25 research outputs found
Exploring the Effect of Different Storage Conditions on the Aroma Profile of Bread by Using Arrow-SPME GC-MS and Chemometrics
No full textIn 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
Optimization of an analytical method based on SPME-Arrow and chemometrics for the characterization of the aroma profile of commercial bread
No full textA SPME-Arrow GC-MS approach, coupled with chemometrics, was used to thoroughly investigate the impact of different types of yeast (sourdough, bear's yeast and a mixture of both) and their respective leaving time (one, three and five hours) on VOCs of commercial bread samples. This aspect is of paramount importance for the baking industry to adjust recipe modifications and production parameters, as well as to meet consumer needs in formulating new products.
A deep learning approach, PARADISe (PARAFAC2-based deconvolution and identification system), was used to analyse the obtained chromatograms in an untargeted manner. In particular, PARADISe, was able to perform a fast deconvolution of the chromatographic peaks directly from raw chromatographic data to allow a putatively identification of 66 volatile organic compounds, including alcohols, esters, carboxylic acids, ketones, aldehydes. Finally, Principal Component Analysis, applied on the areas of the resolved compounds, showed that bread samples differentiate according to their recipe and highlighted the most relevant volatile compounds responsible for the observed differences
Near Infrared and UV-Visible Spectroscopy Coupled with Chemometrics for the Characterization of Flours from Different Starch Origins
No full textThis work tested near-infrared (NIR) and UV-visible (UV-Vis) spectroscopy coupled with chemometrics to characterize flours from different starch origins. In particular, eighteen starch-containing flours (e.g., type 00 flour, rye, barley, soybean, chestnut, potato, spelt, buckwheat, oat, millet, rice, durum wheat, amaranth, chickpea, sesame, corn, hemp and sunflower flours) were analyzed with a twofold objective: chemically characterizing the investigated flours and laying the groundwork for the development of a fast and suitable method that can identify the botanical source of starch in food. This could ensure ingredient traceability and aid in preventing/detecting food fraud. Untargeted approaches were used for this study, involving the simultaneous acquisition of a large amount of chemical information (UV-Vis on extracted starch and NIR signals on raw flours) coupled with chemometric techniques. UV-VIS spectra were acquired between 225 and 800 nm after sample pretreatment to extract starch. NIR spectra were acquired between 900 and 1700 nm using a poliSPEC NIRe portable instrument on the flours without any kind of pretreatments. An initial exploratory investigation was conducted using principal component analysis and cluster analysis, obtaining interesting preliminary information on patterns among the investigated flours. In particular, the UV-Vis model successfully discerned samples such as potato, chestnut, sunflower, durum wheat, sesame, buckwheat, rice, corn, spelt and 00-type flours. PCA model results obtained from the analysis of NIR spectra also provided comparable results with the UV-Vis model, particularly highlighting the differences observed between hemp and potato flours with soybean flour. Some similarities were identified between other flours, such as barley and millet, rye and oats, and chickpea and amaranth. Therefore, some flour samples underwent surface analysis via scanning electron microscope (SEM) using the Nova NanoSEM 450 to detect distinctive morphology
Optimization of an analytical method based on the use of zwitterionic- phosphorylcholine -HILIC column for the determination of multiple polar emerging contaminants in reclaimed water
No full textThe aim of this study was to optimize a Liquid Chromatography Mass Spectrometry (LC-MS) method using a zwitterionic phosphorylcholine HILIC column for the determination of several Persistent and Mobile Organic Contaminants (PMOC) in wastewater samples. An experimental design approach was implemented to both better understand the retention mechanisms of several polar compounds and to find the optimal operating conditions for their detection and quantification. Eleven PMOCs, with logDpH=7 ranging from -5.27 to 0.24, were considered, including pesticides, artificial sweeteners, pharmaceuticals, and central nervous system stimulants. Key chromatographic variables—such as the initial percentage of the organic mobile phase, temperature, flow rate, gradient time, acid percentage, and the type and concentration of two different salts— were studied to assess their influence on peak areas, retention times and separation efficiency. The results indicated buffer type, flow rate, and initial percentage of organic mobile phase as the most influential factors affecting retention, though the effects were closely related to the chemical and physicochemical properties of the analytes. The optimized instrumental method demonstrated acceptable figures of merit, with recoveries ranging from 49 % to 100 % for all analytes (except taurine, which may require a different experimental preprocessing step). The method also showed satisfactory precision (repeatability of the entire experimental procedure), in terms of Relative Standard Deviation (RSD %), which was <10 % for all analytes. The developed method was successfully applied to the analysis of reclaimed water samples collected in six wastewater treatment plants in two regions of northern Italy. All target ECs were detected and quantified, except for clenbuterol, terbutaline, acesulfame K and 2,4-dichlorophenoxyacetic acid, which were below the detection limit
Gli Aratea di Cicerone. Per un commento al proemio (frr. 1-2) e alla mappa delle costellazioni (frr. 3-34,222).
