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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 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(10): 3136-3146
DOI: https://doi.org/10.20546/ijcmas.2018.710.363


Nonlinear Modeling of Area and Production of Sugarcane in Tamil Nadu
Dinesh Kumar*, Bishvajit Bakshi and V. Manjunath
Department of Agricultural Statistics, Applied Mathematics and Computer Sciences, UAS, GKVK, Bengaluru-65, Karnataka, India
*Corresponding author
Abstract:

The present investigation was carried out to model the trend of area and production of sugarcane in Tamil Nadu. It was obtained by using the secondary data of area and production over a period of 30 years (1984-85 to 2014-15). For this purpose, Different nonlinear models such as Logistic, Gompertz, Rational, Gaussian, Weibull, Hoerl and Sinusoidal models were employed. Levenberg-Marquardt technique was used to obtain the estimates of the unknown parameters of the nonlinear regression models. To select a best fitted model for the area and production of sugarcane in Tamil Nadu, the model adequacy statistics such R2, RMSE, MAE and residual assumption tests such as Runs test, Shapiro-Wilks test and Durbin-Watson test were carried out. For area of sugarcane, it was found that Logistic model had the lowest Root Mean Square Error (27.770), Mean Absolute Error (18.737) and the highest R2 value (74.7 per cent). Hence, Logistic model is the most suitable among the fitted nonlinear model which can be used for further trend analysis on the area under sugarcane. For production of sugarcane, Gaussian model had the lowest Root Mean Square Error (2.604), Mean Absolute Error (2.760) and the highest R2 value (78.2 per cent). Hence, Gaussian model is the most suitable among the fitted nonlinear model which can be used for further trend analysis on the production of sugarcane.


Keywords: Nonlinear models, R2, Root mean square error, Mean absolute error, Durbin-Watson statistic, Levenberg-Marquardt technique, Shapiro-Wilks statistic
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How to cite this article:

Dinesh Kumar, P., Bishvajit Bakshi and Manjunath, V. 2018. Nonlinear Modeling of Area and Production of Sugarcane in Tamil Nadu.Int.J.Curr.Microbiol.App.Sci. 7(10): 3136-3146. doi: https://doi.org/10.20546/ijcmas.2018.710.363