Physicochemical parameters combined flash GC e-nose and artificial neural network for quality and volatile characterization of vinegar with different brewing techniques

Machine Learning Driven Atom-Thin Materials for Fragrance Sensing

Fragrance plays a crucial role in the daily lives. Its importance spans various sectors, from therapeutic purposes to personal care, making the understanding and accurate identification of fragrances essential. To fully harness the potential of fragrances, efficient and precise fragrance sensing and identification are necessary. However, current fragrance sensors face several limitations, particularly in detecting and differentiating complex scent profiles with high accuracy. To address these challenges, the use of atom-thin materials in fragrance sensors has emerged as a groundbreaking approach. These atom-thin sensors, characterized by their enhanced sensitivity and selectivity, offer significant improvements over traditional sensing technology. Moreover, the integration of Machine Learning (ML) into fragrance sensing has opened new opportunities in the field. ML algorithms applied to fragrance sensing facilitate advancements in four key domains: accurate fragrance identification, precise discrimination between different fragrances, improved detection thresholds for subtle scents, and prediction of fragrance properties. This comprehensive review delves into the synergistic use of atom-thin materials and ML in fragrance sensing, providing an in-depth analysis of how these technologies are revolutionizing the field, offering insights into their current applications and future potential in enhancing the understanding and utilization of fragrances.

Discrimination between raw and ginger juice processed Fructus Gardeniae based on UHPLC-Q-TOF-MS and Heracles NEO ultra-fast gas phase electronic nose

INTRODUCTION

Fructus Gardeniae (ZZ), a traditional Chinese herb, has been used in treating patients with jaundice, inflammation, etc. When mixed with ginger juice and stir-baked, ginger juice-processed Fructus Gardeniae (JZZ) is produced, and the chemical compositions in ZZ would be changed by adding the ginger juice.

OBJECTIVE

To illuminate the differential components between ZZ and JZZ.

METHODS

HPLC, UHPLC-Q-TOF-MS, and Heracles NEO ultra-fast gas phase electronic nose were applied to identify the differential components between ZZ and JZZ.

RESULTS

HPLC fingerprints of ZZ and JZZ were established, and 24 common peaks were found. The content determination results showed that the contents of shanzhiside, geniposidic acid, genipin-1-β-D-gentiobioside and geniposide increased, while the contents of crocin I and crocin II decreased in JZZ. By UHPLC-Q-TOF-MS, twenty-six possible common components were inferred, among which 11 components were different. In further investigation, eight components were identified as the possible distinctive non-volatile compounds between ZZ and JZZ. By Heracles NEO ultra-fast gas phase electronic nose, four substances were inferred as the possible distinctive volatile compounds in JZZ.

CONCLUSION

Shanzhiside, caffeic acid, genipin-1-β-D-gentiobioside, geniposide, rutin, crocin I, crocin II, and 4-Sinapoyl-5-caffeoylquinic acid were identified as the possible differential non-volatile components between ZZ and JZZ. Aniline, 3-methyl-3-sulfanylbutanol-1-ol, E-3-octen-2-one, and decyl propaonate were inferred as the possible distinctive volatile compounds in JZZ. This experiment explored a simple approach with objective and stable results, which would provide new ideas for studying decoction pieces with similar morphological appearance, especially those with different odors.

Volatilome and flavor analyses based on e-nose combined with HS-GC-MS provide new insights into ploidy germplasm diversity in Platostoma palustre

