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- Title
Evaluation of Zebra Chip Using Image Analysis.
- Authors
Hernández-Deheza, María Guadalupe; Rojas-Martínez, Reyna Isabel; Rivera-Peña, Antonio; Zavaleta-Mejía, Emma; Ochoa-Martínez, Daniel Leobardo; Carrillo-Salazar, José Alfredo
- Abstract
Candidatus Liberibacter solanacearum induced the disease known as zebra chip, manifested as an internal brown discoloration of potato tuber. This bacterium causes the vascular tissue of the tuber to turn brown, which shows up on potato chips after they have been fried, and which causes economic losses. There are no quantitative scales for determining the disease severity on potato chips and it is usually estimated using qualitative criteria. In this research, the percentage area and intensity of internal brown discoloration was quantitatively determined using two image segmentation methods of pixels: a single threshold of grayscale images and a classifier with artificial neural networks of color images. The one threshold method and the classifier with neural networks presented 98 and 99% of overall accuracy, respectively. The use of this method made it possible to distinguish cultivars that are resistant from those that are susceptible to Candidatus Liberibacter solanacearum.
- Subjects
IMAGE analysis; IMAGE segmentation; ZEBRAS; ARTIFICIAL neural networks; POTATO chips
- Publication
American Journal of Potato Research, 2020, Vol 97, Issue 6, p586
- ISSN
1099-209X
- Publication type
Article
- DOI
10.1007/s12230-020-09807-y