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 |
The model of forewarning about the infection of red rot disease in sugarcane was studied and observations were recorded at fortnight interval starting from June upto December during each year of experimentation. The maximum infection was recorded during 2nd fortnight of July while minimum (1.4%) was at 1st fortnight of June. Using the original data on the response variable i.e. infection of red rot disease, the simple linear regression model was fitted with fortnightly as explanatory variable and describe the severity of the infection of red rot disease during the fortnight. The value of multiple correlations for red rot disease was 0.7159. We also include meteorological factors i.e. maximum temperature, minimum temperature (0C), relative humidity percentage (at 7.00 hrs and 14.00 hrs) and sunshine hours in the model. This model provides the severity of infection of the above mentioned disease forewarning. Meteorological factors played an important role in seasonal infection, distribution and disease build up. It is difficult to give a direct cause and effect relationship between any single factor and disease incidence because the impact of meteorological factors is usually compounded.
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