Maturity monitoring of intact fruit and arils of pomegranate cv. 'Mollar de Elche' using machine vision and chemometrics
Pomegranate fruit cv. ‘Mollar de Elche’ were collected at seven different harvest times. Colour and hyperspectral images of the intact fruit and arils were acquired at each harvest. Physicochemical properties such as total soluble solids, titratable acidity, maturity index, BrimA, internal colour, t...
| Main Authors: | , , , , |
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| Format: | Artículo preliminar |
| Language: | Inglés |
| Published: |
Elsevier
2019
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11939/6283 https://www.sciencedirect.com/science/article/abs/pii/S0925521419303904 |
| _version_ | 1855492052533379072 |
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| author | Munera, Sandra Hernández, Francisca Aleixos, Nuria Cubero, Sergio Blasco, José |
| author_browse | Aleixos, Nuria Blasco, José Cubero, Sergio Hernández, Francisca Munera, Sandra |
| author_facet | Munera, Sandra Hernández, Francisca Aleixos, Nuria Cubero, Sergio Blasco, José |
| author_sort | Munera, Sandra |
| collection | ReDivia |
| description | Pomegranate fruit cv. ‘Mollar de Elche’ were collected at seven different harvest times. Colour and hyperspectral images of the intact fruit and arils were acquired at each harvest. Physicochemical properties such as total soluble solids, titratable acidity, maturity index, BrimA, internal colour, total phenolic compounds content and antioxidant activity were measured in the juice of each fruit. Relationships between colour (L*, a*, b*) and spectral (720–1050 nm) data obtained from the images of the intact fruit and arils were investigated physicochemical properties using partial least square regression models. Discrimination of the different maturity stages also was carried out using partial least square discriminant analysis models. Similar results were obtained in the prediction of the physicochemical properties using the colour and hyperspectral images of the intact fruit. However, the predictions achieved for the information about the arils were higher using hyperspectral imaging. In the discrimination of maturity stage, the highest accuracies were obtained using hyperspectral imaging, where 95% of intact fruit and 100% of arils where correctly classified. These results indicate the great potential of machine vision techniques, especially hyperspectral imaging, for monitoring the quality of intact ‘Mollar de Elche’ pomegranate fruit and arils. |
| format | Artículo preliminar |
| id | ReDivia6283 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | ReDivia62832025-04-25T14:46:44Z Maturity monitoring of intact fruit and arils of pomegranate cv. 'Mollar de Elche' using machine vision and chemometrics Munera, Sandra Hernández, Francisca Aleixos, Nuria Cubero, Sergio Blasco, José RGB Q02 Food processing and preservation Pomegranates Image analysis Food quality Punica granatum NIR spectroscopy Pomegranate fruit cv. ‘Mollar de Elche’ were collected at seven different harvest times. Colour and hyperspectral images of the intact fruit and arils were acquired at each harvest. Physicochemical properties such as total soluble solids, titratable acidity, maturity index, BrimA, internal colour, total phenolic compounds content and antioxidant activity were measured in the juice of each fruit. Relationships between colour (L*, a*, b*) and spectral (720–1050 nm) data obtained from the images of the intact fruit and arils were investigated physicochemical properties using partial least square regression models. Discrimination of the different maturity stages also was carried out using partial least square discriminant analysis models. Similar results were obtained in the prediction of the physicochemical properties using the colour and hyperspectral images of the intact fruit. However, the predictions achieved for the information about the arils were higher using hyperspectral imaging. In the discrimination of maturity stage, the highest accuracies were obtained using hyperspectral imaging, where 95% of intact fruit and 100% of arils where correctly classified. These results indicate the great potential of machine vision techniques, especially hyperspectral imaging, for monitoring the quality of intact ‘Mollar de Elche’ pomegranate fruit and arils. 2019-12-13T08:23:16Z 2019-12-13T08:23:16Z 2019 acceptedVersion Munera, S., Hernández, F., Aleixos, N., Cubero, S., & Blasco, J. (2019). Maturity monitoring of intact fruit and arils of pomegranate cv.‘Mollar de Elche’using machine vision and chemometrics. Postharvest Biology and Technology, 156, 110936. 0925-5214 http://hdl.handle.net/20.500.11939/6283 10.1016/j.postharvbio.2019.110936 https://www.sciencedirect.com/science/article/abs/pii/S0925521419303904 en Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Elsevier |
| spellingShingle | RGB Q02 Food processing and preservation Pomegranates Image analysis Food quality Punica granatum NIR spectroscopy Munera, Sandra Hernández, Francisca Aleixos, Nuria Cubero, Sergio Blasco, José Maturity monitoring of intact fruit and arils of pomegranate cv. 'Mollar de Elche' using machine vision and chemometrics |
| title | Maturity monitoring of intact fruit and arils of pomegranate cv. 'Mollar de Elche' using machine vision and chemometrics |
| title_full | Maturity monitoring of intact fruit and arils of pomegranate cv. 'Mollar de Elche' using machine vision and chemometrics |
| title_fullStr | Maturity monitoring of intact fruit and arils of pomegranate cv. 'Mollar de Elche' using machine vision and chemometrics |
| title_full_unstemmed | Maturity monitoring of intact fruit and arils of pomegranate cv. 'Mollar de Elche' using machine vision and chemometrics |
| title_short | Maturity monitoring of intact fruit and arils of pomegranate cv. 'Mollar de Elche' using machine vision and chemometrics |
| title_sort | maturity monitoring of intact fruit and arils of pomegranate cv mollar de elche using machine vision and chemometrics |
| topic | RGB Q02 Food processing and preservation Pomegranates Image analysis Food quality Punica granatum NIR spectroscopy |
| url | http://hdl.handle.net/20.500.11939/6283 https://www.sciencedirect.com/science/article/abs/pii/S0925521419303904 |
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