An effective chromatographic fingerprinting workflow based on comprehensive two-dimensional gas chromatography - Mass spectrometry to establish volatiles patterns discriminative of spoiled hazelnuts (Corylus avellana L.).

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) Æ´-nonalactone, Æ´-hexalactone, acetone, and 1-nonanol that are decisive to classify OK and rancid samples; (c) heptanoic and hexanoic acids and Æ´-octalactone present in high relative abundance in rancid-solvent and rancid-stale samples.

Adding extra-dimensions to hazelnuts primary metabolome fingerprinting by comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry featuring tandem ionization: Insights on the aroma potential.

The information potential of comprehensive two-dimensional gas chromatography combined with time of flight mass spectrometry (GC × GC-TOFMS) featuring tandem hard (70 eV) and soft (12 eV) electron ionization is here applied to accurately delineate high-quality hazelnuts (Corylus avellana L.) primary metabolome fingerprints. The information provided by tandem signals for untargeted and targeted 2D-peaks is examined and exploited with pattern recognition based on template matching algorithms. EI-MS fragmentation pattern similarity, base-peak m/z values at the two examined energies (i.e., 12 and 70 eV) and response relative sensitivity are adopted to evaluate the complementary nature of signals. As challenging bench test, the hazelnut primary metabolome has a large chemical dimensionality that includes various chemical classes such as mono- and disaccharides, amino acids, low-molecular weight acids, and amines, further complicated by oximation/silylation to obtain volatile derivatives. Tandem ionization provides notable benefits including larger relative ratio of structural informing ions due to limited fragmentation at low energies (12 eV), meaningful spectral dissimilarity between 12 and 70 eV (direct match factor values range 222-783) and, for several analytes, enhanced relative sensitivity at lower energies. The complementary information provided by tandem ionization is exploited by untargeted/targeted (UT) fingerprinting on samples from different cultivars and geographical origins. The responses of 138 UT-peak-regions are explored to delineate informative patterns by univariate and multivariate statistics, providing insights on correlations between known precursors and (key)-aroma compounds and potent odorants. Strong positive correlations between non-volatile precursors and odorants are highlighted with some interesting linear trends for: 3-methylbutanal with isoleucine (R2 0.9284); 2,3-butanedione/2,3-pentanedione with monosaccharides (fructose/glucose derivatives) (R2 0.8543 and 0.8860); 2,5-dimethylpyrazine with alanine (R2 0.8822); and pyrroles (1H-pyrrole, 3-methyl-1H-pyrrole, and 1H-pyrrole-2-carboxaldehyde) with ornithine and alanine derivatives (R2 0.8604). The analytical work-flow provides a solid foundation for a new strategy for hazelnuts quality assessment because aroma potential could be derived from precursors' chemical fingerprints.

Formation of by-products during chemical interesterification of lipids. Detection and characterization of dialkyl ketones by non-aqueous reversed-phase liquid chromatography-high resolution mass spectrometry and gas chromatography-mass spectrometry.

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.

Evolution of potent odorants within the volatile metabolome of high-quality hazelnuts (Corylus avellana L.): evaluation by comprehensive two-dimensional gas chromatography coupled with mass spectrometry.

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. Graphical abstract 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.