International Journal of Statistical Distributions and Applications

| Peer-Reviewed |

Application of Regression Models for Area, Production and Productivity Growth Trends of Cotton Crop in India

Received: 11 September 2017    Accepted: 11 November 2017    Published: 19 January 2018
Views:       Downloads:

Share This Article

Abstract

Computing the growth of any entity over a time period is important for understanding the past behaviour and for future planning. ‘Compound growth rate’ is one of the frequently used methods for calculating the growth rate models. Among the statistical study was carried out on different growth models viz., linear, quadratic, cubic, exponential, compound, logarithmic, inverse, power, growth and S-curve models to project the area, production and productivity cotton crop in India for 1951 to 2013. The study revealed that through all models exhibited significant; the cubic model is the best fitted, for its highest adjusted R2 on increasing future projection trends with respect to area, production and productivity of cotton in India.

DOI 10.11648/j.ijsd.20180401.11
Published in International Journal of Statistical Distributions and Applications (Volume 4, Issue 1, March 2018)
Page(s) 1-5
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Regression Growth Models, Area, Production, Productivity, Cotton, Adjusted R2, Growth Models

References
[1] Aparna, B., S. M. Shareef, V. T. Raju and V. Srinivasa Rao (2008). Growth trends of major vegetables in Visakhapatnam. The Andhra Agricultural Journal, 55 (1), 68-69.
[2] Ahuja, K. N., 1987. Indian’s food demand in 2000. International Seminar on Agricultural Research Systems and Management in the 21st Century. NARM, Hyderabad, December 8-10, ppA32-41.
[3] Borthakur. S and B. K. Bhattacharyya (1998). Trend analysis of Area, Production and Productivity of Potato in Assam 1951-1993, Economic Affairs. Vol. 43 (4) issue.
[4] Chengappa, P. G., 1981, Growth rates of area, production and productivity of coffee, Indian Journal of Coffee Research. 11 (2): 19-26.
[5] Dhakre and Amod Sharma (2009). Growth and instability analysis of ginger production in North-east: region. Agricultural Situation in India. 463-465.
[6] D. P. Sing et al., (2014). Developing statistical models to study the growth rates of paddy crops in different districts of Chhattisgarh, American International Journal of Research in Formal, Applied & Natural Science. 5 (1), 102-104.
[7] Finger, R., (2007). Evidence of slowing yield growth the example of swiss cereal yield. Agri-Food and Agri-Environmental Economics Group, ETH Zurich, Switzerland.
[8] Hussaini. Mairiga, (2014). Trend Analysis of Productivity of Some Selected Cereal Crops in Nigeria: 1983-2008. Tahir, Research on Humanities and Social Sciences. Vol. 4, No. 8, 2014.
[9] Karim, M. R., M. A. Awal and M. Akter, (2010). Forecasting of wheat production in Bangladesh. Bangladesh J. Agric. Res., 35: 17-28.
[10] Kvalseth, T. O. (1985). Cautionary note about (R2), Amer. Statistician, 39, 279-85.
[11] Martin and Yeh, H. 1965. Yield predictions for 1965 wheat, oats and barely in Manitoba. Canadian Journal of Agricultural Economic. 13: 306-309.
[12] Mohan Naidu. G., (2015). Selection of appropriate growth model for projection of sugarcane area, production and productivity of Andhra Pradesh. International Journal Agricultural Statistical Science. Vol. 11, No. 1, pp. 215-218.
[13] Rajarathinam, A., Parmar, R. S. and Vaishnav P. R. 2010. Estimating Models for Area, Production and Productivity Trends of Tobacco (Nicotiana tabacum) Crop for Anand Region of Gujarat State, India. J. App. Sci., 10: 2419-25.
[14] Rimi, R. H., S. H. Rahman, S. Karmakar and S. G. Hussain, (2009). Trend analysis of climate change and investigation on its probable impacts on rice production at Sathkhira, Bangladesh. Pak. J. Meteorol., 6: 37-50.
[15] Srinivasa Rao, V and Srinivasulu, R. (2006). Growth comparisons of turmeric up to 2020 AD. The Andhra Agricultural Journal. 53 (1&2): 108-109.
Author Information
  • Department of Statistics, Govt. Arts College (Affiliated Bharathiar University), Coimbatore, India

