Discrimination of Annonaceae using herbarium leaf reflectance spectra under limited sample size conditions

Herbarium collections offer an unparalleled archive of plant biodiversity, but their use for species identification through spectral data remains constrained by uncertain effects of preservation histories. This study assesses whether a single herbarium specimen can reliably represent its species based on its leaf reflectance spectrum, despite variations in age, geographic origin, or conservation method. We scanned herbarium specimens of different ages and geographic distribution of 14 species of the pantropical Annonaceae. In addition, we used a second dataset of 9 species where some specimens were conserved in alcohol prior to drying and some not. We used five supervised classification models frequently used for high-dimensional data such as spectroscopy. All models achieved high accuracy (>80%) when trained on multiple specimens per species. However, when using only one specimen per species, accuracy varied substantially depending on the taxon. Alcohol preservation prior to drying had little impact on classification success. Our findings demonstrate that herbarium specimens often retain a strong taxonomic signal in their spectra, however, inter-individual variability affects accuracy in some taxa. These findings confirm the usefulness of herbarium spectroscopy as a non-destructive tool for species identification and offer a promising avenue for digitizing historical biodiversity data into high-dimensional trait space.