Identification of Citrus Huanglongbing Disease at the Pre-Symptomatic Stage Using Polarized Imaging Technique. Issue 16 (2016)

• Record Type: Journal Article
• Authors: Pourreza, Alireza; Lee, Won Suk; Etxeberria, Ed; Zhang, Yao
• Is Part Of: IFAC-PapersOnLine. Volume 49:Issue 16(2016)
• Page Start: 110
• Page End: 115
• Publication Date: 2016
• Subjects: Citrus greening -- Disease diagnosis -- Image analysis -- Starch -- Polarization -- Sensing; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2016.10.021
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Huanglongbing (HLB), also known as yellow shoot or citrus greening, is a devastating disease, associated with ' Candidatus Liberibacter asiaticus ( C Las).' Unfortunately, there is no effective cure for this disease, and since a tree is infected, it will eventually die. HLB has negatively affected citrus industries in many countries in Africa, Asia, and South America. In 2005, HLB was confirmed in a groove in South Florida, and after a few years, the entire state of Florida got infected. Timely detection and removal of HLB-affected trees are substantially necessary for managing the disease. Accumulation of starch that appears as yellow/light-green islands on the citrus leaf is known as an early diagnostic symptom of HLB. A polarized imaging system was used to follow the hyper-accumulation of starch in leaves of graft-inoculated citrus plants. Time-lapse images of citrus leaves were acquired in a weekly manner after plants were grafted with a disk from another HLB-affected leaf to follow the variation in the images' gray values at different locations on a leaf. An image analysis algorithm was developed to highlight the regions of citrus leaf samples with an increase in average gray value as an indication of starch accumulation in the pre-symptomatic stage. The proposed method was able to detect successfully any local increase in the image gray values which associates with hyper-accumulation of starch, and consequently, the existence of C Las.