Short communication: Evaluation of nitrogen excretion equations from cattle

Johnson, A.; Reed, K.F.; Kebreab, E.

doi:10.3168/jds.2015-10730

Cited by 24 publications

(20 citation statements)

References 93 publications

(15 reference statements)

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“…The performance of FN prediction was intermediate (overall mean RMSPE = 21.3% and CCC = 0.59) compared with UN and TN predictions. In agreement with Johnson et al (2016) who indicated that equations developed by Reed et al (2015) for lactating cows resulted in greater prediction accuracy and less error compared with other exsiting models evaluated.…”

Section: Comparison Of Model Evaluation For the Five Forms Of N Excresupporting

confidence: 74%

“…An RMSPE value below 25% was deemed acceptable and an RMSPE below 10% of the mean was considered good. For error decomposition, mean or systemic bias larger than 5% of the total error was considered unacceptable (Johnson et al, 2016).…”

Section: Calculation Of Model Evaluationmentioning

confidence: 99%

“…Over the past 20 years, many N excretion models for dairy cows have been developed for specific countries or regions (i.e., Wilkerson et al, 1997;Jonker et al, 1998;Castillot et al, 2000;Kauffman and St-Pierre, 2001; Nennich et al, 2005;Nennich et al, 2006;Yan et al, 2006;Huhtanen et al, 2008;Marini et al, 2008;Kebreab et al, 2010;Higgs et al, 2012;Spek et al, 2013;Reed et al, 2015). Various evaluations (Nennich et al, 2006;Higgs et al, 2012;Reed et al, 2015;Johnson et al, 2016) of model performance for predicting manure N output from cows in developed countries have been published. Performance of the models varied across countries and regions due to differences in dietary and animal factors.…”

Section: Introductionmentioning

confidence: 99%

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Performance Evaluation of Manure Nitrogen Output Models Suitable for Lactating Dairy Cows in China

Dong¹,

Dong²,

Beauchemin³

et al. 2018

Transactions of the ASABE

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Abstract. Manure nitrogen (N) output from dairy cattle is a major environmental concern in China. Various empirical models are available to predict manure N output from dairy cattle, but the accuracy and precision of these models has not been assessed for Chinese conditions. The objective of this study was to evaluate the performance of extant models that predict different forms of manure N output for lactating dairy cows in China with the aim of identifying the best-fit and most suitable prediction models. A total of 35 empirical models were evaluated for their ability to predict N excretion of dairy cows in China fed a wide range of diets. The data set consisted of 99 treatment means from 32 publications with information on animal and dietary characteristics and N output flows. Performance of the models was evaluated using root mean square prediction error (RMSPE) and concordance correlation coefficient (CCC) analysis. A model (eq. 19) based on N intake (NI) was selected as best for predicting fecal N excretion (RMSPE = 15.8% and CCC = 0.75). Another model that also used NI as an input variable was most suitable for predicting urinary N (RMSPE = 26.0% and CCC = 0.63, eq. 14) and total N (RMSPE = 15.8% and CCC = 0.81, eq. 31). Models predicting urinary urea N (UUN) and urinary N / total N performed poorly. Overall, the deviation of the regression line from the equality line (y = x line) for even the best-fit urinary, fecal, and total N excretion models demonstrated the need to develop improved models for use under Chinese conditions. Using N output data from dairy cows in China to develop manure N output models may help improve environmental stewardship of the dairy industry in China. Keywords: Dairy cows, Evaluation, Manures, Model performance, Nitrogen excretion.

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Section: Comparison Of Model Evaluation For the Five Forms Of N Excresupporting

confidence: 74%

Section: Calculation Of Model Evaluationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Performance Evaluation of Manure Nitrogen Output Models Suitable for Lactating Dairy Cows in China

Dong¹,

Dong²,

Beauchemin³

et al. 2018

Transactions of the ASABE

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“…Digestibility analytical methods were performed via methods utilized by Johnson et al (2016) . Three methods were used to evaluate the markers: the root mean square prediction error ( RMSPE ), the Nash–Sutcliffe efficiency ( NSE ), and the concordance correlation coefficient ( CCC ).…”

