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.

Salinity Effect on Horticultural Crops: Morphological, Physiological, and Biomolecular Elements of Salinity Stress Response

Among abiotic stresses, high salinity stress is the most severe environmental stress. High salinity exerts its negative impact mainly by disrupting the ionic and osmotic equilibrium of the cell. In saline soils, high levels of sodium ions lead to plant growth inhibition and even death. Salt tolerance in plants is a multifarious phenomenon involving a variety of changes at molecular, organelle, cellular, tissue as well as whole plant level. In addition, salt tolerant plants show a range of adaptations not only in morphological or structural features but also in metabolic and physiological processes that enable them to survive under extreme saline environments. The main objectives of my dissertation were understanding the main physiological and biomolecular features of plant responses to salinity in different genotypes of horticultural crops that are belonging to different families Solanaceae (tomato) and Cucurbitaceae (melon) and Brassicaceae (cabbage and radish). Several aspects of crop responses to salinity have been addressed with the final aim of combining elements of functional stress response in plants by using several ways for the assessment of plant stress perception that ranging from destructive measurements (eg. leaf area, relative growth rate, leaf area index, and total plant fresh and dry weight), to physiological determinations (eg. stomatal conductance, leaf gas exchanges, water use efficiency, and leaf water relation), to the determination of metabolite accumulation in plant tissue (eg. Proline and protein) as well as evaluation the role of enzymatic antioxidant capacity assay in scavenging reactive oxygen species that have been generated under salinized condition, and finally assessing the gene induction and up-down regulation upon salinization (eg. SOS pathway).