Preharvest factors affecting quality and antioxidant levels on Abate Fétel pears: study of superficial scald with a multivariate statistical approach and neural networks

There are only a few insights concerning the influence that agronomic and management variability may have on superficial scald (SS) in pears. Abate Fétel pears were picked during three seasons (2018, 2019 and 2020) from thirty commercial orchards in the Emilia Romagna region, Italy. Using a multivariate statistical approach, high heterogeneity between farms for SS development after cold storage with regular atmosphere was demonstrated. Indeed, some factors seem to affect SS in all growing seasons: high yields, soil texture, improper irrigation and Nitrogen management, use of plant growth regulators, late harvest, precipitations, Calcium and cow manure, presence of nets, orchard age, training system and rootstock. Afterwards, we explored the spatio/temporal variability of fruit attributes in two pear orchards. Environmental and physiological spatial variables were recorded by a portable RTK GPS. High spatial variability of the SS index was observed. Through a geostatistical approach, some characteristics, including soil electrical conductivity and fruit size, have been shown to be negatively correlated with SS. Moreover, regression tree analyses were applied suggesting the presence of threshold values of antioxidant capacity, total phenolic content, and acidity against SS. High pulp firmness and IAD values before storage, denoting a more immature fruit, appeared to be correlated with low SS. Finally, a convolution neural networks (CNN) was tested to detect SS and the starch pattern index (SPI) in pears for portable device applications. Preliminary statistics showed that the model for SS had low accuracy but good precision, and the CNN for SPI denoted good performances compared to the Ctifl and Laimburg scales. The major conclusion is that Abate Fétel pears can potentially be stored in different cold rooms, according to their origin and quality features, ensuring the best fruit quality for the final consumers. These results might lead to a substantial improvement in the Italian pear industry.

Quality and safety of oils and fats obtained as co-products or by-products of the food chain and destined to animal production

The aim of the first part of this thesis was to evaluate the effect of trans fatty acid- (TFA), contaminant, polycyclic aromatic hydrocarbon (PAH)- and oxidation productenriched diets on the content of TFA and conjugated linoleic acid (CLA) isomers in meat and liver of both poultry and rabbit. The enriched feedings were prepared with preselected fatty co-and by-products that contained low and high levels of TFA (low, palm fatty acid distillate; high, hydrogenated palm fatty acid distillate), environmental contaminants (dioxins and PCBs) (two different fish oils), PAH (olive oil acid oils and pomace olive oil from chemical refining, for low and high levels) and oxidation products (sunflower-olive oil blend before and after frying), so as to obtain single feedings with three enrichment degrees (high, medium and low) of the compound of interest. This experimental set-up is a part of a large, collaborative European project (http://www.ub.edu/feedfat/), where other chemical and health parameters are assessed. Lipids were extracted, methylated with diazomethane, then transmethylated with 2N KOH/methanol and analyzed by GC and silver-ion TLC-GC. TFA and CLA were determined in the fats, the feedings, meat and liver of both poultry and rabbit. In general, the level of TFA and CLA in meat and liver mainly varied according to those originally found in the feeding fats. It must be pointed out, though, that TFA and CLA accumulation was different for the two animal species, as well as for the two types of tissues. The TFA composition of meat and liver changes according to the composition of the oils added to the feeds with some differences between species. Chicken meat with skin shows higher TFA content (2.6–5.4 fold) than rabbit meat, except for the “PAH” trial. Chicken liver shows higher TFA content (1.2–2.1 fold) than rabbit liver, except for the “TRANS” and “PAH” trials. In both chicken and rabbit meats, the TFA content was higher for the “TRANS” trial, followed by the “DIOXIN” trial. Slight differences were found on the “OXIDATION” and “PAH” trends in both types of meats. In both chicken and rabbit livers, the TFA content was higher for the “TRANS” trial, followed by those of the “PAH”, “DIOXIN” and “OXIDATION” trials. This trend, however, was not identical to that of feeds, where the TFA content varied as follows: “TRANS” > “DIOXIN” >“PAH” > “OXIDATION”. In chicken and rabbit meat samples, C18:1 TFA were the most abundant, followed by C18:2 TFA and C18:3 TFA, except for the “DIOXIN” trial where C18:3 TFA > C18:2 TFA. In chicken and rabbit liver samples of the “TRANS” and “OXIDATION” trials, C18:1 TFA were the most abundant, followed by C18:2 TFA and C18:3 TFA, whereas C18:3 TFA > C18:2 in the “DIOXIN” trial. Slight differences were found on the “PAH” trend in livers from both species. The second part of the thesis dealt with the study of lipid oxidation in washed turkey muscle added with different antioxidants. The evaluation on the oxidative stability of muscle foods found that oxidation could be measured by headspace solid phase microestraction (SPME) of hexanal and propanal. To make this method effective, an antioxidant system was added to stored muscle to stop the oxidative processes. An increase in ionic strength of the sample was also implemented to increase the concentration of aldehydes in the headspace. This method was found to be more sensitive than the commonly used thiobarbituric acid reactive substances (TBARs) method. However, after antioxidants were added and oxidation was stopped, the concentration of aldehydes decreased. It was found that the decrease in aldehyde concentration was due to the binding of the aldehydes to muscle proteins, thus decreasing the volatility and making them less detectable.

