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Filler formulations are complex systems, characterized by a high number of components with different nature, as resins, extenders, additives. One of the main properties of a two‐component epoxy filler used for yacht application is the rheology. Thus, rheological additives are studied in both components after different times from the production. Rheological analysis produces a very large amount of information so statistical methods are useful to elaborate the data. In this study, a univariate approach (ANOVA) and a multivariate data processing, namely, principal component analysis after low‐level data fusion are carried out. It is shown that the multivariate approach provides the maximum useful information on the system. No differences are highlighted in the rheological behavior for the epoxy component, by using different additives while, for the polyamide component, the best rheological additive among the tested is the one that has a polyamide nature, being a polar system as itself. [ABSTRACT FROM AUTHOR]

PoliBrush is a freely distributed, stand-alone software designed for teaching exploratory multivariate analysis in the frame of color RGB and spectral imaging. PoliBrush implements principal component analysis (PCA) as its core method. It features a single main window that provides users with essential tools for spectral image preprocessing and exploration. The software emphasizes an interactive brushing approach, enabling users to gain a comprehensive understanding of the relationships between PCA score space and image pixel space.In the present paper, PoliBrush usage and its operational procedure is demonstrated through two case studies, which are also available for download. The software has already been successfully used in various educational settings and workshops on multivariate approaches for spectral imaging, proving its effectiveness in teaching key concepts. With this original software publication, our aim is to make these tools also accessible to both experienced and novice image analysts. • PoliBrush is a user-friendly interface for exploratory multivariate image analysis. • PoliBrush includes several strategies for spectral image preprocessing. • PoliBrush implements brushing techniques on PCA score plot and image. • PoliBrush is especially designed for teaching purposes. • PoliBrush is a freely distributed stand-alone software. [ABSTRACT FROM AUTHOR]

The GlutoPeak test can predict wheat flour quality by measuring gluten aggregation properties in a short time and using a small amount of sample; thus it has usefulness along the entire wheat delivery chain. However, no information on the suitability of this new test on whole grain flours is available. In this contest a multivariate approach was used to assess the GlutoPeak test ability to predict dough quality directly from whole grain flour. GlutoPeak test was performed on both refined and whole grain flours (22 samples), obtaining both profiles and calculated indices, which were subjected to data exploration through Principal Component Analysis. Results suggested a trend according to farinographic stability values. Furthermore, k-Nearest Neighbours classification models were developed using the GlutoPeak profiles to predict farinographic stability, leading to average prediction ability of 81.8% for both refined and whole grain flour data. The present outcome suggests the possibility of predicting farinographic stability by GlutoPeak test directly on whole grain flour, thus skipping the refinement process. [ABSTRACT FROM AUTHOR]

• Cheese ripening is a complex process involving dehydration, proteolysis, lipolysis. • An analytical strategy based on near-infrared hyperspectral imaging is developed. • NIR bands associated to the main biochemical phenomena are deeply investigated. • The contribution of dehydration, proteolysis and lipolysis is deconvolved. • Multivariate chemical maps show spatial and temporal evolution of cheese ripening. Cheese represents one of the most complex food matrices, for the high number of factors contributing to the chemical composition, and so its evaluation represents an important analytical challenge. The present study describes an innovative and non-destructive analytical approach, based on hyperspectral imaging in the near-infrared region (HSI-NIR) and multivariate pattern recognition, to study and monitor the extent – spatial and temporal – of biochemical phenomena responsible for cheese ripening. NIR spectral bands characterising dehydration, proteolysis and lipolysis were individuated and studied by exploiting a representative sample set of characteristic cheeses. The information obtained was employed to develop score maps based on principal component analysis (PCA), which permitted to monitor and visualise the ripening of Formaggetta , a commercial semi-hard cheese typical of Liguria, an Italian region, providing a deep understanding of the evolution of dehydration, proteolysis and lipolysis during the maturation period that precedes the placing on the market. [ABSTRACT FROM AUTHOR]

