| The calibration models for Brix in sugarcane initial-pressed juice were established and optimized by near infrared spectroscopy (NIR) and chemometrics method. In the paper, both the high Signal to Noise Ratio (SNR) spectra bands and feature combination wavelengths were selected, and the stability of the models were also discussed. Firstly, some methods of NIR experiment for sugarcane initial-pressed juice were studied. Then, a sort of classified method for the calibration and prediction samples was gotten, which based on predictive effect of the best single-point model with all samples. On this condition, the calibration models were established by single-point regression, direct PLS, PLS with Savitzky-Golay smoothing, moving window PLS, and moving window MLR with fixed interval, respectively. Then the models' parameters were designed according to RMSEP and Rp which were the optimum objective. Through a large number of computer experiments, the optimum models were selected out and the stability of models were also discussed.The results showed that the classified method for the calibration and prediction samples was representative, objective and stable; Savitzky-Golay smoothing can improve model's predictive accuracy greatly; Moving window PLS method can be used to select the high SNR spectra bands; Moving window MLR with fixed interval can be used to select combination wavelengths effectively and have the best predictive accuracy, so that the complexity of the model was reduced greatly. The RMSEP, RRMSEP and R_p for the best predictive effect of optimum models reached 0.2623°Bx, 1.27%, 0.9102, respectively. The results provided excellent and stable models for quantitative analysis Brix in sugarcane initial-pressed juice by NIR technology. It also provided an important basis for the design of high SNR spectrophotometric system with the small-scale NIR analyzer for measuring Brix in sugarcane initial-pressed juice.
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