Potential geo-discriminative tools to trace the origins of the dried slices of shiitake (Lentinula edodes) using stable isotope ratios and OPLS-DA

Combining stable isotopes and multi-elements with machine learning chemometric models to identify the geographical origins of Tetrastigma hemsleyanum Diels et Gilg

Tetrastigma hemsleyanum Diels et Gilg (T. hemsleyanum) is an edible plant with considerable medicinal properties, the quality of which varies depending on its origin. Therefore economically motivated adulteration has emerged. So there is an urgent need to develop effective techniques for determining the origin of T. hemsleyanum. This study combined stable isotopes and multiple elements with machine learning chemometric models (SVM, RF and FNN models) for T. hemsleyanum origin traceability. The results showed that this approach successfully distinguished T. hemsleyanum form different regions with the SVM, RF and FNN models all displaying a 100 % prediction accuracy and the FNN model exhibiting superior performance. This study provides a technical and theoretical basis for research on the origin traceability of T. hemsleyanum.

Isotope Ratio Mass Spectrometry (IRMS)-Based Authentication of the Geographic Origins of Volvariella volvacea (Bull.) Singer

The growing consumption of Volvariella volvacea has heightened concerns regarding its geographical authenticity. This study analyzed the proteins, 16 common amino acids, and 10 mineral elements (Ca, Cu, Fe, K, Mn, Mg, Na, Se, Sr, Zn) in samples from Fujian, Guangdong, Hubei, Jiangsu, Jiangxi, Shanghai, and Zhejiang, China, along with regional variations in stable isotope ratios. PCA and PLS-DA were applied for origin authentication. The results showed an average protein content of approximately 30 g/100 g (dry basis), with Guangdong samples being the highest. Amino acids exhibited significant regional differences, but the total essential amino acid and total amino acid contents did not. Mineral elements varied significantly by region, except for Cu and K. The Fujian, Hubei, Jiangxi, and Zhejiang samples exhibited significantly higher δ13C and δ15N values, while Shanghai samples had significantly higher δ2H and δ18O values. These differences enabled PCA to classify the samples into two groups: FHJZ (Fujian, Hubei, Jiangxi, Zhejiang) and GJS (Guangdong, Jiangsu, Shanghai). The PLS-DA model achieved 93.60% accuracy in distinguishing these two groups. Pairwise accuracy within the GJS group exceeded 80%, whereas that within the FHJZ group requires further improvement. These findings support the feasibility of stable isotope analysis for authenticating the geographical origin of Volvariella volvacea.

Optimizing geographical traceability models of Chinese Lycium barbarum: Investigating effects of region, cultivar, and harvest year on nutrients, bioactives, elements and stable isotope composition

Lycium barbarum is a type of "medicine-food homology" whose geographical origin has attracted strong interest from consumers due to different regional quality characteristics. A sophisticated OPLS-DA model to verify Lycium barbarum origin was developed using 266 samples gathered from five cultivars in two regions between 2020 and 2022, which was based on 67 indices, including nutrients, bioactives, elements and stable isotopes. Twelve variables (fructose, δ2H, glucose, tartaric acid, Mo, Na, Sr, His, Phe, Mn, Lys and Rb) were selected to refine models that could distinguish Lycium barbarum origin without being impacted by cultivar or year. The model of training set and testing set samples had discrimination rates of 100 % and 94.71 % to 98.28 %, suggesting an optimized multi-variate analysis strategy using OPLS-DA model could correctly predict the origin of blind Lycium barbarum samples. This study provides new evidence for constructing a reliable traceability model for the geographical origins of Lycium barbarum.

Chemical analysis of different parts from agarwood columns by artificially agarwood-inducing method based on GC-MS and UPLC-TOF-MS

Agarwood is resin-containing wood produced by plants that have been injured. It is widely used in herbal medicine, incense, decorative items, and so on. In this study, we conducted resin area statistical analysis, determined starch particle and reducing sugar contents, and performed multivariate statistical analysis of chemical composition by GC-MS and UPLC-Q-TOF-MS to explore the different components in sections cut from an agarwood column, designated as A1-A4. The results showed that after stimulation by Agar-Bit inducer, the internal phloem parenchyma cells of the column started to form agarwood, and then starch granules were converted into soluble reducing sugars and agarwood resin. Section A1 showed rapid loss of starch granules, resulting in higher contents of reducing sugars and resin. The resin areas of agarwood in the respective sections were different, gradually decreasing on going from A1 to A4. Total numbers of metabolites of 87 and 63 were identified by GC-MS and UPLC-Q-TOF-MS, respectively. Of these, 10 and 16 metabolites with significant differences (variable importance projection >1) were selected through multivariate statistical analysis. These metabolites included chromones, sesquiterpenes, alkanes, and fatty acids. Among them, 6-methoxy-2-(2-phenylethyl)chromone and 6,7-dimethoxy-2-(2-phenylethyl)chromone were significant markers detected by both GC-MS and UPLC-Q-TOF-MS, which may be essential substances responsible for differences in the agarwood-forming capacities of the cut sections. In conclusion, there has been limited research on the different agarwood-forming capacities of agarwood columns. Here, we explored the differences in various sections of agarwood through chemical analysis to provide a more comprehensive and in-depth understanding of its constitution.

