To provide a scientific basis and technical support for agroforestry management practices, such as interrow configuration and soil water and fertilizer management, a stratified excavation method was performed both to explore the fine-root spatial distribution and niche differentiation and to quantify the below-ground interspecific competition status of 3-, 5-, and 7-year-old apple (Malus pumila M.)–soybean (Glycine max L. Merr.) intercropping systems and monocropping systems. The fine roots of older trees occupied a larger soil space and had both a greater fine-root biomass density (FRMD) and a greater ability to reduce the FRMD of soybean, but this ability decreased with the distance from the apple tree row. Similarly, the FRMD of apple trees was also adversely affected by soybean plants, but this effect gradually increased with a decrease in tree age or with the distance from the tree row. Compared with that of the 3- and 5-year-old monocropped apple trees, the FRMD of the 3- and 5-year-old intercropped apple trees increased in the 40–100 cm and 60–100 cm soil layers, respectively. However, compared with that of the 7-year-old apple and soybean monocropping systems, the FRMD of the 7-year-old intercropped apple trees and soybean plants decreased in each soil layer. Compared with that of the corresponding monocropped systems, the fine-root vertical barycenter (FRVB) of the intercropped apple trees displaced deeper soil and that of the intercropped soybean plants displaced shallower soil. Furthermore, the FRVB of both intercropped apple trees and intercropped soybean plants displaced shallower soil with increasing tree age. Intense below-ground interspecific competition in the 3-, 5-, and 7-year-old apple–soybean intercropping systems occurred in the 0–40 cm soil layer at distances of 0.5–0.9, 0.5–1.3, and 0.5–1.7 m from the apple tree row, respectively.

The under-canopy light environment in agroforestry systems is a key limiting factor for the growth of intercropped crops. However, the impact of under-canopy light heterogeneity on crop yield remains unclear. This study focused on 4 (Y4)-, 6 (Y6)-, and 8 (Y8)-year-old apple tree/soybean intercropping systems with root barriers, measuring under-canopy photosynthetically active radiation, yield, and yield components at different phenological stages of soybean, and establishing a quantitative relationship between light heterogeneity and soybean yield. In the apple/soybean intercropping system, the spatial heterogeneity of accumulated photosynthetically active radiation (APAR) is greatest in Y6, with the APAR divided into five categories parallelized along the tree rows. Y4, which had the least spatial APAR heterogeneity, was divided into three categories. The APAR was split into two classes in Y8. The seed number per plant and 100-seed weight of soybean decreased with the increase in tree age. Compared to Y4, yields of Y6 and Y8 treatments decreased by 22.6% and 46.2%, respectively. The reduction in APAR showed a negative effect on yield and its components of soybean, especially in Y4. The shading intensity and under-canopy light heterogeneity jointly constrained the intercropped soybean yield; this effect was gradually strengthened with increasing tree age. Different measures should be taken according to different tree ages and soybean growth stages in intercropping systems to reduce the adverse effects of under-canopy light on soybean yield.

The canopy shading model is widely used in agroforestry systems. However, the canopy shading model cannot be verified by the measured shading distribution of an apple tree due to the uneven ground and adjacent apple trees. This paper measures the spatial‒temporal distribution of the shading of apple trees based on the similarity principle of parallel solar light combined with 3D printing technology to improve the canopy shading model. The following results are drawn: (1) The current widely used canopy shading model does not consider the effect of the canopy penumbra, resulting in poor simulation accuracy in the shading distribution compared to the actual measurement; (2) The effect of canopy penumbra causes the deflection of sunlight. Hence, the paper presents the deflection equation of sunlight with statistically defined parameters derived using measured data of the shading distribution. The deflection equation of sunlight is added to the improved canopy shading model. The improved model can accurately simulate the shading distribution of an apple tree, and the simulation accuracy exceeds 94.12% when compared with the shading distribution of an apple tree; (3) The improved canopy shading model is applied to simulate the spatial‒temporal distribution of the shading of apple trees in a conventional arrangement (4 m × 5 m), and the simulation accuracy exceeds 89%. Thus, the improved canopy shading model can be applied to simulate the spatial‒temporal distribution of shading of apple trees.