Firmness prediction in 'Rojo Brillante' persimmon using hyperspectral imaging technology
Visual evaluation of external colour is the most used maturity index for harvesting of persimmon fruit, since skin colour evolution from green to red during the fruit maturity process is closely linked to internal physicochemical changes. The decline of firmness that takes place as persimmon mature...
| Autores principales: | , , , , , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
ISHS
2021
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.11939/7061 https://www.actahort.org/books/1194/1194_108.htm |
| _version_ | 1855492208819437568 |
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| author | Munera, Sandra Besada, Cristina Blasco, José Cubero, Sergio Salvador, Alejandra Talens, Pau Aleixos, Nuria |
| author2 | Artés-Hernández, F. |
| author_browse | Aleixos, Nuria Artés-Hernández, F. Besada, Cristina Blasco, José Cubero, Sergio Munera, Sandra Salvador, Alejandra Talens, Pau |
| author_facet | Artés-Hernández, F. Munera, Sandra Besada, Cristina Blasco, José Cubero, Sergio Salvador, Alejandra Talens, Pau Aleixos, Nuria |
| author_sort | Munera, Sandra |
| collection | ReDivia |
| description | Visual evaluation of external colour is the most used maturity index for harvesting of persimmon fruit, since skin colour evolution from green to red during the fruit maturity process is closely linked to internal physicochemical changes. The decline of firmness that takes place as persimmon mature is of special importance from a commercial point of view, as fruit firmness is determinant to decide the appropriate postharvest conditions in order to preserve fruit quality. Hyperspectral imaging has been shown as a powerful fruit inspection system to assess ripeness features or to detect damages or contaminants in different fruits. In the present study, we evaluate the potential use of hyperspectral imaging system to predict persimmon firmness. To this end, 'Rojo Brillante' persimmons were harvested at three different maturity stages based on visual evaluation of external colour. A standard hyperspectral imaging system in reflectance mode in the range 420-1080 nm was used to capture the images of the fruit. Then, external colour was determined with a colorimeter (Hunter Lab parameters) and fruit firmness was determined with a texturometer and was expressed as force (N) to break the flesh. Study of correlations between flesh firmness and hyperspectral imaging data and between flesh firmness and Hunter Lab parameters were performed by using partial least square regression (PLS-R). After selecting the three wavelengths that showed the highest correlation with fruit firmness, the firmness prediction by hyperspectral imaging was better (R2=0.79 and a standard error of prediction (SEP) = 4.33(N)) than that obtained by colorimetry (R2=0.71 and SEP=5.10(N)). Therefore, hyperspectral imaging is presented as a potential non-destructive tool to acutely predict firmness of persimmon. |
| format | Objeto de conferencia |
| id | ReDivia7061 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | ISHS |
| publisherStr | ISHS |
| record_format | dspace |
| spelling | ReDivia70612025-04-25T14:53:48Z Firmness prediction in 'Rojo Brillante' persimmon using hyperspectral imaging technology Munera, Sandra Besada, Cristina Blasco, José Cubero, Sergio Salvador, Alejandra Talens, Pau Aleixos, Nuria Artés-Hernández, F. Image Hunter Lab N01 Agricultural engineering Q02 Food processing and preservation Diospyros kaki Firmness Quality Computer vision Visual evaluation of external colour is the most used maturity index for harvesting of persimmon fruit, since skin colour evolution from green to red during the fruit maturity process is closely linked to internal physicochemical changes. The decline of firmness that takes place as persimmon mature is of special importance from a commercial point of view, as fruit firmness is determinant to decide the appropriate postharvest conditions in order to preserve fruit quality. Hyperspectral imaging has been shown as a powerful fruit inspection system to assess ripeness features or to detect damages or contaminants in different fruits. In the present study, we evaluate the potential use of hyperspectral imaging system to predict persimmon firmness. To this end, 'Rojo Brillante' persimmons were harvested at three different maturity stages based on visual evaluation of external colour. A standard hyperspectral imaging system in reflectance mode in the range 420-1080 nm was used to capture the images of the fruit. Then, external colour was determined with a colorimeter (Hunter Lab parameters) and fruit firmness was determined with a texturometer and was expressed as force (N) to break the flesh. Study of correlations between flesh firmness and hyperspectral imaging data and between flesh firmness and Hunter Lab parameters were performed by using partial least square regression (PLS-R). After selecting the three wavelengths that showed the highest correlation with fruit firmness, the firmness prediction by hyperspectral imaging was better (R2=0.79 and a standard error of prediction (SEP) = 4.33(N)) than that obtained by colorimetry (R2=0.71 and SEP=5.10(N)). Therefore, hyperspectral imaging is presented as a potential non-destructive tool to acutely predict firmness of persimmon. 2021-02-02T14:43:08Z 2021-02-02T14:43:08Z 2018 conferenceObject Munera, S., Besada, C., Blasco, J., Cubero, S., Salvador, A., Talens, P. and Aleixos, N. (2018). Firmness prediction in 'Rojo Brillante' persimmon using hyperspectral imaging technology. Acta Hortic. 1194, 761-768 978-94-62611-90-0 0567-7572 (print) 2406-6168 (electronic) http://hdl.handle.net/20.500.11939/7061 10.17660/ActaHortic.2018.1194.108 https://www.actahort.org/books/1194/1194_108.htm en 2016-06-21 VIII International Postharvest Symposium: Enhancing Supply Chain and Consumer Benefits - Ethical and Technological Issues Cartagena, Murcia (Spain) Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ closedAccess ISHS electronico |
| spellingShingle | Image Hunter Lab N01 Agricultural engineering Q02 Food processing and preservation Diospyros kaki Firmness Quality Computer vision Munera, Sandra Besada, Cristina Blasco, José Cubero, Sergio Salvador, Alejandra Talens, Pau Aleixos, Nuria Firmness prediction in 'Rojo Brillante' persimmon using hyperspectral imaging technology |
| title | Firmness prediction in 'Rojo Brillante' persimmon using hyperspectral imaging technology |
| title_full | Firmness prediction in 'Rojo Brillante' persimmon using hyperspectral imaging technology |
| title_fullStr | Firmness prediction in 'Rojo Brillante' persimmon using hyperspectral imaging technology |
| title_full_unstemmed | Firmness prediction in 'Rojo Brillante' persimmon using hyperspectral imaging technology |
| title_short | Firmness prediction in 'Rojo Brillante' persimmon using hyperspectral imaging technology |
| title_sort | firmness prediction in rojo brillante persimmon using hyperspectral imaging technology |
| topic | Image Hunter Lab N01 Agricultural engineering Q02 Food processing and preservation Diospyros kaki Firmness Quality Computer vision |
| url | http://hdl.handle.net/20.500.11939/7061 https://www.actahort.org/books/1194/1194_108.htm |
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