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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha : |
17/04/2017 |
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Actualizado : |
11/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
LAKIN, S.M.; DEAN, C.; NOYES, N.R.; DETTENWANGER, A.; ROSS, A. S.; DOSTER, E.; ROVIRA, P.J.; ABDO, Z.; JONES, K.L.; RUIZ, J.; BELK, K.E.; MORLEY, P.S.; BOUCHER, C. |
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Afiliación : |
STEVEN M. LAKIN; CHRIS DEAN; NOELLE R. NOYES; ADAM DETTENWANGER; ANNE SPENCER ROSS; ENRIQUE DOSTER; PABLO JUAN ROVIRA SANZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. Department of Animal Sciences, Colorado State University, USA.; ZAID ABDO; KENNETH L. JONES; JAIME RUIZ; KEITH E. BELK; PAUL S. MORLEY; CHRISTINA BOUCHER. |
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Título : |
MEGARes: an antimicrobial resistance database for high throughput sequencing. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Nucleic Acids Research, 2017 v.45 p.574-580. |
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DOI : |
10.1093/nar/gkw1009 |
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Idioma : |
Inglés |
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Notas : |
Article History: Published online 2016 Nov 24.
DOI: https://doi.org/10.1093/nar/gkw1009 |
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Contenido : |
Antimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database. |
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Palabras claves : |
BASE DE DATOS; BIOINFORMÁTICA; DATASETS; DRUG RESISTANCE; GENES; METAGENÓMICA; METAGENOMICS; MICROBIAL; POLYMERASE CHAIN REACTION; PUBLIC HEALTH MEDICINE; RESISTENCIA ANTIMICROBIANA; SEQUENCE ANALYSIS. |
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Asunto categoría : |
L01 Ganadería |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/6677/1/Rovira-arb-2017-1.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210519/
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Marc : |
LEADER 02505naa a2200433 a 4500
001 1057051
005 2019-10-11
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1093/nar/gkw1009$2DOI
100 1 $aLAKIN, S.M.
245 $aMEGARes$ban antimicrobial resistance database for high throughput sequencing.$h[electronic resource]
260 $c2017
500 $aArticle History: Published online 2016 Nov 24. DOI: https://doi.org/10.1093/nar/gkw1009
520 $aAntimicrobial resistance has become an imminent concern for public health. As methods for detection and characterization of antimicrobial resistance move from targeted culture and polymerase chain reaction to high throughput metagenomics, appropriate resources for the analysis of large-scale data are required. Currently, antimicrobial resistance databases are tailored to smaller-scale, functional profiling of genes using highly descriptive annotations. Such characteristics do not facilitate the analysis of large-scale, ecological sequence datasets such as those produced with the use of metagenomics for surveillance. In order to overcome these limitations, we present MEGARes (https://megares.meglab.org), a hand-curated antimicrobial resistance database and annotation structure that provides a foundation for the development of high throughput acyclical classifiers and hierarchical statistical analysis of big data. MEGARes can be browsed as a stand-alone resource through the website or can be easily integrated into sequence analysis pipelines through download. Also via the website, we provide documentation for AmrPlusPlus, a user-friendly Galaxy pipeline for the analysis of high throughput sequencing data that is pre-packaged for use with the MEGARes database.
653 $aBASE DE DATOS
653 $aBIOINFORMÁTICA
653 $aDATASETS
653 $aDRUG RESISTANCE
653 $aGENES
653 $aMETAGENÓMICA
653 $aMETAGENOMICS
653 $aMICROBIAL
653 $aPOLYMERASE CHAIN REACTION
653 $aPUBLIC HEALTH MEDICINE
653 $aRESISTENCIA ANTIMICROBIANA
653 $aSEQUENCE ANALYSIS
700 1 $aDEAN, C.
700 1 $aNOYES, N.R.
700 1 $aDETTENWANGER, A.
700 1 $aROSS, A. S.
700 1 $aDOSTER, E.
700 1 $aROVIRA, P.J.
700 1 $aABDO, Z.
700 1 $aJONES, K.L.
700 1 $aRUIZ, J.
700 1 $aBELK, K.E.
700 1 $aMORLEY, P.S.
700 1 $aBOUCHER, C.
773 $tNucleic Acids Research, 2017$gv.45 p.574-580.
