2019 Awarded Scoping Projects 

We were delighted to receive 34 applications to our 2019 Collaborative Scoping Call from a great variety of our members. We had an extremely high standard of applications once again and we are pleased to have been able to award so many of these (including the 2 awarded at our March Sandpit event) thanks, in part, to a £24k award from Defra that has gone towards some of the projects best aligned with their strategic priorities.

A tool to predict optimum harvest maturity of apples
​​PI – Deborah Rees (National Resources Institute, University of Greenwich)
Food Side Co-Investigators - Lori Fisher (NRI, University of Greenwich), Richard Colgan (NRI, University of Greenwich)
STFC Side Co-Investigators - Hugh Mortimer (STFC RAL Space)

The UK grown apple market is worth more than £220M per annum. Quality is critically dependent on timing the harvest so that the fruit is at optimum maturity, especially where fruit are stored long-term, as growers seek to extend their marketing season.
The current system for determining harvest time depends mainly on following the breakdown of starch to sugars, by sampling fruit from across an orchard and using iodine staining to indicate presence or absence of starch within areas of the fruit tissue.  This method is time consuming and also gives very little advanced warning of fruit maturation. 
This project seeks to develop a tool using hyperspectral imaging that will detect the breakdown of starch into sugars at an earlier stage, thereby providing growers with the potential to manage their crop harvest more efficiently and have fruit of better quality for long-term storage.

​Combination of FT-IR, Fluorescence and Spatially Offset Raman Spectroscopy (SORS) for the determination of botanical origin and provenance of monofloral UK honeys
​​​PI - Maria Anastasiadi (Cranfield University)
Food Side Co-Investigators - Fady Mohareb (Cranfield University)
STFC Side Co-Investigators - Pavel Matousek (STFC Rutherford Appleton Laboratory)

UK honey production covers ~14% of the local demand with many bee farmers striving to produce monofloral honeys with unique flavour characteristics which are highly prized by the consumers and allow higher profit margin. However, the quality traits of UK monofloral honeys are not yet well established and often fail to meet the criteria of the 2001 EU directive. Moreover reliable authentication (botanical and geographical origin) requires costly and time consuming analytical techniques not readily available to the producers. This project will explore the combination of rapid non-invasive techniques including Fluorescence, Infrared and Spatially Offset Raman Spectroscopy (SORS) coupled with Machine Learning algorithms for the authentication and quality control of UK monofloral honeys. All the above techniques are potentially deployable in field. STFC unique expertise in SORS can provide the added benefit of through-container analysis of honey, with applications in both adulteration detection and quality monitoring throughout storage. 

DryGro Hi-Resolution Spectrometric Crop Monitoring
​PI – Sean Peters (DryGro CO2i LTD)
Food Side Co-Investigators – Brendan Cawley (DryGro)
STFC Side Co-Investigators – Kadmiel Maseyk (The Open University), Stephen Serjeant (The Open University)

This project is a collaboration between DryGro (CO2i Ltd.) and Open University to investigate the use of spectrometry to measure quality and other vegetative indexes of the high-protein macrophyte crop Lemna.
DryGro has developed technology to grow a low-cost animal feed using 99% less water than conventional feed. Our ability to do this in arid and semi-arid regions alleviates their need to import this key resource. High-quality crop metrics are a significant enabler for this process given that, unlike conventional grows, we grow in harsh conditions and harvest daily.
We will use spectrometry to identify quality properties in two varieties of Lemna, grown at three temperatures and two fertilizer concentrations. Wet-laboratory analysis will be used to quantify nutrient content. The results of this project will then be translated into a field trial, followed by commercial operations if results are compelling.

Earlier detection of campylobacter on chicken farms
​​​PI – Geraint Morgan (The Open University)
Food Side Co-Investigators - Gemma Bray (Applied Group), Ashley Ball (Applied Group), David Speller (Applied Group)
Lynn McIntyre (Harper Adams University)
STFC Side Co-Investigators - Simona Nicoara (The Open University), Sonia Garcia-Alcega (The Open University)

Campylobacter is the major cause of food borne illnesses in the UK, causing sickness in over 300,000 people each year. Around 15,000 people are admitted to hospital and ~80 people die every year. Poultry is the major source in the food chain, responsible for ~70% of cases. The 2010-15 UK Research and Innovation Strategy for Campylobacter - in the Food Chain, identified the need for the development of a rapid, on-farm test.
So far, no such solution exists; however, approaches such as measuring metabolites or excretion profiles with e-noses have shown potential. The Applied Group and Harper Adams University have separately investigated this route, with mixed results.
It is our hypothesis that by applying lessons learnt from these studies and from the development of Ptolemy (a miniature GC-MS that successfully sniffed the chemical composition of a comet as part of ESA’s Rosetta Mission), a rapid, on-farm test could now become a reality.

Exploring application of STFC sensing technology to automate food quality management and enhance food manufacturing efficiency within the food industry - A case study of Mondelēz International
​​​PI – Rakesh Nayak (University of Hull)
Food Side Co-Investigators - Rossana Caccamo (Mondelez Int), Diogo Monteiro (University of Newcastle), Wantao Yu (University of Roehampton), Tao Chen (University of Surrey), Raymond Obayi (University of Manchester), Seyed M Ebrahimim (University of Sheffield)
STFC Side Co-Investigators - Jens Jensen (STFC Scientific Computing Department), Dr Daniel Gerber (STFC Rutherford Appleton Laboratory), Tom Kirkham (STFC Hartree Centre)

Our project aims at combining the technological capabilities and potential know-how of STFC’s sensor technology and data sciences with Mondelēz’s state-of-the-art food manufacturing process to prevent food quality defects through automation. The food industry is looking for new digital and inferential tools to improve product’s quality and maximise production line’s efficiency. Current offline analytical methods could be time-demanding and complex, error-prone, which limits the industry’s potential to achieve maximum operational excellence. Using STFC’s proven expertise in sensing technology, big data analytics, AI and image processing, this project would explore how tailor-made sensors could be installed within Mondelez’s production line to collect real-time data and use big data analytics and image processing to enable real-time process decisions - preventing quality defects and resultant food waste. It also aims to build a technology prototype that can be scalable to other industry sectors for bigger impact on issues such as food quality, waste and sustainability.