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.

Study of the components of quality in SO2-free wines obtained by innovative vinification protocols. Evaluation of the pre-fermentative addition of lysozyme and oenological tannins.

The research performed during the PhD candidature was intended to evaluate the quality of white wines, as a function of the reduction in SO2 use during the first steps of the winemaking process. In order to investigate the mechanism and intensity of interactions occurring between lysozyme and the principal macro-components of musts and wines, a series of experiments on model wine solutions were undertaken, focusing attention on the polyphenols, SO2, oenological tannins, pectines, ethanol, and sugar components. In the second part of this research program, a series of conventional sulphite added vinifications were compared to vinifications in which sulphur dioxide was replaced by lysozyme and consequently define potential winemaking protocols suitable for the production of SO2-free wines. To reach the final goal, the technological performance of two selected yeast strains with a low aptitude to produce SO2 during fermentation were also evaluated. The data obtained suggested that the addition of lysozyme and oenological tannins during the alcoholic fermentation could represent a promising alternative to the use of sulphur dioxide and a reliable starting point for the production of SO2-free wines. The different vinification protocols studied influenced the composition of the volatile profile in wines at the end of the alcoholic fermentation, especially with regards to alcohols and ethyl esters also a consequence of the yeast’s response to the presence or absence of sulphites during fermentation, contributing in different ways to the sensory profiles of wines. In fact, the aminoacids analysis showed that lysozyme can affect the consumption of nitrogen as a function of the yeast strain used in fermentation. During the bottle storage, the evolution of volatile compounds is affected by the presence of SO2 and oenological tannins, confirming their positive role in scaveging oxygen and maintaining the amounts of esters over certain levels, avoiding a decline in the wine’s quality. Even though a natural decrease was found on phenolic profiles due to oxidation effects caused by the presence of oxygen dissolved in the medium during the storage period, the presence of SO2 together with tannins contrasted the decay of phenolic content at the end of the fermentation. Tannins also showed a central role in preserving the polyphenolic profile of wines during the storage period, confirming their antioxidant property, acting as reductants. Our study focused on the fundamental chemistry relevant to the oxidative phenolic spoilage of white wines has demonstrated the suitability of glutathione to inhibit the production of yellow xanthylium cation pigments generated from flavanols and glyoxylic acid at the concentration that it typically exists in wine. The ability of glutathione to bind glyoxylic acid rather than acetaldehyde may enable glutathione to be used as a ‘switch’ for glyoxylic acid-induced polymerisation mechanisms, as opposed to the equivalent acetaldehyde polymerisation, in processes such as microoxidation. Further research is required to assess the ability of glutathione to prevent xanthylium cation production during the in-situ production of glyoxylic acid and in the presence of sulphur dioxide.

