Combination of computer vision and backscattering imaging for predicting the moisture content and colour changes of sweet potato (Ipomoea batatas L.) during drying

Onwude, Daniel I. and Hashim, Norhashila and Abdan, Khalina and Janius, Rimfiel and Chen, Guangnan (2018) Combination of computer vision and backscattering imaging for predicting the moisture content and colour changes of sweet potato (Ipomoea batatas L.) during drying. Computers and Electronics in Agriculture, 150. pp. 178-187. ISSN 0168-1699

Abstract

This study seeks to investigate the potential of using combined computer vision (CV) and laser-induced backscattering imaging (LLBI) in monitoring the quality attributes of sweet potato during drying. CV and backscattered images of 4mm thickness sweet potato slices were captured after every one-hour of drying, at drying temperatures of 50–70 °C. Reference quality properties, such as moisture content, L∗, a∗ and b∗ colour coordinates were measured hourly under the same drying conditions. Principal component analysis (PCA) and partial least square regression (PLS) were applied to the extracted combined CV (based on RGB) and backscattering imaging parameters to analyse the quality changes of sweet potato during drying. The results showed that there was significant effect of drying temperature and time on combined CV and backscattering imaging parameters. The combined optical method showed good correlation with moisture content and colour properties i.e L∗ and a∗ of sweet potato with R2 > 0.7. Specifically, the redness (a∗) gave the highest coefficient of determination (R2) of 0.80, while the moisture ratio (MR) showed the lowest root mean square error of validation (RMSEV) with the value of 0.18. Thus, this study has shown that combined CV and backscattering imaging parameters can serve as a non-destructive tool for detecting the changes in quality parameters of sweet potato
during drying.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Restricted access to published version in accordance with copyright policy of publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying
Date Deposited: 17 May 2018 04:36
Last Modified: 21 May 2018 00:27
Uncontrolled Keywords: drying; digital imaging; backscattering imaging; sweet potatoes; quality attributes
Fields of Research : 09 Engineering > 0999 Other Engineering > 099901 Agricultural Engineering
Socio-Economic Objective: B Economic Development > 82 Plant Production and Plant Primary Products > 8203 Industrial Crops > 820399 Industrial Crops not elsewhere classified
Identification Number or DOI: 10.1016/j.compag.2018.04.015
URI: http://eprints.usq.edu.au/id/eprint/34064

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