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Predicting enteric methane production from cattle in the tropics

Published online by Cambridge University Press:  11 August 2020

R. S. Ribeiro,
J. P. P. RodriguesOpen the ORCID record for J. P. P. Rodrigues[Opens in a new window],
R. M. Maurício,
A. L. C. C. Borges,
R. Reis e Silva,
T. T. Berchielli,
S. C. Valadares Filho,
F. S. Machado,
M. M. Campos and
A. L. Ferreira
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R. S. Ribeiro
Affiliation:
Bio-Engineering Department, Federal University of São João Del Rei, 36307-352São João Del Rei, Minas Gerais, Brazil
J. P. P. Rodrigues
Affiliation:
Federal University of Southern and Southeastern Pará (UNIFESSPA), 68557-335Xinguara, Pará, Brazil
R. M. Maurício
Affiliation:
Bio-Engineering Department, Federal University of São João Del Rei, 36307-352São João Del Rei, Minas Gerais, Brazil
A. L. C. C. Borges
Affiliation:
Federal University of Minas Gerais State (UFMG), 31270-901Belo Horizonte, Minas Gerais, Brazil
R. Reis e Silva
Affiliation:
Federal University of Minas Gerais State (UFMG), 31270-901Belo Horizonte, Minas Gerais, Brazil
T. T. Berchielli
Affiliation:
São Paulo State University (UNESP), 14884-900Jaboticabal, São Paulo, Brazil
S. C. Valadares Filho
Affiliation:
Federal University of Viçosa (UFV), 36570-900Viçosa, Minas Gerais, Brazil
F. S. Machado
Affiliation:
Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil
M. M. Campos
Affiliation:
Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil
A. L. Ferreira
Affiliation:
Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil
R. Guimarães Júnior
Affiliation:
Brazilian Agricultural Research Corporation (EMBRAPA Cerrados), 73310-970Brasília, Distrito Federal, Brazil
J. A. G. Azevêdo
Affiliation:
State University of Santa Cruz, 45662-900Ilhéus, Bahia, Brazil
R. D. Santos
Affiliation:
Brazilian Agricultural Research Corporation (EMBRAPA Semiárido), 56302-970Petrolina, Pernambuco, Brazil
T. R. Tomich
Affiliation:
Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil
L. G. R. Pereira*
Affiliation:
Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil
*
†E-mail: luiz.gustavo@embrapa.br
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Abstract

Accurate estimates of methane (CH4) production by cattle in different contexts are essential to developing mitigation strategies in different regions. We aimed to: (i) compile a database of CH4 emissions from Brazilian cattle studies, (ii) evaluate prediction precision and accuracy of extant proposed equations for cattle and (iii) develop specialized equations for predicting CH4 emissions from cattle in tropical conditions. Data of nutrient intake, diet composition and CH4 emissions were compiled from in vivo studies using open-circuit respiratory chambers, SF6 technique or the GreenFeed® system. A final dataset containing intake, diet composition, digestibility and CH4 emissions (677 individual animal observations, 40 treatment means) obtained from 38 studies conducted in Brazil was used. The dataset was divided into three groups: all animals (GEN), lactating dairy cows (LAC) and growing cattle and non-lactating dairy cows (GCNL). A total of 54 prediction equations available in the literature were evaluated. A total of 96 multiple linear models were developed for predicting CH4 production (MJ/day). The predictor variables were DM intake (DMI), gross energy (GE) intake, BW, DMI as proportion of BW, NDF concentration, ether extract (EE) concentration, dietary proportion of concentrate and GE digestibility. Model selection criteria were significance (P < 0.05) and variance inflation factor lower than three for all predictors. Each model performance was evaluated by leave-one-out cross-validation. The Intergovernmental Panel on Climate Change (2006) Tier 2 method performed better for GEN and GCNL than LAC and overpredicted CH4 production for all datasets. Increasing complexity of the newly developed models resulted in greater performance. The GCNL had a greater number of equations with expanded possibilities to correct for diet characteristics such as EE and NDF concentrations and dietary proportion of concentrate. For the LAC dataset, equations based on intake and animal characteristics were developed. The equations developed in the present study can be useful for accurate and precise estimation of CH4 emissions from cattle in tropical conditions. These equations could improve accuracy of greenhouse gas inventories for tropical countries. The results provide a better understanding of the dietary and animal characteristics that influence the production of enteric CH4 in tropical production systems.

Keywords

beefdairydigestibilityemissionsgreenhouse gas

Information

Type
Research Article
Information
animal , Volume 14 , Issue S3: Greenhouse Gases and Animal Agriculture Conference (GGAA 2019), 4 - 8 August 2019, Iguassu Falls, Brazil , September 2020, pp. s438 - s452
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of The Animal Consortium

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Footnotes

*

These two authors contributed equally to this work.

a

Present address: EMBRAPA Dairy Cattle, Rua Eugênio do Nascimento, 610, Dom Bosco, 36038-330 Juiz de Fora, Minas Gerais, Brazil.

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