# Agmnomy Technical Report Grid Soil Sampling. IOHIO I SG4r;lE UNIVERSITY

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1 Agmnomy Technical Report 9302 Grid Soil Sampling, IOHIO I SG4r;lE UNIVERSITY

3 In fields where fertilizer spreaders have followed the same general spreading pattern for several years, a rectangular rather than square grid sampling pattern may be suitable. The shape of this rectangle may be 2 to 4 times longer than wide. This strategy could greatly reduce sampling and analysis costs. As shown in Table 1 (previous page), the smaller the sampling grid or rectangle, the greater the number of samples and expense for soil analysis. While the average level of soil fertility for an entire field may be known, the nutrient level variation is usually unknown. Wide grid spacings reduce the number of samples and analysis cost, but may not provide adequate definition of the nutrient's concentration variation pattern to serve as an effective guide for nutrient correction. This defeats the purpose of grid sampling. On the other hand, intensive sampling and analysis are very expensive. Growers must select the optimum combination of sampling frequency and cost. Enough samples must be taken to get a clear picture of the nutrient variation without creating excessive costs that cannot be recaptured through more efficient nutrient application. How can this be done? Although the nutrient variability of a field is not known, there is an alternative to guessing at an appropriate grid spacing. One option is to collect a series of soil sample. spaced 30 to 60 feet apart in a straight line 400 feet to 500 feet long perpendicular to the fertilizer spreader's usual travel direction. Analyzing these samples and studying the results will give an indication of the field's nutrient variability and indicate an appropriate sample spacing without creating a great expense. Likewise, a similar series of samples collected in a direction parallel to the travel of the fertilizer spreader may indicate that a rectangular sampling pattern is satisfactory. A composite soil sample for each collection point, or grid intersect, should consist of five sub-samples - one at the intersect and two samples taken on the line to each side at distances of 5 and 10 feet. Figure 1 A shows data for a field sampled every 60 feet Fig. 1A. Soil P at 60-Foot Sampling Intervals Fig. 16. Soil P at 120-Foot Sampling Intervals O GRID MARK (FT) GRID MARK (FT) Fig. 1C. Soil P at 180-Foot Sampling Intervals K S Fig. 1 D. Soil P at 200-Foot Sampling lntervals AC. MEAN - 29 LBS/AC MEAN - 27 LBS/AC GRID MARK (FT) GRID MARK (FT)

4 Fig. 2. Distribution of Soil P in the 144-Acre Field Fig. 3. Distribution of Soil K in the 144-Acre Field in a straight line for 540 feet. In Figure 1 A, every sample value (pounds of phosphorus per acre) was plotted, while in Figures lb, 1C and ID, every 2nd, 3rd or 4th sample value, respectively, was plotted. Depending on the distance between samples or the number of samples, the phosphorus concentration means vary from 23 to 33 pounds of phosphorus per acre. The cost of enough phosphate tochange the soil test level from 23 to 33 is about \$22 per acre. If only one sample from this field had been collected, the soil test value could have-been as low as 10 or as high as 63, assuming those were the lowest and highest values present. This variation provides the rationale for collecting and compositing many subsamples from a field where one analysis will be used to represent an entire field. Once the ideal grid spacing is determined and soil samples are collected and analyzed, the data for each plant nutrient can be plotted to produce a three-dimensional graph. As an example, a 144-acre field was grid-sampled every 100 feet and the samples were analyzed for ph, phosphorus, potassium andcec. Figures 2 and 3 show the distribution of soil phosphorus and potassium levels in three-dimensional graphs, which indicate a wide variation over the field. The variation from sample to sample can be made to appear great or small, depending on scaling factors used for plotting the vertical (concentration) scale. To illustrate that possibility, Figure 4 was made using the same data presented in Figure 3. Because one can easily misinterpret data presented in a 3-D format, management decisions should be based on 1) the actual data and 2) the realistic precision that can be expected from the application equipment. Computer plotting software makes it possible to "slice through" such charts to get an idea of the location Fig. 4. Distribution of Soil K in the 144-Acre Field, Plotted Using a Different Scaling Factor Fig. 5. Area Where Soil K Is Greater and Less Than 140 Ib. K per Acre

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