Phenotypic variability and yield component analysis of lima bean (Phaseolus lunatus L.) genotypes under coastal conditions of Peru

• Autores: Camargo Cobeñas, Marcos Antonio, Almidon Ramirez, Karen Karina, Rojas Meza, María Elena, Terán Rojas, José Alfonso
• Formato: artículo
• Fecha de Publicación: 2026
• Institución: Instituto Nacional de Innovación Agraria
• Repositorio: INIA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.inia.gob.pe:20.500.12955/3136
• Enlace del recurso: http://hdl.handle.net/20.500.12955/3136; https://doi.org/10.18805/LRF-946
• Nivel de acceso: acceso abierto
• Materia: Coastal conditions; Condiciones costeras Genetic variability; Variabilidad genética Germplasm; Germoplasma Multivariate analysis; Análisis multivariado Phaseolus lunatus L.; Phaseolus lunatus L.; https://purl.org/pe-repo/ocde/ford#4.01.07; Genotipo; Genotypes; Variación fenotípica; Phenotypic variation; Carácter de rendimiento; Yield components; Plant breeding; Fitomejoramiento; Leguminosa de grano; Grain legumes

Background: Lima bean (Phaseolus lunatus L.) is an important grain legume cultivated in tropical and subtropical regions and contributes significantly to food security and local agriculture, particularly in Peru. However, information on the agronomic variability of lima bean germplasm under coastal conditions of Peru remains limited. This study aimed to evaluate the phenotypic variability and yield-related traits of lima bean genotypes from the INIA Germplasm Bank. Methods: Seven genotypes were evaluated under field conditions in Pisco, Ica (Peru), using a randomized complete block design with four replications. Twelve agronomic and morphological traits related to pod, seed and yield components were recorded. Data were analyzed using analysis of variance, Pearson correlation, principal component analysis and hierarchical clustering. Result: Significant differences among genotypes were observed for most traits, indicating considerable phenotypic variability. Grain yield per plant showed positive correlations with the total number of pods per plant and the number of marketable pods. The first two principal components explained 51.14% of the total variation and separated genotypes mainly according to yield components and morphological traits. Cluster analysis grouped the genotypes into three clusters, identifying genotype Ac4 as the most promising material due to its favorable association with yield-related traits and lower incidence of pest-infested pods.