Analysis of volatile compounds of Tremella aurantialba fermentation via electronic nose and HS‐SPME‐GC‐MS

Intelligent Evaluation and Dynamic Prediction of Oyster Freshness with Electronic Nose Based on the Distribution of Volatile Compounds Using GC-MS Analysis

The quality of oysters is reflected by volatile organic components. To rapidly assess the freshness level of oysters and elucidate the changes in flavor substances during storage, the volatile compounds of oysters stored at 4, 12, 20, and 28 °C over varying durations were analyzed using GC-MS and an electronic nose. Data from both GC-MS and electronic nose analyses revealed that alcohols, acids, and aldehydes are the primary contributors to the rancidity of oysters. Notably, the relative and absolute contents of Cis-2-(2-Pentenyl) furan and other heterocyclic compounds exhibited an upward trend. This observation suggests the potential for developing a simpler test for oyster freshness based on these compounds. Linear Discriminant Analysis (LDA) demonstrated superior performance compared to Principal Component Analysis (PCA) in differentiating oyster samples at various storage times. At 4 °C, the classification accuracy of the optimal support vector machine (SVM) and random forest (RF) models exceeded 90%. At 12 °C, 20 °C, and 28 °C, the classification accuracy of the best SVM and RF models surpassed 95%. Pearson correlation analysis of the concentrations of various volatile compounds and characteristic markers with the sensor response values indicated that the selected sensors were more aligned with the volatiles emitted by oysters. Consequently, the volatile compounds in oysters during storage can be predicted based on the response information from the sensors in the detection system. This study also demonstrates that the detection system serves as a viable alternative to GC-MS for evaluating oysters of varying freshness grades.

Key components, formation pathways, affecting factors, and emerging analytical strategies for edible mushrooms aroma: A review

Aroma is one of the decisive factors affecting the quality and consumer acceptance of edible mushrooms. This review summarized the key components and formation pathways of edible mushroom aroma. It also elaborated on the affecting factors and emerging analytical strategies of edible mushroom aroma. A total of 1308 volatile organic compounds identified in edible mushrooms, 61 were key components. The formation of these compounds is closely related to fatty acid metabolism, amino acid metabolism, lentinic acid metabolism, and terpenoid metabolism. The aroma profiles of edible mushrooms were affected by genetic background, preharvest factors, and preservation methods. Molecular sensory science and omics techniques are emerging analytical strategies to reveal aroma information of edible mushrooms. This review would provide valuable data and insights for future research on edible mushroom aroma.

Exploitation of microbial activities at low pH to enhance planetary health

Awareness is growing that human health cannot be considered in isolation but is inextricably woven with the health of the environment in which we live. It is, however, under-recognized that the sustainability of human activities strongly relies on preserving the equilibrium of the microbial communities living in/on/around us. Microbial metabolic activities are instrumental for production, functionalization, processing, and preservation of food. For circular economy, microbial metabolism would be exploited to produce building blocks for the chemical industry, to achieve effective crop protection, agri-food waste revalorization, or biofuel production, as well as in bioremediation and bioaugmentation of contaminated areas. Low pH is undoubtedly a key physical-chemical parameter that needs to be considered for exploiting the powerful microbial metabolic arsenal. Deviation from optimal pH conditions has profound effects on shaping the microbial communities responsible for carrying out essential processes. Furthermore, novel strategies to combat contaminations and infections by pathogens rely on microbial-derived acidic molecules that suppress/inhibit their growth. Herein, we present the state-of-the-art of the knowledge on the impact of acidic pH in many applied areas and how this knowledge can guide us to use the immense arsenal of microbial metabolic activities for their more impactful exploitation in a Planetary Health perspective.

