Integrated Approach of Life Cycle Assessment and Experimental Design in the Study of a Model Organic Reaction: New Perspectives in Renewable Vanillin-Derived Chemicals.

This work is focused on performing a quantitative assessment of the environmental impacts associated with an organic synthesis reaction, optimized using an experimental design approach. A nucleophilic substitution reaction was selected, employing vanillin as the substrate, a phenolic compound widely used in the food industry and of pharmaceutical interest, considering its antioxidant and antitumoral potential. To carry out the reaction, three different solvents have been chosen, namely acetonitrile (ACN), acetone (Ace), and dimethylformamide (DMF). The syntheses were planned with the aid of a multivariate experimental design to estimate the best reaction conditions, which simultaneously allow a high product yield and a reduced environmental impact as computed by Life Cycle Assessment (LCA) methodology. The experimental results highlighted that the reactions carried out in DMF resulted in higher yields with respect to ACN and Ace; these reactions were also the ones with lower environmental impacts. The multilinear regression models allowed us to identify the optimal experimental conditions able to guarantee the highest reaction yields and lowest environmental impacts for the studied reaction. The identified optimal experimental conditions were also validated by experimentally conducting the reaction in those conditions, which indeed led to the highest yield (i.e., 93%) and the lowest environmental impacts among the performed experiments. This work proposes, for the first time, an integrated approach of DoE and LCA applied to an organic reaction with the aim of considering both conventional metrics, such as reaction yield, and unconventional ones, such as environmental impacts, during its lab-scale optimization.

An innovative method for the extraction and HPLC analysis of bioactive policosanols from non-psychoactive Cannabis sativa L.

Policosanols (PCs) refer to a mixture of long-chain aliphatic alcohols. Sugar cane is the main industrial source of PCs, but others, including beeswax and Cannabis sativa L., are also known. In the raw material PCs are bonded to fatty acids to form long-chain esters, known as waxes. PCs are mainly used as a cholesterol-lowering product, even though their efficacy is controversial. More recently, the pharmacological interest in PCs has increased, as they have been investigated as antioxidant, anti-inflammatory and anti-proliferative agents. Given their promising biological implications, the development of efficient extraction and analytical methodologies for the determination of PCs is extremely important to identify new potential sources of these compounds and to ensure the reproducibility of biological data. Conventional techniques used for the extraction of PCs involve time-consuming approaches leading to low yields, while analytical methods for their quantification are based on gas-chromatographic (GC) techniques, which require an additional derivatization step during the sample preparation to increase their volatility. In the light of all the above, this work was aimed at the development of an innovative method for the extraction of PCs from non-psychoactive C. sativa (hemp) inflorescences, taking advantage of the microwave-assisted technology. In addition, a new analytical method based on high-performance liquid chromatography (HPLC) coupled with an evaporative light scattering detector (ELSD) was developed for the first time for both the qualitative and quantitative analysis of these compounds in the extracts. The method was validated according to ICH guidelines, and it was applied to the analysis of PCs in hemp inflorescences belonging to different varieties. The results were analyzed using Principal Component Analysis (PCA) and hierarchical clustering analysis to rapidly identify samples with the highest content of PCs, which might find an application as alternative sources of these bioactive compounds in both the pharmaceutical and nutraceutical fields.

Exploring the Effect of Different Storage Conditions on the Aroma Profile of Bread by Using Arrow-SPME GC-MS and Chemometrics.

In the present feasibility study, SPME Arrow-GC-MS method coupled with chemometric techniques, was used for investigating the impact of two different storage conditions, namely freezing and refrigeration, on volatile organic compounds (VOCs) of different commercial breads. The SPME Arrow technology was used as it is a novel extraction technique, able to address issues arising with traditional SPME fibers. Furthermore, the raw chromatographic signals were analysed by means of a PARAFAC2-based deconvolution and identification system (PARADISe approach). The use of PARADISe approach allowed for an efficient and rapid putative identification of 38 volatile organic compounds, including alcohols, esters, carboxylic acids, ketones, and aldehydes. Additionally, Principal Component Analysis, applied on the areas of the resolved compounds, was used to investigate the effects of storage conditions on the aroma profile of bread. The results revealed that the VOC profile of fresh bread is more similar to the one of bread stored in the fridge. Furthermore, there was a clear loss of aroma intensity in frozen samples, which could be explained by phenomena related to different starch retrogradation that occurs during freezing and refrigeration. However, considering the limited number of investigated samples, this study must be considered as a proof of concept; a more statistically representative sampling and further examinations of other properties, such as bread texture, need to be performed to better understand whether samples destined for eventual analysis should be frozen or refrigerated.

