scholarly journals Genetic variation in milk urea nitrogen concentration of dairy cattle and its implications for reducing urinary nitrogen excretion

animal ◽  
2019 ◽  
Vol 13 (10) ◽  
pp. 2164-2171 ◽  
Author(s):  
P.R. Beatson ◽  
S. Meier ◽  
N.G. Cullen ◽  
H. Eding
2013 ◽  
Vol 4 (s1) ◽  
pp. 28-36 ◽  
Author(s):  
Donagh P. Berry

Animal breeding should be considered as a permanent and cumulative approach to reducing the environmental footprint of dairy cattle production systems within an overall national and global mitigation strategy. Current international dairy cattle breeding goals do not explicitly include environmental traits, but observed improvements in milk production and both fertility and longevity contribute substantially to improving the environmental footprint relative to output. Ideally, however, environmental related traits, most notably greenhouse gas emissions and nitrogen excretion, should be explicitly included in national breeding goals with their own economic weight. Access to routine phenotypic observations for the environmental traits or other information including genomic information or information on heritable correlated traits is required for inclusion in the selection index. There is, however, a considerable paucity of information on the genetic parameters for, in particular, greenhouse gas emissions in dairy cattle; these parameters include genetic variance estimates, as well as genetic and phenotypic (co)variances with other performance traits. Large studies with well phenotyped animals across a range of environments are needed to estimate such parameters and also investigate the extent, if any, of genotype-by-environment interactions across contrasting environments. Considerable genetic variation in milk urea nitrogen, as a proxy for nitrogen excretion in the urine, exist and suggest that breeding programmes to improve nitrogen use efficiency will be fruitful. However, because of the antagonistic genetic correlations between milk urea nitrogen and milk production, genetic gain in milk yield is expected to be compromised within a breeding goal that includes milk urea nitrogen.


2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 171-171
Author(s):  
Matthew R Beck ◽  
Cameron Marshall ◽  
Konagh Garrett ◽  
Andrew P Foote ◽  
Ronaldo Vibart ◽  
...  

Abstract Urine nitrogen excretion (g/d; UN) represent a significant environmental impact for both confinement feeding and pastoral based dairy systems. It is difficult to measure UN directly due to animal handling and labor requirements, especially in forage based production systems. The currently available milk urea nitrogen (MUN) equations have been shown to overestimate UN excretion of grazing dairy cows compared with an equation using urinary creatinine and UN concentration, indicating that diet may alter the relationship between MUN and UN. This potential was explored using data retrieved (treatment means: n = 69 and 27 for fresh forage [FF] and total mixed ration [TMR] fed cattle, respectively) from the literature and new data obtained from dairy cows fed FF (n = 15) in metabolism crates was used to test the new equations. The TMR data from literature was further split into a training set (to develop the model; n = 53) and a test set (to validate the model; n = 16). There was an interaction for diet type (P < 0.01) where UN (g/d) = 0.023 × MUN (mg/dL) × live-weight (kg, LW) for TMR fed cattle, (similar to a pre-established equation); however, UN (g/d) = 0.015 × MUN × LW for FF fed cattle. For FF based equations, the New MUN equation and the creatinine equation showed good precision and accuracy (Lin’s CCC = 0.79 and 0.74, respectively) and adequate predictive ability (RMSEP = 29.8 and 35.9, respectively). The new MUN equation for TMR fed cattle showed excellent accuracy and precision (Lin’s CCC = 0.87) with good predictive ability (RMSEP = 24.3) for UN excretion (observed mean = 216.5 g/d). The new equations generated during this meta-analysis provide promising predictive ability of UN excretion, which can be used for management considerations, future research, and policy making.


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