Influence of electrohydrodynamics on the drying characteristics, microstructure and volatile composition of apricot abalone mushroom (Pleurotus eryngii)

The study explored the use of current fluid dynamics drying technology for apricot abalone mushroom, examining how different output voltages (15, 25, and 35 kV) affected drying characteristics, microstructure, and volatile components. Comparisons were made with samples dried using hot air drying (HAD) and natural air drying (AD). Results revealed that HAD had the fastest drying rate at 0.29664(g·h-1). However, apricot abalone mushroom treated with electrohydrodynamic drying (EHD) maintained a color closer to fresh samples, exhibited a 21% increase in the ordered structure of protein secondary structure, a 12.5-fold increase in bound water content, and the most stable cell structure compared to HAD and AD treatments. A total of 83 volatile organic compounds were identified in the apricot abalone mushroom, with alcohols and aldehydes being the most prominent in terms of threshold and relative content, peaking in the 35 kV treatment group. These findings provide both experimental and theoretical insights into applying current fluid dynamics for drying apricot abalone mushroom.

Machine Learning Models to Classify Shiitake Mushrooms (Lentinula edodes) According to Their Geographical Origin Labeling

The shiitake mushroom has gained popularity in the last decade, ranking second in the world for mushrooms consumed, providing consumers with a wide variety of nutritional and healthy benefits. It is often not clear the origin of these mushrooms, so it becomes of great importance to the consumers. In this research, different machine learning algorithms were developed to determine the geographical origin of shiitake mushrooms (Lentinula edodes) consumed in Korea, based on experimental data reported in the literature (δ13C, δ15N, δ18O, δ34S, and origin). Regarding the origin of shiitake in three categories (Korean, Chinese, and mushrooms from Chinese inoculated sawdust blocks), the random forest model presents the highest accuracy value (0.940) and the highest kappa value (0.908) for the validation phase. To determine the origin of shiitake mushrooms in two categories (Korean and Chinese, including mushrooms from Chinese inoculated sawdust blocks in the latter ones), the support vector machine model is chosen as the best model due to the high accuracy (0.988) and kappa (0.975) values for the validation phase. Finally, to determine the origin in two categories (Korean and Chinese, but this time including the mushrooms from Chinese inoculated sawdust blocks in the Korean ones), the best model is the random forest due to its higher accuracy value (0.952) in the validation phase (kappa value of 0.869). The accuracy values in the testing phase for the best selected models are acceptable (between 0.839 and 0.964); therefore, the predictive capacity of the models could be acceptable for their use in real applications. This allows us to affirm that machine learning algorithms would be suitable modeling instruments to determine the geographical origin of shiitake.

Profiling flavor characteristics of cold brew coffee with GC-MS, electronic nose and tongue: effect of roasting degrees and freeze-drying

BACKGROUND

Roasting is an important process in the formation of coffee flavor characteristics, which determines the quality of coffee and consumer acceptance. However, the influence of roasting degree on the flavor characteristics of cold brew coffee has not been fully described.

RESULTS

In the present study, the flavor characteristics of cold brew coffee with different roasting degrees were compared in detail by using chromatographic and electronic sensory approaches, and the flavor changes induced by freeze-drying were investigated. Pyrazine and heterocyclic compounds were the main aroma compounds in coffee, and gradually dominated with the increase of roasting. Pyridine was consistently present in cold brew coffees of different roasting degrees and showed significant gradient of quantity accumulation. Aroma compounds such as pyrazine, linalool and furfuryl acetate were the main contributors to coffee roasting, floral and fruity flavor. Freeze-drying preserved the fruity and floral aromas of medium-roasted cold brew coffee, whereas reducing the bitterness, astringency and acidity properties that are off-putting to consumers.

CONCLUSION

The higher consumer acceptance and enjoyment in medium roast cold brew coffee may be related to its stronger floral and fruity aroma. The aroma profile qualities of freeze-drying processed medium roasted cold brewed coffee were more dominant and more suitable for freeze-drying processing than medium dark roasting. Application of freeze-drying for cold brew coffee will promote the convenience of drinking. The present study provides valuable technical guidance in improving the flavor and quality of cold brew coffee, and also promotes its commercialization process. © 2024 Society of Chemical Industry.

