Recent analyses using solid phase microextraction in industries related to food made into or from liquids

Determination of volatile compounds in white brine cheese and ultrafiltered cheese during ripening and shelf-life using nano-adsorbent fibers

In this study, determination of aromatic compounds in cheese samples was performed by headspace solid-phase microextraction (HS-SPME) using a new adsorbent as a novel coated fiber in combination with a gas chromatography/mass spectrometry or flame ionization detector to evaluate the changes during ripening. Brine and ultrafiltrated (UF) cheese were sampled via HS-SPME and analyzed by gas chromatography/mass spectrometry. Polysulfone and mesoporous carbon nitride were used as two types of fibers for coating. The results showed that the pH had significant decreased during the 120 days for brine cheese (p < 0.001), and during the 90 days (p < 0.001) for UF cheese. Acidity was relatively stable during the ripening period for both cheeses (p > 0.05). Protein content decreased during the ripening period for both cheeses (p < 0.001). Moisture content also significantly decreased during the ripening period for both cheeses (p < 0.001). 74 compounds were identified in brine cheese and 27 major components in UF cheese. Fatty acids were the predominant components, followed by aldehydes (n: 17, 22.9%), alcohol (n; 12, 16.2%), ester (n: 11, 14.8%), alkane (n: 7, 9.4%), and ketone (n: 6, 8.1%) for white brine cheese, while for UF cheese fatty acid (n: 12, 44.4%) and aldehyde (n: 5, 18.5%), alcohol (n: 3, 11.1%), ketone (n: 3, 11.1%), ester (n: 2, 7.4%) and alkane (n: 1, 3.7%).

Advanced micro-extraction techniques (SPME, HiSorb) for the determination of goat cheese whey wastewater VOCs

HiSorb and solid-phase microextraction (SPME), two environmentally friendly micro-extraction techniques based on the same fundamental principles, were evaluated for their extraction efficiency of volatile organic compounds (VOCs) from goat cheese whey wastewater. For this purpose, a sample preparation method based on the headspace-HiSorb technique was developed and evaluated for its efficiency in terms of the amount of extracted compounds and reproducibility of results. Thermal desorption-gas chromatography/mass spectrometry (TD-GC/MS) and GC/MS analytical methods were used to perform the wastewater analysis, respectively. The experimental parameters of HiSorb were evaluated in terms of probe coating, extraction time, stirring speed, sample volume, extraction temperature and salt addition. Under optimal extraction conditions, it was observed that the use of the divinylbenzene/carbon wide range/polydimethylsiloxane (DVB/CWR/PDMS) triple coating for HiSorb and DVB/Carboxen (CAR)/PDMS for SPME, was best suited to extract a broader range of VOCs with higher peak intensities. A total of 34 VOCs were extracted and determined with the DVB/CWR/PDMS HiSorb probe, while only 23 VOCs were determined with the conventional DVB/CAR/PDMS SPME fiber. The DVB/CWR/PDMS HiSorb probe has a higher adsorbent capacity which results in a higher sensitivity for VOCs compared to the DVB/CAR/PDMS SPME fiber. Furthermore, the HiSorb technique exhibits better reproducibility, as indicated by the lower relative standard deviation (RSD) of 3.7% compared to 7.1% for SPME. Therefore, the HiSorb technique is an effective method for detecting VOCs in complex matrices, such as wastewater.

Study of Consumer Liking of Six Chinese Vinegar Products and the Correlation between These Likings and the Volatile Profile

As the aroma of Chinese vinegar is a key quality trait that influences consumer liking, a combination of sensory data and instrumental measurements were performed to help understand the aroma differences of six types of Chinese vinegar. A total of 52 volatile compounds, mostly ethyl acetate, acetic acid, and phenethyl alcohol, were detected in six types of Chinese vinegar using solid-phase microextraction coupled with gas chromatography–mass spectrometry (SPME-GC–MS). Combined with open-ended questions, the correlation between consumer liking and the volatile profile of the vinegar was further investigated. More consumers preferred the potato vinegar (B6) described as “having a sweet aroma and fruity vinegar aroma”. The Heng-shun Jinyou balsamic vinegar (B5) was not favored by consumers with its exhibition of “too pungent vinegar aroma”. Based on their preference patterns, consumers were grouped into three clusters by k-means clustering and principal component analysis (PCA). Using partial least squares regression (PLSR), the most important volatile compounds that drove consumer liking in the three clusters were obtained, among which 14 compounds such as 1-methylpyrrole-2-carboxaldehyde, ethyl acetate, and acetylfuran had the greatest impact on consumer liking, which could guide manufacturers to improve product quality and customer satisfaction.

