Publications des scientifiques de l'IRD

Lorieul T., Pearson K. D., Ellwood E. R., Goeau H., Molino Jean-François, Sweeney P. W., Yost J. M., Sachs J., Mata-Montero E., Nelson G., Soltis P. S., Bonnet P., Joly A. (2019). Toward a large-scale and deep phenological stage annotation of herbarium specimens : case studies from temperate, tropical, and equatorial floras. Applications in Plant Sciences, 7 (3), p. e1233 [14 p.]. ISSN 2168-0450.

Titre du document
Toward a large-scale and deep phenological stage annotation of herbarium specimens : case studies from temperate, tropical, and equatorial floras
Année de publication
2019
Type de document
Article référencé dans le Web of Science WOS:000461823400007
Auteurs
Lorieul T., Pearson K. D., Ellwood E. R., Goeau H., Molino Jean-François, Sweeney P. W., Yost J. M., Sachs J., Mata-Montero E., Nelson G., Soltis P. S., Bonnet P., Joly A.
Source
Applications in Plant Sciences, 2019, 7 (3), p. e1233 [14 p.] ISSN 2168-0450
Premise of the Study Phenological annotation models computed on large-scale herbarium data sets were developed and tested in this study. Methods Herbarium specimens represent a significant resource with which to study plant phenology. Nevertheless, phenological annotation of herbarium specimens is time-consuming, requires substantial human investment, and is difficult to mobilize at large taxonomic scales. We created and evaluated new methods based on deep learning techniques to automate annotation of phenological stages and tested these methods on four herbarium data sets representing temperate, tropical, and equatorial American floras. Results Deep learning allowed correct detection of fertile material with an accuracy of 96.3%. Accuracy was slightly decreased for finer-scale information (84.3% for flower and 80.5% for fruit detection). Discussion The method described has the potential to allow fine-grained phenological annotation of herbarium specimens at large ecological scales. Deeper investigation regarding the taxonomic scalability of this approach is needed.
Plan de classement
Sciences du monde végétal [076] ; Etudes, transformation, conservation du milieu naturel [082]
Description Géographique
ETATS UNIS ; GUYANE FRANCAISE ; ZONE TEMPEREE ; ZONE TROPICALE ; ZONE EQUATORIALE
Localisation
Fonds IRD [F B010075504]
Identifiant IRD
fdi:010075504
Contact