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Vol. 12, Issue 8 (2023)

Assessing genetic diversity and correlation among 150 elite sugarcane clones based on morphological characterization

Author(s):
Naresh Kumar
Abstract:
The genetic diversity of 150 elite sugarcane clones including 6 checks representing early and mid-late maturing group were assessed in the current study at the experimental farm of Punjab Agricultural University, Regional Research Station, Gurdaspur. The findings of the study emphasized that ample genetic diversity was existing in the clones for all the traits based on genetic diversity parameters. High heritability together with high genetic advance as percentage of mean was detected for no. of shoots, NMC, stalk length, single cane weight and cane yield which indicates that selection for these traits could be more effective because of genes showing additive behaviour for these traits. The correlation results suggest that to improve the cane yield in sugarcane traits such as number of shoots, number of millable canes, stalk length and single cane weight should be given more weightage. The extremity was found between cluster one and five (5.1), followed by cluster three and five (4.63), cluster five and six (4.45). The cluster 2 having clones showed more stalk length, cluster 3 having clones representing maximum no. of shoots and no. of millable canes, cluster 5 having clones showed more cane yield and cluster 7 representing clones having maximum stalk diameter, single cane weight and brix content. The more emphasis was given to the cluster having maximum genetic divergence for the basis of selection and selecting the parents for crossing. Hence, clusters with highest mean value for the required traits shall be take into consideration for selection as parents for crossing or for other population advancement methods in future sugarcane development programmes.
Pages: 2221-2226  |  103 Views  55 Downloads


The Pharma Innovation Journal
How to cite this article:
Naresh Kumar. Assessing genetic diversity and correlation among 150 elite sugarcane clones based on morphological characterization. Pharma Innovation 2023;12(8):2221-2226.

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