Platostoma palustre (Mesona chinensis Benth or Hsian-tsao, also known as "Xiancao" in China), is an edible and medicinal plant native to India, Myanmar, and Indo-China. It is the main ingredient in the popular desserts Hsian-tsao tea, herbal jelly, and sweet herbal jelly soup. P. palustre is found abundantly in nutrient-rich substances and possesses unique aroma compounds. Variations in the contents of volatile compounds among different germplasms significantly affect the quality and flavor of P. palustre, causing contradiction in demand. This study investigates the variation in the volatile compound profiles of distinct ploidy germplasms of P. palustre by utilising headspace gas chromatography-mass spectrometry (HS-GC-MS) and an electronic nose (e-nose). The results showed significant differences in the aroma characteristics of stem and leaf samples in diverse P. palustre germplasms. A total of sixty-seven volatile compounds have been identified and divided into ten classes. Six volatile compounds (caryophyllene, α-bisabolol, benzaldehyde, β-selinene, β-elemene and acetic acid) were screened as potential marker volatile compounds to discriminate stems and leaves of P. palustre. In this study, leaves of P. palustre showed one odor pattern and stems showed two odor patterns under the influence of α-bisabolol, acetic acid, and butyrolactone. In addition, a correlation analysis was conducted on the main volatile compounds identified by HS-GC-MS and e-nose. This analysis provided additional insight into the variations among samples resulting from diverse germplasms. The present study provides a valuable volatilome, and flavor, and quality evaluation for P. palustre, as well as new insights and scientific basis for the development and use of P. palustre germplasm resources.

Application of flash GC e-nose and FT-NIR combined with deep learning algorithm in preventing age fraud and quality evaluation of pericarpium citri reticulatae

Pericarpium citri reticulatae (PCR) is the dried mature fruit peel of Citrus reticulata Blanco and its cultivated varieties in the Brassicaceae family. It can be used as both food and medicine, and has the effect of relieving cough and phlegm, and promoting digestion. The smell and medicinal properties of PCR are aged over the years; only varieties with aging value can be called "Chenpi". That is to say, the storage year of PCR has a great influence on its quality. As the color and smell of PCR of different storage years are similar, some unscrupulous merchants often use PCRs of low years to pretend to be PCRs of high years, and make huge profits. Therefore, we did this study with the aim of establishing a rapid and nondestructive method to identify the counterfeiting of PCR storage year, so as to protect the legitimate rights and interests of consumers. In this study, a classification model of PCR was established by e-eye, flash GC e-nose, and Fourier transform near-infrared (FT-NIR) combined with machine learning algorithms, which can quickly and accurately distinguish PCRs of different storage years. DFA and PLS-DA models were established by flash GC e-nose to distinguish PCRs of different ages, and 8 odor components were identified, among which (+)-limonene and γ-terpinene were the key components to distinguish PCRs of different ages. In addition, the classification and calibration model of PCRs were established by the combination of FT-NIR and machine learning algorithms. The classification models included SVM, KNN, LSTM, and CNN-LSTM, while the calibration models included PLSR, LSTM, and CNN-LSTM. Among them, the CNN-LSTM model built by internal capsule had significantly better classification and calibration performance than the other models. The accuracy of the classification model was 98.21 %. The R2P of age, (+)-limonene and γ-terpinene was 0.9912, 0.9875 and 0.9891, respectively. These results showed that the combination of flash GC e-nose and FT-NIR combined with deep learning algorithm could quickly and accurately distinguish PCRs of different ages. It also provided an effective and reliable method to monitor the quality of PCR in the market.

A study of volatiles of young citrus fruits from four areas based on GC-MS and flash GC e-nose combined with multivariate algorithms

The present study has successfully established a scientific and precise approach for distinguishing the geographical origins of young citrus fruits (Qingpi) from four primary production regions in China, using gas chromatography-mass spectrometry (GC-MS) and flash gas chromatography electronic nose (flash GC e-nose) to analyze the volatile composition and odor characteristics. Through the application of chemometric analysis, a clear differentiation among Qingpi samples was established using GC-MS. Additionally, the application of flash GC e-nose facilitated the extraction of flavor information, which enabled the discrimination of geographical origins. Several flavor components were identified as significant factors for origin certification. Furthermore, two pattern recognition algorithms were employed to achieve high accuracy in regional identification. The results of this investigation demonstrate that the amalgamation of multivariate chemometrics and algorithms can proficiently discern the sources of those young citrus fruits. The findings of this research can provide a reference for the assessment of quality control in food and other agricultural commodities in the times ahead.

