Disease sniffing robots to apps fixing plant diseases: applications of artificial intelligence in plant pathology—a mini review

Abstract

The recent advancements in artificial intelligence (AI) and machine learning have wide applications in plant pathology with sensors, drones, robots and intelligent monitoring systems. Computer vision based phenotyping of plant stress, diagnostics and severity assessment of plant diseases has gained momentum in horticultural and field crops. Internet of things based on networking sensors for biomarkers of disease like volatile organic compounds are being used for early detection and prediction of plant diseases and host-pathogen interaction studies. Unmanned arial vehicles are employed for phenotyping orchards for precise application of plant protection chemicals. Smartphone based field diagnostics are gaining popularity across the world especially in the remote locations where the laboratory diagnostics of diseases is difficult. AI in plant pathology is still at its infancy. Integration of AI and augmented reality will enhance the accuracy and automation for remote diagnostics of plant diseases and precision plant protection. The “self sufficient, disease free, perfect plant” concept will soon become reality with the help of plant-robot bio-hybrids. This mini review explores the present status of AI technologies in plant pathology and tries to find answers for the questions like what are the common platforms used, which are the diseases where technology is applied, what are the challenges and the future prospects.