6.5   Assessment of Alternative Methods of Applying Precision Deep Tillage

Investigators

            Larry G. Wells, Biosystems and Agricultural Engineering, lwells@bae.uky.edu
            Timothy S. Stombaugh, Biosystems and Agricultural Engineering
            Carl R. Dillon, Agricultural Economics
            Thomas G. Mueller, Agronomy

Cooperator    

Mike Ellis, Worth and Dee Ellis Farms, Shelbyville, KY

Introduction

            The utilization of large heavy equipment has resulted in excessive compaction of soil that has been associated with decreased crop yield.  It is relatively common for Kentucky growers to subsoil fields where compaction is suspected and/or heavy vehicles have operated.  A major problem facing producers is reliable determination that such compaction exists and, if so, selecting the most advantageous means of dealing with the problem.  The soil cone penetrometer has been used extensively to determine soil strength that indicates the likelihood of poor root growth and crop performance.  This instrument provides a relatively rapid measurement of soil strength versus depth and, as such, can determine both the location and depth for which tillage is needed.  However, cone index can vary considerably, and its reliability in assessing soil conditions requires acquiring and analyzing multiple readings in a typical field.

            Crop yield maps can indicate areas of reduced yield that may be attributable to excessive soil compaction.  Since there are many causes of reduced crop yield, a means of confirming likely soil compaction is needed.  Remote sensing of soil surface moisture content may identify areas of poor drainage that correspond to excessive compaction.  Electrical conductivity as measured by a Veris unit may also identify adverse changes in soil properties associated with compacted soil.

The purpose of this study is to assess alternative methods of applying remedial tillage from the economic perspective of increasing net returns. The specific objectives of the proposed study are:

1.       To measure and map the spatial distribution of soil compaction as indicated by cone penetrometer resistance, or soil cone index (CI), on a 204 acre farm located in Shelby County.

2.       To acquire remote images of NIR reflectance from this field soon after one or more rainfall events of > 5 cm when no vegetation is present to indicate areas of soil saturation and poor drainage.

3.       To measure electrical conductivity with a Veris unit in selected field cells for comparison with soil cone index measurements.

4.     To compare various methods of applying remedial tillage in this field from the economic standpoint of net returns.

Background

Compaction of soil by machine traffic often produces adverse changes in soil physical properties that result in reduced crop yield.  Soil cone index (ASAE, 2000a) is a measure of soil resistance to penetration by a small probe and is therefore indicative of both compactness and strength.  Numerous researchers have reported reduced crop yields associated with high values of soil cone index (eg. Taylor et al. (1964), Douglas and McKeyes (1983), Al-Adawi and Reed (1996)).

            Tillage is the mechanical disturbance of soil that reduces strength and bulk density and thereby alleviates compaction.  Normal tillage operations do not disturb soil deeper than approximately 20-25 cm and, in the case of no-till crop production, there is generally no disturbance.  When traffic compaction occurs below the normal depth of tillage, deep tillage or subsoiling is required.

            Al-Awadi and Reed (1996) reported reduction in soil cone index from approximately 1.5 to 1.0 MPa at the 40-45 cm depth attributable to subsoiling in a silty clay loam soil.  Chaudhary et al. (1985) found that subsoiling reduced penetration resistance and increased grain yield in a loamy sand soil.  Blancher et al. (1978) reported that root growth decreased as cone index increased above 1 MPa and virtually stopped at  2 Mpa.  Foshee et al. (1998) also suggested a cone index value of 2 MPa to characterize severe compaction.

            Raper et.al. (1998) reported that annual in-row subsoiling could circumvent the detrimental effects of traffic in cotton production, allowing roots to reach moisture in deep zones.  A similar concept of “precision tillage” was described by Carter and Tavernetti (1968) wherein tillage depth was precisely specified to reach and disturb a compacted “pan”.  As the concept of GPS-based precision agriculture has gained acceptance, the idea of precision tillage has evolved to include real-time control of a “smart” tillage tool (Scarlett et al. (1997)) and variable-depth deep tillage (Raper, 1999).

            Precision deep tillage is attractive from the standpoint of eliminating unnecessary tillage.  Evans et al. (1996) reported no improvement of corn yield resulting from subsoiling and suggested that it be used only when compaction is evident.  Threadgill (1982) showed that the loosening effect of subsoiling was temporary, suggesting that regular deep tillage would be required to achieve beneficial results as indicated by Raper et al. (1998).

            In order to apply site-specific deep tillage cost-effectively, a method is needed to minimize costs associated with identifying compacted zones in fields.  Soil cone index is perhaps the least complicated and easiest measurement of soil strength and density to acquire.  However, the collection, recording and analysis of 10, 15 or more cone penetrometer readings per 1-acre field grid cell using equipment such as described by Raper et al. (1999) would involve substantial effort and expense.  The use of supplementary information, such as remotely sensed images or electrical conductivity measurements, in conjunction with yield maps and farmers’ knowledge of fields, could lead to more efficient and cost-effective implementation of precision tillage.

             Remote sensing by satellites is recognized as the only practical method for gathering spatially distributed data for watershed analysis (Engman, 1995).  Schmugge (1983) described the use of microwave reflectance to sense soil moisture near the surface.  Synthetic aperture radar (SAR) provides a remote sensing tool to measure soil moisture that is not compromised by cloud cover.

Remote multi-spectral LANDSAT images are limited by interval between satellite passes and the occurrence of cloud cover (Wells et al., 2000).  Senay et al. (1998) described acquisition of such imagery for assessment of crop yield for use in precision agriculture using aircraft.  Everitt et al. (1989) employed multispectral imagery for determining soil surface conditions, including moisture content.