Correlations between flavor and fermentation days and changes in quality-related physiochemical characteristics of fermented Aurantii Fructus

The effects of different fermentation times (0, 1, 2, 3, 4, and 5 days) on the physicochemical properties and flavor components of fermented Aurantii Fructus (FAF) were evaluated. Component analysis identified 66 compounds in positive ion mode and 32 compounds in negative ion mode. Flash GC e-nose results showed that propanal, (+)-limonene and n-nonanal may be the flavor characteristic components that distinguish FAF with different fermentation days. Furthermore, we found that the change of total flavonoid content was closely related to colony growth vitality. The total flavonoid content of FAF gradually decreased from 3rd day and then increased from 5th day (3rd day: 0.766 ± 0.123 mg/100 g; 4th day: 0.464 ± 0.001 mg/100 g; 5th day: 0.850 ± 0.192 mg/100 g). Finally, according to antioxidant activity correlation analysis, meranzin, (+)-limonene and total flavonoids were found to be the key substances affecting the fermentation days of FAF. Overall, the optimal fermentation time for FAF was 4 days.

Volatile Fingerprint and Differences in Volatile Compounds of Different Foxtail Millet (Setaria italica Beauv.) Varieties

Aroma components in foxtail millet are one of the key factors in origin traceability and quality control, and they are associated with consumer acceptance and the corresponding processing suitability. However, the volatile differences based on the foxtail millet varieties have not been studied further. The present study was undertaken to develop the characteristic volatile fingerprint and analyze the differences in volatile compounds of 20 foxtail millet varieties by electronic nose (E-Nose), headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), and headspace solid-phase microextraction/gas chromatography-mass spectrometry (HS-SPME/GC-MS). A total of 43 volatile compounds were tentatively identified in foxtail millet samples, 34 and 18 by GC-IMS and GC-MS, respectively. Aldehydes, alcohols, and ketones were the major volatile compounds, and the hexanal content was the highest. The characteristic volatile fingerprint of foxtail millet was successfully constructed. A total of 39 common volatile compounds were found in all varieties. The content of hexanal, heptanal, 1-pentanol, acetophenone, 2-heptanone, and nonanal were explored to explain the aroma characteristics among the different varieties, and different varieties can be separated based on these components. The results demonstrate that the combination of E-Nose, GC-IMS, and GC-MS can be a fast and accurate method to identify the general aroma peculiarities of different foxtail millet varieties.

Comparative study on Angelica sinensis after different processing with yellow rice wine in color, aromas, chemical components, and antioxidant activities

This study aimed to explore the differences in raw Angelica Sinensis (RAS), wine washing AS (WAS), and wine stir-frying AS (WSAS). The results showed there were differences among the three AS in color and aroma, and 34 aroma compounds were identified. The content determination results revealed the ferulic acid and Z-ligustilide levels of RAS decreased after processing, and those in WAS were higher than in WSAS. Furthermore, 85 representative common components and 37 unique components were tentatively identified in three AS. Finally, the free radical scavenging assay results indicated the antioxidant capacity of RAS was reduced after processing, and the antioxidant capacity of WAS was better than WSAS. Collectively, the RAS undergoes significant changes in color, aromas, components, and antioxidant ability after processing, and the different processing methods also result in significant differences between WAS and WSAS.

