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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
11/05/2021 |
Actualizado : |
11/05/2021 |
Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
Autor : |
BERRUETA, C.; GIMÉNEZ, G.; DOGLIOTTI, S. |
Afiliación : |
MARIA CECILIA BERRUETA MOREIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GUSTAVO GIMÉNEZ FRANQUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SANTIAGO DOGLIOTTI, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay. |
Título : |
Scaling up from crop to farm level: Co-innovation framework to improve vegetable farm systems sustainability. [Webinar presentation]. |
Complemento del título : |
Webinar 3-24 March 2021. Chaired by Hatem Belhouchette (CIHEAM Montpellier, France) and PytrikReidsma (Wageningen University and Research, The Netherlands).
Multi-scale and multicriteriatrade-off analysis in the SDG1-SDG2 nexus, to co-design sustainable and healthy agri-food systems and to inform policies. |
Fecha de publicación : |
2021 |
Fuente / Imprenta : |
In: International Symposium for Farming Systems Design, 7th (FSD7), "Designing Climate Smart Agricultural Systems for a Sustainable Transition in the Agri-food Systems of the Dry Areas", International Course, Webinars March 22-25, 2021. |
Idioma : |
Inglés |
Contenido : |
ABSTRACT. - Understanding and ranking main causes of yield variability among farmers, is essential to provide feedback to farmers and extension agents to reduce yield gaps. |
Palabras claves : |
Crop management; Family farms; Farm system. |
Asunto categoría : |
F01 Cultivo |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/15604/1/FSD7-webinar-presentation-Berrueta-Gimenez-Dogliotti-2021.pdf
https://cloud.iamm.fr/index.php/s/frBRzgMMdmQjPQc
https://fsd7.sciencesconf.org/resource/page/id/26
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Marc : |
LEADER 00913nam a2200169 a 4500 001 1062076 005 2021-05-11 008 2021 bl uuuu u00u1 u #d 100 1 $aBERRUETA, C. 245 $aScaling up from crop to farm level$bCo-innovation framework to improve vegetable farm systems sustainability. [Webinar presentation].$h[electronic resource] 260 $aIn: International Symposium for Farming Systems Design, 7th (FSD7), "Designing Climate Smart Agricultural Systems for a Sustainable Transition in the Agri-food Systems of the Dry Areas", International Course, Webinars March 22-25$c2021 520 $aABSTRACT. - Understanding and ranking main causes of yield variability among farmers, is essential to provide feedback to farmers and extension agents to reduce yield gaps. 653 $aCrop management 653 $aFamily farms 653 $aFarm system 700 1 $aGIMÉNEZ, G. 700 1 $aDOGLIOTTI, S.
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INIA Las Brujas (LB) |
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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha actual : |
31/07/2018 |
Actualizado : |
11/10/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
DOSTER, E.; ROVIRA, P.J.; NOYES, N.R.; BURGESS, B. A.; YANG, X.; WEINROTH, M.D.; LAKIN, S.M.; DEAN, C.J.; LINKE, L.; MAGNUSON, R.; JONES, K.I.; BOUCHER, C.; RUIZ, J.; BELK, K.E.; MORLEY, P.S. |
Afiliación : |
ENRIQUE DOSTER, Microbial Ecology Group, Colorado State University, USA. Department of Microbiology, Inmunology and Pathology, Colorado State University. USA.; PABLO JUAN ROVIRA SANZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. Microbial Ecology Group, Colorado State University. Department of Microbiology, Imnunology and Pathology, Colorado State University, USA.; NOELLE R. NOYES., Microbial Ecology Group, Colorado State University. Department of Veterinary Population Medicine, University of Minnesota.; BRANDY A. BURGESS, Department of Population Health, University of Georgia, USA.; XIANG YANG, Microbial Ecology Group, Colorado State University. Department of Animal Sciences, Colorado State University, USA.; MARGARET D. WEINROTH, Microbial Ecology Group, Colorado State University. Department of Animal Sciences, Colorado State University, USA.; STEVEN M. LAKIN, Microbial Ecology Group, Colorado State University. Department of Microbiology, Immunology and Pathology, Colorado State University, USA.; CHRISTOPHER J. DEAN, Microbial Ecology Group, Colorado State University. Department of Microbiology, Immunology and Pathology, Colorado State University, USA.; LYNDSEY LINKE, Department of Clinical Sciences, Colorado State University, USA.; ROBERTA MAGNUSON, Department of Clinical Sciences, Colorado State University, USA.; KENNETH I. JONES, Department of Biochemistry and Molecular Genetics, University of Colorado, USA.; CHRISTINA BOUCHER, Department of Computer and Information Science and Engineering, University of Florida, USA.; JAMIE RUIZ, Department of Computer and Information Science and Engineering, University of Florida, USA.; KEITH E. BELK, Microbial Ecology Group, Colorado State University. Department of Microbiology, Imnunology and Pathology, Colorado State University, USA.; PAUL S. MORLEY, Microbial Ecology Group, Colorado State University, USA. Department of Microbiology, Inmunology and Pathology, Colorado State University. USA. |
Título : |
Investigating effects of tulathromycin metaphylaxis on the fecal resistome and microbiome of commercial feedlot cattle early in the feeding period. |
Fecha de publicación : |
2018 |
Fuente / Imprenta : |
Frontier in Microbiology, 2018, 9:1715. |
Páginas : |
14 p. |
DOI : |
10.3389/fmicb.2018.01715 |
Idioma : |
Inglés |
Notas : |
Article history: Received: 14 April 2018; Accepted: 09 July 2018; Published: 30 July 2018.
