The application of information technology to diagnose postharvest diseases of apple

South Tyrol (northern Italy) produces around one million metric tons of apple fruit annually and contributes to almost 10% of the European apple harvest. Despite the availability of advanced storage technologies, postharvest diseases of apple may lead to the deterioration of quality and losses of fruit not only during the storage process but also in the course of packing, shipment and shelf-life. In order to decide on a strategy for damage control or to implement plant protection programs, it is crucially important to reliably determine the nature of plant diseases. Apart from the observation of macroscopic symptoms and the application of laboratory-dependent microscopic, microbiological and molecular methods, a variety of novel approaches for the detection of plant diseases and pathogens is being developed. The present study focuses on the potential of information technology to bring the diagnosis process closer to practitioners. Particular attention is paid to the application of computer vision techniques and use of decision support systems. We provide a review of existing implementations of computer-based tools to diagnose plant diseases and present an outline of the “DSSApple” research project, which focuses on the development of a decision support system for the determination of postharvest diseases of apples.