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1.9 Case Study in Plant Disease Identification Using AI Technology—Tomato and Potato Crops

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The traditional method of plant disease identification through visual observations of the symptoms of plant leaves leads to a significant high degree of inaccuracy. Today modern tools incorporate graphical processing unit which includes ML-based algorithms which precisely detect the plant disease and assist the pathologist to easily identify the disease. Machine learning is the subset of AI that uses algorithms that predicts experience. Nowadays, a technology named DL using a large amount of processing layers made exponential growth in AI. The common diseases of tomato and potato crops are blackleg, early blight, late blight, stem rot, and ring rot. Figure 1.9 and Figure 1.10 show the late blight and leaf spot of tomato crop and the early blight and stem rot of potato crop, respectively.

Figure 1.9 Late blight and leaf spot of tomato crop.


Figure 1.10 Early blight and stem rot of potato crop.

Apps are given for farmers to know the current status of the crop and get an opinion from the experts [25].

The Digital Agricultural Revolution

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