A new approach to measure fruit ripening could help increase quality and reduce waste for apple growers The apple has long been one of the most popular fruits eaten in Britain, with the UK market worth more than £220 million each year. But few people realise that the juicy, ‘fresh’ apple they buy at the supermarket may have been in cold storage for nearly a year. Timing the apple harvest to ensure long-lasting, delicious fruits is a real challenge for farmers – but one that could soon become easier thanks to research supported by the STFC Food Network+. "Two examples of Braeburn apple samples where multispectral imaging has been tested to see if it can distinguish parts containing starch (stained dark by iodine) from areas where starch had broken down into simple sugars (no staining). As the technology is still in development, the multispectral results are not yet clear for all samples. Photo credit: Deborah Rees and Melina Zempila." “Most apples are harvested in autumn, but the demand for them lasts all year round” says Deborah Rees, who describes herself as a ‘post-harvest’ biologist at the Natural Resources Institute (University of Greenwich). “This means we have to find a way to slow down the deterioration process and keep them in good quality”. Typically, this involves storing them at a low temperature (between 0.5 and 3°C depending on the variety), in a modified atmosphere with low oxygen levels. But even under these conditions, apples continue to ripen. “The longer you want to store apples, the earlier you have to pick them, so the window for harvesting is very narrow” says Deborah. “Growers currently have very little advance notice of this, so it can be a nightmare to recruit enough labour”. This can ultimately lead to waste if fruit cannot be picked at the right time. To address this, Deborah is researching a new approach to capturing the ripening process as it happens.
As fruits ripen, complex starch molecules are converted into simpler sugars, developing the sweet taste we enjoy. This can be measured using potassium iodide dye (iodine), which turns blue-black in the presence of starch. “Many people remember doing iodine staining at school, for instance staining leaves to look at starch production during photosynthesis or to compare the starch levels in different vegetables” Deborah says. “Apple growers use exactly the same process, typically in the boot of a car, right in the middle of the orchard. It’s messy, time consuming and not particularly safe considering that iodine is a hazardous substance”. Deborah hopes this could be replaced with a method based on multispectral or hyperspectral imaging. These methods use wavelengths beyond the visible light spectrum, including ultra-violet and infra-red light. In the case of hyperspectral imaging, hundreds or even thousands of narrow bands (10-20 nm) can be analysed. “The resulting image depends on what wavelengths are absorbed by the sample, which is affected by the chemical composition” says Deborah. “What we wanted to find out was if we could find a signal signature that depended on the concentration of starch.” To investigate this, Deborah and her colleagues collaborated with an apple grower in Kent during the harvest season. “We took cut slices from apples at different maturities and compared the iodine-stained slices with images taken using two hyperspectral cameras to identify promising wavelengths” she says. Once the apple harvest was over, they continued to refine the signal processing method using bananas, since these also ripen when starch molecules convert to sugars. “These were a good substitute model for apples since most bananas are imported immature and then artificially ripened using the plant hormone ethylene” says Deborah. The initial results indicate that hyperspectral imaging shows promise for measuring apple ripening, particularly for wavelengths in the range 460 – 630 nm, 630 – 920 nm. “A particular advantage is that the data give a quantitative readout, whereas iodide staining can only indicate presence or absence of starch” says Deborah. “This could provide a more informative and earlier measurement of starch breakdown.” She uses the analogy of an emptying bathtub, where iodine staining would only tell you when the tub was completely empty. “A quantitative method, on the other hand, can tell you when the tub is half-empty” she says. The next challenge will be to develop a portable multispectral (or hyperspectral if necessary) instrument that could be used directly by farmers on the orchards, without complex training. According to Deborah, some of the UK’s major apple growers have already shown interest. Nigel Kitney of the agricultural and horticultural advice company Hutchinsons says “this is an exciting development which will remove the subjectivity of the starch iodine test enabling growers to harvest the apples at the correct time, improving the product’s consistency for the consumer”. Besides providing funding, the STFC Food Network+ enabled Deborah to connect with researchers at RAL Space who were experts in spectroscopic methods and data analysis, including planetary scientist Hugh Mortimer and a research scientist, Melina Zempila. “Normally they would work on processing satellite data, so it was an opportunity for them to apply their skills to a very different sector”. In addition, her attendance and presentation about the project at the Network’s annual meeting opened up a discussion about a whole range of other potential technologies and fruits to consider. Having worked with apples for over 10 years, it is perhaps not surprising that Deborah enjoys eating them too. “My favourite has to be the Russet apple, although the Bramley is of course the best for a good apple crumble” she says. “I seem to be surrounded by apples all the time at the moment. Even when I go out cycling, it’s usually through the Kent apple orchards!”
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Satellite technology could help us start to reverse the perilous condition of our soils… © Photo by Lizzie Sagoo, ADAS There is a growing crisis underfoot. Our soils – vital to both our ecosystems and agriculture – are degrading at an unprecedented rate, due to factors that include intensive farming, deforestation and pollution. Degraded soils directly affect food security, availability of clean water, global warming mitigation efforts and biodiversity. But it is difficult to know where to begin to address the issue whilst we lack the technology to accurately monitor soil health on a large scale. Thanks to this ambitious new project from the STFC Food Network+, we could soon be using technology from the space sector to shine a light on the state of our soils.
