title: Detection of early blight and late blight diseases on tomato leaves using hyperspectral imaging.
abstract: This study investigated the potential of using hyperspectral imaging for detecting different diseases on tomato leaves. One hundred and twenty healthy, one hundred and twenty early blight and seventy late blight diseased leaves were selected to obtain hyperspectral images covering spectral wavelengths from 380 to 1023 nm. An extreme learning machine (ELM) classifier model was established based on full wavelengths. Successive projections algorithm (SPA) was used to identify the most important wavelengths. Based on the five selected wavelengths (442, 508, 573, 696 and 715 nm), an ELM model was re-established. Then, eight texture features (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation) based on gray level co-occurrence matrix (GLCM) at the five effective wavelengths were extracted to establish detection models. Among the models which were established based on spectral information, all performed excellently with the overall classification accuracy ranging from 97.1% to 100% in testing sets. Among the eight texture features, dissimilarity, second moment and entropy carried most of the effective information with the classification accuracy of 71.8%, 70.9% and 69.9% in the ELM models. The results demonstrated that hyperspectral imaging has the potential as a non-invasive method to identify early blight and late blight diseases on tomato leaves.
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
authors.forename: Chuanqi
authors.initials: C
authors.lastname: Xie
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
authors.forename: Yongni
authors.initials: Y
authors.lastname: Shao
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
authors.forename: Xiaoli
authors.initials: X
authors.lastname: Li
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
authors.forename: Yong
authors.initials: Y
authors.lastname: He
mesh_terms: D000465:Algorithms; D007091:Image Processing, Computer-Assisted; D018551:Solanum lycopersicum / Q000737:chemistry* / Q000378:metabolism; D008962:Models, Theoretical; D010935:Plant Diseases; D018515:Plant Leaves / Q000737:chemistry / Q000378:metabolism / Q000382:microbiology*; D025341:Principal Component Analysis; D013053:Spectrophotometry