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Artículo
Measurement of Ripening of Raspberries (Rubus idaeus L) by Near Infrared and Colorimetric Imaging Techniques
dc.creator | Rodríguez Pulido, Francisco José | es |
dc.creator | Gil Vicente, María | es |
dc.creator | Gordillo Arrobas, Belén | es |
dc.creator | Heredia Mira, Francisco José | es |
dc.creator | González-Miret Martín, María Lourdes | es |
dc.date.accessioned | 2024-03-14T15:30:23Z | |
dc.date.available | 2024-03-14T15:30:23Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Rodríguez Pulido, F.J., Gil Vicente, M., Gordillo Arrobas, B., Heredia Mira, F.J. y González-Miret Martín, M.L. (2017). Measurement of Ripening of Raspberries (Rubus idaeus L) by Near Infrared and Colorimetric Imaging Techniques. Journal of Food Science and Technology, 54 (9), 2797-2803. https://doi.org/10.1007/s13197-017-2716-3. | |
dc.identifier.issn | 0022-1155 | es |
dc.identifier.issn | 0975-8402 | es |
dc.identifier.uri | https://hdl.handle.net/11441/156276 | |
dc.description.abstract | This work includes the evaluation of 168 samples of raspberries ‘Glen Lyon’, representing whole maturation period, by colorimetric and near infrared imaging techniques, as well as the quantification of total phenols, total anthocyanins and antioxidant activity by chemical methods. Samples showed significant differences depending on the maturation stage using CIELAB colour parameters and total anthocyanins content. The application of partial least squares regression allowed predicting the chemical features from image analysis data, with coefficients of determination (R2) up to 0.75. The best prediction for total anthocyanins including colorimetric data was observed. The proposed methodology can be used as a reference method for assessing important quality attributes of raspberries. Moreover, it is useful, rapid and accurate automatic inspection method. | es |
dc.description.sponsorship | Junta de Andalucía PE11-AGR-7843 | es |
dc.format | application/pdf | es |
dc.format.extent | 32 p. | es |
dc.language.iso | eng | es |
dc.publisher | Springer Nature | es |
dc.relation.ispartof | Journal of Food Science and Technology, 54 (9), 2797-2803. | |
dc.subject | Hyperspectral image analysis | es |
dc.subject | Image analysis | es |
dc.subject | Partial least squares regression | es |
dc.subject | Phenolics | es |
dc.subject | Raspberry ‘Glen Lyon’ (Rubus idaeus L) | es |
dc.title | Measurement of Ripening of Raspberries (Rubus idaeus L) by Near Infrared and Colorimetric Imaging Techniques | es |
dc.type | info:eu-repo/semantics/article | es |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Nutrición y Bromatología, Toxicología y Medicina Legal | es |
dc.relation.projectID | PE11-AGR-7843 | es |
dc.relation.publisherversion | https://dx.doi.org/10.1007/s13197-017-2716-3 | es |
dc.identifier.doi | 10.1007/s13197-017-2716-3 | es |
dc.journaltitle | Journal of Food Science and Technology | es |
dc.publication.volumen | 54 | es |
dc.publication.issue | 9 | es |
dc.publication.initialPage | 2797 | es |
dc.publication.endPage | 2803 | es |
dc.contributor.funder | Junta de Andalucía | es |
Ficheros | Tamaño | Formato | Ver | Descripción |
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