Speeding up the collection and integration of raw botanical observation data is a crucial step towards a sustainable development of agriculture and the conservation of biodiversity. Initiated in the context of a citizen sciences project, the main contribution of this paper is an innovative collaborative workflow focused on image-based plant identification as a mean to enlist new contributors and facilitate access to botanical data. Since 2010, hundreds of thousands of geo-tagged and dated plant photographs were collected and revised by hundreds of novice, amateur and expert botanists of a specialized social network. An image-based identification tool - available as both a web and a mobile application - is synchronized with that growing data and allows any user to query or enrich the system with new observations. An important originality is that it works with up to five different organs contrarily to previous approaches that mainly relied on the leaf. This allows querying the system at any period of the year and with complementary images composing a plant observation. Extensive experiments of the visual search engine as well as system-oriented and user-oriented evaluations of the application show that it is already very helpful to determine a plant among hundreds or thousands of species. At the time of writing, the whole framework covers about half of the plant species living in France (2200 species), which already makes it the widest existing automated identification tool (with its imperfections).