How To Get The Most Value Out Of Soil Analysis – for Sep. 6, 2010

It’s soil sampling time and once again I’m getting questions on how do I get more value out of the money spent on soil testing. I believe everything starts with the soil test, and developing a cropping plan is like building a puzzle — the more pieces you have, the clearer the picture. The soil test is the first piece of that puzzle.

DEALING WITH FIELD VARIABILITY

The first thing we all need to get our heads around is the fact that soils are extremely variable. What varies across a field? Well, pretty much everything.

1)pH can easily range by two full units. Remember the pH scale is logarithmic, so this is really a hundredfold difference from the plant’s perspective. Parts of your field can be alkaline while others are acidic. 2) Nutrients can vary anywhere from a three-to hundredfold difference, and even more dramatically if depth and time are accounted for. 3) Texture. It’s not unusual for fields to have two soil types. Some fields will have many types. 4) Organic matter (OM). Depending on the soil types, tillage system, rotation, manure use and more, organic matter levels can easily vary by four per cent or more. 5) Salinity and sodium (Na). Both salinity and sodium levels can vary greatly across a field. Soil depth plays a large role in variability. 6) Topography. Even very small differences in topography on visually flat fields can have big effects on crop growth because of secondary factors (i. e. drainage).

From this variability comes one of the biggest problems with soil testing, and that’s the actual soil sampling. Where the samples are pulled can have a profound effect on the quality and therefore value of the information received back.

An example comes from work done by Penney et al in 1996, where a relatively flat field was sampled in a grid pattern, one sample per acre over 60 acres, and samples were analyzed individually (Fig 1). Despite not having a lot of topography differences, this field had huge differences in SO4-S levels, with a range of 14 to 18,880 pounds per acre (yes, you read that right). The average level was 960 but the Mode or most frequent result was 20 lb./ ac. SO4-S. Less than 20 lb./ac. (zero to 24 inches) is considered deficient for some crops (canola and alfalfa) and less than 10 lb./ac. is deficient for other crops. Therefore, 80 per cent of this field is deficient in sulphur for canola and 61 pre cent of it is deficient when growing cereals, despite an average of 980 lb./ac.

Random or bulk sampling would have never picked up this and the crop would have not received the sulphur required to reach its yield potential.

Figure 1. Effect of soil variability on the distribution/frequency of SO4-S levels.

This year’s excessive rainfall (in many areas) exacerbated any mobile soil nutrient variability in the field… or did it? Now is a good time to look at using benchmark or zone sampling to capture the variability rather than muddy the waters with information from the average values that randomly taken soil samples provide.

SOIL ANALYSIS

I like to get a complete analysis on the surface depth with a basic analysis for the lower depths. For those farmers who already have a few years of soil test history with complete analysis of the top six inches and basic analysis for the six-to 12-inch depth, there is huge value in adding, with little to no additional cost, a basic analysis of the surface depth and complete analysis on the lower depths.

Micronutrient analysis to depth will be useful for five to 10 years minimum; SS (soluble salts) will also give long-term insight. Let’s use an example of soil sample results for copper (Cu) from two fields and the possible conclusions for optimizing cereal yields depending on how complete the data puzzle is. (Note:In this example, we are using Mehlich III extraction attention levels, DTPA extraction has much lower attention levels).

Using these field scenarios, we are either confident or not confident depending on the Cu profile observed. In general, a soil profile that has Cu levels increasing with depth is a profile that we need not worry about (ever) while a decreasing profile has flashing warning lights and sirens blaring no matter what the surface Cu levels are. Why? Because Cu could be deficient especially in dry years or if the soil is sandy textured. If Cu analysis weren’t available to depth, we are just guessing and possibly losing much more in yield and quality than the additional cost of the analysis.

You can construct similar logic tables for many other soil characteristics that only have to be analyzed every five to 10 years. Once you have the information you have much more confidence in your agronomic decisions.

Fields with a wide range of soil variability give us great variability in yield and quality. We may have average yields of 60 bu./ac. with areas at 15 bu./ac. while others are achieving 100+ bu./ac. Our brains can’t help but scream out “Why?” This is where an image can provide a very helpful puzzle piece to help us start sorting out why.

FIELD IMAGERY

Imagery can take the form of yield maps, aerial or satellite pictures, or simple post-harvest observations of fields. Where I grew up near Ryley, Alta., many fields clearly show extreme soil variability, particularly at this time of year, through crop regrowth, especially in canola. Imagery forms the basis of the precision management process (PMP), managing each zone individually to minimize the variability across the field. Critical to using imagery is the groundtruthing of that image — getting out into the field to verify what the image is “telling” you by field scouting and soil and tissue sampling.

I encourage you to pick at least two owned fields and dive into the PMP pool this fall. Many fields can be fixed for a long, long time with relatively low-tech solutions. The information you will gather will change the way you look at and manage fields forever.

We all know how frustrating it is to start building a puzzle only to find out that there are several pieces missing. Imagine if we didn’t know we were missing any pieces at all! Therefore, every analysis is a puzzle piece that helps us complete the picture of what is going on in our fields. The more pieces we have of the puzzle, the more detail is revealed; the more detail revealed, the more confidence we have that the agronomic decisions we make will optimize every dollar spent.

ElstonSolbergisasenioragri-coachand presidentofAgri-TrendAgrology,Ltd.For moreinformationaboutAgri-Trendorthis topicvisit www.agritrend.com.

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0-6

FIELD 1 – GRANDPA’S

ADEQUATE CU LEVELS FOR PLANT GROWTH BUT MAY NEED CU UNDER CONDITIONS THAT RESTRICT ROOT GROWTH TO 0-6” TISSUE TEST

FIELD 2 – GRANDMA’S

ADEQUATE CU FOR PLANT GROWTH BUT MAY NEEDS CU UNDER CONDITIONS THAT CONCENTRATE ROOTS IN 12-24” TISSUE TEST

Sample

Depth

(inches)

6-12

12-24

Conclusion

Surface only

Copper

(ppm –M3)

1.4

??

??

Not Confident

Appears deficient,

so copper is applied but may or may not result in a response

All Depths*

Scenario 1

Copper

(ppm –M3)

1.4

2.1

3.3

Confident

Scenario 2

Copper

(ppm –M3)

1.4

1.2

0.9

Very Confident

Deficient, field needs large amounts or several applications of Cu

*Depth analysis can come from one year or a combination of years since Cu levels don’t change much over time.

Surface only

Copper

(ppm –M3)

2.5

??

??

False Confidence

Appears sufficient,

so may overlook Cu-deficiency symptoms Scenario 1

Copper

(ppm –M3)

2.5

1.2

0.9

Confident

All Depths*

Scenario 2

Copper

(ppm –M3)

2.5

2.1

3.3

Very Confident

Sufficient, Cu is NEVER likely to

be deficient

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