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1. Using Structural Equation Modeling to Understand Interactions Between Bacterial and Archaeal Populations and Volatile Fatty Acid Proportions in the Rumen

Author

Veronica Kaplan-Shabtai, Nagaraju Indugu, Meagan Leslie Hennessy, Bonnie Vecchiarelli, Joseph Samuel Bender, Darko Stefanovski, Camila Flavia De Assis Lage, Susanna Elisabeth Räisänen, Audino Melgar, Krum Nedelkov, Molly Elizabeth Fetter, Andrea Fernandez, Addison Spitzer, Alexander Nikolov Hristov, and Dipti Wilhelmina Pitta

Subjects
dairy cows, host-microbe interactions, inter-species hydrogen transfer, metabolically- active microbes, microbial syntrophy, rumen microbiota, Microbiology, QR1-502
Abstract

Microbial syntrophy (obligate metabolic mutualism) is the hallmark of energy-constrained anaerobic microbial ecosystems. For example, methanogenic archaea and fermenting bacteria coexist by interspecies hydrogen transfer in the complex microbial ecosystem in the foregut of ruminants; however, these synergistic interactions between different microbes in the rumen are seldom investigated. We hypothesized that certain bacteria and archaea interact and form specific microbial cohorts in the rumen. To this end, we examined the total (DNA-based) and potentially metabolically active (cDNA-based) bacterial and archaeal communities in rumen samples of dairy cows collected at different times in a 24 h period. Notably, we found the presence of distinct bacterial and archaeal networks showing potential metabolic interactions that were correlated with molar proportions of specific volatile fatty acids (VFAs). We employed hypothesis-driven structural equation modeling to test the significance of and to quantify the extent of these relationships between bacteria-archaea-VFAs in the rumen. Furthermore, we demonstrated that these distinct microbial networks were host-specific and differed between cows indicating a natural variation in specific microbial networks in the rumen of dairy cows. This study provides new insights on potential microbial metabolic interactions in anoxic environments that have broader applications in methane mitigation, energy conservation, and agricultural production.

Published
2021
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2. Comparison of Two Sampling Techniques for Evaluating Ruminal Fermentation and Microbiota in the Planktonic Phase of Rumen Digesta in Dairy Cows

Author

Camila Flavia de Assis Lage, Susanna Elizabeth Räisänen, Audino Melgar, Krum Nedelkov, Xianjiang Chen, Joonpyo Oh, Molly Elizabeth Fetter, Nagaraju Indugu, Joseph Samuel Bender, Bonnie Vecchiarelli, Meagan Leslie Hennessy, Dipti Pitta, and Alexander Nikolov Hristov

Subjects
non-invasive sampling techniques, stomach tube method, rumen microbiome, rumen cannula, rumen fermentation, stomach tube, Microbiology, QR1-502
Abstract

The objective of this experiment was to compare ruminal fluid samples collected through rumen cannula (RC) or using an oral stomach tube (ST) for measurement of ruminal fermentation and microbiota variables. Six ruminally cannulated lactating Holstein cows fed a standard diet were used in the study. Rumen samples were collected at 0, 2, 4, 6, 8, and 12 h after the morning feeding on two consecutive days using both RC and ST techniques. Samples were filtered through two layers of cheesecloth and the filtered ruminal fluid was used for further analysis. Compared with RC, ST samples had 7% greater pH; however, the pattern in pH change after feeding was similar between sampling methods. Total volatile fatty acids (VFA), acetate and propionate concentrations in ruminal fluid were on average 23% lower for ST compared with RC. There were no differences between RC and ST in VFA molar proportions (except for isobutyrate), ammonia and dissolved hydrogen (dH2) concentrations, or total protozoa counts, and there were no interactions between sampling technique and time of sampling. Bacterial ASV richness was higher in ST compared with RC samples; however, no differences were observed for Shannon diversity. Based on Permanova analysis, bacterial community composition was influenced by sampling method and there was an interaction between sampling method and time of sampling. A core microbiota comprised of Prevotella, S24-7, unclassified Bacteroidales and unclassified Clostridiales, Butyrivibrio, unclassified Lachnospiraceae, unclassified Ruminococcaceae, Ruminococcus, and Sharpea was present in both ST and RC samples, although their relative abundance varied and was influenced by an interaction between sampling time and sampling method. Overall, our results suggest that ruminal fluid samples collected using ST (at 180 to 200 cm depth) are not representative of rumen pH, absolute values of VFA concentrations, or bacterial communities >2 h post-feeding when compared to samples of ruminal fluid collected using RC. However, ST can be a feasible sampling technique if the purpose is to study molar proportions of VFA, protozoa counts, dH2, and ammonia concentrations.

