Disease Severity Diagnosis for Rice Using Fuzzy Verdict Method

M. Kalpana, L. Karthiba and A. V. Senthil Kumar
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M. Kalpana: Tamil Nadu Agricultural University, School of Post Graduate Studies
L. Karthiba: Tamil Nadu Agricultural University, Department of Pulses
A. V. Senthil Kumar: Hindusthan College of Arts and Science

A chapter in New Trends in Computational Vision and Bio-inspired Computing, 2020, pp 873-880 from Springer

Abstract: Abstract Rice (Oryza sativa L.) is susceptible to a number of diseases. Among them, sheath rot disease which is caused by Sarocladium oryzae (Gums & Hawks.) is the most devastating diseases and major challenge to rice cultivation. Use of Plant Growth Promoting Rhizobacteria (PGPR) for biocontrol viz., Pseudomonas fluorescents is an another disease management approach as it is the growth promotion and reduces disease in crops. Fuzzy Expert System with the algorithm Fuzzy Verdict Method is used to find the disease severity of rice. The Fuzzy expert system has three phases; they are fuzzification which is followed by Fuzzy Verdict Method and defuzzification phase. The fuzzification phase helps to change the crisp value into fuzzy value. The proposed algorithm helps to diagnosis the disease severity of rice crop with the input parameters Number of discoloured grains/panicle, Number of chaffy grains/panicle, Lesion Number/tiller, Lesion size (mm)-Length& width and Number of panicles infected/tiller, becomes simpler for farmers and scientist. Algorithm uses triangular membership function with mamdani’s interface. The fuzzy values are changed into crisp values using defuzzification phase. The algorithm was tested using Fuzzy tool box in MATLAB to diagnosis the disease severity of rice.

Keywords: Fuzzy logic; Fuzzy Verdict Method; Rice disease severity (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-41862-5_88

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DOI: 10.1007/978-3-030-41862-5_88

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