Exploring applications of STFC sensor technologies and data analytics for enhancing sustainable production and food safety in the Indonesian shrimp aquaculture industry
​PI – Miying Yang (University of Exeter)
Food Side Co-Investigators - Martino Luis (University of Exeter), Rakesh Nayak (University of Hull)
STFC Side Co-Investigators – Tom Kirkham (STFC Hartree Centre)

According to the FAO 2018, Indonesia is the second largest shrimp producer in the world. However, Indonesian Directorate General of Aquaculture reports that around 40% of shrimps in Indonesia die or are wasted during the cultivation, production and logistics due to the changing water quality, diseases and cannibalism among shrimps. This might cause various food safety issues due to the bacteria in shrimps and the use of banned antibiotics. This project will explore the applications of different STFC sensor technologies and data analytics to address such challenges in productivity and food safety in Indonesian shrimp aquaculture industry. In particular, the project will develop a feasibility study on applying non-invasive STFC sensor technologies and RAL space geospatial data analytics to monitor, predict the real-time environment change of shrimp cultivation and production in Indonesian shrimp farming firms. Such applications can prevent the potential shrimp disease and death, improve food safety, maximise the shrimp quality and productivity, and reduce waste.

Integrating STFC data science, IoT and AI capabilities for standardising and automating food waste (food surplus) data collection in Thailand
​​PI – Sonal Choudhary (University of Sheffield)
Food Side Co-Investigators - Christian Reynolds (University of Sheffield), Lenny Koh (Sheffield University Management School), Bob Doherty (The York Management School), Anurag Tewari (Cranfield University), Chris Oestereich Thammasat University), Suntichai Kotcharin (Department of International Business, Logistics and Transport), Pichawadee Kittipanya-ngam (Department of Operations Management)
STFC Side Co-Investigators - Jens Jensen (STFC Scientific Computing Department), Robin Pinning (STFC Hartree Centre), Tom Kirkham (STFC, Hartree Centre)

Our project aims to explore capabilities and potential of STFC data science, IoT devices and AI for recording and monitoring food surplus data in the supply chain so that it can be efficiently and effectively redistributed. Thailand generates 27.06MT of waste per year and 64% of this is food waste. Most of such waste occurs because of insufficient real-time information about availability of surplus food and lack of connectivity between source of surplus food and places of potential utilisation. There is a huge opportunity to minimise food waste by redirecting the food surplus to needy people in Thailand and contribute to achieving SDGs for Thailand towards zero hunger (SDG 2), good health & Well-being (SDG 3) and reduce climate change impacts (SDG 13). Using STFC’s proven expertise in data analytics, AI and IoT sensor technologies, this project would study the infrastructure requirement for real-time food surplus/ waste data collection, develop standards for food waste data collection in Thailand and identify implementation challenges, market and knowledge gap, in Thailand from multi-stakeholders perspective.

Microstructural design of snack food products for predictive control of nutritional textural and flavour properties
​PI –Elena Simone (University of Leeds)
Food Side Co-Investigators – Mark Auty (Mondelez Intl), ben Gardner (Exeter University), Steve Euston (Heriot-Watt University)
STFC Side Co-Investigators – Jens Jensen (STFC Scientific Computing Department), Claire Pizzey (Diamond Light Source), Sarah Rogers (STFC ISIS Neutron & Muon Source)

The project aims at evaluating and applying synchrotron radiation techniques to understand the link between molecular, nano and microstructure of snack food products and their macroscopic properties such as flavour and texture. Food products are complex materials, whose properties depend on the interactions among ingredients at the nano and micro scales. For example, biscuits are made of flour, butter and sugar but the typical crunchiness and characteristic taste of this snack food is the results of a series of chemical and physical transformations among sucrose, starch, triglycerides and water during the manufacturing process and subsequent storage. Investigating these interactions within actual food products requires the use of non-destructive techniques that enable 3D imaging of multicomponent systems and the chemical identification of each component. Synchrotron neutron and x-ray tomography and diffraction are among the few technologies that have these features, but they have never been used on complex food matrixes

My Digital Twin
​PI – Charlotte Mills (University of Reading)
Food Side Co-Investigators -Julie Crenn (University of Greenwich), Jason Halford (University of Liverpool), Jo Harrold (University of Liverpool), Kerry Whiteside (Samworth Brothers), Diogo Monteiro (Newcastle University)
STFC Side Co-Investigators – David Bogg (STFC Hartree Centre), Tom Kirkham (STFC Hartree Centre)

The chronic nature of non-communicable diseases makes it easy for consumers to overlook their progression. Some of these diseases are preventable by making changes to diet and lifestyle which both reduces disease risk, as well as individual and societal financial burdens (e.g. NHS costs). Behaviour change is challenging; there are internal and external obstacles to any intervention. A potential stronger motivator of behaviour change is the realisation of consequences of current choices on future health. If individuals could see now, the long-term consequences of their choices, they might be keener to make behaviour changes. This project will test whether a digital platform that projects current choice patterns onto likely future health status is feasible and capable of motivating behaviour change. Using big data analytics and complex systems modelling, information about diet and/or lifestyle will predict future heath, presented as a ‘Digital Twin’. Using state-of-the-art imaging, this could be a visual representation of the individual users.

Remote sensing led monitoring and forecasting of global banana production
​PI – Daniel Bebber (University of Exeter)
Food Side Co-Investigators - Varun Varma (University of Exeter)
STFC Side Co-Investigators - Seb Oliver (University of Sussex), Raphael Shirley (University of Sussex)

​Bananas are a globally important agricultural commodity. However, despite facing similar overarching challenges from climate change, pests and diseases, bananas have not received much research emphasis compared to other crops, such as rice, wheat, etc. Poor quality data on extent of cultivation, its dynamics over time, and productivity of plantations at fine enough spatio-temporal scales, poses a major limitation for such research. The application of remote sensing tools has the potential to fill these data gaps. This project will use satellite data combined with plantation scale production data to map past changes in global banana cultivation area and track plantation productivity at fine temporal scales. Outputs will enable a better understanding of climate and disease impacts on plantation productivity, and the prototyping of a near-term (6-9 months) forecasting model for production volume.

