Prediction of Meat Quality Using Infrared Orbital Temperature as a Non-Invasive Tool in Karacabey Merino, Hungarian Merino and Kivircik Lambs

Abstract

The study was conducted to predict meat quality using infrared orbital temperature (IROT) as a non-invasive tool in lambs. The study was carried out on a commercial sheep farm. IROT images were collected from 70 male lambs before slaughter. IROT images of lambs were collected with an infrared camera (FLIR, T540). Meat colour parameters, drip loss, expressed juice and meat pH were evaluated as predictors of meat quality. Linear and quadratic regression analysis was used to investigate the relationship of IROT with numerous meat quality variables. IROT value showed a significant correlation with expressed juice (r=-0.416 P<0.05) in Karacabey Merino, and meat redness (r=0.407, P<0.05) and lightness (r=0.411, P<0.001) values in Kivircik lambs. Prediction equations for expressed juice by using IROT were significant in Karacabey (R2=0.173, RMSE=1.20, P<0.05) and, Hungarian Merino (R2=0.303, RMSE=1.67, P<0.05) lambs. In Kivircik lambs, meat redness (R2=0.165, RMSE=1.39, P<0.05) and Chroma (R2=0.169, RMSE=1.37, P<0.05) values measured after 1h blooming were predicted using IROT as well. In conclusion, IROT value might be used to predict the expressed juice, redness, and Chroma of lamb, but it is noteworthy that all equations exhibited low coefficient of determination values.

Keywords

• Lamb
• drip loss
• expressed juice
• meat colour
• meat pH

References

1. 1. Akçapınar H., Özbeyaz C. Hayvan Yetiştiriciliği Temel Bilgileri. Ankara. Kariyer Matbaacılık Ltd. Şti., 1999.
2. 2. Ekiz E, Yilmaz A, Ozcan O, Kaptan C, Hanoglu H, Erdogan I, Yalcintan H. Carcass measurements and meat quality of Turkish Merino, Ramlic, Kivircik, Chios and Imroz lambs raised under an intensive production system. Meat Sceince 2009; 82(1): 64–70. doi:10.1016/j.meatsci.2008.12.001. https://doi.org/10.1016/j.meatsci.2008.12.001
3. 3. Priolo A, Micol D, Agabriel J. Effects of grass feeding systems on ruminant meat colour and flavour. A review. Animal Research 2001; 50: 185–200. https://doi.org/10.1051/animres:2001125
4. 4. Cuthbertson H, Tarrb G, Loudonc K, Lomaxa S, Whited P, McGreevyd P, Polkinghornee R, Gonzáleza LA. Using infrared thermography on farm of origin to predict meat quality and physiological response in cattle (Bos Taurus) exposed to transport and marketing. Meat Science 2020; 169: 108173. https://doi.org/10.1016/j.meatsci.2020.108173
5. 5. Horcada A, Juárez M, Valera M, Bartolomé E. Using infrared ocular thermography as a tool to predict meat quality from lean cattle breeds prior to slaughter: Exploratory trial. Spanish Journal of Agricultural Research 2019; 17(3): 1¬7. https://doi.org/10.5424/sjar/2019174-15487
6. 6. Weschenfelder AV, Saucier L, Maldague X, Rocha LM, Schaefer AL, Faucitano L. Use of infrared ocular thermography to assess physiological conditions of pigs prior to slaughter and predict pork quality variation. Meat Science 2013; 95:616¬620. https://doi.org/10.1016/j.meatsci.2013.06.003
7. 7. Almeida MD, Stilwell G, Guedes C, Silva SR. Eye and muzzle temperatures measured using infrared thermography to assess sheep stress during shearing and foot trimming. In: Ruiz R. (ed.), López-Francos A. (ed.), López Marco L. (ed.). Innovation for sustainability in sheep and goats. Zaragoza: CIHEAM, 2019. p. 307-310. http://om.ciheam.org/article.php?IDPDF=00007903
8. 8. Joy A, Taheri S, Dunshea FR, Leury BJ, DiGiacomo K, Osei-Amponsah R, Brodie G, Chauhan S. Non-invasive measure of heat stress in sheep using machine learning techniques and infrared thermography. Small Ruminant Research 2022; 207: 106592. https://doi.org/10.1016/j.smallrumres.2021.106592

