Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines
The internal quality of nectarines (Prunus persica L. Batsch var. nucipersica) cv. ‘Big Top’ (yellow flesh) and ‘Magique’ (white flesh) has been inspected using hyperspectral transmittance imaging. Hyperspectral images of intact fruits were acquired in the spectral range of 630–900 nm using transmit...
| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | Inglés |
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Elsevier
2019
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.11939/6287 https://www.sciencedirect.com/science/article/pii/S1537511018312959?via%3Dihub |
| _version_ | 1855032400242802688 |
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| author | Munera, Sandra Blasco, José Amigo, José M. Cubero, Sergio Talens, Pau Aleixos, Nuria |
| author_browse | Aleixos, Nuria Amigo, José M. Blasco, José Cubero, Sergio Munera, Sandra Talens, Pau |
| author_facet | Munera, Sandra Blasco, José Amigo, José M. Cubero, Sergio Talens, Pau Aleixos, Nuria |
| author_sort | Munera, Sandra |
| collection | ReDivia |
| description | The internal quality of nectarines (Prunus persica L. Batsch var. nucipersica) cv. ‘Big Top’ (yellow flesh) and ‘Magique’ (white flesh) has been inspected using hyperspectral transmittance imaging. Hyperspectral images of intact fruits were acquired in the spectral range of 630–900 nm using transmittance mode during their ripening under controlled conditions. The detection of split pit disorder and classification according to an established firmness threshold were performed using PLS-DA. The prediction of the Internal Quality Index (IQI) related to ripeness was performed using PLS-R. The most important variables were selected using interval-PLS. As a result, an accuracy of 94.7% was obtained in the detection of fruits with split pit of the ‘Big Top’ cultivar. Accuracies of 95.7% and 94.6% were achieved in the classification of the ‘Big Top’ and ‘Magique’ cultivars, respectively, according to the firmness threshold. The internal quality was predicted through the IQI with R2 values of 0.88 and 0.86 for the two cultivars. The results obtained indicate the great potential of hyperspectral transmittance imaging for the assessment of the internal quality of intact nectarines. |
| format | article |
| id | ReDivia6287 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | ReDivia62872025-04-25T14:46:45Z Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines Munera, Sandra Blasco, José Amigo, José M. Cubero, Sergio Talens, Pau Aleixos, Nuria Split pit Ripeness Internal quality Hyperspectral imaging Q01 Food science and technology U10 Mathematical and statistical methods Computer vision Stone fruits The internal quality of nectarines (Prunus persica L. Batsch var. nucipersica) cv. ‘Big Top’ (yellow flesh) and ‘Magique’ (white flesh) has been inspected using hyperspectral transmittance imaging. Hyperspectral images of intact fruits were acquired in the spectral range of 630–900 nm using transmittance mode during their ripening under controlled conditions. The detection of split pit disorder and classification according to an established firmness threshold were performed using PLS-DA. The prediction of the Internal Quality Index (IQI) related to ripeness was performed using PLS-R. The most important variables were selected using interval-PLS. As a result, an accuracy of 94.7% was obtained in the detection of fruits with split pit of the ‘Big Top’ cultivar. Accuracies of 95.7% and 94.6% were achieved in the classification of the ‘Big Top’ and ‘Magique’ cultivars, respectively, according to the firmness threshold. The internal quality was predicted through the IQI with R2 values of 0.88 and 0.86 for the two cultivars. The results obtained indicate the great potential of hyperspectral transmittance imaging for the assessment of the internal quality of intact nectarines. 2019-12-17T11:01:56Z 2019-12-17T11:01:56Z 2019 article acceptedVersion Munera, S., Blasco, J., Amigo, J. M., Cubero, S., Talens, P., & Aleixos, N. (2019). Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines. Biosystems Engineering, 182, 54-64. 1537-5110 http://hdl.handle.net/20.500.11939/6287 10.1016/j.biosystemseng.2019.04.001 https://www.sciencedirect.com/science/article/pii/S1537511018312959?via%3Dihub en Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Elsevier electronico |
| spellingShingle | Split pit Ripeness Internal quality Hyperspectral imaging Q01 Food science and technology U10 Mathematical and statistical methods Computer vision Stone fruits Munera, Sandra Blasco, José Amigo, José M. Cubero, Sergio Talens, Pau Aleixos, Nuria Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines |
| title | Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines |
| title_full | Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines |
| title_fullStr | Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines |
| title_full_unstemmed | Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines |
| title_short | Use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines |
| title_sort | use of hyperspectral transmittance imaging to evaluate the internal quality of nectarines |
| topic | Split pit Ripeness Internal quality Hyperspectral imaging Q01 Food science and technology U10 Mathematical and statistical methods Computer vision Stone fruits |
| url | http://hdl.handle.net/20.500.11939/6287 https://www.sciencedirect.com/science/article/pii/S1537511018312959?via%3Dihub |
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