Cereal products for specific dietary requirements. Evaluation and improvement of technological and nutritional properties of gluten free raw materials and end products

Coeliac disease is one of the most common food intolerances worldwide and at present the gluten free diet remains the only suitable treatment. A market overview conducted as part of this thesis on nutritional and sensory quality of commercially available gluten free breads and pasta showed that improvements are necessary. Many products show strong off-flavors, poor mouthfeel and reduced shelf-life. Since the life-long avoidance of the cereal protein gluten means a major change to the diet, it is important to also consider the nutritional value of products intending to replace staple foods such as bread or pasta. This thesis addresses this issue by characterising available gluten free cereal and pseudocereal flours to facilitate a better raw material choice. It was observed that especially quinoa, buckwheat and teff are high in essential nutrients, such as protein, minerals and folate. In addition the potential of functional ingredients such as inulin, β-glucan, HPMC and xanthan to improve loaf quality were evaluated. Results show that these ingredients can increase loaf volume and reduce crumb hardness as well as rate of staling but that the effect diverges strongly depending on the bread formulation used. Furthermore, fresh egg pasta formulations based on teff and oat flour were developed. The resulting products were characterised regarding sensory and textural properties as well as in vitro digestibility. Scanning electron and confocal laser scanning microscopy was used throughout the thesis to visualise structural changes occurring during baking and pasta making

Designing tools that enhance communication and understanding between multiple stakeholders: the case of mobile payment value networks

The pervasive use of mobile technologies has provided new opportunities for organisations to achieve competitive advantage by using a value network of partners to create value for multiple users. The delivery of a mobile payment (m-payment) system is an example of a value network as it requires the collaboration of multiple partners from diverse industries, each bringing their own expertise, motivations and expectations. Consequently, managing partnerships has been identified as a core competence required by organisations to form viable partnerships in an m-payment value network and an important factor in determining the sustainability of an m-payment business model. However, there is evidence that organisations lack this competence which has been witnessed in the m-payment domain where it has been attributed as an influencing factor in a number of failed m-payment initiatives since 2000. In response to this organisational deficiency, this research project leverages the use of design thinking and visualisation tools to enhance communication and understanding between managers who are responsible for managing partnerships within the m-payment domain. By adopting a design science research approach, which is a problem solving paradigm, the research builds and evaluates a visualisation tool in the form of a Partnership Management Canvas. In doing so, this study demonstrates that when organisations encourage their managers to adopt design thinking, as a way to balance their analytical thinking and intuitive thinking, communication and understanding between the partners increases. This can lead to a shared understanding and a shared commitment between the partners. In addition, the research identifies a number of key business model design issues that need to be considered by researchers and practitioners when designing an m-payment business model. As an applied research project, the study makes valuable contributions to the knowledge base and to the practice of management.

Quantifying the value of improved wind energy forecasts in a pool-based electricity market

This work illustrates the influence of wind forecast errors on system costs, wind curtailment and generator dispatch in a system with high wind penetration. Realistic wind forecasts of different specified accuracy levels are created using an auto-regressive moving average model and these are then used in the creation of day-ahead unit commitment schedules. The schedules are generated for a model of the 2020 Irish electricity system with 33% wind penetration using both stochastic and deterministic approaches. Improvements in wind forecast accuracy are demonstrated to deliver: (i) clear savings in total system costs for deterministic and, to a lesser extent, stochastic scheduling; (ii) a decrease in the level of wind curtailment, with close agreement between stochastic and deterministic scheduling; and (iii) a decrease in the dispatch of open cycle gas turbine generation, evident with deterministic, and to a lesser extent, with stochastic scheduling.