The potential of computer vision, optical backscattering parameters and artificial neural network modelling in monitoring the shrinkage of sweet potato (Ipomoea Batatas L.) during drying
Article
Article Title | The potential of computer vision, optical backscattering parameters and artificial neural network modelling in monitoring the shrinkage of sweet potato (Ipomoea Batatas L.) during drying |
---|---|
ERA Journal ID | 5224 |
Article Category | Article |
Authors | Onwude, Daniel I. (Author), Hashim, Norhashila (Author), Abdan, Khalina (Author), Janius, Rimfiel (Author) and Chen, Guangnan (Author) |
Journal Title | Journal of the Science of Food and Agriculture |
Journal Citation | 98 (4), pp. 1310-1324 |
Number of Pages | 15 |
Year | 2018 |
Place of Publication | United Kingdom |
ISSN | 0022-5142 |
1097-0010 | |
Digital Object Identifier (DOI) | https://doi.org/10.1002/jsfa.8595 |
Web Address (URL) | https://onlinelibrary.wiley.com/doi/abs/10.1002/jsfa.8595 |
Abstract | BACKGROUND RESULTS CONCLUSION |
Keywords | drying; shrinkage; computer vision; laser backscattering; process control; sweet potato |
ANZSRC Field of Research 2020 | 300408. Crop and pasture post harvest technologies (incl. transportation and storage) |
Byline Affiliations | University of Putra Malaysia, Malaysia |
Faculty of Health, Engineering and Sciences | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q473q/the-potential-of-computer-vision-optical-backscattering-parameters-and-artificial-neural-network-modelling-in-monitoring-the-shrinkage-of-sweet-potato-ipomoea-batatas-l-during-drying
744
total views13
total downloads1
views this month0
downloads this month