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Predicting enteric methane production from cattle in the tropics.
Ribeiro, R S; Rodrigues, J P P; Maurício, R M; Borges, A L C C; Reis E Silva, R; Berchielli, T T; Valadares Filho, S C; Machado, F S; Campos, M M; Ferreira, A L; Guimarães Júnior, R; Azevêdo, J A G; Santos, R D; Tomich, T R; Pereira, L G R.
Affiliation
  • Ribeiro RS; Bio-Engineering Department, Federal University of São João Del Rei, 36307-352São João Del Rei, Minas Gerais, Brazil.
  • Rodrigues JPP; Federal University of Southern and Southeastern Pará (UNIFESSPA), 68557-335Xinguara, Pará, Brazil.
  • Maurício RM; Bio-Engineering Department, Federal University of São João Del Rei, 36307-352São João Del Rei, Minas Gerais, Brazil.
  • Borges ALCC; Federal University of Minas Gerais State (UFMG), 31270-901Belo Horizonte, Minas Gerais, Brazil.
  • Reis E Silva R; Federal University of Minas Gerais State (UFMG), 31270-901Belo Horizonte, Minas Gerais, Brazil.
  • Berchielli TT; São Paulo State University (UNESP), 14884-900Jaboticabal, São Paulo, Brazil.
  • Valadares Filho SC; Federal University of Viçosa (UFV), 36570-900Viçosa, Minas Gerais, Brazil.
  • Machado FS; Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil.
  • Campos MM; Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil.
  • Ferreira AL; Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil.
  • Guimarães Júnior R; Brazilian Agricultural Research Corporation (EMBRAPA Cerrados), 73310-970Brasília, Distrito Federal, Brazil.
  • Azevêdo JAG; State University of Santa Cruz, 45662-900Ilhéus, Bahia, Brazil.
  • Santos RD; Brazilian Agricultural Research Corporation (EMBRAPA Semiárido), 56302-970Petrolina, Pernambuco, Brazil.
  • Tomich TR; Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil.
  • Pereira LGR; Brazilian Agricultural Research Corporation (EMBRAPA Dairy Cattle), 36038-330Juiz de Fora, Minas Gerais, Brazil.
Animal ; 14(S3): s438-s452, 2020 Sep.
Article in En | MEDLINE | ID: mdl-32778195
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.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Lactation / Diet / Methane Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals Country/Region as subject: America do sul / Brasil Language: En Journal: Animal Year: 2020 Document type: Article Affiliation country: Brasil Country of publication: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Lactation / Diet / Methane Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals Country/Region as subject: America do sul / Brasil Language: En Journal: Animal Year: 2020 Document type: Article Affiliation country: Brasil Country of publication: Reino Unido