A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle

Fikadu Wodajo Tirfie

doi:doi:10.11648/j.avs.20231103.12

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A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle

Fikadu Wodajo Tirfie

Published in Animal and Veterinary Sciences (Volume 11, Issue 3)

Received: 27 February 2023 Accepted: 12 May 2023 Published: 29 May 2023

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Abstract

This review focuses on the genetic and non-genetic parameter estimation for dairy cattle milk composition. Milk is the most widely consumed food in the world, containing proteins, fats, lactose, and various vitamins and minerals. Milk's solids content has a direct impact on both its nutritional and economic value. The milk composition trait performances had obtained in the range from 3.5±0.0038 to 6.1±0.05 for fat percentage, 3.07±0.03 to 4.7±0.09 for protein percentage, 3.3 to 5.52±1.71 for lactose content, 12.16±0.14 to 16.02±0.05 for total solid content and 8.47±0.1 to 9.37±0.24 for the solid not fat content of cow milk, respectively. The composition of cow milk is influenced by breed, animal age and health, lactation phase, nutrition, season, milking method, number of lactations, and individual cows. The heritability of milk composition trait ranged from 0.24 to 0.49±0.03 for fat percentage, 0.28 to 0.53±0.009 for protein percentage, 0.41±0.04 to 0.59 for total solid content and 0.17 to 0.68 for the solid not fat content of cow milk, respectively. The repeatability of fat, protein, total solid and solid not fat percentage of bovine milk ranged between 3.9 to 0.98, 0.4 to 0.99, 0.49 to 0.99 and 0.23 to 0.78, respectively. The genetic and phenotypic correlation between fat and solid not fat of cow milk were weakly positive (0.16±0.15, 0.06 ±0.04), whereas a strong positive relationship was found between protein content and solid not fat of cow milk (0.99±0.05, 0.67±0.03), respectively. Enhancing milk compositional quality through genetic selection based on individual performance is successful.

Published in	Animal and Veterinary Sciences (Volume 11, Issue 3)
DOI	10.11648/j.avs.20231103.12
Page(s)	64-70
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

