关键词: 大鲵肉粉, 掺伪鉴别, 纯度检测, 近红外光谱, 偏最小二乘法

Abstract: In this paper, the adulteration and purity detection of Chinese giant salamander (Andrias davidianus) meat powder were investigated based on near infrared spectroscopy. Infrared spectra of authentic Chinese giant salamander meat powder and adulterated samples with longsnout catfish meat powder, grass carp meat powder or potato starch (40 samples each, 160 samples in total) were collected. After spectral preprocessing, qualitative discrimination models between pure and adulterated samples and among pure sample and adulterated samples with longsnout catfish, grass carp and potato starch) were established by partial least square discriminant analysis (PLS-DA). Partial least squares regression (PLSR) was used to establish a quantitative calibration model for the purity of the three adulterated samples. The results showed that the PLSDA qualitative models with first derivative + multiplicative scatter correction (MSC) spectral preprocessing had the best performance in discriminating the authentic and adulterated samples with 100% predictive accuracy for the calibration and prediction sets. For the PLSR quantitative models of adulteration of longsnout catfish, grass carp and potato starch, the correlation coefficients of the calibration set (Rc 2) were 0.990 6, 0.986 4, and 0.993 3, respectively, and the root mean square errors of calibration (RMSEC) were 1.14%, 1.39%, and 0.88%, respectively. The correlation coefficients of the prediction set (Rp 2) were 0.994 4, 0.992 4, and 0.990 8, respectively, and the root mean squared error of prediction (RMSEP) was 0.83%, 0.89%, and 1.22%, respectively. These results suggest that near infrared spectroscopy combined with chemometrics could be used for adulteration and purity detection of Chinese giant salamander meat powder.

Key words: giant salamander meat powder, adulteration identification, purity detection, near-infrared spectroscopy, partial least square