期刊
JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
卷 61, 期 3, 页码 540-546出版社
AMER CHEMICAL SOC
DOI: 10.1021/jf305272s
关键词
near-infrared spectroscopy; comparative chemometrics; prediction: sugar, acid and phenol content; Chinese hawthorn fruit
资金
- Chinese National Natural Science Foundation [NSFC-21065007]
- State Key Laboratory of Food Science and Technology of Nanchang University [SKLF-MB-201002, SKLF-TS-200919]
Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var, major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.
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