Fresh Produce Safety and Good Agricultural Practices: Stakeholders' Perception and Consumers' Choice in Thailand

Concerns of Thai consumers on food safety have been recently increasing, especially in urban areas and for fresh produce because food safety scandals, such as chemical residues on fresh produce (e.g., cabbage) still frequently occur. The Thai government tried to meet consumer needs by imposing in the domestic market a stronger regulation aimed at increasing the baseline level of food safety assurance and by introducing a voluntary standard (based on Good Agricultural Practices or GAPs and known as Q-GAP) and the related food safety label (i.e., Q mark). However, since standards and regulations are weakly implemented in the domestic market compared to exported products, there is still a lack of Thai consumers’ confidence in the safety of local food products. In this work the current situation of GAPs adoption in Thai fresh produce production is analysed. Furthermore, it is studied whether Thai consumers place value on food safety labels available on the market, to know whether consumer demand could drive the market of certified safer products. This study contains three essays: 1) a review of the literature, 2) a qualitative study on stakeholders' perception toward GAPs adoption and 3) a quantitative study, aimed at analysing consumers' preferences and willingness-to-pay for food safety labels on fresh produce using a discrete choice experiment. This dissertation contributes to the economics of quality assurance and labelling, specifically addressing GAPs and food safety label in the fresh produce supply chain. Results show that Q-GAP could be effectively used to improve food safety in Thai domestic market, but its credibility should be improved. Stakeholder’s awareness toward food safety issues and the delivery of reliable and sound information are crucial. Thai consumers are willing to pay a premium price for food safety labelled produce over unlabelled ones. Implications for both government and business decision-makers are discussed.

Performance evaluation of low environmental impact asphalt concretes using the mechanistic empirical design method based on laboratory fatigue and permanent deformation models

The "sustainability" concept relates to the prolonging of human economic systems with as little detrimental impact on ecological systems as possible. Construction that exhibits good environmental stewardship and practices that conserve resources in a manner that allow growth and development to be sustained for the long-term without degrading the environment are indispensable in a developed society. Past, current and future advancements in asphalt as an environmentally sustainable paving material are especially important because the quantities of asphalt used annually in Europe as well as in the U.S. are large. The asphalt industry is still developing technological improvements that will reduce the environmental impact without affecting the final mechanical performance. Warm mix asphalt (WMA) is a type of asphalt mix requiring lower production temperatures compared to hot mix asphalt (HMA), while aiming to maintain the desired post construction properties of traditional HMA. Lowering the production temperature reduce the fuel usage and the production of emissions therefore and that improve conditions for workers and supports the sustainable development. Even the crumb-rubber modifier (CRM), with shredded automobile tires and used in the United States since the mid 1980s, has proven to be an environmentally friendly alternative to conventional asphalt pavement. Furthermore, the use of waste tires is not only relevant in an environmental aspect but also for the engineering properties of asphalt [Pennisi E., 1992]. This research project is aimed to demonstrate the dual value of these Asphalt Mixes in regards to the environmental and mechanical performance and to suggest a low environmental impact design procedure. In fact, the use of eco-friendly materials is the first phase towards an eco-compatible design but it cannot be the only step. The eco-compatible approach should be extended also to the design method and material characterization because only with these phases is it possible to exploit the maximum potential properties of the used materials. Appropriate asphalt concrete characterization is essential and vital for realistic performance prediction of asphalt concrete pavements. Volumetric (Mix design) and mechanical (Permanent deformation and Fatigue performance) properties are important factors to consider. Moreover, an advanced and efficient design method is necessary in order to correctly use the material. A design method such as a Mechanistic-Empirical approach, consisting of a structural model capable of predicting the state of stresses and strains within the pavement structure under the different traffic and environmental conditions, was the application of choice. In particular this study focus on the CalME and its Incremental-Recursive (I-R) procedure, based on damage models for fatigue and permanent shear strain related to the surface cracking and to the rutting respectively. It works in increments of time and, using the output from one increment, recursively, as input to the next increment, predicts the pavement conditions in terms of layer moduli, fatigue cracking, rutting and roughness. This software procedure was adopted in order to verify the mechanical properties of the study mixes and the reciprocal relationship between surface layer and pavement structure in terms of fatigue and permanent deformation with defined traffic and environmental conditions. The asphalt mixes studied were used in a pavement structure as surface layer of 60 mm thickness. The performance of the pavement was compared to the performance of the same pavement structure where different kinds of asphalt concrete were used as surface layer. In comparison to a conventional asphalt concrete, three eco-friendly materials, two warm mix asphalt and a rubberized asphalt concrete, were analyzed. The First Two Chapters summarize the necessary steps aimed to satisfy the sustainable pavement design procedure. In Chapter I the problem of asphalt pavement eco-compatible design was introduced. The low environmental impact materials such as the Warm Mix Asphalt and the Rubberized Asphalt Concrete were described in detail. In addition the value of a rational asphalt pavement design method was discussed. Chapter II underlines the importance of a deep laboratory characterization based on appropriate materials selection and performance evaluation. In Chapter III, CalME is introduced trough a specific explanation of the different equipped design approaches and specifically explaining the I-R procedure. In Chapter IV, the experimental program is presented with a explanation of test laboratory devices adopted. The Fatigue and Rutting performances of the study mixes are shown respectively in Chapter V and VI. Through these laboratory test data the CalME I-R models parameters for Master Curve, fatigue damage and permanent shear strain were evaluated. Lastly, in Chapter VII, the results of the asphalt pavement structures simulations with different surface layers were reported. For each pavement structure, the total surface cracking, the total rutting, the fatigue damage and the rutting depth in each bound layer were analyzed.

