Equations to predict nitrogen outputs in manure, urine and faeces from beef cattle fed diets with contrasting crude protein concentration. (1st October 2021)

• Record Type: Journal Article
• Authors: Angelidis, Angelos E.; Crompton, Les; Misselbrook, Tom; Yan, Tianhai; Reynolds, Christopher K.; Stergiadis, Sokratis
• Is Part Of: Journal of environmental management. Volume 295(2021)
• Publication Date: 2021-10-01
• Subjects: Nitrogen -- Efficiency -- Beef -- Urine -- Faeces -- Prediction; ADF acid detergent fibre -- AFBI Agri-Food and Biosciences Institute -- BW animal body weight -- CEDAR The Centre for Dairy Research -- CP crude protein -- DM dry matter -- DMI dry matter intake -- EE ether extract -- FNO faeces nitrogen output -- GE gross energy -- GHG green house gases -- ID identity -- Rc Lin's concordance correlation coefficient -- ME metabolisable energy -- MNO manure nitrogen output -- MPE mean prediction error -- MSPE mean squared prediction error -- N nitrogen -- N2O nitrous oxide -- NDF neutral detergent fibre -- NH3 ammonia -- NI nitrogen intake -- NUE nitrogen use efficiency -- OM organic matter -- RDP rumen degradable protein -- ST starch -- TF total forage -- UNO urine nitrogen output; Environmental policy -- Periodicals; Environmental management -- Periodicals; Environment -- Periodicals; Ecology -- Periodicals; 363.705
• DOI: 10.1016/j.jenvman.2021.113074
• Languages: English
• ISSNs: 0301-4797

Abstract

Abstract: Accurately predicting nitrogen (N) outputs in manure, urine and faeces from beef cattle is crucial for the realistic assessment of the environmental footprint of beef production and the development of sustainable N mitigation strategies. This study aimed to develop and validate equations for N outputs in manure, urine and faeces for animals under diets with contrasting crude protein (CP) concentrations. Measurements from individual animals (n = 570), including bodyweight, feed intake and chemical composition, and N outputs were (i) analysed as a merged database and also (ii) split into three sub-sets, according to diet CP concentration (low CP, 84–143 g/kg dry matter, n = 190; medium CP, 144–162 g/kg dry matter, n = 190; high CP, 163–217 g/kg dry matter, n = 190). Prediction equations were developed and validated using residual maximum likelihood analysis and mean prediction error (MPE), respectively. In low CP diets the lowest MPE for N outputs in manure, urine and faeces was 0.244, 0.594 and 0.263, respectively; diet CP-specific equations improved accuracy in certain occasions, by 4.9% and 18.3% for manure N output and faeces N output respectively, while a reduction by 5.7% in the prediction accuracy for urinary N output was noticed. In medium CP diets the lowest MPE for N outputs in manure, urine and faeces was 0.227, 0.391 and 0.394, respectively; diet CP-specific equations improved accuracy by 13.2%, 41.2% and 16.8% respectively. In high CP diets the lowest MPE for N outputs in manure, urine and faeces was 0.120, 0.154 and 0.144, respectively; diet CP-specific equations improved accuracy in certain occasions by 5.8%, 9.1% and 6.3% respectively. This study demonstrated that for improved prediction accuracy of N outputs in manure, urine and faeces from beef cattle, the use of dietary CP concentration is essential while dietary starch, fat, and metabolisable energy concentrations can be used to further improve accuracy. In beef cattle fed low CP concentration diets, using diet CP-specific equations improves prediction accuracy when feed intake or dietary CP concentration are not known. However, in beef cattle fed medium or high CP concentration diets, using equations that have been developed from animals fed similar CP concentration diets, substantially improves the prediction accuracy of N outputs in manure, urine and faeces in most cases. Highlights: Existing prediction models underestimate N output from beef consuming N-rich diets. 570 intake/output data from beef on different diets were used to predict N output. Equations were developed and validated for beef fed different diet N concentrations. Equations specific to beef diet N concentration improve prediction accuracy of N outputs. Diet N is essential predictor and starch, fat and energy concentrations enhance accuracy.