Principal component analysis and genetic correlation studies in Lens culinaris Medik

Autor: S. Pavithra1 , A. Sarkar1 , S. K. Roy1 and P. M. Bhattacharya
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Electronic Journal of Plant Breeding, Vol 14, Iss 3, Pp 1198 -1205 (2023)
Druh dokumentu: article
ISSN: 0975-928X
DOI: 10.37992/2023.1403.097
Popis: Lentil (Lens culinaris Medik.), an important rabi pulse crop grown in the plains of West Bengal, is vulnerable to Stemphylium blight, caused by the fungal pathogen Stemphylium botryosum. Considering the severity of the disease in the existing cropping system, an experiment was undertaken at the instructional farm of Uttar Banga Krishi Viswavidyalaya during Rabi 2021 with the objective to observe the correlation between the quantitative traits and the Area Under Disease Progress Curve (AUDPC) among the 50 lentil genotypes under the incidence of Stemphylium blight. The experiment was planned in Alpha Lattice design with two replications. The disease parameter AUDPC was derived from Hashemi’s disease score. A total of twenty quantitative traits viz., days to 50% flowering, plant height, primary branches/ plant, secondary branches/ plant, nodes/ plant, leaflet number, leaflet length, leaf length, tendril length, peduncle length, 100 - seed weight, seed width, seed thickness, seeds/ pod, pods/ cluster, pods/ plant, days to maturity, pod yield, harvest index and seed yield were recorded. Significant positive correlation was recorded for AUDPC with days to 50% flowering and primary branches/ plant as against significant negative correlation for AUDPC with 100- seed weight and harvest index. The study on Principal Component Analysis (PCA) revealed that the traits viz., seed yield, pod yield, leaf length, leaflet length, pods/ plant, secondary branches, seeds/ pod, days to maturity, AUDPC, nodes/ plant, days to 50% flowering, pods/ cluster, seed thickness and harvest index showed the maximum contribution towards variation (19.49%) among the PC1 variables. The PCA biplot revealed that seed yield and pod yield strongly influenced PC1. Thus, the findings of the current study might be helpful to schedule the crop improvement program as far as the response of the crop to the disease is concerned.
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