Combinatorial and Robust Optimisation Models and Algorithms for Railway Applications

This thesis deals with an investigation of combinatorial and robust optimisation models to solve railway problems. Railway applications represent a challenging area for operations research. In fact, most problems in this context can be modelled as combinatorial optimisation problems, in which the number of feasible solutions is finite. Yet, despite the astonishing success in the field of combinatorial optimisation, the current state of algorithmic research faces severe difficulties with highly-complex and data-intensive applications such as those dealing with optimisation issues in large-scale transportation networks. One of the main issues concerns imperfect information. The idea of Robust Optimisation, as a way to represent and handle mathematically systems with not precisely known data, dates back to 1970s. Unfortunately, none of those techniques proved to be successfully applicable in one of the most complex and largest in scale (transportation) settings: that of railway systems. Railway optimisation deals with planning and scheduling problems over several time horizons. Disturbances are inevitable and severely affect the planning process. Here we focus on two compelling aspects of planning: robust planning and online (real-time) planning.

Congenital Nystagmus eye movements analysis and oculomotor system models evaluation

The term Congenital Nystagmus (Early Onset Nystagmus or Infantile Nystagmus Syndrome) refers to a pathology characterised by an involuntary movement of the eyes, which often seriously reduces a subject’s vision. Congenital Nystagmus (CN) is a specific kind of nystagmus within the wider classification of infantile nystagmus, which can be best recognized and classified by means of a combination of clinical investigations and motility analysis; in some cases, eye movement recording and analysis are indispensable for diagnosis. However, interpretation of eye movement recordings still lacks of complete reliability; hence new analysis techniques and precise identification of concise parameters directly related to visual acuity are necessary to further support physicians’ decisions. To this aim, an index computed from eye movement recordings and related to the visual acuity of a subject is proposed in this thesis. This estimator is based on two parameters: the time spent by a subject effectively viewing a target (foveation time - Tf) and the standard deviation of eye position (SDp). Moreover, since previous studies have shown that visual acuity largely depends on SDp, a data collection pilot study was also conducted with the purpose of specifically identifying eventual slow rhythmic component in the eye position and to characterise in more detail the SDp. The results are presented in this thesis. In addition, some oculomotor system models are reviewed and a new approach to those models, i.e. the recovery of periodic orbits of the oculomotor system in patients with CN, is tested on real patients data. In conclusion, the results obtained within this research consent to completely and reliably characterise the slow rhythmic component sometimes present in eye position recordings of CN subjects and to better classify the different kinds of CN waveforms. Those findings can successfully support the clinicians in therapy planning and treatment outcome evaluation.

Vegetables biofortified with iodine: chemical, agronomic and qualitative aspects of raw and fried potatoes