A Feasibility Study towards the On-Line Quality Assessment of Pesto Sauce Production by NIR and Chemometrics.

The food industry needs tools to improve the efficiency of their production processes by minimizing waste, detecting timely potential process issues, as well as reducing the efforts and workforce devoted to laboratory analysis while, at the same time, maintaining high-quality standards of products. This can be achieved by developing on-line monitoring systems and models. The present work presents a feasibility study toward establishing the on-line monitoring of a pesto sauce production process by means of NIR spectroscopy and chemometric tools. The spectra of an intermediate product were acquired on-line and continuously by a NIR probe installed directly on the process line. Principal Component Analysis (PCA) was used both to perform an exploratory data analysis and to build Multivariate Statistical Process Control (MSPC) charts. Moreover, Partial Least Squares (PLS) regression was employed to compute real time prediction models for two different pesto quality parameters, namely, consistency and total lipids content. PCA highlighted some differences related to the origin of basil plants, the main pesto ingredient, such as plant age and supplier. MSPC charts were able to detect production stops/restarts. Finally, it was possible to obtain a rough estimation of the quality of some properties in the early production stage through PLS.

VOCs Analysis of Three Different Cultivars of Watermelon (Citrullus lanatus L.) Whole Dietary Fiber.

In this study, the trend of VOCs of dietary fiber samples, coming from three different watermelon cultivars Citrullus lanatus L. (variety Gavina®®, Crimson Sweet, and Asahi Miyako) was investigated. This foodstuff, obtained as a by-product of residual agri-food production, has gained increasing attention because of its many bioactive components and high dietary fiber content. The result is a fibrous material for specific applications in food manufacturing, such as corrector for some functional and technological properties. In this study, a method based on headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) was used to characterize the aromatic profiles of the dried raw materials. Therefore, the VOCs of the samples of the three cultivars were investigated. Experimental results have shown that watermelon fibers generate VOCs, which can be grouped into six common classes of analytes. The different distributions of the identified compounds made it possible to effectively differentiate the three cultivars studied based on their peculiar aroma profiles. In particular, Gavina®® fiber is distinguished by the high content of terpenes, Asahi Miyako by the presence of aldehydes generated as fatty acid metabolites, and Crimson Sweet by the higher content of acetyl esters.

Rapid Classification and Recognition Method of the Species and Chemotypes of Essential Oils by ATR-FTIR Spectroscopy Coupled with Chemometrics.

In the present work, the applicability of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy, coupled with chemometric tools in recognizing essential oils (EOs) for routine control, was evaluated. EOs belonging to Mentha, Cymbopogon, and Lavandula families and to S. rosmarinus and T. vulgaris species were analyzed, and the performance of several untargeted approaches, based on the synergistic combination of ATR-FTIR and Partial Least Squares Discriminant Analysis (PLS-DA), was tested to classify the species and chemotypes. Different spectra pre-processing methods were employed, and the robustness of the built models was tested by means of a Receiver Operating Characteristic (ROC) curve and random permutations test. The application of these approaches revealed fruitful results in terms of sensitivity and specificity, highlighting the potentiality of ATR-FTIR and chemometrics techniques to be used as a sensitive, cost-effective, and rapid tool to differentiate EO samples according to their species and chemotype.

Application of experimental design in HPLC method optimisation for the simultaneous determination of multiple bioactive cannabinoids.

