An integrated fingerprinting and kinetic approach to accelerated shelf-life testing of chemical changes in thermally treated carrot puree

Impact of heat treatment on the flavor stability of Longjing green tea beverages: Metabolomic insights and sensory correlations

The flavor stability of tea beverages during storage has long been a concern. The study aimed to explore the flavor stability of Longjing green tea beverage using accelerated heat treatment trials, addressing the shortage of lengthy storage trials. Sensory evaluations revealed changes in bitterness, umami, overall harmonization, astringency, and ripeness as treatment duration increased. Accompanied by a decrease in L-values, ΔE and an increase in a and b-values. Seventeen non-volatile metabolites and three volatile metabolites were identified differential among samples by metabolomics, with subsequent correlation analysis indicating associations between sensory attributes and specific metabolites. Umami was linked to epigallocatechin 3,5-digallate and alpha-D-glucopyranose, astringency was correlated with ellagic acid and 1-ethyl-1H-pyrrole. Ripeness showed associations with ellagic acid, 6,7-dihydroxycoumarin, heptanal, and benzaldehyde, and overall harmonization was linked to 6,7-dihydroxycoumarin, β-myrcene, α-terpineol, and heptanal. A series of verification tests confirmed the feasibility of accelerated heat treatment trials to replace traditional storage trials. These results offer valuable insights into unraveling the complex relationship between sensory and chemical profiles of green tea beverages.

Flavour stability of sterilised chickpeas stored in pouches

The increasing need for sustainable food choices places a demand on developing palatable foods from lower impact production and with a suitable shelf-life. In this context, knowledge of the sensory properties of whole sterilised chickpeas is required to be able to make them more attractive to the consumers. The sensory quality of chickpeas is largely dependent on the aroma and flavour, which can be influenced by storage conditions. In this study, sterilised chickpeas in two different packaging materials with different oxygen permeabilities, stored up to 52 weeks at ambient temperature (20 °C) were investigated using both descriptive sensory profiling and gas chromatography – mass spectrometry – olfactometry analysis (GC-MS-O). During storage, intense, sulphury and meat-like aromas decreased in intensity, while with longer storage time hay-like, green-like and potato-like flavours and aromas became more apparent. A total of 40 odour-active volatiles were detected, of which some had properties reminiscent of the chickpea flavour profiles. However, no clear relationships could be established between these odorants and the sensory changes observed during storage by descriptive sensory analysis. It was concluded that, significant changes in the sensory attributes of sterilised chickpeas occurred during 52 weeks of storage, but that packaging material does not seem to largely influence the sensory attributes during storage.

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Significant sensory changes occur in sterilised chickpeas during 52 weeks storage.

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40 odour-active volatiles are detected in the sterilised chickpeas.

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Sulphur compounds formed during sterilisation change during storage.

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Hay and green attributes are perceived more intense with increased storage time.

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Oxygen permeability of packaging does not impact the sensory quality during storage.

Potential of 1H NMR fingerprinting and a model system approach to study non-enzymatic browning in shelf-stable orange juice during storage

For the first time, a model system approach was combined with ¹H NMR fingerprinting in studying non-enzymatic browning (NEB) of pasteurized shelf-stable orange juice during storage. Various NEB precursors were used individually or in combinations to formulate simple or complex model systems, respectively, in citric acid buffer. Based on orange juice composition, ascorbic acid, sugars (sucrose, glucose and fructose) and amino acids (proline, arginine, asparagine, aspartic acid, serine and glutamic acid) were selected as the precursors for the model systems. After pasteurization and during subsequent accelerated storage (42 °C, 16 weeks) the model systems displayed a three-phase browning development. The initial browning phase was mainly the result of ascorbic acid degradation especially in the presence of amino acids and sugars. In the later phases, the contribution of reactions of sugars and amino acids to browning became apparent. The application of ¹H NMR fingerprinting on a simple model system containing ascorbic acid revealed that its degradation pathway to intermediates such as xylonic acid, acetic acid and erythrulose was responsible for the major changes during storage. When this model system was complexed by inclusion of sugars and amino acids, the hydrolysis of sucrose to glucose and fructose was identified as the main reaction leading to differences in the samples throughout storage. These three sugars dominated the NMR spectra of the samples, overshadowing several important compounds for NEB such as ascorbic acid and its degradation products. Other more advanced NMR experiments such as two-dimensional NMR analyses should be applied in future research to identify unknown compounds from NEB reactions.

