The visual and tactile examination of plant leaves is a standard method for identifying disease in crops and horticultural products. However, such an approach can be highly subjective and is dependent on the skills of the examiners. Writing in the International Journal of Computational Vision and Robotics, a team from Egypt describes a new approach to plant leaf disease detection using deep learning on a mobile device. The team's tests against a standard database of diseased leaf images showed their system to be capable of up to 98% diagnostic accuracy. The process is rapid and showcases the sophisticated computational power available in modern mobile phones for this kind of intensive task.