Food lipids: their effects on quality and oxidative stability of animal tissues and emulsions

Lipolysis and oxidation of lipids in foods are the major biochemical and chemical processes that cause food quality deterioration, leading to the characteristic, unpalatable odour and flavour called rancidity. In addition to unpalatability, rancidity may give rise to toxic levels of certain compounds like aldehydes, hydroperoxides, epoxides and cholesterol oxidation products. In this PhD study chromatographic and spectroscopic techniques were employed to determine the degree of lipid oxidation in different animal products and its relationship with technological parameters like feeding fat sources, packaging, processing and storage conditions. To achieve this goal capillary gas chromatography (CGC) was employed not only to determine the fatty acids profile but also, after solid phase extraction, the amount of sterols (cholesterol and phytosterols) and cholesterol oxidation products (COPs). To determine hydroperoxides, primary products of oxidation and quantify secondary products UV/VIS absorbance spectroscopy was applied. Beef and pork meat in this study were analysed. In actual fact, lipid oxidation is a major deterioration reaction in meat, meat products and results in adverse changes in the colour, flavour, texture of meat and develops different compounds which should be a risk to human health as oxysterols. On beef and pork meat, a study of lipid fraction during storage was carried out to evaluate its shelf-life and some nutritional features life saturated/unsaturated fatty acids ratio and sterols content, in according to the interest that has been growing around functional food in the last years. The last part of this research was focused on the study of lipid oxidation in emulsions. In oil-in-water emulsions antioxidant activity of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) was evaluated. The rates of lipid oxidation of 1.0% stripped soybean oil-in-water emulsions with DOPC were followed by monitoring lipid hydroperoxide and hexanal as indicators of primary and secondary oxidation products and the droplet surface charge or zeta potential (ζ) of the emulsions with varying concentrations of DOPC were tested. This manuscript reports the main results obtained in the three activities briefly summarized as follows: 1. study on effects of feeding composition on the photoxidative stability of lipids from beef meat, evaluated during storage under commercial retail conditions; 2. evaluation of effects of diets and storage conditions on the oxidative stability of pork meat lipids; 3. study on oxidative behavior of DOPC in stripped soybean oil-in-water emulsions stabilized by nonionic surfactant.

Procedures of quality control and data analysis of multi-site ground-based observations for the absolute flux calibration of Gaia

The Gaia space mission is a major project for the European astronomical community. As challenging as it is, the processing and analysis of the huge data-flow incoming from Gaia is the subject of thorough study and preparatory work by the DPAC (Data Processing and Analysis Consortium), in charge of all aspects of the Gaia data reduction. This PhD Thesis was carried out in the framework of the DPAC, within the team based in Bologna. The task of the Bologna team is to define the calibration model and to build a grid of spectro-photometric standard stars (SPSS) suitable for the absolute flux calibration of the Gaia G-band photometry and the BP/RP spectrophotometry. Such a flux calibration can be performed by repeatedly observing each SPSS during the life-time of the Gaia mission and by comparing the observed Gaia spectra to the spectra obtained by our ground-based observations. Due to both the different observing sites involved and the huge amount of frames expected (≃100000), it is essential to maintain the maximum homogeneity in data quality, acquisition and treatment, and a particular care has to be used to test the capabilities of each telescope/instrument combination (through the “instrument familiarization plan”), to devise methods to keep under control, and eventually to correct for, the typical instrumental effects that can affect the high precision required for the Gaia SPSS grid (a few % with respect to Vega). I contributed to the ground-based survey of Gaia SPSS in many respects: with the observations, the instrument familiarization plan, the data reduction and analysis activities (both photometry and spectroscopy), and to the maintenance of the data archives. However, the field I was personally responsible for was photometry and in particular relative photometry for the production of short-term light curves. In this context I defined and tested a semi-automated pipeline which allows for the pre-reduction of imaging SPSS data and the production of aperture photometry catalogues ready to be used for further analysis. A series of semi-automated quality control criteria are included in the pipeline at various levels, from pre-reduction, to aperture photometry, to light curves production and analysis.