Open Access journal.
https://doi.org/10.3389/fmicb.2018.01715 |
Contenido : |
The objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot?and associated changes in diet, geography, conspecific exposure, and environment?may exert a greater influence over the fecal resistome and microbiome of feedlot cattle than common metaphylactic antimicrobial drug treatment. MenosThe objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot?and associated changes in diet, geography... Presentar Todo |
Palabras claves : |
METAGENOMICS; METAPHYLAXIS; MICROBIOME; RESISTOME; TULATHROMYCIN. |
Thesagro : |
BOVINOS; FEEDLOT. |
Asunto categoría : |
L73 Enfermedades de los animales |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/10933/1/fmicb-09-01715.pdf
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Marc : |
LEADER 02931naa a2200409 a 4500 001 1058855 005 2019-10-11 008 2018 bl uuuu u00u1 u #d 024 7 $a10.3389/fmicb.2018.01715$2DOI 100 1 $aDOSTER, E. 245 $aInvestigating effects of tulathromycin metaphylaxis on the fecal resistome and microbiome of commercial feedlot cattle early in the feeding period.$h[electronic resource] 260 $c2018 300 $a14 p. 500 $aArticle history: Received: 14 April 2018; Accepted: 09 July 2018; Published: 30 July 2018. Open Access journal. https://doi.org/10.3389/fmicb.2018.01715 520 $aThe objective was to examine effects of treating commercial beef feedlot cattle with therapeutic doses of tulathromycin, a macrolide antimicrobial drug, on changes in the fecal resistome and microbiome using shotgun metagenomic sequencing. Two pens of cattle were used, with all cattle in one pen receiving metaphylaxis treatment (800 mg subcutaneous tulathromycin) at arrival to the feedlot, and all cattle in the other pen remaining unexposed to parenteral antibiotics throughout the study period. Fecal samples were collected from 15 selected cattle in each group just prior to treatment (Day 1), and again 11 days later (Day 11). Shotgun sequencing was performed on isolated metagenomic DNA, and reads were aligned to a resistance and a taxonomic database to identify alignments to antimicrobial resistance (AMR) gene accessions and microbiome content. Overall, we identified AMR genes accessions encompassing 9 classes of AMR drugs and encoding 24 unique AMR mechanisms. Statistical analysis was used to identify differences in the resistome and microbiome between the untreated and treated groups at both timepoints, as well as over time. Based on composition and ordination analyses, the resistome and microbiome were not significantly different between the two groups on Day 1 or on Day 11. However, both the resistome and microbiome changed significantly between these two sampling dates. These results indicate that the transition into the feedlot?and associated changes in diet, geography, conspecific exposure, and environment?may exert a greater influence over the fecal resistome and microbiome of feedlot cattle than common metaphylactic antimicrobial drug treatment. 650 $aBOVINOS 650 $aFEEDLOT 653 $aMETAGENOMICS 653 $aMETAPHYLAXIS 653 $aMICROBIOME 653 $aRESISTOME 653 $aTULATHROMYCIN 700 1 $aROVIRA, P.J. 700 1 $aNOYES, N.R. 700 1 $aBURGESS, B. A. 700 1 $aYANG, X. 700 1 $aWEINROTH, M.D. 700 1 $aLAKIN, S.M. 700 1 $aDEAN, C.J. 700 1 $aLINKE, L. 700 1 $aMAGNUSON, R. 700 1 $aJONES, K.I. 700 1 $aBOUCHER, C. 700 1 $aRUIZ, J. 700 1 $aBELK, K.E. 700 1 $aMORLEY, P.S. 773 $tFrontier in Microbiology, 2018, 9:1715.
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