The scientific interest in Cannabis sativa L. analysis has been rapidly increasing in recent years, especially for what concerns cannabinoids, plant secondary metabolites which are well known for having many biological properties. High-performance liquid chromatography (HPLC) is frequently used for both the qualitative and quantitative analysis of cannabinoids in plant extracts from C. sativa and its derived products. Many studies have been focused on the main cannabinoids, such as ∆9-tetrahydrocannabinolic acid (∆9-THCA), cannabidiolic acid (CBDA), cannabigerolic acid (CBGA) and their decarboxylated derivatives, such as ∆9-tetrahydrocannabinol (∆9-THC), cannabidiol (CBD) and cannabigerol (CBG). In addition to the abovementioned compounds, the plant produces other metabolites of the same chemical class, and some of them have shown interesting biological activities. In the light of this, it is important to have efficient analytical methods for the simultaneous separation of cannabinoids, which is quite complex since they present similar chemical-physical characteristics. The present work is focused on the use of the Design of Experiments technique (DoE) to develop and optimise an HPLC method for the simultaneous separation of 14 cannabinoids. Experimental design optimisation was applied by using a Central Composite Face-Centered design to achieve the best resolution with minimum experimental trials. Five significant variables affecting the chromatographic separation, including ammonium formate concentration, gradient elution, run time and flow rate, were studied. A multivariate strategy, based on Principal Component Analysis (PCA) and Partial Least Squared (PLS) regression, was used to define the best operative conditions. The developed method allowed for the separation of 12 out of 14 cannabinoids. Due to co-elution phenomena, HPLC coupled with a triple quadrupole mass analyser (HPLC-ESI-MS/MS) was applied, monitoring the specific transitions of each compound in the multiple reaction monitoring (MRM) mode. Finally, the optimised method was applied to C. sativa extracts having a different cannabinoid profile to demonstrate its efficiency to real samples. The methodology applied in this study can be useful for the separation of other cannabinoid mixtures, by means of appropriate optimisation of the experimental conditions.

Diagnostic Strategies and Algorithms for Investigating Cancer Predisposition Syndromes in Children Presenting with Malignancy.

In the past recent years, the expanding use of next-generation sequencing has led to the discovery of new cancer predisposition syndromes (CPSs), which are now known to be responsible for up to 10% of childhood cancers. As knowledge in the field is in constant evolution, except for a few "classic" CPSs, there is no consensus about when and how to perform germline genetic diagnostic studies in cancer-bearing children. Several clinical screening tools have been proposed to help identify the patients who carry higher risk, with heterogeneous strategies and results. After introducing the main clinical and molecular features of several CPSs predisposing to solid and hematological malignancies, we compare the available clinical evidence on CPS prevalence in pediatric cancer patients and on the most used decision-support tools in identifying the patients who could benefit from genetic counseling and/or direct genetic testing. This analysis highlighted that a personalized stepwise approach employing clinical screening tools followed by sequencing in high-risk patients might be a reasonable and cost-effective strategy in the care of children with cancer.

New Indications for Hematopoietic Stem Cell Gene Therapy in Lysosomal Storage Disorders.

Lysosomal storage disorders (LSDs) are a heterogenous group of disorders due to genetically determined deficits of lysosomal enzymes. The specific molecular mechanism and disease phenotype depends on the type of storage material. Several disorders affect the brain resulting in severe clinical manifestations that substantially impact the expectancy and quality of life. Current treatment modalities for LSDs include enzyme replacement therapy (ERT) and hematopoietic cell transplantation (HCT) from allogeneic healthy donors, but are available for a limited number of disorders and lack efficacy on several clinical manifestations. Hematopoietic stem cell gene therapy (HSC GT) based on integrating lentiviral vectors resulted in robust clinical benefit when administered to patients affected by Metachromatic Leukodystrophy, for whom it is now available as a registered medicinal product. More recently, HSC GT has also shown promising results in Hurler syndrome patients. Here, we discuss possible novel HSC GT indications that are currently under development. If these novel drugs will prove effective, they might represent a new standard of care for these disorders, but several challenges will need to be addresses, including defining and possibly expanding the patient population for whom HSC GT could be efficacious.

Comparative Analysis of VOCs from Winter Melon Pomace Fibers before and after Bleaching Treatment with H2O2.

