Pest and disease control is one of the main problems in today’s agriculture. One of the methods to control diseases and pests is to uniformly spray the pesticides over the crops, which requires high efficiency but is not economical, and it also poses the risk of side effects such as ground water contamination and adverse impact on wildlife and ecosystem.

  • Ebrahimi et al. (2017) developed a machine which helps to identify parasites in the green house environment through image processing. SVM method can be used for classification and targeting of parasites. The image processing methodology and SVM method having appropriate option of province and colour index proved to be successful for detection of objective with high efficiency.
  • Moshou et al. (2014) developed an effortless and economical optical gadget for remote ailment exposure, based on awning reflectance in numerous wavebands. They investigated the difference between healthy and ailing plants in early stages of yellow rust ailment, in field images that were obtained by placing a spectrograph at spray resonant point. Then, using intensity normalization we can decrease the spectral high variability caused by canopy architecture at different illumination levels. Quadratic discriminating model based on the reflectance of these wavebands classifies healthy and disease spectra with high success rate.

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