Abstract
The assessment of growth rate of disease is considered as an important parameter for near accurate estimation of disease severity as well as plant life to maximize the yield. The selection of most appropriate method to identify the severity and growth rate of disease is considered as a necessity of agriculturist. The involvement of engineering presimulation technique is one form available in the current methodologies that allows the prediction and estimation of growth rate of disease in appropriate direction. The current study emphasizes on presimulation technique adopted for the assessment of growth rate of Tikka disease on Groundnut crop. The presimulation technique is based on the assortment and selection of artificial data sets. The assortment of artificial data sets is done based on the real data sets collected from the Groundut crop field. Image processing technique in C# language platform is used to create the artificial data sets. These data sets are prepared for both with and without fungicidal applications. A novel algorithm is proposed to effectively predict the rate of increase of Tikka disease using image processing techniques.
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Singh, M., Singh, B.P., Rewar, E. (2019). Analysis of Growth Rate of Tikka Disease Using Image Processing. In: Nath, V., Mandal, J. (eds) Proceedings of the Third International Conference on Microelectronics, Computing and Communication Systems. Lecture Notes in Electrical Engineering, vol 556. Springer, Singapore. https://doi.org/10.1007/978-981-13-7091-5_45
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DOI: https://doi.org/10.1007/978-981-13-7091-5_45
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