In this study, the trend of Volatile Organic Compounds (VOCs) in dietary fiber samples from the winter melon (Cucumis Melo var. Inodorus, Yellow Canary type) were investigated. This foodstuff, obtained as a by-product of agri-food production, has gained increasing attention and is characterized by many bioactive components and a high dietary-fiber content. As regards fiber, it is poorly colored, but it may be whitened by applying a bleaching treatment with H2O2. The result is a fibrous material for specific applications in food manufacturing, for example, as a corrector for some functional and technological properties. This treatment is healthy and safe for consumers and widely applied in industrial food processes. In this study, a method based on headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) was applied for the characterization of the aromatic profile of the dried raw materials. Furthermore, VOC variation was investigated as function of the bleaching treatment with H2O2. The bleached samples were also analyzed after a long storage period (24 months), to assess their stability over time. As a result, the VOC fraction of the fresh raw fiber showed nine classes of analytes; these were restricted to seven for the bleached fiber at t0 time, and further reduced to four classes at the age of 24 months. Alcohols were the main group detected in the fresh raw sample (33.8 % of the total chromatogram area), with 2,3-butanediol isomers as the main compounds. These analytes decreased with time. An opposite trend was observed for the acids (9.7% at t0), which increased with time and became the most important class in the 24-month aged and bleached sample (57.3%).

Tracing geographical origin of Lambrusco PDO wines using isotope ratios of oxygen, boron, strontium, lead and their elemental concentration.

Wine identification is one of the most important aspects in the classification of wines and consumer protection. In particular, assuring wine authenticity is a crucial issue on which researchers are focusing on. This study aims to evaluate the feasibility of using chemical (B, Pb and Sr concentration) and isotopic compositions (δ11B, 20yPb/20xPb, 87Sr/86Sr and δ18O) of wine samples to trace their geographic origins. Different PDO Lambrusco wines coming from a confined area of northern Italy were analyzed and all the isotopic systematics were monitored by using a multi collector inductively coupled plasma mass spectrometer (MC-ICP/MS). The obtained results showed that boron isotope ratio measurements led to a satisfactory degree of accuracy and precision (measured value, n = 28, 11B/10B of NIST SRM 951a equal to 4.04343 ± 0.00178, (u = 2s) with a certified value of 4.04362 ± 0.00136 (u = 2s). Furthermore, in the present study, it has been possible to highlight significant differences among samples by means of one-way analysis of variance (ANOVA) and post hoc Tukey-Kramer test. Finally, Principal Component Analysis (PCA) was also carried out in order to evaluate to which extent the different PDOs can be distinguished from each other, taking into account the whole set of geographical origin descriptors. Although δ11B provided more sensitive information, the obtained results highlighted the important to consider the synergistic combination of all the investigated parameters to trace the different samples and the need to combine the obtained values with the same parameters evaluated in the soil, water and fertilizer as well.

Characterization of Basil Volatile Fraction and Study of Its Agronomic Variation by ASCA.

Basil is a plant known worldwide for its culinary and health attributes. It counts more than a hundred and fifty species and many more chemo-types due to its easy cross-breeds. Each species and each chemo-type have a typical aroma pattern and selecting the proper one is crucial for the food industry. Twelve basil varieties have been studied over three years (2018-2020), as have four different cuts. To characterize the aroma profile, nine typical basil flavour molecules have been selected using a gas chromatography-mass spectrometry coupled with an olfactometer (GC-MS/O). The concentrations of the nine selected molecules were measured by an ultra-fast CG e-nose and Principal Component Analysis (PCA) was applied to detect possible differences among the samples. The PCA results highlighted differences between harvesting years, mainly for 2018, whereas no observable clusters were found concerning varieties and cuts, probably due to the combined effects of the investigated factors. For this reason, the ANOVA Simultaneous Component Analysis (ASCA) methodology was applied on a balanced a posteriori designed dataset. All the considered factors and interactions were statistically significant (p < 0.05) in explaining differences between the basil aroma profiles, with more relevant effects of variety and year.

Preliminary Assessment of Parmigiano Reggiano Authenticity by Handheld Raman Spectroscopy.

