Profiling phytochemical and nutritional components of potato

Potatoes (Solanum Tuberosum L.) contain secondary metabolites that may have an impact on human health. The aim of this study was to assess the levels of some of these compounds in a wide range of varieties, including rare, heritage and commercial cultivars. Vitamin C, total carotenoids, phenolics, flavonoids, antioxidant activity and glycoalkaloids were determined, using spectroscopy and chromatography, in the skin and flesh of tubers grown in field trials. Transcript levels of key synthetic enzymes were assessed by qPCR. Accumulation of selected metabolites was higher in the skin than in the flesh of tubers, except ascorbate, which was undetected in the skin. Differences were on average 2.5 to 3-fold for carotenoids, 6-fold for phenolics, 15 to 16-fold for flavonoids, 21-fold for glycoalkaloids and 9 to 10-fold for antioxidant activity. Higher contents of carotenoids were associated with yellow skin or flesh, and higher values of phenolics, flavonoids and antioxidant activity with blue flesh. Variety ‘Burren’ had maxima values of carotenoids in skin and flesh, variety ‘Nicola’ of ascorbate, variety ‘Congo’ of phenolics, flavonoids and antioxidant activity in both tissues, except antioxidant activity in the skin, which was higher in ‘Edzell Blue’. Varieties ‘May Queen’ and ‘International Kidney’ had highest glycoalkaloid content in skin and flesh respectively. The effect of the environment was diverse: year of cultivation was significant for all metabolites, but site of cultivation was not for carotenoids and glycoalkaloids. Levels of expression of phenylalanine ammonia-lyase and chalcone synthase were higher in varieties accumulating high contents of phenolic compounds. However, levels of expression of phytoene synthase and L-galactono-1,4-lactone dehydrogenase were not different between varieties showing contrasting levels of carotenoids and ascorbate respectively. This work will help identify varieties that could be marketed as healthier and the most suitable varieties for extraction of high-value metabolites such as glycoalkaloids.

The impact of whey protein isolate on energy balance regulation

Using C57BL/6J mice fed whey protein isolate (WPI) enriched high fat (HFD) or low-fat diets (LFD), this study tested the hypothesis that WPI directly impacts on adiposity by influencing lipid metabolism. WPI suppressed HFD-induced body fat and increased lean mass at 8 weeks of dietary challenge despite elevated plasma triacylglycerol (TAG) levels, suggesting reduced TAG storage. WPI reduced HFD-associated hypothalamic leptin and insulin receptor (IR) mRNA expression, and prevented HFD-associated reductions in adipose tissue IR and glucose transporter 4 expression. These effects were largely absent at 21 weeks of HFD feeding, however WPI increased lean mass and cause a trend towards decreased fat mass, with notable increased Lactobacillus and decreased Clostridium gut bacterial species. Increasing the protein to carbohydrate ratio enhanced the above effects, and shifted the gut microbiota composition away from the HFD group. Seven weeks of WPI intake with a LFD decreased insulin signalling gene expression in the adipose tissue in association with an increased fat accumulation. WPI reduced intestinal weight and length, suggesting a potential functional relationship between WPI, gastro-intestinal morphology and insulin related signalling in the adipose. Extending the study to 15 weeks, did not affect adipose fat weight, but decreased energy intake, weight gain and intestinal length. The functionality of protein sensing lysophosphatidic acid receptor 5 (LPA5) in 3T3-L1 pre-adipocytes was assessed. Over-expression of the receptor in 3T3-L1 pre-adipocytes provided a growth advantage to the cells and suppressed cellular differentiation into mature fat cells. In conclusion, the data demonstrates WPI impacts on adiposity by influencing lipid metabolism in a temporal manner, resulting possibly due to changes in lean mass, hypothalamic and adipose gene expression, gut microbiota and gastrointestinal morphology. The data also showed LPA5 is a novel candidate in regulating of preadipocyte growth and differentiation, and may mediate dietary protein effects on adipose tissue.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Self-management education for cystic fibrosis

