Nonlinear regression techniques for analysis of onion (Allium cepa) production in India

Panwar, S and Kumar, A and Singh, K N and Farooqi, S and Rathore, A (2012) Nonlinear regression techniques for analysis of onion (Allium cepa) production in India. Indian Journal of Agricultural Sciences, 82 (12). pp. 1051-1054. ISSN 0019-5022

PDF - Published Version Restricted to ICRISAT users only Download (277kB) | Request a copy

Abstract

India occupies second position in the production of onion in the world. Keeping in view the importance of this crop, the present study has been undertaken to find out the growth in production of onion and discusses the application of nonlinear models, viz. Gompertz, Logistic, MMF, Richards and Weibull models, which measure the growth. Time series data on onion production in major growing states; viz. Andhra Pradesh, Gujarat, Karnataka, Maharashtra, Uttar Pradesh, and all India from 1990–91 to 2009–10 has been utilized for the present study. From a realistic point of view, the relationships among variables in agricultural and horticultural sciences are non-linear in nature. Non-linear models are very popularly used to estimate the trend in various fields such as population studies and animal growth where growth is not symmetrical about the point of inflection. The results showed that Logistic and Gompertz models faired marginally better than Weibull and MMF models

Item Type:	Article
Divisions:	UNSPECIFIED
CRP:	UNSPECIFIED
Uncontrolled Keywords:	Forecasting, Goodness of fit, Growth models, Optimization, Run test, Theil statistic
Subjects:	Others
Depositing User:	Ms K Syamalamba
Date Deposited:	08 May 2014 07:59
Last Modified:	08 May 2014 07:59
URI:	http://oar.icrisat.org/id/eprint/7972
Official URL:	http://epubs.icar.org.in/ejournal/index.php/IJAgS/...
Projects:	UNSPECIFIED
Funders:	UNSPECIFIED
Acknowledgement:	UNSPECIFIED
Links:	Google Scholar

View Statistics

Actions (login required)

View Item