National Academy of Agricultural Sciences (NAAS)
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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 |
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.
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