An ancient whole-genome duplication in barnacles contributes to their diversification and intertidal sessile life adaptation

INTRODUCTION

Whole-genome duplication (WGD) is one of the most sudden and dramatic events rarely reported in invertebrates, but its occurrence can lead to physiological, morphological, and behavioral diversification. WGD has also never been reported in barnacles, which is one of the most unique groups of crustaceans with extremely speciallized morphology (calcareous shells) and habits (intertidal sessile lifestyle).

OBJECTIVES

To investigate whether WGD has occurred in barnacles and examine its potential role in driving the adaptive evolution and diversification of barnacles.

METHODS

Based on a newly sequenced and assembled chromosome-level barnacle genome, a novel WGD event has been identified in barnacles through a comprehensive analysis of interchromosomal synteny, the Hox gene cluster, and synonymous substitution distribution.

RESULTS

We provide ample evidences for WGD in the barnacle genomes. Comparative genomic analysis indicates that this WGD event predates the divergence of Thoracicalcarea, occurring more than 247 million years ago. The retained ohnologs from the WGD are primarily enriched in various pathways related to environmental information processing, shedding light on the adaptive evolution and diversification of intertidal sessile lifestyle. In addition, transcriptomic analyses show that most of these ohnologs were differentially expressed following the ebb of tide. And the cytochrome P450 ohnologs with differential expression patterns are subject to subfunctionalization and/or neofunctionalization for intertidal adaptation. Besides WGD, parallel evolution underlying intertidal adaptation has also occurred in barnacles.

CONCLUSION

This study revealed an ancient WGD event in the barnacle genomes, which is potentially associated with the origin and diversification of thoracican barnacles, and may have contributed to the adaptive evolution of their intertidal sessile lifestyle.

Geographical classification of opium samples from Myanmar and Afghanistan by NMR profiling and chemometrics

This study presents a new strategy to discriminate between opium samples obtained from different geographical regions. Nuclear magnetic resonance (NMR) profiling and chemometrics were applied to geographical classification of opium originating from Myanmar and Afghanistan, which are two major opium producing countries in the world. A total of 50 Myanmar and 46 Afghanistan authentic opium samples were analyzed by 1H-NMR, and the chemical profiles were characterized. Different sample preparation procedures, data processing methods, and chemometrics were compared to obtain the best classification effect. It was found that drying and the addition of buffer solutions were unnecessary for classification purposes; thus, the gum opium samples were extracted directly with CD3OD, which shortened sample preparation time. A full discrimination between the two geographical origins was achieved by 1H-NMR profiling and orthogonal partial least squares discriminant analysis. All 30 opium samples were classified correctly by the developed orthogonal partial least squares discriminant analysis model. Compared with traditional chromatography and mass spectrometry profiling methods, the 1H-NMR profiling method was faster (with instrument analysis time of less than 3 min) and reproducible. This study provides new insights into the applying of NMR profiling and chemometrics to rapid drug profiling analysis.

Comprehensive lipidomics study of basa catfish and sole fish using ultra-performance liquid chromatography Q-extractive orbitrap mass spectrometry for fish authenticity

The authenticity of fish products has become a widespread issue in markets due to substitution and false labeling. Lipidomics combined with chemometrics enables the fraudulence identification of food through the analysis of a large amount of data. This study utilized ultra-high-performance liquid chromatography (UHPLC)-QE Orbitrap MS technology to comprehensively analyze the lipidomics of commercially available basa catfish and sole fish. In positive and negative ion modes, a total of 779 lipid molecules from 21 lipid subclasses were detected, with phospholipid molecules being the most abundant, followed by glycerides molecules. Significant differences in the lipidome fingerprinting between the two fish species were observed. A total of 165 lipid molecules were screened out as discriminative features to distinguish between basa catfish and sole fish, such as TAG(16:0/16:0/18:1), PC(14:0/22:3), and TAG(16:1/18:1/18:1), etc. This study could provide valuable insights into authenticating aquatic products through comprehensive lipidomics analysis, contributing to quality control and consumer protection in the food industry.

Stable Isotope Ratio Analysis for the Geographic Origin Discrimination of Greek Beans "Gigantes-Elefantes" (Phaseolus coccineus L.)

