Modeling and characterization of potato quality by active thermography

Abstract

This research focuses on characterizing a potato with extra sugar content and identifying the location and depth of the extra sugar content using the active thermography imaging technique. The extra sugar content of the potato is an important problem for potato growers and potato chip manufacturers. Extra sugar content could result in diseases or wounds in the potato tuber. In general, potato tubers with low sugar content are considered as having a higher quality. The inspection system and general methodologies characterizing extra sugar content will be presented in this study. The average heating rate obtained from the thermal image analysis is the major factor in characterization procedures. Using information on the average heating rate, the probability of achieving a potato with extra sugar content may be predicted using the logistic regression model. In addition, neural networks are also used to identify the potato with extra sugar contents. The correct rate for identifying a potato with extra sugar content in it can reach 85%. The location of extra sugar content can also be found using the logistic regression model. Results show the overall correct rate predicting the extra sugar content location with a resolution of 20 by 20 pixels is 91%. In predicting the extra sugar content depth, amounts exceeds 2/3 inches are not detectable by analyzing thermal images. The depth of extra sugar content can be discriminated in 0.3 inch increments with a high rate of accuracy (87.5%).