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by Staff Reporter
20 June 2023
Associate Feature: Farming for the future

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Associate Feature: Farming for the future

The advent of summer (and the rare treat of blazing sunshine) has recently tempted many of us to get into the countryside and forget the concerns caused by recent global geopolitical events and the dramatic upswing in the cost of living.

It’s instructive to remember the successful contribution of Scotland’s rural economy to the nation. Some 80 per cent of the country, after all, is under agricultural production. Its farmers, crofters and growers produce output worth around £2.9bn a year and are responsible for much of Scotland’s £5bn food and drink exports.

It’s no rural idyll though: like every other economic sector, farming faces some daunting challenges, such as the effects of Brexit and demanding sustainability targets. While technology accelerates, government support systems that sustain the sector are also changing – as is the need to adapt digitisation to deliver enhanced efficiencies and address the climate emergency. 

One exciting way forward is the ‘digital twin’, a collection of data and mathematical models that can be used to simulate real world events and provide predictions about the future. This could well be a revolutionary new tool that helps manage and grow the rural economy, but its possibilities are not universally understood.  

According to Susanne Baker, techUK’s associate director for climate, environment and sustainability, digital twins “have the potential to support the UK to deliver on net-zero objectives, support the reduction of social inequalities and drive R&D-led growth”.

“However, the lack of consensus around how digital twins can be leveraged and why digital twins can drive better outcomes – for our people, economy, society and planet – means that the full benefits of this technology are yet to be realised,” she says.

At Leidos, a Fortune 500 technology, engineering and science solutions and services company, Mark Watson is passionate about changing this but concedes we are still at the beginning of our journey when it comes to applying this digital technology to the agricultural sector. 

He is Chief Architect for Civil at Leidos in the UK and sits on techUK’s Digital Twin Steering Board. The company’s 46,000 employees, with UK headquarters in Scotland, has a 30-year history of introducing technological innovations to all aspects of the global economy – including the rural economy. 

He firmly believes that Scottish agriculture can be vastly enriched by further investigating the use of digital twin technology. The imperative was last year underlined by the Scottish Government’s Vision for Agriculture, which set out an ambition for the country to become a “global leader in sustainable and regenerative agriculture”, promising a support framework to deliver climate mitigation and adaptation, nature restoration and high-quality food production.

The digital twin, Watson explains, can be central to that by monitoring what happens in the real world so that ministers can see the effect of their policies in near real-time and make tweaks to those policies so they become a better fit for the needs of the Scottish agricultural environment.

He notes that we still adhere to the Common Agriculture Policy (CAP) but that will no longer be the case by 2025. “Speaking to policymakers in Scotland, we know there will be changes from the existing policy and the digital twin is a solution that will provide  the visibility to the impact of any decisions to their desired outcomes,” he says.

It can both inform the policies that Scotland needs and help the agricultural sector take advantage of the detailed information it provides. “For example, a digital model can be constructed of a small farm or croft where multiple simulations of crop growth are modelled using the weather patterns from the past 100 years. 

“This data can then be used to analyse current weather patterns to give an indication of how well the crop may grow. Other variables can be added to the model, such as crop rotation information, pest infestations, planting schedules and fertilisation plans.” 

By adding this richness to the model, he says, the digital twin will build up a picture of the farm or croft, where it will give a higher degree of confidence about the likely outcomes of plans and help inform decisions such as which barley variety to use and when to plant it. 

“Then you can run a multitude of simulations using different types of barley with different weather patterns and different tests until you achieve a model that starts to simulate what real life looks like. 
“That gives the farmer or crofter the confidence that this type of barley, based on current weather patterns and many other factors, is their best chance for the crop to be a good one,” he says. 

Next, the real-world results from the farm are collated and fed into the digital twin. The digital twin learns more from machine learning technologies, tweaking simulations continuously to provide higher and higher levels of confidence in its predictions.

A frequently voiced complaint is the extended time it can take to implement and assess the effectiveness of new government policies but as the digital twin monitors what happens in the real world, ministers can see the impact of these policies in near real time and can adjust them accordingly.

Ultimately, Watson believes that we should be “thinking big” in terms of our ambitions to digitise agriculture across Scotland. He says this will, in time, involve knowing what is happening at the micro level in every single island, farm and field, peatland and forest. 

And the use of sensors is one tool that can facilitate that. “You might have a sensor that sits in the ground and measures the amount of moisture in the soil or optical sensors that can visually measure the health of a crop helping the farmer regulate the use of fertilisers.
 
“Those can be connected very easily now through 3G, 4G or 5G networks to monitor the farmland in real time so that you can establish a digital model that takes in all the information available through looking at the real world.”

To do this for the whole country is an exciting long-term ambition but Watson says that existing technology allows for that work to begin now and expand over time.  “You can start with a single field and grow the project. You don’t need to wait; you can start now at a scale that suits you and expand upon that.” 

In essence, he believes that means thinking big but starting small. “Imagine this model growing to include a neighbouring farm, croft and forest and start to include new crops, livestock, trees and peatland. Imagine this digital twin growing to include the whole of Scotland,” he enthuses.
 
“At this scale the digital twin becomes immensely powerful so while a full model of Scotland would take time to create, the beauty is that it can start small and grow over time.”
 There is no barrier to quickly setting up models to solve pressing issues such as modelling the spread of disease, or the levels of CO2 sequestration achievable by peatland restoration of a certain area, he adds. 

Everyone working in the agriculture sector can take advantage of the information provided by the digital twin.  “By analysing data on soil conditions, weather patterns, and crop requirements, it can suggest optimal planting schedules, irrigation strategies, fertilisation plans and help to identify opportunities for diversification.” 

The digital twin can also help assist in identifying and managing risks through things such as early warning systems, insurance schemes, or pest control measures.

Farmers in Scotland of course are just as tech-savvy as the rest of us and while some still doggedly complete their week’s paperwork on a Sunday evening, others increasingly manage their whole business via a smartphone. 

“There are many apps in the market today that provide value to the farming, crofting and forestry communities. Any digital twin of the future could connect with these to allow rich data to be consumed by the sector and to reduce costs.” 

For example, a farmer could enter all their livestock information into an app that communicates with the digital twin and gives them personalised recommendations, helping them maximise the things they care about – such as working hours, animal welfare and profit.

Watson concedes that identifying and using data in Scotland for a digital twin is not a simple task as the data sharing agreements that protect the public’s information are complex and must be upheld. “However, there are data strategies that can overcome this and ensure the digital twin is effective, while still protecting all parties and their sensitive information.

 “Successful integration of a digital twin into agricultural policy requires collaboration between the agricultural sector, policymakers, data scientists, and technology providers,” he concludes. 
“The use of digital technology can inform better decisions, better policies and ultimately better results – all of which will result in our agriculture sector becoming more efficient.”  

This article is sponsored by Leidos

www.leidos.com

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