Non-destructive egg breed separation using advanced VOC analytical techniques HSSE-GC-MS, PTR-TOF-MS, and SIFT-MS: Assessment of performance and systems' complementarity.

Over the past decade, advanced analytical techniques have been utilized to examine volatile organic compounds (VOCs) in eggs. These VOCs offer valuable insights into factors such as freshness, fertility, the presence of cracks, embryo sex, and breed. In our study, we assessed three mass spectrometry-based systems (headspace sorptive extraction gas chromatography-mass spectrometry; HSSE-GC-MS, proton transfer reaction time-of-flight-mass spectrometry; PTR-TOF-MS; and selected ion flow tube mass spectrometry; SIFT-MS) to analyze and identify VOCs present in intact hatching eggs from three distinct breeds (Dekalb white layer, Shaver brown layer, and Ross 308 broiler). The eggs were sampled on incubation days 2 and 8, to identify VOCs that distinguish breeds irrespective of incubation day. VOC measurements were conducted on 15 eggs per breed by placing them together with PDMS-coated stir bars inside inert Teflon® air sampling bags. After an accumulation period of 2 h, the headspace was analyzed using PTR-TOF-MS and SIFT-MS, while the VOCs adsorbed onto the stir bars were analyzed using GC-MS for additional compound identification. Partial least squares discriminant analysis (PLS-DA) models were constructed for breed differentiation, and variable selection was performed. As a result, 111 VOCs were identified using HSSE-GC-MS, with alcohols and esters being the most abundant. The PLS-DA models demonstrated the efficacy of breed discrimination, with the HSSE-GC-MS and the PTR-TOF-MS exhibiting the highest balanced accuracy of 95.5 % using a reduced set of 11 VOCs and 5 product ions, respectively. The SIFT-MS model had a balanced accuracy of 92.8 % with a reduced set of 11 product ions. Furthermore, complementarity was observed between HSSE-GC-MS, which primarily selected higher molecular weight VOCs, and PTR-TOF-MS and SIFT-MS. A higher correlation was found for compound abundances between the HSSE-GC-MS and the PTR-TOF-MS relative to the SIFT-MS, indicating that the PTR-TOF-MS was better suited to quantify specific compounds identified by the HSSE-GC-MS. Finally, the findings support the presence of VOCs originating from both synthetic and natural sources, highlighting the ability of the VOC analysis systems to non-destructively perform quality control and reveal differences in management practices or biological information encoded in eggs.

Emission and Mechanical Properties of Glass and Cellulose Fiber Reinforced Bio-Polyamide Composites.

Climate change, access, and monopolies to raw material sources as well as politically motivated trade barriers are among the factors responsible for a shortage of raw materials. In the plastics industry, resource conservation can be achieved by substituting commercially available petrochemical-based plastics with components made from renewable raw materials. Innovation potentials are often not used due to a lack of information on the use of bio-based materials, efficient processing methods, and product technologies or because the costs for new developments are too high. In this context, the use of renewable resources such as fiber-reinforced polymeric composites based on plants has become an important criterion for the development and production of components and products in all industrial sectors. Bio-based engineering thermoplastics with cellulose fibers can be used as substitutes because of their higher strength and heat resistance, but the processing of this composite is still challenging. In this study, composites were prepared and investigated using bio-based polyamide (PA) as a polymer matrix in combination with a cellulosic fiber and, for comparison purposes, a glass fiber. A co-rotating twin-screw extruder was used to produce the composites with different fiber contents. For the mechanical properties, tensile tests and charpy impact tests were performed. Compared to glass fiber, reinforced PA 6.10 and PA 10.10, a significantly higher elongation at break with regenerated cellulose fibers, can be achieved. PA 6.10 and PA 10.10 achieve significantly higher impact strengths with the regenerated cellulose fibers than the composites with glass fibers. In the future, bio-based products will also be used in indoor applications. For characterization, the VOC emission GC-MS analysis and odor evaluation methods were used. The VOC emissions (quantitative) were at a low level but the results of the odor tests of selected samples showed values mostly above the required limit values.

