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Journal of Pharmacognosy and Phytochemistry

Journal of Pharmacognosy and Phytochemistry

Vol. 7, Issue 6 (2018)

Development of multivariate statistical Rice yield prediction model for Raipur district

Author(s):

Avinash Yadu, Anil Patel, Shweta Gautam and Shraddha Rawat

Abstract:
The farmers profit is decided by the weather and climatic conditions, climate determines what crops the farmers can grow and weather influences the yield. An attempt has been made in this paper to study the effect of vital weather parameters on Rice yield and to develop a multivariate statistical model for yield forecast of Raipur district Chhattisgarh. On basis of 15 years (2000-2015) weather and rice production 4 types of models have been developed using SPSS software. Result revealed that model 4 was the highest R2 value 0.97, which describes the 97% variability in rice yield due to weather parameters i.e. maximum temperature of 1st week after sowing, minimum temperature of 13th week after sowing, minimum temperature of 2nd week and maximum temperature of 5th week after sowing. This may be due to more weather factors involved in the Model 4, instead of any other models.

Pages: 2404-2406  |  982 Views  202 Downloads


Journal of Pharmacognosy and Phytochemistry Journal of Pharmacognosy and Phytochemistry
How to cite this article:
Avinash Yadu, Anil Patel, Shweta Gautam and Shraddha Rawat. Development of multivariate statistical Rice yield prediction model for Raipur district. J Pharmacogn Phytochem 2018;7(6):2404-2406.

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