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Registro original : |
INIA Treinta y Tres (TT) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
13/06/2023 |
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Actualizado : |
13/06/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
BERRUETA, C.; GRASSO, R.; GARCIA, C.; THOMPSON, R.B.; GALLARDO, M. |
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Afiliación : |
MARIA CECILIA BERRUETA MOREIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RAFAEL GILLSON GRASSO RODRIGUEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CLAUDIO CESAR GARCIA GALLARRETA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RODNEY B. THOMPSON, Departamento de Agronomía, Universidad de Almería, Carretera del Sacramento s/n (04745), La Cañada de San Urbano, Almería, Spain; MARISA GALLARDO, Departamento de Agronomía, Universidad de Almería, Carretera del Sacramento s/n (04745), La Cañada de San Urbano, Almería, Spain. |
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Título : |
Use of the VegSyst model to simulate seasonal dry matter production, N and K uptake and evapotranspiration in greenhouse soil-grown tomato in Uruguay. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Agricultural Water Management. 1 August 2023, Volume 286, 108395. https://doi.org/10.1016/j.agwat.2023.108395 -- OPEN ACCESS. |
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ISSN : |
1873-2283 (online). |
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DOI : |
10.1016/j.agwat.2023.108395 |
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Idioma : |
Inglés |
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Notas : |
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 Nacional de Investigación Agropecuaria (INIA) from Uruguay. -- Corresponding author: Cecilia Berrueta, email: cberrueta@inia.org.uy -- License: Under a Creative Commons license (http://creativecommons.org/licenses/by-nc-nd/4.0/ ) |
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Contenido : |
ABSTRACT.- The VegSyst model, initially developed for nitrogen (N) and irrigation recommendations for greenhouse-grown vegetable crops in southeastern Spain, was calibrated and validated for greenhouse tomato cultivated in soil in Uruguay (South America) for autumn and spring growing seasons. Additionally, the performance of the recalibrated VegSyst model was compared to the calibration for tomato grown in Almeria greenhouses of VegSyst model V3. Five tomato crops, three autumn and two spring crops grown in 2019, 2020 and 2021, were used for model calibration (Spring-19 and Autumn-20) and validation (Autumn-19, Spring-21 and Autumn-21). A major
change to the existing VegSyst model (V3) was the incorporation of the Hargreaves-Samani equation adapted to plastic greenhouses to estimate ETo. The recalibrated VegSyst model accurately simulated dry matter production (DMP), ETc, and crop N and K uptake over time for autumn and spring growing seasons. Using the original
VegSyst V3 calibration, acceptable results were obtained for DMP and N uptake. © 2023 The Authors. Published by Elsevier B.V. |
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Palabras claves : |
ETc; Fertigation; Modeling; Nutrient uptake; Solanum lycopersicum. |
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Asunto categoría : |
F01 Cultivo |
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URL : |
https://www.sciencedirect.com/science/article/pii/S0378377423002603/pdf
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Marc : |
LEADER 02446naa a2200265 a 4500
001 1064189
005 2023-06-13
008 2023 bl uuuu u00u1 u #d
022 $a1873-2283 (online).
024 7 $a10.1016/j.agwat.2023.108395$2DOI
100 1 $aBERRUETA, C.
245 $aUse of the VegSyst model to simulate seasonal dry matter production, N and K uptake and evapotranspiration in greenhouse soil-grown tomato in Uruguay.$h[electronic resource]
260 $c2023
500 $aArticle 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 Nacional de Investigación Agropecuaria (INIA) from Uruguay. -- Corresponding author: Cecilia Berrueta, email: cberrueta@inia.org.uy -- License: Under a Creative Commons license (http://creativecommons.org/licenses/by-nc-nd/4.0/ )
520 $aABSTRACT.- The VegSyst model, initially developed for nitrogen (N) and irrigation recommendations for greenhouse-grown vegetable crops in southeastern Spain, was calibrated and validated for greenhouse tomato cultivated in soil in Uruguay (South America) for autumn and spring growing seasons. Additionally, the performance of the recalibrated VegSyst model was compared to the calibration for tomato grown in Almeria greenhouses of VegSyst model V3. Five tomato crops, three autumn and two spring crops grown in 2019, 2020 and 2021, were used for model calibration (Spring-19 and Autumn-20) and validation (Autumn-19, Spring-21 and Autumn-21). A major change to the existing VegSyst model (V3) was the incorporation of the Hargreaves-Samani equation adapted to plastic greenhouses to estimate ETo. The recalibrated VegSyst model accurately simulated dry matter production (DMP), ETc, and crop N and K uptake over time for autumn and spring growing seasons. Using the original VegSyst V3 calibration, acceptable results were obtained for DMP and N uptake. © 2023 The Authors. Published by Elsevier B.V.
653 $aETc
653 $aFertigation
653 $aModeling
653 $aNutrient uptake
653 $aSolanum lycopersicum
700 1 $aGRASSO, R.
700 1 $aGARCIA, C.
700 1 $aTHOMPSON, R.B.
700 1 $aGALLARDO, M.
773 $tAgricultural Water Management. 1 August 2023, Volume 286, 108395. https://doi.org/10.1016/j.agwat.2023.108395 -- OPEN ACCESS.
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