Sensory, olfactometry and comprehensive two-dimensional gas chromatography analyses as appropriate tools to characterize the effects of vine management on wine aroma

Abstract

For the first time, the influence of different vine management was evaluated in relation to volatile profile and sensory perception through GC×GC/TOFMS, QDA, GC-FID, GC/MS, and GC-O. GC×GC/TOFMS analyses and QDA have shown that a larger spacing between vine rows (2 rather than 1m), attachment of shoots upwards, and irrigation did not result in wine improvement. Conversely, wines elaborated with grapes from a vine with a lower bud load (20 per plant; sample M1) stood out among the other procedures, rendering the most promising wine aroma. GC×GC/TOFMS allowed identification of 220 compounds including 26 aroma active compounds also distinguished by GC-O. Among them, eight volatiles were important to differentiate M1 from other wines, and five out of those eight compounds could only be correctly identified and quantified after separation in second dimension. Higher levels of three volatiles may explain the relation of M1 wine with red and dry fruits.

Volatile Profile of Sparkling Wines Produced with the Addition of Mannoproteins or Lees before Second Fermentation Performed with Free and Immobilized Yeasts

“…Therefore, it seems that the use of commercial immobilized or free yeasts did not result in differences in chromatographic volatile profile to a point that could be visualized in Figure 1. Experimental retention index (RI) calculated using n-alkanes (C8-C24) analyzed in polar (DB-Wax) column of a GC-MS; b literature RI obtained in a polar column: Gürbüz et al, 13 Fan and Qian, 30 Umano et al, 31 Werkhoff et al, 32 Bosch-Fusté et al, 33 Escudero et al, 34 and Zhao et al; 35 c experimental RI calculated using n-alkanes (C8-C24) analyzed in nonpolar (DB-5) column of a GC-MS; d literature RI obtained in a nonpolar column as described by Adams; 36 e odor description as reported by Tao and Li, 14 Nicolli et al, 18 Li et al, 37 Qian and Wang, 38 Choi, 39 and Peinado et al; 40 f positively identified compounds using standards; g LTPRI values were extrapolated from the linear relation between retention times of n-alcanes and their predetermined LTPRI. CAS: Chemical Abstracts Service; LTPRI exp and LTPRI lit : experimental and literature linear temperature programmed retention indices, respectively; DB-Wax: polyethylene glycol stationary phase; DB-5: 5% diphenyl-95% dimethyl polysiloxane stationary phase; NF: in the LTPRI exp column, it means that this compound was not detected in this specific stationary phase; in the odor column, it means that the odor of this specific compound was not found in scientific literature.…”

“…12 Headspace-solid phase microextraction (HS-SPME) and gas chromatography with mass spectrometric detection (GC-MS) are well-established techniques for extraction and determination of volatile compounds of wines, respectively. [13][14][15][16][17][18] SPME integrates extraction and concentration into a single solvent-free step, followed by thermal desorption of analytes in the injection port of the GC-MS. Additional advantages of these combined techniques include selectivity, sensitivity, absence of solvent, and the use of small amounts of sample. 19 Data obtained from different groups of samples may be evaluated using chemometric tools, including cluster analysis.…”

“…20 Another chemometric approach that may be used to evaluate volatile profile of sets of samples is the combination of Fisher ratio (FR) and principal component analysis (PCA). [15][16][17][18] FR is used to determine the features which best describe the data in terms of discriminative power between predefined classes and also to reduce the dimension of the original variables before a multivariate analysis. From the compounds with the highest values of FR, PCA may be used to provide the visualization of the samples and variables in a twodimensional plane organized according to the differences/ similarities between the data.…”

“…From the compounds with the highest values of FR, PCA may be used to provide the visualization of the samples and variables in a twodimensional plane organized according to the differences/ similarities between the data. 16,18 Therefore, the goal of this study was to verify through statistical tools (heat map, HCA, FR and PCA), for the first time, if the use of mannoproteins during autolysis overcomes the drawback that yeast immobilization might cause on volatile profile of sparkling wines obtained by the traditional method. For this purpose, volatile compounds were evaluated in sparkling wines produced with free and immobilized yeasts, in addition to commercial mannoproteins and lees recovered from other sparkling wines previously produced.…”

Characterization of the aroma profile of novel Brazilian wines by solid-phase microextraction using polymeric ionic liquid sorbent coatings

“…Zini and co-workers [24] have illustrated the advantages of GC×GC for wine aroma profiling enabling the successful identification of 220 compounds, which included esters, alcohols, terpenes, acids, aldehydes, ketones, lactones, phenols, furans, and sulfur compounds. Furthermore, 37 of 220 analytes that were identified in Merlot wines exhibited severe peak overlap in the first dimension but were resolved in the second dimension enabling proper identification.…”