Aroma-matrix interaction in food: an APCI approach

An overview is presented of the principle, scope and major applications to date of the use of atmospheric pressure chemical ionisation mass spectrometry (APCI-MS) for monitoring the kinetics of release of flavour volatiles in real time. There are four major areas in this thesis that extend from the measurement of flavour molecular mobility in sugar solutions, to the investigation of APCI-MS as a diagnostic tool for classifying apple cultivars and predicting age of cheese. Headspace techniques are the most extensively employed techniques in food analysis to measure volatile compounds, which play a central role in the perceived quality of food. The use of APCI-MS to measure aroma headspace availability with the addition of solutes was evaluated for two sugars of differing chain lengths (fructose and fructooligosaccharide (FOS)). In vitro aroma release was investigated at equilibrium using APCI-MS. An increase in the concentration of fructose above 25 % (w /w) was shown to significantly (p < 0.05) increase the release of ethyl butyrate, ethyl acetate and benzaldehyde into the gas phase above the aqueous solutions. Proton nuclear magnetic resonance (1 H NMR) was used to investigate the nature of solvent-sugar-aroma interactions with a view to explain the differential availability of aroma volatiles in sweetened and biopolymer rich solutions. The T1 relaxation times, and diffusion coefficients, provided preliminary clues as to the interactions between water, aroma and biopolymer. In the case of in vivo measurement, aroma perception was dependent on two key factors – firstly the equilibrium gas phase concentration of the aroma compounds within the oral/ nasal cavity and secondly the dynamic interaction of the compound with food and saliva (persistence). The overall process was influenced by the properties of the flavour compounds (i.e. its hydrophobicity) and the physiological conditions of the mouth, nose and throat during consumption of the food. A comparison was made between the intensities of anisaldehyde, furaneol and guaiacol in the headspace above simple solutions of water, to demonstrate the impact of matrix on flavour release in a frozen dairy dessert. The oral and nasal persistence of aromas following swallowing samples of a model frozen dairy dessert was investigated by collecting expired air from nose and mouth over 60-seconds. The decay curves (which illustrates persistence) of volatiles in breath showed that furaneol was the most persistent aroma, due to its hydrophilic nature and low volatility, that is expressed by the vapour pressure values of the pure compound. It is presumed to interact with the nasal mucosa, thereby prolonging persistence and potentially offering a significantly different perceptual profile to the less persistent compounds (Hodgson, Parker, Linforth, & Taylor, 2004). Thus, real time APCI-MS headspace data could be used to validate mathematical modelling of flavour release (Harvey & Barra, 2003). The feasibility of APCI-MS volatile compound fingerprinting in conjunction with chemometrics as a new strategy for rapid and non-destructive food classification was demonstrated when 202 clarified monovarietal juices extracted from apples differing in their botanical and geographical origins were characterised. Partial Least Square-Linear Discriminant Analysis (PLS-LDA) gave 100 % correct classification for the categorization by cultivar. Another PLS regression model was built to interpret and predict the age of Cheddar using headspace data from GC-MS and APCI-MS. The RMSEP and R2 values for the prediction model were 3.94 and 0.85 respectively. This further established the applicability of multivariate statistical technique as a tool to monitor the quality of foodstuff. Throughout the thesis, recommendations regarding practical implications for APCI-MS analysis and applications are demonstrated and discussed