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| 61. |  | DALLA RIZZA, M.; SCHVARTZMAN, C.; MURCHIO, S.; BERRUETA, C.; BOSCHI, F.; LENZI, A.; GIMÉNEZ, G. Field performance of resistant potato genotypes transformed with the EFR receptor from Arabidopsis thaliana in the absence of bacterial wilt (Ralstonia solanacearum). Research article. The Plant Pathology Journal, 2022, vol.38 (3): 239-247. OPEN ACCESS. doi: https://doi.org/10.5423/PPJ.OA.01.2022.0008 Article history: Received 20 January 2022; Revised 9 May 2022; Accepted 10 May 2022. -- Corresponding author: Marco Dalla-Rizza, Email: mdallarizza@inia.org.uy -- Marco Dalla-Rizza and Claudia Schvartzman contributed equally to this...| Biblioteca(s): INIA Las Brujas. |
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| 62. | | SCARLATO, M.; DOGLIOTTI, S.; BERRUETA, C.; BARROS, C.; REHERMAN, F.; BORGES, A.; GARCÍA, M.; GIMÉNEZ, G. Explaining yield variability between farmers as a first step to reduce gaps. T3. Crop modeling and yield gap analysis for agricultural systems analysis and design. In: Proceedings of the 5th international symposium for farming systems design. Multi-functional farming systems in a changing world. Montpellier (Francia): European Society of Agronomy, 2015. p. 119-122 Acknowledgements. Without the help of all the farmers that gently contributed their time and fields, and the help of the technical advisers and experts
to select a representative sample of farms, this research would have not be possible,...| Biblioteca(s): INIA Las Brujas. |
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| 64. | | BERRUETA, C.; GRASSO, R.; GARCIA, C.; THOMPSON, R.B.; GALLARDO, M. Use of the VegSyst model to simulate seasonal dry matter production, N and K uptake and evapotranspiration in greenhouse soil-grown tomato in Uruguay. Agricultural Water Management. 1 August 2023, Volume 286, 108395. https://doi.org/10.1016/j.agwat.2023.108395 -- OPEN ACCESS. Article history: Received 30 January 2023, Revised 29 May 2023, Accepted 30 May 2023, Available online 9 June 2023, Version of Record 9 June 2023. -- Handling Editor Dr. B.E. Clothier -- Funding: This work was supported by Instituto...| Biblioteca(s): INIA Las Brujas. |
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| 66. | | DOGLIOTTI, S.; SCARLATO, M.; BERRUETA, C.; BARROS, C.; REHERMANN, F.; RIEPPI, M.; INETTI, C.; SOUST, G.; BORGES, A. Análisis y jerarquización de factores determinantes de las brechas de rendimiento y calidad en los principales cultivos hortícolas del Uruguay. Montevideo (UY): INIA, 2021. 81 p. (Serie FPTA-INIA; 91). Proyecto FPTA 288: "Análisis y jerarquización de factores determinantes de las brechas de rendimiento y calidad en los principales cultivos hortícolas del Uruguay." Período de ejecución: Marzo 2014 - Octubre 2017. Institución Ejecutora:...| Biblioteca(s): INIA Las Brujas. |
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| 67. | | BERRUETA, C.; BORGES, A.; GIMÉNEZ, G.; SENTANARO, G.; LAMMERS, M.; REHERMANN, F.; SOUST, G.; RIEPPI, M.; DOGLIOTTI, S. La producción de tomate bajo invernadero en el sur de Uruguay: caminos para reducir las brechas de rendimiento. Hortifruticultura. Revista INIA Uruguay, 2019, no. 58, p. 31-36. (Revista INIA; 58).| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 67 | |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
04/09/2019 |
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Actualizado : |
16/03/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
-- - -- |
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Autor : |
ROVIRA, P.J.; MCALLISTER, T.; LAKIN, S.M.; COOK, S.R.; DOSTER, E.; NOYES, N. R.; WEINROTH, M.D.; YANG, X.; PARKER, J. K.; BOUCHER, C.; BOOKER, C. W.; WOENER, D. R.; BELK, K. E.; MORLEY, P. S. |
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Afiliación : |
PABLO JUAN ROVIRA SANZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, USA.; TIM MCALLISTER, Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada.; STEVEN M. LAKIN, Department of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, USA.; SHAUN R. COOK, Alberta Agricultural and forestry, Lethbridge, Canada.; ENRIQUE DOSTER, Department of Microbiology, Immunology and Pathology, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, USA.; NOELLE R. NOYES, Veterinary Population Medicine Department, University of Minnesota, USA.; MAGGIE D. WEINROTH, Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, USA.; XIANG YANG, Department of Animal Science, University of California, Davis, USA.; JENNIFER K. PARKER, Deparment of Molecular Biosciences, University of Florida, Gainesville, FL, USA.; CHRISTINA BOUCHER, Deparment of Computer and Information Science and Engineering, University of Florida, Gainessville, FL, USA.; CALVIN W. BOOKER, Feedlot Health Management Services, Okotoks, AB, Canada.; DALE R. WOEMER, Deparment of Animal and Food Sciences, College of Agricultural Sciences & Natural Resources, Texas University, TX, USA.; KEITH E. BELK, Department of Animal Sciences, College of Agricultural Sciences, Colorado State University, USA.; PAUL S. MORLEY, VERO, Veterinary Education, Research , and Outreach Program, Texas A&M University and West Texas A&M University, Canyon, TX, USA. |
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Título : |
Characterization of the microbial resistome in conventional and "raised without antibiotics" beef and dairy production systems. |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
Frontier in Microbiology, September 2019. v. 10, article 1980, 11 p. OPEN ACCESS. |
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DOI : |
10.3389/fmicb.2019.01980 |
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Idioma : |
Inglés |
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Notas : |
Received 18 March 2019 // Accepted 12 August 2019 // Published 4 September 2019. |
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Contenido : |
Metagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the b-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle source, management practices, diet, horizontal ARGs transfer, and co-selection of resistance), in addition to antimicrobial use, could have impacted resistome profiles. For that reason, we could not establish a cause-effect relationship between antimicrobial use and AMR, although ARGs in feces and effluents were associated with drug classes used to treat animals according to farms' records (tetracyclines and macrolides in feedlots, b-lactams in dairies), whereas ARGs in soil were dominated by multidrug resistance.
