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JournalISSN: 0021-8812

Journal of Animal Science 

About: Journal of Animal Science is an academic journal. The journal publishes majorly in the area(s): Beef cattle & Population. It has an ISSN identifier of 0021-8812. Over the lifetime, 29825 publication(s) have been published receiving 930744 citation(s).


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Journal ArticleDOI
TL;DR: The Cornell Net Carbohydrate and Protein System has a submodel that predicts rates of feedstuff degradation in the rumen, the passage of undegraded feed to the lower gut, and the amount of ME and protein that is available to the animal.
Abstract: The Cornell Net Carbohydrate and Protein System (CNCPS) has a submodel that predicts rates of feedstuff degradation in the rumen, the passage of undegraded feed to the lower gut, and the amount of ME and protein that is available to the animal. In the CNCPS, structural carbohydrate (SC) and nonstructural carbohydrate (NSC) are estimated from sequential NDF analyses of the feed. Data from the literature are used to predict fractional rates of SC and NSC degradation. Crude protein is partitioned into five fractions. Fraction A is NPN, which is trichloroacetic (TCA) acid-soluble N. Unavailable or protein bound to cell wall (Fraction C) is derived from acid detergent insoluble nitrogen (ADIP), and slowly degraded true protein (Fraction B3) is neutral detergent insoluble nitrogen (NDIP) minus Fraction C. Rapidly degraded true protein (Fraction B1) is TCA-precipitable protein from the buffer-soluble protein minus NPN. True protein with an intermediate degradation rate (Fraction B2) is the remaining N. Protein degradation rates are estimated by an in vitro procedure that uses Streptomyces griseus protease, and a curve-peeling technique is used to identify rates for each fraction. The amount of carbohydrate or N that is digested in the rumen is determined by the relative rates of degradation and passage. Ruminal passage rates are a function of DMI, particle size, bulk density, and the type of feed that is consumed (e.g., forage vs cereal grain).

3,151 citations

Journal ArticleDOI
TL;DR: This procedure implements random effects in the statistical model and permits modeling the covariance structure of the data, and can compute efficient estimates of fixed effects and valid standard errors of the estimates in the SAS System.
Abstract: Mixed linear models were developed by animal breeders to evaluate genetic potential of bulls. Application of mixed models has recently spread to all areas of research, spurred by availability of advanced computer software. Previously, mixed model analyses were implemented by adapting fixed-effect methods to models with random effects. This imposed limitations on applicability because the covariance structure was not modeled. This is the case with PROC GLM in the SAS® System. Recent versions of the SAS System include PROC MIXED. This procedure implements random effects in the statistical model and permits modeling the covariance structure of the data. Thereby, PROC MIXED can compute efficient estimates of fixed effects and valid standard errors of the estimates. Modeling the covariance structure is especially important for analysis of repeated measures data because measurements taken close in time are potentially more highly correlated than those taken far apart in time.

2,654 citations

Journal ArticleDOI
TL;DR: Knowing the factors that impact methane production can result in the development of mitigation strategies to reduce methane losses by cattle and implementation of these strategies should result in enhanced animal productivity and decreased contributions by cattle to the atmospheric methane budget.
Abstract: Increasing atmospheric concentrations of methane have led scientists to examine its sources of origin. Ruminant livestock can produce 250 to 500 L of methane per day. This level of production results in estimates of the contribution by cattle to global warming that may occur in the next 50 to 100 yr to be a little less than 2%. Many factors influence methane emissions from cattle and include the following: level of feed intake, type of carbohydrate in the diet, feed processing, addition of lipids or ionophores to the diet, and alterations in the ruminal microflora. Manipulation of these factors can reduce methane emissions from cattle. Many techniques exist to quantify methane emissions from individual or groups of animals. Enclosure techniques are precise but require trained animals and may limit animal movement. Isotopic and nonisotopic tracer techniques may also be used effectively. Prediction equations based on fermentation balance or feed characteristics have been used to estimate methane production. These equations are useful, but the assumptions and conditions that must be met for each equation limit their ability to accurately predict methane production. Methane production from groups of animals can be measured by mass balance, micrometeorological, or tracer methods. These techniques can measure methane emissions from animals in either indoor or outdoor enclosures. Use of these techniques and knowledge of the factors that impact methane production can result in the development of mitigation strategies to reduce methane losses by cattle. Implementation of these strategies should result in enhanced animal productivity and decreased contributions by cattle to the atmospheric methane budget.

1,987 citations

Journal ArticleDOI
TL;DR: The Cornell Net Carbohydrate and Protein System (CNCPS) has a kinetic submodel that predicts ruminal fermentation and the protein-sparing effect of ionophores is accommodated by decreasing the rate of peptide uptake by 34%.
Abstract: The Cornell Net Carbohydrate and Protein System (CNCPS) has a kinetic submodel that predicts ruminal fermentation. The ruminal microbial population is divided into bacteria that ferment structural carbohydrate (SC) and those that ferment nonstructural carbohydrate (NSC). Protozoa are accommodated by a decrease in the theoretical maximum growth yield (.50 vs .40 g of cells per gram of carbohydrate fermented), and the yields are adjusted for maintenance requirements (.05 vs .150 g of cell dry weight per gram of carbohydrate fermented per hour for SC and NSC bacteria, respectively). Bacterial yield is decreased when forage NDF is < 20% (2.5% for every 1% decrease in NDF). The SC bacteria utilize only ammonia as a N source, but the NSC bacteria can utilize either ammonia or peptides. The yield of NSC bacteria is enhanced by as much as 18.7% when proteins or peptides are available. The NSC bacteria produce less ammonia when the carbohydrate fermentation (growth) rate is rapid, but 34% of the ammonia production is insensitive to the rate of carbohydrate fermentation. Ammonia production rates are moderated by the rate of peptide and amino acid uptake (.07 g of peptide per gram of cells per hour), and peptides and amino acids can pass out of the rumen if the rate of proteolysis is faster than the rate of peptide utilization. The protein-sparing effect of ionophores is accommodated by decreasing the rate of peptide uptake by 34%. Validation with published data of microbial flow from the rumen gave a regression with a slope of .94 and an r2 of .88.

1,239 citations

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Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
2021473
2020890
2019803
20181,072
20171,063
20161,639