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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
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Int.J.Curr.Microbiol.App.Sci.2018.7(12): 1424-1430
DOI: https://doi.org/10.20546/ijcmas.2018.712.170


Genetic Diversity Studies Based on Principal Component Analysis For Yield Attributes in Cassava Genotypes
 B. Babu Rao*1, D.V. Swami1, P. Ashok1, B. Kalyana Babu2, D. Ramajayam3 and K. Sasikala1
1Department of Horticulture, 4 Department of Agronomy, Dr. Y.S.R. Horticultural University, Venkataramannagudem, West Godavari, A.P – 534101, India
2ICAR-Indian Institute of Oil Palm Research, Pedavegi, A.P – 534450, India
3ICAR-National Research Centre for Banana, Tiruchirapally, T.N - 620102, India
*Corresponding author
Abstract:

The present investigation entitled was carried out with seventy seven cassava genotypes along with three check varieties in order to study the variability for different yield attributing characters by Principal components analysis during the period from 2015 to 2016. Principal components analysis showed that, six components with eigen value more than one explained 73.16% of the cumulative variation among traits. Principal component one (PC1) with eigen value of 3.60, contributed 22.49% of the total variability, PC2, with eigen value of 2.13, revealed 13.31% of total variability, PC3 had eigen value of 1.95 and contributed with 12.20 % to the total observed variability, PC4, with eigen value of 1.61, contributed 10.06% of the total variability, PC5 had eigen value of 1.27 and contributed with 7.93 % to the total observed variability, while PC6, with eigen value of 1.15, accounted for 7.17% of total variability observed among the 80 cassava genotypes. The cumulative variance of 73.16% by the first six components with eigen values of >1.0 indicates that the identified traits within these components exhibited great influence on the phenotype of the cassava genotypes and could effectively be used for the selection among them.


Keywords: Cassava, Principal component analysis, Variability, Genetic diversity
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How to cite this article:

Babu Rao, B., D.V. Swami, P. Ashok, B. Kalyana Babu, D. Ramajayam and Sasikala, K. 2018. Genetic Diversity Studies Based on Principal Component Analysis For Yield Attributes in Cassava Genotypes.Int.J.Curr.Microbiol.App.Sci. 7(12): 1424-1430. doi: https://doi.org/10.20546/ijcmas.2018.712.170