利用叶绿素荧光光谱分析技术研究温室黄瓜蚜虫害的侵染及发生等级。 从光谱形态的角度建立监测特征点, 确定F632波段强度值作为健康与蚜虫害叶片的第一特征点, F512～F632光谱曲线的变化速率K值作为第二特征点, 对于符合特征点的植株进行及早预警。 采用最小二乘支持向量机数据挖掘方法的径向基核函数建立蚜虫害的侵染及发生等级模型, 通过对比不同峰谷值所在波段对于蚜虫害的分类准确率和预测准确率, 确定采用F632波段建立模型, 它的预测能力达到96.34%。

The infection and degree of cucumber aphis pests was studied by analyzing chlorophyllfluorescence spectrum in greenhouse. Based on the configuration of the spectrum, characteristic points were established, in which the intensity of waveband F632 was the first characteristic point between healthy and aphis pests leaves. The second characteristic point was K which was the change rate of spectral curve from waveband F512 to F632. The early warning could be executed on plants depending on these two points. The models of the infection and degrees of aphis pests were established for different wavebands by the least square support vector machine classification method (LSSVMR) radial basis function(RBF). The accuracy rate of classification and prediction of the models was compared by different peaks and valleys value in wavebands. The results indicated that the prediction accuracy of the model established by waveband F632 was the most perfect (96.34%).