Way forward in Breeding for Increasing Productivity in Dairy Animals
P P Dubey*, S K Sahoo, Rebeka Sinha and Ramandeep Kaur Department of Animal Genetics and Breeding College of Veterinary Science Guru Angad Dev Veterinary and Animal Sciences, Ludhiana, Punjab
Livestock sector in India is considered as an integral part of rural population as it provides financial security and gainful employment to them. In addition to this, the livestock sector also plays an important role of growth leverage to the national economy. The livestock sector contributed nearly 5.21% of total gross value added (GVA) and 28.36% of the Agriculture and Allied sector GVA (BAHS, 2019). In the recent past, the livestock sector registered an excellent growth rate of 9% and is certainly expected to emerge as an engine of growth in the animal husbandry sector in near future. Cattle and buffaloes are important bovine species of India which contributes significantly to the national livestock wealth. According to 20th Livestock Census, the total bovine population was 303.76 million of which the cattle and buffalo populations were 193.47 and 109.85 million respectively which constitutes, 36.04% and 20.47% of the total livestock population of the country. In Punjab state, it contributes to 1.3% of the total cattle, 3.6% of the total buffalo and 0.23% of the total goat population in India. India is a global leader in buffalo population and ranks second in cattle population status all over the world. These species form the backbone of the Indian dairy industry helping in maintaining the topmost rank among various milk-producing nations of the globe. India is home to a diverse indigenous bovine genetic resource base with 50 cattle and 17 buffalo breeds registered with the National Bureau of Animal Genetic Resources (www.nbagr.res.in). India harbours the second largest cattle population among the world countries with vast genetic diversity. According to 20 th Livestock census (2019), India possess 193.47 million cattle of which 26.55% (51.36 million) are crossbred while the rest 73.45% (142.11 million) are Indigenous/ non- descript cattle. Perusal of 19th and 20th Census data revealed that the cattle population has increased by 1.3% over the previous census. The census also showed that the female cattle population of crossbred and indigenous / non-descript cattle has increased over the previous census by 41.4 and 10.0 per cent, respectively. The crossbred and indigenous / non-descript cattle male populations of cattle have showed a decrease of 39.5 and 29.1 per cent, respectively over the two census periods. The decrease in male population may be attributed to the modernization and mechanization of agriculture operations and the extensive use of frozen semen for artificial insemination by covering larger area resulting in the loss of importance for the locally available breeding bulls (Mitra and Raja 2021). The total buffalo population was 109.85 million showing an increase of about 1.1% over the previous census. The female buffalo population has increased by 8.61% while the male population has declined by 42.3% over the previous census.
Milk productivity of bovines: The average milk productivity of cattle and buffaloes in the country is lower than the world average. As per the BAHS (2020), the average productivity of exotic/crossbred was 8.20 Kg while the estimate for indigenous cattle was 3.08 Kg. The buffaloes also had the average milk productivity lower than the exotic / crossbred cows. Considering the consistent increase in demand for milk production, the milk productivity of the indigenous cattle and buffalo breeds needs to be improved to meet the unnerving task of fulfilling the milk requirement of the huge population in the country. Strategies for increasing the productivity of dairy animals: In order to enhance the milk productivity of the bovines and to develop the rural livestock farming sustainable, it is necessary to follow a multi-dimensional approach through formulating and implementing an area specific genetic improvement programme (Mitra and Raja, 2021). According to the Indian Constitution, the States are empowered to indorse and implement the livestock development programmes and the central government can complement and supplement the efforts of state government by financing various schemes and programmes. Thus, each state of the country formulates and implements its own bovine breeding policy according to the cattle genetic resource, infrastructure facility, financial availability and economic viability.
