2024, Vol. 4, Issue 1, Part A
Use of artificial intelligence in plant pathology
Author(s): Alex Khalkho, AK Jain, Jayant Bhatt, Sushma Nema, Manisha Shyam, Kamini Bisht and Aditya Sahu
Abstract: Rapid development of new technologies like artificial intelligence (AI) provides a unique opportunity for developing automated systems for detection and diagnosis of plant diseases. Artificial intelligence (AI) was introduced in 1956, since then technology is developing but now emerging rapidly throughout the globe. In last few years, disease diagnosis is shifted from symptoms based diagnosis procedures to protein based or molecular based techniques. Different AI technologies like convolution neural network, artificial neural network and deep neural network have been successfully used for disease detection in rice, wheat, maize, cotton, tomato, peas, grapes, potato, cucumber, cassava, peach, mango, banana, apple, tea etc. Plant disease and pathogen detection by imaging sensors and image analysis is increasing rapidly. A recognition method based on visible spectrum image processing to detect symptoms of citrus greening disease on leaves was developed. A vision based novel transfer and deep learning technique for detecting symptoms of leaf scorch on leaves of Olive (Olea europaea) caused by Xylella fastidiosa with a true positive rate of 95.8±8% was also developed. Methods for disease diagnostics are still in the developmental stage. Computer vision based diagnostics and severity assessment of plant diseases has gained momentum in horticultural and field crops. Smartphone based field diagnostics are gaining popularity among the peoples engaged in farming systems. AI tools are so advanced that they can process huge data within seconds. Image based disease detection, sensor data fusion, precision agriculture and targeted treatments, disease prediction models, mobile applications, data bases and knowledge repositories will help for the development of AI driven solutions for farmers in the context of plant disease management.
Pages: 23-27 | Views: 489 | Downloads: 380Download Full Article: Click Here
How to cite this article:
Alex Khalkho, AK Jain, Jayant Bhatt, Sushma Nema, Manisha Shyam, Kamini Bisht, Aditya Sahu. Use of artificial intelligence in plant pathology. Int J Plant Pathol Microbiol 2024;4(1):23-27.