Abstract：The objective of this work was to investigate the potential of Fourier transform near infrared reflectance (FT-NIR) spectroscopy and chemometrics methods to rapidly determine tuna meat freshness. NIR spectra of meat cuts from different tuna species stored for different durations were recorded in the wavenumber range of 4000‒12000 cm-1 and preprocessed for the establishment of a quantitative model to predict K value, thiobarbituric acid (TBA) value, metmyoglobin (MetMb) content, pH, L* value and a* value of tuna meat using partial least squares regression (PLSR) method. The results indicated that all above parameters could be predicted quickly and accurately by the developed models with correlation coefficients of calibration set (RC) of 0.876 7, 0.908 7, 0.893 7, 0.753 2, 0.815 0 and 0.723 2, and root mean square errors of cross validation (RMSECV) of 3.641 1, 0.654 8, 4.700 9, 0.053 4, 1.286 3 and 1.317 3, respectively. The models were validated using an external test set and T-test. It was found that no significant difference existed between the predicted values and the actual values (P > 0.05). Accordingly, the models were reliable and could be used to predict the freshness of tuna meat.
陶 瑞，史智佳，贡 慧，杨 震，刘 梦，王 辉. 傅里叶变换近红外光谱技术快速检测金枪鱼新鲜度[J]. 肉类研究, 2017, 31(4): 43-49.
TAO Rui, SHI Zhijia, GONG Hui, YANG Zhen, LIU Meng, WANG Hui. Rapid Determination of Tuna Meat Freshness Based on Fourier Transform Near Infrared Reflectance Spectroscopy (FT-NIR). Meat Research, 2017, 31(4): 43-49.
