The automatic analysis of the images with algorithms of the ML/DL type (machine learning/deep learning) allows a good ability to recognize plants with some type of suffering. As described in deliverable D421 the accuracy of the various models is around 80%, and similarly the F1-score for diseased plants. In particular this means that the models have few false negatives (i.e. plants with some problems indicate as healthy). False negatives are evidently the worst cases from a farm management point of view, while false positives (plants without problems indicate as unhealthy) are more, but also less serious from a farm management point of view.