[Visible/NIR analysis of fat, protein and water in chilled pork].

Fat, protein and water were determined by visible and NIR transmittance spectroscopy in chilled pork. After preprocessed by multiplicative scatter correction (MSC), the quantitative analysis models were developed based on the original, first derivative and second derivative spectra by using partial least squares (PLS) at the temperatures of 0-4 degrees C and 20 degrees C, respectively. By comparing the correlation coefficient (r), RMSEC, and SEP, we found that the first derivative model was the best, and the performance for 0-4 degrees C was better than that for 20 degrees C. At 0-4 degrees C and 20 degrees C, the correlation coefficients were 0.950 and 0.924 for fat, 0.713 and 0.455 for protein and 0.944 and 0.914 for water respectively, SEP values were 2.41 and 2.95 for fat, 5.44 and 4.25 for protein, and 2.37 and 2.38 for water respectively. The results showed that the visible and NIR analysis could measure the fat and water contents in chilled pork well, but was bad for protein, and this was caused by processing line of chilled pork. What's more, the spectrum offset was found in the original spectra at about 770 nm to be about 10 nm.

[Online detection of soluble solids content of pear by near infrared transmission spectrum].

The research was to detect soluble solids content (SSC) of pear online by near infrared transmission spectrum. The movement speed of pear was 0.5 m x s(-1) the power of light source was 300 W, and semi-transmission was used to collect the spectrum of pears. The total experiment samples were 187 pears, with a calibration set of 147 pears and a validation set of 40 pears. Partial least squares (PLS) and principal component regression (PCR) technique were used to develop the calibration model for online detection. Spectral ranges of 550-700 nm, 700-850 nm, 550-850 nm were used to establish the calibration models, and it was found that the model with 550-850 nm was better than others whether for PLS or for PCR. Also, the models based on different pretreatment methods such as Savitzky-Golay smooth, first derivative, second derivative and so on were compared, and the result showed that the five point Savitzky-Golay smooth could increase S/N ratio and improve performance of the model, whereas first derivative and second derivative could do little to improve performance of the model. The best model had the satisfactory calibration and prediction abilities, with the correlation coefficient (Rc) = 0.948 8, root mean square error of calibration (RMSEC) = 0.236 and root mean square error of validation (RMSEP) = 0.548. The result in this study shows that the detection of SSC of pear online is feasible.