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Abstract: This study represents the first phytochemical research of phenolic components of Sercial and Tinta Negra Vitis vinifera L. The phenolic profiles of Sercial and Tinta Negra V. vinifera L. grape skins (white and red varieties, respectively) were established using high performance liquid chromatography–diode array detection–electrospray ionisation tandem mass spectrometry (HPLC–DAD–ESI-MS n ), at different ripening stages (véraison and maturity). A total of 40 phenolic compounds were identified, which included 3 hydroxybenzoic acids, 8 hydroxycinnamic acids, 4 flavanols, 5 flavanones, 8 flavonols, 4 stilbenes, and 8 anthocyanins. For the white variety, in both ripening stages, hydroxycinnamic acids and flavonols were the main phenolic classes, representing about 80% of the phenolic composition. For red variety, at véraison, hydroxycinnamic acids and flavonols were also the predominant classes (71%), but at maturity, anthocyanins represented 84% of the phenolic composition. As far as we know, 10 compounds were reported for the first time in V. vinifera L. grapes, namely protocatechuic acid-glucoside, p-hydroxybenzoyl glucoside, caftaric acid vanilloyl pentoside, p-coumaric acid-erythroside, naringenin hexose derivate, eriodictyol-glucoside, taxifolin-pentoside, quercetin-glucuronide-glucoside, malylated kaempferol-glucoside, and resveratrol dimer. These novel V. vinifera L. grape components were identified based on their MS n fragmentation profile. This data represents valuable information that may be useful to oenological management and to valorise these varieties as sources of bioactive compounds. [Copyright &y& Elsevier]

• Morphology changes of MNPs were characterized in a quantitative braising process. • Compositions of MNPs were intrinsically rich in glycoconjugates and triglycerides. • MNPs initially formed were inclined to self-assemble into larger particles. • Mechanisms of MNP evolution were revealed from microcosmic-spatial perspectives. • A hypothesis that MNP might be a key factor of broth flavor regulation was proposed. The formation and transformation mechanisms of micro-nano particles (MNPs) in broth during meat braising were systematically investigated through a sophisticated controlled process. Dynamic changes in the morphology, composition and spatial distribution of MNPs were comprehensively characterized, and subsequently the mechanisms were visually uncovered from microcosmic-spatial perspectives. MNPs formed as circular-shape colloidal systems with an aggrandizing tendency for particle number and size and gradually stabilize eventually. Specifically, the major MNPs gradually increased the size from <400 nm to ~1500 nm and accumulated triglycerides and glycoconjugates resulting from lipid oxidation, Maillard reaction, etc. Continuous formation of MNPs in broth progressively facilitated the spatial coalescence and self-assembly of free substances driven by intermolecular interactions, and consequently principal nutrients and flavor compounds further accumulated in the MNPs by the braising process. Hence, this work not only revealed the MNP formation and transformation mechanisms but offered a foundation for investigating MNP-dependent effect on broth flavor. [ABSTRACT FROM AUTHOR]

• IRN, SVM and RF models based on IR spectra of parvalbumin were constructed and compared. • IRN model had the greatest accuracy for recognizing fish pavalbumin (up to 97.3%). • IRN model was based on highly representative featured from IR spectra of the parvalbumin allergen. • IRN model could detect parvalbumin accurately in seafood matrices. • Infrared spectroscopic IRN method was rapid (~20 min) and effective. We have developed a novel approach that involves inception-resnet network (IRN) modeling based on infrared spectroscopy (IR) for rapid and specific detection of the fish allergen parvalbumin. SDS-PAGE and ELISA were used to validate the new method. Through training and learning with parvalbumin IR spectra from 16 fish species, IRN, support vector machine (SVM), and random forest (RF) models were successfully established and compared. The IRN model extracted highly representative features from the IR spectra, leading to high accuracy in recognizing parvalbumin (up to 97.3%) in a variety of seafood matrices. The proposed infrared spectroscopic IRN (IR-IRN) method was rapid (~20 min, cf. ELISA ~4 h) and required minimal expert knowledge for application. Thus, it could be extended for large-scale field screening and identification of parvalbumin or other potential allergens in complex food matrices. [ABSTRACT FROM AUTHOR]