TEAGASC - The Agriculture and Food Development Authority

The use of high-frequency water quality monitoring has increased over several decades. This has mostly been motivated by curiosity-driven research and has significantly improved our understanding of hydrochemical processes. Despite these scientific successes and the growth in sensor technology, the large-scale uptake of high-frequency water quality monitoring by water managers is hampered by a lack of comprehensive practical guidelines. Low-frequency hydrochemical data are still routinely used to review environmental policies but are prone to missing important event-driven processes. With a changing climate where such event-driven processes are more likely to occur and have a greater impact, the adoption of high-frequency water quality monitoring is becoming more pressing. To prepare regulators and environmental and hydrological agencies for these new challenges, this paper reviews international best practice in high-frequency data provision. As a result, we summarise the added value of high-frequency water quality monitoring, describe international best practices for sensors and analysers in the field, and evaluate the experience with high-frequency data cleaning. We propose a decision workflow that includes considerations of monitoring data needs, sensor choice, maintenance and calibration, and structured data processing. The workflow fills an important knowledge-exchange gap between research and statutory surveillance for future high-frequency water quality sensor uptake by practitioners and agencies.

Background/Objectives: Saliva is gaining importance as a diagnostic sample in pigs. The aim of this research was to evaluate a panel of salivary analytes in three porcine diseases and establish predictive models to detect them. Methods: Saliva samples were obtained from healthy pigs (n = 97) and pigs affected by meningitis due to Streptococcus suis (n = 118), diarrhea due to enterotoxigenic Escherichia coli (ETEC, n = 77), and porcine reproductive and respiratory syndrome (PRRS, n = 52). The following biomarkers were analyzed: adenosine deaminase (ADA), haptoglobin (Hp), calprotectin (Calp), aldolase, alpha-amylase (sAA), lactate dehydrogenase (LDH), total protein (TP), and advanced oxidation protein products (AOPPs). Predictive models based on binary logistic regression and decision trees combining those analytes for detecting specific diseases were constructed. Results: The results showed a different biomarker profile between the groups. S. suis and ETEC pigs showed higher values of ADA, Hp, Calp, aldolase, sAA, LDH, and TP than healthy pigs. Pigs with PRRS showed higher values of Hp, Calp, sAA, and LDH than healthy animals. The constructed predictive models showed overall accuracies of over 78% and 87% for differentiating ETEC and PRRS, respectively, whereas the models did not accurately predict S. suis infection. Conclusions: Salivary analytes show different changes in pigs depending on the disease, and the combination of these analytes can contribute to the prediction of different diseases. Further studies should be conducted in larger populations to confirm these findings and evaluate their possible practical applications.

Background The gut microbiota is essential for maintaining nutritional, physiological and immunological processes, but colonic infections such as swine dysentery, caused by Brachyspira hyodysenteriae ( B. hyo ) disrupt this homeostasis. This study uses shotgun and full-length 16S rRNA sequencing in faeces, colonic contents and mucosa from pigs challenged with B. hyo to provide a high-resolution characterisation of hte taxa, functions and metagenome-assembled genomes (MAGs) of interest, disclose their association with the primary pathogen and how they are affected by the pathological changes of the infection. Results Changes in the microbiota were associated with disease severity. In early infection, no major findings were observed in diversity or abundance analyses, whereas in acute infection, B. hyo load, mucosal neutrophil infiltration, epithelial ulceration and mucosal thickness were clearly associated with changes in microbiota ordination, which were also associated with a decrease in species richness. Changes included a significant increase in Acetivibrio ethanolgignens , Campylobacter hyointestinalis and Roseburia inulinivorans , which, with the exception of C. hyointestinalis , established themselves as part of the core microbiota and shifted the colonic enterotype in acutely infected animals. MAGs analyses revealed that no major virulence genes were detected in the genomes of the species co-interacting with B. hyo in acute infection. Similarly, functional changes were observed only after the onset of clinical signs, with an increase in functions related to inflammation and toxic effects on the colonic epithelium. Conclusions Our study shows that in colitis caused by B. hyo , changes in the microbiota are mainly a consequence of the lesions that occur in the intestine, with no differences observed in early infection. Similarly, the bacterial species that are increased at the onset of clinical signs may promote intestinal inflammation caused by B. hyo infection, but the analysis of their genomes rule out their participation in the primary infection.

