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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.
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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 2019: 96.39
Index Copernicus ICI Journals Master List 2019 - IJCMAS--ICV 2019: 96.39
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.2021.10(4): 653-670
DOI: https://doi.org/10.20546/ijcmas.2021.1004.066


Weather Based Yield Prediction and PDI Model for Grape Production Quality Forecast in Tamil Nadu using Mathematical Modelling
A. Eswari*
Department of Physical Sciences & Information Technology, Agricultural Engineering College & Research Institute, Tamil Nadu Agricultural University, Coimbatore - 641 003,Tamil Nadu, India
*Corresponding author
Abstract:

In this paper, we developed the weather based yield prediction model between weather factors such as maximum temperature (Tmax), minimum temperature (Tmin), relative humidity (RH1), (RH2) and rainfall (RF) observed at Grapes Research station, Theni district during the summer and winter season from 2016 to 2020. This model is built using multiple regression analysis to explain the relationship between grape yield as well as climatic parameters and quality assessment. Our findings indicate that the models provide an effective way to the evaluate and forecast. Furthermore, we show that there exits many factors like downy mildew and powdery mildew to affect the quality of grape, our yield prediction model provide superior performance for grape analysis. Furthermore, the PDI model was developed to forecasting disease incidence; yield of grape by using climatic scenario. A comparison of our estimated results with the numerical simulation and experimental result available is provided.


Keywords: Primary and secondary infection, Grape yield, Climatic variables, Mathematical modelling, Disease incidence; Simulation
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How to cite this article:

Eswari, A. 2021. Weather Based Yield Prediction and PDI Model for Grape Production Quality Forecast in Tamil Nadu using Mathematical Modelling.Int.J.Curr.Microbiol.App.Sci. 10(4): 653-670. doi: https://doi.org/10.20546/ijcmas.2021.1004.066