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Evaluation of Zebra Chip Using Image Analysis

Authors :
Antonio Rivera-Peña
Reyna Isabel Rojas-Martínez
Emma Zavaleta-Mejía
María Guadalupe Hernández-Deheza
Daniel Leobardo Ochoa-Martínez
José Alfredo Carrillo-Salazar
Source :
American Journal of Potato Research. 97:586-595
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

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.

Details

ISSN :
18749380 and 1099209X
Volume :
97
Database :
OpenAIRE
Journal :
American Journal of Potato Research
Accession number :
edsair.doi...........9d75c39a215cc539b57cad736ea84ce4
Full Text :
https://doi.org/10.1007/s12230-020-09807-y