Spatial Analysis: Recent submissions
Now showing items 1-20 of 63
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Mitigating Nutrition and Health Deficiencies in Older Adults: A Role for Food Innovation?The aim of this review is to describe the factors contributing to diminished food intake, resulting in nutritional deficiencies and associated health conditions in older adults and proposes food innovation strategies to mitigate these. Research has provided convincing evidence of a link between healthy eating patterns and healthy aging. There is a need to target new food product development (NPD) with functional health benefits specifically designed to address the particular food-related needs of older consumers. When developing foods for older adults, consideration should be given to the increased requirements for specific macro- and micronutrients, especially protein, calcium, vitamin D, and vitamin B. Changes in chemosensory acuity, chewing difficulties, and reduced or poor swallowing ability should also be considered. To compensate for the diminished appetite and reduced intake, foods should be energy dense, nutritionally adequate, and, most importantly, palatable, when targeting this cohort. This paper describes the potential of new food product development to facilitate dietary modification and address health deficiencies in older adults.
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Plasma lutein and zeaxanthin concentrations associated with musculoskeletal health and incident frailty in The Irish Longitudinal Study on Ageing (TILDA)Introduction Lutein and zeaxanthin are diet-derived carotenoids that are proposed to help mitigate frailty risk and age-related declines in musculoskeletal health via their anti-oxidant and anti-inflammatory properties. Therefore, this study aimed to investigate the association between lutein and zeaxanthin status and indices of musculoskeletal health and incident frailty among community-dwelling adults aged ≥50 years in the Irish Longitudinal Study on Ageing (TILDA). Methods Cross-sectional analyses (n = 4513) of plasma lutein and zeaxanthin concentrations and grip strength, usual gait speed, timed up-and-go (TUG), probable sarcopenia (defined as grip strength <27 kg in men, <16 kg in women), and bone mass (assessed using calcaneal broadband ultrasound stiffness index) were performed at Wave 1 (2009–2011; baseline). In the longitudinal analyses (n = 1425–3100), changes in usual gait speed (at Wave 3, 2014–2015), grip strength (Wave 4, 2016) and TUG (at Wave 5, 2018), incident probable sarcopenia (at Wave 4) and incident frailty (Fried's phenotype, Frailty Index, FRAIL Scale, Clinical Frailty Scale-classification tree, at Wave 5) were determined. Data were analysed using linear and ordinal logistic regression, adjusted for confounders. Results Cross-sectionally, plasma lutein and zeaxanthin concentrations were positively associated with usual gait speed (B [95 % CI] per 100-nmol/L higher concentration: Lutein 0.59 [0.18, 1.00], Zeaxanthin 1.46 [0.37, 2.55] cm/s) and inversely associated with TUG time (Lutein −0.07 [−0.11, −0.03], Zeaxanthin −0.14 [−0.25, −0.04] s; all p < 0.01), but not with grip strength or probable sarcopenia (p > 0.05). Plasma lutein concentration was positively associated with bone stiffness index (0.54 [0.15, 0.93], p < 0.01). Longitudinally, among participants who were non-frail at Wave 1, higher plasma lutein and zeaxanthin concentrations were associated lower odds of progressing to a higher frailty category (e.g. prefrailty or frailty) by Wave 5 (ORs 0.57–0.89, p < 0.05) based on the Fried's phenotype, FRAIL Scale and the Clinical Frailty Scale, and in the case of zeaxanthin, Frailty Index. Neither plasma lutein nor zeaxanthin concentrations were associated with changes in musculoskeletal indices or incident probable sarcopenia (p > 0.05). Conclusion Higher plasma lutein and zeaxanthin concentrations at baseline were associated with a reduced likelihood of incident frailty after ~8 years of follow up. Baseline plasma lutein and zeaxanthin concentrations were also positively associated with several indices of musculoskeletal health cross-sectionally but were not predictive of longitudinal changes in these outcomes over 4–8 years.
