Plant Voxel Generator (PlantVG): a low-cost semi-automated method for creating voxel models of plant cells

Lodging, the structural failure of herbaceous stems due to abiotic factors like wind, significantly reduces crop yield and is a major challenge to global food security. Improving lodging resistance requires enhancing the stem’s tissue material properties, a complex, high-level phenotype difficult to correlate directly with the genome. To address this, plant scientists must investigate lower- and intermediate-level phenotypes, such as cellular microstructure, which determine the tissue’s stiffness and strength. Current methods for phenotyping cellular microstructure, such as using micro computed tomography for generating 3D computational models, are often cost-prohibitive and resource-intensive, limiting accessibility for many researchers. This study introduces the Plant Voxel Generator (PlantVG), a novel, user-friendly computational tool that provides an alternative, low-cost method for creating fully three-dimensional (3D) voxel finite element models of the cellular microstructure of homogeneous parenchyma regions of herbaceous stem. PlantVG leverages standard optical microscopy images to probabilistically construct a 3D model. The tool employs image processing to calculate cell length distributions and transverse cell morphology, then uses a Normal Cumulative Distribution Function to generate staggered cell end-cap locations, and finally generates the 3D voxel array with fillets at the cell end-caps. This approach allows researchers to generate an unlimited number of parametric 3D in silico models from a single pair of stem’s longitudinal and transverse microscope images. PlantVG represents a significant advancement by making the link between stem cellular microstructure and tissue material properties accessible and scalable. These generated models can be used to perform detailed sensitivity studies, enabling researchers to develop quantitative response curves that correlate intermediate-level cellular phenotypes with higher-level tissue properties, ultimately supporting the development of more effective genomic strategies to engineer stronger, more resilient stems.