Adulteration of high-value agricultural products is a critical issue worldwide for consumers and industries. Discrimination of the geographical origin can verify food authenticity by reducing risk and detecting adulteration. Between agricultural products, beans are a very important crop cultivated worldwide that provides food rich in iron and vitamins, especially for people in third-world countries. The aim of this study is the construction of a map of the locally characteristic isotopic fingerprint of giant beans, "Fasolia Gigantes-Elefantes PGI", a Protected Geographical Indication product cultivated in the region of Kastoria and Prespes, Western Macedonia, Greece, with the ultimate goal of the discrimination of beans from the two areas. In total, 160 samples were collected from different fields in the Prespes region and 120 samples from Kastoria during each cultivation period (2020-2021 and 2021-2022). The light element (C, N, and S) isotope ratios were measured using Isotope Ratio Mass Spectrometry (IRMS), and the results obtained were analyzed using chemometric techniques, including a one-way ANOVA and Binomial logistic regression. The mean values from the one-way ANOVA were δ15NAIR = 1.875‱, δ13CV-PDB = -25.483‱, and δ34SV-CDT = 4.779‱ for Kastoria and δ15NAIR = 1.654‱, δ13CV-PDB = -25.928‱, and δ34SV-CDT = -0.174‱ for Prespes, and showed that stable isotope ratios of C and S were statistically different for the areas studied while the Binomial logistic regression analysis that followed correctly classified more than 78% of the samples.

Trace the origin of yak meat in Xizang based on stable isotope combined with multivariate statistics

In this study, the feasibility of tracing the origin of yak meat in Xizang Autonomous Region based on stable isotope combined with multivariable statistics was researched. The δ13C, δ15N, δ2H and δ18O in yak meat were determined by stable isotope ratio mass spectrometry, and the data were analyzed by analysis of variance, fisher discriminant analysis (FDA), back propagation (BP) neural network and orthogonal partial least squares discrimination analysis (OPLS-DA). The results showed that the δ13C, δ15N, δ2H and δ18O had significant differences among different origins (P < 0.05). The overall original correct discrimination rate of fisher discriminant analysis was 89.7 %, and the correct discrimination rate of cross validation was 88.2 %. The correct classification rate of BP neural network based on training set was 93.38 %, and the correct classification rate of BP neural network based on test set was 89.83 %. The OPLS-DA model interpretation rate parameter R2Y was 0.67, the model prediction rate parameter Q2 was 0.409, which could distinguish yak meat from seven different producing areas in Xizang Autonomous Region. The results showed that the origin of yak meat in Xizang Autonomous Region can be traced based on stable isotope combined with multivariate statistics.

Chemical profile and difference analysis of four parts of Strobilanthes sarcorrhiza by ultrafast flow liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry and multivariate statistical analysis

Strobilanthes sarcorrhiza (CTS) is a medicinal plant with various pharmacological effects such as tonifying kidney and anti-inflammatory. However, the chemical composition and difference of its four parts (leaves, stems, rhizomes, and root tubers) have been rarely reported. In this study, ultrafast flow liquid chromatography coupled with quadrupole-time-of-flight MS was applied to analyze the chemical profile of CTS and identify 55 compounds, including terpenoids, phenylethanol glycosides, fatty acid derivatives, chain glycosides, flavonoid glycosides, and others. Among these compounds, 34 compounds were first identified in CTS. They were mainly terpenoids, phenylethanol glycosides, fatty acid derivatives, and so forth. Multivariate statistical analysis, such as principal component analysis and orthogonal partial least squares-discriminant analysis were also used to evaluate the difference in chemical compounds from the four parts of CTS. The results showed that phenylethanol glycosides were the main compounds of the underground parts, while terpenoids were the main compounds of the aboveground parts. This study revealed the chemical diversity and similarity of CTS and suggested that the rhizomes could be used as an alternative medicinal part to improve the resource utilization of CTS.

A systematical strategy for quality markers screening of different methods processing Platycodonis radix based on phytochemical analysis and the impact on Chronic Obstructive Pulmonary Disease

ETHNOPHARMACOLOGICAL RELEVANCE

Baihezhijiegeng is a processed product of Platycodonis radix, and it's effective in the treatment of Chronic Obstructive Pulmonary Disease (COPD). However, the specific mechanism of action has not been reported in the literature.

AIM OF THE STUDY

We attempted to evaluate the phytochemical composition and pharmaco-dynamics of Platycodon grandiflorum (PG) and BJ to clarify the mechanism behind the expectorant effect of BJ.

