Skip to main content
ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #282100

Title: Relating mobile sensor soil strength to penetrometer cone index

item CHUNG, SUN-OK - Chungnam National University
item Sudduth, Kenneth - Ken
item MOTAVALLI, PETER - University Of Missouri
item Kitchen, Newell

Submitted to: Soil & Tillage Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/29/2012
Publication Date: 2/1/2013
Citation: Chung, S., Sudduth, K.A., Motavalli, P.P., Kitchen, N.R. 2013. Relating mobile sensor soil strength to penetrometer cone index. Soil & Tillage Research. 129:9-18. DOI: 10.1016/j.still.2012.12.004.

Interpretive Summary: Precision agriculture aims both to minimize costs and environmental damage caused by agricultural activities and to maximize crop yield and profitability, all based on information collected at within-field locations. Soil strength, or compaction, is a factor that can vary considerably within fields and can also greatly affect crop yields. Because of this, farmers need a quick and inexpensive way to measure compaction. To meet this need, we previously built an on-the-go sensor that can take measurements continuously while traveling across a field. In this research, we compared the data from our sensor to data from a cone penetrometer, the standard device currently used to measure compaction. Two kinds of comparisons were made – one comparison was based on computer models describing the two different sensors, while the other comparison was based on experimental data collected with them. From the computer models, we found that the two devices should interact with the soil very similarly, and that measurements from the two devices should be strongly related. These findings were partially confirmed by experiments, but the relationships were not as strong as the computer models predicted, and were also more complex. The relationships we developed in this research were only for certain soil conditions. If additional research confirms the relationships over a wider range of conditions, it will mean that the many scientific findings from cone penetrometer research can also be readily applied to our sensor. This will benefit researchers and practitioners wanting to use this more efficient way of assessing soil compaction.

Technical Abstract: A horizontally operating on-the-go soil strength profile sensor (SSPS) was previously developed so that the within-field spatial variability in soil strength could be measured at five evenly spaced depths up to 50 cm. Force divided by the base area of the sensing tip of the SSPS was defined as a prismatic soil strength index (PSSI, MPa), similar to the cone index (CI, MPa) of a vertically operating cone penetrometer. This study was conducted to obtain theoretical and empirical relationships between PSSI and CI data. Comparison of mathematical models and a sensitivity analysis of model parameters documented patterns of CI and PSSI in different soil and operating conditions. Patterns for both the soil strength indices were: (1) linear as a function of unit weight of soil, cohesion, adhesion, and operating depth, (2) exponential as a function of internal friction and soil-tool friction angles, and (3) quadratic as a function of operating speed. When a single model parameter was varied, the simulated CI and PSSI data showed highly significant linear relationships. Field data showed that, in general, both CI and PSSI were greater with higher bulk density, lower apparent soil electrical conductivity (ECa, where lower values indicate coarser texture), and lower gravimetric soil water content. Relationships were different when the data were divided into sub-groups by operating depth and ECa range. In models estimating CI, the effects of PSSI and its interaction with other variables were relatively clear at 30- and 40-cm depths. CI prediction models with the highest coefficients of determination were also found at these depths. Including operating depth in the regression model increased coefficients of determination from 0.35 to 0.45 and from 0.51 to 0.53 for the two test sites. These results would be useful to understand different approaches to soil strength measurement and to relate data obtained with the SSPS to the extensive research literature where CI has been used to quantify soil strength.