Using genomic information, local ruminant populations can be better characterized and compared to selected ones. Genetic relationships between animals can be established even without systematic pedigree recording, provided a budget is available for genotyping. Genomic selection (GS) can rely on a subset of the total population and does not require a costly national infrastructure, e.g., based on progeny testing. Yet, the use of genomic tools for animal breeding in developing countries is still limited. We identify three main reasons for this: (i) the instruments for cheap recording of phenotypes and data management are still limiting. (ii) many developing countries are recurrently exposed to unfavorable conditions (heat, diseases, poor nutrition) requiring special attention to fitness traits, (iii) a high level of expertise in quantitative genetics, modeling, and data manipulation is needed to perform genomic analyses. Yet, the potential outcomes go much beyond genetic improvements and can improve the resilience of the whole farming system. They include a better management of genetic diversity of local populations, a more balanced genetic progress and the possibility to unravel the genetic basis of adaptation of local breeds through whole genome approaches. A GS program being developed by BAIF, a large Indian NGO, is analyzed as a pilot case. It relies on the creation of a female reference population of Bos indicus and crossbreds, recorded with modern technology (e.g., smartphones) to collect performances at low cost in tiny herds on production and fertility. Finally, recommendations for the implementation of GS in developing countries are proposed.

Background The genetic structure of a diverse set of 15 Indian indigenous breeds and non-descript indigenous cattle sampled from eight states was examined, based on 777 k single nucleotide polymorphism (SNP) genotypes obtained on 699 animals, with sample sizes ranging from 17 to 140 animals per breed. To date, this is the largest and most detailed assessment of the genetic diversity of Indian cattle breeds. Results Admixture analyses revealed that 109 of the indigenous animals analyzed had more than 1% Bos taurus admixture of relatively recent origin. Pure indigenous animals were defined as having more than 99% Bos indicus ancestry. Assessment of the genetic diversity within and between breeds using principal component analyses, F statistics, runs of homozygosity, the genomic relationship matrix, and maximum likelihood clustering based on allele frequencies revealed a low level of genetic diversity among the indigenous breeds compared to that of Bos taurus breeds. Correlations of SNP allele frequencies between breeds indicated that the genetic variation among the Bos indicus breeds was remarkably low. In addition, the variance in allele frequencies represented less than 1.5% between the Indian indigenous breeds compared to about 40% between Bos taurus dairy breeds. Effective population sizes (Ne) increased during a period post-domestication, notably for Ongole cattle, and then declined during the last 100 generations. Although we found that most of the identified runs of homozygosity are short in the Indian indigenous breeds, indicating no recent inbreeding, the high FROH coefficients and low FIS values point towards small population sizes. Nonetheless, the Ne of the Indian indigenous breeds is currently still larger than that of Bos taurus dairy breeds. Conclusions The changes in the estimates of effective population size are consistent with domestication from a large native population followed by consolidation into breeds with a more limited population size. The surprisingly low genetic diversity among Indian indigenous cattle breeds might be due to their large Ne since their domestication, which started to decline only 100 generations ago, compared to approximately 250 to 500 generations for Bos taurus dairy cattle.

Background India is the largest milk producer globally, with the largest proportion of cattle milk production coming from smallholder farms with an average herd size of less than two milking cows. These cows are mainly undefined multi-generation crosses between exotic dairy breeds and indigenous Indian cattle, with no performance or pedigree recording. Therefore, implementing genetic improvement based on genetic evaluation has not yet been possible. We present the first results from a large smallholder performance recording program in India, using single nucleotide polymorphism (SNP) genotypes to estimate genetic parameters for monthly test-day (TD) milk records and to obtain and validate genomic estimated breeding values (GEBV). Results The average TD milk yield under the high, medium, and low production environments were 9.64, 6.88, and 4.61 kg, respectively. In the high production environment, the usual profile of a lactation curve was evident, whereas it was less evident in low and medium production environments. There was a clear trend of an increasing milk yield with an increasing Holstein Friesian (HF) proportion in the high production environment, but no increase above intermediate grades in the medium and low production environments. Trends for Jersey were small but yield estimates had a higher standard error than HF. Heritability estimates for TD yield across the lactation ranged from 0.193 to 0.250, with an average of 0.230. The additive genetic correlations between TD yield at different times in lactation were high, ranging from 0.846 to 0.998. The accuracy of phenotypic validation of GEBV from the method that is believed to be the least biased was 0.420, which was very similar to the accuracy obtained from the average prediction error variance of the GEBV. Conclusions The results indicate strong potential for genomic selection to improve milk production of smallholder crossbred cows in India. The performance of cows with different breed compositions can be determined in different Indian environments, which makes it possible to provide better advice to smallholder farmers on optimum breed composition for their environment.