“There is currently a real gap in our knowledge when it comes to monitoring soils on a large scale” says soil scientist Marcelo Galdos (University of Leeds). “Currently, soil analysis typically involves taking a sample at a discrete location and sending it to a laboratory. At a large scale, this would be expensive and highly labour intensive”. Working with collaborators through the STFC Food Network+, Marcelo is developing a proposal for a completely new approach, using remote satellite imaging and biogeochemical modelling. “For this project, we are focusing on estimating soil organic carbon, as this is a proxy for overall soil health” he says. “It indicates the rate at which the soil is being degraded and its ability to produce food or provide ecosystem services, such as purifying water and removing CO2 from the atmosphere”. Consequently, determining soil organic carbon by integrating satellite data, modelling and field measurements could provide an instant map of UK soil health, complementing ‘on the ground’ surveys. To begin, Marcelo and his colleagues are scoping all the possible ways that satellite data could potentially be used, to produce a shortlist of the most promising approaches. These include using remote sensing to estimate soil temperature, soil moisture levels, land use and land cover, and aboveground biomass. Combining these quantitative measurements with field-scale data could demonstrate how different land uses or crop types affect soil health. “This could even be extended to compare the impact of different soil management systems, such as no-till techniques, cover crops and crop rotations” says Marcelo. If data was collected over a time series, this could even show how the timings between tilling, planting and harvest affect soil quality. All of this valuable data could ultimately feed into policies to support the UK Government’s 25-year Environment Plan, which aims to incentivise farmers to improve vital ecosystem services, including soils. It could also prove crucial in our ongoing battle against climate change. “Achieving net-zero will only be possible if we both reduce emissions and remove carbon from the atmosphere” Marcelo says. An accurate map of UK soil condition would enable high-carbon areas, such as peatland, to be preserved and also identify regions where soil carbon could be improved through better management techniques. Clearly, the potential benefits of this project are significant, but it can only succeed with input from a wide range of disciplines – from soil scientists and agronomists, to satellite experts and climate modellers. Indeed, Marcelo had first thought about using satellites to monitor soils several years ago, but the catalyst for the project came when he attended the STFC Food Network+ Sandpit Event ‘Adapting to climate change: climate-smart agriculture’ in March 2019. It was here he met his future collaborators, Lizzie Sagoo (ADAS, an environmental consultancy), Daniel Morton (UK Centre for Ecology and Hydrology) and Martin Hardcastle (University of Hertfordshire). Since then, the network has grown exponentially, resulting in a workshop in September 2019 attended by experts in a wide range of fields. “This had a truly multidisciplinary and even international reach, including participants from Brazil, the US and Norway, besides start-up companies that use satellite data, such as SatSense” says Marcelo. “Talking with so many different people really helped to formulate our ideas”. Once these techniques have been refined, they could potentially be applied to sensors on drones, opening links to precision agriculture, where inputs (e.g. fertilisers and pesticides) are only applied where and when needed. Ultimately, Marcelo believes major benefits could be realised by this combination of modelling and remote sensing in developing countries, or in his home country of Brazil. “During my early research years, I spent time in Africa researching sustainable agricultural techniques, and I am currently involved in a large project on climate-smart agriculture there. I would really like to apply this approach to support climate change adaptation and mitigation strategies globally” he says. In the meantime, the challenge of mapping the UK’s soils is enough. And when he’s not at work, Marcelo turns his attention to the soils around his home. “As a soil scientist, perhaps it is not surprising that I am a keen gardener!” he jokes. For millions of people across the globe, rice is the foundation of their diet. But this particular crop can contain unsafe levels of arsenic: a poisonous mineral that can cause death. One project funded by the STFC Food Network+ is seeking to understand how exactly arsenic accumulates in rice, which could ultimately inform safer production and cooking practices. Arsenic naturally occurs in underlying rock, particularly in the regions that border the Himalayan mountain range such as India and Bangladesh. This means that arsenic can easily contaminate groundwater in these regions. “Most people in these regions are aware that they shouldn’t drink water contaminated with arsenic” says Manoj Menon, a lecturer of environmental soil science at the University of Sheffield. “But there is a wider issue of arsenic accumulating in the food chain. Rice is especially problematic because it is a very thirsty plant that takes up a lot of water”. Indeed, for typical paddy-field style irrigation systems, it takes an estimated 2,500 litres of water to produce a single kilogram of unmilled rice. Furthermore, for many countries in south Asia, the average daily rice consumption can be as high as 500g-700g per day (pre-cooked weight), compared with just 15g for Europe. Clearly, this issue needs a holistic approach where crop breeding, irrigation schemes and cooking methods are all optimised to reduce arsenic contamination in rice. But before this can start, many fundamental gaps in our understanding need to be answered. Manoj began this task by asking how arsenic is distributed within the rice grains themselves – does it concentrate in particular regions or is it present throughout? To answer this, he turned to the UK’s national synchrotron Diamond Light Source, based at the Science and Technology Facilities Council’s Rutherford Appleton Laboratory. Diamond works like a giant microscope, but is 10,000 times more powerful than traditional models. It harnesses the power of electrons by accelerating them to near-light speeds, so that they give off light a billion times brighter than the sun. The