Low pH foods can attenuate the glycemic response to starch-rich foods. It has been demonstrated that lemon juice, due to its low pH (pH≈2.3), inhibited key digestive enzymes thereby interrupting gastric digestion of starch in vitro. This effect can significantly reduce the glycemic response in humans. In particular, adding lemon juice to a starch rich meal reduced the mean blood glucose concentration peak by 30%. Considering the panoply of food options available, it is likely that other combinations have similar effects but no work has been conducted to develop a consolidated knowledge base to exploit this strategy. GlucoMatchMaker will go beyond the state-of-the art by addressing this knowledge gap. The main goal is to develop and test the real-life effectiveness of the first mobile app to guide individuals on how to mix and match starchy foods with other foods/beverages to attenuate glycemic responses. The research work will employ multidisciplinary knowledge and methodologies and is divided into 4 parts (1) Selection and characterization of starch-rich foods, low-pH foods/beverages and of how their combination influences starch digestion in vitro (WP1). (2) Determination of the conditions of effectiveness of these combinations (in silico models) (WP2). (3) Development of the first mobile app that will integrate this knowledge to guide the user on how to mix and match starch-rich foods with others to lower their glycemic impact (WP3). (4) Test the effectiveness of the developed strategy in a real-life context (WP4). This project addresses the United Nations and EU target to reduce premature mortality from non-communicable diseases by one third as part of the 2030 Agenda for Sustainable Development. The research plan was developed in the framework of “H2020 Work Programme - Health, demographic change and wellbeing”, specifically the aim to “translate new knowledge into innovative applications and accelerate large-scale uptake and deployment”.

Breeding for improved perennial ryegrass (PRG) cultivars to support pastoral based production systems for milk and meat is a critically important goal. However, genetic gains for traits such as forage yield and quality have very much lagged behind genetic gain for agronomic traits in cereals. One reason for this is the long breeding cycle in a typical PRG breeding programme, where a single cycle of selection can take 5-6 years. Genomic selection (GS) is a form of marker assisted selection that simultaneously estimates all loci, haplotype, or marker effects across the entire genome to calculate Genomic Estimated Breeding Values (GEBVs). The main advantage that GS could offer PRG breeding is to enable multiple cycles of selection to be achieved in the same time it takes to do a single cycle of conventional selection, thereby increasing the rate of genetic gain. Improving digestibility of the forage leads to an increase in animal performance, and is therefore an important target trait for forage breeders. Furthermore, it has already been shown that increases in organic matter digestibility can reduce methane emissions. Reducing methane emissions is a key target of the EUs climate and energy policy. In this action I will focus on developing and validating GS equations for feed parameters that are being used as model inputs into the Cornell Net Carbohydrate and Protein System (CNCPS). This CNCPS is currently being adapted to predict nutritional value to the grazing animal in pasture based production systems, and it is envisaged that it will be able to identify feed parameters limiting milk-solid production and thereby direct future forage breeding efforts. The work of this action will lead to a novel and innovative forage breeding programme that can select for multiple feed parameters to develop the ideal forage cultivars for pasture production systems.

Plant viruses continue to be one of the main threats to European agriculture, exacerbated by climate change, evolution of pesticide resistance, and loss of crop protection chemistries. Europe has ambitions of creating a more sustainable food system with a goal of reducing pesticide usage by 50% by 2030 as part of the European Farm to Fork Strategy. Achieving these goals requires robust integrated pest-management (IPM) approaches and real-time decision support systems (DSS) for farmers. In disease management there is a strong reliance on rapid, sensitive, and specific diagnostic tools built on a clear understanding of viral diversity. HealthyPlants will use high-throughput sequencing to (i) complete the first systematic survey of viruses of cultivated plants in Ireland and establish a baseline upon which to build improved diagnostic tools, (ii) establish the importance of arable margins and hedgerows as cereal virus reservoirs, and (iii) identify viruses on newly imported crops with potential phytosanitary risks. HealthyPlants will deliver the first database of viral sequences of cultivated plants on the island of Ireland, an open-access platform to support development of robust diagnostics within Europe.

The human gastrointestinal tract harbors a complex community of microorganisms that confer metabolic, immunological and neurological benefits to the host. This assemblage is known as the Gut Microbiome and has received increased attention over the last decade. Scientists have begun to uncover the importance of these bacterial inhabitants and expand investigations to consider how site-specific microbiomes affect host physiology. While more than one million cholecystectomies (gallbladder removal surgeries) are performed throughout Europe each year, the bacterial communities associated with the human gallbladder and its disease states remain unknown. Studies are lacking that characterize the effects of cholecystectomies on the gut microbiome. Without the ability to regulate bile entering the duodenum during food intake, it is expected that gallbladder removal will lead to downstream changes in the intestinal population. Here, the microbial composition of human bile, gallbladder mucosa, and biopsies of surgically removed healthy gallbladders (adherent and non-adherent microbiota) will be investigated using 16S rRNA metagenomics. The profiles will be compared to samples of a second cohort undergoing emergency cholecystectomies, in order to identify possible biomarkers for gallbladder disease. Once the gallbladder microbiome has been elucidated, the impact of its removal on the gut microbiome will be assessed. Using molecular and cultivation based techniques, on stool samples (collected during the recovery period) and analyzed for community composition, metabolomics, bile, fat and energy content. GallBiome will form the basis for establishing relationships between gallbladder microbiota, gut microbiota, and human health with a view to informing future development of diagnostics and therapeutics. Ultimately, characterization of the core gallbladder microbiome has important biological and medical implications with potential to lower the risk and incidence of cholelithiasis.

Today, there is a considerable desire to consume sustainable products due to healthy and ethical reasons, environmental sustainability, and issues related to greenhouse gas emissions. Ireland now specializes in producing beef, lamb, and dairy—which are the most emission-intensive foods—but plans to cut greenhouse emissions (50%) by 2030 and reach net zero emissions by 2050. Cheese manufacturing consumes significant quantities of energy (4.9-8.9 MJ/kg) and the study on the novel dairy-free cheeses has gained high interest due to the new opportunities offered by the worldwide market where it is predicted to rise to 3.90 billion USD by 2024. The dairy-free industry faces major challenges to formulate dairy-free cheeses with excellent nutritional properties, functionality, flavour, and texture—compared with the dairy-based cheeses. This study proposes to evaluate and manipulate interactions of plant proteins/carbohydrates/relevant ingredients through food material science, aiming to design an innovative dairy-free cheese with similar physicochemical, rheological, and sensory properties to the dairy-based cheese. This project will be carried out during a 2-year period at Teagasc with a 3-month secondment in University College Cork. Firstly, the physico-chemical interactions, structures and functional properties of materials will be studied and the most appropriate materials and their ranges will be determined (WP1). After producing some prototypes of dairy-free cheeses, the properties of them will be determined (WP2), and then, formulation(s) will be optimized (WP3). Finally, the quality of the optimized sample will be compared with commercially available cheeses (WP4). Results of this study will contribute to the industrial/sustainable production of dairy-free cheeses; thus, it will provide food security, sustainable lifestyles, and consumption patterns in alignment with current Teagasc goals, Horizon 2022, EU, and Irish government research initiatives.