Raman spectroscopy, and handheld spectrometers in particular, are gaining increasing attention in food quality control as a fast, portable, non-destructive technique. Furthermore, this technology also allows for measuring the intact sample through the packaging and, with respect to near infrared spectroscopy, it is not affected by the water content of the samples. In this work, we evaluate the potential of the methodology to model, by multivariate data analysis, the authenticity of Parmigiano Reggiano cheese, which is one of the most well-known and appreciated hard cheeses worldwide, with protected denomination of origin (PDO). On the other hand, it is also highly subject to counterfeiting. In particular, it is critical to assess the authenticity of grated cheese, to which, under strictly specified conditions, the PDO is extended. To this aim, it would be highly valuable to develop an authenticity model based on a fast, non-destructive technique. In this work, we present preliminary results obtained by a handheld Raman spectrometer and class-modeling (Soft Independent Modeling of Class Analogy, SIMCA), which are extremely promising, showing sensitivity and specificity of 100% for the test set. Moreover, another salient issue, namely the percentage of rind in grated cheese, was addressed by developing a multivariate calibration model based on Raman spectra. It was possible to obtain a prediction error around 5%, with 18% being the maximum content allowed by the production protocol.

Aesthetic compatibility assessment of consolidants for wall paintings by means of multivariate analysis of colorimetric data.

BACKGROUND AND METHODS: Wall paintings and architectural surfaces in outdoor environments are exposed to several physical, chemical and biological agents, hence they are often treated with different products to prevent or slow down their deterioration. Among the factors that have to be taken into account in the selection of the most suitable treatment for decorated surfaces, the aesthetic compatibility with the substrate is of great importance in the cultural heritage field; minimizing colour variation after treatment application is a crucial issue in particular for painted surfaces. In the framework of the European Project Nanomatch the color variation induced on wall painting mock-ups by the two innovative consolidants (calcium alkoxides) developed was evaluated using colorimetry in comparison with two traditional products. In this work these innovative consolidants have been also tested in combination with two commercial biocides and the results of colorimetric measurements discussed. Moreover, as the univariate approach didn't allow to draw clear conclusions on the relation between the different sources of data variability, multivariate analysis was performed on colorimetric data. RESULTS: Principal Component Analysis and multi-way Parallel Factor Analysis (PARAFAC) were successfully applied to colorimetric data to investigate the short-term effects of the application of different consolidants on wall painting surfaces, making it possible to study at the same time the different sources of data variability, i.e. treatments, painting techniques, pigments. Finally, a ranking list of the treatments under study in terms of colour variation induced on the surface was established, in function of the painting technique and pigment, taking also in consideration the combination consolidant/biocide. In particular, given the true multi-way nature of the data, PARAFAC model turned out to be extremely useful in the study of the dependence of colour variation on pigments, a critical issue for painted surfaces, that was not clear using univariate approach. CONCLUSIONS: Multivariate approach to colorimetric data and especially 3-way PARAFAC method resulted a powerful technique to evaluate in short-term the color compatibility of consolidants for wall paintings, improving data interpretation and visualization, and thus outperforming the univariate statistical analysis.

Development of 87Sr/86Sr maps as targeted strategy to support wine quality.

This study summarizes the results obtained from a systematic and long-term project aimed at the development of tools to assess the provenance of food in the oenological sector. In particular, 87Sr/86Sr isotope ratios were measured on statistically representative set of soils, vine branches and wines sampled in the production district of Modena, worldwide known for the Lambrusco wines production. The obtained data were used to build strontium isotopic maps able to objectively support the Lambrusco PDO wines origin as well as other products of the Modena district. Finally, a strong relationship was found between the 87Sr/86Sr isotope ratios of soils and vine branches on a large scale, highlighting and confirming once more the idea that plants can also represent an optimal sampling device to support geographical traceability.

LC-HRMS for Characterizing Durum Wheat Pasta Production Variability and Consumer Overall Liking.

