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Historical development of plant disease detection methods

Gavrish Mikhail Konstantinovich  (Graduate student, Federal State Budgetary Educational Institution of Higher Education "Novosibirsk State Technical University")

Aleinikov Alexander Fedorovich  (doctor of technical sciences, professor, Federal State Budgetary Educational Institution of Higher Education "Novosibirsk State Technical University")

One of the biggest challenges facing humanity is increasing the global productivity of the food industry to feed a growing world population. First of all, this concerns the industrialization of the production of food of plant origin. It should be noted that a significant part of the crop is lost due to pests and diseases. Most diseases (about 80%) are caused by fungi. In world practice, the problem of establishing the type of fungal diseases and its degree of damage at an early stage of diagnosis has not been solved. Microbiological research is a laborious method and takes a lot of time; methods based on the polymerase chain reaction require the organization of special laboratory premises and the availability of highly qualified personnel; methods for analyzing multispectral images obtained from unmanned aerial vehicles and based on neural networks show a good percentage of accuracy in determining the disease, but have certain disadvantages. Algorithms of an intelligent decision support system are in demand and are of particular interest due to the increased informatization and industrialization of society.

Keywords:plant disease, diagnosis of plant disease, fungal plant disease, methods for determining plant disease.

 

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Citation link:
Gavrish M. K., Aleinikov A. F. Historical development of plant disease detection methods // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2022. -№07. -С. 33-38 DOI 10.37882/2223-2966.2022.07.04
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