Correlation, Genetic Parameter, Milk, Milk Composition, Phenotypic Correlation

References

[1]	Walstra, P., Wouters Jan, T. M. and Geurts, T. J. (2006). Dairy Science and Technology Second Edition. CRC Press Taylor and Francis Group. pp 763.
[2]	Bobe, G., D. C. Beitz, A. E. Freeman, G. L. Lindberg. (1999). Effect of milk protein genotypes on milk protein composition and its genetic parameter estimates. J. Dairy Sci., 82. pp. 2797-2804.
[3]	Prajapati, B K., K P Singh, Ajoy Mandal, P K Rout and R Roy. (2017). Genetic and phenotypic parameters of milk composition traits in Jamunapari goats. Indian J Dairy Sci. 70 (3).
[4]	Pandy, G. S. and Voskuil, G. C. J. (2011). Manual on milk safety, quality and hygiene. Golden Valley Agricultural Trust. pp 1-50.
[5]	Saba Haile. (2015). Quality assessment of cattle milk in adea berga and ejerie districts of west shoa zone, Ethiopia. M.Sc. Thesis. haramaya university, Haramaya.
[6]	O’Connor, C. B. (1994). Rural Dairy Technology. ILRI Training Manual no. 1. ILRI (International Livestock Research Institute), Addis Ababa, Ethiopia. Pp. 133.
[7]	Aynalem Haile. (2006). Genetic and Economic Analysis of Ethiopian Boran Cattle and Their Crosses with Holstein Friesian in Central Ethiopia. Thesis submitted to PhD. Dissertation, Deemed University, and Haryana, India. Pp. 197.
[8]	Rashida, K., Toqeer, A., and Bushra, M. (2004). Comparative analysis of quality of milk collected from buffalo, cow, goat and sheep of Rawalpindi/Islamabad region of Pakistan: Asian journal of plant science. 3 (3). pp. 300-305.
[9]	Rehrahie Mesfin and Andnet Getachew. (2007). Evaluation of grazing regimes on milk composition of Borana and Boran-Friesian crossbred dairy cattle at Holetta research center, Ethiopia. Livestock Research for Rural Development. 19 (12).
[10]	Charles, C. (1998). Nutrition changes milk composition. Virginia Polytechnic Institute and state University. Virginia co-operative extension Virginia.
[11]	Rege, J. E., O., Aboagye, G. S., Akah, S., Ahunu, B. K. (19940. Crossbreeding Jersey with Ghana Shorthorn and Sokoto Gudali cattle in a tropical environment: additive and heterotic effects for milk production, reproduction and calf growth traits. Anim. Prod. 59. Pp. 21–29.
[12]	Farrington, EH and FW Woll. (2010). Testing milk and its products. Published by Axis books (India). 10-Vyas Ji Ka Nohra Sardar para. India. Pp. 10-13.
[13]	Yadav, S. B. S., Yadav, A. S., Yadav, B. L. and Yadav, M. S. (1989). Factors affecting fat percentage in crossbred dairy cattle. Indian J. Dairy Sci., 42 (3). Pp. 475-481.
[14]	Myburgh, J., G Osthoff, A Hugo, M de Wit, K Nel, and D Fourie. (2012). Comparison of the milk composition of free-ranging indigenous African cattle breeds. South African Journal of Animal Science. 42. Pp. 1-14.
[15]	Cerbulis, J. and H. M. Farrell, JR. (1974). Composition of Milks of Dairy Cattle. I. Protein, Lactose, and Fat Contents and Distribution of Protein Fraction. Journal of Dairy Science. 58 (6).
[16]	ZelalemYilma, Yohannes Gojjam, Gizachew Bekele, AlemuGebre-Wold and Sendros Demeke. (2003). Major milk chemical composition and feed dry matter intake of multiparous Boran cows as affected by the level of milk production under bucket feeding and partial sucking calf rearing methods. Proceedings of the 11th Annual Conference of the Ethiopian Society of Animal Production (ESAP) held in Addis Ababa, Ethiopia, August 28-30, 2003. Pp. 397-411.
[17]	Alganesh Tola. (2006). Assessment of Safety and Quality of Raw Whole Cow Milk Produced and Marketed by Smallholders in Central Highlands of Ethiopia. Food Science and Quality Management. 49. Pp. 62-71.
[18]	ABdElrahman, SM., Ahmed Am., EL Owni Ao., Ahmed MK. (2009). Microbiological and physicochemical properties of raw milk used for processing pasteurized milk in Blue Nile Dairy Company (Sudan). Australian J. Basic Appl. Sci. 3 (4). Pp. 3433-3437.
[19]	Fikrineh Negash, Estefanos Tadesse, Esayas Aseffa, Chali Yimamu and Feyisa Hundessa. (2012). Production, handling, processing, utilization and marketing of milk in the Mid Rift Valley of Ethiopia. Livestock Research for Rural Development (LRRD). 24 (9).
