UF/IFAS Nutrient Management Series: Soil Sampling Strategies for Precision Agriculture
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UF/IFAS Nutrient Management Series: Soil Sampling Strategies for Precision Agriculture

   

UF/IFAS Nutrient Management Series: Soil Sampling Strategies for Precision Agriculture1

Rao S. Mylavarapu and Wonsuk Daniel Lee2

The purpose of this fact sheet is to help identify different soil sampling strategies, and related advantages and disadvantages, if adoption of Precision Agriculture Technology is being considered.

Precision Agriculture promises to improve fertilizer use efficiency when fertilizer is applied in relation to needs identified by soil tests. Precision Agriculture technology aims at providing the ability to apply nutrients and other inputs for crop production at precise locations in the field, based on the soil test level at that location. Representative soil samples are the key to success of any nutrient management program since the analyses and the resulting nutrient recommendation will only be as good as the soil sample itself. Soil sampling assumes much greater significance when Precision or Site-specific Farming is adopted, because of the precision and representation required, the variable rates of nutrient calculation and application, and the economics of the technology as a whole. It is extremely important to consider the components of Precision Technology and assess their availability and management when developing a soil sampling strategy. The type of sampling scheme is also site-specific, depending on the factors involved and the goals set.

Soil sampling and factors to be considered

Sampling Process

A base map of the field to be sampled should be constructed by collecting geo-referenced boundaries using GPS (Global Positioning System) equipment. The resolution of the GPS system being used will significantly influence the accuracy of the maps. After the Selective Availability (SA) has been turned off on May 1, 2000, typical GPS positioning error is about 50 ft. It is ideal if the GPS unit can detect distances 10 feet or less. DGPS (Differential Global Positioning System) provides better positioning accuracy (10-15 ft) and is typically used for soil sampling since precise positioning is required. Several computer software packages are available that can download the GPS data and overlay the boundaries on an aerial photograph of the field. A GIS (Geographical Information System) tool like ArcView or ArcInfo is the most widely used software to draw maps based on geo-referenced information. This process should be repeated for all the sub-areas within the field with identifiable differences. This will enable input applications at variable rates within a field.

Sampling Schemes

Based on the shape and size of individual fields within a farm where crops are to be planted, suitable sampling schemes can be identified.

Grid Sampling

A checkerboard-type grid can be created using special software such as SSTToolbox (SST Development Group, Inc., Stillwater, OK) and superimposed on the field map created. The grid approach works best when large tracts of land are available. While these shapes and sizes can be adjusted to suit the need and convenience, the most popular grid sizes used on the mid-western farms are either 2 1/2- or 2-acre grids. Even one-acre grids are used on areas where a need for intensive sampling is identified. These fixed-area grids will therefore divide the field into equal square-shaped areas from within which samples will be collected. These square shaped areas are also referred to as 'cells'.

A few important aspects of grid sampling must be well-understood before attempting to sample. Samples should be collected at random for adequate representation from within each grid and then consolidated. However, there are at least three methods of sample collection within a grid that are practical. One method is to go to the center of the grid with the GPS unit and walk several steps away from the center in all directions to collect samples from 3-5 spots randomly and consolidate them ( Fig. 1 ). Being relatively simple, this grid-centered approach can be consistently done on any given field. However, for unbiased sampling, care should be taken to avoid concentration of samples around the center point. The second method is to collect samples at random from all across the grid without any bearing on the grid-center ( Fig 2 ). The sampling pattern will not be consistent across the cells but this approach will ensure a better randomization. This procedure may be more time consuming because various sampling points have to be individually accessed across the grid area. If random accessibility within the grids is severely restricted, samples should be collected diagonally across each cell. In either case the application rates will be uniform throughout each of the cells. The application rates can be varied only among the cells if necessary, depending on the nutrient recommendations.

Figure 1. Grid centered soil sampling.

Figure 2. Random sampling within grids.

The third method of grid sampling is to collect samples at grid line intersections ( Fig 3 ). This approach will mathematically integrate the values (interpolate) between the points, which will enable creating contour maps based on the soil nutrient levels. The smaller the grid area chosen the higher the sampling intensity thus increasing the costs.

Figure 3. Sampling at the grid intersections.

Directed Sampling

A self-directed sampling is another scheme that is often adopted. This method requires a prior knowledge of the site characteristics that may be limiting the yield. Once these low/high yielding areas, soil types, areas under different cultural management, cropping systems, etc. are identified within a field, maps would be created to delineate the field accordingly and sampling would be conducted within these sub-regions. However, sampling based on factors that do not influence the yield should be avoided. This will effectively reduce the total number of samples.

Ability to respond to the needs determined from soil sampling and analysis should be the primary factor when designing a sampling scheme. If the capabilities to vary fertilizer rates, modify or amend the limiting factors is lacking, then the sampling intensity should be considerably reduced. Accruing additional information is expensive and can often cause confusion.

In order to obtain optimum returns, a Directed Sampling scheme developed in conjunction with a good assessment of available resources and the ability to apply nutrients at variable rates is highly recommended. Assessment will be most useful by considering the maximum area or Management Unit across which a fertilizer rate CANNOT be varied. A Management Unit will be a subunit of the entire field under consideration and representative samples should be randomly collected and composited for analysis. The results will then be averaged across this area and applications will be made based on averages derived for this unit. Variations, if any, will be made among different units but not within any given unit. This process would be the most effective and economical of all.

A Strategy that Works

Precision, accuracy and reliability are the three main factors that will determine the success of any sampling scheme. Economic feasibility is, of course, the bottom-line. The choices look simple, but may not always be easy to make. For this reason alone, help from professional consultants should be sought when Precision Agriculture is being considered.


Footnotes

1. This document is SL190, a fact sheet of the Soil and Water Science Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida. Published: February 2002. Please visit the EDIS Website at http://edis.ifas.ufl.edu.

2. R.S. Mylavarapu, assistant professor, Nutrient Management Specialist and Director of UF/IFAS ARL/ESTL, Soil & Water Science Department, and W.D. Lee, assistant professor, Precision Farming and Remote Sensing, Agricultural and Biological Engineering Department, University of Florida, IFAS, Gainesville, FL 32611-0290.


The use of trade names in this publication is solely for the purpose of providing specific information. UF/IFAS does not guarantee or warranty the products named, and references to them in this publication does not signify our approval to the exclusion of other products of suitable composition.


The Institute of Food and Agricultural Sciences (IFAS) is an Equal Opportunity Institution authorized to provide research, educational information and other services only to individuals and institutions that function with non-discrimination with respect to race, creed, color, religion, age, disability, sex, sexual orientation, marital status, national origin, political opinions or affiliations. For more information on obtaining other extension publications, contact your county Cooperative Extension service.

U.S. Department of Agriculture, Cooperative Extension Service, University of Florida, IFAS, Florida A. & M. University Cooperative Extension Program, and Boards of County Commissioners Cooperating. Larry Arrington, Dean.



Copyright Information

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