The objective of the study was to evaluate the performance of sex sorted semen that was produced for the first time in India at BAIF semen production facility, Pune, using the technological processes of sexing technologies, USA, under tropical small holder dairy production systems. Additionally, a notable point is that the semen was produced from the population of Indian breeds of cattle, its crosses and buffaloes which co-evolved and adopted to the country' agro climatic conditions. 21,012 artificial insemination data and 2,284 calving records were included in the analysis. The parameters evaluated were conception rate and sex ratio. The statistical analysis was performed using the logistic regression method to estimate the effect of factors on conception rate. The effects studied were states, order of lactation, month of insemination, and breed of bull. The overall mean conception rate was 39.92 ± 0.5 per cent, while the sex ratio of female to male was found to be 90.9 %. All of the effects included in the study significantly influenced the conception rate. Odisha state reported higher conception rate while low conception rate was found in Uttarakhand state. Conception rate increased gradually from November to April and declined later. Heifers showed higher conception rate than cows with subsequent lactations, however the difference among the other lactations was very less. The Holstein Friesian crossbred bulls with 75 per cent exotic blood level showed better conception rate than the rest of the breeds. Present study highlights the technical performance and merits of using sex sorted semen in the Indian dairy sector as a way to increase the country' milk production and reduce the burden of maintaining male calves at farm level.

Dairy farming plays a very important role in improving the economy of rural India. The study was conducted to explore the socio-economic profile of dairy farmers and farmers feedback about dairy development project. The survey was conducted to study the education status, family structure, education status and management of animals, different patterns of rearing of dairy animals and status of milk production. Data was collected from the 3000 dairy farmers of three states namely Maharashtra, Bihar and Uttar Pradesh during year  2016 .Concentration of poor farmers was relatively high in Bihar (35.5%), followed by Uttar Pradesh (30.9%) and 16.3% in case of Maharashtra. Average family size show 8.74 members per household in Bihar, 6.76 members in  Uttar Pradesh  and 6.17 members in Maharashtra. Results revealed that majority of the families were nuclear families. Main source of income was agriculture which includes livestock farming. As regards to the size of land owned, nearly 56% of the landowners were Marginal farmers (owning 0.1 -1 ha of land), 23% were small (1.1-2 ha) landowners while about 12% farmers owned above 2 ha of land. Literacy level was higher among farmers of Maharashtra (71.6%) as compared to Uttar Pradesh (65.8%) and Bihar (65.4%). Majority of the farmers followed mixed cropping system, Maximum number of cows and buffaloes were owned by the farmers of Maharashtra i.e. 3.37 cows and 1.42 buffaloes, followed by Uttar Pradesh (1.60 cows & 1.42 buffaloes) and Bihar (1.75 cows & 0.24 buffaloes).Farmers of Maharashtra owned maximum percentage of crossbred cows (90.97%), followed by Uttar Pradesh (83.4%) and Bihar (75.9%).Maharashtra farmers  possessed maximum number of upgraded buffaloes (79.4%), followed by Bihar (55.7%) and Uttar Pradesh (51.5%). In study of average quantity of milk produced by cows was higher among the crossbred cows (10.18 litres), in indigenous cows it was (4.47 litres) and 4.23 liters in Non-Descript cows. The data shows the same pattern of milk produced across the three states with slight variation. In buffaloes, the average quantity of milk produced was observed to be higher among the upgraded buffaloes (8.42 litres) as compared to Non-Descript buffaloes (5.17 litres). Respondents appreciated the fact that due to dairy development project by BAIF their family and social status have increased.