Introduction Infections caused by Campylobacter spp. represent a severe threat to public health worldwide. National action plans have included source attribution studies as a way to quantify the contribution of specific sources and understand the dynamic of transmission of foodborne pathogens like Salmonella and Campylobacter. Such information is crucial for implementing targeted intervention. The aim of this study was to predict the sources of human campylobacteriosis cases across multiple countries using available whole-genome sequencing (WGS) data and explore the impact of data availability and sample size distribution in a multi-country source attribution model. Methods We constructed a machine-learning model using k-mer frequency patterns as input data to predict human campylobacteriosis cases per source. We then constructed a multi-country model based on data from all countries. Results using different sampling strategies were compared to assess the impact of unbalanced datasets on the prediction of the cases. Results The results showed that the variety of sources sampled and the quantity of samples from each source impacted the performance of the model. Most cases were attributed to broilers or cattle for the individual and multi-country models. The proportion of cases that could be attributed with 70% probability to a source decreased when using the down-sampled data set (535 vs. 273 of 2627 cases). The baseline model showed a higher sensitivity compared to the down-sampled model, where samples per source were more evenly distributed. The proportion of cases attributed to non-domestic source was higher but varied depending on the sampling strategy. Both models showed that most cases could be attributed to domestic sources in each country (baseline: 248/273 cases, 91%; down-sampled: 361/535 cases, 67%;). Discussion The sample sizes per source and the variety of sources included in the model influence the accuracy of the model and consequently the uncertainty of the predicted estimates. The attribution estimates for sources with a high number of samples available tend to be overestimated, whereas the estimates for source with only a few samples tend to be underestimated. Reccomendations for future sampling strategies include to aim for a more balanced sample distribution to improve the overall accuracy and utility of source attribution efforts.

The food supply chain has a long cycle, a complex structure and numerous stakeholders, which makes it a challenge to ensure the security of the supply chain. The traceability system is a product management system that enables forward, backward and non-directional tracking of products. It should provide important guarantees, such as the ability to join all links in the food supply chain, monitor raw material collection, processing, storage and transportation, distribution and sales processes, and have a great impact on food safety and quality. Traditional traceability systems in the food supply chain are grappled with issues such as centralized data management, fragmented information flows, susceptibility to data falsification, and the emergence of isolated 'information islands,' hindering the seamless tracking and monitoring of products from farm to fork. Blockchain technology, heralded as the next disruptive force after the Internet, offers a paradigm shift with its decentralized architecture, distributed ledger, cryptographic security, and transparent data sharing, thus addressing the inherent shortcomings of traditional traceability systems. By leveraging blockchain technology, stakeholders can ensure end-to-end traceability in the food supply chain, facilitating real-time monitoring of crucial processes including raw material sourcing, production, storage, distribution, and retail, thereby bolstering food safety, quality assurance, and consumer trust. This chapter presents the challenges of current traceability systems in food supply chains. It also explains the principles and applications of blockchain in managing the food supply chain to ensure traceability, safety and quality. Despite the potential benefits, the widespread adoption of blockchain in food traceability faces challenges such as scalability limitations, interoperability issues, regulatory complexities, and concerns regarding energy consumption. Addressing these hurdles is pivotal for unlocking the full potential of blockchain technology in revolutionizing the food industry. Looking ahead, the chapter explores avenues for enhancing blockchain scalability, fostering industry-wide collaboration, and navigating regulatory frameworks to facilitate the seamless integration of blockchain solutions into the food supply chain. It offers insights into the innovative applications of blockchain technology, paving the way for a more transparent, resilient, and sustainable food system.