Characterization of the "resistance potential" of animal-derived and environmental samples is the first step toward incorporating metagenomic approaches into AMR surveillance in agricultural systems. Further research is needed to assess the publichealth risk associated with different microbial resistomes. MenosMetagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the b-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle sour... Presentar Todo |
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Palabras claves : |
ANTIBIOTIC RESISTANCE; CATTLE; CATTLE BEEF; DAIRY CATTLE; METAGENOMICA; METAGENOMICS; MICROBIOMA; MICROBIOME; RESISTENCIA A ANTIBIÓTICOS; RESISTOME. |
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Thesagro : |
BOVINOS; BOVINOS DE CARNE; GANADO LECHERO. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/13237/1/Rovira-Front-microb-2019.pdf
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Marc : |
LEADER 03681naa a2200457 a 4500
001 1060137
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008 2019 bl uuuu u00u1 u #d
024 7 $a10.3389/fmicb.2019.01980$2DOI
100 1 $aROVIRA, P.J.
245 $aCharacterization of the microbial resistome in conventional and "raised without antibiotics" beef and dairy production systems.$h[electronic resource]
260 $c2019
500 $aReceived 18 March 2019 // Accepted 12 August 2019 // Published 4 September 2019.
520 $aMetagenomic investigations have the potential to provide unprecedented insights into microbial ecologies, such as those relating to antimicrobial resistance (AMR). We characterized the microbial resistome in livestock operations raising cattle conventionally (CONV) or without antibiotic exposures (RWA) using shotgun metagenomics. Samples of feces, wastewater from catchment basins, and soil where wastewater was applied were collected from CONV and RWA feedlot and dairy farms. After DNA extraction and sequencing, shotgun metagenomic reads were aligned to reference databases for identification of bacteria (Kraken) and antibiotic resistance genes (ARGs) accessions (MEGARes). Differences in microbial resistomes were found across farms with different production practices (CONV vs. RWA), types of cattle (beef vs. dairy), and types of sample (feces vs. wastewater vs. soil). Feces had the greatest number of ARGs per sample (mean = 118 and 79 in CONV and RWA, respectively), with tetracycline efflux pumps, macrolide phosphotransferases, and aminoglycoside nucleotidyltransferases mechanisms of resistance more abundant in CONV than in RWA feces. Tetracycline and macrolide-lincosamide-streptogramin classes of resistance were more abundant in feedlot cattle than in dairy cow feces, whereas the b-lactam class was more abundant in dairy cow feces. Lack of congruence between ARGs and microbial communities (procrustes analysis) suggested that other factors (e.g., location of farms, cattle source, management practices, diet, horizontal ARGs transfer, and co-selection of resistance), in addition to antimicrobial use, could have impacted resistome profiles. For that reason, we could not establish a cause-effect relationship between antimicrobial use and AMR, although ARGs in feces and effluents were associated with drug classes used to treat animals according to farms' records (tetracyclines and macrolides in feedlots, b-lactams in dairies), whereas ARGs in soil were dominated by multidrug resistance. Characterization of the "resistance potential" of animal-derived and environmental samples is the first step toward incorporating metagenomic approaches into AMR surveillance in agricultural systems. Further research is needed to assess the publichealth risk associated with different microbial resistomes.
650 $aBOVINOS
650 $aBOVINOS DE CARNE
650 $aGANADO LECHERO
653 $aANTIBIOTIC RESISTANCE
653 $aCATTLE
653 $aCATTLE BEEF
653 $aDAIRY CATTLE
653 $aMETAGENOMICA
653 $aMETAGENOMICS
653 $aMICROBIOMA
653 $aMICROBIOME
653 $aRESISTENCIA A ANTIBIÓTICOS
653 $aRESISTOME
700 1 $aMCALLISTER, T.
700 1 $aLAKIN, S.M.
700 1 $aCOOK, S.R.
700 1 $aDOSTER, E.
700 1 $aNOYES, N. R.
700 1 $aWEINROTH, M.D.
700 1 $aYANG, X.
700 1 $aPARKER, J. K.
700 1 $aBOUCHER, C.
700 1 $aBOOKER, C. W.
700 1 $aWOENER, D. R.
700 1 $aBELK, K. E.
700 1 $aMORLEY, P. S.
773 $tFrontier in Microbiology, September 2019.$gv. 10, article 1980, 11 p. OPEN ACCESS.
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