Department of Chemistry and SMART Inter-Department Research Center, University of Bari "Aldo Moro", Via E. Orabona 4, 70126 Bari, Italy.
Published: March 2022
AI Article Synopsis
Article Abstract
This review takes a snapshot of the main multivariate statistical techniques and methods used to process data on the concentrations of wine volatile molecules extracted by means of solid phase micro-extraction and analyzed using GC-MS. Hypothesis test, exploratory analysis, regression models, and unsupervised and supervised pattern recognition methods are illustrated and discussed. Several applications in the wine volatolomic sector are described to highlight different interactions among the various matrix components and volatiles. In addition, the use of Artificial Intelligence-based methods is discussed as an innovative class of methods for validating wine varietal authenticity and geographical traceability.
In this study, three fermentation treatments of spontaneous fermentation (SF), direct inoculation of CECA (YF), and inoculation with CECA after addition of dimethyl dicarbonate (YDF) were carried out. Multivariate statistical analysis approved that CECA inoculation significantly influenced the composition of 141 metabolites (15 volatile organic compounds (VOCs) and 126 non-VOCs), mainly consisting of 36 acids and derivatives and 25 lipids and lipid-like molecules. YF and YDF wines exhibited similar correlations with aroma types, while there were differences in the kinds and number of VOCs.
This study explores the potential of indigenous non- yeasts isolated from L. grape skins to improve the quality of regional wines by enhancing their physicochemical and sensory characteristics. Five promising yeast strains were identified at different stages of fermentation: (J1Y-T1), (Y5P-T5), (JF3-T1N), (Y8P-T8), and (WMP4-T4).
Background: The volatile composition of Ruché, a red wine produced from a native grape in Piedmont (Italy), was investigated using headspace-solid phase microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC/MS). The main volatile compounds of the wine were identified and quantified. Chemometric techniques were applied to identify features and possible clusters among the different samples.
School of Agriculture, Food and Wine, and Waite Research Institute, The University of Adelaide, PMB 1, Glen Osmond, South Australia 5064, Australia. Electronic address:
The study focused on three coffee estates in New South Wales, aiming to enhance the flavor profiles of Australian coffee through different processing methods (wet fermented and non-fermented).
Researchers analyzed 33 volatile compounds in both green and roasted coffee beans, identifying various esters, alcohols, acids, and more, while also assessing sensory characteristics like appearance and flavor.
Findings indicated that wet fermentation improved certain desirable aromas and flavors in coffee, particularly enhancing notes associated with premium coffees, such as "black tea leaves" and "dark chocolate."
Department of Wine, Food and Molecular Biosciences, Faculty of Agriculture and Life Sciences, Lincoln University, P.O. Box 85084, Lincoln 7647, New Zealand.
Intestinal mucosal barrier damage is regarded as the critical factor through which chronic unpredictable mild stress (CUMS) leads to a variety of physical and mental health problems. However, the exact mechanism by which CUMS induces intestinal mucosal barrier damage is unclear. In this study, 14, 28, and 42 d CUMS model mice were established.