Background: Self-management education may help patients with cystic fibrosis and their families to choose, monitor and adjust treatment requirements for their illness, and also to manage the effects of illness on their lives. Although self-management education interventions have been developed for cystic fibrosis, no previous systematic review of the evidence of effectiveness of these interventions has been conducted. Objectives: To assess the effects of self-management education interventions on improving health outcomes for patients with cystic fibrosis and their caregivers. Search methods: We searched the Cochrane Cystic Fibrosis and Genetic Disorders Group Trials Register (date of the last search: 22 August 2013). We also searched databases through EBSCO (CINAHL; Psychological and Behavioural Sciences Collection; PsychInfo; SocINDEX) and Elsevier (Embase) and handsearched relevant journals and conference proceedings (date of the last searches: 01 February 2014 ). Selection criteria: Randomised controlled trials, quasi-randomised controlled trials or controlled clinical trials comparing different types of self-management education for cystic fibrosis or comparing self-management education with standard care or no intervention. Data collection and analysis: Two authors assessed trial eligibility and risk of bias. Three authors extracted data. Main results: Four trials (involving a total of 269 participants) were included. The participants were children with cystic fibrosis and their parents or caregivers in three trials and adults with cystic fibrosis in one trial. The trials compared four different self-management education interventions versus standard treatment: (1) a training programme for managing cystic fibrosis in general; (2) education specific to aerosol and airway clearance treatments; (3) disease-specific nutrition education; and (4) general and disease-specific nutrition education. Training children to manage cystic fibrosis in general had no statistically significant effects on weight after six to eight weeks, mean difference -7.74 lb (i.e. 3.51 kg) (95% confidence interval -35.18 to 19.70). General and disease-specific nutrition education for adults had no statistically significant effects on: pulmonary function (forced expiratory volume at one second), mean difference -5.00 % (95% confidence interval -18.10 to 8.10) at six months and mean difference -5.50 % (95% confidence interval -18.46 to 7.46) at 12 months; or weight, mean difference - 0.70 kg (95% confidence interval -6.58 to 5.18) at six months and mean difference -0.70 kg (95% confidence interval -6.62 to 5.22) at 12 months; or dietary fat intake scores, mean difference 1.60 (85% confidence interval -2.90 to 6.10) at six months and mean difference 0.20 (95% confidence interval -4.08 to 4.48) at 12 months. There is some limited evidence to suggest that self-management education may improve knowledge in patients with cystic fibrosis but not in parents or caregivers. There is also some limited evidence to suggest that self-management education may result in positively changing a small number of behaviours in both patients and caregivers. Authors' conclusions: The available evidence from this review is of insufficient quantity and quality to draw any firm conclusions about the effects of self-management education for cystic fibrosis. Further trials are needed to investigate the effects of self-management education on a range of clinical and behavioural outcomes in children, adolescents and adults with cystic fibrosis and their caregivers.

Infant milk formula manufacture: process and compositional interactions in high dry matter wet-mixes

Infant milk formula (IMF) is fortified milk with composition based on the nutrient content in human mother's milk, 0 to 6 months postpartum. Extensive medical and clinical research has led to advances in the nutritional quality of infant formula; however, relatively few studies have focused on interactions between nutrients and the manufacturing process. The objective of this research was to investigate the impact of composition and processing parameters on physical behaviour of high dry matter (DM) IMF systems with a view to designing more sustainable manufacturing processes. The study showed that commercial IMF, with similar compositions, manufactured by different processes, had markedly different physical properties in dehydrated or reconstituted state. Commercial products made with hydrolysed protein were more heat stable compared to products made with intact protein, however, emulsion quality was compromised. Heat-induced denaturation of whey proteins resulted in increased viscosity of wet-mixes, an effect that was dependant on both whey concentration and interactions with lactose and caseins. Expanding on fundamental laboratory studies, a novel high velocity steam injection process was developed whereby high DM (60%) wet-mixes with lower denaturation/viscosity compared to conventional processes could be achieved; powders produced using this process were of similar quality to those manufactured conventionally. Hydrolysed proteins were also shown to be an effective way of reducing viscosity in heat-treated high DM wet-mixes. In particular, using a whey protein concentrate whereby β-Lactoglobulin was selectively hydrolysed, i.e., α-Lactalbumin remained intact, reduced viscosity of wet-mixes during processing while still providing good emulsification. The thesis provides new insights into interactions between nutrients and/or processing which influence physical stability of IMF both in concentrated liquid and powdered form. The outcomes of the work have applications in such areas as; increasing the DM content of spray drier feeds in order to save energy, and, controlling final powder quality.

