Zhang et al. (2024) designed subsoiling shovels whose tip and handle contours follow the longitudinal profile curves of mole-cricket (Gryllotalpa orientalis) forefoot claw toes and reported, entirely from EDEM discrete-element simulations on a calibrated South China red-soil model, that the best design (BS2) reduces tillage draft force by 9.25% and energy consumption by 10.58% relative to a conventional shovel, while a fourth-toe design (BS4) saves force but consumes 14.37% more energy and a manual hybrid (BS5) performs worst among the bionic designs. No physical test of any of these shovels exists, the simulations rest on one discretization (6 mm minimum particle radius) and one soil condition, and the contour selection was manual. The open problem is to establish by soil-bin and/or field experiments whether these claw-toe-contour designs genuinely reduce draft force and energy in deep tillage; complementary open directions are to quantify how sensitive the claimed reductions are to discrete-element modeling choices and how far they generalize beyond the single calibrated red-soil condition (soil types, moisture, compaction, and stony or heterogeneous conditions), and to explore replacing the manual contour selection with a systematic optimization of the claw-toe design space. No work is known to date that physically validates these specific designs, so the problem remains open.

Background

Subsoiling is deep tillage, typically to about 30 cm or more, that breaks up the plough pan — the compacted, low-porosity layer that forms beneath the annually tilled topsoil under machinery traffic and that impedes water infiltration and root growth. Subsoiling shovels (also called subsoilers or deep-loosening shovels) are the soil-engaging parts that do this work; because they operate deep in the soil, they experience high draft force (the horizontal force needed to pull the tool through the soil), which dominates the traction energy demand of the operation. Red soils of hilly South China are particularly difficult: they are sticky, cohesive, and form hard plough pans, so reducing subsoiling draft force and energy there is an active agricultural-engineering topic.

One established strategy is engineering bionics: copying the geometry of body parts of soil-digging animals onto tillage tools. The mole cricket (Gryllotalpa orientalis) is a common biological model because its forefoot claw toes are efficient digging structures. Earlier work in this lineage includes discrete-element simulation of bionic subsoilers derived from such claw-toe contours (Sun et al. 2018), EDEM simulation of a low-resistance animal-bionic device on red soil (Sun et al. 2020), and field experiments that validated a biomimetic shark-inspired subsoiler (Wang et al. 2020) — the latter showing that bionic subsoilers of other inspirations can pass physical field validation, which has not yet been done for mole-cricket-contour subsoiling shovels on red soil.

The standard analysis tool is the discrete element method (DEM), implemented in commercial software such as EDEM: soil is modeled as thousands of particles whose contacts follow a calibrated model — here Hertz–Mindlin contact (a standard elastic–frictional contact model for colliding particles), with JKR adhesion for the loose tillage layer and a bonding variant for the compacted plow pan in which adjacent particles are bonded together to represent cohesive, compacted soil. In the source's model the tillage-layer particles are not all spherical: single spherical particles and tetrahedral, linear, and triangular combinations of spherical particles (multi-sphere clumps) are employed to approximate bulky, columnar, strip, and flaky soil particles. Contact parameters are calibrated against simple physical measurements — in this paper the soil accumulation (repose) angle of red soil, the slope angle of a poured soil pile — tuned with a steepest-climbing parameter search and a Box–Behnken experimental design (a response-surface design of statistical experiments). A DEM soil bin — a simulated tank of layered soil, here an 18 cm cultivated layer over a compacted plough pan — is then dragged past a tool model, and the time-averaged draft force on the tool and the kinetic energy imparted to soil particles are compared between candidate designs. (In agricultural engineering a soil bin also denotes the physical analogue: an indoor test channel filled with prepared soil through which a tool is drawn.) Smaller particles give more accurate soil behavior but cost far more computation, so practitioners choose a minimum radius (6 mm here) as a compromise; how strongly the results depend on this and other discretization choices is rarely characterized.

Within this setting, Zhang et al. (2024) (the source work for this problem) extracted the contour curves of the four claw toes of the mole cricket forefoot, used toes 1–3 to shape the tips and handles of three bionic subsoiling shovels (BS1–BS3), derived BS4 from the short fourth toe, and manually combined the best-performing BS2 tip with the BS3 handle to form BS5. In EDEM simulation on the calibrated red-soil model (soil bin 1300 × 800 × 500 mm, forward speed 0.83 m/s, plowing depth 30 cm, minimum particle radius 6 mm), the conventional shovel (CS) needed an average total tillage resistance of 391.410 N; BS2 needed 355.216 N (a 9.25% reduction, with 11.43% less force at the tip) and consumed 10.58% less energy; BS4 saved tip force but increased handle force and consumed 14.37% more energy; and BS5, the manual hybrid, experienced the largest total resistance among the bionic designs. The authors concluded that BS2 is the best choice, suitable for well-conditioned soil without excessive stones and debris, and that research on bionic designs to reduce tillage resistance should continue.