Published
2020
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3. Uncertainties in enteric methane inventories and measurement techniques

Author

Alexander Nikolov Hristov, Ermias Kebreab, Mutian Niu, Oh, J., Melgar, A., Bannink, A., Bayat, Ali R., Tommy Boland, Brito, André F., David Casper, Crompton, Les A., Jan Dijkstra, Eugène, Maguy A., Garnsworthy, P. C., Haque, N., Anne Louise Frydendahl Hellwing, Huhtanen, P., Michael Kreuzer, Björn Kuhla, Peter Lund, Madsen, J., Cécile Martin, Moate, Peter J., Stefan Muetzel, Muñoz, C., Nico Peiren, Powell, J. M., Reynolds, Christopher K., Angela Schwarm, Shingfield, Kevin J., Storlien, T. M., Martin Riis Weisbjerg, Yáñez-Ruiz, David R., Zhongtang Yu, Berndt, Alexandre, Ribeiro, Luiz Gustavo Pereira, and Abdalla, Adibe Luis

Subjects
dry matter intake, cattle, uncertainty, enteric methane
Published
2019

4. Evaluation of mathematical models to predict methane emissions from ruminants under different dietary mitigation strategies

Author

Mohammed Benaouda, Cécile Martin, Xinran Li, Ermias Kebreab, Alexander Nikolov Hristov, Zhongtang Yu, Yáñez-Ruiz, David R., Reynolds, Christopher K., Crompton, Les A., Jan Dijkstra, Bannink, A., Angela Schwarm, Michael Kreuzer, Mark McGee, Peter Lund, Anne Louise Frydendahl Hellwing, Martin Riis Weisbjerg, Moate, Peter J., Bayat, Ali R., Shingfield, Kevin J., Nico Peiren, Eugène, Maguy A., Unité Mixte de Recherches sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Institut National de la Recherche Agronomique (INRA), Animal Science, University of California [Davis] (UC Davis), University of California-University of California, Department of Animal Sciences, Microbiology, Ohio State University [Columbus] (OSU), Estación Experimental del Zaidín, Center for Dairy Research, Animal Science, University of Reading (UOR), Scool of Agriculture, Policy and Developement, Animal Nutrition Group, Animal Science, Wageningen University, Livestock research, Animal Science, Wageningen University and Research Center (WUR), Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences (NMBU), Institute of Agricultural Sciences, Ecole Polytechnique Fédérale de Zurich, Universita degli Studi di Padova, Department of Animal Sciences, University of Illinois at Urbana-Champaign [Urbana], University of Illinois System-University of Illinois System, Department of Animal Science, McGill University, Veterinary Science, Queen's University [Belfast] (QUB), Biology, SAMS, Berndt, Alexandre, Ribeiro, Luiz Gustavo Pereira, Abdalla, Adibe Luis, Unité Mixte de Recherche sur les Herbivores - UMR 1213 (UMRH), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de la Recherche Agronomique (INRA)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Wageningen University and Research [Wageningen] (WUR), McGill University = Université McGill [Montréal, Canada], and Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement

