Improving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries
On-farm methane (CH4) emissions need to be estimated accurately so that the mitigation effect of recommended practices can be accounted for. In the present study prediction equations for enteric CH4 have been developed in lieu of expensive animal measurement approaches. Our objectives were to: (1) c...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | info:ar-repo/semantics/artículo |
| Language: | Inglés |
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Elsevier
2024
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.12123/16550 https://www.sciencedirect.com/science/article/pii/S0048969722062271 https://doi.org/10.1016/j.scitotenv.2022.159128 |
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| author | Congio, Guilhermo F.S. Bannink, André Mayorga, Olga L. Rodrigues, João P. P. Bougouin, Adeline Kebreab, Ermias Carvalho, Paulo C.F. Berchielli, Telma T. Mercadante, Maria E.Z. Valadares-Filho, Sebastião C. Borges, Ana L. C.C. Berndt, Alexandre Rodrigues, Paulo H.M. Ku-Vera, Juan C. Molina-Botero, Isabel C. Arango, Jacobo Reis, Ricardo A. Posada-Ochoa, Sandra L. Tomich, Thierry R. Castelán-Ortega, Octavio A. Marcondes, Marcos I. Gómez, Carlos Ribeiro-Filho, Henrique M.N. Gere, José Ignacio Ariza-Nieto, Claudia Giraldo, Luis A. Gonda, Horacio Ceron Cucchi, Maria Esperanza Hernandez, Olegario Ricci, Patricia Hristov, Alexander N. |
| author_browse | Arango, Jacobo Ariza-Nieto, Claudia Bannink, André Berchielli, Telma T. Berndt, Alexandre Borges, Ana L. C.C. Bougouin, Adeline Carvalho, Paulo C.F. Castelán-Ortega, Octavio A. Ceron Cucchi, Maria Esperanza Congio, Guilhermo F.S. Gere, José Ignacio Giraldo, Luis A. Gonda, Horacio Gómez, Carlos Hernandez, Olegario Hristov, Alexander N. Kebreab, Ermias Ku-Vera, Juan C. Marcondes, Marcos I. Mayorga, Olga L. Mercadante, Maria E.Z. Molina-Botero, Isabel C. Posada-Ochoa, Sandra L. Reis, Ricardo A. Ribeiro-Filho, Henrique M.N. Ricci, Patricia Rodrigues, João P. P. Rodrigues, Paulo H.M. Tomich, Thierry R. Valadares-Filho, Sebastião C. |
| author_facet | Congio, Guilhermo F.S. Bannink, André Mayorga, Olga L. Rodrigues, João P. P. Bougouin, Adeline Kebreab, Ermias Carvalho, Paulo C.F. Berchielli, Telma T. Mercadante, Maria E.Z. Valadares-Filho, Sebastião C. Borges, Ana L. C.C. Berndt, Alexandre Rodrigues, Paulo H.M. Ku-Vera, Juan C. Molina-Botero, Isabel C. Arango, Jacobo Reis, Ricardo A. Posada-Ochoa, Sandra L. Tomich, Thierry R. Castelán-Ortega, Octavio A. Marcondes, Marcos I. Gómez, Carlos Ribeiro-Filho, Henrique M.N. Gere, José Ignacio Ariza-Nieto, Claudia Giraldo, Luis A. Gonda, Horacio Ceron Cucchi, Maria Esperanza Hernandez, Olegario Ricci, Patricia Hristov, Alexander N. |
| author_sort | Congio, Guilhermo F.S. |
| collection | INTA Digital |
| description | On-farm methane (CH4) emissions need to be estimated accurately so that the mitigation effect of recommended practices can be accounted for. In the present study prediction equations for enteric CH4 have been developed in lieu of expensive animal measurement approaches. Our objectives were to: (1) compile a dataset from individual beef cattle data for the Latin America and Caribbean (LAC) region; (2) determine main predictors of CH4 emission variables; (3) develop and cross-validate prediction models according to dietary forage content (DFC); and (4) compare the predictive ability of these newly-developed models with extant equations reported in literature, including those currently used for CH4 inventories in LAC countries. After outlier's screening, 1100 beef cattle observations from 55 studies were kept in the final dataset (∼ 50 % of the original dataset). Mixed-effects models were fitted with a random effect of study. The whole dataset was split according to DFC into a subset for all-forage (DFC = 100 %), high-forage (94 % ≥ DFC ≥ 54 %), and low-forage (50 % ≥ DFC) diets. Feed intake and average daily gain (ADG) were the main predictors of CH4 emission (g d−1), whereas this was feeding level [dry matter intake (DMI) as % of body weight] for CH4 yield (g kg−1 DMI). The newly-developed models were more accurate than IPCC Tier 2 equations for all subsets. Simple and multiple regression models including ADG were accurate and a feasible option to predict CH4 emission when data on feed intake are not available. Methane yield was not well predicted by any extant equation in contrast to the newly-developed models. The present study delivered new models that may be alternatives for the IPCC Tier 2 equations to improve CH4 prediction for beef cattle in inventories of LAC countries based either on more or less readily available data. |
