Grass pea is a pulse crop with remarkable tolerance to drought as well as flooding, making its seeds an important local food source in several tropical countries, especially Ethiopia, Sudan and Eritrea as well as India and Bangladesh. In times of weather extremes causing crop losses, grass pea often remains one of the most available foods and the cheapest source of protein, helping people survive during food shortages. The mounting challenge of climate change increases the need for crops that can be grown sustainably and withstand weather extremes. Through its 8000-year history of cultivation grass pea has been a part of human diets - from Neolithic sites in the Balkans, through the bronze-age middle east, the Roman Empire and medieval Europe until the modern day. But despite its value for food and nutritional security, grass pea carries the stigma of a potentially dangerous food. Its seeds and leaves contain a neurotoxic compound that can cause a debilitating disease known as neurolathyrism. This disease only appears in people who are malnourished and consume large amounts of grass pea over several months. Yet the fear of neurolathyrism, which has been known since antiquity, has led to grass pea being undervalued by farmers, breeders and scientists, making it an 'orphan crop'. There is no significant international trade in grass pea and too little research to develop the potential of this resilient, sustainable source of protein. Grass pea is able to fix nitrogen from the air (through symbiosis with nodulating bacteria), can efficiently use soil phosphate through its mycorrhizal associations, can penetrate into hard, heavy soil and is relatively tolerant to pests and diseases. All these characteristics make it an ideal crop for agriculture where farming inputs (fertiliser, pesticides, irrigation, etc.) are limited, as is the case in most smallholder farms in Sub-Saharan Africa. We therefore believe that improved grass pea varieties can have a significant impact beyond the millions of people who already cultivate it in Africa today and could become a crucial sustainable food source for many more. Our project aims to remove the limitations of this crop by using the tools and resources we have already developed in our previous research to breed new varieties that are safe to consume, high-yielding, nutritious and resilient to environmental stress. We have identified new low-toxin variants with lower beta-ODAP contents than any existing varieties. In addition we have sequenced and assembled the grass pea genome and transcriptomes under stress and non-stress conditions and we are working to enable modern crop improvement methods on the back of these. Through this research partnership we have access to grass pea lines representing the global diversity of the crop and those that are locally adapted to East Africa and to expertise on smallholder agriculture and seed systems. The UPGRADE project will build on this foundation and create a partnership to translate bioscience research advances on grass pea into new varieties with tangible benefits for smallholder farmers. Besides this, our research will generate valuable data on the performance of grass pea and the physiological role and regulation of the production of the toxin in the plant. Through a better foundational understanding, we and other researchers will be better able to direct future breeding efforts and deliver the promise of grass pea.

The vast majority of problems that lie at the forefront of science are governed by mathematical equations that cannot be solved exactly. In the modern era, large-scale numerical computation and data analysis are powerful tools, but many questions still elude brute-force computation. For complex multi-scale and multi-parameter systems, it is often necessary to apply key reductions dependent on the smallness or largeness of certain parameters. The application of these reductions is called asymptotic analysis; these methods have the power to dramatically simplify complex systems to their salient features, extract key mechanisms, and provide details in regions where numerics and experiments fail. As noted by Crighton [1] "[the] design of computational or experimental schemes without the guidance of asymptotic information is wasteful at best, and dangerous at worst, because of the possible failure to identify crucial (stiff) features..." Some of the most challenging problems relate to the prediction of exponentially small effects that are invisible to traditional asymptotic analysis and often mistakenly considered as negligible. In some cases, these effects may correspond to some observable feature, such as an oscillation or wave in the system; in other cases, they may be largely non-observable, but instead serve to determine whether certain solutions are permissible. Over the last few decades, there has been an appreciation for the ubiquity of problems where exponentially-small effects are paradoxically important -- these problems can be found in studies related to dendritic crystal growth, viscous fluid flow, water waves, quantum tunneling, geophysics, and more. There are significant mathematical and computational challenges for the study of exponentially small terms. For example, the traditional mathematical techniques that exist, developed in the early 20th century, are usually insufficient. Exponential asymptotics is the name given to the set of specialised techniques that have been developed over the last two decades for these problems. In the last few years, some of the most significant applications of exponential asymptotics have related to the development of theory for free-surface flows. This includes the study of (i) water waves produced by gravity-driven flows past slow-moving full-bodied ships; (ii) solitary waves in a fluid of finite depth including both gravity and capillary effects; and (iii) viscous flows where bubbles or fingers are produced at an interface. These problems all involve crucial exponentially small effects. Despite the above successes, a significant bottleneck has emerged in numerous studies in the area: the majority of existing exponential asymptotic techniques are limited to ordinary differential equations where, for instance, only a one-dimensional fluid interface is considered. Many of the spectacular successes of exponential asymptotics that have emerged in the last two decades have analogues in higher-dimensional space or in time-dependent formulations, where the system is governed by partial differential equations. However, the standard techniques in exponential asymptotics are not easily adapted to study such situations. The most recent preliminary work on seeking extensions of the theory has shown that the likely avenue for progress lies with combining analytical methods with computational and data-driven approaches---hence a hybrid numerical-asymptotic approach to exponential asymptotics. The development of these methodologies, and the subsequent applications to multi-dimensional problems in fluid mechanics forms the main thrust of this project. [1] Crighton, D. G. (1994). Asymptotics--an indispensable complement to thought, computation and experiment in applied mathematical modelling. In Proc. 7th Eur. Conf. on Math. Industry (ECMI), Montecatini (pp. 3-19).

