Feasibility of Using the Optical Sensing Techniques for Early Detection of Huanglongbing in Citrus Seedlings
AbstractA vision sensor was introduced and tested for early detection of citrus Huanglongbing (HLB). This disease is caused by the bacterium Candidatus Liberibacter asiaticus (CLas) and is transmitted by the Asian citrus psyllid. HLB is a devastating disease that has exerted a significant impact on citrus yield and quality in Florida. Unfortunately, no cure has been reported for HLB. Starch accumulates in HLB infected leaf chloroplasts, which causes the mottled blotchy green pattern. Starch rotates the polarization plane of light. A polarized imaging technique was used to detect the polarization-rotation caused by the hyper-accumulation of starch as a pre-symptomatic indication of HLB in young seedlings. Citrus seedlings were grown in a room with controlled conditions and exposed to intensive feeding by CLas-positive psyllids for eight weeks. A quantitative polymerase chain reaction was employed to confirm the HLB status of samples. Two datasets were acquired; the first created one month after the exposer to psyllids and the second two months later. The results showed that, with relatively unsophisticated imaging equipment, four levels of HLB infections could be detected with accuracies of 72%–81%. As expected, increasing the time interval between psyllid exposure and imaging increased the development of symptoms and, accordingly, improved the detection accuracy. View Full-Text
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Pourreza, A.; Lee, W.S.; Czarnecka, E.; Verner, L.; Gurley, W. Feasibility of Using the Optical Sensing Techniques for Early Detection of Huanglongbing in Citrus Seedlings. Robotics 2017, 6, 11.
Pourreza A, Lee WS, Czarnecka E, Verner L, Gurley W. Feasibility of Using the Optical Sensing Techniques for Early Detection of Huanglongbing in Citrus Seedlings. Robotics. 2017; 6(2):11.Chicago/Turabian Style
Pourreza, Alireza; Lee, Won S.; Czarnecka, Eva; Verner, Lance; Gurley, William. 2017. "Feasibility of Using the Optical Sensing Techniques for Early Detection of Huanglongbing in Citrus Seedlings." Robotics 6, no. 2: 11.
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