The present study was conducted with 120 germplasm of linseed (Linumusitatissimum L) including six checks, to assess the extent and pattern of genetic divergence. The experiment was conducted in Alpha lattice Design at Holeta and Kulumsa Research Centers, highlands of Ethiopia during rainfed season 2019/20. The genetic diversity was estimated by Mahalanobis D2statistics and the genotypes were grouped into four clusters using the average linkage clustering method each clusters having 69, 22, 29 and 6 genotypes respectively. The poor intra-cluster distance was found in all cluster groups, suggesting impossibility of easy trait manipulation between these genotypes for linseed improvement. Cluster III showing the highest mean for days to 50% flowering, days to maturity, high harvest index, carbohydrate content, linoleic acid and low plant height, number of primary branches per plant, number of secondary branches per plant, number of capsules per plant, number of seeds per capsule, thousand seed weight, biological yield per plant, linolenic acid, oil yield per plant and seed yield per plant, appears a desirable parent. The maximum inter cluster was between Cluster-II and IV (246.58) followed by Cluster II and III (170.18), Cluster I and II (80.08), Cluster I and IV (67.63) and Cluster I and III (38.08) The minimum being Cluster III and IV (30.94). Generally this study showed that the genotypes included in this study are moderately divergent. Principle component analysis (PCA) showed the first four PCs had eigen value >1.00 and accounted more than 79.29% of total variation. The predominance nature of yield contributing traits like oil yield per hectare, number of seeds per capsule, thousand seed weight, biological yield per plant, plant height, days of 50% flowering, days to maturity. Number of primary branches and number of capsules per plant, indicated that these components were proven more important and crossing between and/ or within cluster may give good recombinants for linseed improvement.

Keywords: linseed, genetic diversity, principle component analysis