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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 (2020)
[Effective from January 1, 2020]
For more details click here

ICV 2018: 95.39
Index Copernicus ICI Journals Master List 2018 - 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(5): 3506-3511
DOI: https://doi.org/10.20546/ijcmas.2018.705.405


Weather Based Forewarning Model for Yellow Rust of Wheat in Scarcity Zone of Jammu & Kashmir
Indar Singh1, Vishal Gupta1, Kausar Fatima1*, V.K. Razdan1, Dechan Choskit1, Seethiya Mahajan1 and Satish Sharma2
1Division of Plant Pathology, Faculty of Agriculture, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Chatha 180 009, India
2Seed Multiplication Farm, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Chatha 180 009, India
*Corresponding author
Abstract:

A forewarning model of stripe rust of wheat for predicting the disease initiation in Jammu sub-tropics was developed by the analysis of disease severity data pertaining to the years from 2005-06 to 2012-13 obtained from AICRP research experiments available in the Division of Plant Pathology. The analyzed data was validated during rabi season 2014-16. Predicted severity by Gompertz model (1.93 to 55.93%) was very close to the observed values (1.14 to 57.66%) with a precision of 99.50 per cent from 1st to 14th SMW as compared to predicted estimate of 4.42 to 54.70 per cent by Logistic model having precision of 98.50 per cent in 2005-13. The prediction of disease severity through analyzed data of 2014-16 by using models (Logistic and Gompertz) revealed that Gompertz showed an accuracy of 99.60 per cent in which predicted severity was 2.47 to 57.60 per cent.


Keywords: Non-liner model, Prediction model, Yellow rust, Wheat
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How to cite this article:

Indar Singh, Vishal Gupta, Kausar Fatima, V.K. Razdan, Dechan Choskit, Seethiya Mahajan and Satish Sharma. 2018. Weather Based Forewarning Model for Yellow Rust of Wheat in Scarcity Zone of Jammu & Kashmir.Int.J.Curr.Microbiol.App.Sci. 7(5): 3506-3511. doi: https://doi.org/10.20546/ijcmas.2018.705.405