What the paper does not do is the subject of this problem. No soil-bin or field experiment tests any of the shovels themselves (the only physical experiments in the paper calibrate soil parameters); all force, energy, and soil-disturbance comparisons come from one discretized simulation of one calibrated soil condition; the contour selection that produced the BS4 and BS5 tradeoffs was manual rather than the result of any systematic search; and durability questions — wear, clogging, structural strength, manufacturability of the curved contours — are never evaluated. These gaps define a coherent follow-on objective: bring the claw-toe bionic subsoiling shovel from a simulation claim to a physically validated design, with the robustness of that claim and a systematic exploration of the contour design space as complementary open directions.

Problem Statement

The problem is to establish by soil-bin and/or field experiments whether the mole-cricket claw-toe contour bionic subsoiling shovels of Zhang et al. (2024) genuinely reduce draft force and energy in deep tillage of South China red soil, a claim that currently rests entirely on discrete-element simulation. The core open problem, left by the source study, is physical validation: test the bionic shovels — at least BS2, on which the strongest claim rests, and ideally the full set BS1-BS5 — against a common subsoiling shovel in controlled soil-bin experiments and/or field tests on South China red soil with its characteristic cultivated layer over a compacted plough pan, measuring draft force, energy consumption, and soil disturbance under matched operating conditions (the source simulations used 0.83 m/s forward speed and 30 cm depth), and determine whether the simulated BS2 reductions — 9.25% in draft force and 10.58% in the source's energy metric, the average kinetic energy imparted to soil particles — are reproduced, reporting the force agreement and the energy agreement separately and quantified between simulation and experiment, each with its metric stated (the experimental energy measure to be defined explicitly, for example draft work per unit distance in a soil-bin test or fuel or power consumption in a field test); checking the adverse BS4/BS5 tradeoffs, which requires testing BS4 and BS5.

Two complementary directions are also left open by the source study. Robustness and generalization: how sensitive the claimed force and energy reductions are to discrete-element modeling choices — particle radius and size distribution, particle shape, contact model, and calibration procedure — and how far they extend beyond the single calibrated red-soil condition, across soil types, moisture contents, compaction states, and stony or debris-rich heterogeneous conditions; here the source's own envelope statements are not consistent — Section 3.2 recommends BS2 for 'well-conditioned soil and no excessive stones and debris', while Section 3.3 deems BS2 'more effective and better suited for scenarios with more soil stones and high energy consumption'. Systematic design optimization: whether a systematic exploration of the claw-toe contour design space (tip and handle curves and their combinations) can replace the manual contour selection behind BS1-BS5 and yield designs that reduce draft force and energy without the force-energy tradeoffs observed in BS4 and BS5 — an outcome the source's own data do not guarantee, given the force-energy decoupling already visible in BS3 (-6.55% force but only -0.49% energy) — and how the practical feasibility of such geometries would be assessed: manufacturability of the curved contours, wear, clogging, and structural strength under realistic operating loads.