Iodine is an essential microelement for human health because it is a constituent of the thyroid hormones that regulate growth and development of the organism. Iodine Deficiency Disorders (IDDs) are believed to be one of the commonest preventable human health problems in the world today, according to the World Health Organization: that diseases include endemic goiter, cretinism and fetal abnormalities, among others, and they are caused by lack of iodine in the diet, that is the main source of iodine. Since iodine intake from food is not enough respect to human needs, this can be remedied through dietary diversification, mineral supplementation, food fortification, or increasing the concentration and/or bioavailability of mineral elements in the edible portions of crops through agricultural intervention or genetic selection (biofortification). The introduction of iodized salt is a strategy widely used and accepted to eradicate iodine deficiency, because it is an inexpensive source of stable iodine. Since the intake of salt, though iodized, must still be limited according to the risk of cardiovascular disease, so the increase of iodine content in plants for the production of functional foods is representing a field of study of particular interest and a potential market. In Italy potatoes enriched with iodine are produced by a patented procedure of agronomic biofortification for the fresh market since several years, furthermore they are recently accepted and recommended by Italian Thyroid Association, as an alternative source of iodine. Researches performed during the PhD course intended to characterize this innovative vegetables products, focusing the attention on different aspects, such as chemistry, agriculture, and quality of fresh and fried potatoes. For this purpose, lipid fraction of raw material was firstly investigated, in order to assess whether the presence of iodine in plant metabolism can affect fatty acid or sterol biosynthesis, according to the hypothesis that iodine can be bounded to polyunsaturated fatty acids of cell membranes, protecting them from peroxydation; phytosterols of plant sterol are also studied because their importance in reducing serum cholesterol, especially in potato plant sterols are also involved in synthesis of glycoalkaloid, a family of steroidal toxic secondary metabolites present in plants of the Solanaceae family. To achieve this goal chromatographic analytical techniques were employed to identify and quantify fatty acids and sterols profile of common and iodine enriched row potatoes. Another aim of the project was to evaluate the effects of frying on the quality of iodine-enriched and common potatoes. Since iodine-enriched potatoes are nowadays produced only for the fresh market, preliminary trials of cultivation under controlled environment were carried out to verify if potato varieties suitable for processing were able to absorb and accumulate iodine in the tuber. In a successive phase, these varieties were grown in the field, to evaluate their potential productivity and quality at harvest and after storage. The best potato variety to be destined for processing purposes, was finally subjected to repeated frying cycles; the effects of lipid oxidation on the composition and quality of both potatoes and frying oil bath were evaluated by chromatographic and spectrophotometric analytical techniques. Special attention were paid on volatile compounds of fried potatoes.

NMR, Metabonomics and Molecular Profiles: Applications to the Quality Assessment of Foodstuffs

Nuclear Magnetic Resonance (NMR) is a branch of spectroscopy that is based on the fact that many atomic nuclei may be oriented by a strong magnetic field and will absorb radiofrequency radiation at characteristic frequencies. The parameters that can be measured on the resulting spectral lines (line positions, intensities, line widths, multiplicities and transients in time-dependent experi-ments) can be interpreted in terms of molecular structure, conformation, molecular motion and other rate processes. In this way, high resolution (HR) NMR allows performing qualitative and quantitative analysis of samples in solution, in order to determine the structure of molecules in solution and not only. In the past, high-field NMR spectroscopy has mainly concerned with the elucidation of chemical structure in solution, but today is emerging as a powerful exploratory tool for probing biochemical and physical processes. It represents a versatile tool for the analysis of foods. In literature many NMR studies have been reported on different type of food such as wine, olive oil, coffee, fruit juices, milk, meat, egg, starch granules, flour, etc using different NMR techniques. Traditionally, univariate analytical methods have been used to ex-plore spectroscopic data. This method is useful to measure or to se-lect a single descriptive variable from the whole spectrum and , at the end, only this variable is analyzed. This univariate methods ap-proach, applied to HR-NMR data, lead to different problems due especially to the complexity of an NMR spectrum. In fact, the lat-ter is composed of different signals belonging to different mole-cules, but it is also true that the same molecules can be represented by different signals, generally strongly correlated. The univariate methods, in this case, takes in account only one or a few variables, causing a loss of information. Thus, when dealing with complex samples like foodstuff, univariate analysis of spectra data results not enough powerful. Spectra need to be considered in their wholeness and, for analysing them, it must be taken in consideration the whole data matrix: chemometric methods are designed to treat such multivariate data. Multivariate data analysis is used for a number of distinct, differ-ent purposes and the aims can be divided into three main groups: • data description (explorative data structure modelling of any ge-neric n-dimensional data matrix, PCA for example); • regression and prediction (PLS); • classification and prediction of class belongings for new samples (LDA and PLS-DA and ECVA). The aim of this PhD thesis was to verify the possibility of identify-ing and classifying plants or foodstuffs, in different classes, based on the concerted variation in metabolite levels, detected by NMR spectra and using the multivariate data analysis as a tool to inter-pret NMR information. It is important to underline that the results obtained are useful to point out the metabolic consequences of a specific modification on foodstuffs, avoiding the use of a targeted analysis for the different metabolites. The data analysis is performed by applying chemomet-ric multivariate techniques to the NMR dataset of spectra acquired. The research work presented in this thesis is the result of a three years PhD study. This thesis reports the main results obtained from these two main activities: A1) Evaluation of a data pre-processing system in order to mini-mize unwanted sources of variations, due to different instrumental set up, manual spectra processing and to sample preparations arte-facts; A2) Application of multivariate chemiometric models in data analy-sis.

