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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2020)
[Effective from January 1, 2020]
For more details click here

ICV 2018: 95.39
Index Copernicus ICI Journals Master List 2018 - IJCMAS--ICV 2018: 95.39
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
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Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2017.6(7): 354-359
DOI: https://doi.org/10.20546/ijcmas.2017.607.041


Cluster and Principal Component Analysis in Maize
L. Suryanarayana1*, M. Reddi Sekhar3, D. Ratna Babu4, A.V. Ramana2 and V.Srinivasa Rao5
1Department of Genetics and Plant Breeding,
2Department of Agronomy, Agricultural College, Naira, A.P., India
3Department of Genetics and Plant Breeding, S.V. Agricultural College, Tirupati, A.P., India
4Plant Breeding, RARS, Lam farm, Guntur, A.P., India
5Department of Statistics and Mathematics, Agricultural College, Bapatla, A.P., India
*Corresponding author
Abstract:

In the present study all the 30 genotypes were grouped into six non overlapping clusters based on non- hierarchical Euclidean cluster analysis. Maximum numbers of genotypes (7) were grouped in cluster-I, IV and VI followed by cluster-II (5), cluster-V (3) and cluster III with one genotype. Inter-cluster distances was highest between cluster IV and VI (916.73) followed by III and V (846.80). Among the 21 characters studied, grain yield plant-1, stover yield plant-1, number of kernels per row and ear height contributed maximum towards the total divergence.


Keywords: Maize, Cluster analysis, Principal Component Analysis.
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How to cite this article:

Suryanarayana, L., M. Reddi Sekhar, D. Ratna Babu, A.V. Ramana and Srinivasa Rao, V. 2017. Cluster and Principal Component Analysis in Maize.Int.J.Curr.Microbiol.App.Sci. 6(7): 354-359. doi: https://doi.org/10.20546/ijcmas.2017.607.041