Fecha/hora: 03/06/2024 05:12:56

Biblioteca(s): 	INIA Las Brujas.	
Fecha corriente: 	15/03/2022	
Fecha de la última actualización: 	15/03/2022	
Autoria: 	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.	
Año 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-Clave: 	Crop breeding; Drought; Mathematical modeling; Stomatal conductance.	
Categoría del tema: 	F01 Cultivo	
URL: 	https://www.mdpi.com/2073-4395/12/3/575/pdf	
Registro original: 	INIA Las Brujas (LB)	
Ejemplares: 	LB - (103021-1) - PXI - AP - DD - PP/AGRONOMY/2022 -  -  - DIS