Resilience of Livelihoods in a Climate Change Context: Scoping study to identify datasets, models and knowledge frameworks
​​PI - Lisa Emberson (Stockholm Environment Institute at York, University of York)
Food Side Co-Investigators – Eleanor Jew (University of York), Naresh Magan (University of Cranfield), Wayne Martindale (The National Centre for Food Manufacturing), Christian Thierfelder (The International Maize and Wheat Improvement Center - CIMMYT)
STFC Side Co-Investigators - Althea Wilkinson (Jodrell Bank), Dawn Geatches (STFC Daresbury), Peter Allan (STFC Rutherford Appleton Laboratory)

Climate smart agriculture aims to reduce emissions, enhance yields and improve livelihoods. To date, considerable effort has gone into understanding how physical datasets and modelling methods developed by STFC can support estimates of emissions from agricultural systems and associated yields of arable crops. Far less attention has been given to exploring how this physical environment might influence socio-economic conditions and how environmental change ‘plays out’ in the overall context of farmers’ livelihoods. This project will explore this knowledge gap, focusing on data-poor environments in Southern Africa, identifying a wide range of physical and socio-economic datasets and associated modelling methods that will combine to influence farmers’ livelihoods. Specifically, we will look for past trends in correlations between key indicators that describe physical and socio-economic systems to develop a framework to provide a better understanding of how future perturbations of physical systems will influence livelihoods and hence the sustainability of food systems.

Satellite-based UK Soil Organic Carbon Observatory
​PI – Marcelo Valadares Galdos (University of Leeds)
Food Side Co-Investigators - Lizzie Sagoo (ADAS), Daniel Morton (CEH)
STFC Side Co-Investigators - Martin Hardcastle (University of Hertfordshire)

Fertile soil is being lost at the rate faster than it can recovered, primarily from inadequate agricultural management practices and by climate change. Monitoring soil organic carbon (SOC), a key indicator of soil health, is challenging due to difficulties in sampling soils with enough frequency and spatial coverage. Remote sensing data has been used to identify the location of specific crops and estimating yields from those crops. This information can be used in computer models to estimate the impact of land use and agricultural management on SOC. This project will synthetize methods for combining remote sensing and modelling to assess SOC changes in agricultural systems at regional scales. It will involve collecting and organizing spatial data on climate, soil properties, crop yields and agricultural management practices, and proposing methodologies that can be used to inform national greenhouse gas inventories, agri-environmental policy and sustainability assessments in the food supply chain

​Scoping how daily photographs of agricultural crops might be converted into numeric measures of crop development
PI - Iain Bethune (STFC Hartree Centre)
Food Side Co-Investigators – GroundData LTD
STFC Side Co-Investigators – Jonny Castagna (STFC Hartree Centre)

​This project will examine possible techniques to convert daily photographs of potato crops into numeric measures of crop development, the measures desired are: emergence, leaf canopy percentage, possibly senescence. Machine learning should allow an algorithm to be trained to produce these measures which will feed agronomists’ models to increase the agroeconomic output of potatoes and increase standards of husbandry.
Grounddata has used cellular data in an agricultural context since a successful Proof of Concept study carried out in 2017 under the supervision of the technical manager of Britain’s largest potato packer.
During 2019 we will be collecting photographs from several farms in East Anglia.  Using Artificial Intelligence will relieve the pressure on growers with a dozen or more fields to monitor and agronomists with 100+.  This technique will automate an error prone manual process and provide input for systems such as the NIAB Potato Yield Model.

SIM Farm 2030
​PI – Jake Bishop (University of Reading)
Food Side Co-Investigators - Edward Pope (Met Office), Lisa Emberson (University of York)
STFC Side Co-Investigators - Seb Oliver (University of Sussex), Raphael Shirley (University of Sussex)

The effective assessment of new crop cultivars is an essential part of ensuring food security in a changing climate. The current assessment for UK wheat relies on a simple yield comparison of cultivars at a small number of sites. This approach is unlikely to adequately quantify variations in crop performance, particularly the dependence on weather and soil conditions at the test sites and the anticipated performance across the UK environment, nor does it address the anticipated performance under climate change scenarios. Building on the heritage of the SFN+ funded project FACYNation, we propose to develop a simulation tool that will learn a yield model for existing and new UK wheat cultivars and map that model across the UK to predict performance (and spatio-temporal variability) for current and future environments using UKCP18 climate projections. This tool will also allow us to investigate hypothetical cultivars to guide crop breeders in their design.

Tackling Challenges to Water Reuse in Agri-Food Sector [Water-Food] ​
​​PI – Devendra Saroj (University of Surrey)
STFC Side Co-Investigators – Donna Pittaway (STFC Daresbury Laboratory), Tina Geraki (Diamond Light Source)

​The availability of freshwater is essential for sustaining the agri-food sector and its climate resilience. Recent studies have shown that the freshwater requirement of the agri-food sector to feed the growing population can be supported by the reuse of wastewater. The composition of wastewater is complex, particularly when it contains the constituents of industrial origin. There are existing evidences of the potential of water reuse in agri-food sector. However, I order to make a step change in water reuse in agrifood sector, a deeper understanding and an assessment of both advanced wastewater treatment and accumulation of contaminants in seeds and plants is essential. As a first approach, we seek to identify complex contaminants which can be degraded using electron beam, in combination with conventional wastewater treatment methods. Furthermore, we seek to identify any accumulation or formation of contaminants in sprouting seeds using high-resolution X-ray spectroscopy.

