高野 温子

Abstract Digital extraction of label data from natural history specimens along with more efficient procedures of data entry and processing is essential for improving documentation and global information availability. Herbaria have made great advances in this direction lately. In this study, using optical character recognition (OCR) and named entity recognition (NER) techniques, we have been able to make further advancements towards fully automatic extraction of label data from herbarium specimen images. This system can be developed and run on a consumer grade desktop computer with standard specifications, and can also be applied to extracting label data from diverse kinds of natural history specimens, such as those in entomological collections. This system can facilitate the digitization and publication of natural history museum specimens around the world.

Abstract Species delimitation has long been a subject of controversy, and there are many alternative concepts and approaches used to define species in plants. The genus Amana (Liliaceae), known as ”East Asian tulips” has a number of cryptic species and a huge genome size (1C = 21.48–57.35 pg). It also is intriguing how such a spring ephemeral genus thrives in subtropical areas. However, phylogenetic relationships and species delimitation within Amana are challenging. Here we included all species and 84 populations of Amana, which are collected throughout its distribution range. A variety of methods were used to clarify its species relationships based on a combination of morphological, ecological, genetic, evolutionary and phylogenetic species concepts. This evidence supports the recognition of at least 12 species in Amana. Moreover, we explored the complex evolutionary history within the genus and detected several historical hybridization and introgression events based on phylogenetic trees (transcriptomic and plastid), phylonetworks, admixture and ABBA‐BABA analyses. Morphological traits have undergone parallel evolution in the genus. This spring ephemeral genus might have originated from a temperate region, yet finally thrives in subtropical areas, and three hypotheses about its adaptive evolution are proposed for future testing. In addition, we propose a new species, Amana polymorpha, from eastern Zhejiang Province, China. This research also demonstrates that molecular evidence at the genome level (such as transcriptomes) has greatly improved the accuracy and reasonability of species delimitation and taxon classification.

Abstract Herbarium specimens are dried plants mounted onto paper. They are used by a limited number of researchers, such as plant taxonomists, as a source of information on morphology and distribution. Recently, digitised herbarium specimens have begun to be used in comprehensive research to address broader issues. However, some specimens have been misidentified, and if used, there is a risk of drawing incorrect conclusions. In this study, we successfully developed a system for identifying taxon names with high accuracy using an image recognition system. We developed a system with an accuracy of 96.4% using 500,554 specimen images of 2171 plant taxa (2064 species, 9 subspecies, 88 varieties, and 10 forms in 192 families) that grow in Japan. We clarified where the artificial intelligence is looking to make decisions, and which taxa is being misidentified. As the system can be applied to digitalised images worldwide, it is useful for selecting and correcting misidentified herbarium specimens.