Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: A meta-analysis

Manure nitrogen (N) from cattle contributes to nitrous oxide and ammonia emissions and nitrate leaching. Measurement of manure N outputs on dairy farms is laborious, expensive, and impractical at large scales; therefore, models are needed to predict N excreted in urine and feces. Building robust prediction models requires extensive data from animals under different management systems worldwide. Thus, the study objectives were (1) to collate an international database of N excretion in feces and urine based on individual lactating dairy cow data from different continents; (2) to determine the suitability of key variables for predicting fecal, urinary, and total manure N excretion; and (3) to develop robust and reliable N excretion prediction models based on individual data from lactating dairy cows consuming various diets. A raw data set was created based on 5,483 individual cow observations, with 5,420 fecal N excretion and 3,621 urine N excretion measurements collected from 162 in vivo experiments conducted by 22 research institutes mostly located in Europe (n = 14) and North America (n = 5). A sequential approach was taken in developing models with increasing complexity by incrementally adding variables that had a significant individual effect on fecal, urinary, or total 2manure N excretion. Nitrogen excretion was predicted by fitting linear mixed models including experiment as a random effect. Simple models requiring dry matter intake (DMI) or N intake performed better for predicting fecal N excretion than simple models using diet nutrient composition or milk performance parameters. Simple models based on N intake performed better for urinary and total manure N excretion than those based on DMI, but simple models using milk urea N (MUN) and N intake performed even better for urinary N excretion. The full model predicting fecal N excretion had similar performance to simple models based on DMI but included several independent variables (DMI, diet crude protein content, diet neutral detergent fiber content, milk protein), depending on the location, and had root mean square prediction errors as a fraction of the observed mean values of 19.1% for intercontinental, 19.8% for European, and 17.7% for North American data sets. Complex total manure N excretion models based on N intake and MUN led to prediction errors of about 13.0% to 14.0%, which were comparable to models based on N intake alone. Intercepts and slopes of variables in optimal prediction equations developed on intercontinental, European, and North American bases differed from each other, and therefore region-specific models are preferred to predict N excretion. In conclusion, region-specific models that include information on DMI or N intake and MUN are required for good prediction of fecal, urinary, and total manure N excretion. In absence of intake data, region-specific complex equations using easily and routinely measured variables to predict fecal, urinary, or total manure N excretion may be used, but these equations have lower performance than equations based on intake

Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: a meta-analysis

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Invited review: Large-scale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions

Publication history: Accepted - 7 December 2016; Published online - 1 February 2017.Efforts to reduce the carbon footprint of milk production through selection and management of low-emitting cows require accurate and large-scale measurements of methane (CH4) emissions from individual cows. Several techniques have been developed to measure CH4 in a research setting but most are not suitable for large-scale recording on farm. Several groups have explored proxies (i.e., indicators or indirect traits) for CH4; ideally these should be accurate, inexpensive, and amenable to being recorded individually on a large scale. This review (1) systematically describes the biological basis of current potential CH4 proxies for dairy cattle; (2) assesses the accuracy and predictive power of single proxies and determines the added value of combining proxies; (3) provides a critical evaluation of the relative merit of the main proxies in terms of their simplicity, cost, accuracy, invasiveness, and throughput; and (4) discusses their suitability as selection traits. The proxies range from simple and low-cost measurements such as body weight and high-throughput milk mid-infrared spectroscopy (MIR) to more challenging measures such as rumen morphology, rumen metabolites, or microbiome profiling. Proxies based on rumen samples are generally poor to moderately accurate predictors of CH4, and are costly and difficult to measure routinely onfarm. Proxies related to body weight or milk yield and composition, on the other hand, are relatively simple, inexpensive, and high throughput, and are easier to implement in practice. In particular, milk MIR, along with covariates such as lactation stage, are a promising option for prediction of CH4 emission in dairy cows. No single proxy was found to accurately predict CH4, and combinations of 2 or more proxies are likely to be a better solution. Combining proxies can increase the accuracy of predictions by 15 to 35%, mainly because different proxies describe independent sources of variation in CH4 and one proxy can correct for shortcomings in the other(s). The most important applications of CH4 proxies are in dairy cattle management and breeding for lower environmental impact. When breeding for traits of lower environmental impact, single or multiple proxies can be used as indirect criteria for the breeding objective, but care should be taken to avoid unfavorable correlated responses. Finally, although combinations of proxies appear to provide the most accurate estimates of CH4, the greatest limitation today is the lack of robustness in their general applicability. Future efforts should therefore be directed toward developing combinations of proxies that are robust and applicable across diverse production systems and environments.Technical and financial support from the COST Action FA1302 of the European Union