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Sustainability levels in Irish dairy farming: a farm typology according to sustainable performance indicatorsFeeding the world’s population in a sustainable manner is one of the key challenges facing the future of global agriculture. The recent removal of the milk quota regime in the European Union has prompted an expansionary phase in dairy farming, especially in Ireland. Achieving this expansion in a sustainable manner is crucial to the long-term survival and success of the Irish dairy sector. In this paper we examine the sustainability of Irish dairy farming, defi ning ‘sustainability’ as economically profi table, environmentally friendly and socially effi cient. A typology of Irish dairy farms has been created using data on profi tability, environmental effi ciency and social integration derived from the Teagasc National Farm Survey. Economic, social and environmental performance indicators were determined and aggregated and then used in a multivariate analysis for the identifi cation and classifi cation of farm clusters. The purpose of this study to classify Irish dairy farms using performance indicators, thereby, assisting policy makers in identifying patterns in farm performance with a view to formulating more targeted policies. Two of the three clusters elicited from the analysis were similar in regards to their respective indicator scores. However, the remaining cluster was found to perform poorly in comparison. The results indicate a clear distinction between ‘good’ and ‘weak’ performers, and the positive relationship between the economic, environmental and social performance of Irish dairy farms is evident.
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Satellite remote sensing of grasslands: from observation to managementAims Grasslands are the world’s most extensive terrestrial ecosystem, and are a major feed source for livestock. Meeting increasing demand for meat and other dairy products in a sustainable manner is a big challenge. At a field scale, Global Positioning System and ground-based sensor technologies provide promising tools for grassland and herd management with high precision. With the growth in availability of spaceborne remote sensing data, it is therefore important to revisit the relevant methods and applications that can exploit this imagery. In this article, we have reviewed the (i) current status of grassland monitoring/observation methods and applications based on satellite remote sensing data, (ii) the technological and methodological developments to retrieve different grassland biophysical parameters and management characteristics (i.e. degradation, grazing intensity) and (iii) identified the key remaining challenges and some new upcoming trends for future development. Important Findings The retrieval of grassland biophysical parameters have evolved in recent years from classical regression analysis to more complex, efficient and robust modeling approaches, driven by satellite data, and are likely to continue to be the most robust method for deriving grassland information, however these require more high quality calibration and validation data. We found that the hypertemporal satellite data are widely used for time series generation, and particularly to overcome cloud contamination issues, but the current low spatial resolution of these instruments precludes their use for field-scale application in many countries. This trend may change with the current rise in launch of satellite constellations, such as RapidEye, Sentinel-2 and even the microsatellites such as those operated by Skybox Imaging. Microwave imagery has not been widely used for grassland applications, and a better understanding of the backscatter behaviour from different phenological stages is needed for more reliable products in cloudy regions. The development of hyperspectral satellite instrumentation and analytical methods will help for more detailed discrimination of habitat types, and the development of tools for greater end-user operation.
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Implementation of the EU LEADER programme at member-state level: Written and unwritten rules of local project selection in rural PolandLocal Action Groups (LAGs) are multi-sectoral, area-based partnerships operating throughout the European Union to support participatory local development in rural areas. One of the operational elements of the programme is that multi-sectoral partnerships at the local level select and fund local development projects. The aim of this paper is to explore the dynamics of the selection process at the local level, paying attention to both exogenous and endogenous dynamics that originate at both the EU, national and local levels and how these influence the selection and funding of local development projects. We present the results of qualitative case studies conducted of 15 LAGs in rural Poland. Results indicate that centrally prescribed scoring criteria for the selection of projects issued are used, but, in many cases, local unwritten rules favouring territorial distribution of funds according to number of inhabitants and perceived fairness are highly influential on the selection process. We highlight in this context how local criteria shape top-down rules for the operationalisation of LEADER at the local level, illustrating features of mixed exogenous-endogenous development. We discuss how the interplay of local and external decision-making factors ultimately determine the activities of EU-funded development programmes, highlighting benefits of local decision-making in rural development but also signalling that EU procedures are realised to variable extents.