A rise in antimicrobial resistance coupled with consumer preferences towards natural preservatives has resulted in increased research towards investigating antimicrobial compounds from natural sources such as macroalgae (seaweeds), which contain antioxidant, antimicrobial, and anticancer compounds. This study investigates the antimicrobial activity of compounds produced by the Irish seaweed Alaria esculenta against Escherichia coli and Listeria innocua, bacterial species which are relevant for food safety. Microwave-assisted extraction (MAE), ultrasound-assisted extraction (UAE), ultrasound–microwave-assisted extraction (UMAE), and conventional extraction technologies (maceration) were applied to generate extracts from A. esculenta, followed by their preliminary chemical composition (total phenolic content, total protein content, total soluble sugars) and antimicrobial activity (with minimum inhibitory concentration determined by broth microdilution methods), examining also the molecular weight distribution (via high performance size exclusion chromatography) and oligosaccharide fraction composition (via high-performance liquid chromatography) of the polysaccharides, as they were the predominant compounds in these extracts, aiming to elucidate structure–function relationships. The chemical composition of the extracts demonstrated that they were high in total soluble sugars, with the highest total sugars being seen from the extract prepared with UAE, having 32.68 mg glucose equivalents/100 mg dried extract. Extracts had antimicrobial activity against E. coli and featured minimum inhibitory concentration (MIC) values of 6.25 mg/mL (in the case of the extract prepared with UAE) and 12.5 mg/mL (in the case of the extracts prepared with MAE, UMAE, and conventional maceration). No antimicrobial activity was seen by any extracts against L. innocua. An analysis of molar mass distribution of A. esculenta extracts showed high heterogeneity, with high-molecular-weight areas possibly indicating the presence of fucoidan. The FTIR spectra also indicated the presence of fucoidan as well as alginate, both of which are commonly found in brown seaweeds. These results indicate the potential of antimicrobials from seaweeds extracted using green technologies.

In Northern Europe, the application of fungicides to winter wheat crops is primarily for the control of septoria tritici blotch (STB) caused by the fungal pathogen Zymoseptoria tritici. Unfortunately, intensive use of the demethylation inhibitors (DMI) and succinate dehydrogenase (SDHI) fungicides has led to the development of resistance in the European Z. tritici population. Levels of disease control achieved by both modes of action are partly dependent on the presence and frequencies of specific alleles, including CYP51-S524T, SDHC-T79N, C-N86S and C-H152R, in the population. To determine how frequent these are across the major wheat producing regions of Europe, a survey of Z. tritici was conducted in 2022, using specific qPCR assays to detect the frequencies of each allele. A west–east gradient of resistant allele frequencies was observed, with higher levels observed in the west. Comparing frequencies detected to a previous survey conducted in 2019 confirms the continued evolution of fungicide resistance in the European Z. tritici population. To ensure the continued effectiveness of these fungicides, it is essential ensure they are applied as part of an integrated disease control strategy that aims to reduce the overall need for their application.

Controlling Listeria monocytogenes and its associated biofilms in the food industry requires various disinfection techniques, including physical, chemical, and biological treatments. Biocides, owing to their ease of use, cost‐effectiveness, dissolvability in water, and efficacy against a wide range of microorganisms, are frequently selected options. Nonetheless, concerns have been raised about their efficacy in controlling L. monocytogenes biofilm, as laboratory‐based and commercial studies have reported the persistence of this bacterium after cleaning and disinfection. This review systematically examined scientific studies, sourced from the Web of Science, Scopus, and PubMed databases between January 2010 and May 2024, that investigated the effectiveness of the most commonly used biocides in the food industry against L. monocytogenes biofilms. A total of 92 articles which met the screening criteria, were included, with studies utilizing biocides containing sodium hypochlorite, quaternary ammonium compounds, and peroxyacetic acid being predominant. Studies indicated that several key factors may potentially influence biocides’ efficacy against L. monocytogenes biofilms. These factors included strain type (persistent, sporadic), serotype, strain origin (clinical, environmental, or food), surface type (biotic or abiotic), surface material (stainless steel, polystyrene, etc.), incubation time (biofilm age) and temperature, presence of organic matter, biocide's active agent, and the co‐culture of L. monocytogenes with other bacteria. The induction of the viable but nonculturable (VBNC) state following disinfection is also a critical concern. This review aims to provide a global understanding of how L. monocytogenes biofilms respond to biocides under different treatment conditions, facilitating the development of effective cleaning and disinfection strategies in the food industry.

