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A SEFARI Gateway Specialist Advisory Group on Artificial Intelligence (AI) has been created to advise the Scottish Government on the use, future opportunities, risks and regulatory aspects of AI both as being used, or might be applied, to support Environment, Natural Resources and Agriculture (ENRA) policy in Scotland.

This report outlines the initial workshop's findings which considered key questions, such as what is meant and understood by AI in an ENRA context, issues with data availability and completeness, and the specific ethical issues of data and AI in the fields of environmental science and agriculture.

Report prepared by: Dr Ellen W. Evans ZERO2FIVE Food Industry Centre, Cardiff Metropolitan University

We’re delighted to be jointly hosting an event titled ‘Safeguarding the Health of Scotland’s Farmed and Natural Ecosystem’ with EPIC (Centre of Expertise on Animal Disease Outbreaks) and the PHC (Plant Health Centre of Expertise).

Date: Friday, 21st June

Time: 10:30 to 11:30

Venue: Royal Highland Show

The event will showcase work within the Scottish Government’s Environment, Natural Resources and Agriculture (ENRA) Research Portfolio. After an opening address, presentations will focus on animal and plant health risks, before concluding with a networking reception.

In addition, the Moredun Research Institute, Rowett Institute and Scotland's Rural College will again all have they familiar pavilion presences and a full series of engagements and activities.

The following report was undertaken between January and March 2023 as part of a SEFARI Research Fellowship funded via Food and Drink Federation Scotland on behalf of the Scotland Food & Drink Net Zero Task Force to support their understanding of the opportunities and barriers for the Scottish Food and Drink sector moving towards net zero.

The report has explored the background literature and current drivers for change to deliver net zero for Scotland’s food and drink industry.  It explores the need for a root and stem redesign of our food system, while recognising that the food and drink sector is by its nature a complex system.  The report explores how change is realised in complex systems and some of the barriers faced by stakeholders in understanding what actions best deliver sustainable sector economic growth, while also achieving the UK’s challenging net zero objectives.

While the pathways to delivering systemic change are widely understood, the process lacks the ability to bring together the complex networks of primary growers, producers, supply chains, retailers and consumers into a common framework that recognises and validates efforts and progress against a common set of benchmarks, which is the challenge this work aims to combat.

There were two key outcomes from this work:  Firstly, a System Resilience Framework that has outlined how a complete food and drink system might be modelled within a Scottish context.  The Framework facilitates the ability to explore both horizontal and vertical relationships between stakeholders, and opportunities for partnership.  The second was to develop a methodology and process for defining and measuring the maturity of the systems that manage carbon outcomes within the food and drink sector.  The Food and Drink Framework and Systems Mapping template set out a methodology for exploring the systems that are creating the outcomes (carbon emissions), rather than just the outcomes themselves. 

By exploring and understanding the process used to manage behaviour we get better transparency into where the numbers originate and how to deliver real systems change.  The report concludes with recommendations for actions going forward, which include undertaking sector specific consultation exercises to further develop carbon management system templates for each Tier/Sector and to roll out a Pilot Study for a region in Scotland to test the validity and practicality of the Resilience Framework and Carbon Systems Benchmarking Template.

The drought of 2018 raised the profile of droughts in Scotland, with broad coverage of impacts. Future occurrence and magnitude of droughts are predicted to increase, with periods previously only occurring once every 40 years happening once every 20 years by 2050. Recent work by NatureScot found increases in extreme droughts across Scotland with the highest likelihood in eastern Scotland including Grampian and Caithness. However, these spatial patterns do not always map to surface water and groundwater vulnerabilities.

Antimicrobial resistance (AMR) is a biological emerging contaminant (EC) with the potential to have significant consequences. ECs, such as pharmaceuticals, personal care products (PPCPs) and microplastics have been detected in surface and ground waters, sewage effluent and at trace concentrations in drinking waters and river sediment. There are data gaps in baseline information on pharmaceuticals in the water environment in Scotland in 18 local authority areas and a bias towards effluents. ECs have the potential to cause both ecotoxicological effects and impacts on human health, therefore their prevalence is of particular concern concerning drinking water sources. Microplastics threaten biodiversity, ecosystem services and potentially human health, yet minimal data pertain to their detection in Scottish freshwaters.

While the impacts of future changes on water quality in Scotland represent a major knowledge gap, water quality modelling frequently suffers from a lack of available data at a high-enough spatial and temporal resolution as well as high uncertainty. Therefore, novel monitoring and modelling approaches are urgently needed to address these challenges. Monthly data typically available from national regulatory water quality monitoring is at risk of underestimating true pollutant concentrations and loads, making it difficult to inform cost-effective targeting of pollution mitigation measures. Wide deployment of high-temporal resolution monitoring instruments continues to be hindered by high cost and there is an urgent need for innovative techniques for cheaper, reliable high-resolution field assessment to understand pollutant sources, pathways, and responses to mitigation measures.

While modelling facilitates an understanding of both current drivers and future risks to the water environment, the application of models to AMR is rare and hindered by a lack of data, limited mechanistic understanding and a failure to consider the role of environmental factors on transmission. The temporal and spatial dynamics of Antibiotic resistance genes (ARGs) in catchment systems is likely to be important in influencing risk levels across seasons and scales but is not well represented in models to date. Further, while new ECs appear every year, for many we do not have sufficient monitoring data or knowledge to characterise their behaviour in the environment.

The key drivers of this research are the needs of policymakers and managers to:

• Have tools to predict where and when drought may occur in Scotland.
• Understand where vulnerabilities to drought lie in our environment, economy and society.
• Understand future changes in water quality in Scottish catchments; what drivers of change are and how this impacts ecosystem services and water users.
• Improve and monitor rural drinking water quality and increase awareness of potential health risks from their water supplies.

The agricultural sector is in a period of rapid change; some of which include the tendency towards larger farms, with more animals but fewer people to care for these animals. This can lead to increased difficulties in the effective detection of welfare issues. Options that could help are to use methods to help stockkeepers decide where intervention is required i.e., data-driven decisions. This information can originate from a variety of sources, for example, new tools, such as wearable sensors or strategic use of diagnostics. The approach is known as precision livestock farming (PLF) which is a farming method where equipment, data or software is used which allows the use of information at an individual level for targeting decisions, inputs, and treatments more precisely. These approaches have been embraced by sectors such as dairy cattle and poultry, with a variety of them currently used on commercial farms e.g., sensors to identify the onset of calving and lameness detection, but little uptake or development of appropriate systems have been conducted for sheep.

As well as data collection at an individual level, significant improvements in animal welfare, particularly in extensively managed sheep-rearing systems, can also be achieved through an overall reduction in disease burden. One example of this type of approach is the use of diagnostic tests to target the control of specific diseases in local or regional settings. However, there are few practical on-farm applications of these tools for use in sheep, but there are exciting opportunities to develop innovative tools to support farming systems to promote positive welfare.

PLF tools can be used to improve the assessment of welfare issues: validation/evaluation of sensor-based tools to assess welfare in grazing animals, for the early detection of negative welfare-inducing diseases such as sheep scab and mastitis, and the strategic use of a diagnostic test to improve welfare through early detection of disease. These tools could provide livestock keepers with non-labour-intensive options to monitor the welfare of their animals. Implementation of these tools will allow the promotion of positive welfare, improved sustainable farming practices and climate change mitigation through the early detection of welfare issues and optimised, effective and early treatment of disease, which will reduce chemical substance use in farming.