Subjects
livestock, base de données, prediction equation, marsh gas, [SDV]Life Sciences [q-bio], atténuation, nutritional practices, méthane, ruminant, hedging, enteric methane
Abstract

This study evaluated the ability of published models to predict enteric methane (CH4) emissions from dairy cattle, beef cattle, sheep and dairy goat, using a large database (3183 individual animal data). Models for each animal subcategory and CH4 dietary mitigating strategies of lipid or starch supplementation and of diet quality (described by organic matter digestibility and neutral-detergent fiber digestibility) were assessed. Models were ranked according to root mean square prediction error (RMSPE; % of observed mean) to standard deviation of observed values ratio (RSR) and RMSPE, using all data within each animal subcategory. For dairy cattle, CH4 emissions (g/day) were predicted with the smallest RSR using the model based on feeding level [dry matter intake (DMI)/body weight (BW)], digestibility of feed gross energy (dGE) and dietary ether extract (EE) content (RSR=0.66, RMSPE=15.6%). For beef cattle, the smallest RSR was obtained using GE intake, BW, forage and EE content (RSR=0.83, RMSPE=27.2%). For sheep and goat, there were limited published models; the smallest RSR was observed for a sheep model based on digestible energy intake (RSR = 0.61, RMSPE = 19.2%). IPCC Tier 2 models (1997; 2006) had low predictive ability for variation in dietary EE content, neutral detergent fiber content and organic matter digestibility (RMSPE 14.3-30.5% and 23.0-40.5% for dairy and beef cattle, respectively). No model predicted CH4 emissions accurately under all dietary mitigation strategies. Some models gave satisfactory predictions and for improved prediction, models should include feed intake, digestibility and information on dietary chemical composition.

5. Enteric methane emissions: Prediction and mitigation, the GLOBAL NETWORK projekt

Author

Alexander Nikolov Hristov, Ermias Kebreab, Mutian Niu, Oh, J., Arndt, C., Andre Bannink, Alireza Bayat, Andre Brito, David Casper, Crompton, L. A., Dijkstra, J., Garnsworthy, Phil C., Md Najmul Haque, Anne Louise Frydendahl Hellwing, Huhtanen, P., Michael Kreuzer, Björn Kuhla, Peter Lund, Jørgen Madsen, Mcclelland, S. C., Moate, Peter J., Muñoz, C., Nico Peiren, Powell, J. M., Reynolds, C. K., Angela Schwarm, Shingfield, Kevin J., Storlien, T., and Martin Riis Weisbjerg

Subjects
livestock, methane, prediction

6. Enteric methane mitigation strategies for ruminant livestock systems in the Latin America and Caribbean region: a meta-analysis