  • Department of Statistics, Govt. Arts College (Affiliated Bharathiar University), Coimbatore, India

Cite This Article
  • APA Style

    M. Sundar Rajan, M. Palanivel. (2018). Application of Regression Models for Area, Production and Productivity Growth Trends of Cotton Crop in India. International Journal of Statistical Distributions and Applications, 4(1), 1-5. https://doi.org/10.11648/j.ijsd.20180401.11

    Copy | Download

    ACS Style

    M. Sundar Rajan; M. Palanivel. Application of Regression Models for Area, Production and Productivity Growth Trends of Cotton Crop in India. Int. J. Stat. Distrib. Appl. 2018, 4(1), 1-5. doi: 10.11648/j.ijsd.20180401.11

    Copy | Download

    AMA Style

    M. Sundar Rajan, M. Palanivel. Application of Regression Models for Area, Production and Productivity Growth Trends of Cotton Crop in India. Int J Stat Distrib Appl. 2018;4(1):1-5. doi: 10.11648/j.ijsd.20180401.11

    Copy | Download

  • @article{10.11648/j.ijsd.20180401.11,
      author = {M. Sundar Rajan and M. Palanivel},
      title = {Application of Regression Models for Area, Production and Productivity Growth Trends of Cotton Crop in India},
      journal = {International Journal of Statistical Distributions and Applications},
      volume = {4},
      number = {1},
      pages = {1-5},
      doi = {10.11648/j.ijsd.20180401.11},
      url = {https://doi.org/10.11648/j.ijsd.20180401.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijsd.20180401.11},
      abstract = {Computing the growth of any entity over a time period is important for understanding the past behaviour and for future planning. ‘Compound growth rate’ is one of the frequently used methods for calculating the growth rate models. Among the statistical study was carried out on different growth models viz., linear, quadratic, cubic, exponential, compound, logarithmic, inverse, power, growth and S-curve models to project the area, production and productivity cotton crop in India for 1951 to 2013. The study revealed that through all models exhibited significant; the cubic model is the best fitted, for its highest adjusted R2 on increasing future projection trends with respect to area, production and productivity of cotton in India.},
     year = {2018}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Application of Regression Models for Area, Production and Productivity Growth Trends of Cotton Crop in India
    AU  - M. Sundar Rajan
    AU  - M. Palanivel
    Y1  - 2018/01/19
    PY  - 2018
    N1  - https://doi.org/10.11648/j.ijsd.20180401.11
    DO  - 10.11648/j.ijsd.20180401.11
    T2  - International Journal of Statistical Distributions and Applications
    JF  - International Journal of Statistical Distributions and Applications
    JO  - International Journal of Statistical Distributions and Applications
    SP  - 1
    EP  - 5
    PB  - Science Publishing Group
    SN  - 2472-3509
    UR  - https://doi.org/10.11648/j.ijsd.20180401.11
    AB  - Computing the growth of any entity over a time period is important for understanding the past behaviour and for future planning. ‘Compound growth rate’ is one of the frequently used methods for calculating the growth rate models. Among the statistical study was carried out on different growth models viz., linear, quadratic, cubic, exponential, compound, logarithmic, inverse, power, growth and S-curve models to project the area, production and productivity cotton crop in India for 1951 to 2013. The study revealed that through all models exhibited significant; the cubic model is the best fitted, for its highest adjusted R2 on increasing future projection trends with respect to area, production and productivity of cotton in India.
    VL  - 4
    IS  - 1
    ER  - 

    Copy | Download

  • Sections