S.M. van Ruth

Volatile compounds of rehydrated French beans, bell peppers and leeks. Part 1. Flavour release in the mouth and in three mouth model systems

Abstract Flavour release from three rehydrated vegetables: French beans, red bell peppers, and leeks, was studied directly in the mouth of 12 assessors (oral vapour) and in three mouth model systems; purge-and-trap, and dynamic headspace with and without mastication. Volatile compounds were analysed by gas chromatography and mass spectrometry, which resulted in 30, 52 and 42 identified compounds in French beans, bell, peppers, and leeks, respectively. Propanal, 2-methylpropanal, 2- and 3-methylbutanal, pentanal, hexanal, 2-pentenal, trans -2-hexenal, 2-heptenal, 2-butanone, and 6-methyl-5-hepten-2-one were present in each of them. Flavour release from the three vegetables in model system ‘dynamic headspace and mastication’ did not differ significantly from release in the mouth. Peak areas of volatiles released in the mouth had larger coefficients of variance than the ones released in the model system. Although assessors released volatile compounds with different efficiencies, they showed a statistically consistent efficiency in flavour release across the vegetables.

Analytical strategy coupled with response surface methodology to maximize the extraction of antioxidants from ternary mixtures of green, yellow, and red teas (Camellia sinensis var. sinensis).

This work aimed at using a simplex-centroid design to model the effects of green, yellow, and red tea mixtures (Camellia sinensis var. sinensis) on metal chelation activity, phenolic composition, antioxidant activity, and instrumental taste profile. The regression models that described the extraction of flavan-3-ols, o-diphenols, total phenolic compounds (TPC), free radical scavenging activity toward 2,2-diphenyl-1-picrylhydrazyl radical (DPPH), cupric ion reducing antioxidant activity (CUPRAC), and ferric reducing antioxidant power (FRAP) were significant, and data were fit satisfactorily (R(2) > 80%). A mixture of green and red teas had a synergism in CUPRAC and TPC, whereas a mixture of yellow and red teas had a positive effect on CUPRAC and DPPH. An optimization was performed to maximize the antioxidant activity and flavan-3-ol content and to render a tea with mild bitterness, and results showed that a mixture of 14.81% green, 56.86% yellow, and 28.33% red teas would be the most suitable combination of factors.

Gas chromatography/sniffing port analysis evaluated for aroma release from rehydrated French beans (Phaseolus vulgaris)

The technique of gas chromatography/sniffing port analysis was evaluated for studying the release of aroma compounds from rehydrated diced French beans. The aroma compounds 2-—methylbutanal and hexanal were released at a constant rate over time. An identical selection of odour active compounds was obtained at different sampling times. Mutual proportions were remained among the sampling times, although the total number of perceptions of assessors were different.

Geographical provenance of palm oil by fatty acid and volatile compound fingerprinting techniques

Analytical methods are required in addition to administrative controls to verify the geographical origin of vegetable oils such as palm oil in an objective manner. In this study the application of fatty acid and volatile organic compound fingerprinting in combination with chemometrics have been applied to verify the geographical origin of crude palm oil (continental scale). For this purpose 94 crude palm oil samples were collected from South East Asia (55), South America (11) and Africa (28). Partial least squares discriminant analysis (PLS-DA) was used to develop a hierarchical classification model by combining two consecutive binary PLS-DA models. First, a PLS-DA model was built to distinguish South East Asian from non-South East Asian palm oil samples. Then a second model was developed, only for the non-Asian samples, to discriminate African from South American crude palm oil. Models were externally validated by using them to predict the identity of new authentic samples. The fatty acid fingerprinting model revealed three misclassified samples. The volatile compound fingerprinting models showed an 88%, 100% and 100% accuracy for the South East Asian, African and American class, respectively. The verification of the geographical origin of crude palm oil is feasible by fatty acid and volatile compound fingerprinting. Further research is required to further validate the approach and to increase its spatial specificity to country/province scale.

Verification of organic feed identity by fatty acid fingerprinting.

The origin and authenticity of feed for laying hens is an important and fraud-susceptible aspect in the production of organic eggs. Chemical fingerprinting in combination with chemometric methods is increasingly used in conjunction with administrative controls to verify and safeguard the authenticity of food commodities. On the basis of fatty acid fingerprinting data of 36 organic and 60 conventional feeds, we have developed a chemometric classification model to discriminate between organic and conventional chicken feed. A two-factor partial least squares-discriminant analysis (PLS-DA) model was developed using 70% of the original data. External validation of the model with the remaining 30% of the data showed that all of the organic feeds and 90% of the conventional feeds (18 of 20) were correctly identified by the model. These results indicate that the PLS-DA model developed in this study could be routinely used to verify the identity of unknown or suspicious feed for laying hens.

