How to take a good soil sample

High yielding canola and cereal crops will have drained the soil of a lot of nutrients. Taking good soil samples will help determine how much is left, and how to adjust fertilizer rates for the 2014 crop.

Avoid sampling areas that may exaggerate the soil test readings. These areas include low spots, sandy ridges, old yard sites, hilltops, saline areas and old burn piles. If hiring a custom soil sampler, advise or accompany the person taking the samples to be sure those areas are avoided.

Here are some sampling patterns to consider:

Random sample — This approach involves collecting at least 20 soil cores at random from a field and then mixing them to produce a single representative composite sample for analysis. While this is the simplest and most often used sampling method, it does not provide any estimate of how nutrient levels vary in a field. Taken in the fall it can provide a snapshot of residual nutrient levels following the preceding crop, and a basis for estimating average nutrient requirements for the next crop. However, it is not the ideal sampling pattern for tracking soil nutrient levels over years or for more intensive fertilizer management over the landscape (e.g. identifying management units, variable rate fertilization).

Benchmark sample — Select one or a few small representative areas, for example a quarter acre, in the field. Take 15 to 20 soil cores from each area. Use GPS to return to the benchmark location from year-to-year to get a better indication of soil nutrient trends over time. These trends can be used to assess whether fertilizer applications rates for crops throughout the rotation are adequate, excessive or deficient.

Grid sample — This is the systematic collection of samples in a pattern across the whole field, with the field divided into 1-to-5 acre squares. While this method is the most expensive means of sampling a field, the large number of samples provides an accurate measure of field variability, which can be used for variable rate nutrient application.

Smart sample — This method is a hybrid between the benchmark and grid sampling methods. It involves separating the field into distinct management units based on soil type, topography, and/or yield map history. Management units in the field can then be sampled separately, resulting in 3 to 5 samples from a field. Smart sampling improves the assessment of soil fertility status over a single benchmark sample and allows for the implementation of site-specific fertilizer management to optimize crop production.

The 0-6” sample. Sampling depth must be consistent and accurate. Ideally, multiple depth samples (0-6” and 6-12” and 12-24”, or 0-6” and 6-24”) will provide a better picture of the status of various nutrients throughout the soil profile. If providing only one sample depth, submit 0-6”.

Choosing a lab. Labs use different measuring techniques, and often have different ways of setting recommended rates. Therefore, results for the same sample will vary from lab to lab. Once you find a lab you like, stick with it. Using the same lab and sampling the same locations each year (using GPS) will make year to year comparisons possible, and make soil tests more valuable.

Click here for a list of labs

Ask for actual soil residual nutrient measurements as well as the lab’s recommendations. If recommendations are not in line with fertilizer rates you’d use based on actual soil residual levels, ask the lab how it calculates its recommendations. This will help to better understand how your specific production practices might lead to differences in recommendations.

The more you test, the more you can learn from the numbers. Benchmark samples collected from the same places for years will tell you more than a random sample done once. To see trends, you need several years. You can also learn to identify sample results that don’t seem right.

The removal technique. Some growers look at how much yield was harvested, convert that to nutrient removal, and then set fertilizer rates based on this. This technique could be skewed in a year where crops have higher biomass but lower than expected yield. Removal calculations based on grain yield alone might not accurately reflect crop needs for following years if more nutrients were trapped in the biomass than usual. Nutrients such as nitrogen and sulphur can be taken up by the plant, but through disease or drought or whatever other reason, not moved into the seed. Those nutrients would be in the biomass, and therefore not be immediately available to next year’s canola crop.