| format | info:ar-repo/semantics/artículo |
| id | INTA16550 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | Elsevier |
| publisherStr | Elsevier |
| record_format | dspace |
| spelling | INTA165502025-07-30T12:28:40Z Improving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries Congio, Guilhermo F.S. Bannink, André Mayorga, Olga L. Rodrigues, João P. P. Bougouin, Adeline Kebreab, Ermias Carvalho, Paulo C.F. Berchielli, Telma T. Mercadante, Maria E.Z. Valadares-Filho, Sebastião C. Borges, Ana L. C.C. Berndt, Alexandre Rodrigues, Paulo H.M. Ku-Vera, Juan C. Molina-Botero, Isabel C. Arango, Jacobo Reis, Ricardo A. Posada-Ochoa, Sandra L. Tomich, Thierry R. Castelán-Ortega, Octavio A. Marcondes, Marcos I. Gómez, Carlos Ribeiro-Filho, Henrique M.N. Gere, José Ignacio Ariza-Nieto, Claudia Giraldo, Luis A. Gonda, Horacio Ceron Cucchi, Maria Esperanza Hernandez, Olegario Ricci, Patricia Hristov, Alexander N. Nutrients Gases de Efecto Invernadero Análisis de la Regresión Ganado de Carne América Latina y el Caribe Nutrientes Greenhouse Gases Regression Analysis Beef Cattle Methane Emission Latin America and the Caribbean Emisiones de Metano Model Cross Validation Validación Cruzada del Modelo On-farm methane (CH4) emissions need to be estimated accurately so that the mitigation effect of recommended practices can be accounted for. In the present study prediction equations for enteric CH4 have been developed in lieu of expensive animal measurement approaches. Our objectives were to: (1) compile a dataset from individual beef cattle data for the Latin America and Caribbean (LAC) region; (2) determine main predictors of CH4 emission variables; (3) develop and cross-validate prediction models according to dietary forage content (DFC); and (4) compare the predictive ability of these newly-developed models with extant equations reported in literature, including those currently used for CH4 inventories in LAC countries. After outlier's screening, 1100 beef cattle observations from 55 studies were kept in the final dataset (∼ 50 % of the original dataset). Mixed-effects models were fitted with a random effect of study. The whole dataset was split according to DFC into a subset for all-forage (DFC = 100 %), high-forage (94 % ≥ DFC ≥ 54 %), and low-forage (50 % ≥ DFC) diets. Feed intake and average daily gain (ADG) were the main predictors of CH4 emission (g d−1), whereas this was feeding level [dry matter intake (DMI) as % of body weight] for CH4 yield (g kg−1 DMI). The newly-developed models were more accurate than IPCC Tier 2 equations for all subsets. Simple and multiple regression models including ADG were accurate and a feasible option to predict CH4 emission when data on feed intake are not available. Methane yield was not well predicted by any extant equation in contrast to the newly-developed models. The present study delivered new models that may be alternatives for the IPCC Tier 2 equations to improve CH4 prediction for beef cattle in inventories of LAC countries based either on more or less readily available data. Instituto de Patobiología Fil: Congio, Guilhermo F. S. University of São Paulo. Luiz de Queiroz College of Agriculture. Department of Animal Science; Brasil Fil: Bannink, André. Wageningen University & Research. Wageningen Livestock Research; Países Bajos Fil: Mayorga, Olga L. Colombian Corporation for Agricultural Research; Colombia Fil: Rodrigues, João P. P. Federal Rural University of Rio de Janeiro. Department of Animal Production. Animal Science Institute; Brasil Fil: Bougouin, Adeline. University of California. Department of Animal Science; Estados Unidos Fil: Kebreab, Ermias. University of California. Department of Animal Science; Estados Unidos Fil: Carvalho, Paulo C. F. Federal University of Rio Grande do Sul. Department of Forage Plants and Agrometeorology; Brasil Fil: Berchielli, Telma T. São Paulo State University. Department of Animal Science; Brasil Fil: Mercadante, Maria E. Z. São Paulo Agribusiness Technology Agency. Institute of Animal Science; Brasil Fil: Valadares-Filho, Sebastião C. Federal University of Viçosa. Department of Animal Science; Brasil Fil: Borges, Ana L. C. C. Federal University of Minas Gerais. Department of Animal Science; Brasil Fil: Berndt, Alexandre. Embrapa Southeast Livestock. Brazilian Agricultural Research Corporation; Brasil Fil: Rodrigues, Paulo H. M. University of São Paulo. Faculty of Veterinary Medicine and Animal Science. Department of Animal Nutrition and Production; Brasil Fil: Ku-Vera, Juan C. University of Yucatan. Faculty of Veterinary Medicine and Animal