Céad Mile Fáilte go T-Stór (Welcome to T- Stór)

Update:  The repository was upgraded in July 2025 to a new DSpace version.

T-Stór is Teagasc’s Open Access Repository, maintained by the Teagasc Library Service. Stór is the Gaelic word for Repository or Store or Warehouse, and T-Stór is an online “store” of Teagasc Research outputs and related documents. T-Stór collects preserves and makes freely available scholarly communication, including peer-reviewed articles, working papers and conference papers created by Teagasc researchers. Where material has already been published it is made available subject to the open-access policies of the original publishers. Click here to read more about Teagasc. 

Featured Items

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A comparison of grassland vegetation from three agri-environment conservation measures

O hUallachain, Daire; Finn, John; Keogh, Blathnaid; Fritch, R.; Sheridan, Helen; Teagasc Walsh Fellowship Programme

Semi-natural grassland habitats have declined significantly throughout Europe. To halt the decline, grassland conservation measures have been included in most European agri-environment schemes. This is the first study to compare the botanical composition of grassland habitats managed under the Irish Agri-Environment Options Scheme (AEOS). Sixty fields on drystock pastoral farms in receipt of agri-environment payments for grassland conservation were surveyed, with 20 fields being enrolled in each of the following AEOS options: Traditional Hay Meadow (THM), Species-Rich Grassland (SRG) and Natura 2000 species-rich grassland (Natura). The vegetation quality of sites enrolled in the Natura measure was higher than the quality of those enrolled in the THM and SRG measures. Natura sites had the greatest species richness, with a mean >40 species per site, which included approximately 17 species indicative of high botanical quality. Traditional Hay Meadows sites had the lowest species richness (mean: 29 species per site) and were dominated by species associated with improved grassland. Some THM sites had good levels of botanical richness and were similar in composition to Natura sites, with some Natura sites having lower vegetation quality, more similar to that of THM sites. Species-Rich Grassland had botanical richness that was intermediate between THM and Natura sites. A thorough assessment of the effectiveness of these measures was confounded by a lack of quantitative objectives for the target community composition to be attained. We discuss limitations and potential opportunities regarding the design, targeting, implementation and cost-effectiveness of these agri-environment measures.

2016-12

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Learning from Agricultural Land Market Regulation Policies in EU Member States

Loughrey, Jason; Geoghegan, Cathal; Department of Agriculture, Food and the Marine; 2019R414; 2019R414

This article draws from economic theory and the recent European Commission report on agricultural land market regulation to assess the suitability of selected regulatory policies for agricultural land markets in Ireland. Insights from policy in other EU Member States indicates that some flexibility is always required to permit the existence of temporary land leasing contracts. Farmland rental prices in Ireland have mainly followed the underlying returns to agriculture and been much less influenced by speculative bubbles relative to farmland sales markets. The land rental data for 2019 do not point to the need for maximum price regulation. The availability of reliable statistics is not a sufficient condition to prevent bubbles from emerging, but farmland markets need to be closely monitored with up-to-date official statistics informing potential market participants and public policy.

2024-06-18

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The MAP model: approaching behaviour change conversations on farm

Gribben, Laura; Burrell, Alison; Walsh Scholarship

With the increasing focus on preventative medicine, herd health management and sustainability, farmers are continually being challenged to make changes to their farm routine and farm behaviours (Bord Bia, 2022; Svensson et al., 2022). In this context, the role of the veterinary practitioner becomes ever more critical as an advocate for change. However, to fulfil the potential of this role, it has been recognised that veterinary practitioners could benefit from training in evidence-based communication strategies, specifically designed to support behaviour change (Bard et al. 2019). The behavioural sciences such as health psychology have extensively studied the area of behaviour change, exploring its theoretical underpinnings and developing strategies which can be used to encourage it. This has led to a growing interest in adapting behavioural science-based behaviour change communication strategies to the field of veterinary medicine (Svensson et al. 2020a; 2020b; Bard 2018). One such behaviour change communication strategy which may be applicable is the MAP (Motivation, Action and Prompts) of Behaviour Change model (NHS Education for Scotland (NES), 2022).

