Cotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactions

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...

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Main Authors: Scarpin, Gonzalo Joel, Bhattarai, Anish, Hand, Lavesta C., Snider, John L., Roberts, Phillip M., Bastos, Leonardo M.
Format: info:ar-repo/semantics/artículo
Language:Inglés
Published: Elsevier 2025
Subjects:
Online Access:http://hdl.handle.net/20.500.12123/21592
https://www.sciencedirect.com/science/article/pii/S0378429025000875
https://doi.org/10.1016/j.fcr.2025.109822
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author Scarpin, Gonzalo Joel
Bhattarai, Anish
Hand, Lavesta C.
Snider, John L.
Roberts, Phillip M.
Bastos, Leonardo M.
author_browse Bastos, Leonardo M.
Bhattarai, Anish
Hand, Lavesta C.
Roberts, Phillip M.
Scarpin, Gonzalo Joel
Snider, John L.
author_facet Scarpin, Gonzalo Joel
Bhattarai, Anish
Hand, Lavesta C.
Snider, John L.
Roberts, Phillip M.
Bastos, Leonardo M.
author_sort Scarpin, Gonzalo Joel
collection INTA Digital
description 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 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.
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institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
publishDate 2025
publishDateRange 2025
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spelling INTA215922025-03-07T12:17:34Z Cotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactions Scarpin, Gonzalo Joel Bhattarai, Anish Hand, Lavesta C. Snider, John L. Roberts, Phillip M. Bastos, Leonardo M. Algodón Rendimiento Calidad Interacción Genotipo Ambiente Georgia (EUA) Cotton Yields Quality Genotype-environment Interaction Gossypium hirsutum Georgia (USA) 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 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. EEA Reconquista Fil: Scarpin, Gonzalo Joel. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Scarpin, Gonzalo Joel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Reconquista; Argentina Fil: Bhattarai, Anish. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Hand, Lavesta C. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Snider, John L. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos Fil: Roberts, Phillip M. University of Georgia. Department of Entomology; Estados Unidos Fil: Bastos, Leonardo M. University of Georgia. Department of Crop and Soil Sciences; Estados Unidos 2025-03-07T12:15:20Z 2025-03-07T12:15:20Z 2025-04 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/21592 https://www.sciencedirect.com/science/article/pii/S0378429025000875 0378-4290 1872-6852 https://doi.org/10.1016/j.fcr.2025.109822 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Georgia .......... (state) (World, North and Central America, United States) 7007248 Elsevier Field Crops Research 325 : 109822. (April 2025)
spellingShingle Algodón
Rendimiento
Calidad
Interacción Genotipo Ambiente
Georgia (EUA)
Cotton
Yields
Quality
Genotype-environment Interaction
Gossypium hirsutum
Georgia (USA)
Scarpin, Gonzalo Joel
Bhattarai, Anish
Hand, Lavesta C.
Snider, John L.
Roberts, Phillip M.
Bastos, Leonardo M.
Cotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactions
title Cotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactions
title_full Cotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactions
title_fullStr Cotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactions
title_full_unstemmed Cotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactions
title_short Cotton lint yield and quality variability in Georgia, USA: Understanding genotypic and environmental interactions
title_sort cotton lint yield and quality variability in georgia usa understanding genotypic and environmental interactions
topic Algodón
Rendimiento
Calidad
Interacción Genotipo Ambiente
Georgia (EUA)
Cotton
Yields
Quality
Genotype-environment Interaction
Gossypium hirsutum
Georgia (USA)
url http://hdl.handle.net/20.500.12123/21592
https://www.sciencedirect.com/science/article/pii/S0378429025000875
https://doi.org/10.1016/j.fcr.2025.109822
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