Abstract
Advance computing techniques Capitalized as Mobile base identification of cotton diseases and control of pest, using Automatic system for rural area farmers. This technology base farm management system is Capitalized to identify and analyze the diseases, profitability, sustainability and safety for the land resource. The sharing of plant physical condition knowledge on a regional basis can support both crop manufacture and trade. In this model of work, a new computing technology has been proposed to help the farmer to take a superior decision concerning several aspects of the crop manufacturing process. Suitable evaluation and diagnosis of crop diseases in the field is very critical for the increased production. Foliar is the most important fungal disease of cotton and occurs in all growing Indian cotton regions. In this work we express technological strategies using mobile captured symptoms of cotton leaf spot images and classify the diseases using neural network. This system can identify diseases and provide pest recommendation to farmers.
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References
Chidambaram P (2007) Integrated disease management to reduce yield losses in quality cotton. pp 99–109
Li H, Ji R, Zhang J, Yuan X, Hu K, Qi L (2011) WEB-based intelligent diagnosis system for cotton diseases control. IFIP Adv Info Commun Technol 346:483–490
Zhang YC, Mao HP, Hu B, Xili M (2007) Features selection of cotton disease leaves image based on fuzzy feature selection techniques. In: Proceedings of IEEE, Beijing, China, pp 124–129
Hayat SA, Abdullah A, Muhammad, Chaudary A, Malik YJ, Gillani W “Automatic Cleansing and classification on Cotton leaves, bolls and flowers using CMYK color splitting”
Bernardes AA, Rogeri JG, Marranghello N, Pereira AS, Araujo AF, João Manuel RS (2011) Tavares. Identification of Foliar Diseases in Cotton Crop. SP, Brazil
Gulhane VA, Gurjar AA (2011) Detection of diseases on cotton leaves and its possible diagnosis. J Image Process(IJIP) 5(5):591–598
Meunkaewjinda A, Kumsawat P, Attakitmongcol K, Sirikaew A (2008) Grape leaf disease detection n from color imaginary using hybrid intelligent system. In: Proceedings of ECTI-CON
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Revathi, P., Hemalatha, M. (2013). SMS Based HPCCDD Algorithm for the Identification of Leaf Spot Diseases. In: S, M., Kumar, S. (eds) Proceedings of the Fourth International Conference on Signal and Image Processing 2012 (ICSIP 2012). Lecture Notes in Electrical Engineering, vol 221. Springer, India. https://doi.org/10.1007/978-81-322-0997-3_5
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DOI: https://doi.org/10.1007/978-81-322-0997-3_5
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