2023-02

Recent Submissions

  • ItemOpen Access
    Polyphenols selectively reverse early-life stress-induced behavioural, neurochemical and microbiota changes in the rat
    (Elsevier BV, 2020-6) Donoso, Francisco; Egerton, Sian; Bastiaanssen, Thomaz F.S.; Fitzgerald, Patrick; Gite, Snehal; Fouhy, Fiona; Ross, R. Paul; Stanton, Catherine; Dinan, Timothy G.; Cryan, John F.; Science Foundation Ireland
    There is a growing emphasis on the role of the microbiota-gut-brain axis as modulator of host behaviour and as therapeutic target for neuropsychiatric disorders. In addition, accumulating evidence suggests that early-life stress can exert long-lasting changes on the brain and microbiota, and this early adversity is associated with increased risk for developing depression in later life. The maternal separation (MS) model in rats is a robust paradigm to study the effects of early-life stress on the microbiota-gut-brain axis. Recently, we have shown that polyphenols, naturally occurring compounds associated with several health benefits, have anti-stress effects in in vitro models. In this study, we assess the therapeutic potential of a variety of both flavonoid and non-flavonoid polyphenols in reversing the impact of MS on behaviour and the microbiota-gut-brain axis. Rats underwent a dietary intervention with the naturally-derived polyphenols xanthohumol and quercetin, as well as with a phlorotannin extract for 8 weeks. Treatment with polyphenols prevented the depressive- and anxiety-like behaviours induced by MS, where xanthohumol effects were correlated with rescue of BDNF plasma levels. In addition, MS resulted in altered brain levels of 5-hydroxyindoleacetic acid (5-HIAA) and dopamine, accompanied by abnormal elevation of plasma corticosterone. Although polyphenols did not reverse neurotransmitter imbalance, xanthohumol normalised corticosterone levels in MS rats. Finally, we explored the impact of MS and polyphenolic diets on the gut microbiota. We observed profound changes in microbial composition and diversity produced by MS condition and by xanthohumol treatment. Moreover, functional prediction analysis revealed that MS results in altered enrichment of pathways associated with microbiota-brain interactions that are significantly reversed by xanthohumol treatment. These results suggest that naturally-derived polyphenols exert antidepressant-like effects in MS rats, which mechanisms could be potentially mediated by HPA regulation, BDNF levels rescue and modulation of the microbiota-gut-brain axis.
  • ItemOpen Access
    A bio-economic model for cost analysis of alternative management strategies in beef finishing systems
    (Elsevier BV, 2020-4) Kamilaris, C.; Dewhurst, R.J.; Vosough Ahmadi, B.; Crosson, P.; Alexander, P.; Teagasc Walsh Fellowship
    Global population growth together with rising incomes is increasing the demand for meat-based products. This increases the need to optimize livestock production structures, whilst ensuring viable returns for the farmers. On a global scale, beef producers need tools to assist them to produce more high-quality products whilst maintaining economic efficiency. The Grange Scottish Beef Model (GSBM) was customized to simulate beef finishing enterprises using data from Scottish beef finishing studies, as well as agricultural input and output price datasets. Here we describe the model and its use to determine the cost-effectiveness of alternative current management practices (e.g. forage- and cereal-based finishing) and slaughter ages (i.e. short, medium or long finishing duration). To better understand drivers of profitability in beef finishing systems, several scenarios comparing finishing duration, gender, genetic selection of stock for growth rate or feed efficiency, as well as financial support were tested. There are opportunities for profitable and sustainable beef production in Scotland, for both cereal and forage based systems, particularly when aiming for a younger age profile at slaughtering. By careful choice of finishing systems matched to animal potential, as well as future selection of high performing and feed efficient cattle, beef finishers will be able to enhance performance and increase financial returns.
  • ItemEmbargo
    Advancing microplastics detection and prediction: Integrating traditional methods with machine learning for environmental and food safety application
    (Elsevier BV, 2025-5) Zhang, Chi; Xiao, Liwen; Wang, Jing Jing; Song, Qinghe; Miao, Song; Teagasc
    Background Microplastics (MPs) have emerged as a significant environmental threat, necessitating the development of advanced detection and analysis approaches. Traditional identification techniques are limited by accuracy and processing efficiency constraining, hindering a comprehensive understanding of the prevalence and impact of MPs in both environment and food. Scope and approach Machine learning (ML) and deep learning (DL) models have gained attention in MPs research, offering the potential to enhance MPs detection accuracy and predictive capabilities. This review comprehensively explores the integration of ML and DL models into MPs research, particularly on the applications in detection and prediction. We critically assess the current limitations of ML approaches, such as the challenges of limited datasets that restrict the effectiveness of ML approaches. To address these issues, we highlight the significance of data augmentation and synthetic data generation as crucial strategies for improving model robustness and overcoming the limitations in small and imbalanced datasets. Key findings and conclusions This review highlights the significant potential of combining ML models with detection and prediction methods in MPs research. The incorporation of data augmentation techniques is emphasized as crucial for enhancing model performance. This article also highlights the limitations of current ML approaches for MPs analysis, emphasizing the need for further research on real-world samples and nanoscale MPs. Furthermore, it underscores the promising future applications of these techniques in food safety.
