Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: September 29, 2011
Publication Date: November 18, 2011
Citation: Windham, W.R., Poole, G.H., Park, B., Heitschmidt, G.W., Albano, J.P., Gottwald, T.R., Lawrence, K.C., Hawkins, S.A. 2011. Rapid screening of huanglongbing-infected citrus leaves by near infrared reflectance spectroscopy. Transactions of the ASABE. 54(6):2253-2258. Interpretive Summary: Citrus greening, also called Huanglongbing (HLB) or yellow dragon disease, is a serious disease of citrus and has the potential to wipe out most of the citrus groves in the United States. Trees can be infected for up to several years before showing symptoms during which time it may have been passed on to other nearby trees. An infected tree produces fruit that is unsuitable for sale as fresh fruit or for juice. Currently, the method for detecting the presence of the disease is a type of DNA testing called polymerase chain reaction which is both costly and time consuming. Using light, from the near infrared region of the spectrum a mathematical model was developed to predict the presence of the disease in leaves from infected trees. With this detection method a citrus leaf sample can be collected, dried, ground and analyzed in a matter of minutes to detect citrus greening disease.
Technical Abstract: The citrus disease Haunglongbing (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 of diagnosis of trees suspected of infection by citrus greening pathogens is by analysis of DNA which is costly and time consuming. Near infrared reflectance spectroscopy may have the potential to detect HLB positive leaves. The primary difference between the 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 reveal differences in carbohydrates and cuticle waxes indicating that a change occurred in either 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, 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%.