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
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