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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 2018: 95.39
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2018: 95.39
For more details click here

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Original Research Articles

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

Int.J.Curr.Microbiol.App.Sci.2018.7(6): 3410-3422
DOI: https://doi.org/10.20546/ijcmas.2018.706.400


Pre-Harvest Forecasting of Rice Yield for Effective Crop Planning Decision in Surat District of South Gujarat, India
K. B. Banakara1*, Y. A. Garde2, R. R. Pisal3 and B. K. Bhatt4
1Department of Agricultural Statistics, Navsari Agricultural University, Navsari,
Gujarat – 396 450, India
2Department of Agricultural Statistics, College of Agriculture, Navsari Agricultural University, Waghai, Dang, Gujarat – 394730, India
3Department of Agronomy, College of Agriculture, Navsari Agricultural University, Waghai, Dang, Gujarat – 394730, India
4Department of Agricultural Statistics, ASPEE College of Horticulture and Forestry, Navsari Agricultural University, Navsari, Gujarat – 396 450, India
*Corresponding author
Abstract:

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.


Keywords: Weather indices; MLR techniques; Discriminant function analysis; Forecast
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How to cite this article:

Banakara K. B., Y. A. Garde, R. R. Pisal and Bhatt B. K. 2018. Pre-Harvest Forecasting of Rice Yield for Effective Crop Planning Decision in Surat District of South Gujarat.Int.J.Curr.Microbiol.App.Sci. 7(6): 3410-3422. doi: https://doi.org/10.20546/ijcmas.2018.706.400