light is directed into laboratories known as ‘beamlines’, where it is used to study anything from viruses and vaccines to ancient scrolls and jet engines. “Our samples were longitudinal sections of individual white rice grains, less than a millimetre thick” says Manoj. Using the X-ray beamline, Manoj produced a high-resolution map comparing the distribution of arsenic with other compounds. Crucially, arsenic was mostly concentrated around the outer layers of the grains. The essential nutrient zinc, on the other hand, was present around the embryonic part of the seed. “This fits previous works and also suggests that arsenic levels could be reduced without affecting the abundance of important micronutrients. This could be through refining the polishing process that removes the outer bran layer, or through alternative cooking methods”. Following this, Manoj investigated how arsenic levels varied across different rice cultivars and genotypes. His range of samples covered 55 different varieties, including both wild rice and supermarket brands. “We looked at brown rice, white rice, long grain, short grain, medium grain, organically produced and non-organically produced” says Manoj. Since it took between eight and nine hours to produce each high-resolution map using the Diamond Light Source, Manoj used classic analytical techniques to allow a faster comparison: Liquid Chromatography and Mass Spectrometry. Reassuringly, the results showed that for most of the samples, the levels of arsenic fell well below the European safety threshold for adults of less than 0.25 milligrams per kilogram. However, many of the samples exceeded the threshold for children, who have a much lower safety limit of 0.1 milligrams per kilogram. “In particular the highest arsenic levels were seen in organic rice samples” says Manoj. The results also confirmed previous studies which found that brown rice has higher arsenic levels than white. But Manoj cautions against avoiding brown rice on this principle: “Brown rice has health benefits not found in white rice, including higher levels of fibre, vitamins and minerals”. Since these initial results, the project has taken on a momentum of its own. “After this work with the STFC Food Network+, we have secured additional funding from the Global Challenges Research Fund, which allowed us to set up an Arsenic in Rice Research Network (ARRNet)” Manoj says. He is currently using this to investigate how different cooking methods may affect the distribution of arsenic, besides conducting surveys to understand how aware people in India and Bangladesh are of arsenic contamination in rice. A rice field experiment has been planned in India in 2020-21 to optimise irrigation practices. “Our long-term goal is to apply this knowledge in these regions to help people live with arsenic in the environment” Manoj says. “This initial small grant from the STFC Food Network+ acted as a spark that has really changed my life a lot” he adds. “It is a brilliant initiative to have small pots of money available that are easier for researchers to access than big grants with more competitive and lengthy application processes. This helps to get projects started”. Despite his work, he still enjoys a good plate of rice, and advises that Europeans shouldn’t be too worried about arsenic contamination. “Our message is that it is the total amount of rice you eat that is the main risk factor” he says. “For the average consumption rate of Europeans, arsenic contamination shouldn’t be a problem, although it is perhaps best to restrict how much rice children are given”. Manoj and his team have had two papers published on this project: Menon et al (2020) Do Arsenic levels in rice pose a health risk to the UK population? Ecotoxicology and Environmental Safety Menon et al (2020) Improved rice cooking approach to maximise arsenic removal while preserving nutrient elements Across the world, many communities are already experiencing increasing droughts due to climate change. As the global population increases, securing enough supplies of clean, safe freshwater is a critical priority and using our current resources more efficiently needs to be part of this. Since farming is one of the largest consumers of freshwater, reusing waste water within agriculture could have a significant impact, however existing techniques are limited and difficult to apply at scale. But exciting pilot studies funded through the STFC Food Network+ are already bearing fruit – quite literally – in finding an alternative approach. “The novel aspect of this project is that we are using an established technique for a purpose it has never been used for before - to purify waste water” says project lead Devendra Saroj, Head of the Centre for Environmental Health and Engineering at the University of Surrey. The main issue with using waste water from industrial sources within agriculture is the presence of contaminants which can then accumulate in plants and seeds. Devendra’s approach is based on treating waste water with pulses of electrons that will react with organic compounds and instantly degrade them. Similar electron beams are already used widely in other applications, such as the security and health sectors. “Ultimately, using electron beams could purify wastewater to a very high standard within minutes” Devendra says. This is in stark contrast to existing membrane-based purification methods which can take several hours. His initial results on wastewater samples from textiles and mixed industrial uses are already promising, with over 95% of organic compounds being removed. “This is on a par with conventional techniques but much faster” Devendra says. To assess whether this water could safely be used for agricultural purposes, the team have been testing the purified water on plants (such as lettuce and beans) grown in petri dishes. Reassuringly, the results showed little difference between tap water and the purified wastewater, with the seedlings appearing completely healthy with no growth defects. “We are now talking with companies who specialise in hydroponic growing systems, to test this water on vegetables grown commercially” says Devendra. “Since these are closed agricultural systems, these could potentially be coupled to places where waste water is generated”. Another long-term goal is to use wastewater from actual farms, for instance to purify water containing run-off from organic fertilisers. But the immediate issue is to scale-up the process, since the current bench-size prototype model is only capable of handling sizes up to a litre. This may require a fundamental shift in