Determination of the Oxidative Stability of Camellia Oils Using a Chemometrics Tool Based on 1H NMR Spectra and α-Tocopherol Content

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Abstract
This study for the first time, predicted oxidative stability in camellia oils by partial least squares (PLS) built with proton nuclear magnetic resonance (1H NMR) and α-tocopherol content. The prediction models were established by the PLS method. Outlier detection, latent variables (LVs) optimization, data pre-processing and important variables selection were applied for models optimizing. All the developed models exhibited good performance as indicated by R2 greater than 0.895, RMSEE, RMSEP lower than 0.322 and 0.307. To verify the contribution of 1H NMR spectra and α-tocopherol for the prediction performance, PLS model with fatty acids composition instead of 1H NMR spectra and with only 1H NMR spectra as input variables were developed respectively. The results showed that the models of 1H NMR data-based were more accurate and precise than fatty acid composition data-based. And the performance of the models was significantly degraded without α-tocopherol as input variables.
Funding Information
  • National Natural Science Foundation of China (21866021, 31471647)
  • Natural Science Foundation of Jiangxi Province (20171ACB21015)
  • Jiangxi Province (20152ACF60012)

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