  • PublicationOpen Access
    A genomic analysis of twinning rate and its relationship with other reproductive traits in Holstein-Friesian cattle
    (American Dairy Science Association, 2025-2) Kirkpatrick, Brian W.; Berry, Donagh P.; Science Foundation Ireland; Department of Agriculture, Food and Marine; 16/RC/3835
    Twin births in dairy cattle is generally unfavorably associated with reproductive performance and calf survival in dairy cows. Genetic selection to reduce twinning rate in dairy cattle may be desirable, provided no undesirable correlated responses in other traits exist. The current study was undertaken to characterize the genomic architecture of twinning rate in the Irish Holstein-Friesian population, and to quantify the genetic relationship of twinning with other reproductive traits and milk yield. Calving records from the years 1996 to 2022 were used together with pedigree information to generate breeding value estimates for twinning rate. Genome-wide association analyses of twinning rate, calving interval, cow survival and age at first calving were conducted using de-regressed breeding values estimates for 2,656 Holstein-Friesian sires. Full genome sequence data imputed from ∼50,000 single nucleotide polymorphisms were available for all sires. The h2 of twinning rate was 0.0118 ± 0.0010. Twinning rate was very weakly genetically correlated with both milk yield (0.13) and the reproductive traits (−0.26 to 0.14). Genomic analyses detected an association with twinning rate at 31.1 Mb on BTA11 in close proximity to genes for FSH receptor and luteinizing hormone-chorionic gonadotropin receptor, supporting previous studies. The most significant SNP in this region was not associated with milk yield, indicating the potential for selection to reduce twinning rate without detrimentally affecting milk yield. Novel SNP associations with age at first calving on BTA27 and from a meta-analysis of calving interval and age at first calving on BTA29 were also identified and are candidates for future validation and study.
  • ItemOpen Access
    Invited review: Contribution of milk harvesting research to optimal interaction between biology and milking technology
    (American Dairy Science Association, 2025-11) Upton, J.; Bruckmaier, R.M.; Mein, G.A.; Reinemann, D.J.; Wieland, M.; Paulrud, C.O.; Baines, J.; Ohnstad, I.; Rasmussen, M.D.; Research Ireland; Department of Agriculture, Food and Marine; 21/RC/10303_P2
    The broad focus of this review is on milk harvesting in machine-milked herds. With particular emphasis on: (1) milk secretion and storage dynamics in the udder, (2) milk ejection, (3) milk flow profiles and their effect on milking efficiency, (5) immunological activity and milking efficiency, (5) milking machine aspects of milk removal, and (6) the future potential of milking technology. Machine milking has evolved from its early mechanical beginnings into a technologically advanced, data-driven process that must balance speed, chosen completeness, and gentleness on teat tissue to support efficient milk removal and optimal udder health. This review summarizes the current understanding of milk harvesting from a physiological, mechanical, and managerial perspective and outlines the key factors shaping its future development. Fundamentally, milk harvesting is built upon a biological sequence involving milk synthesis, ejection, and removal. Milk synthesis occurs at the alveolar level and is influenced by local quarter-specific physiology. Milk ejection is driven by the oxytocin-mediated contraction of myoepithelial cells, a process sensitive to the degree of udder filling, familiarity with the milking environment, and cow–operator interactions. Milk flow profiles, shaped by these biological processes, provide crucial insights into milking efficiency and udder health outcomes. At the machine level, key variables include milking vacuum, pulsation characteristics, liner properties, and teatcup removal strategies. Optimal settings for each of these parameters depend on dynamic interactions with cow physiology and milking stage. Recent research highlights the need to consider these factors not in isolation but as part of an integrated milking system, where vacuum, pulsation, liner design, and timing of teatcup removal interact to affect milking speed, teat condition, and udder health. Automation of milking systems and indeed automated milking systems have driven a shift toward individualized milking at the quarter level, enabling more precise control of extraction timing and flow rate. The integration of real-time sensor data, machine learning, and adaptive milking parameters represents a major step forward in the optimization of milking systems. In the near future, distinctions between automated milking systems and conventional systems will become increasingly blurred, as both adopt automation and intelligent controls tailored to individual cows and quarters. This review also explores the role of immunological activity in shaping milking efficiency. Elevated SCC has been associated with altered milk flow curves and decreased productivity. There is emerging evidence suggesting that modern selection and management strategies may reduce the historical link between fast milking and mastitis risk. This relationship remains complex and context dependent. The detection and management of abnormal milk (supported by more advanced inline sensor systems) is expected to become a cornerstone of future milking technology. Looking forward, the drivers of change in milk harvesting will include labor availability, economic pressures, environmental concerns, animal health, and consumer expectations. A new era of biologically aware, data-informed, and precision-engineered milking systems is emerging. These systems will support the gentle, efficient removal of milk to a user-defined end point, tailored to each animal and each milking event.
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