小麦PLS近红外定量分析中温度修正的研究

以45个小麦籽粒为实验样品，研究样品温度对小麦PLS近红外定量分析的影响, 并提出引入温度修正量对样品光谱进行修正的方法。采用PLS算法将光谱受温度影响部分剔除后，得到不受温度影响的光谱，再进行模型建立与样品分析。实验结果表明：引入温度修正可以有效的消除温度对模型预测结果的影响，从而提高模型的稳定性及应用范围。

Study of Temperature Correction in the PLS Near-Infrared Quantitative Analysis of the Wheat

The influence of sample temperature on the wheat PLS near infrared(NIR)quantitative analysis was studied with 45 wheat seeds.The original spectra of the wheat seeds were measured at different temperatures.The temperature corrections were subtracted from the original spectra of the samples by using the PLS algorithm.The corrected spectra were used to build the mathematical model of the near-infrared quantitative analysis of the wheat.The results show that the influence of sample temperature on the mathematical model can be eliminated effectively when the temperature correction was performed in the calculation,improving the stability and prediction of this mathematical model.