Isolation, structures, bioactivities, application and future prospective for polysaccharides from Tremella aurantialba: A review

Since ancient times, Tremella aurantialba has been proposed to have medicinal and food benefits. Modern phytochemistry and pharmacological studies have demonstrated that polysaccharides, the main components from T. aurantialba appear to be an all-round talent resisting a variety of chronic inflammatory diseases and protecting against different types of tumors, diabetes and cardiovascular diseases. These health and pharmacological benefits have gained much attention from scholars around the world. Further, more and more methods for polysaccharides extraction, purification, structure identification have been proposed. Significantly, the bioactivity of fungus polysaccharides is affected by many factors such as extraction and purification conditions and chemical structure. This paper provides an overview of recent advances in the isolation, structural features and biological effects of polysaccharides derived from T. aurantialba, covers recent advances in the field and outlines future research and applications of these polysaccharides.

Evaluation of pharmacological activities and active components in Tremella aurantialba by instrumental and virtual analyses

As a kind of medicinal and edible homologous fungus, there is a lack of data on the medicinal value of Tremella aurantialba. In this study, ultra-performance liquid chromatography-quadrupole-time of flight-mass spectrometry (UPLC-Q-TOF/MS) was used to screen the chemical components in T. aurantialba. Then, network pharmacology was used to reveal the potential biological activities, active compounds, and therapeutic targets of T. aurantialba. Finally, the potential binding sites of the active compounds of T. aurantialba and key targets were studied by molecular docking. Results showed that 135 chemical components in T. aurantialba, especially linoleic acid, and linolenic acid have significant biological activities in neuroprotective, anticancer, immune, hypoglycemic, and cardiovascular aspects. The existence of these bioactive natural products in T. aurantialba is consistent with the traditional use of T. aurantialba. Moreover, the five diseases have comorbidity molecular mechanisms and therapeutic targets. The molecular docking showed that linolenic acid, adenosine, and vitamin D2 had higher binding energy with RXRA, MAPK1, and JUN, respectively. This study is the first to systematically identify chemical components in T. aurantialba and successfully predict its bioactivity, key active compounds, and drug targets, providing a reliable novel strategy for future research on the bioactivity development and utilization of T. aurantialba.

Comprehensive Flavor Analysis of Volatile Components During the Vase Period of Cut Lily (Lilium spp. 'Manissa') Flowers by HS-SPME/GC-MS Combined With E-Nose Technology

Volatile compounds could affect the flavor and ornamental quality of cut flowers, but the flavor change occurring during the vase period of the cut flower is unclear. To clarify the dynamic changes during the vase period of cut lily (Lilium spp. 'Manissa') flowers, comprehensive flavor profiles were characterized by the electronic nose (E-nose) and headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME/GC-MS). The response value of sensor W2W was significantly higher than other sensors, and its response value reached the highest on day 4. A total of 59 volatiles were detected in cut lilies by HS-SPME/GC-MS, mainly including aldehydes, alcohols, and esters. There were 19 volatiles with odor activity values (OAVs) greater than 1. Floral and fruity aromas were stronger, followed by a pungent scent. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) could effectively discriminate lily samples derived from different vase times on the basis of E-nose and HS-SPME-GC-MS. In summary, our study investigates the flavor change profile and the diversity of volatile compounds during the vase period of cut lilies, and lilies on day 4 after harvest exhibited excellent aroma and flavor taking into consideration of the flavor intensity and diversity. This provided theoretical guidance for the assessment of scent volatiles and flavor quality during the vase period of cut lily flowers and will be helpful for the application of cut lilies during the postharvest process.