Background Farmers around the world are at risk of depression, anxiety, and suicidal ideation yet many avoid seeking help. In Ireland, farmers’ mental health is a national concern, as farmers face barriers of masculine norms around help-seeking. This study aimed to examine the prevalence and relationship between mental health literacy and mental health help-seeking in the Irish farming community. It also aimed to identify if mental health literacy or mental health help-seeking differed depending on gender, age, education, health status and income level. Methods We conducted a cross-sectional assessment of 351 Irish farmers’ mental health literacy and help-seeking using validated psychometric measures: the Mental Help Seeking Intention Scale (MHSIS), the Attitudes Toward Seeking Professional Psychological Help Short Form (ATSPPH-SF), and the Multicomponent Mental Health Literacy Measure (MMHL). Results Irish farmers’ mental health literacy and help-seeking scores were interrelated. Though low, farmers’ scores were comparable to the general population and higher than some European samples. Despite broadly favourable attitudes towards seeking professional mental health help, Irish farmers perceived significant barriers to accessing care and exhibited stoic health attitudes. Farmers with less education and men were particularly at risk. Conclusion Irish farmers’ stoic attitudes may be a response to their perceived lack of services. Interventions providing mental health literacy education and improving access to existing mental health services are particularly important for this population of farmers.

Background Numerous studies have highlighted the impact of bacterial communities on the quality and safety of raw ewe milk-derived cheeses. Despite reported differences in the microbiota among cheese types and even producers, to the best of our knowledge, no study has comprehensively assessed all potential microbial sources and their contributions to any raw ewe milk-derived cheese, which could suppose great potential for benefits from research in this area. Here, using the Protected Designation of Origin Idiazabal cheese as an example, the impact of the environment and practices of artisanal dairies (including herd feed, teat skin, dairy surfaces, and ingredients) on the microbiomes of the associated raw milk, whey, and derived cheeses was examined through shotgun metagenomic sequencing. Results The results revealed diverse microbial ecosystems across sample types, comprising more than 1300 bacterial genera and 3400 species. SourceTracker analysis revealed commercial feed and teat skin as major contributors to the raw milk microbiota (45.6% and 33.5%, respectively), being a source of, for example, Lactococcus and Pantoea, along with rennet contributing to the composition of whey and cheese (17.4% and 41.0%, respectively), including taxa such as Streptococcus, Pseudomonas_E or Lactobacillus_H. Functional analysis linked microbial niches to cheese quality- and safety-related metabolic pathways, with brine and food contact surfaces being most relevant, related to genera like Brevibacterium, Methylobacterium, or Halomonas. With respect to the virulome (virulence-associated gene profile), in addition to whey and cheese, commercial feed and grass were the main reservoirs (related to, e.g., Brevibacillus_B or CAG-196). Similarly, grass, teat skin, or rennet were the main contributors of antimicrobial resistance genes (e.g., Bact-11 or Bacteriodes_B). In terms of cheese aroma and texture, apart from the microbiome of the cheese itself, brine, grass, and food contact surfaces were key reservoirs for hydrolase-encoding genes, originating from, for example, Lactococcus, Lactobacillus, Listeria or Chromohalobacter. Furthermore, over 300 metagenomic assembled genomes (MAGs) were generated, including 60 high-quality MAGs, yielding 28 novel putative species from several genera, e.g., Citricoccus, Corynebacterium, or Dietzia. Conclusion This study emphasizes the role of the artisanal dairy environments in determining cheese microbiota and, consequently, quality and safety. BtzRqvysXYp6yqc11nP1jYVideo Abstract

