Use of essential oils and biocontrol cultures for the improvement of shelf-life of fresh cut products

The demand of minimally processed fruits and vegetables has increased in the last years. However, their intrinsic characteristics may favor the growth of pathogens and spoilage microbiota. The negative effects on human health reported for some traditional chemical sanitizers have justified the search for substitutes to guarantee food safety and quality. In this work we have evaluate the potential of some essential oils and their components to improve the safety and the shelf life of Lamb’s lettuce (Valerianella locusta) and apples (Golden delicious). Moreover, the effects of selected lactic acid bacteria alone or in combination with essential oils or their components, on the shelf-life and safety as well as organoleptic properties of minimally processed products, were evaluated. Since the lack of knowledge of microbial cell targets of essential oils represent one of the most important limit to the use of these molecules at industrial level, another aim of this thesis was the study of the action mechanisms of essential oils and their components. The results obtained showed the beneficial effects of the natural antimicrobials as well as the selected lactic acid bacteria on minimally processed fruit and vegetable safety and shelf-life, without detrimental effects on the quality parameters. The beneficial effects obtained by the use of the selected biocontrol agents were further increased combining them with selected natural antimicrobials. The natural antimicrobial employed induced noticeable modifications of membrane fatty acid profiles and volatile compounds produced by microbial cells during the growth. The modification of the expression in genes involved in fatty acid biosynthesis suggesting that the cytoplasmic membrane of microbial cells is one of the major cellular target of essential oils and their components. The comprehension of microbial stress response mechanisms can contribute to the scaling up of natural antimicrobials and bio-control agents at industrial level.

Quality of Service in Distributed Stream Processing for large scale Smart Pervasive Environments

The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variety of devices and the availability of almost ubiquitous Internet connectivity make it possible to collect an unprecedented amount of real time information about the environment we live in. These data streams, if properly and timely analyzed, can be exploited to build new intelligent and pervasive services that have the potential of improving people's quality of life in a variety of cross concerning domains such as entertainment, health-care, or energy management. The large heterogeneity of application domains, however, calls for a middleware-level infrastructure that can effectively support their different quality requirements. In this thesis we study the challenges related to the provisioning of differentiated quality-of-service (QoS) during the processing of data streams produced in pervasive environments. We analyze the trade-offs between guaranteed quality, cost, and scalability in streams distribution and processing by surveying existing state-of-the-art solutions and identifying and exploring their weaknesses. We propose an original model for QoS-centric distributed stream processing in data centers and we present Quasit, its prototype implementation offering a scalable and extensible platform that can be used by researchers to implement and validate novel QoS-enforcement mechanisms. To support our study, we also explore an original class of weaker quality guarantees that can reduce costs when application semantics do not require strict quality enforcement. We validate the effectiveness of this idea in a practical use-case scenario that investigates partial fault-tolerance policies in stream processing by performing a large experimental study on the prototype of our novel LAAR dynamic replication technique. Our modeling, prototyping, and experimental work demonstrates that, by providing data distribution and processing middleware with application-level knowledge of the different quality requirements associated to different pervasive data flows, it is possible to improve system scalability while reducing costs.