National Academy of Agricultural Sciences (NAAS)
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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 2018: 95.39 NAAS RATING 2020: 5.38 |
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.
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