Correlation between physicochemical properties and volatile compound profiles in tilapia muscles subjected to four different thermal processing techniques

This work studied the physicochemical properties and odor profiles of tilapia muscles after exposure to four types of thermal processing methods: microwaving, roasting, boiling, or steaming. The effect of thermal processing on textural properties followed a pH-water state-water content-tissue microstructure-mass loss-textural properties route, expressed in the following manner: microwaving > roasting > steaming ≈ boiling. After processing, muscle pH increased from 6.59 ± 0.10 to 6.73 ± 0.04-7.01 ± 0.06, and hardness changed from 1468.49 ± 180.77 g to 452.76 ± 46.94-10723.66 ± 2898.46 g. Gas chromatography-based E-nose analysis confirmed that these methods had significant odor fingerprint effects on the tilapia muscles. Finally, the combined analysis of headspace solid-phase microextraction-gas chromatography-mass spectrometry, statistical MetaboAnalyst, and odor activity value showed that the microwaved, roasted, steamed, and boiled tilapia muscles had, respectively, three (hexanal, nonanal, and decanal), four (2-methyl-butanal, 3-methyl-butanal, decanal, and trimethylamine), one (2-methyl-butanal), and one (decanal) relatively important volatile compounds.

Characterization of volatile metabolites in Pu-erh teas with different storage years by combining GC-E-Nose, GC-MS, and GC-IMS

Storage time is one of the important factors affecting the aroma quality of Pu-erh tea. In this study, the dynamic changes of volatile profiles of Pu-erh teas stored for different years were investigated by combining gas chromatography electronic nose (GC-E-Nose), gas chromatography-mass spectrometry (GC-MS), and gas chromatography-ion mobility spectrometry (GC-IMS). GC-E-Nose combined with partial least squares-discriminant analysis (PLS-DA) realized the rapid discrimination of Pu-erh tea with different storage time (R2Y = 0.992, Q2 = 0.968). There were 43 and 91 volatile compounds identified by GC-MS and GC-IMS, respectively. A satisfactory discrimination (R2Y = 0.991, and Q2 = 0.966) was achieved by using PLS-DA based on the volatile fingerprints of GC-IMS. Moreover, according to the multivariate analysis of VIP > 1.2 and univariate analysis of p < 0.05, 9 volatile components such as linalool and (E)-2-hexenal were selected as key variables to distinguish Pu-erh teas with different storage years. The results provide theoretical support for the quality control of Pu-erh tea.

E-eye, flash GC E-nose and HS-GC-MS combined with chemometrics to identify the adulterants and geographical origins of Ziziphi Spinosae Semen

Ziziphi Spinosae Semen (ZSS), a valuable seed food, has faced increasing authenticity issues. In this study, the adulterants and geographical origins of ZSS were successfully identified by electronic eye, flash gas chromatography electronic nose (Flash GC e-nose) and headspace gas chromatography-mass spectrometry (HS-GC-MS). As a result, there were color differences between ZSS and adulterants, mainly represented by the a* value of ZSS was less than adulterants. In ZSS, 29 and 32 compounds were detected by Flash GC e-nose and HS-GC-MS. Spicy, sweety, fruity and herbal were the main flavor of ZSS. Five compounds were determined to be responsible for flavor differences between different geographical origins. In the HS-GC-MS analysis, the relative content of Hexanoic acid was the highest in ZSS from Hebei and Shandong, while 2,4-Decadien-1-ol was the highest in Shaanxi. Overall, this study provided a meaningful strategy for addressing authenticity problems of ZSS and other seed foods.

Characterization and intrinsic quality correlation of raw and vinegar-processed Curcumae Radix

Among the existing criteria, the traits of Curcumae Radix (CW) rely on traditional empirical identification, and the correlation between extrinsic traits and intrinsic components hasn't been systematically studied. In this study, a spectrophotometer, HS-GC-MS, and fast GC e-nose, combined with chemometrics were used to correlate the trait characteristics and intrinsic qualities of CW and vinegar-processed CW (VCW). The overall color of VCW was dark, red, and yellow, but the powder color was similar and difficult to distinguish with the naked eye. The exclusive discriminatory functional equations were established for the characterization between the two. 31 odor components were identified by fast GC e-nose. After vinegar preparation, 3 odor components disappeared and 8 odor components were generated. In addition, there were significant differences between the common components. 27 volatile components were identified by HS-GC-MS, 21 of which were terpenoids. Meanwhile, the difference discrimination models could be used for the rapid and accurate identification of CW and VCW. Through the comprehensive analysis of the color-odor-component, it was speculated that curzerene, germacrene D, and germacrone were potential chemical markers. The quality evaluation model based on the color-odor-composition of trait characteristics combined with internal components provided a basis for rapid identification and quality control of CW and VCW.

