Modeling and visualization of three-dimensional young apple tree root growth under different modes of drip irrigation

Roots absorb not only nutrients and water, but also chemically signal the state of soil nutrient and propagate the signal in soils to control physiological activities of above-ground plant organs such as stomata opening/closing, leaf blade expansion and fruit development. Therefore establishing and maintaining a healthy root system in the ground for normal development of stem, leaf and fruit is critical in crop production. But because most plant roots and growth environments are not visible, the spatial configuration and distribution of plant roots are difficult to map out. Plant visualization simulation provides quick visual effect for studying plant root growth behavior. Hence model simulation of three-dimensional plant root conformation and distribution in soils and computer visual expression are vital for the interpretation of the absorption and utilization of water and nutrient by root. This study simulated young apple tree root growth behavior under field conditions of different modes of drip irrigation. The study proposed the Otsu method to statistically analyze root distribution in space after root image partitioning. By using image processing library to obtain spatial distribution statistics matrix in Python language programming, a structure-function model was established for young apple tree root distribution under different modes of field drip irrigation. The Lynch root structure model was used as a prototype of the combined root structure-function model. Finally, three-dimensional visualization of young apple tree root growth was simulated by using the OpenAlea model. Using field young apple trees for verification, the results showed that the Otsu algorithm effectively segmented young apple tree root image data. The young apple tree root structure-functional model was established by combining general function-structure parameters and spatial distribution statistics matrix scientifically, and the model could scientifically