Insausti Barrenetxea, Kizkitza
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Insausti Barrenetxea
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Kizkitza
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Agronomía, Biotecnología y Alimentación
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IS-FOOD. Research Institute on Innovation & Sustainable Development in Food Chain
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Publication 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 GobernuaCharacteristics 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.Publication 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 UnibertsitateNowadays, 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.