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Nominal sorbitan tristearate (E492) commercial samples are widely used generally as emulsifiers and particularly as anti‐bloom agents in confectionery products. In spite of this generalized use, their qualitative and quantitative evaluation is poorly documented in literature and the relative works go back to the last decades of last century. In the present work, a deep study by HPLC‐High Resolution Mass Spectrometry of qualitative composition of five E492 commercial samples was made up showing a very complex pattern of stearic and palmitic acid esters with the sorbitol anhydrides, sorbitan, and isosorbide. A clear distinction of sorbitan mono‐, di‐, tri‐, and tetra‐esters, of sorbitol penta‐ and hexa‐esters and isosorbide mono‐ and di‐esters was achieved. Contemporarily, difference in the qualitative pattern between E492 commercial samples coming from different suppliers was established. As a consequence, quantitative evaluation can be reliably obtained by using as calibration standard the same E492 present in real samples. The accuracy and recovery of the method were determined allowing in this way a reliable application to commercial confectionery products. The detailed knowledge of STS composition may be of great help to orient the synthesis conditions in order to modulate its properties as a function of various experimental necessities. [ABSTRACT FROM AUTHOR]

Within the pattern of volatiles released by food products (volatilome), potent odorants are bio-active compounds that trigger aroma perception by activating a complex array of odor receptors (ORs) in the regio olfactoria. Their informative role is fundamental to select optimal post-harvest and storage conditions and preserve food sensory quality. This study addresses the volatile metabolome from high-quality hazelnuts (Corylus avellana L.) from the Ordu region (Turkey) and Tonda Romana from Italy, and investigates its evolution throughout the production chain (post-harvest, industrial storage, roasting) to find functional correlations between technological strategies and product quality. The volatile metabolome is analyzed by headspace solid-phase microextration combined with comprehensive two-dimensional gas chromatography and mass spectrometry. Dedicated pattern recognition, based on 2D data (targeted fingerprinting), is used to mine analytical outputs, while principal component analysis (PCA), Fisher ratio, hierarchical clustering, and analysis of variance are used to find decision makers among the most informative chemicals. Low-temperature drying (18-20 °C) has a decisive effect on quality; it correlates negatively with bacteria and mold metabolic activity, nut viability, and lipid oxidation products (2-methyl-1-propanol, 3-methyl-1-butanol, 2-ethyl-1-hexanol, 2-octanol, 1-octen-3-ol, hexanal, octanal and (E)-2-heptanal). Protective atmosphere storage (99% N2-1% O2) effectively limits lipid oxidation for 9-12 months after nut harvest. The combination of optimal drying and storage preserves the aroma potential; after roasting at different shelf-lives, key odorants responsible for malty and buttery (2- and 3-methylbutanal, 2,3-butanedione and 2,3-pentanedione), earthy (methylpyrazine, 2-ethyl-5-methyl pyrazine and 3-ethyl-2,5-dimethyl pyrazine) and caramel-like and musty notes (2,5-dimethyl-4-hydroxy-3(2H)-furanone - furaneol and acetyl pyrrole) show no significant variation.Comprehensive two-dimensional gas chromatography (GC × GC) coupled with mass spectrometric detection captures hazelnut volatiles signatures while advanced fingerprinting approaches based on pattern recognition enable access to a higher level of information [ABSTRACT FROM AUTHOR]

Highlights • EI mass spectra for structural characterization of dialkyl ketones. • Validation protocol for dialkyl ketones quantitative determination by GC–MS and LC-HRMS. • Comparison of DAK detection performance of GC–MS and LC-HRMS techniques. Abstract A new class of foreign substances present in the unsaponifiable fraction of vegetable oils undergone to chemical interesterification was systematically investigated. Their chemical structure, corresponding to dialkyl ketones (DAK) molecules, was elucidated both by gas chromatography-mass spectrometry (GC–MS), and liquid chromatography-high resolution mass spectrometry (LC-HRMS). An analytical protocol aimed to qualitative and quantitative detection of DAK molecules in vegetable oils of confectionery industry interest was developed. Being the range of concentration levels to be evaluated dependent on the technological task of interesterification process, the quantitation step was thoroughly examined. All the validation parameters were satisfactory and particularly the concentration determinations were made more reliable by the contemporary use of several quantitation standards. GC–MS and LC-HRMS analytical techniques exhibited comparable performances even if the second one shown better detection sensitivity. [ABSTRACT FROM AUTHOR]

• Composite class-images discriminate patterns related to sensory defects. • Volatile patterns from spoiled hazelnuts are effectively cross-compared. • GC × GC fingerprinting reveals differences between sample groups. • Flexibility and versatility of pattern recognition fingerprinting. • Exploring dense patterns of chemical information from GC × GC. The volatile fraction of hazelnuts encrypts information about: cultivar/geographical origin, post-harvest treatments, oxidative stability and sensory quality. However, sensory features could be buried under other dominant chemical signatures posing challenges to an effective classification based on pleasant/unpleasant notes. Here a novel workflow that combines Untargeted and Targeted (UT) fingerprinting on comprehensive two-dimensional gas-chromatographic patterns is developed to discriminate spoiled hazelnuts from those of acceptable quality. By flash-profiling, six hazelnut classes are defined: Mould , Mould-rancid-solvent , Rancid , Rancid - stale , Rancid - solvent, and Uncoded KO. Chromatographic fingerprinting on composite 2D chromatograms from samples belonging to the same class (i.e., composite class-images) enabled effective selection of chemical markers: (a) octanoic acid that guides the sensory classification being positively correlated to mould; (b) ƴ-nonalactone, ƴ-hexalactone, acetone, and 1-nonanol that are decisive to classify OK and rancid samples; (c) heptanoic and hexanoic acids and ƴ-octalactone present in high relative abundance in rancid-solvent and rancid-stale samples. [ABSTRACT FROM AUTHOR]