基于近红外漫反射检测的红枣定性分析模型中的预处理方法研究

Pretreatment methods of near infrared diffuse reflection spectra used for qualitative analysis of jujube

利用近红外漫反射光谱技术对红枣进行定性分析,针对病虫害果实问题,以马氏判据法建立定性分析模型,研究不同光谱预处理方法对光谱分析结果的影响。结果表明,利用原始光谱进行分类建模的正确性是87.08%,经过各种预处理后的校正和预测集均有提高,小波结合微分建模结果最优,准确率为96.67%。利用近红外技术进行红枣分类建模是可行的,且具有较高的识别准确度。

This work uses diffuse reflectance spectrum of NIR as sample to study the qualitative analysis of jujube,and classify infested and intact jujubes. The effects of different spectral pretreatment methods on the results of spectral analysis are studied. The results show that the combination of wavelet transform and derivative can effectively improve the accuracy of the near-infrared spectrum. The correctness of classification of original spectrum is 87. 08%,after data pretreatment in both calibration and prediction set. So the wavelet transform differential modeling result is best the accuracy is 96. 67%. NIR is illustrated could be applied to classify jujubes.