Author

Paulo Henrique Mazza Rodrigues, Jaime Ricardo Rosero-Noguera, Fábio Luis Henrique, André Bannink, Marcos Inácio Marcondes, Isabel Cristina Molina-Botero, Laura Bibiana Gualdrón-Duarte, Medardo Antonio Díaz Céspedes, Laura Astigarraga, María Paz Tieri, Víctor Ilich Alvarado Bolovich, Alexander N. Hristov, Xiomara Gaviria-Uribe, Telma Teresinha Berchielli, Adibe Luiz Abdalla, María Fernanda Vázquez-Carrillo, Roberto Soto-Blanco, Ana Luiza Costa Cruz Borges, F.A.S. Silva, Olga Lucía Mayorga Mogollón, Mohammed Benaouda, José Gere, L. S. Sakamoto, Thierry Ribeiro Tomich, Sandra Lucía Posada-Ochoa, Alda Lúcia Gomes Monteiro, Jacobo Arango, Luiz Gustavo Ribeiro Pereira, María Esperanza Cerón-Cucchi, Lucia Galvão de Albuquerque, Luiza Ilha Borges, Patrícia Perondi Anchão Oliveira, Octavio Alonso Castelán-Ortega, Sebastiao de Campos Valadares-Filho, Rafael Jiménez-Ocampo, Andrea Milena Sierra-Alarcón, Alexandre Berndt, Ricardo Reis e Silva, Sergio Abarca-Monge, Adibe Luiz Abdalla-Filho, Luis Alfonso Giraldo Valderrama, Ana Cláudia Ruggieri, Lorena Inés Mestra-Vargas, Carlos Alfredo Gómez-Bravo, Paulo César de Faccio Carvalho, Maria Eugênia Zerlotti Mercadante, Gustavo Jaurena, Abmael da Silva Cardoso, Rogério Martins Maurício, Juan Carlos Ku-Vera, Guilhermo Francklin de Souza Congio, Fernanda Samarini Machado, Ricardo Andrade Reis, Diego Zanetti, M. B. Chiavegato, María Paula Juliarena, Patricia Ricci, Sila Carneiro da Silva, Jusiane Rossetto, Ever del Jesus Flores-Santiago, Mariana Magalhães Campos, Flávio Perna Júnior, Tainá Silvestre Moreira, Claudia Janeth Ariza-Nieto, Jean Victor Savian, Helena Ferreira Lage, Juliana Duarte Messana, Banira Lombardi, Camila Muñoz, Rolando Barahona-Rosales, Henrique Mendonça Nunes Ribeiro-Filho, Olegario Hernández, Abimael Ortiz-Chura, João Paulo Pacheco Rodrigues, Horacio Leandro Gonda, Tibaitatá, Universidade de São Paulo (USP), Wageningen University & Research, The Pennsylvania State University, University of Buenos Aires (UBA), Swedish University of Agricultural Sciences, National Technological University (UTN), National Scientific and Technical Research Council (CONICET), National Institute of Agricultural Technology (INTA) (INTA–CONICET), Dairy Value Chain Research Institute (IDICAL) (INTA–CONICET), UTN, INTA, National University of the Centre of the Buenos Aires Province (UNCPBA), Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), Associated Colleges of Uberaba (FAZU), Universidade Federal do Paraná (UFPR), Santa Catarina State University (UDESC), Universidade Federal de Viçosa (UFV), São Paulo Agribusiness Technology Agency (APTA), Universidade Estadual Paulista (Unesp), Federal University of Rio Grande do Sul (UFRGS), National Institute of Agricultural Research (INIA) Treinta y Tres, Universidade Federal de Sergipe (UFS), Federal University of Southern and Southeastern Pará (UNIFESSPA), Universidade Federal de Minas Gerais (UFMG), Newton Paiva University, The Ohio State University, Science and Technology of Southern Minas Gerais, INIA Remehue, Turipaná, National Agrarian University La Molina (UNALM), Universidad Nacional de Colombia (UNAL), International Center for Tropical Agriculture (CIAT), University of Antioquia (UdeA), National Institute of Innovation and Agricultural Technology Transfer (INTA), University of Yucatan (UADY), Experimental Field Valle del Guadiana, South-Southeast Regional Unit (URUSSE), Autonomous University of the State of Mexico (UAEMex), and Environment (INRAE), AgroSup Dijon, University of the Republic of Uruguay (UdelaR), GUILHERMO FRANCKLIN DE SOUZA CONGIO, USP, ANDRÉ BANNINK, Wageningen University & Research, OLGA LUCÍA MAYORGA MOGOLLÓN, AGROSAVIA, GUSTAVO JAURENA, Universidade de Buenos Aires, HORACIO