Skip main navigation

Prescription Maps

Learn more about prescription maps, what they are, how they are created and how they are used.
© EIT Food

Prescription maps are generated from a range of geo-referenced data, such as soil nutrient levels and historical yields, and provide input rates for defined zones of a field. Using the field position from a GPS receiver and a prescription map of the required input amount, the concentration of an input (eg fertiliser or seeds) is changed as the applicator moves through the field [1].

Prescription Maps for Nitrogen Fertilisation

Prescription maps enable variable rate application (VRA) of, for example, fertilisers, herbicides or seeds, adapting the dose to give specific areas of a field pre-defined amounts. This is particularly useful for nitrogen (N) fertilisation of cereal crops. A lack of nitrogen can mean a reduction in yield and grain quality, whereas too much leads to pollution and unnecessary costs [2].

There are three steps to constructing a prescription map [3, 1]:

  1. Identify homogeneous areas of the field (where the same dose can be applied).
  2. Decide on the fertilisation strategy.
  3. Calculate the appropriate fertiliser/herbicide/seed dose for each area of the field.

Calculating the appropriate dose can take into account:

  • Soil nutrient status (eg nitrogen content of the soil determined by lab analysis)
  • Soil conductivity (EM38), a measurement of soil water content
  • Historical yield data, which can be taken from yield maps
  • Crop biomass and yield sampling
  • NDVI (Normalised Difference Vegetation Index) (see Step 2.5) or other indices that indicate a crop need.

Variable spatial and temporal applications can be prescribed by combining the above parameters [4] to identify the homogeneous areas of the field; this increases the overall efficiency of N fertilisation.

Diagram showing how different types of data are combined by a cloud based data fusion application to generate a prescription map which then informs the automated application of the required input

How the data can be combined to create prescription maps. Click to expand. ©University of Hohenheim

Homogeneous Zones

Variable-rate fertilisation involves subdividing fields into homogeneous zones to which uniform doses of fertiliser are distributed. Homogenous zones are areas with the same or similar characteristics (eg similar yields or soil characteristics). Defining homogeneous areas for nitrogen fertilisation can be done using a range of data but vegetation indices, such as the NDVI, are most often used [5,6].

When developing prescription maps you need to consider not only the characteristics of the field but also the limitations of variable rate technologies (VRT) [7]. They work best with large homogeneous zones. Limitations such as lag position, the response to rate changes at zone borders, and working width shifts make VRA less effective which must be taken into account when establishing the homogeneous zones [8]. It’s also important to note that these maps can be made as precise as possible but ultimately it depends on the machine’s technical ability to execute these orders.

Agricolus has an innovative way of defining zones. Using a vegetation index (such as NDVI) the algorithm defines, on the basis of a statistical index, the maximum number of zones the field should be divided into for the most effective VRA, and the values of each zone.

screenshot showing Agricolus software in action with a satellite photo of a patchwork of fields with one area highlighted in yellow, orange and red

Homogenous zone management based on NDVI map of fields. Click to expand. ©Agricolus

The Pix4D software platform has taken an innovative approach to calculate and analyse the entire process from multispectral imagery to prescription map and there are many other useful web-based decision support interfaces that can help.

Fertilisation strategies

There are two different fertilisation strategies. The direct strategy assumes that the cause of the reduction in crop vigour is lack of nitrogen and so aims to minimise differences between homogeneous zones (ie, more fertiliser is needed in low yielding zones). Conversely, the reverse strategy tends to maximise them: it assumes that the limiting factor of the yield is not nitrogen, but other factors such as soil characteristics or water stagnation (ie, less fertiliser in low yielding zones).

Prescription maps incorporate one of these two strategies – it is included in the field application file. Therefore, VRA can increase yields by using optimal levels of input where it adds the most value, while lowering inputs in places where they have less impact on yields [2].

You can find more on variable rate application in the ‘See Also’ section at the end of this Step.

Not just N fertilisers

As well as nitrogen fertiliser applications, prescription maps can also be used when:

  • Applying other fertilisers, such as phosphorus (P) and potassium (K)
  • Applying herbicides
  • Variable rate planting/seeding [9]
  • Irrigating crops [10]

They all use data (on aspects such as plant crop biomass, historical yields, soil water content and use) from a range of sources and sensors.

© EIT Food
This article is from the free online

Innovation in Arable Farming: Technologies for Sustainable Farming Systems

Created by
FutureLearn - Learning For Life

Our purpose is to transform access to education.

We offer a diverse selection of courses from leading universities and cultural institutions from around the world. These are delivered one step at a time, and are accessible on mobile, tablet and desktop, so you can fit learning around your life.

We believe learning should be an enjoyable, social experience, so our courses offer the opportunity to discuss what you’re learning with others as you go, helping you make fresh discoveries and form new ideas.
You can unlock new opportunities with unlimited access to hundreds of online short courses for a year by subscribing to our Unlimited package. Build your knowledge with top universities and organisations.

Learn more about how FutureLearn is transforming access to education