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Seongwon Seo

Researcher at Chungnam National University

Publications -  87
Citations -  2364

Seongwon Seo is an academic researcher from Chungnam National University. The author has contributed to research in topics: Hanwoo & Genome. The author has an hindex of 19, co-authored 78 publications receiving 2097 citations. Previous affiliations of Seongwon Seo include Cornell University & Seoul National University.

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The Genome Sequence of Taurine Cattle: A Window to Ruminant Biology and Evolution

Christine G. Elsik, +328 more
- 24 Apr 2009 - 
TL;DR: To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage and provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.
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A revised CNCPS feed carbohydrate fractionation scheme for formulating rations for ruminants

TL;DR: In this paper, a modified version of the Cornell Net Carbohydrate and Protein System (CNCPS) was used to predict the digestibility of ruminant diets for appropriate levels and types of dietary carbohydrates.
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Dietary l-Carnitine Improves Nitrogen Utilization in Growing Pigs Fed Low Energy, Fat-Containing Diets

TL;DR: It is concluded that endogenous carnitine biosynthesis may be adequate to maintain sufficient tissue levels during growth, but that supplemental dietary Carnitine may be retained sufficiently so as to alter nutrient partitioning and thus body composition of 20-kg pigs.
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Glycerol as a feed supplement for ruminants: In vitro fermentation characteristics and methane production

TL;DR: McAllister et al. as mentioned in this paper found a fractional gas production rate of 0.051/h with a lag of 7.9 ǫ for glycerol, which was a slower rate and a longer lag than for the other substrates (P 4 production, pH, ammonia and volatile fatty acid concentrations (VFA) were measured.
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Development and evaluation of empirical equations to predict feed passage rate in cattle

TL;DR: In this paper, a random coefficients model that used each study effect as a random variable was used to select statistically significant input variables to predict rate of passage for all classes of dairy and beef cattle.