Breeding strategies:
Animal registration, data recording and management: Animal identification, pedigree and performance recording need to be expanded at the grass root level. In India majority of farmers are smallholding with only a few animals maintained. Monthly recording with foolproof system as done by NDDB should be expanded for all dairy breeds. The low coverage of National Animal Identification System (NAIS) severely hampers the data recording in field, resulting in failure to execute the selection schemes and also to quantify the impact of improvement programmes. There are scattered efforts for animal identification in field by small groups; however, these efforts have limitations of project funding and duration. Establishment of a NAIS will open opportunities for actual recording of the data, monitoring the progress of the breeding schemes and evaluating the realistic gains of breeding programmes. This will also help for expansion of the area to be covered in the breeding programme for each breed. A complete infrastructure with a dedicated team exclusively for NAIS is necessary and this would necessitate substantial investment. The huge task of NAIS can also be linked with Panchayati Raj system, with empowerment of local people for animal identification tools. (Gowane et al. 2019). In the Indian conditions, elite germplasm, once identified through selection programmes, can be disseminated effectively by incorporating them in nucleus breeding schemes (Sreenivas, 2013). Another issue with Indian dairy industry is improper phenome data recording which leads to faulty parameter estimation and ultimately no gains from breeding programmes. Strengthening and coordinating the data collection, record keeping and database maintenance shall help in the long run. An integrated database system wherein the data is exchanged among various stakeholders can be helpful to make informed breeding policy decisions. Participatory breeding can be a good approach to ensure proper phenome data recording in Indian conditions.
Improving the Artificial insemination and veterinary facility: The lack of artificial insemination (AI) and veterinary facilities to the bovines maintained under small holdings is one of the major limiting factor. Strengthening the AI facility at the doorsteps of the farmers along with prompt veterinary facilities for prevention and treatment of various diseases will help to improve the production performance of the animals. At present, country faces shortage in the availability of genetically proven breeding bulls of different breeds as only around 30% of the animals are covered under artificial insemination (AI) and the rest 70% are bred by the natural service using locally available bulls. Indiscriminate breeding using bulls with unknown pedigree and genetic worth will surely hamper the prime objective of genetic improvement in dairy animals.
Establishment of National Genetic Evaluation System (NGES): The NGES will help in selection of the best bulls of each breed which may be used for the breeding of cattle and buffalo in the region. The uniform criteria of evaluation will also favour the use of breeding bulls across the states for upgrading the non-descript animals. For efficient bovine productivity, the large number of low producing non-descript bovines need to be replaced with high producing graded animals. The implementation of NGES will also help in changing the genetic constitution of the Indigenous non-descript population by increasing the number of upgraded high yielders at the expense of the low producing non-descript cattle.
Pedigree selection and Progeny testing: The capacity to store performance and pedigree data for use in genetic evaluations is continuously increasing and requires trained personnel in the field of animal breeding and genetics. Computer programmes have been developed to optimize selection decisions for a given list of candidates for which pedigree information and EBVs are available (Weigel and Lin, 2000). In turn, the impact of a breeding programme depends on the dissemination of genetic progress to customers or into the wider livestock population. Reproductive technologies, particularly artificial insemination play an important role in dairy animals as they allow genetic material to be transported around the world and greatly increase the number of offspring that can be obtained from a superior breeding animal.
Selection Indexes: The selection index is a method for estimating the breeding value of an animal by combining all information available on the animal and its relatives. It is the best linear prediction of an individual breeding value. When records are available from multiple sources, e.g. records on the animal itself, its dam, half sibs, progeny, etc., it will obviously be most beneficial to use all records to estimate the breeding value. Selection indexes, constructed with attention to the genetic and economic bases for the various traits, should be valuable in livestock breeding programs. The sire index, widely used in selecting sires for butterfat and milk production, is a practical example of an index based on one trait but using information about several relatives. Breed specific breeding index should be developed. Along with production traits, reproduction traits, type traits and functional traits should be included (RFI, thermo tolerance traits and udder conformation traits) in selection criteria. It stands true especially for dairy animals, wherein there is an urgent need to formulate selection indices involving traits other than production and reproduction. In milch breeds, there is an utmost need to include functional traits in the selection programmes. Traits such as behaviour/ temperament, milk letdown, longevity, disease tolerance, udder characteristics, reproductive indices, fertility, lameness incidence and residual feed efficiency etc. need to be given proper weightage in breeding programmes (König & May, 2019). Many countries like Netherlands, USA, Germany, Israel France etc. based on geographical representation, Interbull membership, and size of progeny testing programs, developed the selection indexes based on several traits as per their requirements. The Israeli breeding program is monitored by the Israeli Breeding and Herdbook Committee, which includes representatives of the farmers, the Israel Cattle Breeders Association, the Institute of Animal Sciences of the Agricultural Research Organization, the SION AI Institute and the Hachaklait Veterinary Services. Index coefficients for milk, fat, and protein were computed to maximize expected farmer profit. The index coefficients were computed by differentiating the profit equation with respect to each component. The index coefficients were normalized so that one standard kg of milk with 3.574% fat and 3.186% protein would have a unit value. The index coefficient for somatic cell score (SCS) was computed so that expected changes for SCS would be close to zero. The index coefficients for daughters’ fertility, herd life, persistency, and calf mortality were computed to account for the economic value of those traits relative to milk production.
