Oil bodies (OBs) are seed-specific lipid storage organelles that allow the accumulation of neutral lipids that sustain plantlet development after the onset of germination. OBs are covered with specific proteins embedded in a single layer of phospholipids. Using fluorescent dyes and confocal microscopy, we monitored the dynamics of OBs in living Arabidopsis (Arabidopsis thaliana) embryos at different stages of development. Analyses were carried out with different genotypes: the wild type and three mutants affected in the accumulation of various oleosins (OLE1, OLE2, and OLE4), three major OB proteins. Image acquisition was followed by a detailed statistical analysis of OB size and distribution during seed development in the four dimensions (x, y, z, and t). Our results indicate that OB size increases sharply during seed maturation, in part by OB fusion, and then decreases until the end of the maturation process. In single, double, and triple mutant backgrounds, the size and spatial distribution of OBs are modified, affecting in turn the total lipid content, which suggests that the oleosins studied have specific functions in the dynamics of lipid accumulation.The seed is a complex, specific structure that allows a quiescent plant embryo to cope with unfavorable germinating conditions and also permits dissemination of the species. To achieve these functions, seeds accumulate reserve compounds that will ensure the survival of the embryo and fuel the growth of the plantlet upon germination. Accumulation of lipids occurs in many eukaryotic cells and is a rather common means of storing carbon and energy. Lipid droplets (LDs) can be found in all eukaryotes, such as yeast (Saccharomyces cerevisiae;

We review a set of recent multiscale imaging techniques, producing high-resolution images of interest for plant sciences. These techniques are promising because they match the multiscale structure of plants. However, the use of such high-resolution images is challenging in the perspective of their application to high-throughput phenotyping on large populations of plants, because of the memory cost for their data storage and the computational cost for their processing to extract information. We discuss how this renews the interest for multiscale image processing tools such as wavelets, fractals and recent variants to analyse such high-resolution images.

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