Section: Methodsmentioning

confidence: 99%

Effects of two equine digestive aid supplements on hindgut health1

Johnson

Rossow

2018

Translational Animal Science

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Gastrointestinal disease is the number one killer of horses. Little is known about the maintenance of microbes in the equine hindgut and how to distinguish a healthy gut in a live horse. Utilization of internal and external digestibility markers and starch fermentation has been extensively studied in ruminants and is the basis for research conducted on horses. The aims of this study were to investigate the effects of two equine feed digestive aid supplements on hindgut health (HGH) as reflected in fecal pH and digestibility and to compare and validate DM digestibility measurements through the use of internal and external markers such as chromium oxide (CR), lignin (Lig), indigestible ADF (iADF), indigestible NDF (iNDF), and indigestible lignin (iLig). Nine mature Quarter horses (six geldings, three mares) were used in a crossover design, three feeding periods of 17 d (51 d total), using three treatments: control, no feed additive (CON), Smartpak (SP; Plymouth, MA), or Platinum Performance (PP; Buellton, CA). Both SP and PP contained a strain of Lactobacillus, whereas SP further supplied mannanoligosaccharides (MOS) and fructooligosaccharides (FOS) and PP supplied Saccharomyces boulardii. Within the 17-d period, horses were offered orchard grass hay and sweet cob grain and the assigned treatment daily and four CR cookies to deliver 8 g/d of CR for the last 7 d of each period. Total feces were collected from 15 to 17 d. Feed and fecal samples were dried, ground, and sent to ANALAB (Fulton, IL) for nutrient analysis. Duplicate samples of feed and feces were placed in ruminally cannulated cows for in situ determination of iADF, iNDF, and iLig to estimate digestibility. Estimated CR fecal output, CR DMI, and DM digestibilities were evaluated using the root mean square prediction error percentage of the observed mean (RMSPE), concordance correlation coefficient (CCC), and Nash–Sutcliffe efficiency methods. Marker predictive ability tests showed iADF to have the least amount of bias with the smallest RMSPE (4%), largest CCC (0.43), and the largest amount of random bias (error of dispersion = 0.45). Supplementation of PP decreased CR DM digestibility (P < 0.02). Smartpak increased fecal pH (P < 0.09), but PP had no effect on fecal pH. Therefore, SP had a beneficial effect on HGH that is believed to be due to MOS and FOS.

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“…From a recent summary of published N balance studies on beef cattle offered high and low CP diets, Sánchez Chopa, Nadin, Agnelli, Trindade, and Gonda (2016) concluded that the effect of increased N intake on N-use efficiency was equivocal, with increases and decreases in efficiency observed across experiments. Compared to (lactating) dairy cows (Huhtanen, Nousiainen, Rinne, Kytölä, & Khalili, 2008;Kebreab, Strathe, Fadel, Moraes, & France, 2010;Warner et al, 2015;Whelan et al, 2017), there is much less understood about the relationships between beef cattle nutrition and N excretion (Johnson, Reed, & Kebreab, 2016;Waldrip, Todd, & Cole, 2013), and even less so in relation to beef cattle offered fresh grass (Sánchez Chopa et al, 2016).…”

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confidence: 99%

Digestion and nitrogen metabolism in beef cattle and in vitro rumen fermentation of autumn grass differing in fertilizer nitrogen application rate

O’Connor

McGee

Moloney

et al. 2019

Grass and Forage Science

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Beef cattle partition dietary nitrogen (N) into meat or excrete it mainly in faeces and urine, which can contribute significantly to water and air pollution. The effects of two inorganic nitrogen (N) fertilizer application rates—15 (LN) or 80 (HN) kg N/ha—to Lolium perenne‐dominant swards in autumn, on herbage chemical composition, intake, digestion and N balance in beef cattle, and in vitro fermentation and methane production were studied. Four growing beef steers used in a 2 × 2 crossover design experiment were offered zero‐grazed grass harvested 21 days post‐N application between July and October. The same grasses were incubated in an eight‐vessel rumen simulation technique in a randomized complete block experiment. Grass dry‐matter (DM) concentration was 26 g/kg lower and crude protein (CP) concentration was 35 g/kg DM higher for HN compared to LN. There was no difference in herbage DM intake or in vivo DM digestibility between treatments. Nitrogen intake and the digestibility of N were higher for HN compared to LN. Total and urine N loss were 41 and 45 g/day greater, respectively, for HN compared to LN, but faecal N loss did not differ between treatments. The quantity of N retained and therefore N‐use efficiency did not differ between LN and HN (25% vs. 22%). In vitro rumen pH and ammonia‐N concentrations were higher for HN compared to LN, whereas volatile fatty acid concentrations and molar proportions did not differ between treatments. In vitro methane and total gas production were 0.9 mmol/day and 280 ml/day lower for HN than LN respectively. Under the particular conditions of this experiment, reducing fertilizer N application rate reduced total and urinary N excretion, which has potential environmental benefits; however, methane output measured in vitro was increased.

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Short communication: Evaluation of nitrogen excretion equations from cattle

Cited by 24 publications

References 93 publications

Performance Evaluation of Manure Nitrogen Output Models Suitable for Lactating Dairy Cows in China

Performance Evaluation of Manure Nitrogen Output Models Suitable for Lactating Dairy Cows in China

Effects of two equine digestive aid supplements on hindgut health1

Digestion and nitrogen metabolism in beef cattle and in vitro rumen fermentation of autumn grass differing in fertilizer nitrogen application rate

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