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Research Article | Open Access

A comparative analysis of carcass and meat traits of yaks

Yu Ma1Guoyuan Ma1Xiangying Kong2Hongmei Shi3Li Zhang1( )Qunli Yu1Xue Yang1Ya Zheng4
College of Food Science and Engineering, Gansu Agricultural University, Lanzhou 730070, China
Haibei Tibetan Autonomous Prefecture Agricultural and Livestock Integrated Service Center, Haiyan 810299, China
Gannan Tibetan Autonomous Prefecture Livestock Workstation, Hezuo 747000, China
Institute of Agricultural Product Storage and Processing, Gansu Academy of Agricultural Sciences, Lanzhou 730000, China
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Abstract

This study primarily compares the carcass and meat quality traits of yaks of different ages and genders. Measurements of carcass weight and characteristics were taken for male and female Gannan yaks aged 1–2, 2–4, 4–6, and 6 years and older. Additionally, the weight and meat quality of 9 major cuts were measured. The results indicated significant variations in various aspects of yak carcasses around the age of 4, and substantial differences between male and female yaks after the age of 4. Different body regions showed distinct meat quality. The tenderness of the tenderloin is the highest (P < 0.05), while the striploin is the lowest (P < 0.05), and the protein content of the hindquarter cuts is higher. Principal component analysis (PCA) was employed to identify key factors significantly affecting total meat yield. Subsequently, predictive models for total meat yield were developed for yaks aged 1–4 years, 4+ years for males, and 4+ years for females based on these factors. Furthermore, the meat from the 9 major cuts was classified according to its intrinsic meat quality traits, which holds significant reference value for the assessment of yak carcass yield grades and the grading of quality in meat cuts, ultimately contributing to the realization of the full potential of the yak meat industry.

References

[1]

G. B. Schaller, W. Liu, Distribution, status, and conservation of wild yak Bos grunniens, Biol. Conserv. 76 (1996) 1–8. https://doi.org/10.1016/0006-3207(96)85972-6.

[2]

A. Fischer, T. Luginbühl, L. Delattre, et al., Rear shape in 3 dimensions summarized by principal component analysis is a good predictor of body condition score in Holstein dairy cows, J. Dairy Sci. 98 (2015) 4465–4476. https://doi.org/10.3168/jds.2014-8969.

[3]

C. Wakholi, J. Kim, S. Nabwire, et al., Deep learning feature extraction for image-based beef carcass yield estimation, Biosystems Engineering. 218 (2022) 78–93. https://doi.org/10.1016/j.biosystemseng.2022.04.008.

[4]

X. Bai, W. Tian, F. Yin, et al., Age-specific effect on endogenous oxidative and antioxidative characteristics of longissimus thoracis muscle of yak during early postmortem period, Food Chem. 374 (2022) 131829. https://doi.org/10.1016/j.foodchem.2021.131829.

[5]

H. W. Seo, H. V. Ba, P. N. Seong, et al., Relationship between body size traits and carcass traits with primal cuts yields in Hanwoo steers, Anim. Biosci. 34 (2021) 127–133. https://doi.org/10.5713/ajas.19.0809.

[6]

L. Zhang, B. Sun, Q. Yu, et al., The breed and sex effect on the carcass size performance and meat quality of yak in different muscles, Korean J. Food Sci. An. 36 (2016) 223–229. https://doi.org/10.5851/kosfa.2016.36.2.223.

[7]

A. Cecchinato, M. de Marchi, M. Penasa, et al., Near-infrared reflectance spectroscopy predictions as indicator traits in breeding programs for enhanced beef quality, J. Anim. Sci. 89 (2011) 2687–2695. https://doi.org/10.2527/jas.2010-3740.

[8]

T. Needham, J. G. Laubser, R. Kotrba, et al., Sensory characteristics of the Longissimus thoracis et lumborum and Biceps femoris muscles from male and female common eland (Taurotragus oryx), Meat Sci. 158 (2019) 107918. https://doi.org/10.1016/j.meatsci.2019.107918.

[9]

K. O. Honikel, Reference methods for the assessment of physical characteristics of meat, Meat Sci. 49 (1998) 447–457. https://doi.org/10.1016/S0309-1740(98)00034-5.

