Follow
International Journal of Current Microbiology and Applied Sciences (IJCMAS)
IJCMAS is now DOI (CrossRef) registered Research Journal. The DOIs are assigned to all published IJCMAS Articles.
Index Copernicus ICI Journals Master List 2018 - IJCMAS--ICV 2018: 95.39 For more details click here
National Academy of Agricultural Sciences (NAAS) : NAAS Score: *5.38 (2019) [Effective from January 1, 2019]For more details click here

Login as a Reviewer

Indexed in



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

See Guidelines to Authors
Current Issues

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 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(1): 2180-2183
DOI: https://doi.org/10.20546/ijcmas.2018.701.262


Yield Prediction of Wheat at Pre-Harvest Stage Using Regression Based Statistical Model for 8 District of Chhattisgarh, India
U.K. Diwan*, H.V. Puranik, G.K. Das and J.L. Chaudhary
Department of Agrometeorology, Indira Gandhi Krishi Vishwavidyalaya,Raipur-492012 (CG), India
 
*Corresponding author
Abstract:

Pre harvest crop yield forecast is required for storage, pricing, marketing, import, export etc. Weather is the main factor which affects crop yield. Variability in weather causes the losses in the yield. Use of weather can be done for crop production forecast. Weather plays an important role in crop growth. Therefore model based on weather parameters can be provide reliable forecast in advance for crop yield. In this study, the focus was on the development crop yield forecast (CYF) model through stepwise linear regression technique using weather variables and historic crop yield. The model use, maximum and minimum temperature, rainfall, relative humidity and sunshine hours during crop growing period and long term yield data of wheat crop. Yield prediction was carried out for Wheat (Triticum aestivum) in 8 districts of Chhattisgarh state during 2015-16. The rabi wheat yield and weather data from 1971 to 2012 for 8 districts of Chhattisgarh state were used to develop wheat yield forecast model. From the CYF models it can be inferred that among all the weather variables, temperature (maximum & minimum) and relative humidity play key role as predictor in all the districts. The models were validated with the actual yield for the 2013 and 2014. Accuracy of these models tested with coefficient of determination (R2).


Keywords: Regression technique, Wheat, Weather, Temperature, CYF
Download this article as Download

How to cite this article:

Diwan, U.K., H.V. Puranik, G.K. Das and Chaudhary, J.L. 2018. Yield Prediction of Wheat at Pre-Harvest Stage Using Regression Based Statistical Model for 8 District of Chhattisgarh, India.Int.J.Curr.Microbiol.App.Sci. 7(1): 2180-2183. doi: https://doi.org/10.20546/ijcmas.2018.701.262