Evaluation of vegetable sauerkraut quality during storage based on convolution neural network

Vegetable sauerkraut is a traditional fermented food. Due to oxidation reactions that occur during storage, the quality and flavor in different periods will change. In this study, the quality evaluation and flavor characteristics of 13 groups of vegetable sauerkraut samples with different storage time were analyzed by using physical and chemical parameters combined with electronic nose. Photographs of samples of various periods were collected, and a convolutional neural network (CNN) framework was established. The relationship between total phenol oxidative decomposition and flavor compounds was linearly negatively correlated. The vegetable sauerkraut during storage can be divided into three categories (full acceptance period, acceptance period and unacceptance period) by principal component analysis and Fisher discriminant analysis. The CNN parameters were fine-tuned based on the classification results, and its output results can reflect the quality changes and flavor characteristics of the samples, and have better fitting, prediction capabilities. After 50 epochs of the model, the accuracy of three sets of data namely training set, validation set and test set recorded 94%, 85% and 93%, respectively. In addition, the accuracy of CNN in identifying different quality sauerkraut was 95.30%. It is proved that the convolutional neural network has excellent performance in predicting the quality of Szechuan Sauerkraut with high reliability.

Variations in volatile flavour compounds in Crataegi fructus roasting revealed by E-nose and HS-GC-MS

Introduction

Crataegi fructus (CF) is an edible and medicinal functional food used worldwide that enhances digestion if consumed in the roasted form. The odour of CF, as a measure of processing degree during roasting, significantly changes. However, the changes remain unclear, but are worth exploring.

Methods

Herein, the variations in volatile flavour compounds due to CF roasting were investigated using an electronic nose (E-nose) and headspace gas chromatography-mass spectrometry (HS-GC-MS).

Results

A total of 54 components were identified by GC-MS. Aldehydes, ketones, esters, and furans showed the most significant changes. The Maillard reaction, Strecker degradation, and fatty acid oxidation and degradation are the main reactions that occur during roasting. The results of grey relational analysis (GRA) showed that 25 volatile compounds were closely related to odour (r > 0.9). Finally, 9 volatile components [relative odour activity value, (ROAV) ≥ 1] were confirmed as key substances causing odour changes.

Discussion

This study not only achieves the objectification of odour evaluation during food processing, but also verifies the applicability and similarity of the E-nose and HS-GC-MS.

FT-IR combined with chemometrics in the quality evaluation of Nongxiangxing baijiu

Recently, there has been an increasing demand for developing a reliable method to assess the quality of liquor in the baijiu industry quickly and accurately. The present study sought to establish a strategy for rapid quantitative analysis of the primary flavor components in Nongxiangxing baijiu. Under the experimental conditions, 7 of the 10 major flavor components in Nongxiangxing baijiu could be quantified effectively, such as ethyl butyrate (R²p = 0.9942), ethyl lactate (R²p = 0.9438), n-butanol (R²p = 0.9048), isobutanol (R²p = 0.9696), acetic acid (R²p = 0.9600), butyric acid (R²p = 0.8448), caproic acid (R²p = 0.9971). This result indicates that FT-IR combined with quantitative chemometric modeling could be a potential approach for rapid quality assessment of Nongxiangxing baijiu. Overall, this study provides a theoretical basis for subsequent related studies on Nongxiangxing baijiu.

