International Journal of Pure & Applied Bioscience (IJPAB)
Year : 2017, Volume : 5, Issue : 5
First page : (222) Last page : (227)
Article doi: http://dx.doi.org/10.18782/2320-7051.5159
Using Different Statistical Techniques for Selection a Stable Varieties of Rice in Chhattisgarh State
Roshan Kumar Bhardwaj1* and R. R. Saxena2
1Ph. D. (Agricultural Statistics), Deptt. Of Physical Science, M.G.C.G.V, Chitrakoot, Satna (M.P.)
2Professor, Deptt. Of Statistics & SS., IGKV, Raipur (C.G.)
*Corresponding Author E-mail: roshan_smcs@rediffmail.com
Received: 9.07.2017 | Revised: 20.07.2017 | Accepted: 21.07.2017
ABSTRACT
The objective of this study was to explore the effect of genotype and genotype x environment interaction on yield of 10 rice varieties in thirty different environments. Various statistical methods are available to analyze the data in MVATs. However, the information on these methods and their relative performance on evaluation of adaptability of rice varieties are limited. Therefore, in these studies was compare the statistical methods available for analysis of MVATs data of rice. It considered of yield data on performance of 10 varieties at 10 locations over 3 years. The statistical techniques such as ANOVA, stability parameters, ranking, multivariate techniques as a traditional method are used to approach were tested with the data. The result revealed that ANOVA method is not effective in describing pattern of G x E interaction but effective in describing main effects. Different stability methods consider different aspects of variability of varieties vary according to the parameter considered. Multivariate methods describe G x E interaction effectively with AMMI stability value that is easy to understand.
Key words: Adaptability, AMMI, G x E Interaction, IPCA, Variety stability.
Full Text : PDF; Journal doi : http://dx.doi.org/10.18782
Cite this article: Bhardwaj, R.K. and Saxena, R.R., Using Different Statistical Techniques for Selection a Stable Varieties of Rice in Chhattisgarh State, Int. J. Pure App. Biosci.5(5): 222-227 (2017). doi: http://dx.doi.org/10.18782/2320-7051.5159