The new challenge in the investigation of cultural heritage is the possibility to obtain stratigraphical information about the distribution of the different organic and inorganic components without sampling. In this paper recently commercialized analytical set-up, which is able to co-register VNIR, SWIR, and XRF spectral data simultaneously, is exploited in combination with an innovative multivariate and multiblock high-throughput data processing for the analysis of multilayered paintings. The instrument allows to obtain elemental and molecular information from superficial to subsurface layers across the investigated area. The chemometric strategy proved to be highly efficient in data reduction and for the extraction and integration of the most useful information coming from the three different spectroscopies, also filling the gap between data acquisition and data understanding through the combination of principal component analysis (PCA), brushing, correlation diagrams and maps (within and between spectral blocks) on the low-level fused. In particular, correlation diagrams and maps provide useful information for the reconstruction of a stratigraphic structure without the need to take any sample, thanks to the effective account for inter-correlation among data (variables), which is able to effectively characterize the possible combinations of components located in the same depth level. The highly innovative technology and the data processing strategy are applied for the multi-level characterization of a complex painting reproduction as an illustrative pilot study. [Display omitted] • Novel whiskbroom hyperspectral scanner for high space-coherence chemical mapping. • Simultaneous acquisition of XRF, VNIR and SWIR spectral ranges. • Multiblock approach for the assessment of correlation between spectral ranges. • Multivariate data processing for a thorough characterization of multi-layered samples. [ABSTRACT FROM AUTHOR]

The following research focuses on the characterization of the major components of Extra Virgin Olive Oils (EVOOs), viz. triacylglycerols (TAGs), analyzed both in their intact form and after conversion into fatty acid methyl esters (FAMEs). Samples coming from different Italian regions were evaluated in order to obtain quali/quantitative information, which can be correlated to the cultivar, label and/or place of origin. Two fast chromatographic methods were developed for the determination of TAGs and FAMEs in 200 EVOOs by liquid and gas chromatography, respectively. In both cases, a mass spectrometry library with embedded Linear Retention Indices was explored for the identification of single molecular species. Principal components analysis was performed as a multivariate display method; the score plots showed a clear demarcation between southern and central-northern regions, as well as a discrimination based on the variety of olives. In particular, southern EVOOs were satisfactorily differentiated on the basis of the cultivar, while the central-northern EVOOs showed a partial overlapping, unless a significant reduction of the total variability was carried out, considering only EVOOs produced according to a specific regulation, e.g. oils labelled with Protected Designation of Origin. • Lipid profiles of top-quality Italian extra virgin olive oils (EVOOs) were compared. • Fatty acids and triacylglycerols (TAGs) were determined by fast GC and LC methods. • An MS library of TAGs with embedded Linear Retention Indices (LRI) was tested in LC. • The statistical analysis highlighted significant differences among Italian EVOOs. • Both the cultivar and pedoclimatic conditions affected EVOO clusterization. [ABSTRACT FROM AUTHOR]

The present study describes a multivariate strategy that can be used for automatic on-site processing of reflection mode macro FTIR mapping (MA-rFTIR) data obtained during investigation of artworks. The chemometric strategy is based on the integration of principal component analysis (PCA) with a clustering approach in the space subtended by the three lowest-order principal components and allows to automatically identify the regions of interest (ROIs) of the area scanned and to extract the average FTIR spectra related to each ROI. Thanks to the automatic data management, in-field HSI (hyperspectral imaging)-based analyses may be performed even by staff lacking specific advanced chemometric expertise, as it is sometimes the case for conservation scientists or conservators with a scientific background. MA-rFTIR was only recently introduced in the conservation field and, in this work the technique was employed to characterize the surface of metallic artefacts. The analytical protocol was employed as part of a rapid procedure to evaluate the conservation state and the performance of cleaning methods on bronze objects. Both activities are commonly part of restoration campaigns of bronzes and require an on-site analytical procedure for efficient and effective diagnosis. The performance of the method was first evaluated on aged standard samples (bronzes with a layer of green basic copper hydroxysulphate, treated with different organic coatings) and then scrutinized in situ on areas of the 16th century Neptune fountain statue (Piazza del Nettuno, Bologna, Italy) by Gianbologna. Image 1 • A new multivariate strategy for automatic on-site processing of hyperspectral data. • A powerful clustering algorithm (DBSCAN) to automatically identify ROIs. • Automatic visualization of ROIs and exploratory extraction of average spectra. • Data analysis is easier and applicable in real time during diagnostic campaigns. [ABSTRACT FROM AUTHOR]