Performance profiling of Prunus persica (L.) Batsch collection and comprehensive association among fruit quality, agronomic and phenological traits

Abstract

Nowadays, although there are several studies based on peach phenotypic diversity and adaptability, there is no current research regarding associations among characters using multivariate statistical methods which provide more trustable conclusions than bivariate analysis. For this reason, we evaluated not only the adaptability of the accessions but also the relationships among qualitative and quantitative traits applying Multiple Correspondence Analysis and Factor Analysis, respectively. The study was carried out on seventy-seven nectarine and one hundred and thirty-two peach accessions grown in Argentina that were characterized with 35 fruit quality, agronomic and phenological traits during 3 seasons. Multiple Correspondence Analysis revealed that freestone trait would be associated with strong anthocyanin coloration of the flesh around the brown dark stone while semi-freestone trait would be related to weak or no anthocyanin coloration of the flesh around the light brown stone. Then, Factor Analysis enabled us to identify positive relationships between blooming and sprouting date; harvesting period and yield and among fruit development period, harvesting date, fruit weight and soluble solid content. In addition, 'phenology traits', 'productivity' and 'fruit quality and reaping time' would be unrelated to each other. Furthermore, the agglomerative hierarchical cluster analysis grouped the accessions in accordance to their similarities and allowed the identification of the most adapted cultivars. We have demonstrated that this approach is a powerful tool that should be considered for further studies on peach germplasm and it has also the possibility to be applied for other fruit species. Finally, the results of this study provide valuable information for germplasm characterization and for breeding practices aiming to develop accessions adapted to the climatic conditions of the northern of Buenos Aires province.