Rapid character scoring and tabulation of large leaf-image libraries using Adobe Bridge

Premise: Digital image libraries are an integral part of specimen-based research. However, coding and extracting metadata for hundreds of specimens on a personal computer can be complex. In addition, most existing workflows require downsampling or platform switching and do not link character data directly to the images. Methods and Results: We demonstrate a method to code and embed into images the standard leaf architecture and insect-damage characters that are widely used in paleobotany. Using the visual file browser Adobe Bridge, customizable and searchable keywords can be applied directly and reversibly to individual full-resolution images, and the data can be extracted and formatted into a matrix using scripts. Conclusions: Our approach is intuitive and acts as a digital mimic and complement to the experience of sorting and analyzing specimens in-person. Keywords can be easily customized for other data types that require visual sorting using image libraries.