[Study on Characteristic Bands Selection of Lamb pH Value Based on Hyperspectral Imaging and Partial Least Squares(PLS)].

Characteristic bands method selection and subsequent spectral extraction has a great influence on the hyperspectral model performance. For rapid and accurate detection of mutton pH value, the effects of 2 band-selection methods on PLS models of mutton pH based on HSI technique were carried out and discussed. Initially, the preprocessing method of second derivative (2D), multiplicative scatter correction (MSC) and mean-centering together was implemented on the representative spectra of mutton muscle portion. Then, 2 methods of synergy interval partial least square (siPLS) and the combination of synergy interval partial least squares with genetic algorithm (siPLS-GA) were used to extract the characteristic bands in the spectral range of 473～1 000 nm. Finally, 2 PLS models of lamb pH value were established with the corresponding characteristic bands, and were also compared with the effect of full-band PLS model. The results indicated that the effect of siPLS-GA-PLS model was the best. As for the siPLS-GA-PLS model, 56 characteristic wavelength points were chosen, the correlation coefficient(Rcal) and root mean square error(RMSEC) of calibration set was 0.96 and 0.043 respectively, and the correlation coefficient(Rp) and root mean square error(RMSEP) of prediction set was 0.96 and 0.048 respectively. Spectral variables were reduced and model accuracy was improved. It can be concluded that characteristic bands selection and rapid and accurate detection of lamb pH can be achieved using hyperspectral imaging technique combined with siPLS-GA method.