Semolina pasta represents one of the most important dishes in Italian cuisine worldwide. Italy is the leader in its production and, recently, the worldwide diffusion of its production has begun to grow tremendously. The perceived quality of a food product, such as pasta, is a key feature that allows a company to increase and maintain the competitive advantage of a specific brand. The overall flavor perception of the consumer, therefore, has become as important as other key quality factors such as texture and color; thus, the food industry needs to meet consumer expectations and needs the tools to objectively "measure" the quality of food products. Untargeted fingerprinting by means of coupling LC with high-resolution MS (HRMS) has been well received within the analytical community, and different studies exploiting this approach for the characterization of high-value food products have recently been reported in the literature. In the present work, a tentative application of the sensomics approach to cluster analysis of semolina pasta obtained using different production conditions was developed to objectively define target molecules that correlate with consumer overall liking of an industrial standard product. Principal component analysis of chemical and physical testing, GC-MS, LC-HRMS, and sensory data were performed with the aim of identifying the main parameters to discern similarities and differences among samples and clustering them according to these features. The correlation between analytical data and compounds related to sensory data was further investigated, and lastly, a partial least-squares regression model for the prediction of consumer overall liking was reported.

From soil to grape and wine: Variation of light and heavy elements isotope ratios.

In the development of a geographical traceability model, it is necessary to understand if the value of the monitored indicators in a food is correlated to its origin or if it is also influenced by 'external factors' such as those coming from its production. In this study, a deeper investigation of the trend of direct geographical traceability indicators along the winemaking process of two traditional oenological products was carried out. Different processes were monitored, sampling each step of their production (grape juice, intermediate products and wine). The results related to the determinations of δ(18)O, (D/H)I, (D/H)II, δ(13)C, δ(15)N and (87)Sr/(86)Sr have been reported. Furthermore, correspondence with the isotopic values coming from the respective soil and vine-branch samples have been investigated as well, showing the optimal traceability power of the monitored geographical tracers.

An analytical approach to Sr isotope ratio determination in Lambrusco wines for geographical traceability purposes.

Geographical origin and authenticity of food are topics of interest for both consumers and producers. Among the different indicators used for traceability studies, (87)Sr/(86)Sr isotopic ratio has provided excellent results. In this study, two analytical approaches for wine sample pre-treatment, microwave and low temperature mineralisation, were investigated to develop accurate and precise analytical method for (87)Sr/(86)Sr determination. The two procedures led to comparable results (paired t-test, with t

Geographical traceability based on 87Sr/86Sr indicator: a first approach for PDO Lambrusco wines from Modena.

The main goal of this study was to evaluate (87)Sr/(86)Sr ratio in different matrices, namely soils, branches, and grape juices, of an oenological food chain in order to develop a robust analytical strategy able to link the investigated food to its territory of origin. The (87)Sr/(86)Sr has been used as traceability marker and several aspects, affected its variability, i.e. geological features of the investigated area, the bio-available fraction of elements in the soils and the up-take of the plant, have been taken into account. Optimisation of an analytical procedure for the separation of Sr from its interferences and investigation of the analytical performances in terms of precision of used methodology have been carried out as well. This work highlighted a good match between the isotopic values monitored in the bio-available fraction of soils and their respective grape juices for almost all the investigated areas. The correlation with food satisfyingly improves when isotopic relative abundance values of branches vine are considered.

Application of data fusion techniques to direct geographical traceability indicators.

A hierarchical data fusion approach has been developed proposing multivariate curve resolution (MCR) as a variable reduction tool. The case study presented concerns the characterization of soil samples of the Modena District. It was performed in order to understand, at a pilot study stage, the geographical variability of the zone prior to planning a representative soils sampling to derive geographical traceability models for Lambrusco Wines. Soils samples were collected from four producers of Lambrusco Wines, located in in-plane and hill areas. Depending on the extension of the sampled fields the number of points collected varies from three to five and, for each point, five depth levels were considered. The different data blocks consisted of X-ray powder diffraction (XRDP) spectra, metals concentrations relative to thirty-four elements and the (87)Sr/(86)Sr isotopic abundance ratio, a very promising geographical traceability marker. A multi steps data fusion strategy has been adopted. Firstly, the metals concentrations dataset was weighted and concatenated with the values of strontium isotopic ratio and compressed. The resolved components described common patterns of variation of metals content and strontium isotopic ratio. The X-ray powder spectra profiles were resolved in three main components that can be referred to calcite, quartz and clays contributions. Then, a high-level data fusion approach was applied by combining the components arising from the previous data sets. The results show interesting links among the different components arising from XRDP, the metals pattern and to which of these (87)Sr/(86)Sr Isotopic Ratio variation is closer. The combined information allowed capturing the variability of the analyzed soil samples.