Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging
The internal quality of intact persimmon cv. ‘Rojo Brillante’ was assessed trough visible and near infrared hyperspectral imaging. Fruits at three stages of commercial maturity were exposed to different treatments with CO2 to obtain fruit with different ripeness and level of astringency (soluble tan...
| Autores principales: | , , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
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Elsevier
2017
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| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.11939/5726 http://www.sciencedirect.com/science/article/pii/S0023643816307344 |
| _version_ | 1855491973156175872 |
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| author | Munera, Sandra Besada, Cristina Aleixos, Nuria Talens, Pau Salvador, Alejandra Sun, Da-Wen Cubero, Sergio Blasco, José |
| author_browse | Aleixos, Nuria Besada, Cristina Blasco, José Cubero, Sergio Munera, Sandra Salvador, Alejandra Sun, Da-Wen Talens, Pau |
| author_facet | Munera, Sandra Besada, Cristina Aleixos, Nuria Talens, Pau Salvador, Alejandra Sun, Da-Wen Cubero, Sergio Blasco, José |
| author_sort | Munera, Sandra |
| collection | ReDivia |
| description | The internal quality of intact persimmon cv. ‘Rojo Brillante’ was assessed trough visible and near infrared hyperspectral imaging. Fruits at three stages of commercial maturity were exposed to different treatments with CO2 to obtain fruit with different ripeness and level of astringency (soluble tannin content). Spectral and spatial information were used for building classification models to predict ripeness and astringency trough multivariate analysis techniques like linear and quadratic discriminant analysis (LDA and QDA) and support vector machine (SVM). Additionally, flesh firmness was predicted by partial least square regression (PLSR). The full spectrum was used to determine the internal properties and later principal component analysis (PCA) was used to select optimal wavelengths (580, 680 and 1050 nm). The correct classification was above 92% for the three classifiers in the case of ripeness and 95% for QDA in the case of astringency. A value of R2 = 0.80 and a ratio of prediction deviation (RPD) of 1.86 were obtained with the selected wavelengths for the prediction of firmness which demonstrated the potential of hyperspectral imaging as a non-destructive tool in the assessment of the firmness, ripeness state and astringency level of ‘Rojo Brillante’ persimmon. |
| format | Artículo |
| id | ReDivia5726 |
| institution | Instituto Valenciano de Investigaciones Agrarias (IVIA) |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | ReDivia57262025-04-25T14:45:53Z Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging Munera, Sandra Besada, Cristina Aleixos, Nuria Talens, Pau Salvador, Alejandra Sun, Da-Wen Cubero, Sergio Blasco, José Diospyros kaki, internal fruit quality, soluble tannins, astringency, classification, computer vision. J11 Handling, transport, storage and protection of plant products Diospyros kaki Food quality Image analysis The internal quality of intact persimmon cv. ‘Rojo Brillante’ was assessed trough visible and near infrared hyperspectral imaging. Fruits at three stages of commercial maturity were exposed to different treatments with CO2 to obtain fruit with different ripeness and level of astringency (soluble tannin content). Spectral and spatial information were used for building classification models to predict ripeness and astringency trough multivariate analysis techniques like linear and quadratic discriminant analysis (LDA and QDA) and support vector machine (SVM). Additionally, flesh firmness was predicted by partial least square regression (PLSR). The full spectrum was used to determine the internal properties and later principal component analysis (PCA) was used to select optimal wavelengths (580, 680 and 1050 nm). The correct classification was above 92% for the three classifiers in the case of ripeness and 95% for QDA in the case of astringency. A value of R2 = 0.80 and a ratio of prediction deviation (RPD) of 1.86 were obtained with the selected wavelengths for the prediction of firmness which demonstrated the potential of hyperspectral imaging as a non-destructive tool in the assessment of the firmness, ripeness state and astringency level of ‘Rojo Brillante’ persimmon. 2017-08-04T12:33:54Z 2017-08-04T12:33:54Z 2017 article acceptedVersion Munera S, Besada C, Aleixos N, Talens P, Salvador A, Sun, D-W, Cubero C, Blasco J (2017) Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging. LWT - Food Science and Technology, 77C, 241-248. http://hdl.handle.net/20.500.11939/5726 10.1016/j.lwt.2016.11.063. http://www.sciencedirect.com/science/article/pii/S0023643816307344 en Info:eu-repo/grantAgreement/MINECO/Programa Nacional de Investigación Fundamental/RTA2012-00062-C04-01 Info:eu-repo/grantAgreement/MINECO/Programa Nacional de Investigación Fundamental/RTA2012-00062-C04-03 Info:eu-repo/grantAgreement/MINECO/Programa Nacional de Investigación Fundamental/RTA2013-00043-C02 This work has been partially funded by the INIA through projects RTA2012-00062-C04-01, RTA2012-00062-C04-03 and RTA2013-00043-C02 with FEDER funds, GVA through the project AICO/2015/122, and the International S&T Cooperation Programs of China (2015DFA71150) and Guangdong Province, China (2013B051000010). Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging Elsevier |
| spellingShingle | Diospyros kaki, internal fruit quality, soluble tannins, astringency, classification, computer vision. J11 Handling, transport, storage and protection of plant products Diospyros kaki Food quality Image analysis Munera, Sandra Besada, Cristina Aleixos, Nuria Talens, Pau Salvador, Alejandra Sun, Da-Wen Cubero, Sergio Blasco, José Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging |
| title | Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging |
| title_full | Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging |
| title_fullStr | Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging |
| title_full_unstemmed | Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging |
| title_short | Non-destructive assessment of the internal quality of intact persimmon using colour and VIS/NIR hyperspectral imaging |
| title_sort | non destructive assessment of the internal quality of intact persimmon using colour and vis nir hyperspectral imaging |
| topic | Diospyros kaki, internal fruit quality, soluble tannins, astringency, classification, computer vision. J11 Handling, transport, storage and protection of plant products Diospyros kaki Food quality Image analysis |
| url | http://hdl.handle.net/20.500.11939/5726 http://www.sciencedirect.com/science/article/pii/S0023643816307344 |
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