Impact of Coffee Bean Roasting on the Content of Pyridines Determined by Analysis of Volatile Organic Compounds

The aim of the study was to analyze the process of roasting coffee beans in a convection-conduction roaster (CC) without a heat exchanger and a convection-conduction-radiation roaster (CCR) with a heat exchanger for determination of the aroma profile. The aroma profile was analyzed using the SPME/GC-MS technique, and an Agrinose electronic nose was used to determine the aroma profile intensity. Arabica coffee beans from five regions of the world, namely, Peru, Costa Rica, Ethiopia, Guatemala, and Brazil, were the research material. The chemometric analyses revealed the dominance of azines, alcohols, aldehydes, hydrazides, and acids in the coffee aroma profile. Their share distinguished the aroma profiles depending on the country of origin of the coffee beans. The high content of pyridine from the azine group was characteristic for the coffee roasting process in the convection-conduction roaster without a heat exchanger, which was shown by the PCA analysis. The increased content of pyridine resulted from the appearance of coal tar, especially in the CC roaster. Pyridine has an unpleasant and bitter plant-like odor, and its excess is detrimental to the human organism. The dominant and elevated content of pyridine is a defect of the coffee roasting process in the CC roaster compared to the process carried out in the CCR machine. The results obtained with the Agrinose showed that the CC roasting method had a significant effect on the sensor responses. The effect of coal tar on the coffee beans resulted in an undesirable aroma profile characterized by increased amounts of aromatic volatile compounds and higher responses of Agrinose sensors.

Nutritional Function and Flavor Evaluation of a New Soybean Beverage Based on Naematelia aurantialba Fermentation

The soy beverage is a healthy product rich in plant protein; however, its unpleasant flavor affects consumer acceptance. The aim of this study was to determine the feasibility of using Naematelia aurantialba as a strain for the preparation of fermented soybean beverages (FSB). Increases in Zeta potential, particle size, and viscosity make soy beverages more stable. We found that nutrient composition was increased by fermenting N. aurantialba, and the antioxidant activity of soybean beverages significantly increased after 5 days of fermentation. By reducing the content of beany substances such as hexanal and increasing the content of 1-octen-3-ol, the aroma of soybean beverages fermented by N. aurantialba changed from “beany, green, and fatty” to “mushroom and aromatic”. The resulting FSB had reduced bitterness but considerably increased sourness while maintaining the fresh and sweet taste of unfermented soybean beverages (UFSB). This study not only provides a theoretical basis for the market promotion of FSB but also provides a reference for basidiomycetes-fermented beverages.

Research advance in gas detection of volatile organic compounds released in rice quality deterioration process

Rice quality deterioration will cause grievous waste of stored grain and various food safety problems. Gas detection of volatile organic compounds (VOCs) produced by deterioration is a nondestructive detection method to judge rice quality and alleviate rice spoilage. This review discussed the research advance of VOCs detection in terms of nondestructive detection methods of rice quality deterioration, applications of VOCs in grain detection, inspection of characteristic gas produced during rice spoilage, rice deterioration prevention and control, and detection of VOCs released by rice mildew and insect attack. According to the main causes of rice quality deterioration and major sources of VOCs with off-odor generated during rice storage, deterioration can be divided into mold and insect infection. The results of literature manifested that researches mainly focused on the infection of Aspergillus in the mildew process and the attack of certain pests in recent years, thus the research scope was limited. In this paper, the gas detection methods combined with the chemometrics to qualitatively analyze the VOCs, as well as the correlation with the number of colonies and insects were further studied based on the common dominant strains during rice mildew, that is, Aspergillus and Penicillium fungi, and the common pests during storage, that is, Sitophilus oryzae and Rhyzopertha dominica. Furthermore, this paper pointed out that the quantitative determination of characteristic VOCs, the numeration relationship between VOCs and the degree of mildew and insect infestation, the further expansion of detection range, and the application of degraded rice should be the spotlight of future research.