[20]	Alganesh Tola, Ofodile, L. N. and Fekadu Beyene. (2007). Microbial Quality and chemical composition of raw whole milk from Horro cattle in East Wollega, Ethiopia. Ethiopian Journal of Education and Sciences. Jimma University, Ethiopia. 3 (1). Pp. 1-10.
[21]	Teklemichael, T. (2012). Quality and Safety of Raw and Pasteurized Cow Milk Produced and Marketed in Dire Dawa Town, M.Sc. Thesis. Haramaya University, Ethiopia.
[22]	Hirpha Ketema, Amanuel Bekuma, Mitiku Eshetu and Kefana Effa. (2018). Chemical Quality of Raw Cow’s Milk Detection and Marketing system in Walmera District of Oromia Regional State, Ethiopia. International Journal of Advanced Research in Biological Sciences. 5 (10). Pp. 38-4.
[23]	Debebe Worku. (2010). Physicochemical Properties and Safety of Streetvended Milk in and Around Addis Ababa City (Kotebe, Bishoftu and Chancho), M.Sc. Thesis. Haramaya University, Ethiopia.
[24]	Bekuma, A., Debela, D., and Mokenin, A. (2023). Milk Composition, Hygiene Practices and Marketing System in Wachale District, North Shewa, Ethiopia. Global Journal of Animal Scientific Research, 11 (1). Pp. 16-36.
[25]	Bille, P G., Haradoeb BR., Shigweda N. (2009). Evaluation of chemical and bacteriological quality of raw milk from Neudamn Dairy Farm in Namibia. African Journal of Agric. Nutrition. Dev. 9 (7). Pp. 1511-1523.
[26]	Janstova B, Necidova L, Navratilova L. (2010). Quality of raw milk from a farm with automatic milking system in the Czech Republic. Pp. 207-2014.
[27]	Sudhakar, Krovvidi, S. Panneerselvam, A. K. Thiruvenkadan, John Abraham and G. Vinodkumar. (2013). Factors effecting milk composition of crossbred dairy cattle in southern India. International Journal of Food, Agriculture and Veterinary Sciences. 3 (1). pp. 229-233.
[28]	Gurmessa Terfa Gurmessa, Mitiku Eshetu and Alemayehu Regassa. (2015). Physico-chemical qualities of raw cow milk in Ethiopia. The case of Borana zone, Yabello District Yabello Pastoral and Dry Land Agriculture Research Center, Yabello, Ethiopia. Global Journal of Dairy Farming and Milk Production. 3 (2). pp. 086-091.
[29]	Helen Nigussie and Eyassu Seifu. (2007). Effect of the lactoperoxidase system and container smoking on the microbial quality of cows’ milk produced in Kombolcha woreda, eastern Ethiopia. Livestock Research for Rural Development. 19. Pp. 157.
[30]	Alganesh Tola. (2002). Traditional milk and milk products handling practices and raw milk quality in Eastern Wollega. M.Sc. Thesis, Alemaya University. Dire Dawa, Ethiopia. Pp. 108.
[31]	Araújo, Thalita Polyana Monteiro, Adriano Henrique do Nascimento Range, Guilherme Ferreira da Costa Lima, Maria Gabriela Campolina Diniz Peixoto, Stela Antas Urbano and Joadilza da Silva Bezerra. (2018). Gir and Guzerat cow milk production and composition according to lactation stage, somatic cell count, physiological state and body condition. Acta Scientiarum. Animal Sciences. 40.
[32]	Derese T. (2008). Present situation of urban and peri urban milk production and quality of raw milk produced in west Shoa zone, Oromia region. Ethiopia. Haramaya University.
[33]	Tamime A. Y. (2009). Milk Processing and Quality Management. Society of Dairy Technology, United Kingdom.
[34]	Ewonetu Kebede. (2018). Effect of Cattle Breed on Milk Composition in the same Management Conditions. Ethiop. J. Agric. Sci. 28 (2). Pp. 53-63.
[35]	Alganesh Tola. (2016). Assessment of Safety and Quality of Raw Whole Cow Milk Produced and Marketed by Smallholders in Central Highlands of Ethiopia. Food Science and Quality. 49. Pp. 63-71.
[36]	Shibiru D, Tamir B, Kasa F, Goshu G. (2019). Effect of season, parity, exotic gene level and lactation stage on milk yield and composition of Holstein Friesian crosses in central highlands of Ethiopia. Eur exp bio. 9 (4). Pp. 15.
[37]	Hossain, M. E., T. Chanda, G. K. Debnath, M. M. Hassan and M. A. Haque. (2014). Influence of Dietary Energy and Protein Intake on Yield and Composition of Milk in Crossbred Dairy Cows. Iranian Journal of Applied Animal Science. 4 (4). Pp. 687-692.
[38]	Bindya Liz Abraham and S. L. Gayathri. (2015). Milk composition of crossbred and desi cattle maintained in the sub-tropical high ranges of kerala. Ind. J. Vet. & Anim. Sci. Res. 44 (1). Pp. 53-55.