AUSTRALIA

This project will investigate the drivers of eating behaviour that occur during a prolonged period of overconsumption (excess intake of calories). Overconsumption is important as a major cause of weight (re)gain and obesity. The type of society which exists in many developed countries is said to represent an 'obesigenic' environment. This type of environment facilitates a high consumption of food (as well as encouraging sedentariness) and generates rapid weight gain that leads to obesity. The obesigenic environment 'offers' the possibility for people to overeat. People are able to eat too much of some foods because of excessive activation of hedonic (pleasure related) processes, or because of a defect in homeostatic processes. Firstly this means that people will eat more because of elevated sensations of pleasure during eating or heightened motivation to obtain a looked-for food. These (hedonic) processes are termed 'liking' & 'wanting'. Secondly, people will eat more because their physiological systems fail to shut off eating quickly (leading to large meals) or because food fails to suppress their hunger after eating. These last two processes are called 'satiation' and 'satiety'. The pleasure of eating can be divided into two components /'liking' & 'wanting'. Although these terms often occur together, they are quite different. Sometimes we do not have a strong wanting for foods that we like a lot; at other times we have a strong wanting for foods that are not especially liked (e.g. potatoes/food staples). Importantly, we have developed procedures that measure both the liking & wanting of foods. It is not known if overconsumption results from an increase in liking for certain foods, or from an increase in wanting for those foods. We will identify the types of foods selected during a prolonged period of overeating and whether this is driven to a greater degree by increased liking or wanting. At the same time it is important to be able to measure the actual changes in processes that control meal size (satiation) and which lead to the reduction of hunger after eating (satiety). We will identify which aspect of eating plays the major role in allowing overeating /a large meal size, or weak suppression of hunger. This will inform us how to use specific foods to control these two aspects of eating. It is important to be able to relate changes in sensations and behavior to underlying physiological processes. This means measuring chemicals in the blood that are known to be involved in appetite control. Some of these chemicals are thought to be involved mainly in hunger (ghrelin) or in satiety (GLP1, CCK) or in both hunger/satiety, liking & wanting (leptin). We will therefore assess the particular ways in which these signals influence overconsumption. Generating overconsumption in the long term leads to a gain in weight which may never be lost again and could impair health. We have therefore developed a 'safe' model of overconsumption that has arisen from a BBSRC project just finished. When overweight and obese people volunteer for a 12 week programme of supervised daily exercise (of fixed energy expenditure) some individuals lose weight and others do not. However, independent of weight loss all volunteers show decreases in heart rate, blood pressure, and an increase in fitness (key to becoming healthy). The reason behind this variability in response is that the poor responders who do not lose weight have increased their food intake to negate the energy lost. This increase can be interpreted as overconsumption and amounts to ~290 kcal/day. In absence of exercise this would lead to a dramatic weight increase of more than 6kg over a year. Therefore we can use this 'safe' form of overconsumption to examine changes in underlying behavioral drivers /liking & wanting, satiation and satiety/ and their association with signalling peptides. This provides a relevant long term method for investigating the drivers of food behaviour.