Design, Construction, and Evaluation of a Spatial Depth Measurement System for Subsoiler in Sugarcane Fields

ماشین های کشاورزی

Article 4, Volume 15, Issue 2 - Serial Number 36, June 2025, Pages 193-209   

Document Type: Research Article

DOI: 10.22067/jam.2024.87809.1242

Authors

N. Loveimi^{* 1}; A. Azizi¹; A. Kaab^{2, 3}; A. Neisi^{4, 5}

¹Agricultural Engineering Research Department, Khuzestan Agricultural and Natural Resources Research and Education Center, AREEO, Ahvaz, Iran

²Department of Agricultural Machinery Engineering, Faculty of Agriculture, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

³Mechanization and remote sensing expert of Imam Khomeini Sugarcane Agro-Industrial Company, Ahvaz, Iran

⁴Department of Soil Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran

⁵Head of Water, Soil and Meteorology Department of Imam Khomeini Sugarcane Agro-Industrial Company, Ahvaz, Iran

Abstract

Introduction
Subsoiling is a critical tillage operation for many crops, particularly sugarcane, due to the impact of agricultural machinery traffic and its significance in managing heavy-textured and compacted soils. Given the extensive size of sugarcane fields and the time-intensive nature of subsoiling operations, the application of intelligent control techniques for monitoring and managing these processes is of considerable importance. Currently, subsoiling operations are monitored using manual gauges. This approach involves collecting a limited number of samples per hectare, typically after the operation is completed, which makes it nearly impossible to implement real-time corrections. To address this limitation, the development and implementation of a depth measurement system offer a promising solution. Such a system enables real-time observation of working depth by both the operator, via an on-screen display, and by a remote observer through an online platform. This capability allows for immediate adjustments during the operation, ensuring greater precision and efficiency. Furthermore, by integrating recorded depth data with geospatial information, it becomes possible to generate detailed maps illustrating depth variations across the field. These maps can serve as valuable tools for further evaluations, such as performance monitoring in areas where subsoiling depth deviates from the desired range, either being too shallow or excessively deep. This technological advancement has the potential to significantly enhance the accuracy and effectiveness of subsoiling operations in modern agricultural practices.
Materials and Methods
This study focused on the design, development, and evaluation of a depth measurement system for a subsoiler attached to a track-type tractor, specifically tailored for sugarcane fields. The system not only provided real-time depth display but also recorded the location and transmitted it online. The research employed three distinct depth measurement techniques and was conducted using a randomized complete block design with split plots. The main plots are the three depth measurement techniques: based on the angles of the driving profiles of the subsoiler shanks (T₁), the laser distance measurement method (T₂), and the ultrasonic distance measurement method (T₃), and sub-plots are depth ranges at three levels: 0-30 cm (R₁: surface range), 30-60 cm (R₂: mid-range), and 60-90 cm (R₃: deep range). Initially, we calculated the absolute difference between the depths recorded by the system and those measured manually with a rod at each location. Following this, we analyzed key statistical indicators, including the average, standard deviation, and the minimum and maximum of errors, for comparison.
Results and Discussion
The results showed that the depth measurement error was significantly influenced by the technique employed. The angle technique yielded the lowest average error of 1.91 cm, while the ultrasonic technique resulted in the highest average error of 3.83 cm. Across all depth ranges, statistical indicators for depth error were significant. Specifically, within these ranges, the deep range exhibited an average depth error of 2.33 cm, and the surface range had an average error of 3.65 cm. Statistical analysis revealed that only indices related to minimum and maximum errors for interactions between factors were significant. The lowest minimum error value (0.05 cm) was observed with the angle technique at deeper depths, whereas the highest minimum error (0.34 cm) occurred with ultrasonic measurements at shallower depths on surfaces. Similarly, maximum errors followed this trend: The lowest maximum error (3.21 cm) was associated with angle measurements at deeper depths, while ultrasonic measurements on surfaces yielded a higher maximum error (8.63 cm). Both laser and ultrasonic techniques consistently demonstrated greater errors across all three depth ranges compared to angle-based methods. This discrepancy may be attributed to inaccuracies inherent in rangefinders when their beams encounter obstacles like clods or pits during field operations. Notably, as working depths increased across all measurement techniques, errors in depth measurement decreased significantly due to reduced vibrations from subsoiler devices at greater depths, thereby minimizing vibration-related inaccuracies.
Conclusion
The results indicate that the depth measurement technique based on the angles of the driving profiles of subsoiler shanks exhibits superior accuracy in determining the working depth of subsoilers mounted on tractors, particularly during sugarcane field operations. The laser distance meter technique ranked second in terms of accuracy, while the ultrasonic distance meter method demonstrated the least precision. Notably, as working depths increased, reduced vibrations during operation were observed, leading to enhanced accuracy in depth calculations across all techniques. This improvement is attributed to decreased mechanical disturbances at greater depths. Overall, measurements within deeper ranges achieved higher levels of accuracy compared to those at shallower surface ranges. This trend suggests that operational conditions and device stability play significant roles in optimizing measurement accuracy.

