Leng, Tuo ^{[1
]}

Wang, YangLing ^{[1
]}

Guo, Cong ^{[1
]}

Xie, MingYong ^{[1
]}

机构：

[1] Nanchang Univ, State Key Lab Food Sci & Technol, Nanchang 330047, Jiangxi, Peoples R China

来源：

FOOD CHEMISTRY | 2019年 / 279卷

基金：

中国国家自然科学基金;

关键词：

Camellia oil; Fatty acid composition; PLS; H-1; NMR; VIRGIN OLIVE OILS; CHEMOMETRIC ANALYSIS; GAS-CHROMATOGRAPHY; SEED OILS; SPECTROSCOPY; METABOLOMICS; DISCRIMINATION; CLASSIFICATION; ADULTERATION; MULTIVARIATE;

D O I：

10.1016/j.foodchem.2018.12.025

中图分类号：

O69 [应用化学];

学科分类号：

081704 ;

摘要：

A rapid method for the determination of fatty acid (FA) composition in camellia oils was developed based on the H-1 NMR technique combined with partial least squares (PLS) method. Outliers detection, LVs optimization and data pre-processing selection were explored during the model building process. The results showed the optimal models for predicting the content of C18:1, C18:2, C18:3, saturated, unsaturated, monounsaturated and polyunsaturated FA were achieved by Pareto scaling (Par) pretreatment, with correlation coefficient (R-2) above 0.99, the root mean square error of estimation and prediction (RMSEE, RMSEP) lower than 0.954 and 0.947, respectively. Mean-centering (Ctr) was more suitable for the model of C16:0 and C18:0 with the best performance indicators (R-2 >= 0.945, RMSEE <= 0.377, RMSEP <= 0.212). This study indicated that H-1 NMR has the potential to be applied as a rapid and routine method for the analysis of FA composition in camellia oils.

引用

页码：339 / 346

页数：8

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