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Sunil Kumar Sirohi

Researcher at National Dairy Research Institute

Publications -  42
Citations -  800

Sunil Kumar Sirohi is an academic researcher from National Dairy Research Institute. The author has contributed to research in topics: Rumen & Population. The author has an hindex of 15, co-authored 39 publications receiving 697 citations.

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New aspects and strategies for methane mitigation from ruminants

TL;DR: The construction of a methanogenic gene catalogue through these approaches will lead to understand the microbiome function, its relation with the host and feeds, and therefore, will form the basis of practically viable and eco-friendly methane mitigation approaches, while improving the ruminant productivity.
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Factors affecting rumen methanogens and methane mitigation strategies

TL;DR: The present article aimed to cover comprehensively the different aspects of rumen methanogenesis such as the phylogeny of methanogens, their microbial ecology, factors affecting methane emission, mitigation strategies and need for further study.
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Molecular tools for deciphering the microbial community structure and diversity in rumen ecosystem

TL;DR: This review describes the different molecular methods and their applications in elucidating the rumen microbial community and reveals nucleic acid-based molecular approaches that allow both the qualitative and quantitative assessment of microbial diversity.
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Microbial profiles, in vitro gas production and dry matter digestibility based on various ratios of roughage to concentrate

TL;DR: The results indicate that methane emission, enteric fermentation patterns, and change in methanogens population appear only with higher level of roughage, which is important for reducing methane without any impact on rumen performance.
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Dominance of Methanomicrobium phylotype in methanogen population present in Murrah buffaloes (Bubalus bubalis).

TL;DR: To study the diversity of rumen methanogens in Murrah buffaloes (Bubalus bubalis) from North India by using 16S rRNA gene libraries obtained from the pooled rumen content from four animals and using suitable software analysis.