production processes as Devendra explains: “Most electron beam applications are for scientific uses in laboratory settings. Manufacturers will have to adapt the instruments if they are to be used mainstream”. With so many factors to consider, including cost, ease of use and electron beam concentration, these proof-of-concept results will play a key role in convincing manufacturers to take up the challenge. For Devendra, the project illustrates perfectly the STFC Food Network’s goal of catalysing new ideas through bringing different disciplines together. “I would encourage researchers to participate in the network, even if they don’t see an immediate connection to their work” he says. It was through one of the Food Network’s Sandpit events, for instance, that he met physicists who develop accelerators that create electron beams. “They hadn’t thought of using this technology in an application like water recycling but with my environmental background I saw the opportunity” Devendra says. “I enjoy actively participating in the STFC Food Network because it allows me to bring my skills and contribute to areas that I don’t have specific expertise in, such as climate change. Bringing different disciplines together allows problems to be addressed from different angles”. With particular thanks to Dr Donna Pittaway at STFC Daresbury Laboratory Specially-equipped drones could soon help small holder farmers control one of the deadliest killers of coffee plants. Coffee is one of the most traded agricultural commodities and has become a lifeline for many developing regions in the world. This includes the Chiang Mai region in Thailand, where the government is on a mission to become the ‘coffee capital of South-East Asia’, focusing on the premium Arabica varieties. But these ambitions could be jeopardised by a parasitic fungus. Coffee leaf rust is a global disease which attacks the leaves of coffee plants, ultimately decimating the coffee bean harvest. The fungal spores spread easily via wind and rain, meaning that a single outbreak can wipe out plantations over entire regions. Sri Lanka, for instance, was once exclusively planted with coffee until a coffee leaf rust epidemic in 1892 destroyed all of the trees, prompting the farmers to plant tea instead. With fungicides being prohibitively expensive and not an option for organically-certified farms, the only way smallholder farmers can control the parasite is to remove infected plants as soon as possible. Yet even this is currently a challenge – although this STFC-funded project could soon make the process much easier. “It’s very difficult for these farmers to monitor coffee leaf rust, because the plantations are often on the sides of rugged mountains and intercropped with different species: very different from the neat rows we have on UK farms” explains Anthony Brown (Durham University). He first became aware of the problem of coffee leaf rust when he was introduced via the STFC Food Network+ to Oliver Windram, a researcher of remote-sensing technologies for crop plants (Imperial College, London). Oliver’s earlier research in plant pathology had uncovered a real need within agriculture for methods that could quantitatively measure plant disease in the field. This led him to develop remote-sensing technologies for measuring disease on wheat and broccoli, using machine learning to detect and quantify infection. Together, Oliver and Anthony proposed an image-based detection system using drones that could easily fly over the hillsides, allowing infected plants to be identified much more quickly. This draws on Anthony’s expertise in data analytics and unmanned aerial vehicles, and is based on recording spectral data. Their method measures the wavelengths of light reflected off the surface of the plant leaves and records how the intensity of light varies as a function of frequency. The result is a ‘heatmap’ where a large difference in signal intensity indicates the presence of coffee leaf rust. The project began with field visits to coffee plantations in Thailand to test which wavelengths could most accurately discriminate between healthy and infected plants. This in itself proved an experience: “It was the first time I realised that coffee berries are actually red!” Anthony jokes. The team walked among the plants with spectroscopes to compare the signatures of reflected light from uninfected plants and those with varying degrees of coffee leaf rust. Unfortunately, the optimum wavelengths all fell within a range not covered by commercially-available cameras. “When we tried using off-the-shelf cameras, the images were just not sensitive enough to detect coffee leaf rust. But it is important that this solution is affordable for farmers, who are the ultimate end-users” says Anthony. For this reason, they are now engaging with industrial partners to develop a bespoke filter that would enable a commercial camera to read these wavelengths. Anthony and Oliver hope that by January 2020 the prototype will be ready to undertake proof-of-concept flights over plantations in Thailand. Focusing on the end-user and engaging them throughout the planning stages also made the team realise that there was another potential application for this technique. “Farmers are really keen to know exactly what varieties of Arabica coffee they have, since pure products can command better prices. But there are very few records for these areas” Anthony says. He is confident, however, that spectral imaging could distinguish between them, potentially opening up new markets for small holders. “Interacting with end-users to learn what is important for them – rather than just assuming what they need - has been one of the most rewarding aspects of this project” he says. Nevertheless, interest in this work has also had a “snowball” effect in opening up a plethora of new research opportunities for him. “Through my work for the STFC Food Network+, I have now been invited to collaborate on projects using remote sensing to understand global warming impacts on trees across Europe and Africa, besides mangrove forests in South America”. The experience has certainly made him keen to be involved with more interdisciplinary projects that combine different skill sets to create novel solutions, and credits the STFC Food Network+ for encouraging these opportunities as part of its fundamental strategy. “Applying your expertise from one field to another can take you out of your comfort zone, but also be some of the most impactful work that you do” he concludes. Air pollution has been described as one of the UK’s most severe public health challenges