Genomic selection: With the advent of genomic selection (GS), a large number of animals without pedigree can be included in the selection programme for more intense selection, increasing accuracy and reducing generation interval (Gowane et al. 2019). Accurate genomic selection depends on the availability of phenotypic data, which are usually lacking in the low-input production systems typically found in developing countries. However, the situation in these countries has not remained static. Formal breeding programmes, usually community-based, have become more common and are improving the productivity of animals and livelihoods of their keepers. Customized chips have recently been developed for both Indian cattle and buffaloes. These mainly include INDUSCHIP and BUFFCHIP developed by National Dairy Development Board (NDDB), Gujarat. Genomic selection aims at higher accuracy and improved gains within shorter time spans. However, genomic selection needs to be employed with caution after taking unique genetic makeup of dairy animal breeds into consideration. National Bovine Genomic Centre has been recently launched in the country for executing genomic selection in dairy cattle. It needs to be strengthened further to achieve rapid rates of genetic gains in dairy breeds resulting in a higher proportion of genomically proven young bulls for future breeding.
Genetic improvement of small herd size: In India, most of livestock are reared under small holder production systems and are always limited by small herd, challenging environment, low input and poor management and uncontrolled mating. The systematic data recording for Livestock in India exists only in Institutional, Government, Dairy Co-Operatives and few Farms owned by govt. institutions and elite group of farmers. The fact remains that our country has one of the highest populations of bovine and breeds available within thespecies are also very large when compared to European and American continents. Under such conditions, the genomic selection programme based on the genomic information of animals would be useful for early selection of animals with increased accuracy. The equation for GEBV prediction already been developed in the reference population can be very well used under field conditions for selection of animals without any phenomic data. It will also help to increase the accuracy of selection with high genetic gain.
Application of Assisted reproductive technologies:The assisted reproductive technologies like embryo transfer, in vitro fertilization, in-vitro maturation, ovum pickup etc., may be utilized for conservation and multiplication of elite germplasm. ETT can potentially help in increasing the bovine population inheriting elite germplasm with an increase in intensity and accuracy of existing selection programmes leading to high genetic gain with lowering the generation interval. Sexed semen can also be used to produce more of particular sex of animals helping in a significant increase in milk production.
Culling policy: A successful breeding programme needs culling of low producing animals to restrict their gene flow to the next generation. A large cattle population with low productivity have become a great liability as they compete for nutritional resources with higher yielding animals. Disposal of males is another problem that has arisen with the slaughter ban. There is no systematic planning to address this problem. Castration of stray male cattle is an absolute priority. Rehabilitation of stray animals through a network of Goshalas is required to be set up with sufficient funding support. The stray animal dung can be a vital source for biogas plants and a source of revenue generation apart from milk for sustenance of these units.
References:
BAHS (2019). Department of Animal Husbandry and Dairying, Ministry of Fisheries, Animal Husbandry and Dairying, Government of India, Krishi Bhawan, New Delhi. Gowane, G. R., Arun Kumar and Chanda Nimbkar. (2019). Challenges and opportunities to livestock breeding programmes in India. Journal of Animal Breeding and Genetics, 136:329–338. DOI: 10.1111/jbg.12391 König, S. and May, K. (2019). Invited review: Phenotyping strategies and quantitativegenetic background of resistance, tolerance and resilience associated traits in dairy cattle. In Animal. https://doi.org/10.1017/S1751731118003208 Mitra A. and Raja, T. V.(2021). Breeding for improving productivity of Indigenous bovines, In: National Conference on Animal Breeding Strategies in the Era of Genomics & Phenomics XV Annual Convention of Indian Society of Animal Genetics & Breeding at ICAR-NBAGR, Karnal, 2021,3-9pp. Sreenivas, D. (2013). Breeding policy strategies for genetic improvement of cattle and buffaloes in India, Veterinary World, 6(7): 455- 460, doi:10.5455/vetworld.2013.455-460 Weigel, K. A. and Lin, S. W. (2000). Use of Computerized Mate Selection Programs to Control Inbreeding of Holstein and Jersey Cattle in the Next Generation. Journal of Dairy Science, 83:822–828
