Margin maps and variable applications with Soyl.

Margin map

I have been working with Soyl for a number of years and have found them to be very helpful. They are always happy to listen, even when some of my ideas seem a bit off the wall. I realise there are many other companies now offering this type of help, but it is Soyl that I have chosen to work with. We have very variable soils across the farm. The field above is a perfect example and has 14 different soil classifications in 24ha. There is also an undulating topography with a couple steep banks to add to the excitement. The soil varies from clay cap to gravel, with a seam of chalk running through part of it. Ideal for variable applications.

My journey into precision farming began in the early noughties with variable applications of P and K along with lime. When you have indices that vary from 1 – 4 across fields it makes a lot of sense not to use blanket applications. Next on my hit list was variable nitrogen, using satellite images to identify different levels of biomass in the spring and then apply nitrogen accordingly. However, I needed to convince myself this actually paid for itself. So after 3 years worth of trials comparing variable against blanket application of nitrogen, I was convinced it paid off even in very dry springs on gravel. We are lucky enough to have a weighbridge here so accurate yields can be measured.

Like most farmers I always want more for my money. As I had invested in the hardware and was paying for images there must be more I could do to help cover the cost. For example, I have had issues in the past with growth regulators in wheat. In the valleys and on the stronger soils a robust rate is needed to stop lodging, however on the thin soils this stunts the crop and as a consequence hits yield. Working with Jeremy Hollis from Soyl, we set up a series of trials using variable applications of growth regulators in wheat and achieved a 0.5t/ha yield increase over the farm standard. In the absence of lodging this increase came from not damaging the plants on the poorer ground, whilst at the same time stopping the crop from falling over on the better soils and in the valleys. The latest project is trialling variable seed rates in maize based on available soil moisture. Last year’s results look promising but more work is needed yet.

When I approached them last year about margin maps, once again they agreed to help. My reasoning being that as government support is removed we need to know the areas of the farm which consistently underperform financially. As farmers we all know which parts of the fields tend to give poor yields, but by how much in cash terms is much more difficult to calculate. It needs several years of data to pin point the under achieving areas, but having been yield mapping for a number of years we already have that. Soyl also have a vast data bank of bio mass images that can be used. As an illustration, the above image shows the under performing areas in shades of blue. Using a sliding scale you can move this to show various bands of both net and gross margins using actual farm figures. So using this information I can make decisions on what areas might be taken out of production and used for  future environmental payments. I can also target input spend on the higher performing parts of the field and decide maybe not to crop certain areas with lower performing break crops. I think the graphics need tweaking to make it easier to read, however the information it provides is useful.  An uncertain future awaits, but never the less an exciting one as we grapple with the changes.

3 thoughts on “Margin maps and variable applications with Soyl.

  1. Very interesting. Just started on variable rate P andK after years of FYM and no artificial ferts. NVZs have forced us to cut FYM applications, hence the need. Our farms are on ‘Wold’ land which is allegedly ‘very even’. Far from it when we’ve had proper sampling done by SOYL!

  2. Good to hear Simon. I’m at the same stage with the margin maps from Soyl and already discovering some interesting facts when adding our costs to years of yield data. Well done Soyl.

  3. A really useful addition to their service. Could do with a different graphic to make it easier to compare several years side by side then we would be able to identify and draw different zones.

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