Hyperplan crop monitoring advances enable response to Net Zero


The move to hyperspectral imagery would offer a step-change in prediction and forecasting of crop performance, according to Rémi Banquet, Commercial Marketing Director for Hyperplan, a ‘Software as a Service’ company. He explains that insights gained from its crop monitoring software will enable agribusinesses to adapt their business models and secure sustainable growth during the transition to regenerative agriculture.

Hyperplan provides decision support services to suppliers, buyers and planners in agri-businesses and agricultural cooperatives.

The Hyperplan platform ingests satellite data about the crop canopy, weather and soils and combines this with crop yield models to anticipate supply volatility.

The service is proving popular with agri-input businesses as it allows their commercial and marketing teams to grow their portfolio of farmers, manage KPIs and respond quickly to opportunities created by changes in production.

Remi Banquet, Hyperplan's Chief Growth Officer
Volatility in agriculture means it is difficult to gain an objective assessment, says Remi Banquet, Hyperplan’s Chief Growth Officer.

Anticipating supply volatility

Rémi explains that there is considerable volatility in agricultural production, and it is difficult to gain an accurate and objective assessment of crop acreage, performance and potential yield. “With Hyperplan our clients can determine what is grown, where, the volume, and monitor the stage of maturity through the season.”

The company was co-founded in France in 2021 by three former McKinsey consultants, each with a decade of expertise in developing supply chain operations for agri-food businesses. They saw the commercial requirement for improved crop monitoring software that could provide predictive insights.

The company now has clients across France, Germany and Spain and is looking to enter the UK market.

It works with partners to optimise the crop models. In France, the company is working with ARVALIS, an applied research organisation that works across the value chain with cooperatives and input firms, as well as feed, food and non-food industries.

By combining ARVALIS’ agronomic expertise with Hyperplan’s deep knowledge on statistical modelling, Hyperplan is able to develop advanced hybrid models and optimise the information available from its satellite imagery.

Hyperplan_screenshot
A screenshot from Hyperplan

The system currently uses multispectral satellite imaging to identify the type of crop and monitor development of the crop canopy and vegetation cover. It has access to Meteo weather data and LUCAS Soil, Europe’s largest topsoil database, with real-time information made available through a single, easy to use platform.

The company is working collaboratively with its clients to collect ground truth data and verify the crop classification and yield estimates. 

Current multispectral imaging satellites have 10 to 20 spectral bands available, but future hyperspectral imaging will give access to 10 times more spectral bands, allowing a much more detailed analysis of the crop as Rémi explains:

“For corn we have just done some trials of 3D crop modelling using hyperspectral imaging looking at the potential for assessment of micro stages of maturity. This is really exciting as it will increase the precision of our predictions and also offers the opportunity for quality analysis models in the future.”

Originally Hyperplan was focussed on providing its customers with a collect forecast on their territory. However, the agri input businesses saw the potential of using its technology to offer greater insights at a field level, as this would enable them to offer farmers and growers more personalised services.

“Being able to provide a customised service is particularly important in the transition to regenerative farming, where there is a focus on effective rotations and improving productivity with fewer inputs,” Rémi continues.

“For the agribusinesses, it means that their reps are not going in cold. They have a sufficient level of knowledge to start engagement with the farmer, to have a proper discussion and fine-tune the response.

“They are trying to sell the most efficient products that will help the farmer gain better performance and improved margin, for example a particular variety of corn that grows well in their soils. This includes using historical data on rotations to look ahead to the next season and advise on suitability of follow-on crops.

“We are helping our clients to anticipate the market for the year, and this is invaluable as they are able to plan their budgets and marketing operations very early.”

Hyperplan_screenshot
A screenshot from Hyperplan



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This post originally appeared on TechToday.