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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha : |
07/06/2022 |
Actualizado : |
10/06/2022 |
Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
Autor : |
BUENO, M.; ROEL, A.; OXLEY, A. M. |
Afiliación : |
MARCOS VALLE BUENO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALVARO ROEL DELLAZOPPA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALBERTO MATIAS OXLEY BARRIOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Geonivelación con pendiente variable: principales resultados de dos zafras. |
Fecha de publicación : |
2022 |
Fuente / Imprenta : |
In: Terra, J. A.; Martínez, S.; Saravia, H.; Mesones, B. (Eds.) Arroz 2021. Montevideo (UY): INIA, 2022. p. 13-16. |
Serie : |
(INIA Serie Técnica; 262) |
ISSN : |
1688-9266 |
Idioma : |
Español |
Palabras claves : |
ARROZ; DRENAJE; RIEGO; SISTEMATIZACIÓN; SOJA. |
Asunto categoría : |
F01 Cultivo |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16472/1/st-262-p13-16.pdf
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Marc : |
LEADER 00662naa a2200217 a 4500 001 1063219 005 2022-06-10 008 2022 bl uuuu u00u1 u #d 022 $a1688-9266 100 1 $aBUENO, M. 245 $aGeonivelación con pendiente variable$bprincipales resultados de dos zafras.$h[electronic resource] 260 $c2022 490 $a(INIA Serie Técnica; 262) 653 $aARROZ 653 $aDRENAJE 653 $aRIEGO 653 $aSISTEMATIZACIÓN 653 $aSOJA 700 1 $aROEL, A. 700 1 $aOXLEY, A. M. 773 $tIn: Terra, J. A.; Martínez, S.; Saravia, H.; Mesones, B. (Eds.) Arroz 2021. Montevideo (UY): INIA, 2022. p. 13-16.
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INIA Treinta y Tres (TT) |
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
15/03/2022 |
Actualizado : |
15/03/2022 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
SIMONDI, S.; CASARETTO, E.; QUERO, S.; CERETTA, S.; BONNECARRERE, V.; BORSANI, O. |
Afiliación : |
SEBASTIÁN SIMONDI, Área de Matemática, Facultad de Ciencias Exactas y Naturales, Universidad Nacional de Cuyo (FCEN-UNCuyo), Padre Contreras 1300, Mendoza M5502JMA, Argentina; ESTEBAN CASARETTO, Departamento de Biología Vegetal, Facultad de Agronomía, Universidad de la República, Garzón 809, Montevideo 12900, Uruguay; SEBASTIÁN QUERO, Departamento de Biología Vegetal, Facultad de Agronomía, Universidad de la República, Garzón 809, Montevideo 12900, Uruguay; SERGIO EDUARDO CERETTA SORIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA VICTORIA BONNECARRERE MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OMAR BORSANI, Departamento de Biología Vegetal, Facultad de Agronomía, Universidad de la República, Garzón 809, Montevideo 12900, Uruguay. |
Título : |
A simple and accurate method based on a water-consumption model for phenotyping soybean genotypes under hydric deficit conditions. |
Fecha de publicación : |
2022 |
Fuente / Imprenta : |
Agronomy, 2022, Volume 12, Issue 3, Article number 575. GOLD OPEN ACCESS. doi: https://doi.org/10.3390/agronomy12030575 |
ISSN : |
2073-4395 |
DOI : |
10.3390/agronomy12030575 |
Idioma : |
Inglés |
Notas : |
Article history: Received 14 December 2021; Revised 17 February 2022; Accepted 24 February 2022; Published 25 February 2022.
