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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
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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.2019.8(4): 161-172
DOI: https://doi.org/10.20546/ijcmas.2019.804.017


Comparison of Pre-harvest Forecast Models of Kharif Rice using Weather Parameters in Valsad District of Gujarat State
K.B. Banakara1, Amaresh2*, R. Manjula2 and H.R. Pandya1
1Department of Agricultural Statistics, Navsari Agricultural University, Navsari, Gujarat – 396 450, India
2Department of Agricultural Statistics, Applied Mathematics and Computer Sciences, University of Agricultural Sciences, Bengaluru, Karnataka – 560 065, India
*Corresponding author
Abstract:

The growth of Indian economy mainly depends on agriculture sector as it accounts 18 percent of national GDP. Agriculture sector was one of the main area to impact by climate change. Pre-harvest forecast based on weather parameters plays very important role in developing countries. Rice is the most significant principal food in India which play fundamental role in day-to-day requisite of diet. In the current study statistical crop modeling was engaged to provide forecast in advance. In this paper discriminant function analysis and logistic regression techniques were used for estimating average rice yield for Valsad district in south Gujarat. The weather indices were developed for the years from 1990 to 2012 and utilized for model construction. The cross validation of the developed forecast model were confirmed using data of the years 2013 to 2016. 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 Valsad district, Logistic regression analysis is found better as compared to Discriminant function for pre harvest forecasting of rice crop yield.


Keywords: Weather indices, Discriminant function, Logistic Regression, Forecast
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How to cite this article:

Banakara, K.B., Amaresh, R. Manjula and Pandya, H.R. 2019. Comparison of Pre-harvest Forecast Models of Kharif Rice using Weather Parameters in Valsad District of Gujarat State.Int.J.Curr.Microbiol.App.Sci. 8(4): 161-172. doi: https://doi.org/10.20546/ijcmas.2019.804.017