9. 9. Honikel KO. Reference methods for the assessment of physical characteristics of meat. Meat Science 1998; 49 (4): 447¬457. https://doi.org/10.1016/S0309-1740(98)00034-5
10. 10. Beriain MJ, Bas P, Purroy A, Treacher T. Effect of animal and nutritional factors and nutrition on lamb meat quality. Sheep and goat nutrition: Intake, digestion, quality of products and rangelands; Proceedings of the 8th Seminar of the Sub-Network on Nutrition of the FAO-CIHEAM Inter-Regional Cooperative Research and Development Network on Sheep and Goats, jointly organized by CIHEAM, FAO, INA-PG and INRA, Grignon (France), 3-5 September 1998; Cahiers Options Mediterraneennes (France) , v. 52 Ledin. http://om.ciheam.org/article.php?IDPDF=600313
11. 11. Centre Internationale de L’Eclairage (1976): Definition dun space de coleur por deux coordonees de cromaticite et la luminosite. Supplement 2 to CIE publication no 15 (E-1-3-1) 1971/ (TC-1-3). Cente Internationale de L’Eclairage, Paris.
12. 12. Murray AC. The Evaluation of Muscle Quality. In: Quality and Grading of Carcasses of Meat Animals 1995, CRC press, Inc. London, 83-108.
13. 13. The jamovi project, 2022. Jamovi, (Version 2.3) [Computer Software], Retrieved from https://www.jamovi.org.
14. 14. Eyduran E. The possibility of using data mining algorithms in prediction of live body weights of small ruminants. Canadian Journal of Biomedical Science 2016; 1: 1–4. http://dx.doi.org/10.21065/
15. 15. Cai Z, Cui J, Yuan H, Cheng M. Application and research progress of infrared thermography in temperature measurement of livestock and poultry animals: A review. Computers and Electronics in Agriculture 2023; 205: 107586. https://doi.org/10.1016/j.compag.2022.107586
16. 16. Simela L. Meat Characteristics and Acceptability of Chevon from South African Indigenous Goats. PhD thesis, University of Pretoria, 2005; Chapter 2; 8-52.
17. 17. Sañudo C, Sánchez A, Alfonso M. Small ruminant production systems and factors affecting lamb meat quality. Meat Science 1998; 49: 29-64. https://doi.org/10.1016/S0309-1740(98)90037-7
18. 18. McGeehin B, Sheridan JJ, Butler F. Factors affecting the pH decline in lamb after slaughter. Meat Science 2001; 58: 79¬84. https://doi.org/10.1016/S0309-1740(00)00134-0
19. 19. Abdullah YA, Musallam HS. Effect of different levels of energy on carcass composition and meat quality of male black goats kids. Livestock Science 2007; 107: 70–80. https://doi.org/10.1016/j.livsci.2006.09.028
20. 20. Yalçıntan H. Comparative investigation of finishing, slaughter, carcass and meat quality characteristics of Gokceada, Maltese, Saanen and Hair Goat kids. Istanbul University, Institute of Health Science, Animal Breeding and Husbandry. PhD Thesis. Istanbul. 2011
21. 21. Ekiz E, Kecici PD, Ograk YZ, Yalcintan H, Yilmaz A. Evaluation of the functionality of EUROP carcass classification system in thin-tailed and fat-tailed lambs. Meat Science 2021; 181: 108603. https://doi.org/10.1016/j.meatsci.2021.108603
22. 22. Priolo A, Micol D, Agabriel J, Prache S, Dransfield E. Effect of grass or concentrate feeding systems on lamb carcass and meat quality. Meat Science 2002; 62: 179–185. https://doi.org/10.1016/S0309-1740(01)00244-3
23. 23. Yalcintan H, Ekiz B, Kocak O, Dogan N, Akin P D, Yilmaz A. (2017). Carcass and meat quality characteristics of lambs reared in different seasons. Archives Animal Breeding 2017; 60: 225–233. https://doi.org/10.5194/aab-60-225-2017.