Fusobacterium nucleatum is a human pathogen associated with intestinal conditions including colorectal cancer. Screening for gut-derived strains that exhibit anti-F. nucleatum activity in vitro revealed Streptococcus salivarius DPC6487 as a strain of interest. Whole-genome sequencing of S. salivarius DPC6487 identified a nisin operon with a novel structural variant designated nisin G. The structural nisin G peptide differs from the prototypical nisin A with respect to seven amino acids (Ile4Tyr, Ala15Val, Gly18Ala, Asn20His, Met21Leu, His27Asn, and His31Ile), including differences that have not previously been associated with a natural nisin variant. The nisin G gene cluster consists of nsgGEFABTCPRK with transposases encoded between the nisin G structural gene (nsgA) and nsgF, notably lacking an equivalent to the nisI immunity determinant. S. salivarius DPC6487 exhibited a narrower spectrum of activity in vitro compared to the nisin A-producing Lactococcus lactis NZ9700. Nisin G-producing S. salivarius DPC6487 demonstrated the ability to control F. nucleatum DSM15643 in an ex vivo model colonic environment while exerting minimal impact on the surrounding microbiota. The production of this bacteriocin by a gut-derived S. salivarius, its narrow-spectrum activity, and its anti-F. nucleatum activity in a model colonic environment indicates that this strain merits further attention with a view to harnessing its probiotic potential. IMPORTANCE Fusobacterium nucleatum is a human pathogen associated with intestinal conditions, including colorectal cancer, making it a potentially important therapeutic target. Bacteriocin-producing probiotic bacteria demonstrate the potential to target disease-associated taxa in situ in the gut. A gut-derived strain Streptococcus salivarius DPC6487 was found to demonstrate anti-F. nucleatum activity, which was attributable to a gene encoding a novel nisin variant designated nisin G. Nisin G-producing S. salivarius DPC6487 demonstrated the ability to control an infection of F. nucleatum in a simulated model of the human distal colon while exerting minimal impact on the surrounding microbiota. Here, we describe this nisin variant produced by S. salivarius, a species that is frequently a focus for probiotic development. The production of nisin G by a gut-derived S. salivarius, its narrow-spectrum activity against F. nucleatum, and its anti-F. nucleatum activity in a model colonic environment warrants further research to determine its probiotic-related applications.

The challenge of meeting nutritional requirements for vitamin D because of low supply in the food system means that substantial proportions of the population have low vitamin D intakes and status ⁽¹⁾ . Naturally rich sources such as oily fish are consumed infrequently and foods such as eggs do not have sufficient quantities to meet Dietary Reference Values. Usually, fortification is voluntary and a premium price can be achieved for the fortified product. Hence, there may be a role for mandatory fortification to ensure equal access to healthy, fortified foods for all. The aim of this study was to profile food product launches to the global market over the last 15 years to determine if product launches can potentially meet Vitamin D requirement. The GlobalData ⁽²⁾ is an industry specific intelligence planform that can be accessed to identify and analyse food product launches based on specific inputs such food-type, country, nutrients, health claim etc. This database was mined to retrieve and analyse all food products launched in the 15year period from January 2009 to March 2024 with at least 0.01ug of vitamin D listed in the nutritional content. The search returned a database with a total of 2,203 products launches. From 2009, there was a steady increase in product launches until it peaked in 2012 with 320 products. Thereafter it decreased with a low in 2016 at 50 product launches. Although not exceeding the high in 2012, there has been a steady increase since 2016 with 150 launches reported for 2023. The top three countries for product launches were USA at 11.8% (n = 261) followed by UK at 7.2% (n = 159) and India at 6.6% (n = 146). The market is dominated by dairy foods with nearly half of all launches this category (47%). This was followed by drinks (15%), bakery and cereals (15%) and baby foods (10%). Countries such as the USA and India have voluntary fortification strategies in place which may explain higher proportion of product launches seen in these countries (3,4) . The implementation of a national vitamin D food fortification strategy may help to increase the launch/supply of fortified foods on the market to increase the potential to achieve recommended intakes. The dominance of vitamin D fortification within a small number of food categories such as dairy ⁽⁵⁾ highlights the opportunities and untapped potential for other food categories such as pasta and sauces to also undertake fortification. It is also important to accommodate the diversity of the diet and provide vitamin D fortified foods for non dairy consumers. Studies have shown that food fortification can increase vitamin D status ⁽⁶⁾ Therefore additional and more diverse food fortification should be considered to improve vitamin D intakes in the population.