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Improving a land surface scheme for estimating sensible and latent heat fluxes above grasslands with contrasting soil moisture zonesKnowledge of soil–vegetation–atmosphere energy exchange processes is essential for examining the response of agriculture to changes in climate in both the short and long term. However, there are relatively few sites where all the flux measurements necessary for evaluating these responses are available; where they exist, data are often incomplete and/or of limited duration. At the same time, there is often an extensive observation network available that has gathered key meteorological data (sunshine, wind, rainfall, etc.) over decades. Simulating the terms of the surface energy balance (SEB) using available meteorological, soil and vegetation data can improve our understanding of how agricultural systems respond to climate and how this response will vary spatially. Here, we employ a physically-based scheme to simulate the SEB fluxes over a mid-latitude, maritime temperate environment using routine weather observations. The latent heat flux is a critical SEB term as it incorporates the response of the plant to environmental conditions including available energy and soil water. This response is represented in modeling schemes through surface resistance (rs), which is usually expressed as a function of near-surface water vapor alone. In this study, we simulate the SEB over two grassland sites, where eddy flux observations are available, representing imperfectly- and poorly- drained soils. We employ three different formulations of rs, representing varying degrees of sophistication, to estimate the surface fluxes. Due to differences in soil moisture characteristics between the sites, we ultimately focused our attention on an rs formulation that accounted for soil water retention capacity, based on the Jarvis conductance model; the results at both hourly and daily intervals are in good agreement, with RMSE values of ≈ 40 W m−2 for sensible and latent heat fluxes at both sites. The findings show the potential value of using routine weather observations to generate the SEB where flux observations are not available and the importance of soil properties in estimating surface fluxes. These findings could contribute to the assessment of past and future climate change on grassland ecosystems.
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Upland vegetation mapping using Random Forests with optical and radar satellite dataUplands represent unique landscapes that provide a range of vital benefits to society, but are under increasing pressure from the management needs of a diverse number of stakeholders (e.g. farmers, conservationists, foresters, government agencies and recreational users). Mapping the spatial distribution of upland vegetation could benefit management and conservation programmes and allow for the impacts of environmental change (natural and anthropogenic) in these areas to be reliably estimated. The aim of this study was to evaluate the use of medium spatial resolution optical and radar satellite data, together with ancillary soil and topographic data, for identifying and mapping upland vegetation using the Random Forests (RF) algorithm. Intensive field survey data collected at three study sites in Ireland as part of the National Parks and Wildlife Service (NPWS) funded survey of upland habitats was used in the calibration and validation of different RF models. Eight different datasets were analysed for each site to compare the change in classification accuracy depending on the input variables. The overall accuracy values varied from 59.8% to 94.3% across the three study locations and the inclusion of ancillary datasets containing information on the soil and elevation further improved the classification accuracies (between 5 and 27%, depending on the input classification dataset). The classification results were consistent across the three different study areas, confirming the applicability of the approach under different environmental contexts.
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Introduction: Continuity, Change and the Family FarmThe research presented in this special edition highlights the adaptive capacity of the social system that is the family farm.
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A model framework to investigate the role of anomalous land surface processes in the amplification of summer drought across Ireland during 2018Due to its latitude and ample year-round rainfall, Ireland is typically an energy-limited regime in the context of soil moisture availability and evapotranspiration. However, during the summer of 2018, regions within the country displayed significant soil moisture deficits, associated with anomalous atmospheric forcing conditions, with consequent impacts on the surface energy balance. Here, we explore the utility of a physically based land surface scheme coupled with observational, global gridded reanalysis and satellite-derived data products to analyse the spatial and temporal evolution of the 2018 summer drought event in Ireland over grassland, which represents the dominant agricultural land-cover. While the surface–air energy exchanges were initially dominated by atmospheric anomalies, soil moisture constraints became increasingly important in regulating these exchanges, as the accumulated rainfall deficit increased throughout the summer months. This was particularly evident over the freer draining soils in the east and southeast of the country. From late June 2018, we identify a strong linear coupling between soil moisture and both evapotranspiration and vegetation response, suggesting a shift from an energy-limited evapotranspiration regime into a dry or soil water-limited regime. Applying segmented regression models, the study quantifies a critical soil moisture threshold as a key determinant of the transition from wet to dry evaporative regimes. These findings are important to understand the soil moisture context under which land–atmosphere couplings are strongest in water-limited regimes across the country and should help improve the treatment of soil parameters in weather prediction models, required for subseasonal and seasonal forecasts, consequently enhancing early warning systems of summer climate extremes in the future.