Chemical, biochemical and microbiological indicators to assess soil quality in temperate agro-ecosystems

Soil is a critically important component of the earth’s biosphere. Developing agricultural production systems able to conserve soil quality is essential to guarantee the current and future capacity of soil to provide goods and services. This study investigates the potential of microbial and biochemical parameters to be used as early and sensitive soil quality indicators. Their ability to differentiate plots under contrasting fertilization regimes is evaluated based also on their sensitivity to seasonal fluctuations of environmental conditions and on their relationship with soil chemical parameters. Further, the study addresses some of the critical methodological aspects of microplate-based fluorimetric enzyme assays, in order to optimize assay conditions and evaluate their suitability to be used as a toll to asses soil quality. The study was based on a long-term field experiment established in 1966 in the Po valley (Italy). The soil was cropped with maize (Z. mays L.) and winter wheat (T. aestivum L.) and received no organic fertilization, crop residue or manure, in combination with increasing levels of mineral N fertilizer. The soil microbiota responded to manure amendment increasing it biomass and activity and changing its community composition. Crop residue effect was much more limited. Mineral N fertilization stimulated crop residue mineralization, shifted microbial community composition and influenced N and P cycling enzyme activities. Seasonal fluctuations of environmental factors affected the soil microbiota. However microbial and biochemical parameters seasonality did not hamper the identification of fertilization-induced effects. Soil microbial community abundance, function and composition appeared to be strongly related to soil organic matter content and composition, confirming the close link existing between these soil quality indicators. Microplate-based fluorimetric enzyme assays showed potential to be used as fast and throughput toll to asses soil quality, but required proper optimization of the assay conditions for a precise estimation of enzymes maximum potential activity.

Urban air quality: new high-resolution modeling approaches and forecasting tools for citizens

Air pollution is one of the greatest health risks in the world. At the same time, the strong correlation with climate change, as well as with Urban Heat Island and Heat Waves, make more intense the effects of all these phenomena. A good air quality and high levels of thermal comfort are the big goals to be reached in urban areas in coming years. Air quality forecast help decision makers to improve air quality and public health strategies, mitigating the occurrence of acute air pollution episodes. Air quality forecasting approaches combine an ensemble of models to provide forecasts from global to regional air pollution and downscaling for selected countries and regions. The development of models dedicated to urban air quality issues requires a good set of data regarding the urban morphology and building material characteristics. Only few examples of air quality forecast system at urban scale exist in the literature and often they are limited to selected cities. This thesis develops by setting up a methodology for the development of a forecasting tool. The forecasting tool can be adapted to all cities and uses a new parametrization for vegetated areas. The parametrization method, based on aerodynamic parameters, produce the urban spatially varying roughness. At the core of the forecasting tool there is a dispersion model (urban scale) used in forecasting mode, and the meteorological and background concentration forecasts provided by two regional numerical weather forecasting models. The tool produces the 1-day spatial forecast of NO2, PM10, O3 concentration, the air temperature, the air humidity and BLQ-Air index values. The tool is automatized to run every day, the maps produced are displayed on the e-Globus platform, updated every day. The results obtained indicate that the forecasting output were in good agreement with the observed measurements.

Sensory analysis as a tool to improve the quality of aquaculture products

Sensory analysis is a scientific discipline used to evoke, measure, analyse and interpret the responses to products that are perceived by the senses of sight, smell, taste, touch and hearing. This science is used to highlight the strengths and characteristics of a product, such as in the case of research and development products where alternative ingredients, food waste or by-products are used. It can also be used to evaluate the same characteristics over time, to highlight alterations in one of the sensory components at a given time or over time. This doctoral thesis deals with the valorisation, through characterisation, of various aquaculture fish products. In particular, the products covered by this study were analysed, depending on the objective pursued, with different sensory methods using trained judges and in one case consumers. Therefore, the sensory characterisation of the products was useful for investigating the foods considered in this doctoral research. In particular, specific research topics were taken: 1. The study of alternative ingredients, such as the outcomes of different levels of inclusion of insect larvae (Hermetia illucens) meal on the quality of sea bream (Sparus aurata) fillets. 2. The study of consumer expectations and perceptions on the use of insect meal as a feed for aquaculture products. In particular, this study was done after the characterisation by Quantitative Descriptive analysis (QDA) of the products to exclude sensory differences. 3. Development of a non-destructive and cheap device based on dielectric spectroscopy for assessing fish freshness. In particular in this study, the developed device was evaluated in correlation with a sensory method for assessing the freshness of fish product, the Quality Index Method (QIM)