National Academy of Agricultural Sciences (NAAS)
|
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 |
In the Gujarat State, rice occupies about 7 to 8 per cent of the gross cropped area and accounts for about 14.00 per cent of the total food grain production. Pre harvest forecast may provide useful information to agriculturalists, administration offices and merchants. In the current study statistical crop modeling was engaged to provide forecast in advance harvesting for taking timely pronouncements. In this paper Multiple Linear Regression (MLR) Technique and Discriminant function analysis were derived for estimating average rice production for the district of Surat in south Gujarat. The weather indices were developed using correlation coefficient as weight toweekly weather parameters for the years from 1975 to 2009. The cross authentication of the developed forecast model were confirmed using data of the years 2010 to 2012. It was observed that value of Adj. R2 varied from 0.64 to 0.80 in different models. The study discovered that high value of Adj. R2 was obtained in the model and which indicated that it was appropriate forecast model than other models. Based on the outcomes in Surat district, MLR techniques found to be better than Discriminant function analysis for pre harvest forecasting of rice crop yield.
Citations |
 |
 |
 |
 |