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Food neophobia and its relationship with dietary variety and quality in Irish adults: Findings from a national cross-sectional studyFood neophobia is characterised by a reluctance to eat novel or unfamiliar foods and has been linked to reduced dietary variety and quality. However, this link has been primarily studied in children. Therefore, we aimed to explore the relationship between food neophobia and dietary variety and quality in adults using a sub-sample of the National Adults Nutrition Survey collected between 2008 and 2010 (n = 1088). Food and nutrient intakes were assessed using a 4-day semi-weighed food diary. Food neophobia was measured using the Food Neophobia Scale (FNS). Dietary variety was assessed in three ways; Total Dietary Variety (TDV), Food-Group Variety (FGV) and Fruit and Vegetable Variety (FVV). Diet quality was assessed using the Mean Adequacy Ratio (MAR) and Nutrient-Rich Food Index (NRF9.3). A multivariate general linear model was used to assess the linear relationships between FNS score and all dietary measures, controlling for age, sex, education level, social class, location and BMI. Food neophobia was found to be inversely associated with TDV, FGV and FVV. In addition, food neophobia was negatively associated with vitamin C, magnesium and fruit and vegetable intakes and positively associated with percentage energy from free sugars. However, food neophobia was not significantly associated with all other nutrients, MAR and NRF9.3. While these results suggest food neophobia may not be a particularly important risk factor for poor nutrient status, adherence to certain dietary recommendations remains low within the Irish population and food neophobia may further inhibit the adaption of healthy and sustainable diets. Future research should seek to understand the implications of food neophobia on dietary behaviour change.
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Engaging with selective dry cow therapy: understanding the barriers and facilitators perceived by Irish farmersBackground: Selective dry cow therapy (SDCT) is widely promoted in dairy farming as a method to reduce anti‑ microbial usage. New legislation introduced by the European Union will restrict and regulate the prophylactic and metaphylactic use of antibiotics from January 2022. Blanket dry cow therapy continues to be a practice engaged in by many farmers in Ireland and for many of these farmers, moving towards SDCT would require a signifcant infrastruc‑ tural, behavioural and/or cultural change on their farm. Existing research has reported the important need to under‑ stand farmers’ motivations to initiate any substantial behaviour change. However, it is currently unknown what farm‑ ers know, think and believe about SDCT in Ireland. The aim of this study was to use qualitative methods to explore what barriers and facilitators farmers perceived to exist with SDCT and explore if they had chosen to implement SDCT after voluntarily participating in a funded dry cow consult with a trained veterinarian, with the objective of maximis‑ ing the dry period udder health performance and moving safely to SDCT. Results: In this study, 19 farmers were contacted, and telephone interviews were conducted regarding farmers’ beliefs about the consequences of SDCT. Audio recordings were professionally transcribed verbatim and analysed qualitatively using an inductive thematic analysis. The analysis identifed 6 barriers and 6 facilitators to implement‑ ing SDCT. A signifcant fear of increasing mastitis incidence was evident that caused reluctance towards SDCT and reliance on antibiotics. Mixed perceptions on SDCT, infrastructure limitations, a perceived lack of preventive advice as well as peer infuence were presented as barriers to SDCT. Farmers can build confdence when a graded approach to SDCT is implemented, which could help overcome the fear of SDCT and reliance on antibiotics. Regulatory pressure, high standards of farm hygiene and use of targeted veterinary consults were found to facilitate SDCT. Education was suggested to motivate farmers in the future uptake of SDCT. Despite cited negative infuences, peer infuence can be utilised to encourage the farming community. Conclusions: This study prioritises areas to facilitate the major behaviour change required as a dairy industry in order to move from blanket dry cow therapy to SDCT. Keywords: Selective dry cow therapy, Farmer, Psychology, Behaviour change, CellCheck
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Policy Coherence and the Transition to a Bioeconomy: The Case of IrelandAdvancing a bioeconomy requires that policymakers understand how the design and coherence of public policy can contribute, or create barriers, to its development. Ireland’s first National Policy Statement on the Bioeconomy (February 2018) recognized the significance of policy coherence as a critical factor in a successful transition to a bioeconomy. Qualitative document analysis was employed to assess the level of coherence across a range of relevant policy documents. As is the case with most other countries the key sub-sectors related to the bioeconomy in Ireland have independent policy documents for their own developmental process, with obvious potential for conflict. The results of the analysis indicated inconsistency across sectors, highlighting the requirement to update certain strategy documents in order to raise the level of cross-sectoral coherence. This process is essential in both avoiding a ‘silo’ mentality and enabling the concept of the bioeconomy and its associated objectives to become mainstreamed. The methodology employed in this research is easily transferable and should prove useful for other countries in transition to a bioeconomy to assess the strengths and weaknesses of relevant documents and identify where change is required.
