Rapid Screening of Huanglongbing-Infected Citrus Leaves by Near-Infrared Reflectance Spectroscopy

Abstract

The citrus disease Huanglongbing (HLB, or citrus greening), is one of the more serious diseases of citrus. An infected tree produces fruit that is unsuitable for sale as fresh fruit or for juice. The only definitive method to diagnose trees suspected of infection by citrus greening pathogens is by analysis of DNA, which is costly and time consuming. Near-infrared (NIR) reflectance spectroscopy may have the potential to detect HLB positive leaves. In this study, the primary differences in the visible spectra between HLB positive and negative leaves were the peaks associated with chlorophyll absorption, which decreased for the infected leaves. The NIR region of the spectra of HLB positive leaves revealed differences in carbohydrates and cuticle waxes, indicating that a change occurred in the amount, type, or structure of these chemical components. Partial least squares regression models were developed with 381 leaves from trees that were visually HLB positive or HLB negative with other known citrus disease and nutrient deficiencies. The models had an overall accuracy for true HLB positive and negative leaves ranging from 92% to 99% and a false rate of 1% to 8%.