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ARS Home » Midwest Area » Columbia, Missouri » Cropping Systems and Water Quality Research » Research » Publications at this Location » Publication #165441

Title: EVALUATION OF AN ON-THE-GO-SOIL STRENGTH PROFILE SENSOR USING SOIL BIN AND FIELD DATA

Author
item CHUNG, SUN-OK
item Sudduth, Kenneth - Ken
item PLOUFFE, CAROL
item Kitchen, Newell

Submitted to: American Society of Agricultural Engineers Meetings Papers
Publication Type: Other
Publication Acceptance Date: 6/1/2004
Publication Date: 8/1/2004
Citation: Chung, S.O., Sudduth, K.A., Plouffe, C., Kitchen, N.R. 2004. Evaluation of an on-the-go-soil strength profile sensor using soil bin and field data [CD-ROM]. American Society of Agricultural Engineers Annual International Meeting. Paper No. 041039.

Interpretive Summary: Precision agriculture aims 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, an indication of 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 tested the sensor in the laboratory and in the field. In laboratory tests, we found that the output of the sensor did not change much as speed was varied up to about 6.5 miles per hour. This means that the sensor could collect meaningful data at normal tillage speeds. In field tests, we compared duplicate passes of sensor data collected next to each other. These readings were very similar, showing that the sensor could provide repeatable measurements of compaction. Also in field tests, we related sensor measurements to soil properties known to affect compaction--bulk density, soil water content, and soil texture. We found that these properties affected the sensor data. This study shows the ability of our sensor to collect soil compaction data in field operating conditions, and also shows that these data can be related to soil physical properties. This information will be useful to researchers working on soil compaction sensing, to companies seeking to commercialize compaction sensors, and to crop advisors interpreting data from compaction sensors.

Technical Abstract: An on-the-go soil strength profile sensor (SSPS) has been developed to measure the within-field spatial variability in soil strength at multiple depths up to 50 cm. In this paper, performance of the SSPS was evaluated using soil bin and field data. First, the SSPS was tested in a soil bin at different depths (10, 20, and 30 cm), forward speeds (from 0.5 to 3.0 m s**-1), and compaction levels (high and low). Second, field data were collected from two fields having variable bulk density, water content, and soil texture. Prismatic soil strength index (PSSI, defined as force divided by the base area of the horizontally operating prismatic tip) and cone index were measured at five depths (10, 20, 30, 40, and 50 cm) in entire fields and also more intensively in four 10-m by 10-m areas, selected for soil texture differences. Auxiliary data collected were bulk density, soil water content, and apparent soil electrical conductivity (ECa). When the SSPS was tested in the soil bin, increases in PSSI with speed were less than 15% up to a 3.0-m s**-1 operating speed. We selected 1.5 m s**-1 as a critical speed, below which effects on PSSI would be negligible, for field data collection. PSSI values collected in adjacent, parallel transects were linearly related (r**2=0.93), with slopes not statistically different from 1, confirming the repeatability and stability of soil strength sensing with the SSPS. Field data showed that, in general, PSSI was higher at locations with lower ECa and water contents, and greater bulk density values. Results of stepwise multiple linear regression showed that variability in PSSI was better explained when interactions among the soil variables were included as independent variables and when data were grouped into subsets by depth and/or ECa level. Over entire fields, R**2 values for estimating PSSI were 0.61 and 0.52 for a claypan soil field and a flood plain soil field, respectively. These results will be useful for interpretation of PSSI and for future applications of the SSPS in crop management, e.g., delineation of highly-compacted within-field areas and control of variable tillage operations.