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Top1. Introduction
With the ever-increasing population, there are many problems impacting the environment unfavorably. Food and Water shortage is a major issue which is getting worse in the future due to the increase in population. Global warming is another significant problem that affects the environment, especially the agriculture sector, adversely. In any country, agriculture is mainly dependent on the quantity and quality of plants. Keeping trees and plants healthy can reduce food scarcity and help prevent environmental degradation. A plant disease is defined as “anything that prevents a plant from performing to its maximum potential”. Three components are necessary for a disease to occur in any plant system namely, a susceptible host plant, a virulent pathogen, and a favorable environment. A plant can be caught by a disease when all these three components are present at the same time and the same is shown in Figure 1 (University of Nebraska, 2021).
Various plant diseases occur frequently on a large scale which causes huge economic losses as the crop produced is very less as compared to the amount of crop harvested. According to the Food and Agricultural Organization of the United Nations, between 20 and 40 percent of yield is reduced due to damage wrought by plant diseases as shown in Figure 2. In Africa and Asia, more than 50% of population depend on agriculture production for employment. Thus, in agriculture, plant disease detection and early diagnosis of the same has become a crucial and important task. Moreover, it is very difficult for the farmers to diagnose the disease with the help of observations only. Earlier existing methods used by Plant Pathologists is simply plant disease detection by naked eye. But, for this observation technique many experts are required who should continuously monitor the plant, making it costly and erroneous. Also, in most of the countries, all the farmers do not have the adequate facilities or even contacts with human experts. Hence, we require some automatic tool or technique to better detect the changes caused due to the disease in a plant.
Figure 2.
Percentage of crop loss vs crop yield
To achieve better disease management and yields loss prediction, accurate and automatic identification of plant disease method or a technique is needed to produce higher accuracy using less time. Advances in artificial intelligence (AI), graphical processing units (GPUs), and image processing can expand and improve the results of accurate plant disease detection. As leaf is the most susceptible part of a plant, it gets affected more easily by the diseases as compared to the other parts of a plant. In fact, almost 70% of plant diseases appears on leaves only. In plants, some general symptoms seen are brown and yellow spots, early and late scorch, and others are fungal, viral, and bacterial diseases. The technique should possess good observational skills for detecting characteristic symptoms of any diseases as most plant diseases generate various symptoms in the visible spectrum.