GONDA, Swedish University of Agricultural Sciences, JOSÉ IGNACIO GERE, National Technological University, Argentina / National Scientific and Technical Research Council, MARÍA ESPERANZA CERÓN-CUCCHI, National Institute of Agricultural Technology, ABIMAEL ORTIZ-CHURA, National Institute of Agricultural Technology, MARÍA PAZ TIERI, Dairy Value Chain Research Institute / National Technological University, Argentina, OLEGARIO HERNÁNDEZ, INTA, PATRICIA RICCI, National Scientific and Technical Research Council / INTA, MARÍA PAULA JULIARENA, National Scientific and Technical Research Council / National University of the Centre of the Buenos Aires Province, BANIRA LOMBARDI, National Scientific and Technical Research Council / National University of the Centre of the Buenos Aires Province, ADIBE LUIZ ABDALLA, USP, ADIBE LUIZ ABDALLA-FILHO, USP, ALEXANDRE BERNDT, CPPSE, PATRÍCIA PERONDI ANCHÃO OLIVEIRA, CPPSE, FÁBIO LUIS HENRIQUE, FAZU, ALDA LÚCIA GOMES MONTEIRO, UFPR, LUIZA ILHA BORGES, UFPR, HENRIQUE MENDONÇA NUNES RIBEIRO-FILHO, UDESC, LUIZ GUSTAVO RIBEIRO PEREIRA, CNPGL, THIERRY RIBEIRO TOMICH, CNPGL, MARIANA MAGALHÃES CAMPOS, CNPGL, FERNANDA SAMARINI MACHADO, CNPGL, MARCOS INÁCIO MARCONDES, UFV, MARIA EUGÊNIA ZERLOTTI MERCADANTE, APTA, LEANDRO SANNOMIYA SAKAMOTO, APTA, LUCIA GALVÃO ALBUQUERQUE, UNESP, PAULO CÉSAR DE FACCIO CARVALHO, UFRGS, JUSIANE ROSSETTO, UFRGS, JEAN VÍCTOR SAVIAN, UFRGS / Instituto Nacional de Pesquisa Agropecuária do Uruguai, PAULO HENRIQUE MAZZA RODRIGUES, USP, FLÁVIO PERNA JÚNIOR, USP, TAINÁ SILVESTRE MOREIRA, Universidade Estadual da Pensilvânia / USP, ROGÉRIO MARTINS MAURÍCIO, UFSJ, JOÃO PAULO PACHECO RODRIGUES, UNIFESSPA, ANA LUIZA DA COSTA CRUZ BORGES, UFMG, RICARDO REIS E SILVA, UFMG, HELENA FERREIRA LAGE, Universidade Newton Paiva, RICARDO ANDRADE REIS, UNESP, ANA CLÁUDIA RUGGIERI, UNESP, ABMAEL DA SILVA CARDOSO, UNESP, SILA CARNEIRO DA SILVA, USP, MARÍLIA BARBOSA CHIAVEGATO, Universidade Estadual de Ohio, SEBASTIÃO DE CAMPOS VALADARES-FILHO, UFV, FLÁVIA ADRIANE DE SALES SILVA, UFV, DIEGO ZANETTI, IFSULDEMINAS, TELMA TERESINHA BERCHIELLI, UNESP, JULIANA DUARTE MESSANA, UNESP, CAMILA MUÑOZ, INIA Remehue, CLAUDIA JANETH ARIZA-NIETO, AGROSAVIA, ANDREA MILENA SIERRA-ALARCÓN, AGROSAVIA, LAURA BIBIANA GUALDRÓN-DUARTE, AGROSAVIA, LORENA INÉS MESTRA-VARGAS, AGROSAVIA, ISABEL CRISTINA MOLINA-BOTERO, Universidade Nacional Agrária La Molina, ROLANDO BARAHONA-ROSALES, Universidade Nacional da Colômbia, JACOBO ARANGO, Centro Internacional de Agricultura Tropical (CIAT), XIOMARA GAVIRIA-URIBE, Universidade Nacional da Colombia / Centro Internacional de Agricultura Tropical (CIAT), LUIS ALFONSO GIRALDO VALDERRAMA, Universidade Nacional da Colombia, JAIME RICARDO ROSERO-NOGUERA, Universidade de Antioquia, SANDRA LUCÍA POSADA-OCHOA, Universidade de Antioquia, SERGIO ABARCA-MONGE, INTA, ROBERTO SOTO-BLANCO, INTA, JUAN CARLOS KU-VERA, Universidade de Yucatán, RAFAEL JIMÉNEZ-OCAMPO, Universidade de Yucatán / Instituto Nacional de Investigação Florestal, Agrícola e Pecuária (INIFAP), EVER DEL JESUS FLORES-SANTIAGO, Universidade de Yucatán / Universidade Autónoma de Chapingo, OCTAVIO ALONSO CASTELÁN-ORTEGA, Universidade Autónoma do Estado do México, MARÍA FERNANDA VÁZQUEZ-CARRILLO, Universidade Autónoma do Estado do México, MOHAMMED BENAOUDA, French National Research Institute for Agriculture, Food, and Environment (INRAE) / AgroSup Dijon, CARLOS ALFREDO GÓMEZ-BRAVO, Universidade Nacional Agrária La Molina, VÍCTOR ILICH ALVARADO BOLOVICH, Universidade Nacional Agrária La Molina, MEDARDO ANTONIO DÍAZ CÉSPEDES, Universidade Nacional Agrária La Molina, LAURA ASTIGARRAGA, Universidade da República do Uruguai, and ALEXANDER NIKOLOV HRISTOV, Universidade Estadual da Pensilvânia.

