The Cornell Net Carbohydrate and Protein System:Updates to the model and evaluation of version 6.5

AbstractNew laboratory and animal sampling methods and data have been generated over the last 10 yr that had the potential to improve the predictions for energy, protein, and AA supply and requirements in the Cornell Net Carbohydrate and Protein System (CNCPS). The objectives of this study were to describe updates to the CNCPS and evaluate model performance against both literature and on-farm data. The changes to the feed library were significant and are reported in a separate manuscript. Degradation rates of protein and carbohydrate fractions were adjusted according to new fractionation schemes, and corresponding changes to equations used to calculate rumen outflows and postrumen digestion were presented. In response to the feed-library changes and an increased supply of essential AA because of updated contents of AA, a combined efficiency of use was adopted in place of separate calculations for maintenance and lactation to better represent the biology of the cow. Four different data sets were developed to evaluate Lys and Met requirements, rumen N balance, and milk yield predictions. In total 99 peer-reviewed studies with 389 treatments and 15 regional farms with 50 different diets were included. The broken-line model with plateau was used to identify the concentration of Lys and Met that maximizes milk protein yield and content. Results suggested concentrations of 7.00 and 2.60% of metabolizable protein (MP) for Lys and Met, respectively, for maximal protein yield and 6.77 and 2.85% of MP for Lys and Met, respectively, for maximal protein content. Updated AA concentrations were numerically higher for Lys and 11 to 18% higher for Met compared with CNCPS v6.0, and this is attributed to the increased content of Met and Lys in feeds that were previously incorrectly analyzed and described. The prediction of postruminal flows of N and milk yield were evaluated using the correlation coefficient from the BLUP (R2BLUP) procedure or model predictions (R2MDP) and the concordance correlation coefficient. The accuracy and precision of rumen-degradable N and undegradable N and bacterial N flows were improved with reduced bias. The CNCPS v6.5 predicted accurate and precise milk yield according to the first-limiting nutrient (MP or metabolizable energy) with a R2BLUP=0.97, R2MDP=0.78, and concordance correlation coefficient=0.83. Furthermore, MP-allowable milk was predicted with greater precision than metabolizable energy–allowable milk (R2MDP=0.82 and 0.76, respectively, for MP and metabolizable energy). Results suggest a significant improvement of the model, especially under conditions of MP limitation

Clinical Forms of Chikungunya in Gabon, 2010

Chikungunya fever (CHIK) is a disease caused by a virus transmitted to humans by infected mosquitos. The virus is responsible for multiple outbreaks in tropical and temperate areas worldwide, and is now a global concern. Clinical and biological features of the disease are poorly described, especially in Africa, where the disease is neglected because it is considered benign. During a recent CHIK outbreak that occurred in southeast Gabon, we prospectively studied clinical and biological features of 270 virologically confirmed cases. Fever and arthralgias were the predominant symptoms. Furthermore, variable and distinct clinical pictures including pure febrile, pure arthralgic and unusual forms (neither fever nor arthralgias) were detected. No severe forms or deaths were reported. These findings suggest that, during CHIK epidemics, some patients may not have classical symptoms (fever and arthralgias). Local surveillance is needed to detect any changes in the pathogenicity of this virus

Simulation of rumen particle dynamics using a non-steady state model of rumen digestion and nutrient availability in dairy cows fed sugarcane

An extant dynamic model of digestion and absorption of nutrients in cattle fed sugarcane was adapted for non-steady state feeding conditions. This modified model includes mechanisms of particle size reduction and delay in availability of particles and intracellular contents for microbial fermentation after ingestion. Two trials (one with beef cattle and the other with dairy cattle) were used to evaluate the non-steady state model. In general, predicted values were close to observed values for duodenal neutral detergent fibre (NDF) and nitrogen flows (mean squared prediction error (MSPE) of 14% and 15% of observed mean, respectively). There was no indication of over- or underprediction of NDF and nitrogen flows. An overestimation of rumen volume observed in steers suggests that the equation to calculate rumen volume needs to be adapted for low feed intake. Overall mean of milk production was predicted accurately. Predictions under non-steady state conditions showed higher accuracy when real intake behaviour was simulated. The model can be used to select strategies of supplementation of dairy cows fed sugarcane-based diets