MATERIALS AND METHODS

We integrated the ultra-high-performance liquid chromatography-linear trap quadrupole orbitrap velos mass spectrometry (UPLC-LTQ Orbitrap MS/MS) and the ultra-performance liquid chromatography quadrupole-time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS) methods to identify the chemical constituents of PG and BJ. Moreover, correlation and multivariate statistical analyses were utilized to seek the candidate quality markers of PG and BJ. Analysis of effective herbal chemical components using UPLC-Q-TOF-MS/MS and retrieval of COPD disease targets from OMIM, TTD, GeneCard databases. Protein-protein interaction (PPI) and topology analyses were performed using the String database and Cytoscape 3.7.2 software; gene ontology (GO) functional enrichment analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis were performed using the Metescape platform on common targets. Moreover, we used molecular docking to predict the potential mechanism of quality markers for developing anti-COPD activity. Simultaneously, the model of COPD was established by exposing the animals to cigarette smoke combined with a tracheal drip injection of lipopolysaccharide (LPS). Using the ELISA method, quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting (WB) to determine tumor-necrosis factor (TNF)-α, interleukin (IL)-1β, IL-6, and matrix metalloproteinase (MMP)9 levels in serum and IL-4, IL-10, IFN-γ levels, epidermal growth factor receptor (EGFR) and MUC5AC expression in lung tissue of COPD rats to explore the therapeutic effects of PG and BJ on the COPD rat model.

RESULTS

The chemical identification of JG and PG extracts using UPLC-Q-TOF-MS/MS and UPLC-LTQ Orbitrap MS/MS showed 71 compounds, including 47 saponins, 16 phenolic acids, four flavonoids, and four other components. The multivariate statistical analysis showed that seven quality markers were screened. Network pharmacology results showed a role in biological processes such as cellular response to hydrogen peroxide, positive regulation of pri-miRNA transcription from RNA polymerase II promoter, molecular functions such as oxidoreductase activity, acting on NAD(P)H, quinone or similar compound as acceptor, bile acid binding and other molecular functions. In COPD rats, histopathological findings depicted that BJ administration could effectively inhibit inflammatory cell infiltration and mucus hypersecretion, and improve the lung pathological status in rats with COPD. Moreover, BJ could significantly decrease TNF-α, IL-1β, IL-6, and matrix metalloproteinase (MMP)9 levels in the serum and interferon (IFN)-γ levels in lung tissues of rats with COPD (p < 0.01), and significantly increase IL-4 and IL-10 levels in their lung tissues (p < 0.01), suggesting its inhibition of the inflammatory response in vivo. Additionally, EGFR and MUC5AC were reduced in the lung tissues of rats with COPD and airway mucus hypersecretion in rats with COPD.

CONCLUSION

This study revealed the material basis of PG and BJ for anti-COPD activity and discovered the quality markers of PG and BJ which could affect the anti-COPD activity. The therapeutic effects of BJ may be attributed to the regulation of the inflammatory mediators and mediation of the EGFR/MUC5AC pathway in rats with COPD.

Machine learning-guided REIMS pattern recognition of non-dairy cream, milk fat cream and whipping cream for fraudulence identification

The illegal adulteration of non-dairy cream in milk fat cream during the manufacturing process of baked goods has significantly hindered the robust growth of the dairy industry. In this study, a method based on rapid evaporative ionization mass spectrometry (REIMS) lipidomics pattern recognition integrated with machine learning algorithms was established. A total of 26 ions with importance were picked using multivariate statistical analysis as salient contributing features to distinguish between milk fat cream and non-dairy cream. Furthermore, employing discriminant analysis, decision trees, support vector machines, and neural network classifiers, machine learning models were utilized to classify non-dairy cream, milk fat cream, and minute quantities of non-dairy cream adulterated in milk fat cream. These approaches were enhanced through hyperparameter optimization and feature engineering, yielding accuracy rates at 98.4-99.6%. This artificial intelligent method of machine learning-guided REIMS pattern recognition can accurately identify adulteration of whipped cream and might help combat food fraud.

Discrimination rancidity degree of infant formula rice flour based on Headspace Solid-Phase Microextraction combined with Gas Chromatography-Mass Spectrometry as an alternative to sensory evaluation

To mitigating the serious threat of harmful volatile substances to the health of infants, an alternative method of odor evaluation were proposed based on Headspace solid-phase microextraction (HS-SPME) combined with Gas Chromatography-Mass Spectrometry (GC-MS) to discriminate the degree of rancidity of infant formula rice flour (IFRF). Inspectors can simply calculate the rancidity degree of infant formula rice flour according to the regression equation based on the concentration of rancidity markers. The results showed that the joint application of OPLS-DA, molecular sensory experiments, and unsaturated fatty acids (UFAs) degradation experiments could successfully recognize the rancidity markers without collinearity in multiple linear regression analysis. The rancidity markers curve fitting was helpful for the establishment of multivariate regression model of rancidity grading. The model had an accuracy of more than 92.90% by the verification of odor evaluation. The application of the model to investigate the market IFRF samples showed that about 3% of the samples collected in the experiment were unsuitable for infant feeding. Therefore, the established model was considered to be a robust and less workload method to replace the olfactory evaluation method for discriminating the rancidity degree of IFRF.