Subjects
Mitigação, Animal breeding, Animal Nutrition, Mitigation, 020209 energy, Strategy and Management, SHEPP, Efeito Estufa, Enteric methane, Context (language use), 02 engineering and technology, Beef cattle, Biology, Industrial and Manufacturing Engineering, Animal science, Ruminant, Grazing, Greenhouse gas emissions, 0202 electrical engineering, electronic engineering, information engineering, Metano entérico, Aquecimento global, Dairy cattle, 0505 law, General Environmental Science, Bovino, Sheep, Emissões de gases com efeito de estufa, Ovelha, Renewable Energy, Sustainability and the Environment, business.industry, Global warming, 05 social sciences, Building and Construction, biology.organism_classification, Diervoeding, Metano, Breed, purl.org/becyt/ford/4.2 [https], 050501 criminology, WIAS, Livestock, Cattle, business, Methane, OVINOS, purl.org/becyt/ford/4 [https]
Abstract

Latin America and Caribbean (LAC) is a developing region characterized for its importance for global food security, producing 23 and 11% of the global beef and milk production, respectively. The region's ruminant livestock sector however, is under scrutiny on environmental grounds due to its large contribution to enteric methane (CH4) emissions and influence on global climate change. Thus, the identification of effective CH4 mitigation strategies which do not compromise animal performance is urgently needed, especially in context of the Sustainable Development Goals (SDG) defined in the Paris Agreement of the United Nations. Therefore, the objectives of the current study were to: 1) collate a database of individual sheep, beef and dairy cattle records from enteric CH4 emission studies conducted in the LAC region, and 2) perform a meta-analysis to identify feasible enteric CH4 mitigation strategies, which do not compromise animal performance. After outlier's removal, 2745 animal records (65% of the original data) from 103 studies were retained (from 2011 to 2021) in the LAC database. Potential mitigation strategies were classified into three main categories (i.e., animal breeding, dietary, and rumen manipulation) and up to three subcategories, totaling 34 evaluated strategies. A random effects model weighted by inverse variance was used (Comprehensive Meta-Analysis V3.3.070). Six strategies decreased at least one enteric CH4 metric and simultaneously increased milk yield (MY; dairy cattle) or average daily gain (ADG; beef cattle and sheep). The breed composition F1 Holstein × Gyr decreased CH4 emission per MY (CH4IMilk) while increasing MY by 99%. Adequate strategies of grazing management under continuous and rotational stocking decreased CH4 emission per ADG (CH4IGain) by 22 and 35%, while increasing ADG by 22 and 71%, respectively. Increased dietary protein concentration, and increased concentrate level through cottonseed meal inclusion, decreased CH4IMilk and CH4IGain by 10 and 20% and increased MY and ADG by 12 and 31%, respectively. Lastly, increased feeding level decreased CH4IGain by 37%, while increasing ADG by 171%. The identified effective mitigation strategies can be adopted by livestock producers according to their specific needs and aid LAC countries in achieving SDG as defined in the Paris Agreement. Fil: Congio, Guilhermo Francklin de Souza. Universidade do Sao Paulo. Escola Superior de Agricultura Luiz de Queiroz; Brasil. Corporación Colombiana de Investigación Agropecuaria; Colombia Fil: Bannink, André. University of Agriculture Wageningen; Países Bajos Fil: Mayorga Mogollón, Olga Lucía. Corporación Colombiana de Investigación Agropecuaria; Colombia Fil: Jaurena, Gustavo. