Phenotypic characterisation of niger (Guizotia abyssinica L.F.Cass) germplasm for selection of core collection

Niger (Guizotia abyssinica) is an important industrial oil seed crop. In the present study, a total of 2850 accessions conserved in the Indian National Gene Bank, representing India and other parts of the world, were characterized for their agro-morphological traits and total oil content. The augmented accessions were evaluated for 19 agro-morphological traits, including 13 quantitative and six qualitative traits, along with four check varieties at four different geographical locations in the winter season (2021–2022) through an Augmented Block Design. Five independent core sets were developed using compiled data on agro-morphological traits (standardized to eliminate scale differences) with Core Hunter in R, following optimization of average genetic distance-based criteria. Core size intensity was fixed at 300 accessions, which is approximately 10 % of the size of entire collection. Among the five, the core set EN100 was selected as the best representation based on the evaluation indices like, variance difference of 100 %, coincidence rate of 97.84 %, variable rate of coefficient of variation at 135.16 %, and mean difference at 46.15 %. The developed core collection was evaluated for its maximum diversity representation using the R package EvaluateCore. Diversity indices, Shannon-Weiner (1.014), McIntosh (0.26), and a lower Simpson’s Index (0.57) indicated high diversity in the selected core. The findings, such as a higher coefficient of variation for all traits in the core set than in the entire collection and a symmetrical distribution of accessions across the core set for the majority of traits, showed that the core collection effectively represents the variability present in the entire collection. and the first five principal components explained 66.15 % of cumulative variance in core set EN100, whereas 64.5 % in entire collection, with PC1 and PC2 contributing 21.6 % and 14.5 %, respectively. This highly diverse representative core set EN100 could be used to effectively identify accessions with desirable agronomic traits of industrial importance.