Technology and climate change: a review of STFC Food Network+ projects and future potential
PI – Elta Smith (RAND Europe)
Food Side Co-Investigators - Sonal Choudhary (University of Sheffield), Lisa Emberson (University of York), Marcin Glowacz (University of Greenwich), Courtney Hood (RAND Europe), Manoj Menon (University of Sheffield), Rakesh Nayak (University of Hull), Simon Pearson (University of Lincoln), Ed Pope (Met Office), Christian Reynolds (University of Sheffield), Lizzie Sagoo (ADAS)
STFC Side Co-Investigators - Sarah Bridle (University of Manchester), Martin Hardcastle (University of Hertfordshire), Tom Kirkham (STFC Hartree Centre), Seb Oliver (University of Sussex), Stephen Serjeant (The Open University), Angela Walsh (STFC Hartree Centre)

​How can new technologies address the challenges of reducing agri-food greenhouse gas emissions? This project serves as a pilot for identifying innovations with this potential future impact. The pilot focuses on projects funded by the Science and Technology Facilities Council (STFC) Food Network+ (SFN) over two years, bringing together innovations from astro, nuclear and particle physics to identify opportunities at the intersection of emerging technology (data science, hardware and facilities), climate change mitigation, and food systems

The Role of Biochar in Climate-Smart Agriculture
​PI – Manoj Menon (University of Sheffield)
Food Side Co-Investigators - Sylvia Toet (University of York), Masoud Babaei (University of Manchester), Joseph Hufton (University of Sheffield), James MacPhail (Carbon Gold, UK)
STFC Side Co-Investigators - Genoveva Burca (STFC ISIS Neutron & Muon Source) Shashidhara Marathe (STFC ISIS Neutron & Muon Source), Oxana Magdysyuk (STFC ISIS Neutron & Muon Source),Claire Pizzey (Diamond Light Source)

Soils are essential for food production, and they also provide several valuable ecological functions including regulation of global climate through the emission of greenhouse gases (GHGs). Both soil organic carbon (C) and nitrogen (N) are essential for improving soil quality, health and crop yields and they also contribute significantly to the global GHG (CO2, nitrous oxide (N2O) & methane (CH4)) emissions. Therefore, building climate-smart agricultural soils is crucial for addressing global food security and climate change.  One of such strategies is the addition of biochar in soils which is known to increase C, N and other nutrients stocks leading to better crop yields. To maximise the benefits of biochar, we will need an integrated and mechanistic understanding of the impacts of biochar on soil C and N transformations including their losses as GHGs which will be addressed in this project through a newly developed collaboration between universities, STFC facilities and an industry partner (Carbon Gold UK). 

Virtual Food Labels and Retail: Promoting healthy and sustainable food choices
​PI – Jason Halford (University of Liverpool)
Food Side Co-Investigators – Jo Harrold (University of Liverpool), Paul Christiansen (University of Liverpool), Christian Reynolds (University of Sheffield), Panayiota Julie Alevizou (University of Sheffield), Julie Crenn (University of Greenwich), Charlotte Mills (University of Reading), Bob Doherty (University of York)
STFC Side Co-Investigators – Angela Walsh (STFC Hartree Centre), David Bogg (STFC Hartree Centre)

​Consumers are interested in food labelling and the Food industry must meet commitments on sustainability and health.  Environmental labelling is on the increase with more space on product packaging being devoted to it.  But consumers don’t/can’t pay attention to it all and it may be failing to influence choice. The project examines what do consumers look at when constrained on space, price and time? Current lab based visualisation systems are abstract and findings don’t reliably translate to real world (commercial risk); however, we will use STFC advanced visualisation systems to look at the optimum product labelling in a retail environment.

Climatic influences on strawberry disease epidemics
PI - Helen Cockerton - NIAB EMR
Food Side Co-Investigators - Christopher Nankervis - Weather Logistics
STFC Side Co-Investigators - Peter Allan - STFC Rutherford Appleton Laboratory

Powdery mildew (Podosphaera aphanis) is rated the most important aerial disease for UK strawberry growers, with an untreated epidemic leading to severe yield loss and unmarketable fruit. Climate change is predicted to influence the frequency and prevalence of disease incidence. We propose to survey and analyse pesticide application alongside yield data collected from strawberry growers based across the UK. Data collection will allow us to investigate the link between pesticide application and climatic change over the last decade. This will be achieved through analysing the association between the application of contact fungicides, meteorological data and North Atlantic circulation patterns. The project will combine advanced statistical analysis, machine learning algorithms and existing data to predict the impact of climate change on powdery mildew disease incidence and total marketable strawberry yield. Ultimately, climate change can be used to contextualize and improve existing finer scale weather based disease prediction models.

Enhancing the Potential of the Rhizosphere for Sustainable Food Production: understanding microhabitats around roots with neutron imaging19
PI - Xavier Portell-Canal - Cranfield University
Food Side Co-Investigators - Kai H. Luo - University College London, Carol Verheecke-Vaessen - Cranfield University,  Wilfred Otten - Cranfield University
STFC Side Co-Investigators - Genoveva Burca - STFC ISIS Neutron
​

​The root microbiome holds the key to sustainable food production. Exploitation is however hampered by the absence of a predictive understanding of which traits organisms need for successful introduction into the rhizosphere. For this, we need to better understand the physical environment in the rhizosphere. We will explore neutron scanning to visualise the physical environment surrounding roots. We will develop an experimental system that will allow us to quantify the distribution of water, air and solids surrounding roots and explore suitability of the IMAT beamline and establish the spatial resolution that can be obtained. We will use the data as proof of concept to develop a predictive approach to the rhizosphere. The vision is that the combination of neutron imaging with a pore scale modelling approach can be used to describe the physical microhabitat to inform microbiological rhizosphere models, guiding industry towards optimal ways to introduce microorganisms to the rhizosphere

Bringing waste to life
​PI - Fatima Arrutia - University of Nottingham
​Food Side Co-Investigators - Natalia Falagán - Cranfield University, Lorraine Fisher - University of Greenwich, Usha Ramanathan - Nottingham Trent University
STFC Side Co-Investigators - Tom Kirkham - STFC Hartree Centre, Jonathan Smith- STFC Hartree

​According to Food and Agriculture Organization of the United Nations (UN), one third of the food produced for human consumption is lost or wasted. In 2015, some actions began to address the UN Sustainable Development Goal 12.3 to halve current food waste. To achieve this target, robust data sets are needed to understand the scale of waste and identify the causes. This study will scope and design a platform that will allow anonymous data entry from stakeholders and provide a porthole for the redirection of waste streams. STFC computing and big data expertise will put together existing knowledge on food waste and the data gathered from the different stakeholders. This will provide with a structured database of waste available and potential uses. The outcomes will support the government initiatives and encourage additional industrial participation from those in the sector not fully engaged due to lack of incentive and data protection.