and also damages natural environments. One of the most concerning pollutants is ammonia: besides forming smog and particulate matter that can cause cardiovascular and respiratory disease, it also deposits excess nitrogen in habitats, which reduces biodiversity. Most (88%) of ammonia emissions originate from agriculture, particularly from manure and inorganic fertilisers. Worryingly, unlike other air pollutants such as nitrogen oxides, ammonia emissions are actually increasing and are consequently a key component of the UK Government’s 2019 Clean Air Strategy. But whilst government, industry and researchers agree this trend must be reversed, they face a key obstacle in doing so: measuring ammonia emissions remains no easy task indeed. “It is really important that we are able to accurately measure ammonia emissions from agriculture” says Daniel Gerber, of STFC Rutherford Appleton Laboratory. “At the moment, most UK studies use wind tunnels to measure ammonia emissions: these are typically 2 metres long and funnel air through a liquid acid, which is analysed later in a laboratory. Although this does work, it is slow and requires significant person power”. A physicist by training, Daniel’s work usually involves equipping space missions with highly sensitive instruments to detect radiation in outer space, rather than more ‘down to earth problems’. Indeed, Daniel wasn’t even aware of how severe the problem of ammonia emissions in the UK was until his group leader Brian Ellison (STFC RAL Space) attended a STFC Food Network+ Sandpit event in March 2018. Here he was introduced to Lizzie Sagoo from ADAS, an agricultural and environmental consultancy, who asked if his methods could be applied to measure ammonia emissions on the ground. This presented a stimulating challenge for Daniel and his colleagues: “Although our technology can detect ammonia in outer space, measuring it from earth is a completely different scenario. Since space is a vacuum, it is a benign environment for making measurements but in earth’s atmosphere you have other air particles, winds and temperature variations to contend with. We weren’t sure if it could work”. Brian and Lizzie submitted a proposal for an STFC Food Network+ Scoping Grant, to fund a project that would investigate if remote measuring of ammonia emissions was theoretically possible. This was ultimately successful and, starting at the very beginning, the team first worked out which, if any, radio frequencies could be used for detecting ammonia. Every molecule emits tiny radiowave signals, in the form of electromagnetic waves produced by charged particles within the atoms. The frequency of these waves is characteristic of the molecule’s structure; hence a specific gas can be measured by detecting the strength of its characteristic frequency signature. However, these signals can be weakened by other gases in the atmosphere, especially water vapour. This presents a compromise as Daniel explains: “Low frequency signals are less attenuated in the atmosphere but they also tend to be weaker to begin with, so are harder to detect”. Nevertheless, using models of the atmosphere and simulations, he and his colleagues identified a handful of signals that could be potentially viable. These results enabled them to secure a STFC Proof-of-Concept grant to start designing a prototype instrument. “We envisage that the instrument will be about the size of a small fridge, that could be towed into a field on a trailer or mounted on a wall” Daniel says. Crucially, it would be capable of measuring in real time, allowing it to detect any sudden surges in emissions which could then be investigated. A portable, easy-to-use instrument would also enable a much denser data map of ammonia emissions across the UK. This could ultimately help farmers make informed choices on when and how to spread manure and to assess whether current storage facilities adequately restrict emissions. These potential gains aptly illustrate the STFC Food Network+’s commitment to support projects that can deliver measurable impact towards a sustainable agricultural sector. “Without the STFC Food Network+, we would not have realised the value of an instrument to measure ammonia on the ground” Daniel says. He also stresses how important it was to interact with real people in order to truly understand what was needed. “Our conversations made us realise that ease of use and operation were more critical than using our space heritage to develop a supremely sensitive instrument. We were also able to visit a farm and see the conditions where it would be used: with dust in the air and mud everywhere, it was clear that this instrument couldn’t only be suited to a clean laboratory environment!” Besides the cognitive challenge, Daniel has enjoyed the rich experiences the project has brought. “I normally spend all day in clean offices, then suddenly I was pulling on wellies and wading through manure on farms…” he says. Despite the muck, he is keen to become involved in more interdisciplinary work. “This project has made me wonder how many other potential applications that we are not aware of could benefit from our technology… the challenge now is to connect with and meet those users.” After all, you can only begin to try and solve a problem once you know about it. It sums up the STFC Food Network+‘s ethos perfectly: bringing together those with a need with those that have a potential solution. What conditions create that ‘perfect storm’ where food prices escalate wildly, leading to riots and unrest? Risk analyst Aled Jones (Anglia Ruskin University) is applying techniques he originally used to study the origins of the universe to answer that question – and help protect our food systems from the effects of climate change. “Making our food systems resilient to climate change is not just about producing enough food, as past events have shown. There have been cases where a small food production shock has had a high effect on food availability, and others where a massive physical disruption had no impact on food accessibility. It all depends on market forces and how governments handle the situation” says Aled. As director of the Global Sustainability Institute, he is applying mathematical data processing techniques to understand how social systems interact with agricultural production to ultimately determine food accessibility. One may presume that the most important factor is our ability to produce food in the first place, but Aled argues that price is the dominant issue. “Price has a greater effect on food access than physical access, since it determines who can