Submitted to: American Society of Agri Engineers Special Meetings and Conferences Papers
Publication Type: Proceedings
Publication Acceptance Date: 2/3/2003
Publication Date: 6/15/2003
Citation: Tekeste, M.Z., Grift, T.E., Raper, R.L. 2002. Acoustic compaction layer detection. American Society of Agricultural Engineers, St. Joseph, Michigan. ASAE Paper No. 02-1089. p. 21. Interpretive Summary: The depth of soil compaction has been measured by pushing a probe into the soil numerous times over a broad area. This stop-and-go technique takes a great deal of time and a significant amount of labor to obtain enough data to determine the depth of soil compaction over a large field. A new acoustical method may offer another approach to determining this depth in a faster and less labor-intensive manner. Initial tests conducted in the soil bins at the USDA-ARS National Soil Dynamics Laboratory revealed that the acoustic sensor might be used to determine layers of soil with higher density. Further reserarch will be conducted to verify this result in various soils with differing densities and moisture content. If these tests are successful, this sensor could be used to determine the appropriate depth of tillage that would create the most beneficial soil condition for plant growth.
Technical Abstract: The depth and strength of compacted layers in fields have been determined traditionally using the ASAE standardized cone penetrometer method. However, an on-the-go method would be much faster and much less labor intensive. The soil measurement system described here attempts to locate the compacted layer by measuring the sound produced by a cone being drawn through the soil. It is an empirical method based on the relationship between the amplitude of sound waves in a certain frequency range with degree of compression expressed using soil parameters such as cone index and dry bulk density. Experiments carried out in the soil bins of the USDA-ARS National Soil Dynamics Laboratory, Auburn, AL showed that the depth of the cone and compaction levels of the soil affect the acoustic signals. The variable depth data revealed that the hardpan is detectable in the highest information containing range of the frequency spectrum. The fact that the hardpan can be detected in this simple and inexpensive manner could contribute significantly to sensor-based precision tillage. In addition, with the help of GPS, position functionality can be used to implement map based precision tillage. In further research, the acoustic detector could be used to automatically control the depth of subsoilers to precisely disrupt the hardpan to save energy and time during the tillage operation.