Genetic Selection Of Dairy Cattle
Towards Sustainable Farming System In The Developing World
Introduction
The production of dairy cattle has increased significantly during the past 100 years as a result of numerous scientific breakthroughs. There are currently more than 270 million dairy (or dual-purpose) cows in existence, and each of them produces an average of 2600 kilogrammes of milk every year. However, just 33 nations (FAOSTAT, 2018) have national average milk yields greater than 6000 kg/cow/year, which accounts for about 13% of the world's dairy cattle population but more than 40% of all milk produced. However, the dairy industry's strong emphasis on guaranteeing food security through increased production raises questions about other sustainability characteristics (Clay et al., 2020).
An alarming loss of genetic diversity, unfavourable genetic responses in a number of correlated traits, and decreased selection pressure in traits related to environmental efficiency, animal health and welfare, and general resilience in comparison to performance traits have all been observed along with the increase in productivity. This forces us to re-evaluate continued strategies for milk yield selection in populations (or nations) that have attained very high production levels, but concurrent selection for productivity and functional traits (such as adaptation, welfare, and resilience) should be used in low-producing populations, especially in local breeds.Sustainable intensification involves raising output while reducing the harmful environmental effects of traditional farming methods and enhancing animal welfare. This article discusses the role of genetic selection as an alternative to intensive dairy production systems.
Role of genetic selection as an alternative to intensive dairy production systems
Given that acts on one dimension may have a negative impact on another, achieving sustainability in all of its various dimensions is exceedingly ambitious and hard. In scenarios highlighting significant shifts toward agroecological systems, farm inputs are drastically reduced, which is accompanied by a decline in production. For example, the TYFA model created at a European scale (Poux and Aubert, 2018) comprises two typical dairy production systems in 2050:
(i) a grass-fed system with an average level of output per cow of 5,000 kg of milk per year, in which the majority of the fodder resources come from permanent grasslands and,
(ii) a mixed system where transitory grasses, cereals, and legumes are blended with permanent grasslands as sources of fodder (alfalfa, clover) with average annual milk production is 7000 kg.
Similar to this, the French-scale Afterres 2050 scenario (Couturier et al., 2017) calls for the gradual replacement of high-input dairy systems with low-input systems that have more moderate output levels. Both times, the beef herd was replaced by the dairy herd, and the less-skilled dairy cows were also dual-purpose cows (milk and meat). Meat from culled cows and calves was thought to be less polluting than meat from a herd of nursing calves (Puilletet al., 2012). This pattern can be enhanced by using male sexed semen to generate well-conformed animals for meat production and female sexed semen to renew the dairy herd.
Due to their breeding in pasture-based systems, native cattle can be converted for organic dairy herds (Rodrguez-Bermdezet al., 2019). According to Rodriguez-Bermudez et al. (2019), no approach appears to have been widely embraced in the contemporary organic dairy herds. Instead, farmers continue to experiment with any crossbreeds that are accessible. In specialized organic dairy herds, crossbreeding could be increased. Jersey crossbreds could be suitable for farms that permit year-round grazing. Rotational crossbreeding has the advantage of sustaining the heterosis effect and decreasing inbreeding, which makes it appear to occur more quickly than selection in pure breeds. As in other plants and non-ruminant breeding programmes, evaluations that maximise the heterosis impact could be established from a genetic evaluation point of view (González-Diéguezet al., 2020).In contrast to specialist organic dairy farming, multifunctional organic farming, as demonstrated by Nautaet al. (2009), can use local dairy breed as a business strategy for agritourism and participate in a living gene-bank supported by government subsidies.
Novel breeding goals for long-term sustainability
The breeding programmes have to berefined to incorporate novel breeding objectives which requires the development of high-throughput phenotyping technologies (and structured and continuous data recording streams), investigation of the genetic relationship between novel traits and those typically recorded (and the potential effects of selection for every single trait), performance of large-scale genomic studies, especially genomic predictions and genome-wide association stud.(Cole and VanRaden, 2018).The cost and complexity of measuring a large number of animals for close-to-biology variables, which typically lack well-defined phenotypes, has been the biggest barrier to the inclusion of numerous traits in dairy cattle breeding programmes. Precision technologies, which can be used to various industrial systems, present a chance to assess novel features, particularly resilience, welfare, and environmental efficiency (Britoet al., 2020b). Dairy cattle production systems have been intensified and intensive selection for production qualities has produced animals that are more susceptible to behavioural, physiological, and immunological diseases (Barbatet al., 2010; Colditz and Hine, 2016; Friggenset al., 2017; Lawrence and Wall, 2014; Rauwet al., 1998, 2012; Star et al., 2008).Therefore, the following are important categories of novel traits: health (such as metabolic diseasesandudderand hoof health), methane emissions, feed efficiency, fertility, lifespan, and general resilience.
