Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 9/15/2006
Publication Date: N/A
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, as an indicator of compaction, is a factor that can vary considerably within fields and can also affect crop yields. In current practice, soil strength is most often measured with the cone penetrometer, a device that collects 'cone index' data point-by-point within fields. To make data collection more efficient, it would be useful to understand how cone index is related to easily measured soil physical properties. In this study, we investigated the relationship of cone index to soil electrical conductivity (EC), water content, and bulk density on three fields in central Missouri. We found that several cone index variables were related to EC, which can be quickly measured by mobile sensors. This relationship may help researchers, consultants, and farmers more efficiently choose areas of fields for penetrometer measurements.
Technical Abstract: Soil compaction is a concern in crop production and environmental protection. Compaction is most often quantified in the field, albeit indirectly, using cone penetrometer measurements of soil strength, reported as cone index (CI). The objective of this research was to relate soil compaction, measured as CI, to soil physical properties and crop yields. Penetrometer data were obtained from three fields with spatial variations in soil texture, bulk density, and water content. Auxiliary data included bulk density, water content, and apparent soil electrical conductivity (ECa) as a surrogate for soil texture. CI data and derived variables were significantly but weakly correlated to water content and ECa at all sites. Examination showed that different CI profile shapes were characteristic of different ECa levels. Regression analysis represented > 40% of the variation in CI at the 15- to 25-cm soil depth as a function of ECa and soil water content, and the boundary line method was suggested for additional analysis. Compaction variables were only weakly related to grain yield, with negative correlations in good growing seasons and positive correlations in water-limited seasons. More in-depth analysis would be required to better define the yield-CI relationship in these data. However, the ECa-CI relationship may be useful to locate areas most likely to exhibit high levels of compaction, thus making the process of characterizing within-field compaction variations more efficient.