            Soil electrical conductivity measurements have been correlated with factors that can limit soil productivity such as clay content (Williams and Hoey, 1987), Salinity (Rhoades and Corvin, 1981) and water content (Kachnaowski et al., 1988).  If significantly correlated with soil cone index, this measurement could provide a less expensive method of identifying areas of excessive soil copmpaction. 

Even though remote sensing methods are generally imprecise in quantifying soil moisture content, they may be useful in identifying areas of poor drainage that may indicate compacted soil.  When this information is combined with crop yield maps and known field traffic patterns, areas of suspected soil compaction can be identified and, if necessary, verified by a cone penetrometer before applying precision deep tillage.

Materials and Methods

Characterizing Compaction

The Worth and Dee Ellis Farm in Shelby County leases approximately 204 acres of cropland in which severe soil compaction is suspected because of previous heavy equipment traffic.   The farm is presently in a notill 3-year rotation of corn, soybeans,  and winter wheat/double-crop soybeans.  In March 2001, the field will be divided into 1-acre grid cells using a differentially-corrected GPS system with an accuracy of + 1m.  A multi-probe soil cone penetrometer (developed in a Phase I project) will be used to measure and record cone penetration resistance (soil cone index, CI) versus depth at 15 locations in each cell.  For each cell, the mean CI will be calculated in depth increments of approximately 20 mm and the depths for which CI > 1.5 MPa will be noted.  This magnitude of CI has been associated with reduction of crop yield in some soil types.  It is essential to measure CI when soil is at or near field capacity moisture content.

Remote NIR images of the field will be acquired in 2001.  A remote-controlled aircraft will fly over the field on three successive days after a rainfall event > 5 cm to identify areas of highest moisture content that may correspond to poor drainage associated will excessively compacted soil.  A mean NIR reflectance will be calculated for each grid cell on each day.  The field will be manually scouted on each day after the rainfall event to verify areas of highest soil moisture content.  Everitt et al. (1989) and others have shown excellent correlation between NIR reflectance and surface soil moisture content.

Electrical conductivity measurements will be acquired in various field cells using a Veris device.  These measurements will be compared to cone index measurements to determine potential correlation with respect to identifying compacted areas.  A yield map of the field of the 2000 harvest using the 1-acre grid system described above will be utilized.  Grid cells will be identified for which yield was below-average and the mean NIR reflectance indicated elevated soil moisture content following a substantial rainfall event.

Applying Remedial Tillage

            Deep tillage will be applied using a Case-New Holland Ecolo-till 2500 subsoiler.  The unit is equipped with 5 shanks spaced 76 cm apart that can reach a maximum depth of 40 cm.  Tillage depth can thus be adjusted between approximately 15 and 40 cm. 

            The 1-acre grid cells comprising the farm will be randomly assigned to 4 groupings in order to apply the following experimental treatments following the harvesting of full-season soybeans in 2001:

Measuring and Comparing Yield Response to Deep Tillage

            Yield data on the farm will be mapped onto the system of 1-acre grid cells described above, beginning in 2002 with winter wheat and double-crop soybeans, and followed in 2003 with corn.  Duncan’s Multiple Range test (Duncan, 1975) will be used to assess statistical differences in crop yield associated with the various deep tillage treatments.  A comparative analysis will be conducted to determine the potential increase in crop revenue associated with the various deep tillage treatments.

Assessing the Economic Potential of Precision Deep Tillage

            An economic analysis will be conducted to estimate the costs associated with the various method of assessing soil compaction described above.  Equipment and fabrication cost will be used to estimate the capital cost of the multi-probe cone penetrometer, the system for acquiring remote NIR imagery, and the cost of modifying the deep tillage implement achieve on-the-go control of tillage depth.  The cost of a differentially-corrected GPS system will also be included.  The operational cost associated with tractors and other equipment used in the various treatments will be estimated using ASAE Engineering Practice EP 496 and Data D496 (ASAE, 2000b,c).

Finally, an analysis will be conducted to estimate the net returns associated with each of the deep tillage treatments. Mississippi State Budget Generator, a computerized enterprise budgeting software, will be used. Operating and ownership costs will be estimated using standards for production economics and the American Society of Agricultural Engineers. Data required for these enterprise budgets include machinery prices, input prices, input requirements, yield responses and crop prices. Published data regarding current Kentucky machinery and input prices (Kentucky Agricultural Statistics) will be used when possible and modified to represent the costs of the innovative technology. This data will be supplemented with expert opinion for input prices and requirements. Yield response indicated above will be coupled with Kentucky Agricultural Statistics Service or Kentucky Farm Business Management summary data on crop prices to complete the data requirements. This result should indicate, for instance, whether the cost of a system for assessing soil compaction and applying precision deep tillage can be offset by potential savings in equipment and operational costs associated with conventional deep tillage at uniform depth.    

Expected Benefits

            The results of this study will provide valuable information to help growers determine when tillage is required to alleviate detrimental soil compaction and the most profitable means of applying such tillage.  In particular, the concept of site-specific or precision deep tillage will be evaluated in comparison with other approaches.  If the concept of variable depth tillage proves viable, a methodology of mapping compaction and applying tillage accordingly will have been demonstrated.  Other possible benefits include increased infiltration and reduced runoff and erosion.  Also, these benefits could be achieved with minimal fuel usage.

Deliverables

            This project will result in two or more papers that will be published in refereed technical journals.  At least one extension publication will be published presenting the results of the study.  Results of the study will also be presented at extension meetings and field days as appropriate.  Information from the study will be made available on the Precision Agriculture for Kentucky website (www.bae.uky.edu/~precag/).