Morphometric analysis in "tara" fruits from Yauyos and Ayacucho to identify traits of agromorphological interest

• Autores: Bonilla, Henry, López, Alberto, Carbajal, Yajahaira, Siles, Maria
• Formato: artículo
• Fecha de Publicación: 2016
• Institución: Universidad Nacional de Trujillo
• Repositorio: Revistas - Universidad Nacional de Trujillo
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.unitru.edu.pe:article/1162
• Enlace del recurso: https://revistas.unitru.edu.pe/index.php/scientiaagrop/article/view/1162
• Nivel de acceso: acceso abierto
• Materia: Caesalpinia spinosa; morfometría; discriminación; Ayacucho; Yauyos; morphometric; discrimination

Tara (Caesalpinia spinosa) is an Andean legume which has an economic importance for their active substances and derivate products. However, there are not morphometric studies which allow characterizing populations to have genetic material for breeding or conservation programs. In the present study morphometric variables are analyzed to identify agro-morphological characteristics which permit differentiate populations. Ten variables of pod and seed from Yauyos and Ayacucho were analyzed; the comparison of means was evaluated using the Mann-Whitney. To determine the relationship between variables a Spearman correlation analysis between populations and taking in account the whole population was performed. According to these results, linear regression models were implemented. Finally, principal component analysis (PCA) was used to visualize patterns in the data. Of the ten variables studied, all showed significant differences (p < 0.01) except the large of the pod and the number of seeds per fruit, which presented a median of 6 for both locations and could be considered a characteristic of the species. Seven variables for characterization are proposed: Pod width, fruit weight, weight of pod, seed weight, weight ratio of pod/fruit, weight ratio of seeds/fruit and weight of the central seed. The fruit width showed high correlation (0.78) with the fruit weight, thus this variable allows to quickly characterize fruits in field. The PCA graph showed partial overlap between the populations, which corroborates their differentiation.