A repeatable scoring system for assessing Smartphone applications ability to identify herbaceous plants

Abstract

The ubiquity of Smartphone applications that aim to identify organisms, including plants, make them potentially useful for increasing people’s engagement with the natural world. However, how well such applications actually identify plants has not been compressively investigated nor has an easily repeatable scoring system to compare across plant groups been developed. This study investigated the ability of six common Smartphone applications (Google Lens, iNaturalist, Leaf Snap, Plant Net, Plant Snap, Seek) to identify herbaceous plants and developed a repeatable scoring system to assess their success. Thirty-eight species of plant were photographed in their natural habitats using a standard Smartphone (Samsung Galaxy A50) and assessed in each app without image enhancement. All apps showed considerable variation across plant species and were better able to identify flowers than leaves. Plant Net and Leaf Snap outperformed the other apps. Even the higher preforming apps did not have an accuracy above ~88% and lower scoring apps were considerably below this. Smartphone apps present a clear opportunity to encourage people to engage more with plants. Their accuracy can be good, but should not be considered excellent or assumed to be correct, particularly if the species in question may be toxic or otherwise problematic.