Public evaluations of novel food technologies: a qualitative citizen-scientist deliberative discourse approach

This qualitative research expands understanding of how information about a range of Novel Food Technologies (NFTs) is used and assimilated, and the implications of this on the evolution of attitudes and acceptance. This work enhances theoretical and applied understanding of citizens’ evaluative processes around these technologies. The approach applied involved observations of interactive exchanges between citizens and information providers (i.e. food scientists), during which they discussed a specific technology. This flexible, yet structured, approach revealed how individuals construct meaning around information about specific NFTs. A rich dataset of 42 ‘deliberate discourse’ and 42 postdiscourse transcripts was collected. Data analysis encompassed three stages: an initial descriptive account of the complete dataset based on the top-down bottom-up (TDBU) model of attitude formation, followed by inductive and deductive thematic analysis across the selected technology groups. The hybrid thematic analysis undertaken identified a Conceptual Model, which represents a holistic perspective on the influences and associated features directing ‘sense-making’ and ultimate evaluations around the technology clusters. How individuals make sense of these technologies is shaped by: their beliefs, values and personal characteristics; their perceptions of power and control over the application of the technology; and, the assumed relevance of the technology and its applications within different contexts. These influences form the frame for the creation of sense-making around the technologies. Internal negotiations between these influences are evident and evaluations are based on the relative importance of each influence to the individual, which tend to contribute to attitude ambivalence and instability. The findings indicate the processes of forming and changing attitudes towards these technologies are: complex; dependent on characteristics of the individual, technology, application and product; and, impacted by the nature and forms of information provided. Challenges are faced in engaging with the public about these technologies, as levels of knowledge, understanding and interest vary.

Cost savings from relaxation of operational constraints on a power system with high wind penetration

Wind energy is predominantly a nonsynchronous generation source. Large-scale integration of wind generation with existing electricity systems, therefore, presents challenges in maintaining system frequency stability and local voltage stability. Transmission system operators have implemented system operational constraints (SOCs) in order to maintain stability with high wind generation, but imposition of these constraints results in higher operating costs. A mixed integer programming tool was used to simulate generator dispatch in order to assess the impact of various SOCs on generation costs. Interleaved day-ahead scheduling and real-time dispatch models were developed to allow accurate representation of forced outages and wind forecast errors, and were applied to the proposed Irish power system of 2020 with a wind penetration of 32%. Savings of at least 7.8% in generation costs and reductions in wind curtailment of 50% were identified when the most influential SOCs were relaxed. The results also illustrate the need to relax local SOCs together with the system-wide nonsynchronous penetration limit SOC, as savings from increasing the nonsynchronous limit beyond 70% were restricted without relaxation of local SOCs. The methodology and results allow for quantification of the costs of SOCs, allowing the optimal upgrade path for generation and transmission infrastructure to be determined.

Biomethane production from grass silage: laboratory assessment to maximise yields

On-farm biogas production is typically associated with forage maize as the biomass source. Digesters are designed and operated with the focus of optimising the conditions for this feedstock. Thus, such systems may not be ideally suited to the digestion of grass. Ireland has ca. 3.85 million ha of grassland. Annual excess grass, surplus to livestock requirements, could potentially fuel an anaerobic digestion industry. Biomethane associated with biomass from 1.1 % of grassland in Ireland, could potentially generate over 10 % renewable energy supply in transport. This study aims to identify and optimise technologies for the production of biomethane from grass silage. Mono-digestion of grass silage and co-digestion with slurry, as would occur on Irish farms, is investigated in laboratory trials. Grass silage was shown to have 7 times greater methane potential than dairy slurry on a fresh weight basis (107 m3 t-1 v 16 m3 t-1). However, comprehensive trace element profiles indicated that cobalt, iron and nickel are deficient in mono-digestion of grass silage at a high organic loading rate (OLR) of 4.0 kg VS m-3 d-1. The addition of a slurry co-substrate was beneficial due to its wealth of essential trace elements. To stimulate hydrolysis of high lignocellulose grass silage, particle size reduction (physical) and rumen fluid addition (biological) were investigated. In a continuous trial, digestion of grass silage of <1 cm particle size achieved a specific methane yield of 371 L CH4 kg-1 VS when coupled with rumen fluid addition. The concept of demand driven biogas was also examined in a two-phase digestion system (leaching with UASB). When demand for electricity is low it is recommended to disconnect the UASB from the system and recirculate rumen fluid to increase volatile fatty acid (VFA) and soluble chemical oxygen demand (SCOD) production whilst minimising volatile solids (VS) destruction. At times of high demand for electricity, connection of the UASB increases the destruction of volatiles and associated biogas production. The above experiments are intended to assess a range of biogas production options from grass silage with a specific focus on maximising methane yields and provide a guideline for feasible design and operation of on-farm digesters in Ireland.