An equilibrium approach to modelling social interaction

The aim of this work is to put forward a statistical mechanics theory of social interaction, generalizing econometric discrete choice models. After showing the formal equivalence linking econometric multinomial logit models to equilibrium statical mechanics, a multi- population generalization of the Curie-Weiss model for ferromagnets is considered as a starting point in developing a model capable of describing sudden shifts in aggregate human behaviour. Existence of the thermodynamic limit for the model is shown by an asymptotic sub-additivity method and factorization of correlation functions is proved almost everywhere. The exact solution for the model is provided in the thermodynamical limit by nding converging upper and lower bounds for the system's pressure, and the solution is used to prove an analytic result regarding the number of possible equilibrium states of a two-population system. The work stresses the importance of linking regimes predicted by the model to real phenomena, and to this end it proposes two possible procedures to estimate the model's parameters starting from micro-level data. These are applied to three case studies based on census type data: though these studies are found to be ultimately inconclusive on an empirical level, considerations are drawn that encourage further refinements of the chosen modelling approach, to be considered in future work.

A bayesian model for mixed responses and skew laten variable to measure HRQoL in children

The aim of the thesi is to formulate a suitable Item Response Theory (IRT) based model to measure HRQoL (as latent variable) using a mixed responses questionnaire and relaxing the hypothesis of normal distributed latent variable. The new model is a combination of two models already presented in literature, that is, a latent trait model for mixed responses and an IRT model for Skew Normal latent variable. It is developed in a Bayesian framework, a Markov chain Monte Carlo procedure is used to generate samples of the posterior distribution of the parameters of interest. The proposed model is test on a questionnaire composed by 5 discrete items and one continuous to measure HRQoL in children, the EQ-5D-Y questionnaire. A large sample of children collected in the schools was used. In comparison with a model for only discrete responses and a model for mixed responses and normal latent variable, the new model has better performances, in term of deviance information criterion (DIC), chain convergences times and precision of the estimates.

A molecular phylogeny of bivalve mollusks: ancient radiations and divergences as revealed by mitochondrial genes

The main scope of my PhD is the reconstruction of the large-scale bivalve phylogeny on the basis of four mitochondrial genes, with samples taken from all major groups of the class. To my knowledge, it is the first attempt of such a breadth in Bivalvia. I decided to focus on both ribosomal and protein coding DNA sequences (two ribosomal encoding genes -12s and 16s -, and two protein coding ones - cytochrome c oxidase I and cytochrome b), since either bibliography and my preliminary results confirmed the importance of combined gene signals in improving evolutionary pathways of the group. Moreover, I wanted to propose a methodological pipeline that proved to be useful to obtain robust results in bivalves phylogeny. Actually, best-performing taxon sampling and alignment strategies were tested, and several data partitioning and molecular evolution models were analyzed, thus demonstrating the importance of molding and implementing non-trivial evolutionary models. In the line of a more rigorous approach to data analysis, I also proposed a new method to assess taxon sampling, by developing Clarke and Warwick statistics: taxon sampling is a major concern in phylogenetic studies, and incomplete, biased, or improper taxon assemblies can lead to misleading results in reconstructing evolutionary trees. Theoretical methods are already available to optimize taxon choice in phylogenetic analyses, but most involve some knowledge about genetic relationships of the group of interest, or even a well-established phylogeny itself; these data are not always available in general phylogenetic applications. The method I proposed measures the "phylogenetic representativeness" of a given sample or set of samples and it is based entirely on the pre-existing available taxonomy of the ingroup, which is commonly known to investigators. Moreover, it also accounts for instability and discordance in taxonomies. A Python-based script suite, called PhyRe, has been developed to implement all analyses.

Genetic Manipulation, Gene Silencing and Biomarker Development in Multiple Experimental Models.