actually afford food. But we are really bad at knowing what influences price when there are so many factors, such as markets, speculation and currency values”. With price being so critical, it is essential to know how this responds to disruptions in food production caused by increasingly frequent extreme weather events (so-called ‘food shocks’). To investigate this, Aled collaborates with the marketing and financial sectors, and, through the foreign office, multinational retail consortia and agrochemical companies. “Insurance companies are often ahead of academia in the sense that they have a lot of data about the conditions that surround food production shocks” he says. The traditional methods used to explore how these different sectors respond to food shocks include interviewing and ‘war game’ scenarios: “Essentially this involves locking representatives from markets and government in a room for a day and seeing how they respond to a hypothetical extreme yet plausible event that affects about 10% of global food production” says Aled. However, these methods are highly subjective and don’t always correspond with real-world situations. Searching for a more rigorous approach, Aled remembered his days as a PhD cosmology student, where he used image processing techniques to study telescope data on the cosmic microwave background: the oldest electromagnetic radiation in the universe. “I realised that those techniques of categorising information could provide new insights into food price data – uncovering new patterns and causal components”. Through the STFC Food Network+, he formed partnerships with the Department of Applied Maths and Theoretical Physics at the University of Cambridge and the UK Met Office. The aim was to review a range of analytical techniques for their ability to automatically detect food price shocks within datasets. “It’s really the same thing I did in my PhD: applying maths to clean up data and search for hidden patterns within the signals.” Besides tools from the finance and insurance sectors, these techniques include those used to detect earthquakes and exploding supernova stars. As Aled explains: “Normally people look at when a production shock or food riot has happened and then try to work out what it caused or what caused it. But this can miss cases where similar conditions led to different outcomes. Our aim is to find a technique that can objectively identify when a price shock has happened, what the characteristics of a price shock are and a way of categorising them.”. Having identified a number of promising algorithms, the group are now applying these to past historic events. Ultimately, understanding the conditions and market behaviours that combine to cause food scarcity will allow governments to be proactive and set in place protective strategies. “We hope these techniques can be used to develop hypothetical future scenarios so that governments, businesses and the insurance sector can ‘stress-test’ their plans to manage food shocks” Aled says. He also hopes that it could help develop policies that link up sustainability plans at regional, national and international levels. “Local food systems minimise environmental damage and carbon footprints, but if one is lost due to drought or a flood, you need links to the global system to survive. And when conditions are good, local systems can give their surplus to provide resilience elsewhere” he explains. Aled credits the STFC Food Network+ with giving him the time and space to try a truly novel idea. “This project has allowed us to take a more objective approach than traditional methods. By looking at historic price events and categorising them, we can then work with partners who explore the impact of weather on food production or the impact of prices on people, to better inform automatic models based on those behaviours.” Meanwhile, whilst this work occupies most of his time, Aled’s original love of astronomy has been rekindled through his young sons’ interests. “I now know more names of moons and dwarf planets than I did when I was actually studying astronomy!” he jokes. It just goes to show how creative thinking and interdisciplinary partnerships can generate truly novel solutions to improve our food systems. Climate change is widely claimed to be the biggest challenge facing humankind and is already impacting farmers in some of the world’s poorest regions. Adapting to rapidly-changing weather patterns will be critical if we are to produce enough to feed the growing population. Big Data could be a key instrument to achieve this as Seb Oliver has been demonstrating with his STFC FoodNetwork+ supported project: Forecasting Agricultural Crop Yields at National scales (FACYNation). An astrophysicist at the University of Sussex, Seb is certainly comfortable with using Big Data. His particular specialism is tracking the evolution of galaxies using infra-red light captured by satellites and telescopes. More recently he has become interested in Big Data approaches for more ‘down to earth’ problems, including projects in the medical sector to coordinate patient records over time to improve diagnosis. An introduction to Met Office climate scientist (and former astrophysicist) Edward Pope during the 2018 February STFC Food Network+ Sandpit event inspired an idea to build a modelling tool that could increase the climate-resilience of food supply chains. In the near future, entire regions are projected to experience new temperature regimes, so it is vital that we can forecast how different crops would respond. “One approach would be to use our knowledge of plant biology” says Seb. “But this requires detailed physiological understanding and these forecasts may not correspond with our observations in the field”. To brainstorm new approaches, Seb organised a two-day ‘hackathon’, which brought together meteorologists, theoretical physicists, data scientists and specialists in machine learning. Ultimately, they opted for an empirical approach that converted actual data, in this case USA maize yields and meteorological records, into a model describing the relationship between maize yields, temperature and precipitation. This used a Bayesian modelling technique, originally applied by Seb’s postdoc Peter Hurley to solve astronomy challenges. “A key advantage is that this model is based on actual observations, hence no detailed knowledge of physiology is required” Seb says. “It is also more useful than simple correlation methods since these are only really accurate for slight variations, rather than completely different scenarios.” Another advantage is that the Bayesian