摘要
共采集了112个番茄茎秆高光谱数据(光谱范围400～1 030nm),结合图像处理和化学计量学方法建立了番茄茎秆灰霉病早期诊断模型。应用偏最小二乘法(PLS)模型的隐含变量载荷分布选取了七个特征波长(EW),并建立了番茄茎秆灰霉病早期诊断的最小二乘支持向量机(LS-SVM)模型。结果表明,经过变量标准化(SNV)及多元散射校正(MSC)预处理所建立的EW-LS-SVM模型获得了满意的判别效果,且优于全波段的PLS模型。说明高光谱成像技术进行番茄茎秆灰霉病的早期诊断是可行的,为番茄病害早期诊断和预警提供了新的方法。
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.
出处
《光谱学与光谱分析》
SCIE
EI
CAS
CSCD
北大核心
2013年第3期733-736,共4页
Spectroscopy and Spectral Analysis
基金
国家高技术研究发展计划(863计划)项目(2011AA100705)
国家自然科学基金项目(31071332)
浙江省自然科学基金重点项目(Z3090295)
中国博士后科学基金项目(2011M501009)资助
作者简介
孔汶汶，女，1987年生，浙江大学生物系统工程与食品科学学院博士研究生e-mail：zjukww@163．com
通讯联系人e-mail：ydbao@zjuedu．cn