Projects Awarded in our 2018 Funding Round

We were bowled over by the response of 34 applications to our Collaborative Scoping Call in early 2018. This was more than 3 times what we had profiled to spend at this stage so we are delighted that we have been able to award so many of these (including the 2 awarded at our February Sandpit event) thanks in part to an additional £100k award from the STFC.

You can see how the successful projects fit into our themes and find out all about them below:

Piloting Zooniverse to help us understand citizen food perceptions
PI - Christian Reynolds (University of Sheffield)
Food Side Co-Investigators -  Luca Panzone (University of Newcastle), Ximena Schmidt  (University of Manchester), Astrid Kause (University of Leeds), Charles Ffoulkes (ADAS)
STFC Side Co-Investigators - Chris Lintott (Zooniverse, Oxford University), Stephen Serjeant (Open University), Changqiong Wang (University of Reading), Coleman Krawczyk (University of Portsmouth)

There is a food knowledge disconnect between the food research community, and general population. Food experts know detailed information about foods, but we do not know, (and cannot measure easily) what citizens understand or perceive to know about food. This pilot will use the STFC funded Zooniverse platform to ask citizens to provide their perceptions about images of specific foods (and serving sizes). For each image, one of a range of questions will be asked including perceptions of greenhouse gas emissions and energy (calorie content). We currently have 2 food image banks from prior projects (Intake24, and NU-Food). These will be uploaded to Zooniverse and used as the pilot classification dataset. Results will be analysed using Bayesian statistics, after seeking advice from STFC data scientists.

​Data-driven agri-food supply chains for sustainability and productivity: A case in Henan Province, China
PI - Wantao Yu (University of Roehampton)
Food Side Co-Investigator - Sonal Choudhary (University of Sheffield)
​STFC Side Co-Investigators - Tom Kirkham (STFC Hartree Centre), Tom Collingwood (STFC Hartree Centre)

​This project aims to improve sustainability and productivity of agri-food supply chains by promoting established good practices in Big Data, Internet of Things (IoT) and Blockchain applications. STFC brings its expertise in all three of these areas to this project. This project will predominantly focus on Henan Province, known as “the breadbasket of China”. Recently completed Agri-Tech in China: Newton Network+ (ATCNN) projects show that agri-food enterprises in China have insufficient understanding and knowledge about how IoT and Blockchain applications and collecting, organising and analysing Big Data help manage sustainable food production. To address the knowledge gap, by working closely with the Chinese partners, the project will first identify the best practices in the UK and China using focus group discussion, expert interviews and secondary data analysis, and secondly, facilitate the knowledge transfer through a dissemination workshop.

​Application of Cryogenics to Optimise Cold Supply Chains for Agri-food products in India
PI - Sonal Choudhary (University of Sheffield)
Food Side Co-Investigators - Rakesh Nayak (University of Hull), Sanjay Lanka (University of Sheffield)
STFC Side Co-Investigators - John Vandore (STFC - Rutherford Appleton Laboratory), Bryan Shaughnessy (STFC - RAL SPace)

Our project aims to explore capabilities and potential of STFC Cryogenic and Thermal Modelling for reducing food and energy losses in the supply chain, in places where the infrastructure is not well developed - such as in developing countries (India in this case). Unavailability of appropriate technological knowhow, infrastructure and knowledge results in 90% of food wastage in supply chain of developing countries, most of which are associated with fresh food. Advanced technologies such as Cryogenics have potential to strengthen the fresh-food supply by reducing post harvest losses from production-to-consumption level and reduce energy requirements compared to traditional cold supply chains. Using STFC’s proven expertise in Cryogenics, this project would study the implementation challenges, market and knowledge gap, infrastructure and thermal requirement in India from multi-stakeholders perspective: farmers, food processors, distributors, retailers (Amazon India, Tata Tesco and Reliance Fresh), industry gas companies, infrastructure development company, NGOs and government organisations.

​Combining IR and pattern recognition to enhance pregnancy success in cattle: Sensing well done steak.
​PI - Niamh Forde (University of Leeds)
STFC Side Co-Investigators - Anthony Brown (Durham University), Stephen Serjeant (Open University)

This project will apply pattern recognition techniques, used to analyse astronomical data, to drone-based infrared imaging technology to rapidly survey livestock, spread over a large area, and identify female cows to be inseminated. We will capitalise on the STFC drone expertise for this project. We will look to quantify the accuracy the technique by calibrating the infrared sensors, the accuracy of the automated pattern recognition software, and ultimately, the accuracy of the technique by training against a control sample of cows that are near ovulation. Our proof-of-concept test will be a blind test, with only the PI knowing which cow is near ovulation, and the research Co-I's identifying the cow with drone based imaging.

