期刊
FOOD CHEMISTRY
卷 141, 期 4, 页码 3409-3414出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.foodchem.2013.06.066
关键词
Honey; Near infrared spectroscopy; Antioxidant properties; Modified partial least squares regression; Cross-validation
资金
- University of Vigo (Bolsas de Estadia en Centros de Investigacion)
The selection of antioxidant variables in honey is first time considered applying the near infrared (NIR) spectroscopic technique. A total of 60 honey samples were used to develop the calibration models using the modified partial least squares (MPLS) regression method and 15 samples were used for external validation. Calibration models on honey matrix for the estimation of phenols, flavonoids, vitamin C, antioxidant capacity (DPPH), oxidation index and copper using near infrared (NIR) spectroscopy has been satisfactorily obtained. These models were optimised by cross-validation, and the best model was evaluated according to multiple correlation coefficient (RSQ), standard error of cross-validation (SECV), ratio performance deviation (RPD) and root mean standard error (RMSE) in the prediction set. The result of these statistics suggested that the equations developed could be used for rapid determination of antioxidant compounds in honey. This work shows that near infrared spectroscopy can be considered as rapid tool for the nondestructive measurement of antioxidant constitutes as phenols, flavonoids, vitamin C and copper and also the antioxidant capacity in the honey. (C) 2013 Elsevier Ltd. All rights reserved.
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