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ARS Home » Pacific West Area » Albany, California » Western Regional Research Center » Healthy Processed Foods Research » Research » Publications at this Location » Publication #324736

Research Project: Defining, Measuring, and Mitigating Attributes that Adversely Impact the Quality and Marketability of Foods

Location: Healthy Processed Foods Research

Title: Non-destructive NIR detection of Zebra Chip disease in whole potatoes (abstract)

item Liang, Peishih
item Haff, Ronald - Ron

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 2/18/2016
Publication Date: 7/17/2016
Citation: Liang, P., Haff, R.P. 2016. Non-destructive NIR detection of Zebra Chip disease in whole potatoes (abstract). ASABE International Meeting, July 17-20, 2016, Orlando, FL.

Interpretive Summary:

Technical Abstract: Potatoes are the 4th biggest food crop worldwide and the leading vegetable crop in the U.S., accounting for 15 percent of vegetable sales. Over 50% of potatoes are consumed as processed products such as French fries and chips. Zebra Chip (ZC) is a disease of potatoes that causes brown discoloration of vascular and medullar rays, especially when fried, impacting both marketability and yield. The disease has been an ongoing problem in various potato-growing countries, including Mexico and New Zealand. It was first detected in the U.S. in 2000 and has since been observed in Arizona, California, Colorado, Idaho, Oregon, Kansas, Nebraska, and New Mexico. ZC is caused by the bacterium Candidatus Liberibacter solanacearum and is transmitted by the potato psyllid Bactericera cokerelli Sulc. The aboveground symptoms of the infected plants are similar to that of psyllid yellows, therefore the disease determination is labor intensive and destructive, since the tuber must be sliced and the brown pattern must be observed. In this research, the feasibility of NIR spectroscopy as a means to detect infected potatoes is demonstrated. Reflectance spectra of whole potatoes (both clean and infected) and transmission spectra of sliced potatoes were collected and classification models developed. Preliminary results yielded an error rate as low as 1.36% (i.e. more than 98% of samples were successfully classified) with zero false negative. The detection methods reported here provide the means for improved monitoring of potato quality.