基于太赫兹时域光谱的大米品种识别研究

Identification of Rice Varieties Based on Terahertz Time Domain Spectroscopy

为实现大米品种的准确鉴别,提出一种基于太赫兹时域光谱(Terahertz Time-Domain Spectroscopy, THzTDS)技术的大米品种识别方法。利用标准差(Standard Deviation, SD)和区间偏最小二乘(Interval Partial Least Square, iPLS)选取0.53~1.21 THz波段的吸收光谱信息作为分类模型的输入数据,再采用决策树模型(Decision Tree, DT)对四种大米吸收光谱进行分类识别,并在模型训练过程中结合网格搜索算法寻找模型最优参数。为增加实验对比度,分别使用逻辑回归模型和支持向量机模型进行对比实验,其模型分类准确率分别为80.75%和88.75%。实验结果表明,太赫兹时域光谱技术结合SD、iPLS和DT方法可以实现大米品种的准确识别,准确率可达95%,为农产品品种识别提供了一种新的鉴别方法。

In order to achieve accurate identification of rice varieties,a rice variety identification method based on terahertz time-domain spectroscopy(THz-TDS)technology was proposed.To select the terahertz band by Interval partial least square(iPLS)and standard deviation(SD),which determined the absorption spectrum data of the 0.53~1.21 THz band as the input data of the classification model.Then to use the decision tree(DT)identified absorption spectra of four kinds of rice and the model parameters was obtained by combining with the grid search algorithm.In order to increase the experimental contrast,logistic regression models and support vector machine models were used separately for comparative experiments,and the model classification accuracy was 80.75%and 88.75%,respectively.Experimental results showed that the terahertz time-domain spectroscopy technology combined with SD,iPLS and DT methods can realize the accurate identification of rice varieties with an accuracy rate of up to 95%,providing a new identification method for the identification of agricultural varieties.