Abstract：In the study, a nondestructive and rapid method for detecting the water content of Chinese stir-fired pork was established by near infrared reflectance spectroscopy. The moisture contents of 100 groups of stir-fired pork samples were determined by direct drying method and near infrared spectra of the samples were acquired. The original spectra were pretreated by second derivative and Savitzky-Golay smoothing in order to perform a partial least squares regression. Then inflection point, Mahalanobis distance, root mean square error of cross-validation and studentized residual were used to eliminate the outliers in order to establish a calibration model. The results showed that the proposed predictive model had a high correlation coefficient (r = 0.972 1) with a root mean squared error of calibration of 0.089 1. Furthermore, the prediction accuracy was greater than 98.7% (P < 0.05) when compared with the true value indicating the model established in this study has a good predictive performance. The results showed that the model allows accurate prediction of water content and has the potential for use in Chinese stir-fired pork processing and food industry.
赵钜阳，石长波，方伟佳. 基于近红外光谱仪分析中式爆炒猪肉的水分含量[J]. 肉类研究, 2018, 32(7): 42-47.
ZHAO Juyang, SHI Changbo, FANG Weijia. Detection of Water Content of Chinese Stir-Fired Pork by Near Infrared Spectroscopy. Meat Research, 2018, 32(7): 42-47.
2018, Vol. 32 
