Scottish farmers are among the most proficient in the use of agronomic inputs to create yield and deliver grain for key markets.

Nevertheless, the need to become even more efficient with inputs such as nitrogen fertiliser is a priority because of the longer term economic and environmental benefits accrued. Hot topics are crop nitrogen fertiliser recovery and overall nitrogen use efficiency in cereals.

As spring approaches, fertiliser plans for winter cereals will be being put into action. Applications of nitrogen are essential for maintaining high yield and grain quality – for instance in a winter cereal, the addition of fertiliser nitrogen typically doubles grain yield.

In recent years, crop breeders and farmers have made good progress to increase grain yield whilst keeping nitrogen fertiliser rates static. The net effect of this positive trend has seen an improvement in crop nitrogen use efficiency, or more yield per kg of fertiliser applied.

However, this does not necessarily mean that fertiliser uptake by the crop has become more efficient. Indeed, it is common for 40% or more of the applied fertiliser to go unrecovered. Subsequently, nitrogen can become lost through leaching or gaseous emissions to the atmosphere.

SRUC and the University of Edinburgh have been investigating how soil and crop measurements can be integrated with remote sensing to make applications of nitrogen fertiliser to winter wheat more precise, with benefits for efficiency and reducing loses.

We have been using well-established crop measures such as leaf area and greenness to estimate how soil nitrogen availability varies spatially within fields.

In a project funded by the BBSRC’s ‘Sustainable Agriculture Research and Innovation Club’, we have shown how soil and crop data can be used to remotely monitor the yield potential of wheat. Essential steps have been to understand relationships between soil nutrient supply and crop growth, and evaluate of spectral bands that best inform of crop growth and development.

An emerging message is that temporal changes in leaf area and colour in wheat crops can inform about soil nitrogen supply, which then becomes the basis for adjusting fertiliser nitrogen in a more precise way.

A ‘Normalised Difference Red Edge’ image taken across spring barley plots in late spring. (Image: Simon Gibson-Poole, SRUC)

A ‘Normalised Difference Red Edge’ image taken across spring barley plots in late spring. (Image: Simon Gibson-Poole, SRUC)

The image captures a spring barley fertiliser trial from an AHDB funded project. Here, our remotely sensed data has been converted into a vegetation index, where the lighter colour indicates more advanced or lush growth, whilst the darker colour indicates that the crop is backwards or has poor growth. Such data can be used to refine nitrogen application across a field.

Integration of remotely sensed crop data with mathematic models brings us closer still to yield prediction and improved management of fertiliser inputs.

Our goal is to use remote sensing data for widespread yield forecasting and real-time nutrient management. Fertiliser management can be refined further by use of soil and yield maps to identify parts of fields that have permanent or seasonal limitations to crop growth.

Education and knowledge exchange play a key role in our journey towards improved efficiency in crop production, with SRUC students helping to drive this forward as they engage with agricultural modules in advanced agronomy and agriculture precision technology.

Some of our research findings are to be tested at the AHDB’s Strategic Cereal Farm, in Fife, where we are evaluating more holistic and real-time methods to monitor soil and crop health.

In cereal supply chains, crop production contributes a high proportion of the overall energy or carbon costs. Therefore, improvements in fertiliser recovery and overall nitrogen use efficiency will benefit all stakeholders.

Integrating crop and soil data through remote sensing will place the arable sector in a strong position to realise improved production efficiency.