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

• Autores: Scarpin, Gonzalo Joel; Bhattarai, Anish; Hand, Lavesta C.; Snider, John L.; Roberts, Phillip M.; Bastos, Leonardo M.
• Año de publicación: 2025
• Idioma: inglés
• Tipo de recurso: artículo
• Fuente: Field Crops Research 325 : 109822. (April 2025)
• Materia: Algodón; Rendimiento; Calidad; Interacción Genotipo Ambiente; Georgia (EUA); Cotton; Yields; Quality; Genotype-environment Interaction; Gossypium hirsutum; Georgia (USA)
• Institución: Instituto Nacional de Tecnología Agropecuaria

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