Corresponding author: Borsani, O.; Departamento de Biología Vegetal, Facultad de Agronomía, Universidad de la República, Garzón 809, Montevideo, Uruguay; email:oborsani@fagro.edu.uy -- This article belongs to the Special Issue Plant Responses to Stress and Environmental Stimulus: https://www.mdpi.com/journal/agronomy/special_issues/environmental_stimulus -- Supplementary Material:
https://www.mdpi.com/2073-4395/12/3/575/s1 -- This research was funded by the following projects: CSIC-UdelaR Grupo 418 Estrés abiótico en plantas; Innovagro FSA_1_2013_1_12924, funded by Agencia Nacional de Investigación e Innovación; and Red Nacional de Biotecnología Agrícola, RTS_1_2014_1, funded by Agencia Nacional de Investigación e Innovación, Instituto Nacional de Investigación Agropecuaria, Barraca Erro S.A., Lebu SRL, Fadisol SA, CALMER and COPAGRAN. |
Contenido : |
ABSTRACT. - Drought limits crop productivity and reduces yield stability. Drought tolerance as a selection criterion in breeding programs requires the development of high-throughput, precise, and low-cost phenotyping strategies. We developed a mathematical model, based on biological approaches, for evaluating soybean plants? response to drought under controlled growth conditions. The model describes the kinetics of water consumption of a plant pot substrate system (PPS) with low sampling requirements. The model generated two parameters, t0.5 (time necessary for the PPS to reach half of the maximum amount of evapotranspirable water) and Gw(t0.5 ) (stomatal conductance [Gw] at t0.5 ), which determined the water-consumption curve of each genotype. An analysis of the kinetics of water consumption in response to a progressive water deficit in a biparental and breeding population was performed as a preliminary test of the model. A correspondence analysis between the t0.5 and Gw(t0.5 ) parameters with the genetic structure of the populations shows a genetic association. The phenotyping methodology presented in this work and drought susceptibility in field conditions are discussed based on previous results. This work could be useful for improving the selection of soybean genotypes in relation to their performance under drought conditions. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. |
Palabras claves : |
Crop breeding; Drought; Mathematical modeling; Stomatal conductance. |
Asunto categoría : |
F01 Cultivo |
URL : |
https://www.mdpi.com/2073-4395/12/3/575/pdf
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Marc : |
LEADER 03260naa a2200265 a 4500 001 1062834 005 2022-03-15 008 2022 bl uuuu u00u1 u #d 022 $a2073-4395 024 7 $a10.3390/agronomy12030575$2DOI 100 1 $aSIMONDI, S. 245 $aA simple and accurate method based on a water-consumption model for phenotyping soybean genotypes under hydric deficit conditions.$h[electronic resource] 260 $c2022 500 $aArticle history: Received 14 December 2021; Revised 17 February 2022; Accepted 24 February 2022; Published 25 February 2022. Corresponding author: Borsani, O.; Departamento de Biología Vegetal, Facultad de Agronomía, Universidad de la República, Garzón 809, Montevideo, Uruguay; email:oborsani@fagro.edu.uy -- This article belongs to the Special Issue Plant Responses to Stress and Environmental Stimulus: https://www.mdpi.com/journal/agronomy/special_issues/environmental_stimulus -- Supplementary Material: https://www.mdpi.com/2073-4395/12/3/575/s1 -- This research was funded by the following projects: CSIC-UdelaR Grupo 418 Estrés abiótico en plantas; Innovagro FSA_1_2013_1_12924, funded by Agencia Nacional de Investigación e Innovación; and Red Nacional de Biotecnología Agrícola, RTS_1_2014_1, funded by Agencia Nacional de Investigación e Innovación, Instituto Nacional de Investigación Agropecuaria, Barraca Erro S.A., Lebu SRL, Fadisol SA, CALMER and COPAGRAN. 520 $aABSTRACT. - Drought limits crop productivity and reduces yield stability. Drought tolerance as a selection criterion in breeding programs requires the development of high-throughput, precise, and low-cost phenotyping strategies. We developed a mathematical model, based on biological approaches, for evaluating soybean plants? response to drought under controlled growth conditions. The model describes the kinetics of water consumption of a plant pot substrate system (PPS) with low sampling requirements. The model generated two parameters, t0.5 (time necessary for the PPS to reach half of the maximum amount of evapotranspirable water) and Gw(t0.5 ) (stomatal conductance [Gw] at t0.5 ), which determined the water-consumption curve of each genotype. An analysis of the kinetics of water consumption in response to a progressive water deficit in a biparental and breeding population was performed as a preliminary test of the model. A correspondence analysis between the t0.5 and Gw(t0.5 ) parameters with the genetic structure of the populations shows a genetic association. The phenotyping methodology presented in this work and drought susceptibility in field conditions are discussed based on previous results. This work could be useful for improving the selection of soybean genotypes in relation to their performance under drought conditions. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. 653 $aCrop breeding 653 $aDrought 653 $aMathematical modeling 653 $aStomatal conductance 700 1 $aCASARETTO, E. 700 1 $aQUERO, S. 700 1 $aCERETTA, S. 700 1 $aBONNECARRERE, V. 700 1 $aBORSANI, O. 773 $tAgronomy, 2022, Volume 12, Issue 3, Article number 575. GOLD OPEN ACCESS. doi: https://doi.org/10.3390/agronomy12030575
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