This paper describes the participation of Inria within the Pl@ntNet project at ImageCLEF2013 plant identification task. For the SheetAsBackground category (scans or photographs of leaves with a uniform background), the submitted runs used a multiscale triangle-based approaches, either alone or combined with other shape-based descriptors. For the NaturalBackground category (unconstrained photographs of leaves, flowers, fruits, stems,...), the four submitted runs used local features extracted using different geometric constraints. Three of them were based on large scale matching of individual local feature, while the last one used a Fisher vector representation. Metadata like the flowering date or/and plant identifier were successfully combined to the visual content. Overall the proposed methods performed very well for all categories and sub-categories.