Improving estimates of crop lodging risk | Airbus Crop Analytics

Estimations of crop lodging risk can now be improved using Airbus Crop Analytics: satellite-derived field attributes from Airbus. This article contains a simple example we created to show how this can be achieved.

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Depending on their morphology, Cereal crops can be vulnerable to falling over (lodging). This can result in expensive reductions in yield: up to 75% in the worst cases, according to BASF.

Over the years, overall lodging risk has been reduced by crop breeding, such as by generating dwarf varieties, but lodging is still a problem that farmers want help to address. Farmers can take actions to reduce the risk of crop lodging during the growing season if they understand that there is a significant risk.

Graph demonstrating relationship between Leaf Area Index (LAI) and Green Cover (GCP), two important attributes when calculating crop Lodging Risk

However, these actions are themselves expensive, such as applying plant growth regulators or rolling the crop; so farmers only want to take them if they have to.

The promise of Airbus Crop Analytics data is that it can be used to provide an in-season indication of the status of a crop, e.g. the number of leaves and green cover. These observations are indicative of how vulnerable the cereal crop is to lodging, i.e. the more leaves there are on a stem, and the taller the stem is given a number of leaves, the more likely the crop is to be blown over in the wind.

AHDB provides practical guidelines to farmers on how to evaluate the risk of lodging and on corrective actions that could be taken if the risk is high. Our example, therefore, builds satellite-derived estimations of leaf area index and green cover fraction into the AHDB risk evaluation algorithm.

Using the control widgets, you can define various details of crop management and reveal some crops for which lodging risk is predicted to be high and see the recommended courses of action.

Developers and data scientists can find a walkthrough of example code for this use-case here.

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About Agrimetrics

Agrimetrics is the food and farming sector’s Data Marketplace. We enable organisations to safely share and monetise their data, whilst making it easier for data-consumers to access the information they need. Our goal is to help create a more productive and sustainable food system by enabling next-generation solutions as quickly and affordably as possible.

We are one of four centres for agricultural innovation founded with an initial investment from Innovate UK. Our founding partners are NIAB, SRUC, Rothamsted Research and The University of Reading. We have strategic partnerships with Airbus and Microsoft and are a participant in Microsoft’s prestigious AI for Earth programme.

About the four centres
The Agri-Tech Centres are a unique collaboration between Government, academia and industry created to drive greater efficiency, resilience and wealth across the agrifood sector. A £90m investment from the UK’s strategic innovation agency (Innovate UK) is enabling the Centres to harness leading UK research and expertise as well as build new infrastructures and innovation. They include CHAP (Crop Health and Protection), CIEL (Centre for Innovation Excellence in Livestock), Agri-EPI (Engineering and Precision Technologies), and Agrimetrics.

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