Publications

@article{mateo_lipid_2023,

title = {Lipid characteristics of the muscle and perirenal fat in young tudanca bulls fed on different levels of grass silage},

author = {Javier Mateo and Irma Caro and Sergio Soto and Sonia Andrés and Rocío Aláiz-Rodríguez and Emma Serrano},

url = {https://www.mdpi.com/2076-2615/13/2/261},

year  = {2023},

date = {2023-01-01},

journal = {Animals},

volume = {13},

number = {2},

pages = {261},

abstract = {Grass silage is commonly used as a forage source in winter for finishing bull in European regions under oceanic climates, such as the Cantabrian cornice, where the local Tudanca breed is produced. Grass silage, compared with barley straw in the bull’s diet showed an effect on beef quality, i.e., increased saturated fatty acids, n-3 fatty acids, and β-carotene and decreased monounsaturated and polyunsaturated fatty acids. Beef from silage-fed bulls and straw-fed bulls could be differentiated by fatty acid percentages, especially 18:0, t-18:1, and c9-18:1, b-carotene content, b* colour value, and carotenoid colour index.},

note = {Publisher: MDPI},

keywords = {Authentication, Beef, Fat-soluble Vitamins, Fatty Acids, Feeding System, Volatile Compounds},

pubstate = {published},

tppubtype = {article}

}

@article{guzman-martinez_differentiation_2009,

title = {Differentiation of perirenal and omental fat quality of suckling lambs according to the rearing system from Fourier transforms mid-infrared spectra using partial least squares and artificial neural networks analysis},

author = {Rocío Guzmán-Martínez and MT Osorio and JM Zumalacárregui and Rocío Alaiz-Rodríguez and SB Engelsen and Javier Mateo},

url = {https://www.sciencedirect.com/science/article/pii/S0309174009001119},

year  = {2009},

date = {2009-01-01},

urldate = {2009-01-01},

journal = {Meat science},

volume = {83},

number = {1},

pages = {140–147},

abstract = {FT-IR spectroscopy was evaluated to distinguish suckling lamb carcasses based on rearing systems (ewe’s milk vs. milk replacer). Fat samples (perirenal and omental) were analyzed for fatty acid composition, achieving perfect discrimination using PLS regression. FT-IR spectra were also analyzed using PLS and ANN models, with ANN providing better classification. Perirenal fat was perfectly classified, while omental fat had misclassification rates of 9–13%.},

note = {Publisher: Elsevier},

keywords = {Artificial Neural Networks, Ewe Milk, Fatty Acids, FT-IR, Meat Authenticity, Milk Replacers, Omental Fat, Perirenal Fat, Rearing System},

pubstate = {published},

tppubtype = {article}

}