[39]	Niero, Giovanni, Angela Costa, Marco Franzoi, Giulio Visentin, Martino Cassandro, Massimo De Marchi and Mauro Penasa. (2020). Genetic and Non-Genetic Variation of Milk Total Antioxidant Activity Predicted from Mid-Infrared Spectra in Holstein Cows. Animals. 10. Pp. 2372.
[40]	Talukder, M. A. I., J. M. Panandam, Y. Halimatun and I. Idris. (2013). Milk Composition and Quality of Sahiwal-Friesian Crossbred Cow Studied in Malaysia. The Agriculturists 11 (2). Pp. 58-65.
[41]	Sneddona, NW., N Lopez-Villalobosa, SR Davisb, RE Hicksona, L Shallooc and DJ Garricka. (2016). Estimates of genetic and crossbreeding parameters for milk components and potential yield of dairy products from New Zealand dairy cattle. New Zealand journal of agricultural research. 59 (1). Pp. 79–89.
[42]	Cyprian Alphonsus,, Akpa, Gerald Nwachi, Barje, Peter Pano, Ayigun, Elijah Ade, Zanna, Mustapha, Olaiya, Oluwakemi, Olayinka, Ifeolu Oluseyi, Anoh, Kevin Usman, Opoola, Emmanuel and Abdulahi, Idris. (2014). Effect of post-partum body condition score on milk yield and composition of Friesian x Bunaji dairy cows. Animal Research International. 11 (3). Pp. 2048-2056.
[43]	Bailey, K. E., C. M. Jones, and A. J. Heinrichs. (2005). Economic returns to Holstein and Jersey herds under multiple component pricing. J. Dairy Sci. 88. Pp. 2269-2280.
[44]	Islam, M. A., Alam, M. J., Kabir, M. E., Hossain, S. M. J., & Yasmin, F. (2021). Milk Yield and its Composition of Crossbred Dairy Cows Fed Different Types of Grasses. European Journal of Applied Sciences, 9 (3). Pp. 337-346.
[45]	Misra, S. S. and Joshi, B. K. (2004). Genetic and non-genetic factors affecting lactational milk constituents and yield traits in Karan fries cattle. Indian J. Dairy Sci. 57 (1). Pp. 69-72.
[46]	Jain, D. K., Sharma, K. N. S., Bhatnagar, D. S. and Sharma, R. C. (1987). Fat and SNF concentration in cow milk as affected by parity and stage of lactation. Indian J. Dairy Sci. 40 (1). Pp. 111-118.
[47]	Miglior, Filippo, Allison Fleming, Francesca Malchiodi, Luiz F. Brito, Pauline Martin, and Christine F. Baes. (2017). A 100-Year Review: Identification and genetic selection of economically important traits in dairy cattle. J. Dairy Sci. 100. Pp. 10251–10271.
[48]	Bourdon MR. (1999). Understanding animal breeding. 2nd/ED. Upper saddle River NJ07458, Colorado State University. Pp. 538.
[49]	Wasike, CB. (2006). Genetic evaluation of growth and reproductive performance of the Kenya Boran cattle. MSc Thesis. Egerton University, Kenya. Pp. 108.
[50]	Arendonk JV, Bijm P, Bovenhuis H, Crooijmans R and Tende TVD. (2010). Animal breeding and genetics lecture notes. Wagenningen University, Wageningen, Netherlands. Pp. 230.
[51]	Almaz. Bekele, Z. Wuletaw, A. Haile, S. Gizaw, G. Mekuriaw. (2016). Genetic Parameter Estimation of Pre Weaning Growth Traits of Fogera Cattle At Metekel Ranch, Northwest Ethiopia. IJSRST. 2 (5). Pp. 15-21.
[52]	Javed, K., Mohiuddin G and Akhtar P. (2001). Heritability estimates of some productive traits in Sahiwal cattle. Pakistan vet. J. 21 (3). Pp. 114-117.
[53]	Lobo, R. N. B., Madalena, F. E., Vieira, A. R. (2000). Average estimates of genetic parameters for beef and dairy cattle in tropical regions. Anim. Breed. Abst. 68. Pp. 433–462.
[54]	Missanjo, Edward, Venancio Imbayarwo-Chikosi, and Tinyiko Halimani. [2013]. Estimation of Genetic and Phenotypic Parameters for Production Traits and Somatic Cell Count for Jersey Dairy Cattle in Zimbabwe. ISRN Veterinary Science.
[55]	Sharma, A K., L A., Rodriguez, G. Mekonnen, C J. Wilcox, K C, Bachman and R J. Collier. (1983). Climatological and Genetic Effects on Milk Composition and Yield. Journal of Dairy Science. 66 (1). Pp. 119-126.
[56]	Maiwashe A., K. A. Nephawe and H. E. Theron. (2008). Estimates of genetic parameters and effect of inbreeding on milk yield and composition in South African Jersey cows. South African Journal of Animal Science. 38 (2).
[57]	Moya, J. (1977). Maximum Likelihood estimation of genetic trends in milk yield and composition in the Florida experiment station dairy herd. Master’s Thesis, University of Florida, Gainesville, FL, USA.