Characterization of blue cheese volatiles using fingerprinting, self-organizing maps, and entropy-based feature selection

Understanding which volatile compounds discriminate between products can be useful for quality, innovation or product authenticity purposes. As dataset size and dimensionality increase, linear chemometric techniques like partial least squares discriminant analysis and variable identification (PLS-DA-VID) may not identify the most discriminant compounds. This research compared the performance of self-organizing maps and entropy-based feature selection (SOM-EFS) and PLS-DA-VID to identify discriminant compounds in 17 blue cheese varieties. A total of 172 volatiles were detected using headspace solid phase microextraction, gas chromatography and mass spectrometry, including 1-nonene and 2,6-dimethylpyridine, which were newly identified in blue cheese. Despite SOM-EFS selecting only 14 volatiles compared to 78 for PLS-DA-VID, SOM-EFS proved more effectively discriminant and improved the median five-fold cross-validated prediction accuracy of the model to 0.94 compared to 0.82 for PLS-DA-VID. These findings introduce SOM-EFS as a powerful non-linear exploratory data analysis approach in the field of volatile analytical chemistry.

Headspace Volatile Evaluation of Carrot Samples-Comparison of GC/MS and AuNPs-hpDNA-Based E-Nose

The performances of a quartz crystal microbalances (QCMs) based on an electronic nose (E-nose), modified with hairpin-DNA (hpDNA) for carrot aroma profiling has been evaluated. Solid phase micro-extraction (SPME) headspace sampling, combined with gas chromatography (GC), was used as a reference method. The changes in carrot aroma profiles stored at different temperatures (−18 °C, 4 °C, 25 °C, and 40 °C) were monitored during time up to 26 days. The principal component analysis of the data evidenced the different aroma patterns related to the presence of different key compounds. The output data achieved with the hpDNA-based E-nose were able to detect aroma patterns similar to gas chromatography with mass spectrometry (GC-MS). This work demonstrates that hpDNA has different sizes of loops that can be used for the development of sensor arrays able to detect aroma patterns in food and their changes with advantages in terms of easiness of usage, rapidity, and cost of analysis versus classical methods.

Comparison of Four Extraction Techniques for the Evaluation of Volatile Compounds in Spray-Dried New Zealand Sheep Milk

Recent growth and diversification of sheep milk products means more sophisticated methods are required to ensure their flavour quality. The objective of this study was to compare four extraction techniques for the analysis of volatile compounds in sheep milk by gas chromatography-mass spectrometry (GC-MS). Solvent Assisted Flavour Evaporation (SAFE), Solid Phase Microextraction (SPME), Headspace Sorptive Extraction (HSSE) and Stir Bar Sorptive Extraction (SBSE) were evaluated for their sensitivity, selectivity, reproducibility, and overall efficiency. A total of 48 volatile compounds from nine compound classes were identified in the spray-dried sheep milk. Alcohols, aldehydes, alkanes, carboxylic acids, ketones, lactones, sulphur compounds, nitrogen compounds, and terpenes were all present, but the differences between the methods were most apparent for lactones. SBSE extracted eight lactones, SAFE extracted four lactones and HSSE and SPME only detected trace levels of two lactones. Six of the lactones—δ-hexa-lactone, δ-octalactone, γ-decalactone, γ-dodecalactone, δ-tetradecalactone, and δ-hexadeca-lactone—were identified for the first time in spray-dried sheep milk. The present work demonstrated that SBSE is an effective tool for the extraction and analysis of volatiles, especially lactones, in sheep milk and dairy products in general. A discussion of the benefits and limitations of each method is included.

Shelf Life of Food Products: From Open Labeling to Real-Time Measurements

The labels currently used on food and beverage products only provide consumers with a rough guide to their expected shelf lives because they assume that a product only experiences a limited range of predefined handling and storage conditions. These static labels do not take into consideration conditions that might shorten a product's shelf life (such as temperature abuse), which can lead to problems associated with food safety and waste. Advances in shelf-life estimation have the potential to improve the safety, reliability, and sustainability of the food supply. Selection of appropriate kinetic models and data-analysis techniques is essential to predict shelf life, to account for variability in environmental conditions, and to allow real-time monitoring. Novel analytical tools to determine safety and quality attributes in situ coupled with modern tracking technologies and appropriate predictive tools have the potential to provide accurate estimations of the remaining shelf life of a food product in real time. This review summarizes the necessary steps to attain a transition from open labeling to real-time shelf-life measurements.