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India has the largest dairy industry in the world and accounts for a significant share of the global emission of livestock methane ( CH 4 ), a potent greenhouse gas (GHG). While previous works have examined the large-scale livestock CH 4 emissions in India, bottom-up studies are essential to account for the diverse farm conditions and practices across the subcontinent. We developed a Methane Calculator for Indian livestock sector using the Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology for estimating methane emissions from enteric fermentation and manure management. Using this calculator, we undertook a study of emissions from four dairy farms in the tropical coastal district of Thiruvananthapuram, Kerala, in June 2019. Livestock population and milk production data were collected from the four farms, to compute a mean CH 4 emission of 0.7183 kg CO 2 equivalents/kg of fat and protein corrected milk (kg CO 2 e/kg FPCM), with a notable farm-to-farm variability (63.3%). Having implemented the latest available guidelines outlined by the IPCC, our results are a valuable new addition to the existing body of knowledge in the measurement of dairy farm GHG emissions. We present this as a pilot study, demonstrating a simple method to perform bottom-up investigations of dairy GHG emissions and further formulate policy interventions and mitigation strategies at the farm level. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Though Punjab was among the first states to reap the rich benefits of operation flood, however the contribution of Punjab in country's total milk production has shown a decline in last 20 years from around 9.5% to 6.8%. India after the operation flood in 1960s has emerged, from the shortage of milk at the time of independence, as a top-ranking milk producing country in the world. Though the state has witnessed a constant increase in milk production but contribution of Punjab in country's total milk production has shown a decline in last 20 years from around 9.5% to 6.8%. In these districts, the milk yield per in milk animal for indigenous cattle is also marginal higher than the state average. [Extracted from the article]