This study aimed to investigate the biological activity of crude and purified laminarin and fucoidan samples extracted from Irish brown macroalgae species Laminaria digitata and Fucus vesiculosus. The antioxidant capacity of the samples was evaluated using the 2,2-diphenyl-1-picrylhydrazyl and ferric-reducing antioxidant power assays. The anti-inflammatory potential of the samples was analysed using the cyclooxygenases inhibition activity, and the antidiabetic activity was evaluated using a dipeptidyl peptidase-4 inhibitor screening assay. The cytotoxicity of the samples was measured using the Alamar Blue™ assay with different types of cancer cell lines. The crude laminarin and fucoidan samples exhibited higher antioxidant activity (p < 0.05) than the purified samples and commercial standards. Similarly, the crude extracts showed stronger anti-inflammatory and antidiabetic effects compared to the purified samples. Additionally, the crude laminarin and fucoidan samples showed higher cytotoxic activity. Specifically, as confirmed in the flow cytometry analysis, 3D tumour spheres using different cancer cell lines showed significantly higher resistance to bioactive compounds compared to 2D monolayer cells. The laminarin and fucoidan polysaccharide samples investigated are suitable for potential nutraceutical applications based on the biological activity values observed. Future research is necessary to purify the bioactive compounds investigated and improve their selectivity for targeted therapeutic uses in food and biomedical applications.

BACKGROUND The hemibiotrophic fungus Zymoseptoria tritici causing Septoria tritici blotch (STB), is a devastating foliar pathogen of wheat worldwide. A common group of fungicides used to control STB are the demethylation inhibitors (DMIs). DMI fungicides restrict fungal growth by inhibiting the sterol 14‐α‐demethylase, a protein encoded by CYP51 gene and essential for maintaining fungal cell permeability. However, the adaptation of Z. tritici populations in response to intensive and prolonged DMI usage has resulted in a gradual shift towards reduced sensitivity to this group of fungicides. In this study, 311 isolates were collected pre‐treatment from nine wheat‐growing regions in Europe in 2019. These isolates were analysed by high‐throughput amplicon‐based sequencing of nine housekeeping genes and the CYP51 gene. RESULTS Analyses based on housekeeping genes and the CYP51 gene revealed a lack of population structure in Z. tritici samples irrespective of geographical origin. Minimum spanning network (MSN) analysis showed clustering of multilocus genotypes (MLGs) based on CYP51 haplotypes, indicating an effect of selection due to DMI fungicide use. The majority of the haplotypes identified in this study have been reported previously. The diversity and frequencies of mutations varied across regions. CONCLUSION Using a high‐throughput amplicon‐sequencing approach, we found several mutations in the CYP51 gene combined in different haplotypes that are likely to cause fungicide resistance. These mutations occurred irrespective of genetic background or geographical origin. Overall, these results contribute to the development of effective and sustainable risk monitoring for DMI fungicide resistance. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Fucoidan, a sulphated polysaccharide from brown seaweed composed of several monosaccharides, has been stated to have several bioactive properties such as antioxidant, antiviral, anticancer, antithrombic, anti-inflammatory, and immunomodulatory effects. This paper provides research findings on green extraction methods, structural analysis of fucoidan, and its associated bioactivities. Fucoidans from brown seaweeds, Fucus vesiculosus and Ascophyllum nodosum, were extracted using green solvents such as citric acid (CA) followed by MWCO (molecular weight cut-off) filtration to obtain high-purity polysaccharides. The presence of functional groups typical to fucoidans, namely, fucose, sulfate, and glycosidic bonds, in the extracts were confirmed through the data obtained from FTIR (Fourier-transform infrared spectroscopy), TGA (thermogravimetric analysis), DSC (differential scanning calorimetry), and solid-state CP–MAS (cross-polarization magic angle spinning) analysis. The MWCO analysis identified that the >300 kDa fraction can have better content of fucoidan (FV-CA 79.16%, FV-HCl 63.59%, AN-CA 79.21%, AN-HCl 80.70%) than the conventional extraction process. Furthermore, the >300 kDa fraction showed significantly higher antioxidant activities compared to crude fucoidan extracts. Crude fucoidan extracts showed significant inhibition of cell viability in human lung (A459 lung carcinoma cells) and colorectal adenocarcinoma (Caco-2) cells at higher concentrations. The fucoidan extracted with green solvents and avoiding alcohol-based precipitation has substantial antioxidant/antitumor action, so, due to this activity, it can be employed as functional foods in food applications.