Conclusions
Genetic variety has been lost and critical biological systems (such as health, resilience, robustness, welfare, and lifespan) have gotten poorer in the most widely used dairy cattle breeds as a result of increased output. Continued progress in a number of areas, particularly genetics, the active involvement of all stakeholders (such as farmers, technical and scientific sectors, consumers, and policymakers), diversification of production systems, and strong support from public and private institutions for the investigation and development of alternative production systems are all necessary for the future success of the dairy cattle industry.
There appears to be agreement that the current selection indices and breeding objectives need to be improved further in order to include or place more focus on qualities relating to animal welfare, health, resilience, longevity, and environmental efficiency. Finally, to support significant changes toward sustainable farming systems, genetic selection of high-yielding dairy cattle will need to be a component of more systemic initiatives at the farm scale.
References
Food and Agriculture Organization, 2018. World livestock: transforming the livestock sector through the sustainable development goals. FAO, Rome, Italy
Clay, N., Garnett, T., Lorimer, J., 2020. Dairy intensification: drivers, impacts andalternatives. Ambio 49, 35–48.
Poux, X., Aubert, P-M., 2018. An agroecological Europe in 2050: multifunctionalagriculture for healthy eating. Findings from the Ten Years ForAgroecology(TYFA) modelling exercise. Iddri-AScA, Paris, France.
Couturier, C., Charru, M., Doublet, S., Pointereau, P., 2017.Le scénarioAfterres 2050.Retrieved on 16 September 2020 from www.afterres2050.solagro.org.
Puillet, L., Agabriel, J., Peyraud, J-L., Faverdin, P., 2012.Modelling the national cattleherd to simulate meat and milk production and the greenhouse gas emissionsinventory. Proceedings of Emili2012: International symposium on Emission ofGas and Dust from Livestock, 11-13 June 2012, Saint Malo, France, pp. 423–426.
Rodríguez-Bermúdez, R., Miranda, M., Baudracco, J., Fouz, R., Pereira, V., López-Alonso, M., 2019. Breeding for organic dairy farming: what types of cowsareneeded? Journal of Dairy Research 86, 3–12.
González-Diéguez, D., Tusell, L., Bouquet, A., Legarra, A., Vitezica, Z.G., 2020.Purebred and crossbred genomic evaluation and mate allocation strategies toexploit dominance in pig crossbreeding schemes. G3: Genes Genomes, Genetics10, 2829–2841.
Nauta, W.J., Baars, T., Saatkamp, H., Weenink, D., Roep, D., 2009.Farming strategiesin organic dairy farming: Effects on breeding goal and choice of breed.Anexplorative study. Livestock Science 121, 187–199.
Cole, J.B., VanRaden, P.M., 2018. Symposium review: Possibilities in an age ofgenomics: The future of selection indices. Journal of Dairy Science 101, 3686–3701.
Brito, L.F., Oliveira, H.R., Houlahan, K., Fonseca, P.A.S., Lam, S., Butty, A.M., Seymour,D.J., Vargas, G., Chud, T.C.S., Silva, F.F., Baes, C.F., Canovas, A., Miglior, F.,Schenkel, F.S., 2020a. Invited Review: Genetic mechanisms underlyingfeed utilization and implementation of genomic selection for improved feedefficiency in dairy cattle.Canadian Journal of Animal Science 100,587–604.
Brito, L.F., Oliveira, H.R., McConn, B.R., Schinckel, A.P., Arrazola, A., Marchant-Forde,J.N., Johnson, J.S., 2020b. Large-scale phenotyping of livestock welfare incommercial production systems: a new frontier in animal breeding. Frontiers inGenetics 11, 793.
Barbat, A., Le Mezec, P., Ducrocq, V., Mattalia, S., Fritz, S., Boichard, D., Ponsart, C.,Humblot, P., 2010. Female fertility in French dairy breeds: current situation andstrategies for improvement. The Journal of Reproduction and Development 56, S15–S21.
Colditz, I.G., Hine, B.C., 2016. Resilience in farm animals: biology, management,breeding and implications for animal welfare. Animal Production Science 56,1961.
Friggens, N.C., Blanc, F., Berry, D.P., Puillet, L., 2017. Review: Deciphering animalrobustness. A synthesis to facilitate its use in livestock breeding andmanagement. Animal 11, 2237–2251.
Lawrence, A.B., Wall, E., 2014. Selection for environmental fit from existingdomesticated species. Revue Scientifiqueet Technique-Office Internationaldes Epizooties 33, 171–179.
Rauw, W.M., 2012. Immune response from a resource allocation perspective.Frontiers in Genetics 3, 267.
Star, L., Ellen, E.D., Uitdehaag, K., Brom, F.W.A., 2008. A plea to implementrobustness into a breeding goal: Poultry as an example. Journal of Agriculturaland Environmental Ethics 21, 109–125.
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Dr. Sreyass K S
Assistant Professor (Animal Husbandry)
Dept. of Crop Management
Vanavarayar Institute of Agriculture
Manakkadavu, Pollachi