Combination of spectral and textural features of hyperspectral imaging for the authentication of the diet supplied to fattening cattle
| dc.contributor.author | León Ecay, Sara | |
| dc.contributor.author | Insausti Barrenetxea, Kizkitza | |
| dc.contributor.author | Arazuri Garín, Silvia | |
| dc.contributor.author | Goenaga Uceda, Irantzu | |
| dc.contributor.author | López Maestresalas, Ainara | |
| dc.contributor.department | Agronomía, Biotecnología y Alimentación | es_ES |
| dc.contributor.department | Agronomia, Bioteknologia eta Elikadura | eu |
| dc.contributor.department | Ingeniería | es_ES |
| dc.contributor.department | Ingeniaritza | eu |
| dc.contributor.department | Institute on Innovation and Sustainable Development in Food Chain - ISFOOD | en |
| dc.contributor.funder | Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa | es |
| dc.date.accessioned | 2024-02-02T15:44:05Z | |
| dc.date.available | 2024-02-02T15:44:05Z | |
| dc.date.issued | 2024 | |
| dc.date.updated | 2024-02-02T15:28:40Z | |
| dc.description.abstract | This study explored the potential of hyperspectral imaging in the near infrared region (NIR-HSI) as a non-destructive and rapid tool to discriminate among two beef fattening diets. For that purpose, a feeding trial was carried out with a total of 24 purebred Pirenaica calves. Twelve of them were fed barley and straw (BS) while 11 animals were finished on vegetable by-products (VBPR). When comparing the reference measurements of the meat coming from those animals, only the total collagen ratio expressed the feeding effect (p-value<0.05). To undertake the authentication procedure, two discrimination approaches were run: partial least squares discriminant analysis (PLS-DA) and radial basis function-support vector machine (RBF-SVM). To precisely extract spectral and textural information from the lean portion of the meat steaks, various techniques were executed, such as principal component (PC) images, competitive adaptive reweighted sampling (CARS) for selecting optimal wavelengths, and gray-level-co-occurrence matrix (GLCM). After hyperspectral imaging and the combination of their own texture features, samples were classified according to feeding diet with an overall accuracy of 72.92% for PLS-DA and 80.56% for RBF-SVM. So, the potential of using HSI technology to authenticate the meat obtained from beef supplied a diet based on circular economy techniques was made in evidence. | en |
| dc.description.sponsorship | This research was funded by Universidad Pública de Navarra through a PhD scholarship (UPNA-2022 (Res.2178/2022)), by the Government of Navarra in the framework of an Industrial PhD 2020 scholarship (0011-1408-2020-000009), and by the Government of Navarra and the European Regional Development Fund (ERDF) via project BEEF+ “Carne saludable a través de la economía circular” 0011-1365-2020-000288. Open access funding provided by Universidad Pública de Navarra. | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | León-Ecay, S., Insausti, K., Arazuri, S., Goenaga, I., López-Maestresalas, A. (2024) Combination of spectral and textural features of hyperspectral imaging for the authentication of the diet supplied to fattening cattle. Food Control, 159, 1-12. https://doi.org/10.1016/j.foodcont.2024.110284. | en |
| dc.identifier.doi | 10.1016/j.foodcont.2024.110284 | |
| dc.identifier.issn | 0956-7135 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/47322 | |
| dc.language.iso | eng | en |
| dc.publisher | Elsevier | en |
| dc.relation.ispartof | Food Control, 159, 2024, 110284 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/Gobierno de Navarra//0011-1408-2020-000009/ | |
| dc.relation.projectID | info:eu-repo/grantAgreement/Gobierno de Navarra//0011-1365-2020-000288/ | |
| dc.relation.publisherversion | https://doi.org/10.1016/j.foodcont.2024.110284 | |
| dc.rights | © 2024 The Authors. This is an open access article under the CC BY-NC license. | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0/ | |
| dc.subject | Meat quality | en |
| dc.subject | Animal feeding | en |
| dc.subject | Hyperspectral imaging | en |
| dc.subject | Feature combination | en |
| dc.subject | Machine learning | en |
| dc.title | Combination of spectral and textural features of hyperspectral imaging for the authentication of the diet supplied to fattening cattle | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dspace.entity.type | Publication | |
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