Classification and Identification of Essential Oils from Herbs and Fruits Based on a MOS Electronic-Nose Technology

The frequent occurrence of adulterated or counterfeit plant products sold in worldwide commercial markets has created the necessity to validate the authenticity of natural plant-derived palatable products, based on product-label composition, to certify pricing values and for regulatory quality control (QC). The necessity to confirm product authenticity before marketing has required the need for rapid-sensing, electronic devices capable of quickly evaluating plant product quality by easily measurable volatile (aroma) emissions. An experimental MAU-9 electronic nose (e-nose) system, containing a sensor array with 9 metal oxide semiconductor (MOS) gas sensors, was developed with capabilities to quickly identify and classify volatile essential oils derived from fruit and herbal edible-plant sources. The e-nose instrument was tested for efficacy to discriminate between different volatile essential oils present in gaseous emissions from purified sources of these natural food products. Several chemometric data-analysis methods, including pattern recognition algorithms, principal component analysis (PCA), and support vector machine (SVM) were utilized and compared. The classification accuracy of essential oils using PCA, LDA and QDA, and SVM methods was at or near 100%. The MAU-9 e-nose effectively distinguished between different purified essential oil aromas from herbal and fruit plant sources, based on unique e-nose sensor array responses to distinct, essential-oil specific mixtures of volatile organic compounds (VOCs).

Monitoring microstructural changes and moisture distribution of dry-cured pork: a combined confocal laser scanning microscopy and hyperspectral imaging study

BACKGROUND

Various spectral profiles, including reflectance, absorbance, and Kubelka-Munk spectra, have been derived from hyperspectral images and used to develop multivariate models to evaluate changes in the quality of meat and meat products as a function of processing. However, none of these has the capacity to produce images of the structural changes often associated with processing. This study explored the feasibility of combining hyperspectral imaging (HSI) with confocal laser scanning microscopy (CLSM) to examine the impact of processing on microstructural changes and the evolution of moisture. Reflectance spectra features were obtained and transformed into absorbance and Kubelka-Munk spectra and their ability to predict moisture content using models established on partial least-squares regression were evaluated.

RESULTS

The partial least-squares regression model (full-band wavelength) dubbed Rs-MSC yielded the best result, with R c 2 = 0.967 , RMSEC = 0.127, R cv 2 = 0.949 , RMSECV = 0.418, R p 2 = 0.937 , RMSEP = 0.824. Next, a total of 16 optimum wavelengths were selected using the competitive adaptive reweighted sampling algorithm. These wavelengths also yielded good results for Rs-MSC, with R c 2 = 0.958 , RMSEC = 0.840, R cv 2 = 0.931 , RMSECV = 0.118, R p 2 = 0.926 , RMSEP = 0.121. Regarding moisture distribution and microstructure analysis, HSI and CLSM were able to reveal moisture content distribution and conformational differences in microstructure in the test samples.

CONCLUSION

Using HSI in synergy with CLSM may offer a reliable means for assessing both the chemical and structural changes that occur in other congener food products during processing. © 2020 Society of Chemical Industry.

Application of volatile and spectral profiling together with multimode data fusion strategy for the discrimination of preserved eggs

The maturity level of eggs during pickling is conventionally assessed by choosing few eggs from each curing batch to crack open. Yet, this method is destructive, creates waste and has consequences for financial losses. In this work, the feasibility of integrating electronic nose (EN) with reflectance hyperspectral (RH) and transmittance hyperspectral (TH) data for accurate classification of preserved eggs (PEs) at different maturation periods was investigated. Classifier models based solely on RH and TH with EN achieved a training accuracy (93.33%, 97.78%) and prediction accuracy (88.89%; 93.33%) respectively. The fusion of the three datasets, (EN + RH + TH) as a single classifier model yielded an overall training accuracy of 98.89% and prediction accuracy of 95.56%. Also, 52 volatile compounds were obtained from the PE headspace, of which 32 belonged to seven functional groups. This study demonstrates the ability to integrate EN with RH and TH data to effectively identify PEs during processing.