approach allows further variables to be added easily, such as soil conditions or pollution levels. Having demonstrated proof-of-concept with maize grown in the USA, Seb and the team are keen to develop the model for different crops, countries and varieties. “We are also investigating new sources of data, for instance earth-observation photographs to quantify yields from banana plantations” Seb says. Ultimately, he hopes the model will become a freely-available, open-source platform that researchers around the world can develop and contribute to. Since the model’s algorithms don’t require super-computers, farmers in developing countries could particularly benefit from it. Nevertheless, for the next stage he is focusing closer to home by developing a model for UK wheat breeders. Currently, new varieties of wheat are trialled by growing them at specific test sites and measuring the average yield over five years. However, the results at these sites may not reflect the variation that would be seen if the crop were planted over the whole UK. Through an extension grant from the Food Network+, Seb is now helping to develop SIMfarm 2030: a model that can use the initial test results to predict how new varieties would perform across the whole UK. This is being led by plant physiologist Jake Bishop (University of Reading), who specialises in how crops are affected by stressful weather conditions. Potentially, SIMfarm 2030 could hypothesize the best-suited varieties for different climate-change scenarios. “This project came from the success of FACYNation and builds on the Met Office’s “food and farming” research programme sponsored by the Government’s Department for Food, Environment and Rural Affairs” Seb says. Throughout this work, collaboration has been – and continues to be- a strong theme, engaging researchers across disciplines, from PhD students to Professors. Having convened interdisciplinary meetings in the past to investigate how to apply data science to global challenges, Seb appreciates the strategic role of networks such as the Food Network+. “Events like the STFC Food Network+ Sandpits are so important because bringing people together is key” Seb says. “As data scientists, we have valuable tools to offer but we don’t necessarily know where the problems are”. Seb also credits the Food Network+ for supporting a sector of the knowledge-transfer chain that can struggle to attract funding. “Taking knowledge and theory to the next level of practical application can be challenging” says Seb. “But having proof of principle gives us a stronger case to take to investors and stakeholders”. Outside work, Seb’s fascination with models continues. “I like to play board games, especially strategy games such as ‘Ticket to Ride’ and ‘Pandemic’ he says. But I am always trying to work out the mathematics of the game!” No doubt, it won’t be long before the real world presents another challenge for him to get his teeth into… We’d all like to trust that the ingredients of our food products match their labels but unfortunately food adulteration – where certain ingredients are substituted for cheaper, indistinguishable alternatives – is rampant within the industry. Although such products can be identified using high-spec laboratory equipment, there is an urgent need for a portable and cheap detection system on the front line - a problem Paul Richardson has been addressing with the wider STFC Food Network+. “The adulterated products that are caught are currently only the tip of the iceberg – we have no idea how much is circulating undetected” says Paul, whose interest in the issue began with his Master’s degree project which investigated whether spectroscopic methods could detect adulterated coconut water. Proclaimed as a natural ‘superfood’ with a wealth of health benefits, coconut water sales have rocketed over recent years. But severe allergic reactions and even deaths have resulted from counterfeit products containing undeclared cow’s milk, often used to improve the product’s appearance. For his Master’s project, Paul demonstrated that contaminated coconut water could be detected using Raman scattering, which irradiates samples with a laser beam and measures the pattern of scattered light. Depending on the types of atoms, some of the scattered light undergoes an energy change, causing the wavelength to shift. Examining the scattering spectrum produces a distinct ‘fingerprint’ that can be used to work out the molecular composition. Whilst this works well in the lab on carefully-prepared samples, conventional Raman can’t be used on drinks still in the original packaging, which slows down the testing procedure. As Paul explains, “Conventional Raman only measures the scattering directly at the incident spot, meaning that surface scattering completely overpowers deeper signals. The only way to increase depth is to build a more powerful laser which would damage the sample”. At the STFC Food Network+ Sandpit event in February 2018, Paul’s supervisor Roy Goodacre (Formerly University of Manchester - now University of Liverpool) joined forces with Pavel Matousek (STFC Central Laser Facility) to pitch the idea for a project investigating a new technique for through-container detection: Spatially Offset Raman Spectroscopy (SORS). For Paul, it would perfectly combine his analytical skills, interest in food adulteration and thirst for research experience. “I was delighted to be able to extend this work through the STFC Scoping Project award, particularly as SORS could be a very valuable detection technology within food systems” Paul says. SORS is based on the principle that deeper scattering is more likely to be detected at a spatial offset from the incident laser. Measurements are made at both the incident spot (to get the surface measurement) and at the offset (where more deeply penetrated signals are stronger than the surface), then statistical methods used to subtract the surface signal. Crucially, this allows greater penetration to be achieved without a stronger laser. This time Paul turned his attention to adulterated fruit juices. Since pure products command a considerably higher ‘premium’ price tag, easy money can be made by substituting fruit sugars for high-fructose corn syrup. To see whether SORS can detect this, Paul prepared a range of fresh fruit juices adulterated with different amounts of syrup, but with the same total sugar concentration. Keeping things as realistic as possible, Paul tested the solutions in packaging from supermarket-bought products but immediately hit a problem. “We found that Tetra Pak and wax cartons completely