Algorithms can help detect Xylella fastidiosa - scientists

Thanks to satellites, probabilistic models, algorithms, remote sensing and citizen participation "we have the tools to greatly improve the effectiveness of surveillance against Xylella fastidiosa", French researcher Samuel Soubeyrand has said at a major conference on the plant pathogen.
Scholars from all over the world presented sophisticated Xylella fastidiosa surveillance and early detection experimental tools at the final virtual meeting of the XF-ACTORS Project, a EU-funded research program entirely devoted to the plant pathogen.
Tomàs Poblete of the University of Melbourne illustrated the results of the use of hyperspectral images and a machine learning algorithm.
In addition to digital tools, "citizens could play a very important role in detecting diseased plants", said Alexander Mastin of the University of Salford (UK).