Christian Lindinger

Comparison of nosespace, headspace, and sensory intensity ratings for the evaluation of flavor absorption by fat

The goal of this study was to better understand the correspondence between sensory perception and in-nose compound concentration. Five aroma compounds at three different concentrations increasing by factors of 4 were added to four matrixes (water, skim milk, 2.7% fat milk, and 3.8% fat milk). These were evaluated by nosespace analysis with detection by proton transfer reaction mass spectrometry (PTR-MS), using five panelists. These same panelists evaluated the perceived intensity of each compound in the matrixes at the three concentrations. PTR-MS quantification found that the percent released from an aqueous solution swallowed immediately was between 0.1 and 0.6%, depending on the compound. The nosespace and sensory results showed the expected effect of fat on release, where lipophilic compounds showed reductions in release as fat content increases. The effect is less than that observed in headspace studies. A general correlation between nosespace concentration and sensory intensity ratings was found. However, examples of perceptual masking were found where higher fat milks showed reductions in aroma compound intensity ratings, even if the nosespace concentrations were the same.

When machine tastes coffee: instrumental approach to predict the sensory profile of espresso coffee.

A robust and reproducible model was developed to predict the sensory profile of espresso coffee from instrumental headspace data. The model is derived from 11 different espresso coffees and validated using 8 additional espressos. The input of the model consists of (i) sensory profiles from a trained panel and (ii) on-line proton-transfer reaction mass spectrometry (PTR-MS) data. The experimental PTR-MS conditions were designed to simulate those for the sensory evaluation. Sixteen characteristic ion traces in the headspace were quantified by PTR-MS, requiring only 2 min of headspace measurement per espresso. The correlation is based on a knowledge-based standardization and normalization of both datasets that selectively extracts differences in the quality of samples, while reducing the impact of variations on the overall intensity of coffees. This work represents a significant progress in terms of correlation of sensory with instrumental results exemplified on coffee.

Influence of Foam Structure on the Release Kinetics of Volatiles from Espresso Coffee Prior to Consumption

The relationship between the physical structure of espresso coffee foam, called crema, and the above-the-cup aroma release was studied. Espresso coffee samples were produced using the Nespresso extraction system. The samples were extracted with water with different levels of mineral content, which resulted in liquid phases with similar volatile profiles but foams with different structure properties. The structure parameters foam volume, foam drainage, and lamella film thickness at the foam surface were quantified using computer-assisted microscopic image analysis and a digital caliper. The above-the-cup volatile concentration was measured online by using PTR-MS and headspace sampling. A correlation study was done between crema structure parameters and above-the-cup volatile concentration. In the first 2.5 min after the start of the coffee extraction, the presence of foam induced an increase of concentration of selected volatile markers, independently if the crema was of high or low stability. At times longer than 2.5 min, the aroma marker concentration depends on both the stability of the crema and the volatility of the specific aroma compounds. Mechanisms of above-the-cup volatile release involved gas bubble stability, evaporation, and diffusion. It was concluded that after the initial aroma burst (during the first 2-3 min after the beginning of extraction), for the present sample space a crema of high stability provides a stronger aroma barrier over several minutes.

Prediction of the overall sensory profile of espresso coffe by on-line headspace measurement using proton transfer reaction-mass spectrometry

Abstract Analytical and sensory profiling were performed on different commercially available espresso coffees. Chemical information about differences in composition of the coffee headspace characterising different coffee blends was obtained by on-line analysis using PTR-MS. In addition, an expert panel trained for coffee tasting described each sample by scoring key flavour attributes on an 11-point intensity scale. The overall sensory description of each sample was correlated with the analytically obtained differences in chemical composition to develop a tool predicting the sensory profile based on analytical data. This novel and efficient approach of characterising the coffee aroma by on-line analysis may shorten the time required for the development of new products and improve quality control in a more automated and objective manner.

Methods for artificial perception : Can machine replace man?

Summary The previous ‘Scandinavian’ Weurman Flavour Symposium held in Oslo, Norway, in 1987 had as the main themes chemistry, biotechnology, sensory science and data analysis in flavour research [1]. Since then, many advances have been made, however, when comparing with the Weurman Symposium in 2005, the subject areas and topics of research have not changed very much. Flavour scientists still work with identification of aroma and taste components in foods, their formation, stability and release as well as sensory and data analytical aspects. The knowledge about flavour components in foods and the understanding of the way we perceive them has though considerably expanded. Advances have also been made in the way one can analyse flavours in foods and beverages, and measure responses from and in human subjects. One can say that the toolbox with methods and techniques for flavour analysis has expanded remarkably offering many new possibilities to understand flavour from different perspectives and levels of details. The workshop presented some state-of-the-art applications of modern in vivo and in vitro flavour analysis as well as visual sensory assessments of meals made by machines equipped with sensors and artificial networks processing capability. Also, new ways of studying multisensory processes by stimulating sensory subjects with defined stimuli were discussed. Intelligent ‘artificial perception’ systems may replace some routine sensory analysis and monotonous production tasks in the future, but the development of such systems still require sensory assessments by humans.