Early Detection of Botrytis cinerea on Eggplant Leaves Based on Visible and Near-Infrared Spectroscopy

Visible and near-infrared reflectance spectroscopy was applied to the early detection of Botrytis cinerea on eggplant leaves before symptoms appeared. Chemometrics methods were used to build the prediction model based on the spectral reflectance data. Owing to the complexity of the original spectral data, principal component analysis was executed to reduce the numerous wavelengths to several principal components (PCs) in order to decrease the amount of calculation and improve the accuracy. These PCs were set as input variables of back-propagation neural networks (BP-NN). The BP-NN model developed has an accuracy rate of 85% in predicting fungal infections. Furthermore, partial least squares regression was executed to obtain seven sensitive wavelengths. Based on these wavelengths, the prediction accuracy rate of the BP-NN model was 70%. This preliminary study, which was done in a closed room with restrictions to avoid intereference of the field environment, indicated that it is possible to apply spectral technology to the early detection of Botrytis cinerea on eggplant leaves. There is a potential to establish an online field application in early disease detection based on visible and near-infrared spectroscopy.

[1]  M. Putnam.  Evaluation of selected methods of plant disease diagnosis , 1995 .

[2]  Tsuguo Okamoto,et al.  Automatic diagnosis of plant disease - Spectral reflectance of healthy and diseased leaves , 1998 .

[3]  D. Wu,et al.  Infrared spectroscopy technique for the nondestructive measurement of fat content in milk powder. , 2007, Journal of dairy science.

[4]  F. Boochs,et al.  Shape of the red edge as vitality indicator for plants , 1990 .

[5]  V. P. Polischuk,et al.  Changes in reflectance spectrum characteristic of nicotiana debneyi plant under the influence of viral infection , 1997 .

[6]  S. Pennypacker,et al.  Influence of grower activity on concentrations of airborne conidia of Botrytis cinerea among geranium cuttings , 1991 .

[7]  L. Janik,et al.  Quantification of carbon derived from lignite in soils using mid-infrared spectroscopy and partial least squares , 2001 .

[8]  G. Carter,et al.  Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. , 2001, American journal of botany.

[9]  H. Ramon,et al.  Early Disease Detection in Wheat Fields using Spectral Reflectance , 2003 .

[10]  Roberto Oberti,et al.  Plant disease detection based on data fusion of hyper-spectral and multi-spectral fluorescence imaging using Kohonen maps , 2005, Real Time Imaging.

[11]  P. A. Gorry.  General least-squares smoothing and differentiation by the convolution (Savitzky-Golay) method , 1990 .

[12]  Y. Elad,et al.  Comparison of Antagonists of Botrytis cinerea in Greenhouse-grown Cucumber and Tomato under Different Climatic Conditions , 1999, European Journal of Plant Pathology.

[13]  D. Shtienberg,et al.  Effect of Some Host and Microclimate Factors on Infection of Tomato Stems by Botrytis cinerea. , 1997, Plant disease.

[14]  Susanne Jacobsen,et al.  A chemometric evaluation of the underlying physical and chemical patterns that support near infrared spectroscopy of barley seeds as a tool for explorative classification of endosperm genes and gene combinations , 2005 .

[15]  Yong He,et al.  Fast Measurement of Sugar Content of Yogurt Using Vis/NIR-Spectroscopy , 2007 .

[16]  A.A. El-Keib,et al.  A review of ANN-based short-term load forecasting models , 1995, Proceedings of the Twenty-Seventh Southeastern Symposium on System Theory.

[17]  Walter E. Riedell,et al.  Leaf Reflectance Spectra of Cereal Aphid-Damaged Wheat , 1999 .

[18]  Y. Elad.  Reduced sensitivity of Botrytis cinerea to two sterol biosynthesis‐inhibiting fungicides: fenetrazole and fenethanil , 1992 .

[19]  Hsuan-Liang Liu,et al.  Artificial neural network to predict the growth of the indigenous Acidthiobacillus thiooxidans , 2008 .

[20]  J. LaMondia,et al.  Sensitivity of Botrytis cinerea from Connecticut Greenhouses to Benzimidazole and Dicarboximide Fungicides. , 1997, Plant disease.