[10]

N. Prieto, S. Andrés, F. J. Giráldez, et al., Ability of near infrared reflectance spectroscopy (NIRS) to estimate physical parameters of adult steers (oxen) and young cattle meat samples, Meat Sci. 79 (2008) 692–699. https://doi.org/10.1016/j.meatsci.2007.10.035.

[11]

M. C. Bourne, Texture profile analysis, Food Technology 32 (1978) 62–72.

[12]

A. Heggli, O. Alvseike, F. Bjerke, et al., Carcase grading reflects the variation in beef yield: a multivariate method for exploring the relationship between beef yield and carcase traits, Animals 17 (2023) 100854. https://doi.org/10.1016/j.animal.2023.100854.

[13]

C. Gajaweera, K. Y. Chung, S. H. Lee, et al., Assessment of carcass and meat quality of Longissimus thoracis and Semimembranosus muscles of Hanwoo with Korean beef grading standards, Meat Sci. 160 (2020) 107944. https://doi.org/10.1016/j.meatsci.2019.107944.

[14]

P. Polidori, S. Pucciarelli, N. Cammertoni, et al., The effects of slaughter age on carcass and meat quality of Fabrianese lambs, Small Ruminant Res. 155 (2017) 12–15. https://doi.org/10.1016/j.smallrumres.2017.08.012.

[15]

J. Soulat, B. Picard, V. Monteils, Influence of cattle category and slaughter age on Charolais-breed carcase and meat traits, Ital. J. Anim. Sci. 22 (2023) 263–275. https://doi.org/10.1080/1828051X.2023.2182720.

[16]

A. Turan, H. Yalcintan, A. Orman, et al., Effects of gender and slaughter age on meat quality of Anatolian water buffaloes, Trop. Anim. Health Prod. 53 (2021) 415. https://doi.org/10.1007/s11250-021-02835-8.

[17]

S. S. C. Maulid, A. Susilo, D. P, Kuswati, The effect of slaughter age and sex class to carcass characteristic of red Brahman crossbred cattle, IOP Conf. Ser. :Earth Environ. Sci. 888 (2021) 012028. https://doi.org/10.1088/1755-1315/888/1/012028.

[18]

L. Xie, J. Qin, L. Rao, et al., Effects of carcass weight, sex and breed composition on meat cuts and carcass trait in finishing pigs, J. Integr. Agr. 22 (2023) 1489–1501. https://doi.org/10.1016/j.jia.2022.08.122.

[19]

D. Matthews, T. Pabiou, R. D. Evans, et al., Predicting carcass cut yields in cattle from digital images using artificial intelligence, Meat Sci. 184 (2022) 108671. https://doi.org/10.1016/j.meatsci.2021.108671.

[20]

J. Segura, J. L. Aalhus, N. Prieto, et al., Prediction of primal and retail cut weights, tissue composition and yields of youthful cattle carcasses using computer vision systems; whole carcass camera and/or ribeye camera, Meat Sci. 199 (2023) 109120. https://doi.org/10.1016/j.meatsci.2023.109120.

[21]

P. Negretti, G. Bianconi, G. Cannata, et al., Visual Image Analysis for a new classification method of bovine carcasses according to EU legislation criteria, Meat Sci. 183 (2022) 108654. https://doi.org/10.1016/j.meatsci.2021.108654.

[22]

M. Naserkheil, D. Lee, K. Chung, et al., Estimation of genetic correlations of primal cut yields with carcass traits in Hanwoo beef cattle, Animals 11 (2021) 3102. https://doi.org/10.3390/ani11113102.

[23]

S. N. McCarthy, M. Henchion, A. White, et al., Evaluation of beef eating quality by Irish consumers, Meat Sci. 132 (2017) 118–124. https://doi.org/10.1016/j.meatsci.2017.05.005.

[24]

J. Żurek, M. Rudy, R. Stanisławczyk, et al., The effect of kosher determinants of beef on its color, texture profile and sensory evaluation, Int. J. Env. Res. Pub. He. 20 (2023) 1378. https://doi.org/10.3390/ijerph20021378.

[25]

J. H. Kim, D. H. Kim, D. Ji, et al., Effect of aging process and time on physicochemical and sensory evaluation of raw beef top round and shank muscles using an electronic tongue, Korean J. Food Sci. Anim. Resour. 37 (2017) 823–832. https://doi.org/10.5851/kosfa.2017.37.6.823.

