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resumen

Resumen
Context: Georgia is one of the largest cotton producer in the United States. Genotype x environment analysis have been previously performed, although there still exists a gap in knowledge related to i) newer varieties and ii) characterization of environmental potential in relation to meteorological patterns during the growing season. Objectives: i) to quantify the effects of environment, genotype, and management on yield and quality; ii) to evaluate the [ver mas...]
dc.contributor.authorScarpin, Gonzalo Joel
dc.contributor.authorBhattarai, Anish
dc.contributor.authorHand, Lavesta C.
dc.contributor.authorSnider, John L.
dc.contributor.authorRoberts, Phillip M.
dc.contributor.authorBastos, Leonardo M.
dc.coverage.spatialGeorgia .......... (state) (World, North and Central America, United States)es_AR
dc.coverage.spatial7007248es_AR
dc.date.accessioned2025-03-07T12:15:20Z
dc.date.available2025-03-07T12:15:20Z
dc.date.issued2025-04
dc.identifier.issn0378-4290
dc.identifier.issn1872-6852
dc.identifier.otherhttps://doi.org/10.1016/j.fcr.2025.109822
dc.identifier.urihttp://hdl.handle.net/20.500.12123/21592
dc.identifier.urihttps://www.sciencedirect.com/science/article/pii/S0378429025000875
dc.description.abstractContext: Georgia is one of the largest cotton producer in the United States. Genotype x environment analysis have been previously performed, although there still exists a gap in knowledge related to i) newer varieties and ii) characterization of environmental potential in relation to meteorological patterns during the growing season. Objectives: i) to quantify the effects of environment, genotype, and management on yield and quality; ii) to evaluate the performance and responsiveness of different genotypes to different environments, and iii) to identify environmental conditions with increased cotton lint yield or quality parameters. Method: Studies were conducted in 73 site-years as part of a variety trial program. In all the site-years, 22 cotton varieties were evaluated, of which twelve were present in at least 45 site-years. We performed analysis of variance, variance component, Finlay-Wilkinson, and conditional inference tree, to achieve our objectives. Results: The environment had a greater impact on yield and fiber quality (length, strength, uniformity and micronaire) than did genotype. We generate recommendations on variety selection according to each environment index. Conditional inference tree identified temperature and stage duration in squaring and boll opening as the most important variables and stages for affecting micronaire, yellowness, length, and uniformity. Conclusions: Our results will help farmers selecting the proper variety, considering not only their potential but also their main goal (yield or quality). As newer cotton genotypes are introduced yearly, we propose to continue working with these datasets to develop an online application to help farmers to identify and select the best genotype for their environment.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.publisherElsevieres_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/es_AR
dc.sourceField Crops Research 325 : 109822. (April 2025)es_AR
dc.subjectAlgodónes_AR
dc.subjectCottoneng
dc.subjectRendimientoes_AR
dc.subjectYieldseng
dc.subjectCalidades_AR
dc.subjectQualityeng
dc.subjectInteracción Genotipo Ambientees_AR
dc.subjectGenotype-environment Interactioneng
dc.subjectGossypium hirsutumeng
dc.subjectGeorgia (EUA)es_AR
dc.subjectGeorgia (USA)eng
dc.titleCotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactionses_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)es_AR
dc.description.origenEEA Reconquistaes_AR
dc.description.filFil: Scarpin, Gonzalo Joel. University of Georgia. Department of Crop and Soil Sciences; Estados Unidoses_AR
dc.description.filFil: Scarpin, Gonzalo Joel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Reconquista; Argentinaes_AR
dc.description.filFil: Bhattarai, Anish. University of Georgia. Department of Crop and Soil Sciences; Estados Unidoses_AR
dc.description.filFil: Hand, Lavesta C. University of Georgia. Department of Crop and Soil Sciences; Estados Unidoses_AR
dc.description.filFil: Snider, John L. University of Georgia. Department of Crop and Soil Sciences; Estados Unidoses_AR
dc.description.filFil: Roberts, Phillip M. University of Georgia. Department of Entomology; Estados Unidoses_AR
dc.description.filFil: Bastos, Leonardo M. University of Georgia. Department of Crop and Soil Sciences; Estados Unidoses_AR
dc.subtypecientifico


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