Early detection of Sclerotinia sclerotiorum on oilseed rape leaves based on optical properties

Abstract

Oilseed rape ( Brassica napus L.) is susceptible to Sclerotinia sclerotiorum and its yield would reduce dramatically by the sclerotinia disease. Early detection of the pathogen to prevent the spread of sclerotinia is of great significance. In this paper, the optical response of oilseed rape leaves to Sclerotinia sclerotiorum was analyzed and a new method for early detection of sclerotinia disease based on optical properties was proposed. The optical absorption ( μ a ) and reduced scattering ( μ s ′ ) coefficients of healthy and infected (invisible-symptom and visible-symptom) oilseed rape leaves were measured by using a single integrating sphere (SIS) system over 500–1000 nm. Results showed that with the development of Sclerotinia sclerotiorum infection from healthy to visible-symptom leaves, μ a decreased in 600–700 nm that contained obvious absorption peaks by pigments, while μ s ′ increased in 500–1000 nm. Then linear discriminant analysis (LDA) and support vector machines (SVM) models were developed to discriminate infected leaves from healthy ones, with the raw data of μ a in 500–700 nm, μ s ′ in 500–700 nm, and ( μ a - μ s ′ ) in 600–700 nm, as well as corresponding effective wavelengths optimally selected by the successive projections algorithm (SPA). Results showed that the LDA models with the raw and SPA-selected data of μ a in 500–700 nm, and the SPA-selected ( μ a - μ s ′ ) data, and the SVM model with SPA-selected μ a data all provided 100.00% classification accuracy. Overall, this study proved that the optical properties of oilseed rape responded to Sclerotinia sclerotiorum at early stage, and could be a new basis for early detection of sclerotinia disease. • Optical absorption and scattering parameters were measured for oilseed rape leaves. • Optical response of oilseed rape leaves to Sclerotinia sclerotiorum was analyzed. • Optical parameters were optimally selected for Sclerotinia sclerotiorum detection. • Models for classifying infected and healthy oilseed rape leaves were developed. • Early detection of Sclerotinia sclerotiorum was achieved based on optical properties.