No full textThis PhD thesis is an edition of the first section of Cicero's Aratea, including the proemium (frr. 1-2) and the star map (frr. 3-34,222), with an Italian translation and commentary.
The linguistic and stylistic analysis highlights the way in which Cicero translates his model, creating thus an original work of poetry. One of the main feature of Cicero's version is the marginalization of the divine providence which Aratus, accordingly to Stoicism, associates to Zeus: this operation could reflect Cicero's first contacts with philosophy, especially with the Epicurean thought.
The Aratea represent a clear effort to build up a poetic language for astronomy: in doing this the author adopts different solutions (transliteration, periphrasis, semantic equivalence), often associated with veritable translator's notes. But more meaningfully, the meta- and translinguistic reflection fits the poem without discontinuity, using resources typical of of the poetic language (such as etymology and polysemy).
Cicero constantly adds pathos to his model emphasising the brightness of the stars and above all personifying the constellations, which became alive: in this way he lends a vivid movement to Aratus' ekphrasis innervating the descriptive structure with narrative elements.
Finally, in the passages of most programmatic relevance (the proemium and the myth of Dike) Cicero's translation shows the mechanism of windows references, trough which the poet alludes to the hesiodic hypotext hidden by Arartus' variations
Corrigendum to “Increasing volume and complexity of pediatric epilepsy surgery with stable seizure outcome between 2008 and 2014: A nationwide multicenter study” [Epilepsy Behav. Oct 2017; 75C:151-157](S1525505017304961)(10.1016/j.yebeh.2017.08.010)
No full textThe authors regret to inform that one of the co-author “Simona Pellacani” is affiliated to IRCCS Stella Maris, Pisa, Italy The authors would like to apologize for any inconvenience caused
Corrigendum to “Increasing volume and complexity of pediatric epilepsy surgery with stable seizure outcome between 2008 and 2014: A nationwide multicenter study” [Epilepsy Behav. Oct 2017; 75C:151-157]
No full textThe authors regret to inform that one of the co-author “Simona Pellacani” is affiliated to IRCCS Stella Maris, Pisa, Italy The authors would like to apologize for any inconvenience caused.</p
On the road to automation:a comparative review on chemometric strategies for GC-MS data analysis
No full textIt is widely proved in the literature the pivotal role of GC-MS technique in obtaining information across diverse research contexts. Given the great importance of GC-MS analysis and the undeniable role of chemometric techniques in signal processing, this review provides perspectives on the latest automatic procedures for performing peak detection, resolution, baseline, and time-shift correction. Herein, insights into the principles behind the most common chemometric methods in scientific literature, PARAFAC2 (PARAllel FACtor analysis 2) and MCR-ALS (Multivariate Curve Resolution - Alternating Least Squares), are provided, along with their respective strengths and limitations. In particular, regarding PARAFAC2, the PARADISe (PARAFAC2-based Deconvolution and Identification System) has been further described, while for MCR-ALS, the latest automated procedures have been explored. The aim of this review is to shed light on the evolving field of automatic GC-MS data analysis and to facilitate the advancement of this field
Multiway fusion of NIR and EEM data for the determination of synthetic caramel in Balsamic Vinegar of Modena
No full textSynthetic caramel is among the most widely used colourants in the food industry. The use of caramel in Balsamic Vinegar of Modena PGI is regulated by the protocol of the Consortium of Balsamic Vinegar of Modena [1]. The addition of caramel may be allowed for colour stabilization and must be declared on the product label. Among the various colouring agents, the most commonly used is the Class IV additive, E-150d, also known as sulphite ammonia caramel. However, caramel may also be “naturally” present in balsamic vinegar due to cooked must, used as raw material during vinegar production. Currently, no official analytical method exists to distinguish between sulphite ammonia caramel and “naturally” occurring caramel in Balsamic Vinegars of Modena PGI. To address this, an analytical approach, combining two spectroscopic techniques, Near Infrared Spectroscopy (NIR) and Fluorescence Spectroscopy was employed. Vinegar samples were analysed both in their original state and after the addition of synthetic caramel.
NIR spectra were acquired, pretreated in order to minimize the non-relevant information and submitted to explorative analysis by Principal Component Analysis.
Fluorescence spectroscopy generated three-dimensional Excitation-Emission Matrices (EEMs) (i.e., samples × emission wavelengths × excitation wavelengths), which required a proper data analysis. Specifically, Parallel Factor Analysis (PARAFAC) [2] was applied to resolve and quantify fluorophores associated with caramel. NIR and EEM data will be fused at both low and mid-level, to build a model to determine the presence of synthetic caramel in balsamic vinegar samples from Modena
Comparative analysis of features extraction protocols for LC-HRMS untargeted metabolomics in mountain cheese ‘identitation’
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