A comparison between mobile and stationary gas chromatography-mass spectrometry devices for analysis of complex volatile profiles.

On-site analysis of volatile organic compounds (VOCs) with miniaturized gas chromatography-mass spectrometry (GC-MS) systems is a very rapidly developing field of application. While, on the one hand, major technological advances are improving the availability of these systems on the market, on the other hand, systematic studies to assess the performance of such instruments are still lacking. To fill this gap, we compared three portable GC-MS devices to a state-of-the-art benchtop (stationary) system for analysis of a standard mixture of 18 VOCs. We systematically compared analytical parameters such as the sensitivity and similarity of the signal response pattern and the quality of the obtained mass spectra. We found that the investigated mobile instruments (i) showed different response profiles with a generally lower number of identified analytes. Also, (ii) mass spectral reproducibility (% relative standard deviation (RSD) of the relative abundance of selective fragments) was generally worse in the mobile devices (mean RSD for all targeted fragments ~9.7% vs. ~3.5% in the stationary system). Furthermore, mobile devices (iii) showed a poorer mass spectral similarity to commercial reference library spectra (>20% deviation of fragment ion relative intensity vs. ~10% in the stationary GC-MS), suggesting a less reliable identification of analytes by library search. Indeed, (iv) the performance was better with higher-mass and/or more abundant fragments, which should be considered to improve the results of library searches for substance identification. Finally, (v) the estimation of the signal-to-noise ratio (S/N) in mobile instruments as a measure of sensitivity revealed a significantly lower performance compared to the benchtop lab equipment (with a ratio among medians of ~8 times lower). Overall, our study reveals not only a poor signal-to-noise ratio and poor reproducibility of the data obtained from mobile instruments, but also unfavorable results with respect to a reliable identification of substances when they are applied for complex mixtures of volatiles.

Discrimination and characterization of the volatile organic compounds in eight kinds of huajiao with geographical indication of China using electronic nose, HS-GC-IMS and HS-SPME-GC-MS.

Huajiao (Zanthoxylum bungeanum maxim. and Zanthoxylum armatum DC.) is a highly prized spice in China due to its distinctive aroma and taste. The volatile organic compounds (VOCs) of eight kinds of red and green huajiao which varied according to geographical indication of P.R. China were evaluated by electronic nose (E-nose), headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). Results showed that red huajiao emitted more terpenes, esters, and fewer alcohols than green huajiao. Partial least squares-discriminant analysis based on GC-MS and GC-IMS data was revealed a good classifying tool for huajiao from different original habitats. Four and eight aroma substances were selected as the potential markers by the variable importance in projection (VIP) variable selection method, respectively. The results of the current study provide a useful basis in the huajiao aroma difference study. Additionally, a rapid huajiao aroma analysis method using GC-IMS was developed.

Developments in effective use of volatile organic compound analysis to assess flavour formation during cheese ripening.

In the burgeoning demand for optimization of cheese production, ascertaining cheese flavour formation during the cheese making process has been the focal point of determining cheese quality. In this research reflection, we have highlighted how valuable volatile organic compound (VOC) analysis has been in assessing contingent cheese flavour compounds arising from non-starter lactic acid bacteria (NSLAB) along with starter lactic acid bacteria (SLAB), and whether VOC analysis associated with other high-throughput data might help provide a better understanding the cheese flavour formation during cheese process. It is widely known that there is a keen interest to merge all omics data to find specific biomarkers and/or to assess aroma formation of cheese. Towards that end, results of VOC analysis have provided valuable insights into the cheese flavour profile. In this review, we are pinpointing the effective use of flavour compound analysis to perceive flavour-forming ability of microbial strains that are convenient for dairy production, intertwining microbiome and metabolome to unveil potential biomarkers that occur during cheese ripening. In doing so, we summarised the functionality and integration of aromatic compound analysis in cheese making and gave reflections on reconsidering what the role of flavour-based analysis might have in the future.

Medical diagnosis at the point-of-care by portable high-field asymmetric waveform ion mobility spectrometry: a systematic review and meta-analysis.