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Co-Operation among Irish Beef Farmers: Current Perspectives and Future Prospects in the Context of New Producer Organisation (PO) LegislationIrish beef farms have experienced poor viability longitudinally, with industry and policy actors citing ‘crisis’ levels in 2013. A crucial differentiator between the beef sector and the dairy sector, which has higher farm incomes, is well-developed infrastructure of farmer-owned dairy processing and marketing co-operatives. To address the lack of representative farmer organisations and power imbalances in the beef supply chain, in 2016 the Department of Agriculture Food and the Marine (DAFM) legislated for the establishment of beef Producer Organisations (POs), facilitating beef producers to collectively strengthen their market positioning. While PO legislation is a significant development in potentially enabling supply chain integration of farmers, how the legislation is operationalised by Irish beef industry stakeholders will ultimately shape the nature and breadth of engagement with the PO model and, consequently, the impact of the legislation. In a context where there is little or no prior experience of such organisations in the beef sector, this paper presents an analysis of current stakeholder views in relation to the establishment of POs. Research involved a desk based review of the submissions made during the consultation period for the beef PO legislation and interviews with key informants in the Irish beef industry. We analysed Irish stakeholders’ views through the lens of lessons learned from the existing literature on how POs operate internationally. Results indicate some stakeholders’ perceptions of the need for a nationally coordinated approach in the establishment of an Association of POs, which concurs with the literature. However, stakeholders have not emphasised the benefits of Interbranch Organisations (IBOs), which involve vertical collaboration with other chain actors such as processors and retailers, an approach that has proven successful internationally. Nor have Irish stakeholders identified the potential of differentiating or premiumising beef products, which, according to international evidence, is necessary for improving profitability and farm-level incomes. Stakeholders identified the main threats to the future success of POs in Ireland as members’ lack of commitment and processors’ lack of willingness to engage with POs.
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Validation of a spatial liver fluke model under field conditions in IrelandFasciola hepatica is the causative agent of fasciolosis, a global disease of a wide range of mammals, particularly sheep and cattle. Liver fluke infection causes annual losses estimated at around €2.5 billion to livestock and food industries worldwide. Various models have been developed to define risk factors and predict exposure to this liver fluke in ruminants in European countries, most of them based exclusively on data from dairy herds. The aim of this study was to validate a published theoretical baseline risk map of liver fluke exposure and cluster maps in Ireland, by including further explanatory variables and additional herd types that are spatially more widespread. Three approaches were employed: i) comparison of predicted and actual exposure; ii) comparison of cluster distribution of hotspots and coldspots; and iii) development of a new model to compare predicted spatial distribution and risk factors. Based on new survey data, the published baseline predictive map was found to have a sensitivity of 94.7%, a specificity of 5%, a positive predictive value of 60% and a negative predictive value of 38.2%. In agreement with the original model, our validation highlighted temperature and rainfall among the main risk factors. In addition, we identified vegetation indices as important risk factors. Both the previously published and our new model predict that exposure to Fasciola is higher in the western parts of Ireland. However, foci of high probability do not match completely, nor do the location of clusters of hotspots and coldspots.
