Morphological Variation and Discriminating Traits of Kersting’s Groundnut Accessions

Autor: Konoutan Médard Kafoutchoni, Raymond Vodouhè, Brice Sinsin, Gilles Y. Chodaton, Sergino Ayi, Appolinaire Adandonon, Symphorien Agbahoungba, F.J. Chadare, Hospice Samson Sossou, Achille Ephrem Assogbadjo, Frejus Ariel Kpedetin Sodedji, Thomas A. Houndété, Eric E. Agoyi
Rok vydání: 2021
Předmět:
Popis: Kersting’s groundnut [Macrotyloma geocarpum (Harms) Maréchal & Baudet] (KG) is a nutritious, subterranean grain legume in West and Central Africa. Only limited information is available on the morphological traits that can discriminate accessions; without such information, appropriate breeding strategies cannot be devised. This study aimed to identify discriminating traits and assess the diversity among accessions of Kersting’s groundnut. Eighty-one KG accessions from Benin and Burkina Faso were evaluated based on 29 qualitative and quantitative traits. An experiment was conducted using an Alpha lattice design with three replications. Standardized Shannon-Weaver index (H') and descriptive statistics were calculated for qualitative traits. Pearson correlation coefficients, stepwise discriminant analysis, principal component analysis, cluster analysis and canonical discriminant analysis were conducted. Results showed that accessions varied greatly based on growth habit (H'= 0.68), flower color (H' = 0.50), seed-eye shape (H' = 0.47), and stem pigmentation (H' = 0.41). Eight quantitative traits, viz., seed width, seed thickness, number of branches per plant, petiole length, days to 50% flowering, number of seeds per pod, pod width, and pod length, were found to significantly discriminate the accessions. Accessions were grouped into three clusters based on quantitative traits. Cluster 1 had accessions with late flowering and good vegetative growth, Cluster 2 contained accessions with high germination percentage and Cluster 3 had accessions with high yield performance. Seed length varied greatly among accessions, thus indicating the potential for improving yield via seed size.
Databáze: OpenAIRE