Study of Aged Cognac Using Solid-Phase Microextraction and Partial Least-Squares Regression

Abstract

Headspace solid-phase microextraction (SPME) and GC-MS were used to analyze 17 commercial French Cognac brandies (9 young and 8 well-aged, ranging in age from 3 to 55 years). Sixty-four volatiles were chosen on the basis of chromatographic separation and/or known odor importance. Chromatographic peaks were manually integrated and the peak area data analyzed using partial least-squares (PLS) regression to study relationships between volatile composition (X variables) and age (Y variable). When only those compounds with the highest significance were included and from these selected the variables (a total of 33) with the highest correlation loadings on the first two principal components, principal component 1 explained 82% of the variance of the measured compounds and 85% of the variance in age. These were considered the most important volatiles to distinguish products of different ages because young and old samples were separated along principal component 1. Norisoprenoids, terpenes, and acetate esters had weaker positive and negative loadings and were therefore left out. The PLS model could predict sample age accurately with the optimum 33 volatiles as well as with a smaller subset consisting of ethyl esters and methyl ketones.

Solid-Phase Microextraction (SPME) Techniques for Quality Characterization of Food Products: A Review

“…They developed a reliable prediction model having a correlation coefficient (R 2 ) of 0.998, slope of 0.996, root mean square error (RMSE) value of 1.17, and an offset value of 0.081 using 33 variables (including 24 esters, four methyl ketones, two aldehydes, two alcohols, and one lactone). Watts et al (2003) also showed that their model could predict the age of cognac with a reduced subset from the 33 original variables. Using two subsets containing four methyl ketones and 13 ethyl esters either individually or together, they could develop PLS prediction models with R 2 values >0.934 and RMSE error values <6.47.…”

“…Most of the volatiles extraction for the alcoholic beverages were carried out at 22°C to 55°C, and the preferred desorption temperatures were between 200°C to 250°C (Table 2). Watts et al (2003) used SPME to extract volatiles from cognac and used the extracted volatiles to develop a partial least squares (PLS) regression model to predict the aging of cognac. They developed a reliable prediction model having a correlation coefficient (R 2 ) of 0.998, slope of 0.996, root mean square error (RMSE) value of 1.17, and an offset value of 0.081 using 33 variables (including 24 esters, four methyl ketones, two aldehydes, two alcohols, and one lactone).…”

Total Protein and Amino Acid Composition in Selected Fruits of Russia

“…Merchandising as a science is continually evolving, resulting in development of new science based commodity research indicators which may be used for assessing quality and authenticity of the components used for food products (Wakefield 2002;Watts 2003;Dzhakhangirova, 2016).…”

“…Various researches have been conducted for the assessment of proteins and amino acids characteristics in vegetable and natural products (Wakefield, 2002;Watts, 2003;Woolfe, 2004). Further, researcher have developed a new objective as commodity research indicator of vegetable proteins" quality i.e.…”

“…Further, researcher have developed a new objective as commodity research indicator of vegetable proteins" quality i.e. the molecular weight, which is listed as the main criterion in regulatory documentationSpecifications TU-9143-022-56529037-13(Russian Federation) (Winnepenninckx, 1996;Xu, 2002;Watts, 2003), and may be used as a valid criterion for determining the degree of counterfeiting of herbal raw materials and products of processing. The modified method of thin-layer gel-chromatography (TLGC) has been developed for determining the molecular weight as an integral part of the set of methods intended for commodity research and assessment of vegetable proteins, which is simple, economical, and affordable (Winnepenninckx, 1996;Zhang, 2000).…”