Identification of Box Scale and Root Placement for Paddy-Wheat Root System Architecture Using the Box Counting Method

Root fractal analysis is instrumental in comprehending the intricate structures of plant root systems, offering insights into root morphology, branching patterns, and resource acquisition efficiency. We conducted a field experiment on paddy-wheat root systems under varying nitrogen fertilizer strategies to address the need for quantitative standardization in root fractal analysis. The study evaluated the impact of nitrogen fertilizer heterogeneity on root length and number. We established functional relationships and correlations among root fractal characteristics and root length across different box dimension scales and various root placement angles at 2.5, 5, 10, 20, 40, and 80 box dimension scales. Results indicated that nitrogen fertilizer had a limited impact on paddy-wheat axile roots, with a coefficient of variation below 0.35 among samples. Box dimension scale influenced 3D fractal dimension (FD) and fractal abundance (FA), with strong correlations (>78%) among 3D fractal features and low sample errors (<6%). The linear correlation coefficient exceeded 72% between 3D FA and root length and 50% between FA and FD. Different axile root placement angles significantly impacted planar fractal results, particularly at a 10 degrees angle. This stability was maintained throughout the sampling period, with high correlation coefficients (>0.76 for FA and >0.5 for FD) and low sample errors (<1.5% for FA and <4.5% for FD). In conclusion, for calculating the 3D fractal characteristics of paddy-wheat axile roots during the seedling stage, box dimension scales of 2.5, 5, 10, 20, 40, and 80, as well as 2, 5, 10, 20, 50 and 100 and 3, 6, 12, 24, 48 and 96, were suitable. When computing the planar fractal characteristics of paddy-wheat axile roots during this stage, a 10 degrees placement angle between axile root systems yields lower errors. These findings enhance root quantification methods, standardize root analysis, and promote the comparability of crop root system fractal data across different varieties and regions, thereby advancing root-related research.