Researches on berry composition in red grape: agronomical, biochemical and molecular approaches

It is well known that the best grape quality can occur only through the achievement of optimal source/sink ratio. Vine balance is in fact a key parameter in controlling berry sugar, acidity and secondary metabolites content (Howell, 2001; Vanden Heuvel et al., 2004). Despite yield reduction and quality improvement are not always strictly related, cluster thinning is considered a technique which could lead to improvement in grape sugar and anthocyanin composition (Dokoozlian and Hirschfelt, 1995; Guidoni et al., 2002). Among several microclimatic variables which may impact grape composition, the effect of cluster light exposure and temperature, which probably act in synergistic and complex way, has been widely explored showing positive even sometimes contradictory results (Spayd et al., 2001; Tarara et al., 2008). Pre-bloom and véraison defoliation are very efficient techniques in inducing cluster microclimatic modification. Furthermore pre-bloom defoliation inducing a lower berry set percentage On these basis the aim of the first experiment of the thesis was to verify in cv Sangiovese the effects on ripening and berry composition of management techniques which may increase source/sink ratio and /or promote light incidence on berries throughout grape ripening. An integrated agronomic, biochemical and microarray approach, aims to understand which mechanisms are involved in berry composition and may be conditioned in the berries during ripening in vines submitted to three treatments. In particular the treatments compared were: a) cluster thinning (increasing in source/sink ratio) b) leaf removal at véraison (increasing cluster light exposure) c) pre-bloom defoliation (increasing source sink ratio and cluster light exposure). Vine response to leaf removal at véraison was further evaluated in the second experiment on three different varieties (Cabernet Sauvignon, Nero d’Avola, Raboso Piave) chosen for their different genetic traits in terms of anthocyanin amount and composition. The integrated agronomic, biochemical and microarray approach, employed in order to understand those mechanisms involved in berry composition of Sangiovese vines submitted to management techniques which may increase source/sink ratio and induce microclimatic changes, bring to interesting results. This research confirmed the main role of source/sink ratio in conditioning sugars metabolism and revealed also that carbohydrates availability is a crucial issue in triggering anthocyanin biosynthesis. More complex is the situation of pre-bloom defoliation, where source/sink and cluster light increase effects are associated to determine final berry composition. It results that the application of pre-bloom defoliation may be risky, as too much dependent on seasonal conditions (rain and temperature) and physiological vine response (leaf area recovery, photosynthetic compensation, laterals regrowth). Early induced stress conditions could bring cluster at véraison in disadvantage to trigger optimal berry ripening processes compared to untreated vines. This conditions could be maintained until harvest, if no previously described physiological recovery occurs. Certainly, light exposure increase linked to defoliation treatments, showed a positive and solid effect on flavonol biosynthesis, as in our conditions temperature was not so different among treatments. Except the last aspects, that could be confirmed also for véraison defoliation, microclimatic changes by themselves seemed not able to induce any modification in berry composition. Further studies are necessary to understand if the peculiar anthocyanic and flavonols composition detected in véraison defoliation could play important role in both color intensity and stability of wines.

Clustering of variables around latent components: an application in consumer science

The present work proposes a method based on CLV (Clustering around Latent Variables) for identifying groups of consumers in L-shape data. This kind of datastructure is very common in consumer studies where a panel of consumers is asked to assess the global liking of a certain number of products and then, preference scores are arranged in a two-way table Y. External information on both products (physicalchemical description or sensory attributes) and consumers (socio-demographic background, purchase behaviours or consumption habits) may be available in a row descriptor matrix X and in a column descriptor matrix Z respectively. The aim of this method is to automatically provide a consumer segmentation where all the three matrices play an active role in the classification, getting homogeneous groups from all points of view: preference, products and consumer characteristics. The proposed clustering method is illustrated on data from preference studies on food products: juices based on berry fruits and traditional cheeses from Trentino. The hedonic ratings given by the consumer panel on the products under study were explained with respect to the product chemical compounds, sensory evaluation and consumer socio-demographic information, purchase behaviour and consumption habits.

Phytoplankton Response to Environmental Variables and Organic Pollutants. Laboratory Cultures and Numerical Simulations Experiments

Herbicides are becoming emergent contaminants in Italian surface, coastal and ground waters, due to their intensive use in agriculture. In marine environments herbicides have adverse effects on non-target organisms, as primary producers, resulting in oxygen depletion and decreased primary productivity. Alterations of species composition in algal communities can also occur due to the different sensitivity among the species. In the present thesis the effects of herbicides, widely used in the Northern Adriatic Sea, on different algal species were studied. The main goal of this work was to study the influence of temperature on algal growth in the presence of the triazinic herbicide terbuthylazine (TBA), and the cellular responses adopted to counteract the toxic effects of the pollutant (Chapter 1 and 2). The development of simulation models to be applied in environmental management are needed to organize and track information in a way that would not be possible otherwise and simulate an ecological prospective. The data collected from laboratory experiments were used to simulate algal responses to the TBA exposure at increasing temperature conditions (Chapter 3). Part of the thesis was conducted in foreign countries. The work presented in Chapter 4 was focused on the effect of high light on growth, toxicity and mixotrophy of the ichtyotoxic species Prymnesium parvum. In addition, a mesocosm experiment was conducted in order to study the synergic effect of the pollutant emamectin benzoate with other anthropogenic stressors, such as oil pollution and induced phytoplankton blooms (Chapter 5).

In defence of modeling simultaneity for a correct approximation of cultural aspects: implications for food consumers studies with latent variables

Dealing with latent constructs (loaded by reflective and congeneric measures) cross-culturally compared means studying how these unobserved variables vary, and/or covary each other, after controlling for possibly disturbing cultural forces. This yields to the so-called ‘measurement invariance’ matter that refers to the extent to which data collected by the same multi-item measurement instrument (i.e., self-reported questionnaire of items underlying common latent constructs) are comparable across different cultural environments. As a matter of fact, it would be unthinkable exploring latent variables heterogeneity (e.g., latent means; latent levels of deviations from the means (i.e., latent variances), latent levels of shared variation from the respective means (i.e., latent covariances), levels of magnitude of structural path coefficients with regard to causal relations among latent variables) across different populations without controlling for cultural bias in the underlying measures. Furthermore, it would be unrealistic to assess this latter correction without using a framework that is able to take into account all these potential cultural biases across populations simultaneously. Since the real world ‘acts’ in a simultaneous way as well. As a consequence, I, as researcher, may want to control for cultural forces hypothesizing they are all acting at the same time throughout groups of comparison and therefore examining if they are inflating or suppressing my new estimations with hierarchical nested constraints on the original estimated parameters. Multi Sample Structural Equation Modeling-based Confirmatory Factor Analysis (MS-SEM-based CFA) still represents a dominant and flexible statistical framework to work out this potential cultural bias in a simultaneous way. With this dissertation I wanted to make an attempt to introduce new viewpoints on measurement invariance handled under covariance-based SEM framework by means of a consumer behavior modeling application on functional food choices.