Plant microbiota that colonizes different compartments of the plant host plays a key-role in nutrient availability, growth promotion and plant health. Understanding and managing plant microbiota could allow promoting beneficial microbial communities and reducing the impacts of detrimental microbes. While metabarcoding analyses targeting different regions of the 16S rRNA have recently gained popularity to describe large microbial communities of different ecosystems, these cultureindependent surveys may have presented a depth bias and failed in detecting microbial populations with low concentrations. The diversification of culture conditions together with a high throughput identification by mass spectrometry system (MALDI-TOF), i.e. a culturomics approach, can greatly increase the number of detected species (Lagier et al., 2015). Microbial culturomics has been shown to reveal new bacterial repertoires non covered by metabarcoding sequencing in the human gut microbiome study (Lagier et al., 2015). In some cases, culture techniques detected even more bacterial species. In addition, a better understanding of the ecology of the plant-associated microbiota and the interactions between members of the community may require the use of synthetic microbial communities. Using rice as a plant model we aim at describing the spatiotemporal dynamics of rice endophyte microbiota. The 16S rRNA metabarcoding approach will be combined with culturomics approaches in order to compare both molecular and 'cultivable' diversity and evaluate their potential complementarity. Our objectives are to (i) establish a culture collection, (ii) develop a MALDI-TOF database for routine identification of bacterial isolates and (iii) compare the metabarcoding approach and the culturomics approach in terms of characterization of microbial community diversity. We isolated more than 2000 bacterial colonies from superficially rice disinfected tissues collected in two rice fields of Camargue in the Provence r