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Fikadu Wodajo Tirfie. (2023). A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle. Animal and Veterinary Sciences, 11(3), 64-70. https://doi.org/10.11648/j.avs.20231103.12

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Fikadu Wodajo Tirfie. A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle. Anim. Vet. Sci. 2023, 11(3), 64-70. doi: 10.11648/j.avs.20231103.12

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Fikadu Wodajo Tirfie. A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle. Anim Vet Sci. 2023;11(3):64-70. doi: 10.11648/j.avs.20231103.12

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@article{10.11648/j.avs.20231103.12,
  author = {Fikadu Wodajo Tirfie},
  title = {A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle},
  journal = {Animal and Veterinary Sciences},
  volume = {11},
  number = {3},
  pages = {64-70},
  doi = {10.11648/j.avs.20231103.12},
  url = {https://doi.org/10.11648/j.avs.20231103.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.avs.20231103.12},
  abstract = {This review focuses on the genetic and non-genetic parameter estimation for dairy cattle milk composition. Milk is the most widely consumed food in the world, containing proteins, fats, lactose, and various vitamins and minerals. Milk's solids content has a direct impact on both its nutritional and economic value. The milk composition trait performances had obtained in the range from 3.5±0.0038 to 6.1±0.05 for fat percentage, 3.07±0.03 to 4.7±0.09 for protein percentage, 3.3 to 5.52±1.71 for lactose content, 12.16±0.14 to 16.02±0.05 for total solid content and 8.47±0.1 to 9.37±0.24 for the solid not fat content of cow milk, respectively. The composition of cow milk is influenced by breed, animal age and health, lactation phase, nutrition, season, milking method, number of lactations, and individual cows. The heritability of milk composition trait ranged from 0.24 to 0.49±0.03 for fat percentage, 0.28 to 0.53±0.009 for protein percentage, 0.41±0.04 to 0.59 for total solid content and 0.17 to 0.68 for the solid not fat content of cow milk, respectively. The repeatability of fat, protein, total solid and solid not fat percentage of bovine milk ranged between 3.9 to 0.98, 0.4 to 0.99, 0.49 to 0.99 and 0.23 to 0.78, respectively. The genetic and phenotypic correlation between fat and solid not fat of cow milk were weakly positive (0.16±0.15, 0.06 ±0.04), whereas a strong positive relationship was found between protein content and solid not fat of cow milk (0.99±0.05, 0.67±0.03), respectively. Enhancing milk compositional quality through genetic selection based on individual performance is successful.},
 year = {2023}
}

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TY  - JOUR
T1  - A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle
AU  - Fikadu Wodajo Tirfie
Y1  - 2023/05/29
PY  - 2023
N1  - https://doi.org/10.11648/j.avs.20231103.12
DO  - 10.11648/j.avs.20231103.12
T2  - Animal and Veterinary Sciences
JF  - Animal and Veterinary Sciences
JO  - Animal and Veterinary Sciences
SP  - 64
EP  - 70
PB  - Science Publishing Group
SN  - 2328-5850
UR  - https://doi.org/10.11648/j.avs.20231103.12
AB  - This review focuses on the genetic and non-genetic parameter estimation for dairy cattle milk composition. Milk is the most widely consumed food in the world, containing proteins, fats, lactose, and various vitamins and minerals. Milk's solids content has a direct impact on both its nutritional and economic value. The milk composition trait performances had obtained in the range from 3.5±0.0038 to 6.1±0.05 for fat percentage, 3.07±0.03 to 4.7±0.09 for protein percentage, 3.3 to 5.52±1.71 for lactose content, 12.16±0.14 to 16.02±0.05 for total solid content and 8.47±0.1 to 9.37±0.24 for the solid not fat content of cow milk, respectively. The composition of cow milk is influenced by breed, animal age and health, lactation phase, nutrition, season, milking method, number of lactations, and individual cows. The heritability of milk composition trait ranged from 0.24 to 0.49±0.03 for fat percentage, 0.28 to 0.53±0.009 for protein percentage, 0.41±0.04 to 0.59 for total solid content and 0.17 to 0.68 for the solid not fat content of cow milk, respectively. The repeatability of fat, protein, total solid and solid not fat percentage of bovine milk ranged between 3.9 to 0.98, 0.4 to 0.99, 0.49 to 0.99 and 0.23 to 0.78, respectively. The genetic and phenotypic correlation between fat and solid not fat of cow milk were weakly positive (0.16±0.15, 0.06 ±0.04), whereas a strong positive relationship was found between protein content and solid not fat of cow milk (0.99±0.05, 0.67±0.03), respectively. Enhancing milk compositional quality through genetic selection based on individual performance is successful.
VL  - 11
IS  - 3
ER  -

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Fikadu Wodajo Tirfie

Ethiopian Institute of Agricultural Research, Holetta Agricultural Research Center, Addis Ababa, Ethiopia

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Fikadu Wodajo Tirfie. (2023). A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle. Animal and Veterinary Sciences, 11(3), 64-70. https://doi.org/10.11648/j.avs.20231103.12

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Fikadu Wodajo Tirfie. A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle. Anim. Vet. Sci. 2023, 11(3), 64-70. doi: 10.11648/j.avs.20231103.12

