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The aim of this research was select the best combination of contrasting parents to develop a mapping population for drought tolerance, based on phenotypic and genotypic data. Phenotyping was conducted in a greenhouse during 16 days at vegetative stage under well-watered (WW) and water-deficit (WD) conditions. Traits evaluated were: gain of leaf area (GLA), total water use (TWU), net assimilation rate (NAR), water use efficiency (WUE) and transpiration
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dc.contributor.author | Grandon, Nancy Gabriela | |
dc.contributor.author | Martin, Eugenia Alejandra | |
dc.contributor.author | Cicconi, Emmanuel | |
dc.contributor.author | Diaz, Carolina Del Pilar | |
dc.contributor.author | Mamani, Eva Maria Celia | |
dc.contributor.author | Moreno, Maria Valeria | |
dc.date.accessioned | 2024-05-21T14:02:07Z | |
dc.date.available | 2024-05-21T14:02:07Z | |
dc.date.issued | 2021-12-20 | |
dc.identifier.issn | 2693-5015 (online) | |
dc.identifier.other | https://doi.org/10.21203/rs.3.rs-1135239/v1 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12123/17825 | |
dc.identifier.uri | https://www.researchsquare.com/article/rs-1135239/v1 | |
dc.description | Preprint | |
dc.description.abstract | The aim of this research was select the best combination of contrasting parents to develop a mapping population for drought tolerance, based on phenotypic and genotypic data. Phenotyping was conducted in a greenhouse during 16 days at vegetative stage under well-watered (WW) and water-deficit (WD) conditions. Traits evaluated were: gain of leaf area (GLA), total water use (TWU), net assimilation rate (NAR), water use efficiency (WUE) and transpiration rate (TR) response to vapor pressure deficit (VPD) (slope and breakpoint). Genotyping was performed with 127 SSR markers and a cluster analyses was conducted. An important interaction was observed for NAR, WUE and breakpoint in the VPD response. Under WD conditions, all genotypes showed lower GLA and TWU, whereas NAR and WUE increased its values. All genotypes showed reduction of the slope and breakpoint in high VPD response on WD. PCA analysis explains the 80% of the total variability. PC1 discriminated HA89 and R419 due to a lower slope and higher breakpoint, while PC2 separated by water treatment based on the WUE and TWU values. Nighty nine SSR marker were amplified detecting 262 alleles. Cluster analyzes showed two main groups, one including HAR4 and B59 and the other one including five remaining genotypes. According to these results, only R419xHA64 and HA89xHAR4 had a greater genetic distance (1.08), besides a high polymorphism level between ILs (about 60%). Therefore, we conclude that these would be the best combination of contrasting parents to develop mapping populations for drought tolerance in sunflower. | es_AR |
dc.format | application/pdf | eng |
dc.language.iso | eng | es_AR |
dc.publisher | Research Square | es_AR |
dc.rights | info:eu-repo/semantics/openAccess | eng |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | eng |
dc.source | Research Square: v1. 2021 | es_AR |
dc.subject | Girasol | es_AR |
dc.subject | Sunflowers | es_AR |
dc.subject | Drought Tolerance | es_AR |
dc.subject | Tolerancia a la sequia | es_AR |
dc.subject | Phenotyping | es_AR |
dc.subject | Helianthus annuus | es_AR |
dc.subject | Fenotipado | |
dc.subject | Marcadores Genéticos | |
dc.subject | Genetic Markers | eng |
dc.subject.other | Sunflower Inbred Lines | es_AR |
dc.subject.other | Líneas endogámicas de girasol | es_AR |
dc.subject.other | SSR markers | es_AR |
dc.subject.other | Marcadores SSR | es_AR |
dc.subject.other | Water Use Efficiency | es_AR |
dc.subject.other | Eficiencia en el Uso del Agua | es_AR |
dc.subject.other | Vapor Pressure Deficit Response | es_AR |
dc.subject.other | Respuesta al déficit de presión de vapor | es_AR |
dc.title | Selection of Contrasting Parents for Drought Tolerance in Sunfower (Helianthus Annuus L.) | es_AR |
dc.type | info:ar-repo/semantics/artículo | es_AR |
dc.type | info:eu-repo/semantics/article | eng |
dc.type | info:eu-repo/semantics/acceptedVersion | eng |
dc.rights.license | Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) | eng |
dc.description.origen | EEA Manfredi | es_AR |
dc.description.fil | Fil: Grandón, Nancy Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Grupo de Biotecnología en Cultivo; Argentina | es_AR |
dc.description.fil | Fil: Martìn, Eugenia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Campo Experimental Villarino | es_AR |
dc.description.fil | Fil: Dìaz, Carolina del Pilar. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Manfredi. Grupo Economía Estadística; Argentina | es_AR |
dc.description.fil | Fil: Mamani, Eva Maria Celia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Grupo de Biotecnología en Cultivo; Argentina | es_AR |
dc.description.fil | Fil: Moreno, María Valeria. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Grupo de Biotecnología en Cultivo; Argentina | es_AR |
dc.description.fil | Fil: Martin, Eugenia Alejandra. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias. Instituto de Investigaciones en Ciencias Agrarias de Rosario. Campo Experimental Villarino; Argentina | |
dc.description.fil | Fil: Cicconi, Emanuel. Asesor Técnico. Argentina | |
dc.subtype | cientifico |
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