1,720,962 research outputs found
Exploring the Effect of Different Storage Conditions on the Aroma Profile of Bread by Using Arrow-SPME GC-MS and Chemometrics
Get PDFIn 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 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
Optimization of an analytical method based on SPME-Arrow and chemometrics for the characterization of the aroma profile of commercial bread
Get PDFA 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
Get PDFThis 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
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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