1,721,412 research outputs found
Multiclass methods in the analysis of metabolomic datasets: The example of raspberry cultivar volatile compounds detected by GC-MS and PTR-MS
Full text linkMulticlass sample classification and marker selection are cutting-edge problems in metabolomics. In the present study we address the classification of 14 raspberry cultivars having different levels of gray mold (Botrytis cinerea) susceptibility. We characterized raspberry cultivars by two headspace analysis methods, namely solid-phase microextraction/gas chromatography-mass spectrometry (SPME/GC-MS) and proton transfer reaction-mass spectrometry (PTR-MS). Given the high number of classes, advanced data mining methods are necessary. Random Forest (RF), Penalized Discriminant Analysis (PDA), Discriminant Partial Least Squares (dPLS) and Support Vector Machine (SVM) have been employed for cultivar classification and Random Forest-Recursive Feature Elimination (RF-RFE) has been used to perform feature selection. In particular the most important GC-MS and PTR-MS variables related to gray mold susceptibility of the selected raspberry cultivars have been investigated. Moving from GC-MS profiling to the more rapid and less invasive PTR-MS fingerprinting leads to a cultivar characterization which is still related to the corresponding Botrytis susceptibility level and therefore marker identification is still possible.Fil: Cappellin, Luca. Fondazione Edmund Mach. Research and Innovation Centre; ItaliaFil: Aprea, Eugenio. Fondazione Edmund Mach. Research and Innovation Centre; ItaliaFil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Romano, Andrea. Fondazione Edmund Mach. Research and Innovation Centre; ItaliaFil: Gasperi, Flavia. Fondazione Edmund Mach. Research and Innovation Centre; ItaliaFil: Biasioli, Franco. Fondazione Edmund Mach. Research and Innovation Centre; Itali
A multi-product approach for detecting subjects’ and objects’ covariates in consumer preferences
No full textPurpose – A different framework based on a parametric version of the process generating the hedonic scores is adopted. More precisely, a probability distribution for ordinal responses is proposed as a mixture of two components, denoted as feeling (as expressed preference) and uncertainty component (as inherent indecision). The purpose of this paper is to analyse the effect of covariates on the consumers’ behaviour pattern according to a statistical model. Design/methodology/approach – Sample data come from a multidisciplinary research aimed to improve the quality and marketability of soft fruits. Then, a stochastic model with subjects’ and objects’ covariates is built and the interpretation of significant results is discussed. Findings – The joint effects of personal characteristics and chemical contents of juice on the hedonic scores given by consumers are examined and graphically depicted by means of a significant model. Originality/value – The paper suggests a multi-product approach to expressed hedonic scores by means of a generalization of CUB models
Tracing coffee origin by direct injection headspace analysis with PTR/SRI-MS
Full text linkThe headspace of six roasted Coffea arabica coffees, both brew and powder, of different geographical origin (Brazil, Ethiopia, Guatemala, Costa Rica, Colombia, and India) was analysed by Proton Transfer Reaction-Time of Flight-Mass Spectrometry. For the first time, in the case of coffee, a Switching Reagent Ion System has been used to produce different ionisation agents: H3O+, NO+ and O2+. Significant differences were found among volatile concentrations for the different origins both for powders and brews, in particular high concentrations of terpenes for Ethiopia, sulphur compounds for Colombia and thiazoles for Brazil and India. Effective classification models have been set for the different ionization modes and data fusion of data obtained by different reagent ions further reduced the classification errors.Fil: Yener, Sine. Fondazione Edmund Mach. Research and Innovation Centre. Department of Food Quality and Nutrition; Italia. Leopold-Franzens Universität Innsbruck. Insitute für Ionenphysik und Angewandte Physik; AustriaFil: Romano, Andrea. Fondazione Edmund Mach. Research and Innovation Centre. Department of Food Quality and Nutrition; ItaliaFil: Cappellin, Luca. Fondazione Edmund Mach. Research and Innovation Centre. Department of Food Quality and Nutrition; ItaliaFil: Granitto, Pablo Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; ArgentinaFil: Aprea, Eugenio. Fondazione Edmund Mach. Research and Innovation Centre. Department of Food Quality and Nutrition; ItaliaFil: Navarini, Luciano. Illycaffè S.p.a; ItaliaFil: Märk, Tilmann D.. Leopold-Franzens Universität Innsbruck. Insitute für Ionenphysik und Angewandte Physik; AustriaFil: Gasperi, Flavia. Fondazione Edmund Mach. Research and Innovation Centre. Department of Food Quality and Nutrition; ItaliaFil: Biasioli, Franco. Fondazione Edmund Mach. Research and Innovation Centre. Department of Food Quality and Nutrition; Itali
Nanosensor Based on Thermal Gradient and Machine Learning for the Detection of Methanol Adulteration in Alcoholic Beverages and Methanol Poisoning
Full text linkMethanol, naturally present in small quantities in the distillation of alcoholic beverages, can lead to serious health problems. When it exceeds a certain concentration, it causes blindness, organ failure, and even death if not recognized in time. Analytical techniques such as chromatography are used to detect dangerous concentrations of methanol, which are very accurate but also expensive, cumbersome, and time-consuming. Therefore, a gas sensor that is inexpensive and portable and capable of distinguishing methanol from ethanol would be very useful. Here, we present a resistive gas sensor, based on tin oxide nanowires, that works in a thermal gradient. By combining responses at various temperatures and using machine learning algorithms (PCA, SVM, LDA), the device can distinguish methanol from ethanol in a wide range of concentrations (1–100 ppm) in both dry air and under different humidity conditions (25–75% RH). The proposed sensor, which is small and inexpensive, demonstrates the ability to distinguish methanol from ethanol at different concentrations and could be developed both to detect the adulteration of alcoholic beverages and to quickly recognize methanol poisoning
PTR-MS: nuove prospettive in campo agroalimentare dalla versione con analizzatore a tempo di volo
No full textIl PTR-MS (Proton Transfer Reaction-Mass Spectrometry) è stato proposto come strumento per il monitoraggio ad alta sensibilità e risoluzione temporale dei composti organici volatili. I limiti della prima realizzazione di questa tecnica basata su analizzatore a quadrupolo sono stati parzialmente superati dalla nuova versione di questo strumento basata su un analizzatore a tempo di volo (PTR-ToF-MS) che permette di incrementare risoluzione temporale, range dinamico e di massa nonché la risoluzione di massa. Qui presentiamo un approccio metodologico completo, dall’acquisizione degli spettri all’analisi con metodi di data mining, applicabile in contesti agroindustriali, e una rivista delle prime applicazioni in campo agroalimentare di questo nuovo strument
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Full text linkWe 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
Formaggio: così genetica, tipo di allevamento e alimentazione influenzano l'aroma
No full textI composti organici volatili (VOC) contribuiscono a definire l’aroma del formaggio che è uno dei principali criteri di scelta da parte del consumatore. Recentemente abbiamo investigato il profilo aromatico di diverse tipologie di formaggi sia con tecniche gascromatografiche sia di spettrometria di massa (SPME/GC-MS e PTR-ToF-MS) per verificare la possibilità di utilizzare l’impronta aromatica come metodo di tracciabilità dei prodotti. In particolare, abbiamo considerato formaggi di diversa tipologia, provenienti da diverse aziende e alimentazioni e abbiamo studiato gli effetti delle caratteristiche produttive e della genetica delle vacche da latte sul loro profilo aromatico. Dai risultati emerge che l’aroma del formaggio è influenzato sia dalle caratteristiche produttive sia genetiche degli animali e può essere utilizzato come strumento di valorizzazione di prodotto o di processo produttivo
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