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中文摘要：
利用近红外漫反射光谱测定法获取了完整雪青梨的近红外光谱（12 500～4 000cm^-1），采用多元校正算法偏最小二乘法（PLS）方法，选取不同的波段范围对漫反射光谱进行有效信息提取和分析，得出了不同因子数时PLS方法进行酸度分析的结果及其因子数与交互有效检验标准偏差（RMSECV）关系，确定了最佳回归的因子数和用于定量分析的最佳波段范围。实验结果表明：校正模型的预测精度在5 452～12 285cm^-1波段范围内，最佳主因子数为7时，雪青梨总酸的预测精度最好，其预测集的相关系数达到了0.79，预测标准偏差为0.0186。
英文摘要：
Fourier transform near infrared（FT-NIR） spectrum of intact Xueqing pear was obtained by diffusion reflectance. Partial least squares （PLS） regression was carried out, describing the relationships between the data sets of laboratory data and the FT-NIR spectra. ＇Different wave number ranges were chosen for regression and spectral information abstraction. The 3D-curves were shown for different factors, root mean square errors of cross validation （RMSECV）, and prediction residual sum of squares （PRESS）. Analysis results show that the best calibration model gave the relative high correlation coefficient of 0.79 and the low standard errors of prediction of 0.019 when the best wave number range was 5 452-12 285 cm^-1 and the best factor was 7. The method of selecting advantageous wavelength ranges is feasible to obtain high prediction precision.
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