Keywords

Angle sensor; Depth monitoring; Laser distance meter; Precision farming; Ultrasonic distance meter

References

1. Ahmadizadeh, M., & Charaghi, Sh. (2017). Design and construction of depth measurement system and measurement of shear strength in sub-soiling operations and the importance of its application in monitoring the depth control of sub-soil. 4^th International Conference on Agricultural and Environmental Engineering with Sustainable Development Approach, Shiraz. (in Persian).
2. Al-Adawi, S. S., & Reeder, R. C. (1996). Compaction and subsoiling effects on corn and soybean yield and soil physical properties. ASAE, 39(5), 1641-1649. https://doi.org/10.13031/2013.27680
3. Alimardani, R., Shahrbanunjad, M., & Borghee, A. (1998). Designing and construction a system for measuring the working depth of different plows. Iranian Journal of Agricultural Sciences, 29(1), 19-26. (in Persian).
4. Anonymous. (2021). Agricultural crop cultivation model program. Agricultural Research, Education and Extension Organization, Ministry of Jihad Agriculture. (in Persian).
5. Anonymous. (2023). Sugarcane production technology in Iran. Guidelines for the production of agricultural products. Ministry of Jihad Agriculture. (in Persian).
6. Bonaiuto, V., & Zanela, A. (2022). Improvement of the Sensor Capability of the NAO Robot by the Integration of a Laser Rangefinder. Applied System Innovation, 5(6), 105. https://doi.org/10.3390/asi5060105
7. Carullo, A., & Parvis, M. (2001). An ultrasonic sensor for distance measurement in automotive applications. IEEE Sensors Journal, 1(2), 143. https://doi.org/10.1109/JSEN.2001.936931
8. Cassel, D. K., & Edwards, E. C. (1985). Effects of subsoiling and irrigation on corn production. Soil Science Society of America Journal, 49(4), 996-1001. https://doi.org/10.2136/sssaj1985.03615995004900040041x
9. Cheong, L. R. N., Kwong, K. F. K., & Preez, C. C. D. (2009). Soil compaction under sugarcane cropping and mechanization in Mauritius. South African Journal of Plant and Soil, 26, 199-205. https://doi.org/1080/02571862.2009.10639955
10. Fallahikoshali, E., Aghkhani, M., & Bayati, M. (2015). Design, construction and evaluation of the automatic depth control device for tillage tools. Iranian Journal of Biosystems Engineering, 46(2), 117-123. (in Persian). https://doi.org/10.22059/ijbse.2015.55669
11. Kaab, A., Sharifi, M., & Mobli, H. (2019). Analysis and optimization of energy consumption and greenhouse gas emissions in sugarcane production using data envelopment analysis. Iranian Journal of Biosystems Engineering, 50(1), 19-30. (in Persian). https://doi.org/10.22059/ijbse.2018.251593.665035
12. Kiani, S., Kamgar, S. T., & Raoufat, M. (2010). Automatic on-line depth control of seeding units using a non-contacting ultrasonic sensor. International Journal of Natural and Engineering Sciences, 6(2), 39-42.
13. Lou, S., He, J., Lu, C., Liu, P., Li, H., & Zhang, Z. (2021). A Tillage Depth Monitoring and Control System for the Independent Adjustment of Each Subsoiling Shovel. Actuators, 10, 250. https://doi.org/10.3390/act10100250
14. Mahohi, A., & Khatinzadeh, H. (2021). Evaluation of Subsoiling Depth of Fields of Ratoon Cane on some Soil and Plant Indices. Applied Soil Research, 9(3), 134-146. (in Persian).
