基于近红外光谱的番茄黄化曲叶病抗病性识别研究

Study of Identifying Tomato Yellow Leaf Curl Disease Resistance Based on Nearinfrared Spectroscopy Analysis Technique

使用传统的聚合酶链反应技术检测番茄(Lycopersicon esculentum Mill.)植株是否有黄化曲叶病的抗病基因,进而确定植株是否具有抗病性;采集鉴定后的植株叶片的近红外漫反射光谱,采用多种方法对原始光谱进行预处理,并将不同预处理后的数据以及原始光谱作为输入,利用支持向量机建立抗病性的识别模型。采用标准正态变量变换和去趋势算法预处理后所建立的模型对预测集的识别准确率可以达到96.153 8%。表明通过近红外光谱技术可以识别番茄植株对黄化曲叶病是否具有抗病性。

Gene of tomato（Lycopersicon esculentum Mill.） yellow leaf curl disease resistance has been detected by using polymerase chain reaction. This method is widely used to determine the disease resistance of tomato plants. The near-infrared diffuse reflectance spectroscopy of the identified samples was collected. Then the original data and the data preprocessed by different methods are used as the input of Support Vector Machine（SVM） to build the model to judge whether a tomato plant is resistant to the disease. Experimental results show that the model which used the correction method of Standard Normal Variate and Detrending had the best performance and the recognition accuracy of the test set can reach 96.15 3 8%. The result proves that it is feasible to identify the resistance of Tomato Yellow Leaf Curl Disease by Near Infrared Spectroscopy.