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Development of prediction equation for methane-related traits in beef cattle under high concentrate diets.
Development of prediction equation for methane-related traits in beef cattle under high concentrate diets.
- Source :
- Animal Science Journal; Jan-Dec2020, Vol. 91 Issue 1, p1-11, 11p
- Publication Year :
- 2020
-
Abstract
- The objective of this study was to develop a prediction equation for methanerelated traits in beef cattle and evaluate this equation using datasets with different cattle breeds and roughage rates. Enteric methane emission (CH<subscript>4</subscript>, l/day) was measured using open-circuit respiration chambers. Dry matter intake (DMI, kg/day), body weight (BW, kg), daily gain (DG, kg), total digestible nutrients (TDN, %DMI), and roughage rate (Rrate, %) were used as independent variables, and methane-related traits--CH<subscript>4</subscript>, CH<subscript>4</subscript> per DMI (CH<subscript>4</subscript>/DMI, l/kg), and methane conversion factor (MCF, %)--were used as dependent variables. The best-fit equations to predict methanerelated traits using a total of 76 records were CH<subscript>4</subscript> = -676.7 + 0.04194 × BW + 29.88 × DMI + 7.883 × TDN + 4.367 × Rrate, CH<subscript>4</subscript>/DMI = -52.24 - 1.193 × 10<superscript>-3</superscript> × BW - 5.9 05 × DG + 1.077 × TDN + 0.5008 × Rrate, and MCF = -11.43 - 5.308 × 10<superscript>-4</superscript> × BW - 1.223 × DG + 0.2336 × TDN + 0.1157 × Rrate. The predictive ability of the developed equations differed between roughage rates but not between breeds. For CH<subscript>4</subscript>, the predictive ability of the developed equations was better compared with previously reported equations in the low roughage rate dataset, but not in the high roughage rate dataset. Our results suggest that the developed equations of methane-related traits can be applied in beef cattle fed with low roughage diets. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13443941
- Volume :
- 91
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Animal Science Journal
- Publication Type :
- Academic Journal
- Accession number :
- 144576089
- Full Text :
- https://doi.org/10.1111/asj.13341