The ability to manipulate brain function through the communication between the microorganisms in the gastrointestinal tract and the brain along the gut-brain axis has emerged as a potential option to improve cognitive and emotional health. Dietary composition and patterns have demonstrated a robust capacity to modulate the microbiota-gut-brain axis. With their potential to possess pre-, pro-, post-, and synbiotic properties, dietary fibre and fermented foods stand out as potent shapers of the gut microbiota and subsequent signalling to the brain. Despite this potential, few studies have directly examined the mechanisms that might explain the beneficial action of dietary fibre and fermented foods on the microbiota-gut-brain axis, thus limiting insight and treatments for brain dysfunction. Herein, we evaluate the differential effects of dietary fibre and fermented foods from whole food sources on cognitive and emotional functioning. Potential mediating effects of dietary fibre and fermented foods on brain health via the microbiota-gut-brain axis are described. Although more multimodal research that combines psychological assessments and biological sampling to compare each food type is needed, the evidence accumulated to date suggests that dietary fibre, fermented foods, and/or their combination within a psychobiotic diet can be a cost-effective and convenient approach to improve cognitive and emotional functioning across the lifespan.

Climate-induced changes in precipitation and river ows are expected to cause changes in river phosphorus loadings. The uncertainty associated with climate-induced changes to water quality is rarely represented in models. Bayesian Belief Networks (BBNs) are probabilistic graphical models incorporating uncertainty in their model parameters, making them ideal frameworks for communicating climate risk. This study presents a set of catchment-speci c BBNs to simulate total reactive phosphorus (P) concentrations in four agricultural catchments under projected climate change. Six climate models (ve models plus the ensemble mean) across two objective functions (NSE vs log NSE), two Representative Concentration Pathways (RCP 4.5 and 8.5), and three time periods (the 2020s, the 2040s, and the 2080s) were used to create discharge scenarios as model inputs. The simulated monthly mean P concentrations show no obvious trends over time or differences between the two RCP scenarios, with the model ensemble essentially replicating the results obtained for the baseline period. However, the P concentration distributions simulated using the outputs from the HadGEM2-ES model rather than the ensemble, showed differences from the baseline in drier months. A sensitivity analysis demonstrated that this difference occurred because the catchment-speci c BBNs were sensitive to changes in the mean total monthly discharge which were captured in the HadGEM2-ES projections but not by the ensemble mean.

Although various studies have examined the relative influence of farm production diversity and market access on household dietary diversity, few studies have empirically investigated their joint interplay in shaping such diversity. This research addresses this gap based on cross-sectional data from 396 smallholder households in rural Tigray in Northern Ethiopia. In the analysis, a graphical interpretation of the relationship between farm production diversity and market access is followed by a deeper investigation using Poisson estimation methods. We use an alternative measure of market access, households’ frequency of food market visits, rigorously tested for stability, and compare it with alternative measures. Our findings reveal that farm production diversity and market access, jointly and independently, have a positive and significant nonlinear influence on rural smallholder household dietary diversity. The right mix between farm production diversity and smallholder households’ frequency of food market visits increases rural household dietary diversity.