The Fourier transform near infrared spectroscopy (FT-NIR) analysis technology was used to establish the calibration model based on partial least squares (PLS) for the measurement and predication of Antarctic krill meal samples. The feasibility and accuracy of calibration model for predicting moisture, fat and protein content in atarctic krill meal samples was explored in this study. The result showed that the optimal pretreatment method for the NIR spectra was standard normal variate transform (SNV)+ first derivative (FD)+ Norris derivative filter (NDF). Compared with the original samples, root mean square error of cross validation (RMSECV), root mean square error of external prediction (RMSEP) and the ratio of the RMSEP to standard deviation of reference data in the prediction (RPDEV) of the calibration model of mixed samples were improved. After pretreatment, the correlation coefficient in calibration (RC), the correlation coefficient in cross validation (RCV) and correlation coefficient in external validation (REV) of the calibration model was above 0.94. However, the REV of the fat was 0.905 8 and RPD was above 2.5. Therefore, NIR technology can be used to quickly, conveniently and accurately determine the moisture, fat and protein content of shrimp meal. This study provided reference data for the onboard application of near infrared spectroscopy (NIR) technology for rapid determination of the quality of antarctic krill meal.
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