International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 110 | Views: 291

Research Paper | Mathematics | India | Volume 5 Issue 9, September 2016 | Popularity: 6.3 / 10


     

Pre-Harvest Forecasting Model of Mustard Cropyield Basis on Weather Parameters in Gandhinagar District of Gujarat

C. M. Chaudhari, M. B. Thaker, N. V. Patel


Abstract: The crop productiondirectly or indirectly depends on Weather parameters. Therefore, Weather is an important factor for agriculture practice. Present investigation was done to examine three types of model using meteorological weather variables and mustard crop yield (Productivity) inGandhinagar district of Gujarat state in India. Data were used for mustard crop during the time period 1980-81 to 2014-15. The step wise regression analysis was employed for mustard crop to determine a set of explanatory variable, which satisfied the equation and explain maximum variation in yield. Average mustard yield was considering as dependent variable and weather variables like Maximum and Minimum Temperature in degree Celsius, Relative Humidity in morning and evening in percentage, Sun-Shine hours per day and Annual Rainfall in mm as independent variables. Finally, the model which has provided the earliest forecast with high coefficient of determination, t value and minimum percentage deviation from the observed mustard average yields of Gandhinagar district was consider as suitable pre harvest forecast model.


Keywords: Weather variables, Mathematical approach


Edition: Volume 5 Issue 9, September 2016


Pages: 1421 - 1427



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C. M. Chaudhari, M. B. Thaker, N. V. Patel, "Pre-Harvest Forecasting Model of Mustard Cropyield Basis on Weather Parameters in Gandhinagar District of Gujarat", International Journal of Science and Research (IJSR), Volume 5 Issue 9, September 2016, pp. 1421-1427, https://www.ijsr.net/getabstract.php?paperid=ART20161936, DOI: https://www.doi.org/10.21275/ART20161936



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