Scoping the feasibility of low-cost GC and GCxGC platforms for using volatile organic compound markers to assess quality of fresh fruit and vegetables throughout the supply chain.
PI - Hilary Rogers (Cardiff University)
Food Side Co-Investigator - Carsten Müller​ (Cardiff University)
STFC Side Co-Investigators - Geraint Morgan (AST Solutions and Open University), Simon Sheridan (AST Solutions and Open University)

Minimally processed fresh fruit and vegetables represent a growing market, providing and enhancing access to fresh produce. However these products have a very short shelf-life resulting in a rapid reduction in nutritional value and high waste. Thus there is a need to develop rapid and cost-effective quality assessment for the industry. We have identified markers based on volatile organic compounds (VOCs), analyzed by thermal desorption gas chromatography- time-of-flight mass spectrometry (TD-GC-ToF-MS), to assess shelf life and effects of processing. The challenge now is to transfer this technology onto a cost-effective platform to allow application at different points in the supply chain from intake to retail. We will explore whether STFC- expertise in bespoke instrumentation development for planetary exploration (Rosetta, Beagle2, LUNA27) can be applied to detect our markers and to develop affordable, portable instruments and rapid data analysis.

​​Forecasting Agricultural Crop Yields at National scales (FACYNation)
PI- Seb Oliver (University of Sussex)
Food Side Co-Investigators - Edward Pope (Met Office), Yoseph Araya (Open University)
STFC Side Co-Investigators - Pete Hurley (University of Sussex), Bjoern Soergel (University of Cambridge, Potsdam Institute for Climate Impacts Research)

​Quantifying the present-day climate risk to global food production, and the likely impacts of climate change, are a vital part of achieving SDG 2 (zero hunger). Recent Met Office research shows that natural climate variability explains 50-90% of wheat, maize and rice yield variability world-wide. In turn, wheat, maize and rice account for nearly 60% of global food energy intake. However, building a sustainable, resilient global food system which ensures food security for all requires a deeper understanding of climate-yield relationships for the world’s staple crops. FACYNation will bring together STFC data science experts and Met Office climate scientists and Open University plant ecologists to exploit this research by assessing the potential for accurate real-time yield forecasts in major production regions, and likely climate change impacts. These are essential for supporting food system decision-makers in understanding and managing their climate risk.

Arsenic Detection and Distribution in Rice Plants Using High Resolution X-ray Imaging
PI - Manoj Menon  (University of Sheffield)
​Food Side Co-Investigators - Christian Reynolds  (University of Sheffield), Maria Romero Gonzalez (University of Sheffield), Binoy Sarkar (University of Sheffield), Edward Rhodes (University of Sheffield), Natasha Falconer  (University of Aberdeen)
​STFC Side Co-Investigators - Sarah Rogers (STFC ISIS Neutron and Muon Source), Fred Mosselmans (Diamond Light Source), Claire Pizzey (Diamond Light Source)

Rice is one of the widely consumed cereal crops in the world. However, likely presence of Arsenic (As) in rice poses a significant health risk when it is grown in an As-rich environment. Rice cultivars vary in their uptake and accumulation of As in grains. Less understood, however, is its spatial distribution and accumulation patterns in different plant parts in cultivars. Arsenic accumulation in other aerial plant parts is a significant concern as both husk and rice straw are widely used for feeding ruminants, extending the risks through consumption of meat and dairy products. The project aims to study the spatial distribution of As in rice plants using x-ray imaging (fluorescence and tomography) facilities at Diamond. This cross-disciplinary project will perform preliminary investigations using a selected number of samples at a very high resolution (2μm). The team aims to produce much-needed research evidence towards future grant applications and publications. Find out more here

​Project APROV - Augmented Procurement Visibility - Developing the self organising capability of agricultural procurement systems
PI- Luciano Batista (University of Northampton)
Food Side Co-Investigator - Ram Ramanathan (University of Bedfordshire)
STFC Side Co-Investigators - Tom Kirkham (STFC Hartree Centre), Brian Matthews (STFC Scientific Computing Department)

According to WRAP, approximately 10 million tonnes of food are annually wasted post farmgate in the UK, with 29% of this total being wasted in the supply chain, before reaching households. This study will address this problem by investigating alternatives to develop the self-organising capability of agricultural logistics and related procurement systems. The objective of the project is to develop a feasibility study on how food supply chains can respond in advance to the risks associated with unforeseen disruptions undermining the continuation of food distribution processes.
The study will seek to enhance food security and supply chain resilience by specifying highly responsive procurement systems enabled by cutting-edge technologies such as IoT, Big Data analytics, and Blockchain platforms that provide food sector stakeholders with timely and reliable access to information on food provenance and quality across the value chain. The project will involve two methodological approaches that entail active participation of key stakeholders from the industry and scientific community.

The use of aroma volatiles profile for detecting mesocarp disorders in avocado fruit
​PI - Marcin Glowacz (Natural Resources Institute, University of Greenwich)
STFC Side Co-Investigators - Geraint Morgan (AST Solutions and Open University), Simon Sheridan (AST Solutions and Open University)

​The avocado fruit is prone to developing various internal disorder  (e.g. vascular browning, grey pulp, fungal decay, etc.) which are not visible from the outside. Thus, the purpose of this research is to investigate the feasibility of using thermal desorption gas chromatography - mass spectrometry (TD-GC-MS) system for determining aroma volatile organic compounds (VOCs) profile. It would inform us whether this system can be used for detecting mesocarp disorders in avocado fruit - reducing the number of poor quality fruit within the supply chain, in this way decreasing the likelihood of consumers’ complaints and thus increasing their satisfaction. This scoping project combines the knowledge of avocado fruit physiology with the specialized expertise in the collection, separation and identification of volatile organic compounds (VOCs) in remote locations, as exemplified by the successful development and application of the Ptolemy instrument, after a 10 year and 4 billion mile journey, for the comet chasing Rosetta mission.

​STRIMER - STrawberry Ripeness Identification by MicrowavE Resonance
​PI - Fumie Costen (University of Manchester)
STFC Side Co-Investigator - Brian Ellison (STFC RAL Space)

Soft fruit produce is a highly productive and competitive sector of UK agricultural industry. It is worth more than £1.2B/year to the economy and provides extensive employment. Of this, approximately 70% is derived from strawberry production; a highly seasonal group with a short and critical harvesting period. Determining optimum strawberry ripeness is essential in maximising crop yield and quality, which increases profit and export competitiveness. The University of Manchester(UoM), with the support of the STFC, proposes to develop a novel strawberry ripeness indicator that uses a microwave resonance technique to measure growth- related variation in the fruit complex permittivity. Manchester and STFC possess advanced microwave software modelling tools, instrumentation and expertise to support preliminary simulation and proof-of-concept experimental work. A ripeness estimation algorithm will be generated and a future portable system conceived that, when developed, will provide fruit farmers with a new agricultural tool.