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Scenarios for European agricultural policymaking in the era of digitalisationCONTEXTDigitalisation affects the agri-food sector and its governance. However, what digitalisation of the sector will imply for future agricultural policymaking remains unclear. OBJECTIVEThe objective of the study is to develop and evaluate explorative scenarios of digitalisation in the agri-food sector of Europe that are explicitly relevant to agricultural policy. The study aims to provide guidance for strategic development of agricultural policy to address the potentials, uncertainties and unknowns arising with digitalisation of the sector. METHODSWe combine a Delphi study and a participatory scenario workshop to develop and evaluate plausible explorative scenarios of digitalisation of Europe's agri-food sector. For all scenarios we identify gaps in achieving a range of important European agricultural policy goals, drawing on the Delphi study and desk-based analysis. Subsequently we deduce strategies to address these agricultural policy gaps. RESULTS AND CONCLUSIONSFour scenarios of digitalisation of the agri-food sector were developed for Europe in 2030. They comprise of 1) digitalisation of the sector following current directions at current rates as a baseline scenario, 2) strong digitalisation of a regulatory government, 3) use of autonomous farming technology and 4) digitalised food business. These explorative scenarios entail various gaps in achieving European agricultural policy goals. Our findings suggest that the baseline scenario needs strategies to ramp up technological and institutional infrastructure for digitalisation. The other scenarios need strategies to prevent risks, e.g., of technological failures or undesired social impacts. They also need strategies to cater for special cases and diversity, e.g., of ecosystems and farming practices. Across the scenarios, it seems useful to increase digital competencies of the stakeholders. SIGNIFICANCEThe study is the first that derives implications for policy strategies from explorative scenarios of future digitalisation of agricultural systems that target gaps in achieving agricultural policy goals. The combination of developing and analysing scenarios generated findings that are of significance to policymaking stakeholders and researchers alike, who all need to address the uncertainties arising with future digitalisation of the agri-food sector.
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A Response to the Draft Climate Change Adaptation Sectoral Plan for Agriculture, Forest and Seafood SectorTeagasc is pleased to have the opportunity to contribute to this Draft Climate Change Adaptation Sectoral Plan for Agriculture, Forest and Seafood Sectors, although our contribution will largely be limited to the agriculture and forestry sectors. We have also taken the liberty to contribute in the form of ‘submissions, observations and comments’ as indicated in the call for contributions rather than in the formal questionnaire which appears to be more appropriate for an individual submission rather than an organisational contribution.
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Beyond ruminants: discussing opportunities for alternative pasture uses in New ZealandThe New Zealand government has set ambitious goals for primary sector growth and of zero net carbon emissions by 2050. This presents an opportunity and obligation to develop new ideas for grassland production systems to increase export value and generate new job opportunities, while reducing environmental impacts. The aim of this paper is to draw on recent research in Europe to investigate some of the alternative and complementary uses for pasture as a feedstock for a green biorefinery. A biorefinery is a facility, or a series of processes, that convert biomass into a spectrum of value-added products. For example, protein can be extracted mechanically from green biomass once harvested. The residual fibre fraction could be used as a low-nitrogen feed for ruminants to reduce urinary nitrogen, while the liquid protein fraction could be processed to make it suitable for mono-gastric or human consumption. Enzymes can promote protein extraction and controlled conversion of insoluble plant fibres and oligosaccharides to foster gut-health promoting prebiotic food ingredients. Anaerobic digestion of residues can then be used to create energy and soilimproving products. Research and demonstration of these approaches in practice, along with the results of feasibility studies, will be required to see which of these opportunities is a good fit for New Zealand pasture systems.
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Investigating the Effectiveness of Representations Based on Word-Embeddings in Active Learning for Labelling Text DatasetsManually labelling large collections of text data is a timeconsuming and expensive task, but one that is necessary to support machine learning based on text datasets. Active learning has been shown to be an effective way to alleviate some of the effort required in utilising large collections of unlabelled data for machine learning tasks without needing to fully label them. The representation mechanism used to represent text documents when performing active learning, however, has a significant influence on how effective the process will be. While simple vector representations such as bag-of-words have been shown to be an effective way to represent documents during active learning, the emergence of representation mechanisms based on the word embeddings prevalent in neural network research (e.g. word2vec and transformer based models like BERT) offer a promising, and as yet not fully explored, alternative. This paper describes a large-scale evaluation of the effectiveness of different text representation mechanisms for active learning across 8 datasets from varied domains. This evaluation shows that using representations based on modern word embeddings, especially BERT, which have not yet been widely used in active learning, achieves a significant improvement over more commonly used vector representations like bag-of-words.
