[1]
S. Andrés, I. Murray, E. Navajas, A. Fisher, N. Lambe, and L. Bunger, Prediction of sensory characteristics of lamb meat samples by near infrared reflectance spectroscopy, Meat Science. 76 (2007) 509-516.
DOI: 10.1016/j.meatsci.2007.01.011
Google Scholar
[2]
C. Venel, A. M. Mullen, G. Downey, and D. Troy, Prediction of tenderness and other quality attributes of beef by near infrared reflectance spectroscopy between 750 and 1100 nm; further studies, Journal of Near Infrared Spectroscopy. 9 (2001) 185-198.
DOI: 10.1255/jnirs.305
Google Scholar
[3]
M. L. Ahnström, M. C. Hunt, and K. Lundström, Effects of pelvic suspension of beef carcasses on quality and physical traits of five muscles from four gender-age groups, Meat Science. 90 (2012) 528-535.
DOI: 10.1016/j.meatsci.2011.09.003
Google Scholar
[4]
A. Serrano, J. Librelotto, S. Cofrades, F. Sanchez-Muniz, and F. Jiménez-Colmenero, Composition and physicochemical characteristics of restructured beef steaks containing walnuts as affected by cooking method, Meat Science. 77 (2007) 304-313.
DOI: 10.1016/j.meatsci.2007.03.017
Google Scholar
[5]
J. Aalhus, S. Jones, A. Tong, L. Jeremiah, W. Robertson, and L. Gibson, The combined effects of time on feed, electrical stimulation and aging on beef quality, Canadian Journal of Animal Science. 72 (1992) 525-535.
DOI: 10.4141/cjas92-065
Google Scholar
[6]
M. S. Brewer and J. Novakofski, Cooking rate, pH and final endpoint temperature effects on color and cook loss of a lean ground beef model system, Meat Science. 52 (1999) 443-451.
DOI: 10.1016/s0309-1740(99)00028-5
Google Scholar
[7]
M. Viljoen, L. Hoffman, and T. Brand, Prediction of the chemical composition of mutton with near infrared reflectance spectroscopy, Small Ruminant Research. 69 (2007) 88-94.
DOI: 10.1016/j.smallrumres.2005.12.019
Google Scholar
[8]
E. Delgado, M. Rubio, F. Iturbe, R. Méndez, L. Cassís, and R. Rosiles, Composition and quality of Mexican and imported retail beef in Mexico, Meat Science. 69 (2005) 465-471.
DOI: 10.1016/j.meatsci.2004.10.003
Google Scholar
[9]
V. Alonso, M. M. Campo, L. Provincial, P. Roncalés, and J. A. Beltrán, Effect of protein level in commercial diets on pork meat quality, Meat Science. 85 (2010) 7-14.
DOI: 10.1016/j.meatsci.2009.11.015
Google Scholar
[10]
G. Stolowski, B. Baird, R. Miller, J. Savell, A. Sams, J. Taylor, J. Sanders, and S. Smith, Factors influencing the variation in tenderness of seven major beef muscles from three Angus and Brahman breed crosses, Meat Science. 73 (2006) 475-483.
DOI: 10.1016/j.meatsci.2006.01.006
Google Scholar
[11]
N. Prieto, R. Roehe, P. Lavín, G. Batten, and S. Andrés, Application of near infrared reflectance spectroscopy to predict meat and meat products quality: A review, Meat Science. 83 (2009) 175-186.
DOI: 10.1016/j.meatsci.2009.04.016
Google Scholar
[12]
M. D. Aaslyng, C. Bejerholm, P. Ertbjerg, H. C. Bertram, and H. J. Andersen, Cooking loss and juiciness of pork in relation to raw meat quality and cooking procedure, Food quality and preference. 14 (2003) 277-288.
DOI: 10.1016/s0950-3293(02)00086-1
Google Scholar
[13]
T. Nishimura, A. Hattori, and K. Takahashi, Structural changes in intramuscular connective tissue during the fattening of Japanese Black cattle: effect of marbling on beef tenderization, Journal of Animal Science. 77 (1999) 93.
DOI: 10.2527/1999.77193x
Google Scholar
[14]
P. Toscas, F. Shaw, and S. Beilken, Partial least squares (PLS) regression for the analysis of instrument measurements and sensory meat quality data, Meat Science. 52 (1999) 173-178.
DOI: 10.1016/s0309-1740(98)00165-x
Google Scholar
[15]
L. Meinert, S. C. Christiansen, L. Kristensen, C. Bjergegaard, and M. D. Aaslyng, Eating quality of pork from pure breeds and DLY studied by focus group research and meat quality analyses, Meat Science. 80 (2008) 304-314.
DOI: 10.1016/j.meatsci.2007.12.021
Google Scholar