Short communication: Using infrared ocular thermography as a tool to predict meat quality from lean cattle breeds prior to slaughter: Exploratory trial

Alberto Horcada, Manuel Juárez, Mercedes Valera, Ester Bartolomé

Abstract


Aim of study: To assess the potential of using infrared ocular thermography (IROT) as a tool to predict beef quality at the slaughterhouse.

Area of study: The study was carried out in the Salteras’s slaughterhouse (Seville, Spain).

Material and methods: Ocular temperature images were captured from 175 lean young bulls prior to slaughter. Carcasses were classified into three groups according to weight: ˂250 kg, 250-310 kg and ˃310 kg. IROT was measured just before slaughter and pH was measured 24 h later. Colour parameters (CIELAB space) were evaluated 48 h post-slaughter. Water holding capacity was evaluated at seven days after slaughter.

Main results: IROT mean values were higher in heavier bulls (p<0.05), probably due to these animals appeared to movilize a greater blood flow, thus increasing ocular temperature. Furthermore, IROT showed a statistically significant correlation with both pH from light carcasses (r=0.66; p<0.001), and mean Hue value from all carcass weights (r=-0.22; p<0.05). A quadratic regression analysis accounting carcass weight as a continuous variable, found medium to strong fit values for pH (R2=0.52; RMSE=0.032; p<0.01) and medium fit values for H* (R2=0.41; RMSE=3.793; p<0.001), changing their relation with IROT depending on carcass weight.

Research highlights: IROT showed potential to become a useful tool to assess pH in light carcasses and to assess H* in all carcasses of young bulls prior to slaughter, regardless their weight. However, further studies would be recommended under more variable pre-slaughter stress conditions.


Keywords


eye temperature; Spanish native cattle breeds; beef quality; stress; water holding capacity; colour parameters, pH

Full Text:

PDF HTML XML

References


Alcalde MJ, Suárez M, Rodero E, Álvarez R, Saéz M, Martínez T, 2017. Effects of farm management practices and transport duration on stress response and meat quality traits of suckling goat kids. Animal 11: 1626-1635. https://doi.org/10.1017/S1751731116002858

Amakiri SF, 1976. Arteriovenous anastomoses in the skin of tropical cattle. Acta Anat 96: 285-300. https://doi.org/10.1159/000144680

Church J, Hegadoren P, Paetkau M, Miller C, Regev-Shoshani G, Schaefer A, Schwartzkopf-Genswein K, 2014. Influence of environmental factors on infrared eye temperature measurements in cattle. Res Vet Sci 96: 220-226. https://doi.org/10.1016/j.rvsc.2013.11.006

CIE, 1986. Official Recommendations on Uniform Colour Spaces. Colour Difference Equations and Metric Colour Terms. Suppl. No. 2. Commission International de l'Éclairage, Publication No. 15, Colourimetry. Paris.

EC, 2005. Council Regulation (EC) No 1/2005 of 22 December 2004 on the protection of animals during transport and related operations. https://eur-lex.europa.eu/eli/reg/2005/1/oj (Accessed 15.08.2019).

EC, 2009. Council Regulation (EC) No 1099/2009 of 24 September 2009 on the protection of animals at the time of killing. https://eur-lex.europa.eu/eli/reg/2009/1099/oj (Accessed 15.08.2019).

Eriksen M, Rødbotten R, Grøndahl A, Friestad M, Andersen I, Mejdell C, 2013. Mobile abattoir versus conventional slaughterhouse-Impact on stress parameters and meat quality characteristics in Norwegian lambs. Appl Ani Behav. Sci 149: 21-29. https://doi.org/10.1016/j.applanim.2013.09.007

Gagaoua M, Picard B, Monteils V, 2018. Associations among animal, carcass, muscle characteristics, and fresh meat color traits in Charolais cattle. Meat Sci 140: 145-156. https://doi.org/10.1016/j.meatsci.2018.03.004

Grau R, Hamm R, 1953. In: Muscle as food; Bechtel PJ (Ed). Food Science and Technology, A Series of Monograph. Academic Press, NY.

