Real-Time Measurement of In-Field Soil Surface Roughness Using Laser and Infrared Sensors

ماشین های کشاورزی

Articles in Press, Accepted Manuscript, Available Online from 03 June 2025   

Document Type: Research Article

DOI: 10.22067/jam.2024.90374.1300

Authors

N. Salehi Babamiri¹; H. Haji Agha Alizadeh^{* 1}; M. Dowlati²

¹Department of Biosystems Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran

²Department of Food Science and Technology, Tuyserkan Faculty of Engineering and Natural Resources, Bu-Ali Sina University, Hamedan, Iran

Abstract

Introduction
Soil surface roughness is an important factor in determining the intensity and quality of tillage operations, and obtaining accurate information essential for precision tillage. Using an inappropriate technique due to the lack of precise discrepancy detection can lead to increased time spent on analysis and potential damage. Generally, there are two methods for measuring soil surface roughness: contact and non-contact. Contact methods are less accurate for measuring the roughness of soft soil because they involve physical contact, which can partially disturb the soil. Most non-contact measurement methods are also performed in stop-and-go conditions, which increases measurement time and related analysis. The aim of this study is to measure soil surface roughness in real-time using optical sensors in the field. The accuracy and precision of two non-contact measurement methods will be compared to determine the best approach for precision tillage operations.
Materials and Methods
In the current research, a real-time soil surface roughness measurement system consisting of mechanical and electrical modules, data collection, and processing was built. The system performance was evaluated at different forward speeds and roughness categories, with two types of infrared and laser sensors. To assess the sensors’ accuracy, the collected data was compared against the pin gauge method, which served as the reference standard. The method exhibiting the least variation from this reference is considered to provide the most reliable data. Also, to further examine the accuracy of the sensors, the roughness data obtained from the sensor at various frequencies was compared against the roughness data obtained from the pin measuring device at the same level, resulting in a suitable curve plot. The interpretation of the obtained mathematical relationship indicates the precision of the sensor data.
Results and Discussion
The results obtained from the optical sensors were compared to the pin meter, used as the reference method, in both stationary and moving conditions. It was demonstrated that the optical sensors detect distance in the static state similarly to the reference pin meter. The calibration curve interpretation factor was 0.99 for the infrared sensor and 1 for the laser sensor, indicating a strong correlation between the sensor signals and their distance from the soil surface. The random roughness index was significant for different roughness classes at the 1% probability level, showing that this index effectively distinguishes between the resulting roughness classes. Analysis of variance results revealed that the measurement method had a significant effect at the 1% level. The method with the smallest difference from the reference method is considered the most appropriate measurement technique. The effect of forward speed was also significant at the 1% level; the speed at which the sensor’s performance did not significantly differ from the reference method was identified as the optimal speed for the system. Additionally, the effect of roughness class was significant at the 1% level, confirming that the created roughness classes had meaningful differences. The results of the sensor accuracy evaluation showed that the data obtained from the laser sensor at speeds of 1 and 2.6 km h^-1 had no significant difference with the reference method. Therefore, it is appropriate to use the laser sensor at speeds of 1 and 2.6 km h^-1. At speeds higher than 3.5 km h^-1, the laser sensor successfully detected smooth surfaces, but did not correctly distinguish uneven surfaces. In general, the laser sensor was able to detect all categories of roughness at a speed of 2.6 km h^-1. One reason the laser sensor did not perform well at speeds above 2.6 km h^-1 was its low data acquisition rate. By using laser sensors with a higher data collection rate, the soil height profile can be plotted similarly to a pin scale. The infrared sensor was successful only in detecting smooth surfaces but failed to detect other types of surfaces.
Conclusion
Due to limited accuracy and the risk of damaging or altering the surface roughness, the contact method is not recommended for use on soft soil surfaces. Among non-contact methods, the most suitable technique is the one that provides the highest accuracy and precision while minimizing cost and time for data collection and analysis. In this study, two types of sensors including laser and infrared ranging were selected based on their reasonable price, ease of operation, compatibility with a mobile system, and ability to deliver real-time roughness measurements in the shortest possible time. The results demonstrated that real-time measurement of soil surface roughness can effectively replace traditional, tedious, and time-consuming methods.

Keywords

Infrared sensor; Laser sensor; Precision; Real-Time measurement; Surface roughness

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