Effects of different storage containers on the flavor characteristics of Jiangxiangxing baijiu

Storage is a key factor controlling the quality of Jiangxiangxing baijiu, and storage time and the type of storage container play crucial roles in shaping the baijiu's distinct flavor. To investigate the influence of storage containers on the flavor characteristics of Jiangxiangxing baijiu, the sensory qualities, flavor components, and metal ions of Jiangxiangxing baijiu were measured during 24 months of storage in a pottery jar or a stainless steel tank. The results showed that Jiangxiangxing baijiu preserved in a pottery jar was superior to that stored in a stainless steel tank. A total of 96 flavor substances were detected, and 17 key flavor characteristic substances were screened by combining the results of odor activity values (OAV) and orthogonal partial least squares-discriminant analysis (OPLS-DA). A correlation heat map and redundancy analysis (RDA) showed that aluminum, cadmium, iron, cobalt, magnesium, potassium, and copper ions promoted the formation of key characteristic substances including diethoxymethane, lactic acid, 2,3-dimethyl-5-ethylpyrazine, 1-hexanol, and 2-methyl-1-propanol. Overall, the results show that 24-month pottery jar storage can promote the flavor quality of Jiangxiangxing baijiu. This study established a theoretical foundation to select the appropriate storage conditions and control the flavor quality of Jiangxiangxing baijiu.

Honey Origin Authentication via Mineral Profiling Combined with Chemometric Approaches

In the present study, the potential of elemental analysis combined with statistical tools to identify honey origin was evaluated by mineral characterization of 173 honeys of 13 floral types (acacia, fir, spruce, linden, chestnut, lavender, coriander, thistle, honeydew, rosemary, sage, euphorbia and ziziphus plant species) collected from five geographical regions (Slovenia, Croatia, Bulgaria, Turkey, and Morocco). The objective of the study was to accurately and reliably differentiate the mineral composition among honey varieties. The aim was to establish traceability, to ensure product authenticity and to improve quality control measures within the honey industry. For this purpose, 18 major, minor and trace elements were quantified using microwave digestion, followed by ICP-MS measurement. Statistical evaluation of elemental concentration was undertaken using principal component analysis (PCA) to distinguish honey floral types. The research give light on the specific elements that can serve as indicators for determining the geographical and botanical source of honey. Our findings indicate that certain elements, such as Mn, K, and Ca, are primarily influenced by the type of pollen present in the honey, making them indicative of the floral source. On the other hand, levels of Na, Mg, and Fe were found to be more strongly influenced by environmental factors and can be considered as markers of geographical origin. One novel aspect of this research is the exploration of the relationship between honey minerals and honey botanical source. This was achieved through the analysis of chestnut tree samples and a subsequent comparison with the composition of chestnut honey.

The differences in main components, enzyme activity, and microbial composition between substandard and normal jiuyao

BACKGROUND

Jiuyao is a critical fermenting agent in traditional huangjiu brewing and it affects the quality of huangjiu. To assess and monitor the quality of jiuyao effectively we determined the differences between two common types of substandard jiuyao and normal jiuyao, with emphasis on the comparison of the main components, enzymatic activity, volatile substances, and microbial community structure.

RESULTS

The water and starch content, acid protease activity, and esterification capability of type I substandard jiuyao were significantly lower than those of the normal jiuyao, and the protein contents, liquefaction capability, glycation capability, and neutral protease activity were substantially higher than those of the normal jiuyao. Type II substandard jiuyao had significantly lower indices than the normal group except for the starch and free amino acid content, which were significantly higher than those of the normal jiuyao. Significant differences were observed between substandard and normal jiuyao in the content of 21 volatile compounds. 2-Pentylfuran could be used as a marker of substandard jiuyao. Type I substandard jiuyao contained a higher abundance of aerobic Pediococcus and Marivita in comparison with the normal jiuyao. Type II substandard jiuyao consisted of a greater abundance of anaerobic Mucor and Staphylococcus.

CONCLUSION

The quality of jiuyao was significantly affected by the water content. Due to the different abundances of aerobic and anaerobic bacteria in jiuyao, oxygen may also be an important parameter affecting the quality of jiuyao. We believe that the present study offers a theoretical basis for the evaluation and control of the quality of jiuyao. © 2023 Society of Chemical Industry.

