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Models to predict enteric methane emissions from cows fed different forage sources.

A. S. Atzori

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06-24-2020

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Abstract:

W70
Models to predict enteric methane emissions from cows fed different forage sources.
R. Manconi1, A. S. Atzori*1, J. A. D. R. N. Appuhamy2. 1Dipartimento di Agraria, University of Sassari Sassari, Italy, 2Iowa State University Ames, IA.

Addressing the diversity in forage sources is a key requirement of developing region-specific models to predict methane emissions (CH4) from dairy cattle. This study was aimed to develop empirical models to predict enteric CH4 from dairy cows fed different forage sources. A literature search was conducted for trials with enteric CH4 measurements (g/cow/d) of European dairy cows, which were published from 2000 to 2019. The database had 41 studies providing 195 treatment means of the CH4 of cows fed: 1) corn silage (CS, n = 37), 2) grass silage (GS, n = 66), 3) corn silage and grass silage (CGS, n = 69), and 4) pasture (PST, n = 23). Data were divided to 4 subsets based on the forage source. The models to predict CH4(g/cow/d) were developed separately for each forage source with a random-effect meta-analysis approach using the metaforpackage in R software. To avoid multicollinearity issues, 3 separate model development schemes including DMI (kg/d), GEI (MJ/d), or milk yield (MY, kg/d) with dietary CP, NDF, and EE (% of DM), milk protein (MPr, %) and milk fat (MFt, %), and BW (kg) were employed within each forage source. Models were evaluated using data used for model development. Following models having lowest root mean square prediction error as a % of mean observed value (RMSPE) were ranked best within each forage source. CS: CH4 = −431.7 + (1.4 � GEI) + (23.2 � CP) − (13.7 � EE) − (6.2 � NDF) + (39.8 � MFt) GS:CH4 = −282.0 + (11.9 � MY) + (2.9 � CP) − (6.6 � EE) + (4.9 � NDF) − (0.04 � BW) − (44.8 � MFt) CSG: CH4 = 171.6 + (8.7 � DMI) − (2.9 � CP) − (21.1 � EE) + (0.2 � BW) − (26.7 � MPrt) + (12.3 � MFt) PST: CH4 = 271.1 − (2.8 � MY) − (3.2 � CP) + (31.2 � EE) − (5.3 � NDF) + (0.6 � BW) The best model in CS, GS, CGS, and PST predicted the observed CH4 well as evident by low RMSPE (18.6, 11.5, 8.6, and 13.3%, respectively), a major proportion of which (95, 95, 99, and 86%, respectively) was due to random variability of data. This study provides a set of models that can be used predict accurately CH4 from dairy cows fed wide variety of forages using routinely available information. Models however need to be evaluated possibly with an independent data set to draw firmer conclusions on their predictive power.

Keywords: meta-analysis, grass, Europe.