Oxidative Quality of Dairy Powders: Influencing Factors and Analysis

Lipid oxidation (LO) is a primary cause of quality deterioration in fat-containing dairy powders and is often used as an estimation of a products shelf-life and consumer acceptability. The LO process produces numerous volatile organic compounds (VOC) including aldehydes, ketones and alcohols, which are known to contribute to the development of off-flavours in dairy powders. The main factors influencing the oxidative state of dairy powders and the various analytical techniques used to detect VOC as indicators of LO in dairy powders are outlined. As the ability to identify and quantify specific VOC associated with LO improves this review highlights how these techniques can be used in conjunction with olfactory and sensory analysis to better understand product specific LO processes with the aim of maximizing shelf-life without compromising quality.

Comparison of Automated Extraction Techniques for Volatile Analysis of Whole Milk Powder

Volatile profiling of whole milk powder is valuable for obtaining information on product quality, adulteration, legislation, shelf life, and aroma. For routine analysis, automated solventless volatile extraction techniques are favored due their simplicity and versatility, however no single extraction technique can provide a complete volatile profile due to inherent chemical bias. This study was undertaken to compare and contrast the performance of headspace solid phase microextraction, thermal desorption, and HiSorb (a sorptive extraction technique in both headspace and direct immersion modes) for the volatile analysis of whole milk powder by gas chromatography mass spectrometry. Overall, 85 unique volatiles were recovered and identified, with 80 extracted and identified using a non-polar gas chromatography column, compared to 54 extracted, and identified using a polar gas chromatography column. The impact of salting out was minimal in comparison to gas chromatography column polarity and the differences between the extraction techniques. HiSorb extracted the most and greatest abundance of volatiles, but was heavily influenced by the number and volume of lactones extracted in comparison to the other techniques. HiSorb extracted significantly more volatiles by direct immersion than by headspace. The differences in volatile selectivity was evident between the techniques and highlights the importance of using multiple extraction techniques in order to obtain a more complete volatile profile. This study provides valuable information on the volatile composition of whole milk powder and on differences between extraction techniques under different conditions, which can be extrapolated to other food and beverages.

Insight on a comprehensive profile of volatile compounds of Chlorella vulgaris extracted by two "green" methods

Some green extraction methods were selected and tested for the extraction of volatile compounds from different samples of the microalga Chlorella vulgaris: ultrasound-assisted liquid-liquid extraction using environment-friendly solvents (LLE) and solid-phase microextraction (SPME). The obtained profiles of volatile chemical compounds were different. Only one molecule was found in common to both extractions. Using the SPME method, the main chemical classes of identified volatile compounds were sulfuric compounds, aldehydes, and alcohols. Using the LLE method, the volatile profile was more balanced with alkanes, fatty acids, terpenes, alcohols, and aldehydes. Multivariate data analyses permitted discrimination among samples. Additionally, the relationship between the physicochemical properties of identified volatile compounds and the methods of extraction was studied. The results showed that the LLE extraction allowed the extraction of volatile compounds having a high boiling point (>160°C) and a high log P (>3). The SPME method was more effective to extract volatile compounds with a low boiling point (<160°C) and a low log P (<3). It is thus necessary to combine several extraction methods to obtain a complete view of the volatile profile for microalgae samples.

Development of a SPME-GC-MS method for the determination of volatile compounds in Shanxi aged vinegar and its analytical characterization by aroma wheel

A solid-phase microextraction followed by gas chromatography-mass spectrometry method was developed to determine the volatile compounds in Shanxi aged vinegar. The optimal extraction conditions were: 50 °C for 20 min with a PDMS/DVB fiber. This analytical method was validated and showed satisfactory repeatability (0.5 %<RSD<12 %), reproducibility (2.5 %<RSD<15.6 %), accuracy and linearity in analysis of volatile compounds. According to the calculation of odor activity value, 19 volatile compounds were identified as aroma-active compounds. Among them, propanoic acid, acetic acid, trimethyl-oxazole, butanoic acid, acetoin, 3-methylbutanoic acid and furfural were the most powerful odorants. The aroma wheel of Shanxi aged vinegar showed that the classes of sensory descriptors are first fatty and roasty, next woody and nutty and minor fruity and floral. Principal component analysis enabled us to investigate dissimilarity/similarity of Shanxi aged vinegar sample of different raw material and ageing time.