Science. Department of Animal Nutrition; México Fil: Molina-Botero, Isabel C. National Agrarian University La Molina. Faculty of Animal Science. Department of Animal Husbandry; Perú Fil: Arango, Jacobo. International Center for Tropical Agriculture; Colombia Fil: Reis, Ricardo A. São Paulo State University. Department of Animal Science; Brasil Fil: Posada-Ochoa, Sandra L. University of Antioquia. Faculty of Agricultural Sciences; Colombia Fil: Tomich, Thierry R. Embrapa Dairy Cattle. Brazilian Agricultural Research Corporation; Brasil Fil: Castelán-Ortega, Octavio A. Autonomous University of the State of Mexico. Faculty of Veterinary Medicine and Animal Science; México Fil: Marcondes, Marcos I. Washington State University. Department of Animal Sciences; Estados Unidos Fil: Gómez, Carlos. National Agrarian University La Molina. Faculty of Animal Science. Department of Animal Husbandry; Perú Fil: Ribeiro-Filho, Henrique M. N. Santa Catarina State University. Department of Animal and Food Science; Brasil Fil: Gere, Jose Ignacio. Universidad Tecnológica Nacional. División de Investigación y Desarrollo de Ingeniería; Argentina Fil: Gere, Jose Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Ariza-Nieto, Claudia. Colombian Corporation for Agricultural Research; Colombia Fil: Giraldo, Luis A. National University of Colombia. Faculty of Agricultural Sciences. Department of Animal Production; Colombia Fil: Gonda, Horacio. Swedish University of Agricultural Sciences. Faculty of Veterinary Medicine and Animal Science. Department of Animal Nutrition and Management; Suecia Fil: Ceron Cucchi, Maria Esperanza. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Patobiologia; Argentina Fil: Ceron Cucchi, Maria Esperanza. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Hernandez, Olegario. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santiago del Estero; Argentina Fil: Ricci, Patricia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Ricci, Patricia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce; Argentina Fil: Hristov, Alexander N. The Pennsylvania State University. Department of Animal Science; Estados Unidos 2024-01-12T16:19:52Z 2024-01-12T16:19:52Z 2023-01 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/16550 https://www.sciencedirect.com/science/article/pii/S0048969722062271 1879-1026 https://doi.org/10.1016/j.scitotenv.2022.159128 eng info:eu-repo/semantics/restrictedAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Elsevier Science of the Total Environment 856 (2) : 159128 (Enero 2023) |
| spellingShingle | Nutrients Gases de Efecto Invernadero Análisis de la Regresión Ganado de Carne América Latina y el Caribe Nutrientes Greenhouse Gases Regression Analysis Beef Cattle Methane Emission Latin America and the Caribbean Emisiones de Metano Model Cross Validation Validación Cruzada del Modelo Congio, Guilhermo F.S. Bannink, André Mayorga, Olga L. Rodrigues, João P. P. Bougouin, Adeline Kebreab, Ermias Carvalho, Paulo C.F. Berchielli, Telma T. Mercadante, Maria E.Z. Valadares-Filho, Sebastião C. Borges, Ana L. C.C. Berndt, Alexandre Rodrigues, Paulo H.M. Ku-Vera, Juan C. Molina-Botero, Isabel C. Arango, Jacobo Reis, Ricardo A. Posada-Ochoa, Sandra L. Tomich, Thierry R. Castelán-Ortega, Octavio A. Marcondes, Marcos I. Gómez, Carlos Ribeiro-Filho, Henrique M.N. Gere, José Ignacio Ariza-Nieto, Claudia Giraldo, Luis A. Gonda, Horacio Ceron Cucchi, Maria Esperanza Hernandez, Olegario Ricci, Patricia Hristov, Alexander N. Improving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries |
| title | Improving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries |
| title_full | Improving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries |
| title_fullStr | Improving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries |
| title_full_unstemmed | Improving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries |
| title_short | Improving the accuracy of beef cattle methane inventories in Latin America and Caribbean countries |
| title_sort | improving the accuracy of beef cattle methane inventories in latin america and caribbean countries |
| topic | Nutrients Gases de Efecto Invernadero Análisis de la Regresión Ganado de Carne América Latina y el Caribe Nutrientes Greenhouse Gases Regression Analysis Beef Cattle Methane Emission Latin America and the Caribbean Emisiones de Metano Model Cross Validation Validación Cruzada del Modelo |
| url | http://hdl.handle.net/20.500.12123/16550 https://www.sciencedirect.com/science/article/pii/S0048969722062271 https://doi.org/10.1016/j.scitotenv.2022.159128 |
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