Open Access
Combination of spectral and textural features of hyperspectral imaging for the authentication of the diet supplied to fattening cattle
(Elsevier, 2024) León Ecay, Sara; Insausti Barrenetxea, Kizkitza; Arazuri Garín, Silvia; Goenaga Uceda, Irantzu; López Maestresalas, Ainara; Agronomía, Biotecnología y Alimentación; Agronomia, Bioteknologia eta Elikadura; Ingeniería; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
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.
Open Access
Comparative description of growth, fat deposition, carcass and meat quality characteristics of Basque and Large White pigs
(EDP Sciences, 2005) Alfonso Ruiz, Leopoldo; Mourot, Jacques; Insausti Barrenetxea, Kizkitza; Mendizábal Aizpuru, José Antonio; Arana Navarro, Ana; Producción Agraria; Nekazaritza Ekoizpena; Gobierno de Navarra / Nafarroako Gobernua
Characteristics of growth, fat deposition, carcass and meat quality of pigs from the Basque Black Pied breed were described and compared with those of Large White pigs. Four pens, two per breed, of eleven pigs born during the same two week period, were simultaneously fattened and slaughtered, under the same conditions. The experiment was carried out over a fixed duration (124 days) and slaughter was carried out at a fixed average age (202 days). Basque pigs showed lower growth and feed efficiency and higher backfat depth (2.6 vs. 1.7 cm, P < 0.001) than Large White pigs. The difference was especially noticeable in the middle subcutaneous fat layer (0.5 cm, P < 0.001). The meat of Basque pigs was darker, redder, more marbled, and with higher pH values than in Large White pigs. Differences in fatty acid composition were observed between breeds but they were not statistically significant (P > 0.05) because of high variability observed between animals. The Basque breed exhibited an early and higher adipose development and a higher activity of enzymes responsible for lipid synthesis than the Large White. The diameter of intramuscular adipose cells was larger in Basque (40.2 vs. 33.0 μm, P < 0.001) than in Large White pigs. The results show the particular characteristics of the Basque breed as compared to pig lines highly selected for lean growth efficiency.
Open Access
Classification of beef longissimus thoracis muscle tenderness using hyperspectral imaging and chemometrics
(MDPI, 2022) León Ecay, Sara; López Maestresalas, Ainara; Murillo Arbizu, María Teresa; Beriain Apesteguía, María José; Mendizábal Aizpuru, José Antonio; Arazuri Garín, Silvia; Jarén Ceballos, Carmen; Bass, Phillip D.; Colle, Michael J.; García, David; Romano Moreno, Miguel; Insausti Barrenetxea, Kizkitza; Agronomia, Bioteknologia eta Elikadura; Ingeniaritza; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Agronomía, Biotecnología y Alimentación; Ingeniería; Gobierno de Navarra / Nafarroako Gobernua Universidad Pública de Navarra / Nafarroako Unibertsitate
Nowadays, the meat industry requires non-destructive, sustainable, and rapid methods that can provide objective and accurate quality assessment with little human intervention. Therefore, the present research aimed to create a model that can classify beef samples from longissimus thoracis muscle according to their tenderness degree based on hyperspectral imaging (HSI). In order to obtain different textures, two main strategies were used: (a) aging type (wet and dry aging with or without starters) and (b) aging times (0, 7, 13, 21, and 27 days). Categorization into two groups was carried out for further chemometric analysis, encompassing group 1 (ngroup1 = 30) with samples with WBSF < 53 N whereas group 2 (ngroup2 = 28) comprised samples with WBSF values 53 N. Then, classification models were created by applying the partial least squares discriminant analysis (PLS-DA) method. The best results were achieved by combining the following pre-processing algorithms: 1st derivative + mean center, reaching 70.83% of correctly classified (CC) samples and 67.14% for cross validation (CV) and prediction, respectively. In general, it can be concluded that HSI technology combined with chemometrics has the potential to differentiate and classify meat samples according to their textural characteristics.

Insausti Barrenetxea, Kizkitza

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