Influencing phosphorus speciation in Soil-Root environment for reduced phosphorus accumulation and sustainable global food production [InRoot]
PI - Devendra Saroj (University of Surrey)
STFC Side Co-Investigator - Tony Parker (STFC Central Laser Facility)

The phosphorus (P) leaching from agricultural runoff and P pollution from wastewater results in eutrophication of freshwater bodies. A significant progress has been made during last few decades on the recycling of phosphorus in agriculture to reduce the eutrophication of freshwater bodies and reduce the fertiliser demand. However, the demand for phosphorus mining continues to grow due to soil P accumulation. In order to make a step change in the demand for phosphorus mining, the problem of soil P accumulation must be addressed, besides the recycling of phosphorus as fertiliser. This project aims at developing a new understanding of P accumulation and speciation on soil and plant root environment. As a first approach, we seek to develop quantification of P levels in soil and will seek to use STFC's Raman spectroscopy expertise to determine retention times following treatment of a variety of soil systems under a range of simulated wetting conditions.

Through-container detection and quantification of the adulteration of fruit juices and coconut water using handheld spatially offset Raman scattering
PI - Roy Goodacre (University of Manchester)
Food Side Co-Investigator - David Ellis (University of Manchester)
STFC Side Co-Investigator - Pavel Matousek (STFC Central Laser Facility)

The project is to develop and test the ability of spatially offset Raman spectroscopy (SORS), coupled with robust multivariate data analysis, for assuring the integrity of food. We have chosen fruit juices and coconut water as potential foodstuffs that are susceptible to adulteration. Both products are popular in the UK (and indeed worldwide), of high value and we have worked with these drinks before. All applicants have experience of SORS for through container counterfeit detection in alcoholic drinks. We consider that SORS has the potential to be a highly disruptive technology for food integrity analysis and could be a very valuable capable guardian (detection technology) within food systems. Both Manchester and STFC have SORS instruments so this would also allow for inter-laboratory comparisons which are needed for robust analyses across many laboratories.

​Remote sensing of soil water content.
​PI - Anthony Brown  (Durham University)
Food Side Co-Investigator - Karen Rial-Lovera (Royal Agricultural University)
STFC Side Co-Investigator - Genoveva Burca (STFC - ISIS Neutron and Muon Source)

Knowing the amount of water that is present in the soil is fundamentally important to food production. Too little or too much water and the crops don’t grow properly, if at all. Furthermore, saturated ground increases the likelihood of water run-off carrying away important nutrients and fertilisers. This project will look to produce a drone-based prototype to remotely sense the presence of water, using a variety of pass-band filters for optical/infrared light, to concentrate on key water absorption features in reflected light. Comparing the amount of light in these different pass-bands allows us to sense the presence of water. One of the key aspects of this project will be the attention given to calibrating the optical/infrared detectors which draws on our previous STFC-funded work on using these detectors for telescope calibration. Using well calibrated light sources, we will investigate how accurate off-the-shelf cameras are. Using off-the-shelf components will allow the technique to be accessible to the wider farming community then a select few.

​Mapping and early detection of coffee leaf rust in coffee fields in northern Thailand
PI - Oliver Windram
Food Side Co-Investigator - Katherine Denby (University of York)
​STFC Side Co-Investigator - Dr Anthony Brown (University of Durham)

​Coffee is the most valuable and widely traded tropical agricultural product. In Thailand, coffee production began in the region north of Chiang Mai 30 years ago to replace opium. It now represents an important source of income and development opportunity in Chiang Mai. Chiang Mai has government backing to establish itself as the coffee capital of South-East Asia with production in the hill villages focused on the higher quality Arabica varieties. However, high-quality coffee production, as a livelihood, is difficult in these regions. Coffee leaf rust (CLR) is a world-wide fungal disease with potentially devastating impacts on coffee production. With hill farmers unable to afford fungicides, early detection of CLR and removal of infected trees is critical. We will use drones to gather multispectral image data to identify coffee plants in hillside fields and identify initial signatures for detection of CLR prior to visible symptoms.

​Exploring novel techniques to assess food price shocks
​PI - Aled Jones (Anglia Ruskin University)
Food Side Co-Investigator - Valeria Shumaylova (University of Cambridge)

​Food systems represent a significant risk to financial and political stability in a number of regions around the world. The Global Sustainability Institute at Anglia Ruskin University has been building models, gathering data and developing methods to explore the dynamics involved in civil unrest, financial instability and local responses associated with food production shocks. These include agent based modelling, systems dynamic modelling, narratives, scenario development, access to weather systems monitoring and war gaming. However, the analysis techniques applied to understanding historic food price dynamics as a result of production shocks are simple econometric tools such as regression testing. A much more sophisticated approach to data analysis could yield new insights in historic price shocks that would better inform policy and market based responses. By working with STFC expertise from the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge this project will explore some of those techniques.

