scholarly journals Detection of Sclerotinia Stem Rot on Oilseed Rape (Brassica napus L.) Leaves Using Hyperspectral Imaging

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1764 ◽  
Author(s):  
Wenwen Kong ◽  
Chu Zhang ◽  
Feng Cao ◽  
Fei Liu ◽  
Shaoming Luo ◽  
...  
2019 ◽  
Vol 62 (1) ◽  
pp. 123-130
Author(s):  
Fei Liu ◽  
Fei Liu ◽  
Tingting Shen ◽  
Jian Wang ◽  
Yong He ◽  
...  

Abstract. In this study, a novel approachser-induced breakdown spectroscopy (LIBS) is proposed to rapidly diagnose stem rot (SSR) in oilseed rape ( L.). A rapid diagnostic method is important to prevent this worldwide disease and promote growth of oilseed rape. A total of 120 fresh leaves, including 60 healthy and 60 SSR-infected leaves, were collected to acquire LIBS spectra. Robust baseline estimation (RBE) and wavelet transform (WT) were applied to preprocess the raw LIBS spectra for baseline correction and denoising. K-nearest neighbor (KNN), radial basis function neural network (RBFNN), random forest (RF), and extreme learning machine (ELM) methods combining full LIBS spectra were chosen to establish classification models to identify healthy and SSR-infected leaves, and the ELM model obtained classified accuracy of more than 80.00% in the prediction set. Twenty-four emission lines were selected by second-derivative spectra as the most relevant to distinguish healthy and SSR-infected leaves. The ELM model using the optimal emission lines improved the classified accuracy to more than 85% and the specificity to 95.00%. Compared with full-spectra models, the number of variables in the models based on optimal wavelengths was reduced from 22,036 to 24, a reduction of 99.89%. This study indicates that LIBS combined with appropriate chemometric m. Keywords: Chemometrics, Laser-induced breakdown spectroscopy, Oilseed rape, Sclerotinia stem rot.


Plant Disease ◽  
2008 ◽  
Vol 92 (10) ◽  
pp. 1473-1473 ◽  
Author(s):  
G. T. Tziros ◽  
G. A. Bardas ◽  
J. T. Tsialtas ◽  
G. S. Karaoglanidis

Oilseed rape (Brassica napus L.) was recently introduced into Greece for the production of biofuels. During May of 2007, symptoms typical of stem rot were observed on oilseed rape plants in three commercial fields in the area of Galatades-Pella, Central Macedonia, Greece. Approximately 30% of the plants were affected. Symptoms began as a chlorotic wilt on the foliage and developed into necrosis of basal stems. In the advanced stages of the disease, stems and branches became bleached and eventually died. White, as well as black, mycelium and irregularly shaped sclerotia (2 to 5 mm in diameter) were produced abundantly on and inside the affected stems. To isolate the pathogen, 20 symptomatic 6-month-old plants were collected from each field. Sclerotia were dipped in 70% ethanol, surface sterilized in 1% sodium hypochlorite for 1 min, and rinsed in sterile water. Sclerotia placed on potato dextrose agar (PDA) were incubated in the dark at 25°C for 10 days. Sclerotinia sclerotiorum (Lib.) de Bary was identified on the basis of morphological characteristics (2). To conduct pathogenicity tests, 10 6-week-old oilseed rape plants (cv. Titan) were each inoculated with a 5-mm-diameter colonized PDA disk placed in wounds made in the basal stem with a sterile scalpel. Five control plants were treated similarly except that the agar disk did not contain mycelium. Plants were then covered with a plastic bag to maintain high humidity. After 72 h, the bags were removed and the plants were maintained in a growth chamber at 23 to 25°C with a 12-h photoperiod and 75% relative humidity. Pathogenicity tests were repeated three times. Symptoms identical to those observed in the field developed within 12 days after inoculation; control plants remained healthy. The fungus was reisolated from all inoculated plants, confirming Koch's postulates. S. sclerotiorum has been reported on oilseed rape in Argentina, Australia, Brazil, Canada, the United States, and New Zealand (1). To our knowledge, this is the first report of Sclerotinia stem rot of oilseed rape in Greece. References: (1) D. F. Farr et al. Fungal Databases. Systematic Botany and Mycology Laboratory. Online publication. ARS, USDA, 2008. (2) L. M. Kohn. Phytopathology 69:881, 1979.


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