Share your opinion about one of the SolACE innovations: Decision support systems (bread and durum wheat)

At the stakeholder event in May, in Foggia, Italy, SolACE partners presented several of the innovations being tested in the SolACE project. One of these innovations is a new decision support tool to manage N on winter wheat. The innovation as well as the discussion with stakeholders is outlined below. Please share your opinion or give us your feedback using the discussion tool below.

In SolACE work package 3, we will test a new decision support tool to manage N on winter wheat.

Our technological environment is changing (e.g., quick evolution of computing power and data processing tools; more detailed knowledge on agronomy, soil sciences or ecophysiology; increasingly powerful and accessible sensors; increasingly useful and interoperable decision support tools), so our decision support tools have to change too.

One example is N management. We can now use crop models to develop a new N balance method on winter wheat with a dynamic approach. In France, we test the “CHN” crop model (C for Carbon, H for H2O and N for Nitrogen) with this goal.

In the French context, N management begins with the estimation of a forecast N rate (using a balance sheet method). This is a theoretical step. Then we adjust the flag leaf application, using decision support tools, based on plant indicators, such as the chlorophyll meter. Approximatively 60% of French farmers use these decision support tools. The most famous is Farmstar, based on remote sensing by satellite. It was launched in 2002 and is now used on one million hectares. Finally, some farmers use intra-field modulation systems, which permit the user to modulate the N amount into the field.

With French farmers, advisors and scientists, we recently developed a radical new method for managing N fertilization (see figure 1).

  • Step 1: The first step is to define favourable condition periods, according to a climatic analysis.
  • Step 2: Then the second step is to estimate the Nitrogen Nutrition Index (NNI) using real time modelling (for example with CHN, or/and sensor measurements).
  • Step 3: During periods of favourable conditions, the estimated NNI is compared to a minimum NNI path.
  • Step 4: If there is a risk of not maintaining NNI above the minimum path until the next period with favourable conditions, a nitrogen application is advised, and the rate is calculated to maintain NNI above the minimum path until the next period with favourable conditions.

Models are never perfect. To improve their efficiency, we can use remote sensing and data assimilation.

We began to test this new approach two years ago on bread wheat and durum wheat, and the first results are good. Therefore, we are confident that it is effective, but we have to continue those tests in various contexts.


The following discussion took place at the SolACE Stakeholder event in Foggia, Italy in May, 2018. If you would like to share your opinion, please use the discussion tool below.

Question: Does the method also provide suggestions for the other stages such as the tillage stage and not just the flag stage? Does it make suggestions for the type of nitrogen to be used in particular areas? Does it contain data about varieties?

Answer: It is not only for the last application in flag leaf application; it is for every application. We do not advise one fertiliser specifically, but we take into account different losses, which can be different according to the fertilizer product. For example, urea ammonia nitrate (UAN) or urea, show more ammonia valorisation. The model can simulate those the losses.

Q: Is there a user-friendly version? Does it run on a PC or smartphone?

A: At the moment, there is no a commercial tool; it works on a PC or a network. However, in the future, the model will work on a network and you could watch the results on a computer or on a smartphone.

We could use a smartphone like a vector to consult the model, but also like a sensor.

Q: In Italy, there is the very successful DSS,, which was implemented six or seven years ago. It was funded privately and designed as a spin off by Vicenza University. Why does the European Commission support this model, if a model is already on the market?

A: we developed our own model to be able to connect to our databases (e.g. the fertilizer database) to be able to make projections until the end of the growing season. There are many models from research, and they are not very easy to use, but the CHN model is. This model was developed before the SolACE project, and it is not funded by SolACE. However, it is used in the project; it is not a commercial product. However, there is contact with the developers of the other models.