You can see a review of this study here

Hacking the second green revolution
​PI - Paul Scholefield (NERC Centre for Ecology and Hydrology)
Food Side Co-Investigators - Toby Waine (Cranfield University)
STFC Side Co-Investigators - Yonghuai Liu (Aberystwyth University), Rene Breton (University of Manchester), Joseph Fennell (University of Manchester), Hugh Mortimer (STFC RAL Space)

​Understanding crop yield prediction and crop productivity requires a scaling of measurement and monitoring for a global approach. While remote sensing techniques provide high temporal resolution and broad coverage, the hyperspectral imaging provides data to distinguish the growth conditions and species of plants. Here the key issue is how to combine these two kinds of data for such purposes of plant growth monitoring and yield prediction at high spatial resolution such as in small scale crop production. While each has its own characteristics,this project intends to bring STFC data scientists together to analyse both hyperspectral and LIDAR data to calibrate plant canopy reflectance. In return, the reflection properties can be used to predict the plant growth conditions and ultimately yield. Such projects involve several stages of data fusion and analysis such as data capture, noise removal/data normalization, data modeling, model testing and improvement. Various tools and methods will be implemented and developed for noise removal, data normalization, 3D modeling, visualization, skeletonization, trait measurement, association of light reflection and plant growth conditions and yield, and for the statistical analysis of the effects of different features within the models. New data will be collected in due course for testing during model development. The research findings will be presented in international conferences and workshops and published in the international journals.

Scoping the possibilities for Multi-modal sensing for non-destructive assessment of avocado fruit quality
PI - Mike O'Toole (University of Manchester)
Food Side Co-Investigator - Marcin Glowacz (Natural Resources Institute, University of Greenwich)
STFC Side Co-Investigator - Hugh Mortimer (STFC RAL Space)

This project will look into the investigation of new sensor technologies for non-destructive measurement of avocado fruit maturity. Avocado fruit is a high-value fruit of growing popularity among consumers. However, retailers have noticed that supplied batches/cartons have considerable variation in maturity. Furthermore, it has become clear that the traditional method of gauging ripeness – by colour change – has proven unreliable. This has prompted complaints from consumers, and poses a problem for industry, who are seeking a consistent and accurate method for measuring fruit maturity. We aim to investigate two sensor modalities: (1) hyper-spectral imaging of the fruit using new sensors originally developed for planetary observation, and (2) a magnetic induction method which uses bio-impedance spectroscopy to obtain information about the cell properties of a bulk biological sample. This method has been shown to be capable of robust measurement of various agricultural produce, such as apples, potatoes, pears, amongst others.

​Making vertical farming stack-up
PI- Seb Oliver (University of Sussex)
Food Side Co-Investigators - Jack Farmer (LettUs Grow Ltd), Charlie Guy (LettUs Grow Ltd), Benjamin Crowther (LettUs Grow Ltd)
STFC Side Co-Investigators - Philip Rooney (University of Sussex),  Pete Hurley (University of Sussex)

Indoor farms, whether they be a greenhouse or vertical farm, require close control over a wide range of environmental variables. The temperature, humidity, and air flow around the plant shoots and roots is a crucial determinant of crop growth rate. These can be balanced alongside lighting, irrigation, and nutrient delivery, to generate the perfect microenvironment for individual plant species – and maximise growth rate within the facility. Similarly, while large facilities have the budget to purchase multi- million-pound solutions from factory automation experts, most vertical farmers do not have access to automated sowing, harvesting, or packaging machines. This results in prohibitively high labour costs, as employees are put to work cutting crops by hand. This scoping project will involve collaboration between the STFC, LettUs Grow, and researchers from the Harper Adams University, to investigate technical solutions to the problems experienced by vertical farmers.

​Continuous Ammonia Monitoring for AGriculture - CAMAG
​PI - Brian Ellison (STFC RAL Space)
​Food Side ​Co-Investigators - Lizzie Sagoo (ADAS), Fangjie Zhao (Rothamsted)

Ammonia (NH3) is an atmospheric pollutant of international environmental concern. Its release into the atmosphere is predominantly associated with agricultural use; particularly from livestock where, for example, it is lost from grazing, housing, hard-standings, manure storage and land spreading. Within the UK, about 80% of agricultural ammonia emissions are also from livestock, with the remaining 20% from mineral fertilizer application. International targets aimed at achieving emission reduction have therefore been established and methods of abatement relating to, for example, optimizing slurry application, incorporation and storage have been identified. Ensuring adequate abatement requires precise detection and continuous monitoring of NH3. To achieve this, the CAMAG project will both apply and explore an advanced gas sensing technique, originally developed for radio astronomy research, that detects the natural microwave spectral emission signature of NH3. The accuracy of the methodology will be determined and assessed, and its performance compared with alternative sensing methods. 

Investigating the nano to microstructural architecture of ingredients and intermediates to improve industrial snack product performance
​​PI - ​Bruce Linter (PepsiCo International)
Food Side ​Co-Investigators - Bhavnita Patel (PepsiCo), David Jones (PepsiCo), Amanda Talhat (PepsiCo), John Bows (PepsiCo) Ian Hamilton (PepsiCo), Tim Ingmire (PepsiCo), Stacie Tibos  (PepsiCo)
STFC Side Co-Investigators - Tom Kirkham (STFC Hartree Centre) Genoveva Burca (STFC - ISIS Neutron and Muon Source), Dave Clarke (STFC - Central Laser Facility), Kathryn Welsby (STFC - Central Laser Facility), Claire Pizzey (STFC - Diamond Light Source) Sally Irvine (STFC - Diamond Light Source), Lee Connor (STFC - Diamond Light Source)

Food and drink is the largest manufacturing sector in the UK. PepsiCo is among the biggest businesses in the sector, both nationally and globally. Despite the use of  identical ingredients and manufacturing, we still experience varied consumer perceptions of our product textures across our markets. This suggests not only a requirement for further development of our specifications, but also a deeper microstructural understanding of our ingredients. Furthermore, we need to improve our understanding of the expansion of our products, particularly crisps and crackers.  This funding will be used to scope a future PepsiCo-STFC project, with the aim of investigating the microstructure and material science of the ingredients, aspects which are typically not included in material specifications to determine new ingredients. The funding requested will be used to host a facilitated technical workshop with leading academics, PepsiCo employees and key members of the STFC. These, in turn, will be used to propose technical work packages for projects via different routes of funding such as Bridging for Innovation.

​Page Header Image: An example of simulated data modelled for the CMS detector on the Large Hadron Collider (LHC) at CERN -  Source: Lucas Taylor for CERN http://cdsweb.cern.ch/record/628469