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Animal. Cátedra de Nutrición Animal; Argentina Fil: Gonda, Horacio Leandro. Uppsala Universitet; Suecia Fil: Gere, José Ignacio. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Patobiología Veterinaria - Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Patobiología Veterinaria; Argentina Fil: Cerón Cucchi, María Esperanza. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Patobiología; Argentina Fil: Ortiz Chura, Abimael. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Patobiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Tieri, María Paz. Universidad Tecnológica Nacional. Facultad Regional Rafaela; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación de la Cadena Láctea. - Instituto Nacional de Tecnología Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria Rafaela. Instituto de Investigación de la Cadena Láctea; Argentina Fil: Hernandez, Olegario. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Tucuman-Santiago del Estero; Argentina Fil: Ricci, Patricia. Instituto Nacional de Tecnologia Agropecuaria. Centro Regional Buenos Aires Sur. Estacion Experimental Agropecuaria Balcarce. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible. Grupo Vinculado Estacion Experimental Agropecuaria Cuenca del Salado Al Ipads | Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Mar del Plata. Instituto de Innovación Para la Producción Agropecuaria y El Desarrollo Sostenible. Grupo Vinculado Estacion Experimental Agropecuaria Cuenca del Salado Al Ipads.; Argentina Fil: Juliarena, María Paula. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentina Fil: Lombardi, Banira. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. - Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; Argentina Fil: Abdalla, Adibe Luiz. Universidade de Sao Paulo; Brasil Fil: Abdalla Filho, Adibe Luiz. Universidade de Sao Paulo; Brasil Fil: Berndt, Alexandre. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Oliveira, Patrícia Perondi Anchão. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Henrique, Fábio Luis. Colegios Asociados de Uberaba; Brasil Fil: Monteiro, Alda Lúcia Gomes. Universidade Federal do Paraná; Brasil Fil: Borges, Luiza Ilha. Universidade Federal do Paraná; Brasil Fil: Ribeiro Filho, Henrique Mendonça Nunes. Universidade Federal de Santa Catarina; Brasil Fil: Ribeiro Pereira, Luiz Gustavo. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Tomich, Thierry Ribeiro. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Campos, Mariana Magalhães. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Machado, Fernanda Samarini. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Marcondes, Marcos Inácio. Universidade Federal de Viçosa.; Brasil Fil: Mercadante, Maria Eugênia Zerlotti. Agencia de Tecnología Agroindustrial de Sao Paulo; Argentina Fil: Sakamoto, Leandro Sannomiya. Agencia de Tecnología Agroindustrial de Sao Paulo; Argentina Fil: Albuquerque, Lucia Galvão. Universidade Estadual Paulista Julio de Mesquita Filho; Brasil Fil: Carvalho, Paulo César de Faccio. Universidade Federal do Rio Grande do Sul; Brasil Fil: Hristov, Alexander Nikolov. State University of Pennsylvania; Estados Unidos. University of Agriculture Wageningen; Países Bajos. Universidade de Sao Paulo; Brasil. Corporación Colombiana de Investigación Agropecuaria; Colombia

Published
2021

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