Collection and characterisation of plant materials is a crucial step in crop improvement programmes. The objective of this study was to characterise a sweet potato (Ipomoea batatas [L.] Lam.) collection from the Centre National de Recherche Agronomique (CNRA) in Côte d'Ivoire, based on morphological characters, and to elucidate the relationships among them. The experiment was carried out in a Fisher design with two replications. The descriptive analyses revealed a substantial phenotypic variation within the collection. The multiple correspondence analysis showed that 15 characters out of 27 were the most discriminant to explain the variation. Furthermore, significant relationships were observed between phenotypic traits related to leaves, stems and storage roots. The hierarchical classification placed accessions into three genetic groups regardless of their geographical origin and revealed the existence of duplicate accessions. The results obtained could be used for the selection, improvement and sustainable management of sweet potato genetic resources.

The characterization of genetic resources is essential for improvement and conservation programs. The objective of this study was to study the morphological and agronomic variability of the sweet potato (Ipomoea batatas (L.) Lam.) collection of the Centre National de Recherche Agronomique (CNRA) of Côte d'Ivoire. The work was carried out with 88 accessions on the basis of 12 agronomic characters according to a Fisher design with two replicates. The correlations observed showed the degree of linkage between the traits. Principal component analysis revealed significant variability between individuals in the four groups formed (1.1, 1.2, 1.3, and 1.4). The most discriminating characters of sweet potato accessions were percentage of productive plants (PPPR), total number of storage roots (SRNU), total storage root weight (SRNU), storage root yield (SRYD), mosaic incidence (VIRD), weevil incidence (SRWE), nematode incidence (SRNE) and rodent incidence (SRRO). The hierarchical cluster analysis resulted in the formation of five groups of accessions independently of geographical origin. Discriminant factor analysis revealed that the grouping of accessions is a function of yield characteristics and disease and pest incidence.