运用近红外光谱技术,通过不同光谱预处理和不同光谱波段选择,研究苹果品种(嘎啦、乔纳金、金冠、寒富)及货架期(0、14、28 d)的近红外判别模型。结果表明,不同品种苹果定标判别模型最优光谱预处理方法为：在全波长范围(408.8~2 492.8 nm)内,采用去散射结合二阶导数光谱预处理,对未知样品判别正确率为85.00%~95.00%;苹果货架期较优定标模型在1 108~2 492.8 nm范围内,光谱预处理方法为标准正常化处理(standard normal variate, SNV)+去散射处理(detrend, D)+一阶导数,预测样品正确率为91.67%~96.67%。实验证明,近红外光谱技术对采后苹果品种及货架期检测具有适用性。
The near-infrared discrimination model of apple varieties (Gala, Jonagold, Golden Delicious, Hanfu) and shelf life (0, 14, 28 d), which are using the near-infrared spectroscopy technology by means of different spectral pre-processing methods and different spectral bands selections were studied. The results showed that the optimal spectral pre-processing methods for different apple varieties was determined to be within the full wavelength range (408.8 to 4922.8 nm), derivative spectral pretreatment, the positive rate for unknown samples was 85.00% to 95.00%. Apple's shelf life optimal calibration model was in the range of 1108 to 2492.8 nm, and the spectral pretreatment method was standard normal variate(SNV)+ detrend (D)+ first derivative to predict the accuracy of the sample. The accuracy of the sample was from 91.37% to 96.67%. The results demonstrated that near-infrared spectroscopy has applicability to postharvest apple varieties and shelf life testing.
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