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BRIAR: Biomass Retrieval in Ireland Using Active Remote Sensing (2014-CCRP-MS.17)Biomass Retrieval Using Active Remote Sensing Hedgerows are a very significant component of the Irish landscape. They perform multiple functions, acting as boundary markers, acting as stock-proof fencing, supporting bio-diversity and controlling run-off. They function as reservoirs of above-ground biomass and their potential as carbon sinks was explored in an earlier study which found that hedgerows potentially sequester 0.5–2.7tCO2 /ha/year. The earlier study used light detection and ranging (lidar) scanning to build 3D models of hedgerows to successfully estimate biomass, but at the time the cost–benefit of doing so was poor. However, this has since changed with the availability of free lidar sources and the reduced cost of commissioning/ acquiring lidar data. The purpose of the present study was to examine the use of another active remote sensing tool, imaging radar, to estimate biomass in hedgerows. The study area around Fermoy in County Cork was field surveyed using new drone technology to collect data on a sample of hedgerows from which estimates of biomass could be drawn. These field estimates were used with new high-resolution TerraSAR-X Staring Spotlight (TSX-SS) radar imagery to model hedgerows directly from radar backscatter. The study found that hedgerow biomass cannot be derived directly from radar backscatter. There were a number of reasons for this, such as the hedgerow biomass density, with an average of 10kg/m2 , being above the threshold of saturation for radar in the X-band frequency range. However, other radar sensors with lower frequencies, and thus higher saturation limits, do not have the spatial resolution to map hedgerows. An alternative method of investigating hedgerow structure, and thus inferring biomass, interferometry, is not successful as the level of coherence between the observations in our dataset was too low to build a 3D model (i.e. the backscatter from the hedgerow changed too much between observations). A new method that examines the cross-sectional response of the radar return across a hedgerow was shown to be successful at modelling the relationship between the width of the backscatter profile and the width of the hedgerow. However, this too was sensitive to the orientation of the hedgerow to the sensor. Therefore, this study shows that radar data does not seem to be an appropriate technology for estimating hedgerow properties in Ireland. In order to estimate the national stock of hedgerow, the new Prime2 spatial data storage model (OSI, 2014) was applied in conjunction with developed maps showing the probability of a field boundary being a stone wall or a hedgerow, to give a new national estimate for hedgerow length in Ireland of 689,000km. This estimate is double the frequently quoted figure of 300,000km because of a much wider definition of “hedgerow” used in this report. Net change in hedgerow length was examined using the aerial photographic records from 1995, 2005 and 2015, along with county-level survey records, showing that there has been a net removal of hedgerows between 1995 and 2015 of between 0.16% and 0.3% per annum, although the rate is much slower in the latter half of that period. As X-band radar seems to be inappropriate for hedgerow evaluation (especially for the obvious case of the identification of the complete removal of large hedgerows, for which it is much more expensive and time-consuming than the detection of hedgerow removal using aerial photography), the existing national lidar surveys from the Geological Survey of Ireland were examined for their appropriateness for hedgerow evaluation. A digital canopy model derived from these data successfully estimated heights (mean and maximum) in the trial test site, with an r 2 value of 0.79.
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583 Evidence-based social learning for safety and health promotion among irish dairy farmersIntroduction Farming is an occupation that incurs high rates of occupational injuries and illness, including fatalities. Internationally, legislative approaches to improve agricultural occupational safety and health (OSH) practices have been inconsistent in achieving those objectives. Many alternative initiatives to influence agricultural OSH practices have been developed, frequently emphasising information provision. In Ireland, evaluation of information provision approaches, such as classroom-based learning, has found that this is ineffective for improving agricultural OSH practices. However, peer-based learning using communities of practice (COPs), such as Teagasc dairy farmer discussion groups, presents a promising context for agricultural OSH promotion in Ireland. Research has established the efficacy of farmer discussion groups for promoting adoption of novel technologies and production practices. Little research has been undertaken to assess whether they are effective for promoting agricultural OSH practices. This paper describes the extent to which Teagasc dairy discussion groups engage with agricultural OSH, and identifies the characteristics associated with agricultural OSH engagement. The results are evaluated with respect to the existing literature regarding effective social learning for farming and OSH promotion, to assess the suitability of these COPs for agricultural OSH promotion. Methods Information about discussion group characteristics and engagement with OSH topics was collected using a survey of Teagasc dairy discussion group members, and a survey of Teagasc dairy discussion group facilitators. The statistical software R was used to assess variation in discussion group engagement with OSH, and the group characteristics statistically associated with that variation. Result Analysis of the results is ongoing and will be completed in September 2017. Discussion The findings of this study, including the evaluation framework developed from literature review, can contribute to effective agricultural OSH promotion in Ireland, and internationally. This is especially true for other countries with existing farmer COPs, such as farmer discussion groups in New Zealand and Wales.