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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
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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(12): 2968-2972
DOI: https://doi.org/10.20546/ijcmas.2018.712.339


Arimax Models for Cotton Yield Forecasting in Haryana
Alisha, Sanjeev, Puneet Verma and Urmil Verma*
*Department of Mathematics & Statistics, CCS Haryana Agricultural University, Hisar-125004, India
*Corresponding author
Abstract:

Crop yield models are abstract presentation of interaction of the crop with its environment and can range from simple correlation of yield with a finite number of variables to the complex statistical models with predictive end. The pre-harvest forecasts are useful to farmers to decide in advance their future prospects and course of action. ARIMAX models have been fitted for cotton yield forecasting in Hisar, Fatehabad and Sirsa districts of Haryana. The models have been fitted using the time-series cotton yield data for the period 1980-81 to 2010-11 of Hisar and Sirsa districts and 1997-98 to 2010-11 of Fatehabad district. The fortnightly weather data have been utilized as input series from 1980-81 to 2016-17 for fitting/testing ARIMA with weather input i.e. ARIMAX models. Models have been validated for six-steps ahead i.e. 2011-12 to 2016-17, not included in the development of the models. The predictive performance of ARIMAX models were observed in terms of the percent deviations of cotton yield forecasts in relation to the observed yield(s). The ARIMAX models performed well in all time regimes for cotton yield forecasting in the districts under consideration.


Keywords: Autocorrelation function, Partial autocorrelation function, Stationarity, Invertibility, Fortnightly maximum temperature, Minimum Temperature, Rainfall, Sunshine hour and relative humidity and ARIMAX models
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How to cite this article:

Alisha, Sanjeev, Puneet Verma and Urmil Verma. 2018. Arimax Models for Cotton Yield Forecasting in Haryana.Int.J.Curr.Microbiol.App.Sci. 7(12): 2968-2972. doi: https://doi.org/10.20546/ijcmas.2018.712.339