Diagnosis of bacterial spot of tomato using spectral signatures

Abstract

Ultraviolet, visible, and near-infrared reflectance spectroscopy was used to determine the disease severity of tomato ( Lycopersicon esculentum) leaves infected with Xanthomonas perforans, the causal agent of bacterial leaf spot of tomato. Chemometric methods were used to identify significant wavelengths and create spectral-based prediction models. Significant wavelengths were identified through analysis of the B-matrix from partial least squares (PLS) regression, analysis of a correlation coefficient spectrum, and through the use of a stepwise multiple linear regression (SMLR) procedure. These analysis methods revealed several significant regions wavelengths and produced predictive models of disease severity based on absorbance spectra. The best model predicted the disease severity of the validation data set with a root mean square difference (RMSD) of 4.9% and a coefficient of determination ( R 2) of 0.82. The results of this initial study indicate the potential for the use of spectral technology to detect bacterial leaf spot of tomato in the field.