Authentication of cattle finishing diets (conventional vs. vegetable by-products) using near-infrared spectroscopy
| dc.contributor.author | León Ecay, Sara | |
| dc.contributor.author | López Maestresalas, Ainara | |
| dc.contributor.author | Goenaga Uceda, Irantzu | |
| dc.contributor.author | Mendizábal Aizpuru, José Antonio | |
| dc.contributor.author | Insausti Barrenetxea, Kizkitza | |
| dc.contributor.department | Institute on Innovation and Sustainable Development in Food Chain - ISFOOD | en |
| dc.contributor.funder | Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa | |
| dc.date.accessioned | 2025-08-13T08:28:15Z | |
| dc.date.available | 2025-08-13T08:28:15Z | |
| dc.date.issued | 2025 | |
| dc.date.updated | 2025-08-13T08:21:39Z | |
| dc.description.abstract | This study explored the potential of a portable near-infrared (NIR) spectrophotometer (1200 - 2200 nm; 2-nm bandwidth) to discriminate meat and carcasses from cattle fed two different diets: a control of 90% barley and 10% straw (C, n = 12) and, a ration including 37.5% of vegetable by-products (VBPR, n = 11). At 24 h postmortem spectra were collected on the exterior surface of the left carcass, first, between the 5th and 6th ribs, and afterwards, on the 12th and 13th ribs. After fabrication and 7 d of aging, spectral data was acquired from the intact steaks while keeping muscle integrity. When spectra were collected from the carcasses, partial least squares-discriminant analysis (PLS-DA) correctly classified (%CC) >66.67% in both Train and cross-validation (CV) whereas radial basis function-support vector machine (RBF-SVM) discriminated 100 - 83.33% in Train and CV, respectively, using the full spectrum. Reducing the initial matrix ((λ=501) by interval-PLS (iPLS) led into a >75% of well-sorted carcasses by finishing diet while RBFSVM increased the %CC up to >83.33%. Using both discriminant approaches, carcasses were authenticated with a subtle improvement over intact meat (>90% vs. >75% in Train and >80% vs. >65% in CV for C and VBPR, respectively). Variable importance in projection (VIP) scores showed how variables >1592 nm had higher weight in the discrimination process. The results achieved showed the potential of NIR technology as a sustainable, fast and chemical-free tool to assist the integration of the meat industry into the digital age of connectivity and digitization. | en |
| dc.description.sponsorship | This research has been founded by the Government of Navarra and the European Regional Development Fund via project BEEF+ 'Carne saludable a través de la economía circular' (0011-1365-2020-000288), by Universidad Pública de Navarra through a PhD scholarship UPNA-2022 (Res.2178/2022) and, an Industrial PhD 2020 scholarship from the Government of Navarra (0011-1408-2020-000009). | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.citation | León-Ecay, S., López-Maestresalas, A., Goenaga, I., Mendizabal, J. A., Insausti, K. (2025) Authentication of cattle finishing diets (conventional vs. vegetable by-products) using near-infrared spectroscopy. In Katsoulas N. (Ed.), Agricultural Engineerring challenges in existing and new agroecosystems: 1-4 July 2024, Agricultural University of Athens, Greece. (pp. 1159-1163). Hellenic Society of Agricultural Engineers. 978-618-82194-1-0 | |
| dc.identifier.isbn | 978-618-82194-1-0 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/54699 | |
| dc.language.iso | eng | |
| dc.publisher | Hellenic Society of Agricultural Engineers | |
| dc.relation.ispartof | In Katsoulas, N. (Ed.). Agricultural Engineerring challenges in existing and new agroecosystems: 1-4 July 2024, Agricultural University of Athens, Greece. Hellenic Society of Agricultural Engineers; 2025. p. 1159-1163 | |
| 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.rights | Con permiso de la editorial. | |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.subject | Beef | en |
| dc.subject | Feeding diet | en |
| dc.subject | Chemometrics | en |
| dc.subject | Machine learning | en |
| dc.title | Authentication of cattle finishing diets (conventional vs. vegetable by-products) using near-infrared spectroscopy | en |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dspace.entity.type | Publication | |
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