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


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Authors

  • SANJEEV PANWAR Indian Agricultural Statistics Research Institute, Pusa, New Delhi 110012
  • ANIL KUMAR Indian Agricultural Statistics Research Institute, Pusa, New Delhi 110012
  • K N SINGH Indian Agricultural Statistics Research Institute, Pusa, New Delhi 110012
  • MD SAMIR FAROOQI Indian Agricultural Statistics Research Institute, Pusa, New Delhi 110012
  • ABHISHEK RATHORE ICRISAT, Hyderabad

https://doi.org/10.56093/ijas.v82i12.26253

Keywords:

Forecasting, Goodness of fit, Growth models, Optimization, Run test, Theil statistic

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.

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References

Draper N R and Smith H. 1998. Applied Regression Analysis, 3rd ed. Wiley, NY.

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Chandran K P and Prajneshu. 2004. Computation of growth rates in agriculture: Nonparametric regression approach. Journal of Indian Society of Agricultural Statistics 57: 382–92.

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Submitted

2013-01-12

Published

2013-01-12

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Section

Articles

How to Cite

PANWAR, S., KUMAR, A., SINGH, K. N., FAROOQI, M. S., & RATHORE, A. (2013). Nonlinear regression techniques for analysis of onion (Allium cepa) production in India. The Indian Journal of Agricultural Sciences, 82(12), 1051–4. https://doi.org/10.56093/ijas.v82i12.26253
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