15. Mansourirad, D. (1993). Tractors and agricultural machines. Bouali Sina Publications. (in Persian).
16. Mckyes, E., Nego, S., Douglas, F., Taylor, F., & Raghavan, G. S. U. (1979). The effect of machinery traffic and tillage on the physical properties of clay and on yield of silage corn. Journal of Agricultural Engineering Research, 24, 143- 148. https://doi.org/10.1016/0021-8634(79)90048-9
17. Moradinejad, N. (2017). Designing and implementing the electro-hydraulic tension adjustment system for the Massey Ferguson tractor using a new electronic control valve. International Journal of Biosystems Engineering, 48(1), 155-163. (in Persian). https://doi.org/10.22059/ijbse.2017.61575
18. Naseri, H., Gholamiparshekuhi, M., Ranjbar, I., & Mohammad Zamani, D. (2022). Evaluation of the effect of reduced and conventional tillage methods on machine performance parameters, soil properties and quantitative and qualitative efficiency of sugarcane. Agricultural Mechanization and Systems Research, 80(22), 17-32. (in Persian). https://doi.org/10.22092/amsr.2021.353026.1373
19. Pankhurst, C. E., Magarey, R. C., Sirling, G. R., Blair, B. L., Bell M. J., & Garside, A. L. (2003). Management practices to improve soil health and reduce the effects of detrimental soil biota associated with yield decline of sugarcane in Queensland, Australia. Soil and Tillage Research, 72, 125-137. https://doi.org/10.1016/S0167-1987(03)00083-7
20. Sharif-Nasab, H., Heydari, A., Mehdi-Niya, H., Sadegh Nejad, R., & Shahrbanunjad, M. (2014). Investigating and determining the effect of using deep tillage tools on physical and chemical properties of soil and wheat yield. Research report of Agricultural Engineering and Technical Research Institute. Agricultural Research, Education and Extension Organization. (in Persian).
21. Slowinska–Jurkiewicz, A. (1994). Change in structure and physical properties of soil during spring tillage operations. Soil and Tillage Research, 29, 397-407. https://doi.org/10.1016/0167-1987(94)90111-2
22. Solhjo, A., Dehghanian, S. A., Sepaskhah, A., & Niromand Jahormi, J. (2006). Effect of subsoiling and Irrigation Fr3equencies on Soil Physical Properties and Sugarbeet Yield. Journal of Agricultural Engineering Research, 6(4), 131-144. (in Persian).
23. TaheriGaravand, A., Asakereh, A., & Haghani, K. (2010). Energy elevation and economic analysis of canola production in Iran a case study: Mazandaran province. International Journal of Environmental Sciences, 1, 236- 243.
24. Torres, J. L. R., Pereira, M. G., Cunha, M. A., Martins, M. E., & Vieira, D. M. S. (2013). Physicochemical properties of soil and biomass in sugarcane harvesting systems. Agricultural Science Magazine, 56, 311-318. https://doi.org/10.4322/rca.2013.047
25. Tu, Y., Song, Y., Liu, F., Zhou, Y., Li, T., Zhi, S., & Wang, Y. (2022). An accurate and stable extrinsic calibration for a camera and a 1D laser range finder. IEEE Sensors Journal, 22(10), 9832-9842. https://doi.org/10.1109/JSEN.2022.3166243
26. Wang, Y., Jing, H., Zhang, D., Cui, T., Zhong, X., & Yang, L. (2018). Development and performance evaluation of an electric-hydraulic control system for subsoiler with flexible tines. Computers and Electronics in Agriculture, 151, 249-257. https://doi.org/10.1016/j.compag.2018.06.027