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AMA Style

Fikadu Wodajo Tirfie. A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle. Anim Vet Sci. 2023;11(3):64-70. doi: 10.11648/j.avs.20231103.12

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@article{10.11648/j.avs.20231103.12,
  author = {Fikadu Wodajo Tirfie},
  title = {A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle},
  journal = {Animal and Veterinary Sciences},
  volume = {11},
  number = {3},
  pages = {64-70},
  doi = {10.11648/j.avs.20231103.12},
  url = {https://doi.org/10.11648/j.avs.20231103.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.avs.20231103.12},
  abstract = {This review focuses on the genetic and non-genetic parameter estimation for dairy cattle milk composition. Milk is the most widely consumed food in the world, containing proteins, fats, lactose, and various vitamins and minerals. Milk's solids content has a direct impact on both its nutritional and economic value. The milk composition trait performances had obtained in the range from 3.5±0.0038 to 6.1±0.05 for fat percentage, 3.07±0.03 to 4.7±0.09 for protein percentage, 3.3 to 5.52±1.71 for lactose content, 12.16±0.14 to 16.02±0.05 for total solid content and 8.47±0.1 to 9.37±0.24 for the solid not fat content of cow milk, respectively. The composition of cow milk is influenced by breed, animal age and health, lactation phase, nutrition, season, milking method, number of lactations, and individual cows. The heritability of milk composition trait ranged from 0.24 to 0.49±0.03 for fat percentage, 0.28 to 0.53±0.009 for protein percentage, 0.41±0.04 to 0.59 for total solid content and 0.17 to 0.68 for the solid not fat content of cow milk, respectively. The repeatability of fat, protein, total solid and solid not fat percentage of bovine milk ranged between 3.9 to 0.98, 0.4 to 0.99, 0.49 to 0.99 and 0.23 to 0.78, respectively. The genetic and phenotypic correlation between fat and solid not fat of cow milk were weakly positive (0.16±0.15, 0.06 ±0.04), whereas a strong positive relationship was found between protein content and solid not fat of cow milk (0.99±0.05, 0.67±0.03), respectively. Enhancing milk compositional quality through genetic selection based on individual performance is successful.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - A Review of Genetic and Non-Genetic Parameter Estimates for Milk Composition of Cattle
AU  - Fikadu Wodajo Tirfie
Y1  - 2023/05/29
PY  - 2023
N1  - https://doi.org/10.11648/j.avs.20231103.12
DO  - 10.11648/j.avs.20231103.12
T2  - Animal and Veterinary Sciences
JF  - Animal and Veterinary Sciences
JO  - Animal and Veterinary Sciences
SP  - 64
EP  - 70
PB  - Science Publishing Group
SN  - 2328-5850
UR  - https://doi.org/10.11648/j.avs.20231103.12
AB  - This review focuses on the genetic and non-genetic parameter estimation for dairy cattle milk composition. Milk is the most widely consumed food in the world, containing proteins, fats, lactose, and various vitamins and minerals. Milk's solids content has a direct impact on both its nutritional and economic value. The milk composition trait performances had obtained in the range from 3.5±0.0038 to 6.1±0.05 for fat percentage, 3.07±0.03 to 4.7±0.09 for protein percentage, 3.3 to 5.52±1.71 for lactose content, 12.16±0.14 to 16.02±0.05 for total solid content and 8.47±0.1 to 9.37±0.24 for the solid not fat content of cow milk, respectively. The composition of cow milk is influenced by breed, animal age and health, lactation phase, nutrition, season, milking method, number of lactations, and individual cows. The heritability of milk composition trait ranged from 0.24 to 0.49±0.03 for fat percentage, 0.28 to 0.53±0.009 for protein percentage, 0.41±0.04 to 0.59 for total solid content and 0.17 to 0.68 for the solid not fat content of cow milk, respectively. The repeatability of fat, protein, total solid and solid not fat percentage of bovine milk ranged between 3.9 to 0.98, 0.4 to 0.99, 0.49 to 0.99 and 0.23 to 0.78, respectively. The genetic and phenotypic correlation between fat and solid not fat of cow milk were weakly positive (0.16±0.15, 0.06 ±0.04), whereas a strong positive relationship was found between protein content and solid not fat of cow milk (0.99±0.05, 0.67±0.03), respectively. Enhancing milk compositional quality through genetic selection based on individual performance is successful.
VL  - 11
IS  - 3
ER  -

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