[26]

L. W. Coleman, N. M. Schreurs, P. R. Kenyon, et al., Growth, carcass and meat quality characteristics of Charolais-sired steers and heifers born to Angus-cross-dairy and Angus breeding cows, Meat Sci. 201 (2023) 109178. https://doi.org/10.1016/j.meatsci.2023.109178.

[27]

A. Listrat, M. Gagaoua, J. Normand, et al., Are there consistent relationships between major connective tissue components, intramuscular fat content and muscle fibre types in cattle muscle?, Animals. 14 (2020) 1204–1212. https://doi.org/10.1017/S1751731119003422.

[28]

R. P. Daniels, J. C. Wicks, M. D. Zumbaugh, et al., Reduced scald time does not influence ultimate pork quality, Meat Sci. 194 (2022) 108958. https://doi.org/10.1016/j.meatsci.2022.108958.

[29]

A. Hailemariam, W. Esatu, S. Abegaz, et al., Effect of genotype and sex on breast meat quality characteristics of different chickens, J. Agri. Food Res. 10 (2022) 100423. https://doi.org/10.1016/j.jafr.2022.100423.

[30]

A. J. Mueller, C. J. Maynard, A. R. Jackson, et al., Assessment of meat quality attributes of four commercial broiler strains processed at various market weights, Poultry Sci. 102 (2023) 102571. https://doi.org/10.1016/j.psj.2023.102571.

[31]

S. Liu, Y. Zhang, G. Zhou, et al., Protein degradation, color and textural properties of low sodium dry cured beef, Int. J. Food Prop. 22 (2019) 487–498. https://doi.org/10.1080/10942912.2019.1591444.

[32]

H. Zhuang, E. M. Savage, Comparisons of sensory descriptive flavor and texture profiles of cooked broiler breast fillets categorized by raw meat color lightness values1, Poultry Sci. 89 (2010) 1049–1055. https://doi.org/10.3382/ps.2009-00422.

[33]

M. A. Akbar, K. Javed, A. Faraz, et al., Principal component analysis of morphometric traits explain the morphological structure of Thalli sheep, Pak. J. Zool. 54 (2022) 207–212. https://doi.org/10.17582/journal.pjz/20200220060257.

[34]
A. K. Mishra, A. Jain, S. Singh, et al., Study of body conformation of carpet wool type Chitarangi sheep of India using principal component analysis, Ind. J. Anim. Sci. (2021). https://doi.org/10.18805/IJAR.B-4285.
[35]
V. E. Ormachea, C. B. Calsin, S. E. Aguilar, et al., Principal component analysis of morphological characteristics in Creole sheep (Ovis aries), AAVS 11 (2023). https://doi.org/10.17582/journal.aavs/2023/11.6.903.909.
[36]
A. William Canaza-Cayo, R. Reis Mota, F. Amarilho-Silveira, et al., Principal Component Analysis for Body Weight Prediction of Corriedale Ewes from Southern Peru, JAHP 9 (2021). https://doi.org/10.17582/journal.jahp/2021/9.4.417.424.
[37]

D. K. Yadav, R. Arora, A. Jain, Predicting body weights of Kolhapuri sheep using principal component scores, Indian Journal of Small Ruminants. 27 (2021) 168–172. https://doi.org/10.5958/0973-9718.2021.00030.1.

[38]

B. S. Mavule, V. Muchenje, C. C. Bezuidenhout, et al., Morphological structure of Zulu sheep based on principal component analysis of body measurements, Small Ruminant Res. 111 (2013) 23–30. https://doi.org/10.1016/j.smallrumres.2012.09.008.

Food Science of Animal Products
Article number: 9240035
Cite this article:
Ma Y, Ma G, Kong X, et al. A comparative analysis of carcass and meat traits of yaks. Food Science of Animal Products, 2023, 1(3): 9240035. https://doi.org/10.26599/FSAP.2023.9240035

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Received: 31 July 2023
Revised: 09 August 2023
Accepted: 28 October 2023
Published: 18 December 2023
© Beijing Academy of Food Sciences 2023.

Food Science of Animal Products published by Tsinghua University Press. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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