Non-invasive medical diagnosis by analysing volatile organic compounds (VOCs) at the point-of-care is becoming feasible owing to recent advances in portable instrumentation. A number of studies have assessed the performance of a state-of-the-art VOC analyser (micro-chip high-field asymmetric waveform ion mobility spectrometry, FAIMS) for medical diagnosis. However, a comprehensive meta-analysis is needed to investigate the overall diagnostic performance of these novel methods across different medical conditions. An electronic search was performed using the CAplus and MEDLINE database through the SciFinder platform. The review identified a total of 23 studies and 2312 individuals. Eighteen studies were used for meta-analysis. A pooled analysis found an overall sensitivity of 80% (95% CI, 74%-85%,I2= 62%), and specificity of 78% (95% CI, 70%-84%,I2= 80%), which corresponds to the overall diagnostic performance of micro-chip FAIMS across many different medical conditions. The diagnostic accuracy was particularly high for coeliac and inflammatory bowel disease (sensitivity and specificity from 74% to 97%). The overall diagnostic performance was similar across breath, urine, and faecal matrices with sparse logistic regression and random forests algorithms resulting in higher diagnostic accuracy. Sources of variability likely arise from differences in sample storage, sampling protocol, method of data analysis, type of disease, sample matrix, and potentially to clinical and disease factors. The results of this meta-analysis indicate that micro-chip FAIMS is a promising candidate for disease screening at the point-of-care, particularly for gastroenterology diseases. This review provides recommendations that should improve the techniques relevant to diagnostic accuracy of future VOC and point-of-care studies.

Estimation model for evaporative emissions from gasoline vehicles based on thermodynamics.

In this study, we conducted seven-day diurnal breathing loss (DBL) tests on gasoline vehicles. We propose a model based on the theory of thermodynamics that can represent the experimental results of the current and previous studies. The experiments were performed using 14 physical parameters to determine the dependence of total emissions on temperature, fuel tank fill, and fuel vapor pressure. In most cases, total emissions after an apparent breakthrough were proportional to the difference between minimum and maximum environmental temperatures during the day, fuel tank empty space, and fuel vapor pressure. Volatile organic compounds (VOCs) were measured using a Gas Chromatography Mass Spectrometer and Flame Ionization Detector (GC-MS/FID) to determine the Ozone Formation Potential (OFP) of after-breakthrough gas emitted to the atmosphere. Using the experimental results, we constructed a thermodynamic model for estimating the amount of evaporative emissions after a fully saturated canister breakthrough occurred, and a comparison between the thermodynamic model and previous models was made. Finally, the total annual evaporative emissions and OFP in Japan were determined and compared by each model.

A new approach to detect early or hidden fungal development in indoor environments.

In addition to the biodegradation problems encountered in buildings, exposure of their occupants to mold is responsible for numerous diseases such as respiratory infections, immediate or delayed allergies and different types of irritations. However, current techniques are unable to detect mold at an early stage of development or hidden contaminants. Moularat et al., in 2008 has established chemical fingerprints of moldy growth from Volatile Organic Compounds (VOCs) arising specifically from fungal metabolism and developed the Fungal Contamination Index (FCI) (Moularat et al., 2008a,b). This index has the advantage of detecting fungal development both reliably and rapidly before any visible signs of contamination could be detected. However, even though the FCI has been widely tested, VOCs' analysis by GC/MS, which is required for index calculation, is incompatible with real-time monitoring strategy for indoor environments. In this context, researches around FCI exploitation have been followed up in order to provide a monitoring device widely deployable which is the result of the miniaturization of an analytical chain for portable, reliable and low-cost applications. This device is based on one hand the selection and concentration of chemical compounds from the sample of interest and on the other hand the development of an array of different conducting polymer based sensors in order to obtain a specific footprint. This fungal contamination detection device was the subject of patent applications by the CSTB. The modularity of the system (ability to vary both the elements of detection polymers and retention time of interest) allows for expansion of its use to other pollutants.