AI Article Synopsis
- The study focused on differentiating Chinese rice wines based on their ageing time and brand using profiles of 16 free amino acids determined through HPLC-DAD.
- Multivariate analyses, including PCA and PLS-DA, were applied to classify the wines, achieving high classification rates of 99.7% for ageing times and 94.9% for brands.
- This method offers an efficient approach to identifying mislabeling in rice wines.
Article Abstract
Discrimination of Chinese rice wines according to ageing time and brand using amino acid profiles was presented in this study. Free amino acids (16) in 98 rice wines were simultaneously determined using high-performance liquid chromatograph-diode array detection (HPLC-DAD). Then the experimental data was subjected to multivariate analysis. Principal component analysis (PCA) was employed to differentiate samples from various ageing times (3, 9, 11 and 15months) and brands ("pagoda", "kuaijishan", and "guyuelongshan"). Partial least square discriminant analysis (PLS-DA) and full (leave-one-out) cross-validation were used to develop classification models. The overall correct classification rate for different ageing times and brands was 99.7% and 94.9%, respectively. The proposed method shows an effective strategy for the detection of mislabelling of rice wines.
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| http://dx.doi.org/10.1016/j.foodchem.2011.04.062 | DOI Listing |
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