stop the laser from getting through” he says. “It’s unfortunate since the vast majority of fruit juice products come in such packaging”. Undeterred, Paul persevered using transparent glass and plastic bottles, which admit laser light, and demonstrated that SORS does have potential for a portable system. “The proof of concept is absolutely there, all we need to do is tweak it” Paul says. “At the moment, there is still some noise from the outer packaging but our group are working on mathematical approaches to subtract this from the final signal”. Although fruit juices may be out at present, an alternative avenue for portable SORS could be the bottled oil market, since these frequently come in glass or clear plastic containers. “There is certainly a need since hazelnut oil is often used in place of more expensive oils, putting people with nut allergies at serious risk” he says. “I’m very proud to be part of the SFN, particularly because as a group it is pushing forward to make the world a better place, working together with companies and industrial partners” says Paul. He particularly attributes it to helping him gain a thorough understanding of the academic world, including forming collaborations, sourcing funding and ‘learning about science I didn’t even imagine existed!” An enthusiastic cook, he has enjoyed learning how his technical skills can be applied to improve food systems for the future. “As an analytical chemist, it would be strange for me to not be interested in food: the kitchen is basically a tasting laboratory and one that deserves honest ingredients” he concludes. A novel project combines drone technology, space science and reproductive biology to detect when cows are ready to be inseminated. Led by Niamh Forde, University of Leeds. If you’re a dairy farmer, one of your biggest concerns is making sure your herd gets pregnant on time. Dairy cows only produce milk following successful calving, but there is a narrow window of time when a farmer needs an animal to become pregnant. Missing these opportunities can quickly generate losses of hundreds of pounds per cow, due to disrupted milk production and having to pay for multiple rounds of artificial insemination. Consequently, dairy farmers have to be on the lookout for when animals display ‘heat’: behavioural and physiological signs that cows show just before ovulation. “Sometimes if you go out early in the morning, you can literally see the steam rising off the cows that are in heat, hence the name” says Niamh. “Unfortunately, most of the time the signs of heat are much more subtle and can be very difficult to see”. Current detection methods are far from perfect and can be very time consuming, for example observing mounting behaviour in a group of females. Given that a typical dairy herd can be over a hundred-strong, the need for a quick, accurate and affordable solution is clear. It seems a problem made for Niamh, who has studied the molecular and physiological events of early pregnancy in a wide range of animals including pigs, cattle, mice, humans and even marsupials. But she arrived at her solution purely by chance. After a colleague couldn’t attend the STFC Food Network Sandpit event in February 2018, Niamh went in their place and “got chatting to the people on my table while charging up my laptop.” One of them was Stephen Serjeant, based at the Open University who designs algorithms to analyse temperature differences in distant galaxies. “I thought ‘If you can measure temperatures in galaxies so far away, then perhaps we could use it to detect heat in cows!’” she says. On finding that her other neighbour, Anthony Brown (Durham University) was an expert in drones, everything suddenly came together. The basic idea is to scale down Stephen’s pattern-recognition algorithms to detect the distinct temperature changes in individual cows during heat. Once perfected, they hope to combine the program with drones fitted with infra-red imaging devices that can sweep across herds while they are out at pasture. A truly interdisciplinary project, it requires the expertise from all three researchers to be successful. Currently, they are demonstrating proof of concept using a static device mounted indoors. “We still need to work out how many data points we need for each individual cow so that we can accurately detect signs of heat” says Niamh. “This is where Stephen’s skills really come into their own”. Once optimised, they intend to move to using drones to conduct an outdoor experiment later this year with a herd of dairy cows synchronised to ovulate at a specific time. “This should give us a baseline set of data that we can use to refine the algorithm so that we get consistent outcomes” Niamh says. A particular benefit about this technique is that it can be applied to farms with very different management systems, from small cooperatives in Sub-Saharan Africa to a high-end operation in the UK or USA. “Speaking to farmers has shown me that they are generally keen to use methods that are based on a physiological process, as it’s something they see occurring in their animals and understand”. If successful, Niamh envisages that this method could easily be applied to other areas, including reproductive management in conservation parks and zoos. It’s been quite a journey for a self-confessed city girl: “My family think it’s hilarious that I now work with the farming industry as I grew up slap-bang in the middle of Galway city on the Irish west coast” Niamh says. Niamh moved to Leeds to start her own lab three years ago and since then has said that being part of the STFC Food Network+ proved invaluable in helping her to integrate into the food-science community. “The Food Network+ has allowed me to interact with people I wouldn’t necessarily have met otherwise, such as Stephen and Anthony, and made what I thought were ‘really difficult’ sciences such as astrophysics more accessible. It gives me the confidence to ask ‘stupid questions’ which often spark new ways of thinking about my own research”. It is a fitting illustration of how the network creates opportunities for researchers from very different disciplines to design novel solutions towards more sustainable food systems. For Niamh, it’s been a very rewarding collaboration. “Reproductive biology is what I’m super-interested in and it’s been wonderful to use my fundamental knowledge towards helping farmers make a better living” she concludes. “The uterus is just the most awesome organ!” |
AuthorSeptember 2022 - Caroline Wood, Freelance Science Writer Archives
December 2023
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