Authentication of organic feed by near-infrared spectroscopy combined with chemometrics: a feasibility study.

Organic products tend to retail at a higher price than their conventional counterparts, which makes them susceptible to fraud. In this study we evaluate the application of near-infrared spectroscopy (NIRS) as a rapid, cost-effective method to verify the organic identity of feed for laying hens. For this purpose a total of 36 organic and 60 conventional feed samples from The Netherlands were measured by NIRS. A binary classification model (organic vs conventional feed) was developed using partial least squares discriminant analysis. Models were developed using five different data preprocessing techniques, which were externally validated by a stratified random resampling strategy using 1000 realizations. Spectral regions related to the protein and fat content were among the most important ones for the classification model. The models based on data preprocessed using direct orthogonal signal correction (DOSC), standard normal variate (SNV), and first and second derivatives provided the most successful results in terms of median sensitivity (0.91 in external validation) and median specificity (1.00 for external validation of SNV models and 0.94 for DOSC and first and second derivative models). A previously developed model, which was based on fatty acid fingerprinting of the same set of feed samples, provided a higher sensitivity (1.00). This shows that the NIRS-based approach provides a rapid and low-cost screening tool, whereas the fatty acid fingerprinting model can be used for further confirmation of the organic identity of feed samples for laying hens. These methods provide additional assurance to the administrative controls currently conducted in the organic feed sector.

Food Fraud and Authenticity : Emerging issues and future trends

Abstract Food fraud is a significant and growing problem, driven by globalization, economic opportunity, and the low probability and severity of punishment. Although food fraud is economically motivated, it may result in serious health consequences. Therefore, emerging food fraud issues are described in this chapter, including the usage of food fraud databases. Analytical verification of food fraud and food authentication is needed to support proper food safety management systems. However, due to time and money constraints, only a restricted number of samples can be analyzed in a laboratory. For analysis outside the laboratory, rapid, nondestructive, nontargeted methods are needed. This can be either handheld equipment for food safety inspectors or in-line equipment for the food manufacturers.

Eggspectation: organic egg authentication method challenged with produce from ten different countries

Many consumers are willing to pay a higher price for organic eggs. Since these eggs retail at a higher price than conventional eggs and their identity is difficult to verify, they are susceptible to fraud. For the authentication of Dutch eggs RIKILT developed an analytical test method based on carotenoid profiling. In the present study, the method was challenged with eggs from 10 countries. Eggs from 94 farms (65 organic, 29 conventional) were subjected to the carotenoid High Performance Liquid Chromatography - Diode Array Detection profiling combined with k-nearest neighbour classification chemometrics to predict the farming management system category: organic or conventional. The eggs from 39 of the 40 EU organic farms and the eggs of 27 of the 29 EU conventional farms, as well as eggs from 17 of the 25 organic farms from outside the EU were classified correctly. The latter lower rate was mainly due to eggs from Turkey; 78% of which were misclassified. The methodology was successful in farming managemen...

Emerging flavour analysis methods for food authentication

Abstract: This chapter starts with an overview of established flavour analysis methods for assessing food authenticity. Secondly the advantages and disadvantages of each method in combination with their application are discussed. Thirdly an integration of emerging methods with combined analytical techniques for validation of food authenticity will be reviewed. Finally data analysis techniques for determining relationships between instrumental flavour analysis, product authenticity and sensory quality are summarised.

Similarities and differences of the volatile profiles of six spices explored by Proton Transfer Reaction Mass Spectrometry

Aroma properties of spices are related to the volatile organic compounds (VOCs) present, which can provide distinct analytical signatures. The aim of the study was to examine similarity and diversity of VOC profiles of six common market spices (black/white pepper, chili paprika, cinnamon, nutmeg and saffron). The key volatiles were identified by PTR-TOFMS. Twelve samples per spice were subjected to PTR-Quadrupole MS (PTR-QMS) and Principal Component Analysis to compare the groups and examine diversity. With PTR-TOFMS, 101 volatile compounds were identified as total sum across all samples by mass and comparing them with literature data. Some spices comprised key character aroma compounds, e.g. cinnamaldehyde in cinnamon. For others, VOC groups, such as terpenes, acids and aldehydes topped the list. The PTR-QMS in combination with variables selection resulted in distinct PCA patterns for each spice. Variation within the spice groups was observed, but varied with the kind of spice. The results are valuable for future authentication studies.