Johnson S, Rao S, Hussey S, Morley P, Traub-Dargatz J, 2011. Thermographic eye temperature as an index to body temperature in ponies. J Equine Vet Sci 31: 63-66. https://doi.org/10.1016/j.jevs.2010.12.004

Lacourt A, Tarrant PV, 1985. Glycogen depletion patterns in myofibres of cattle during stress. Meat Sci 15 (2): 85-100. https://doi.org/10.1016/0309-1740(85)90049-X

Loredo-Osti J, Sánchez-López E, Barreras-Serrano A, Figueroa-Saavedra F, Pérez-Linares C, Ruiz-Albarrán M, Domínguez-Muñoz MA, 2019. An evaluation of environmental, intrinsic and pre- and post-slaughter risk factors associated to dark-cutting beef in a federal inspected type slaughter plant. Meat Sci 150: 85-92. https://doi.org/10.1016/j.meatsci.2018.12.007

Losada-Espinosa N, Villarroel M, María G, Miranda-de la Lama G, 2018. Pre-slaughter cattle welfare indicators for use in commercial abattoirs with voluntary monitoring systems: A systematic review. Meat Sci 138: 34-38. https://doi.org/10.1016/j.meatsci.2017.12.004

Lu X, Zhang Y, Qin L, Ma W, Zhu L, Luo X, 2018. Association of ultimate pH and stress-related blood variables in cattle. Meat Sci 139: 228-230. https://doi.org/10.1016/j.meatsci.2018.02.004

MacDougall DB, 1986. The chemistry of colour and appearance. Food Chem 21 (4): 283-299. https://doi.org/10.1016/0308-8146(86)90063-4

Martins RF, Paim TP, Cardoso CA, Dallago BS, Melo CB, Louvandini H, Mcmanus C, 2013. Mastitis detection in sheep by infrared thermograpy. Res Vet Sci 94 (3): 722-724. https://doi.org/10.1016/j.rvsc.2012.10.021

McManus C, Tanure C, Peripolli V, Seixas L, Fischer V, Gabbi A, Menegassi S, Stumpf M, Kolling G, Dias E, Costa J, 2016. Infrared thermography in animal production: An overview. Comput Electron Agric 123: 10-16. https://doi.org/10.1016/j.compag.2016.01.027

Morgan S, Schaefer A, Tong A, Scott S, Gariépy C, Graham R, 1995. Method for detecting poor meat quality in live animals. Patent W01995001567 A1-1995.

Peña F, Avilés C, Domenech V, González A, Martínez A, Molina A, 2014. Effects of stress by unfamiliar sounds on carcass and meat traits in bulls from three continental beef cattle breeds at different ageing times. Meat Sci 98: 718-725. https://doi.org/10.1016/j.meatsci.2014.07.021

Rocha LM, Devillers N, Maldague X, Kabemba FZ, Fleuret J, Guay F, Faucitano L, 2019. Validation of anatomical sites for the measurement of infrared body surface temperature variation in response to handling and transport. Animals 9: 425-443. https://doi.org/10.3390/ani9070425

Schaefer AL, Matthews LR, Cook NJ, Webster J, Scott SL, 2002. Novel non-invasive measures of animal welfare. Animal Welfare and Behaviour, from science to solution joint NAWAC/ISAE Conference, Hamilton, New Zealand.

Stewart M, Webster JR, Verkerk G, Schaefer L, Colyn JJ, Stafford KJ, 2007. Non-invasive measurement of stress in dairy cows using infrared thermography. Physiol Behav 92: 520-525. https://doi.org/10.1016/j.physbeh.2007.04.034

Vieira C, Cerdeño A, Serrano E, Lavín P, Mantecó AR, 2007. Breed and ageing extent on carcass and meat quality of beef from adult steers (oxen). Livest Sci 107: 62-69. https://doi.org/10.1016/j.livsci.2006.09.004

Viera de Sousa R, Da Silva A, Gomes de Abreu M, Tabile R, Silva L, 2018. Predictive model based on artificial neural network for assessing beef cattle thermal stress using weather and physiological variables. Comput Electron Agric 144: 37-43. https://doi.org/10.1016/j.compag.2017.11.033

Weschenfelder AV, Saucier L, Maldague X, Rocha LM, Schaefer AL, Faucitano, L, 2013. Use of infrared ocular thermography to assess physiological conditions of pigs prior to slaughter and predict pork quality variation. Meat Sci 95 (3): 616-620. https://doi.org/10.1016/j.meatsci.2013.06.003




DOI: 10.5424/sjar/2019174-15487