Discrimination of five brands of instant vermicelli seasonings by HS-SPME/GC-MS and electronic nose

The flavor profile of five brands of instant vermicelli seasonings were identified by headspace solid-phase micro-extraction coupled with gas chromatography-mass spectrometry (HS-SPME/GC-MS) and electronic nose (e-nose). GC-MS showed that the volatile compounds of instant vermicelli seasonings were significantly different. Alkenes, alcohols, aldehydes and ketones were the major volatile compounds in instant vermicelli seasonings. The seasonings could be classified based on differences in volatile compounds. The overall volatiles profiles were also analyzed by e-nose. E-nose determination and GC-MS statistical analysis had similar results. The volatile compounds showed good correlation with e-nose sensors according to partial least square regression models. Both methods had good potential application in evaluating flavor quality and differentiating among instant vermicelli seasonings.

Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics

It is crucial for the efficacy of the apple storage to apply methods like electronic nose systems for detection and prediction of spoilage or infection by Penicillium expansum. Based on the acquisition of electronic nose signals, selected sensitive feature sensors of spoilage apple and all sensors were analyzed and compared by the recognition effect. Principal component analysis (PCA), principle component analysis-discriminant analysis (PCA-DA), linear discriminant analysis (LDA), partial least squares discriminate analysis (PLS-DA) and K-nearest neighbor (KNN) were used to establish the classification model of apple with different degrees of corruption. PCA-DA has the best prediction, the accuracy of training set and prediction set was 100% and 97.22%, respectively. synergy interval (SI), genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) are three selection methods used to accurately and quickly extract appropriate feature variables, while constructing a PLS model to predict plaque area. Among them, the PLS model with unique variables was optimized by CARS method, and the best prediction result of the area of the rotten apple was obtained. The best results are as follows: Rc = 0.953, root mean square error of calibration (RMSEC) = 1.28, Rp = 0.972, root mean square error of prediction (RMSEP) = 1.01. The results demonstrated that the electronic nose has a potential application in the classification of rotten apples and the quantitative detection of spoilage area.

Classification of Chinese vinegar varieties using electronic nose and fuzzy Foley-Sammon transformation

Due to the difference of raw materials and brewing technology, the quality and flavours of vinegar are different. Different kinds of vinegar have different functions and effects. Therefore, it is important to classify the vinegar varieties correctly. This work presented a new fuzzy feature extraction algorithm, called fuzzy Foley-Sammon transformation (FFST), and designed the electronic nose (E-nose) system for classifying vinegar varieties successfully. Principal component analysis (PCA) and standard normal variate (SNV) were used as the data preprocessing algorithms for the E-nose system. FFST, Foley-Sammon transformation (FST) and linear discriminant analysis (LDA) were used to extract discriminant information from E-nose data, respectively. Then, K nearest neighbor (KNN) served as a classifier for the classification of vinegar varieties. The highest identification accuracy rate was 96.92% by using the FFST and KNN. Therefore, the E-nose system combined with the FFST was an effective method to identify Chinese vinegar varieties and this method has wide application prospects.

Antitumor, Antiviral, and Anti-Inflammatory Efficacy of Essential Oils from Atractylodes macrocephala Koidz. Produced with Different Processing Methods

Atractylodes macrocephala Koidz. has been used as an invigorating spleen drug for eliminating dampness and phlegm in China. According to recent researches, different processing methods may affect the drug efficacy, so we collected A. macrocephala from the Zhejiang Province, produced with different processing methods, crude A. macrocephala (CA) and bran-processed A. macrocephala (BA), then analyzed its essential oils (EOs) by GC/MS. The results showed 34 components representing 98.44% of the total EOs of CA were identified, and 46 components representing 98.02% of the total EOs of BA were identified. Atractylone is the main component in A. macrocephala. Compared with CA, BA has 46 detected compounds, 28 of which were identical, and 6 undetected compounds. Pharmacodynamic results revealed that the EOs of CA and atractylone exhibited more effective anticancer activity in HepG2, MCG803, and HCT-116 cells than the EOs of BA; while the EOs of BA exhibited simple antiviral effect on viruses H3N2, both the EOs and atractylone show anti-inflammatory activity by inhibiting the lipopolysaccharide (LPS)-induced nitric oxide (NO) production in ANA-1 cells.