Transcriptomics integrated with widely targeted metabolomics reveals the cold resistance mechanism in Hevea brasiliensis

The rubber tree is the primary source of natural rubber and is mainly cultivated in Southeast Asian countries. Low temperature is the major abiotic stress affecting the yield of the rubber tree. Therefore, uncovering the cold resistance mechanism in the rubber tree is necessary. The present study used RNA-sequencing technology and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to analyze the transcriptomic and metabolomic changes in two rubber tree clones with different cold resistance capacities (temperature-sensitive Reyan 8-79 and cold-resistant Yunyan 77-4) at 0 h, 2 h, 6 h, and 20 h of exposure to 4°C. Independent analysis of the transcriptome and metabolitome showed that under prolonged low-temperature treatment, Yunyan 77-4 expressed more genes involved in regulating enzyme activity, changing cell permeability, and synthesizing significant metabolites, such as flavonoids and amino acids, than Reyan 8-79. The KEGG annotation and enrichment analysis identified arginine metabolism and biosynthesis of flavonoids as the major pathway associated with cold resistance. Integrated transcriptome and metabolome analysis showed that the increase in the expression of genes modulated flavonoid biosynthesis, arginine biosynthesis, and anthocyanins biosynthesis, resulting in higher levels of metabolites, such as naringenin chalcone, apigenin, dihydroquercetin, cyanidin 3-glucoside, L-arginosuccinate, N-acetyl-ornithine, ornithine, and N-acetyl-glutamate, in Yunyan 77-4 than in Reyan 8-79 after prolonged low-temperature treatment. Phylogenetic analysis identified the genes, such as CHS (gene356) and F3H (gene33147) of flavonoid biosynthesis and NAGS (gene16028, gene33765), ArgC (gene2487), and ASS (gene6161) of arginine biosynthesis were the key genes involved in the cold resistant of rubber tree. Thus, the present study provides novel insights into how rubber clones resist cold and is a valuable reference for cold-resistance breeding.

Discrimination of Curculigo orchioides Rhizoma and Curculigo glabrescens Rhizoma using stable isotope and mineral element analyses coupled with chemometrics

Correct species identification is crucial for ensuring the quality, safety, and efficacy of herbal medicine. Market research indicates that Curculigo glabrescens Rhizoma (CGR) was the major counterfeit of the medicine Curculigo orchioides Rhizoma (COR). To accurately discriminate COR and CGR remains a challenge, and it becomes even more difficult when the herbs have been heavily processed into a powder. In this work, combined with high performance liquid chromatography analysis, a novel component in CGR was discovered, and two stable isotopes (N%, C%, δ15N, δ13C) and nineteen mineral elements were determined along with multivariate statistical analysis to distinguish the authentic COR samples and counterfeit CGR samples. The results showed that there were significant differences between the mean value of N%, δ15N and δ13C according to the botanical origins. In addition, these two species can be differentiated by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) analysis. A linear discriminant analysis (LDA) model with a good classification rate (100%) and cross-validation rate (100%) was established. Hence, stable isotope and mineral element contents combined with chemometrics analysis could be considered as an effective and reliable method for discriminating the source species of COR and CGR.

Review of Recent Modern Analytical Technology Combined with Chemometrics Approach Researches on Mushroom Discrimination and Evaluation

Mushroom is a macrofungus with precious fruiting body, as a food, a tonic, and a medicine, human have discovered and used mushrooms for thousands of years. Nowadays, mushroom is also a "super food" recommended by the World Health Organization (WHO) and Food and Agriculture Organization (FAO), and favored by consumers. Discrimination of mushroom including species, geographic origin, storage time, etc., is an important prerequisite to ensure their edible safety and commodity quality. Moreover, the effective evaluation of its chemical composition can help us better understand the nutritional properties of mushrooms. Modern analytical technologies such as chromatography, spectroscopy and mass spectrometry, etc., are widely used in the discrimination and evaluation researches of mushrooms, and chemometrics is an effective means of scientifically processing the multidimensional information hidden in these analytical technologies. This review will outline the latest applications of modern analytical technology combined with chemometrics in qualitative and quantitative analysis and quality control of mushrooms in recent years. Briefly describe the basic principles of these technologies, and the analytical processes of common chemometrics in mushroom researches will be summarized. Finally, the limitations and application prospects of chromatography, spectroscopy and mass spectrometry technology are discussed in mushroom quality control and evaluation.

Geographical origin discrimination of Agaricus bisporus produced by the complete medium: A pilot study in South Korea

The complete medium used for mushroom cultivation is important for reliable crop production. We aimed to identify how the origin of Agaricus bisporus grown in Korea was affected by complete media produced in different geographical regions using stable isotope ratios (SIRs). We found that the SIR features of A. bisporus significantly depended on the complete media origin used; in particular, it appeared the high δ³⁴S in the Chinese complete medium, low δ³⁴S in the Dutch complete medium, and high δ¹⁵N in the Korean complete medium (P < 0.05). The support vector machine method appeared better geo-origin classification of A. bisporus by the complete media compared to a linear discriminant analysis. A large-scale study should be conducted to establish a reliable origin identification model for A. bisporus grown in complete media to improve the global mushroom marketplace.

