title: Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging.
abstract: Infected petals are often regarded as the source for the spread of fungi Sclerotinia sclerotiorum in all growing process of rapeseed (Brassica napus L.) plants. This research aimed to detect fungal infection of rapeseed petals by applying hyperspectral imaging in the spectral region of 874-1734 nm coupled with chemometrics. Reflectance was extracted from regions of interest (ROIs) in the hyperspectral image of each sample. Firstly, principal component analysis (PCA) was applied to conduct a cluster analysis with the first several principal components (PCs). Then, two methods including X-loadings of PCA and random frog (RF) algorithm were used and compared for optimizing wavebands selection. Least squares-support vector machine (LS-SVM) methodology was employed to establish discriminative models based on the optimal and full wavebands. Finally, area under the receiver operating characteristics curve (AUC) was utilized to evaluate classification performance of these LS-SVM models. It was found that LS-SVM based on the combination of all optimal wavebands had the best performance with AUC of 0.929. These results were promising and demonstrated the potential of applying hyperspectral imaging in fungus infection detection on rapeseed petals.
authors.affiliation: College of Biosystems Engineering and Food Science, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310058, China.
authors.forename: Yan-Ru
authors.initials: YR
authors.lastname: Zhao
authors.affiliation: College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling, 712100, China.
authors.forename: Ke-Qiang
authors.initials: KQ
authors.lastname: Yu
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: D001203:Ascomycota / Q000472:pathogenicity*; D029688:Brassica napus; D009181:Mycoses; D012372:ROC Curve; D019265:Spectroscopy, Near-Infrared; D060388:Support Vector Machine