The thesis is set in three different parts, according to the relative experimental models. First, the domestic pig (Sus scrofa) is part of the study on reproductive biotechnologies: the transgenesis technique of Sperm Mediated Gene Transfer is widely studied starting from the quality of the semen, through the study of multiple uptakes of exogenous DNA and lastly used in the production of multi-transgenic blastocysts. Finally we managed to couple the transgenesis pipeline with sperm sorting and therefore produced transgenic embryos of predetermined sex. In the second part of the thesis the attention is on the fruit fly (Drosophila melanogaster) and on its derived cell line: the S2 cells. The in vitro and in vivo models are used to develop and validate an efficient way to knock down the myc gene. First an efficient in vitro protocol is described, than we demonstrate how the decrease in myc transcript remarkably affects the ribosome biogenesis through the study of Polysome gradients, rRNA content and qPCR. In vivo we identified two optimal drivers for the conditional silencing of myc, once the flies are fed with RU486: the first one is throughout the whole body (Tubulin), while the second is a head fat body driver (S32). With these results we present a very efficient model to study the role of myc in multiple aspects of translation. In the third and last part, the focus is on human derived lung fibroblasts (hLF-1), mouse tail fibroblasts and mouse tissues. We developed an efficient assay to quantify the total protein content of the nucleus on a single cell level via fluorescence. We coupled the protocol with classical immunofluorescence so to have at the same time general and particular information, demonstrating that during senescence nuclear proteins increase by 1.8 fold either in human cells, mouse cells and mouse tissues.

Biomolecular studies in Alzheimer’s Disease models: investigations in vitro and in vivo

The Alzheimer’s disease (AD), the most prevalent form of age-related dementia, is a multifactorial and heterogeneous neurodegenerative disease. The molecular mechanisms underlying the pathogenesis of AD are yet largely unknown. However, the etiopathogenesis of AD likely resides in the interaction between genetic and environmental risk factors. Among the different factors that contribute to the pathogenesis of AD, amyloid-beta peptides and the genetic risk factor apoE4 are prominent on the basis of genetic evidence and experimental data. ApoE4 transgenic mice have deficits in spatial learning and memory associated with inflammation and brain atrophy. Evidences suggest that apoE4 is implicated in amyloid-beta accumulation, imbalance of cellular antioxidant system and in apoptotic phenomena. The mechanisms by which apoE4 interacts with other AD risk factors leading to an increased susceptibility to the dementia are still unknown. The aim of this research was to provide new insights into molecular mechanisms of AD neurodegeneration, investigating the effect of amyloid-beta peptides and apoE4 genotype on the modulation of genes and proteins differently involved in cellular processes related to aging and oxidative balance such as PIN1, SIRT1, PSEN1, BDNF, TRX1 and GRX1. In particular, we used human neuroblastoma cells exposed to amyloid-beta or apoE3 and apoE4 proteins at different time-points, and selected brain regions of human apoE3 and apoE4 targeted replacement mice, as in vitro and in vivo models, respectively. All genes and proteins studied in the present investigation are modulated by amyloid-beta and apoE4 in different ways, suggesting their involvement in the neurodegenerative mechanisms underlying the AD. Finally, these proteins might represent novel potential diagnostic and therapeutic targets in AD.

The drivers and implications of environmental innovations: European evidence at different levels of analysis

The present work is a collection of three essays devoted at understanding the determinants and implications of the adoption of environmental innovations EI by firms, by adopting different but strictly related schumpeterian perspectives. Each of the essays is an empirical analysis that investigates one original research question, formulated to properly fill the gaps that emerged in previous literature, as the broad introduction of this thesis outlines. The first Chapter is devoted at understanding the determinants of EI by focusing on the role that knowledge sources external to the boundaries of the firm, such as those coming from business suppliers or customers or even research organizations, play in spurring their adoption. The second Chapter answers the question on what induces climate change technologies, adopting regional and sectoral lens, and explores the relation among green knowledge generation, inducement in climate change and environmental performances. Chapter 3 analyzes the economic implications of the adoption of EI for firms, and proposes to disentangle EI by different typologies of innovations, such as externality reducing innovations and energy and resource efficient innovations. Each Chapter exploits different dataset and heterogeneous econometric models, that allow a better extension of the results and to overcome the limits that the choice of one dataset with respect to its alternatives engenders. The first and third Chapter are based on an empirical investigation on microdata, i.e. firm level data extracted from innovation surveys. The second Chapter is based on the analysis of patent data in green technologies that have been extracted by the PATSTAT and REGPAT database. A general conclusive Chapter will follow the three essays and will outline how each Chapter filled the research gaps that emerged, how its results can be interpreted, which policy implications can be derived and which are the possible future lines of research in the field.