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Characterizing Zebra Chip Symptom Severity and Identifying Spectral Signatures Associated with ‘Candidatus Liberibacter solanacearum’-Infected Potato Tubers

Author:
Zhao, Zhiguo, Prager, Sean M., Cruzado, Regina K., Liang, Xi, Cooper, William R., Hu, Gongshe, Rashed, Arash
Source:
American journal of potato research 2018 v.95 no.5 pp. 584-596
ISSN:
1099-209X
Subject:
Bactericera cockerelli, Candidatus Liberibacter solanacearum, Triozidae, bacteria, discoloration, genotype, growing season, image analysis, near-infrared spectroscopy, potatoes, prediction, reflectance, screening, thermography, tubers, wavelengths, zebra chip disease, United States
Abstract:
Zebra chip (ZC) disease has been a threat to the US potato industry for nearly two decades. ZC is associated with the bacteria ‘Candidatus Liberibacter solanacearum’ (Lso), which is transmitted by the potato psyllid, Bactericera cockerelli (Šulc) (Hemiptera: Triozidae). ZC reduces yield and quality, due to discoloration of the tuber tissue. Symptom severity is affected by the time of infection and early-season infections express relatively higher degrees of ZC. Although tubers infected late in the growing season, i.e. within 2 weeks of harvest, express minimal to no symptoms, they may proceed to express ZC symptoms following storage. Currently, visualization of ZC symptoms in tubers is used by processors to estimate the percentage of ZC-affected tubers in truckloads of potatoes. This approach, however, is time consuming and relies on evaluations of a small sample size. Thus, it is likely to fail in detecting the asymptomatic late infections. Using several potato genotypes infected at different times during the growing season, this study was set to determine if visible and near infrared spectrometry, and infrared thermal imaging, can be used to distinguish ZC-affected tubers, and to predict the severity of ZC symptoms. The subjective symptom score categorization, commonly used in ZC studies, corresponded with the percentage of the symptomatic area in the tubers sliced at the solon attachment end. The percentage of symptomatic area was also correlated with Lso titer. Reflectance effectively distinguished infected and uninfected tubers with high accuracy; the combined wavelengths 468, 582, 680 and 720-nm were the most effective in predicting symptom severity. Near infrared (NIR) and infrared (IR) thermal imaging failed to distinguish tubers based on Lso infection status after storage. The quantitative measure of ZC severity, and the effectiveness of some visual wavelengths in detecting ZC may help to facilitate selection assays for ZC resistance. While in our study infrared imaging did not appear to be effective in distinguishing Lso- affected tubers after storage, additional studies with field harvested tubers are still needed to evaluate the effectiveness of VIS, NIR and IR spectrometry in screening for ZC.
Agid:
6108145
Handle:
10113/6108145