References

  1. Lei Zhang, Xiaowei Wang, Jianneng Chen, Haiyang Wang, Yonggan Cao. Analysis and Optimization of Low-Resistance Animal Bionic Subsoiling Shovel Based on EDEM. Agriculture 2024, 14(11), 2046. DOI 10.3390/agriculture14112046. https://doi.org/10.3390/agriculture14112046
  2. Lei Zhang, Yibin Zhai, Jianneng Chen, Zhien Zhang, Shouzhi Huang. Optimization design and performance study of a subsoiler underlying the tea garden subsoiling mechanism based on bionics and EDEM. Soil and Tillage Research 2022, 220, 105375. DOI 10.1016/j.still.2022.105375. https://doi.org/10.1016/j.still.2022.105375
  3. Jiyu Sun, Yueming Wang, Yunhai Ma, Jin Tong, Zhijun Zhang. DEM simulation of bionic subsoilers (tillage depth >40 cm) with drag reduction and lower soil disturbance characteristics. Advances in Engineering Software 2018, 119, 30-37. DOI 10.1016/j.advengsoft.2018.02.001. https://doi.org/10.1016/j.advengsoft.2018.02.001
  4. Jianfeng Sun, Huaming Chen, Zaiman Wang, Zhiwu Ou, Zhou Yang, Zhu Liu, Jieli Duan. Study on plowing performance of EDEM low-resistance animal bionic device based on red soil. Soil and Tillage Research 2020, 196, 104336. DOI 10.1016/j.still.2019.104336. https://doi.org/10.1016/j.still.2019.104336
  5. Yueming Wang, Na Li, Yunhai Ma, Jin Tong, Wilhelm Pfleging, Jiyu Sun. Field experiments evaluating a biomimetic shark-inspired (BioS) subsoiler for tillage resistance reduction. Soil and Tillage Research 2020, 196, 104432. DOI 10.1016/j.still.2019.104432. https://doi.org/10.1016/j.still.2019.104432
  6. Xiaoyang Wang, Jinguang Li, Junyan Liu, Le Yang, Fancheng Dai, Chanjuan Long, Lijun Zhao. Composite Biomimetic Multi-Subsoiler for Drag Reduction and Wear Resistance Simulation and Experimental Validation. Biomimetics 2025, 10(12), 793. DOI 10.3390/biomimetics10120793. https://doi.org/10.3390/biomimetics10120793
  7. Francisco Garibaldi-Márquez, Ernesto Martínez-Reyes, Cornelio Morales-Morales, Lenin Ramos-Cantú, Mirna Castro-Bello, Armida González-Lorence. Subsoiler Tool with Bio-Inspired Attack Edge for Reducing Draft Force during Soil Tillage. AgriEngineering 2024, 6(3), 2678-2693. DOI 10.3390/agriengineering6030156. https://doi.org/10.3390/agriengineering6030156
  8. Shi-cheng Xu, Gui-xiang Tao, Shu-juan Yi, Song Wang, Yu-hang San. Design and testing of bionic winged deep-loosening shovel for a strip tillage deep-loosening fertilization machine. INMATEH Agricultural Engineering 2025, 77, 550-562. DOI 10.35633/inmateh-77-45. https://doi.org/10.35633/inmateh-77-45
  9. Kui Zhang, Yong-Ying Zhang, Xinliang Zhao, Yun Zhao, Xin Feng, Qi Wang, Jinwu Wang. Design and Test of a Bionic Auxiliary Soil-Crushing Device for Strip-Tillage Machines. Agriculture 2025, 15(9), 944. DOI 10.3390/agriculture15090944. https://doi.org/10.3390/agriculture15090944
  10. Shengbo Lin, Hongyan Sun, Guangen Yan, Kexin Que, Sijia Xu, Zhong Tang, Guoqiang Wang, Jiali Li. Structural Design and Analysis of Bionic Shovel Based on the Geometry of Mole Cricket Forefoot. Agriculture 2025, 15(8), 854. DOI 10.3390/agriculture15080854. https://doi.org/10.3390/agriculture15080854
  11. Lei Zhang, Haolong Chen, Yibin Zhai, Jianneng Chen. Optimization and Experiment of a Subsoiling Mechanism for Hilly and Mountainous Farmland Based on the Discrete Element Method. AgriEngineering 2025, 7(10), 349. DOI 10.3390/agriengineering7100349. https://doi.org/10.3390/agriengineering7100349
  12. Tang Tian, Gang Zhao, Liqing Chen, Jie Liu, Yuxuan Liang. Novel composite biomimetic digging shovel inspired by the claws of mole and mole cricket. Journal of Terramechanics 2026, 123, 101136. DOI 10.1016/j.jterra.2026.101136. https://doi.org/10.1016/j.jterra.2026.101136
  13. Haochao Tan, Congcong Shen, Junlong Ma, Chunlin Wu, Liming Xu, Shuai Ma. The reduction of energy consumption and soil disturbance mechanisms in trenching using biomimetic blades. Computers and Electronics in Agriculture 2025, 230, 109887. DOI 10.1016/j.compag.2024.109887. https://doi.org/10.1016/j.compag.2024.109887
  14. Peichen Chu, Honglei Zhang, Zhao Ding, Meng Fang, Zhan Su, Zhong Tang. Research Progress on Wear Mechanisms and Surface Engineering of Agricultural Soil Contact Components for Tillage and Seeding. Lubricants 2026, 14(8), 293. DOI 10.3390/lubricants14080293. https://doi.org/10.3390/lubricants14080293