Headspace GC/MS and fast GC e-nose combined with chemometric analysis to identify the varieties and geographical origins of ginger (Zingiber officinale Roscoe)

Food authenticity regarding different varieties and geographical origins is increasingly becoming a concern for consumers. In this study, headspace gas chromatography-mass spectrometry (HS-GC-MS) and fast gas chromatography electronic nose (fast GC e-nose) were used to successfully distinguish the varieties and geographical origins of dried gingers from seven major production areas in China. By chemometric analysis, a distinct separation between the two varieties of ginger was achieved based on HS-GC-MS. Furthermore, flavor information extracted by fast GC e-nose realized the discrimination of geographical origins, and some potential flavor components were selected as important factors for origin certification. Moreover, several pattern recognition algorithms were compared in varietal and regional identification, and random forest (RF) led to the highest accuracies for discrimination. Overall, a rapid and precise method combining multivariate chemometrics and algorithms was developed to determine varieties and geographical origins of ginger, and it could also be applied to other agricultural products.

Early Discrimination and Prediction of C. fimbriata-Infected Sweetpotatoes during the Asymptomatic Period Using Electronic Nose

Sweetpotato is prone to disease caused by C. fimbriata without obvious lesions on the surface in the early period of infection. Therefore, it is necessary to explore the possibility of developing an efficient early disease detection method for sweetpotatoes that can be used before symptoms are observed. In this study, sweetpotatoes were inoculated with C. fimbriata and stored for different lengths of time. The total colony count was detected every 8 h; HS-SPME/GC–MS and E-nose were used simultaneously to detect volatile compounds. The results indicated that the growth of C. fimbriata entered the exponential phase at 48 h, resulting in significant differences in concentrations of volatile compounds in infected sweetpotatoes at different times, especially toxic ipomeamarone in ketones. The contents of volatile compounds were related to the responses of the sensors. E-nose was combined with multiple chemometrics methods to discriminate and predict infected sweetpotatoes at 0 h, 48 h, 64 h, and 72 h. Among the methods used, linear discriminant analysis (LDA) had the best discriminant effect, with sensitivity, specificity, precision, and accuracy scores of 100%. E-nose combined with K-nearest neighbours (KNN) achieved the best predictions for ipomeamarone contents and total colony counts. This study illustrates that E-nose is a feasible and promising technology for the early detection of C. fimbriata infection in sweetpotatoes during the asymptomatic period.

Comparison of Different Drying Methods on the Volatile Components of Ginger (Zingiber officinale Roscoe) by HS-GC-MS Coupled with Fast GC E-Nose

Ginger (Zingiber officinale Roscoe) is one of the most popular spices in the world, with its unique odor. Due to its health benefits, ginger is also widely used as a dietary supplement and herbal medicine. In this study, the main flavor components of gingers processed by different drying methods including hot air drying, vacuum drying, sun-drying, and vacuum-freeze drying, were identified on the basis of headspace-gas chromatography coupled with mass spectrometry (HS-GC-MS) and fast gas chromatography electronic-nose (fast GC e-nose) techniques. The results showed that the ginger dried by hot air drying exhibited high contents of volatile compounds and retained the richest odor in comparison with those dried by other methods, which indicated that hot air drying is more suitable for the production of dried ginger. Sensory description by fast GC e-nose exhibited that ginger flavor was mainly concentrated in the spicy, sweet, minty, fruity, and herbaceous odor. The relative content of the zingiberene was significantly higher in the hot air drying sample than those by other methods, suggesting that dried ginger by hot air drying can retain more unique spicy and pungent odorants. Furthermore, the results of chemometrics analyses showed that the main variance components among the samples by different drying methods were α-naginatene, (+)-cyclosativene, and sulcatone in HS-GC-MS analysis, and α-terpinen-7-al, dimethyl sulfide, and citronellal in fast GC e-nose analysis. For comparison of fresh and dried gingers, terpinolene, terpinen-4-ol, 2,4-decadienal, (E, Z)-, and linalool were considered the main variance components. This study generated a better understanding of the flavor characteristics of gingers by different drying methods and could provide a guide for drying and processing of ginger.