Kong Wen-Wen, Yu Jia-Jia, Liu Fei, He Yong, Bao Yi-Dan
College of Biosystems Engineering and Food Science, Zhejing University, Hangzhou, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Mar;33(3):733-6.
Early diagnosis of gray mold on tomato stalks based on hyperspectral data was studied in the present paper. A total of 112 samples' hyperspectral data were collected by hyperspectral imaging system. The study spectral region was from 400 to 1,030 nm. Combined with image processing and chemometric methods, the tomato stalk gray mold diagnosis models were built. Seven effective wavelengths were selected by analysis of variable load distribution in PLS model. The experimental results showed that the excellent results were achieved by EW-LS-SVM model with standard normal variate (SNV) spectral and multiplicative scatter correction (MSC) spectral, and the accuracy of diagnosing gray mold on tomato stalks was satisfied and better than PLS model with whole band. Hence, it is feasible to early diagnose gray mold on tomato stalks using hyperspectral imaging technology, which provides a new early diagnosis and warning method for tomato disease.
本文研究了基于高光谱数据的番茄茎部灰霉病早期诊断。利用高光谱成像系统采集了112个样本的高光谱数据。研究光谱范围为400至1030nm。结合图像处理和化学计量学方法，建立了番茄茎部灰霉病诊断模型。通过分析PLS模型中的变量载荷分布，选择了7个有效波长。实验结果表明，采用标准正态变量（SNV）光谱和多元散射校正（MSC）光谱的EW-LS-SVM模型取得了优异的结果，番茄茎部灰霉病的诊断准确率令人满意，且优于全波段PLS模型。因此，利用高光谱成像技术对番茄茎部灰霉病进行早期诊断是可行的，为番茄病害的早期诊断和预警提供了一种新方法。