Supplementary Figure S2 - Typical fecal excretion curves - JDS19932

Supplementary Figure S2. Typical excretion curves of individual calf observations. The measured concentrations of Co (upper panel), Yb (middle panel), and Cr (lower panel) in feces with the fitted curve using the generalized Michaelis-Menten equation, as proposed by López et al. (2000)

Supplementary Figure S1 - Timeline experimental protocol - JDS19932

Supplementary Figure S1. Timeline of the experimental protocol per batch of calves (2 batches, 24 calves each). For each treatment (6 calves per treatment), the adaptation period ranged from 6 to 9 weeks for pair 1 to 3 (i.e., paired according to BW). The second batch of calves had a higher BW from the start, therefore having a shorter adaptation period ranging from 5 to 8 weeks. The adaptation period was followed by 7 days in climate respiration chambers (pair-housed) to measure the recovery of 13C tracers in breath after intravenous administration of [13C]sodium bicarbonate and oral administration of [1-13C]octanoate and bacterial protein, as detailed for pair 1. Subsequently, calves were fitted with harnesses to which plastic bags were attached and housed individually in a pen for 7 days, to determine the fecal excretion curves of 3 orally administrated indigestible markers (i.e., Cr-NDF, Yb2O3, and Co-EDTA), as detailed for pair 3

Supplementary Figure S1 - Timeline experimental protocol - JDS19932

Supplementary Figure S1. Timeline of the experimental protocol per batch of calves (2 batches, 24 calves each). For each treatment (6 calves per treatment), the adaptation period ranged from 6 to 9 weeks for pair 1 to 3 (i.e., paired according to BW). The second batch of calves had a higher BW from the start, therefore having a shorter adaptation period ranging from 5 to 8 weeks. The adaptation period was followed by 7 days in climate respiration chambers (pair-housed) to measure the recovery of 13C tracers in breath after intravenous administration of [13C]sodium bicarbonate and oral administration of [1-13C]octanoate and bacterial protein, as detailed for pair 1. Subsequently, calves were fitted with harnesses to which plastic bags were attached and housed individually in a pen for 7 days, to determine the fecal excretion curves of 3 orally administrated indigestible markers (i.e., Cr-NDF, Yb2O3, and Co-EDTA), as detailed for pair 3

Supplementary Figure S2 - JDS19933 - passage kinetics in veal calves

Supplementary Figure S2. Typical excretion curves of individual calf observations. The measured concentrations of Co (upper panel), Yb (middle panel), and Cr (lower panel) in feces with the fitted curve using the generalized Michaelis-Menten equation, as proposed by López et al. (2000)

Supplementary Figure S1 - JDS19933 - passage kinetics in veal calves

Supplementary Figure S1. Timeline of the experimental protocol per batch of calves (2 batches, 24 calves each). For each treatment (6 calves per treatment), the adaptation period ranged from 6 to 9 weeks for pair 1 to 3 (i.e., paired according to BW). The second batch of calves had a higher BW from the start, therefore having a shorter adaptation period ranging from 5 to 8 weeks. The adaptation period was followed by 7 days in climate respiration chambers (pair-housed) to measure the recovery of 13C tracers in breath after intravenous administration of [13C]sodium bicarbonate and oral administration of [1-13C]octanoate and bacterial protein, as detailed for pair 1. Subsequently, calves were fitted with harnesses to which plastic bags were attached and housed individually in a pen for 7 days, to determine the fecal excretion curves of 3 orally administrated indigestible markers (i.e., Cr-NDF, Yb2O3, and Co-EDTA), as detailed for pair 3