Phenotypic and agromorphological diversity reveals detailed information about accessions with productive potential for cotton (Gossypium barbadense L.) in northeastern Peru

• Autores: Cordova Sinarahua, Deyvis, Linares Huapaya, Susan Maribel, Manco Céspedes, Emma Imelda
• Formato: artículo
• Fecha de Publicación: 2026
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.inia.gob.pe:20.500.12955/3020
• Enlace del recurso: http://hdl.handle.net/20.500.12955/3020; https://doi.org/10.3390/plants15020314
• Nivel de acceso: acceso abierto
• Materia: Gossypium barbadense L.; Genotypic coefficient of variation; Phenotypic coefficient of variation; Heritability; multivariate analysis; Coeficiente de variación genotípico; Coeficiente de variación fenotípico; Heredabilidad; Análisis multivariado; https://purl.org/pe-repo/ocde/ford#4.01.06; Algodón; Cotton; Variación Genética; Genetic variation; Fenotipo; Phenotypes; Germoplasma; Germplasm; Morfología vegetal; Plant morphology

Cotton (Gossypium barbadense L.) is a crop of great economic importance, as the superior quality of its fiber is highly valued worldwide. The objective of this research was to evaluate the agromorphological diversity of cotton germplasm using both qualitative and quantitative descriptors. A combination of univariate and multivariate statistical analyses was applied to identify promising accessions. The coefficients of variation (GCV and PCV) and high heritability estimates observed for descriptors such as the number of sympodial branches, fiber weight, and number of seeds per capsule confirm genetic control, ensuring the effectiveness of selection in future breeding programs. Correlation analysis revealed a strong positive relationship between lint yield and number of bolls per plant (0.893). Furthermore, principal component analysis indicated that accessions PER1010536, PER1010538, PER1010543, and PER1010547 were associated with high yield and early-maturity traits. Furthermore, multiple correspondence analysis and mixed data factor analysis demonstrated that the observed variability also depends on qualitative traits such as petal spot and bract color, supporting the concept of a complex genetic architecture. These findings provide a solid basis for the development of new cotton cultivars with improved productivity.