Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying
This study aimed to assess the feasibility of a multi-sensor approach for predicting shrinkage of papaya during drying using computer vision methods in combination with optical scattering analysis of light at 650 nm. The top-side area and total surface area derived from computer vision were analyzed...
| Autores principales: | , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Elsevier
2016
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/76370 |
| _version_ | 1855540096984416256 |
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| author | Udomkun, Patchimaporn Nagle, Marcus Argyropoulos, D. Mahayothee, B. Müller, Joachim |
| author_browse | Argyropoulos, D. Mahayothee, B. Müller, Joachim Nagle, Marcus Udomkun, Patchimaporn |
| author_facet | Udomkun, Patchimaporn Nagle, Marcus Argyropoulos, D. Mahayothee, B. Müller, Joachim |
| author_sort | Udomkun, Patchimaporn |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This study aimed to assess the feasibility of a multi-sensor approach for predicting shrinkage of papaya during drying using computer vision methods in combination with optical scattering analysis of light at 650 nm. The top-side area and total surface area derived from computer vision were analyzed, while the illuminated area and light intensity from optical scattering images were used to interpret photon migration in the fruit tissue. The relationship between moisture content and shrinkage in terms of volume and area reduction during drying was satisfactorily explained by a linear model. The results demonstrated that the prediction of papaya shrinkage during drying from top and total surface areas of the sample was possible, but can potentially be improved. Multivariate correlations of computer vision parameters and optical scattering properties showed the enhanced performance for shrinkage prediction. This multi-sensor approach could possibly be applied as a fast, accurate and non-invasive technique for in-line quality control to monitor shrinkage in the production of dried fruits. |
| format | Journal Article |
| id | CGSpace76370 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | CGSpace763702024-05-01T08:19:39Z Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying Udomkun, Patchimaporn Nagle, Marcus Argyropoulos, D. Mahayothee, B. Müller, Joachim comptuer vision postharvest technology dehydration carica This study aimed to assess the feasibility of a multi-sensor approach for predicting shrinkage of papaya during drying using computer vision methods in combination with optical scattering analysis of light at 650 nm. The top-side area and total surface area derived from computer vision were analyzed, while the illuminated area and light intensity from optical scattering images were used to interpret photon migration in the fruit tissue. The relationship between moisture content and shrinkage in terms of volume and area reduction during drying was satisfactorily explained by a linear model. The results demonstrated that the prediction of papaya shrinkage during drying from top and total surface areas of the sample was possible, but can potentially be improved. Multivariate correlations of computer vision parameters and optical scattering properties showed the enhanced performance for shrinkage prediction. This multi-sensor approach could possibly be applied as a fast, accurate and non-invasive technique for in-line quality control to monitor shrinkage in the production of dried fruits. 2016-11 2016-08-10T07:51:04Z 2016-08-10T07:51:04Z Journal Article https://hdl.handle.net/10568/76370 en Limited Access Elsevier Udomkun, P., Nagle, M., Argyropoulos, D., Mahayothee, B. & Müller, J. (2016). Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying. Journal of Food Engineering, 189, 82-89. |
| spellingShingle | comptuer vision postharvest technology dehydration carica Udomkun, Patchimaporn Nagle, Marcus Argyropoulos, D. Mahayothee, B. Müller, Joachim Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying |
| title | Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying |
| title_full | Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying |
| title_fullStr | Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying |
| title_full_unstemmed | Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying |
| title_short | Multi-sensor approach to improve optical monitoring of papaya shrinkage during drying |
| title_sort | multi sensor approach to improve optical monitoring of papaya shrinkage during drying |
| topic | comptuer vision postharvest technology dehydration carica |
| url | https://hdl.handle.net/10568/76370 |
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