Discrimination of Geographical Origins of Wolfberry (Lycium barbarum L.) Fruits Using Stable Isotopes, Earth Elements, Free Amino Acids, and Saccharides

To develop sophisticated approaches for distinguishing goji origins, 325 wolfberry fruit samples of a certain cultivar, plant age, drying method, and collection season were gathered from 26 producing areas across Northwest China in 2017 and 2018. We employed 49 indices, including stable isotopes, earth elements, soluble amino acids, and saccharides, to identify the regions of origin of these goji fruits. Analysis of variance (ANOVA) and heritability analysis were used to assess the effects of the environment (producing areas), cultivar, plant age, drying process, and collection season. Samples from the same place can be classified and partially discriminated using principal component analysis (PCA). We were able to distinguish fruits produced in Zhongning County from those produced in the other five producing provinces using orthogonal projection to latent structure-discriminant analysis (OPLS-DA). Calcium (Ca), manganese (Mn), ornithine (Orn), cystine (Cys-Cys), glutamate (Glu), phenylalanine (Phe), phosphoserine (Ps), serine (Ser), lysine (Lys), taurine (Tau), proline (Pro), and tyrosine (Tyr) indices were chosen using S-plots and heritability analysis, and their repeatability was established with samples collected in 2018. The indices selected in this study can distinguish goji berries produced in Zhongning County from fruits originating from five other Provinces with high repeatability, which was validated with various cultivars, drying methods, harvest seasons, and plant ages and with heritability analysis.

Improved accuracy of geographical origin identification of shiitake grown in sawdust medium: A compound-specific isotope model-based pilot study

In countries like South Korea and the USA, origin labeling of shiitake grown using imported Chinese-inoculated medium is an issue. Therefore, we evaluated the use of compound-specific isotope analysis (CSIA) for the accurate identification of the geographical origin of shiitake (Korean, Chinese-inoculated medium, and Chinese); Chinese-inoculated medium shiitake were cultivated in Korea using inoculated sawdust medium from China. The CSIA-discriminant model showed an overall accuracy of 100% in the geographical classification of the original set and 96.4% for the cross-validated set. Glutamate and aspartate δ¹⁵N values were the most important variables for differentiating shiitake based on their origins. Compared to that observed upon using the bulk stable isotope analysis, the CSIA model was associated with significantly improved predictability of origin identification. Our findings elucidate the importance of isotope signatures in developing a reliable origin labeling method for shiitake cultured on the sawdust medium for the global market.

Comprehensive evaluation integrating omics strategy and machine learning algorithms for consistency of calculus bovis from different sources

In the clinical application of Traditional Chinese Medicine (TCM) substitutes, the consistency evaluation of TCM substitutes from different sources is recognized as the main bottleneck. As the most widely used analytical method in TCM consistency evaluation, fingerprint similarity evaluation suffers from insufficient method sensitivity and poor conformity with the actual characteristics of TCM, which is difficult to adapt to the analytical needs of complex substance systems of TCM. This work aims to develop an effective and more accurate method for consistency evaluation using omics strategy and machine learning algorithms. The natural calculus bovis (NCB) were graded into three groups according to the similarity to in vitro cultured bovis (IVCB), and chemical markers between samples of each grade were screened out. Support vector machine (SVM) models with different kernels were then constructed by using the chemical markers as feature variables. The results showed that the classification accuracy of the SVM classifier of NCB and the consistency evaluation SVM model classifier was 95.74% and 100.0%, respectively. The approach demonstrated in the study presented a good analytical performance with higher sensitivity, accuracy for consistency evaluation of TCM.

An integrated chemical characterization based on FT-NIR, GC-MS and LC-MS for the comparative metabolite profiling of wild and cultivated agarwood

Agarwood is a well-known and precious traditional Chinese medicine, has been widely applied as drugs and spices for century. The large demand for this material has deeply stimulated the emergence of numerous cultivated products. However, it is difficult to distinguish wild agarwood from cultivated agarwood, and the chemical composition difference between them is not clear. In this study, an integrated method of Fourier transform near-infrared (FT-NIR), gas chromatography-mass spectrometry (GC-MS) and ultraperformance liquid chromatography Quadrupole-Exactive Orbitrap tandem mass spectrometry (UHPLC-Q-Exactive Orbitrap/MS) was developed to explore chemical variation between wild and cultivated agarwood in combination with multivariate statistical analysis. Twenty-four wild and cultivated agarwood samples were collected from different regions. FT-NIR profiles were used to obtain the holistic metabolic characterization in combination with principal component analysis (PCA). A total of seventy-six and seventy-nine metabolites, including volatile components and 2-(2-phenethyl) chromones derivatives, were successfully identified by GC-MS and UHPLC-Q-Exactive Orbitrap/MS, respectively. Thereafter, the orthogonal-partial least square method-discriminant analysis (OPLS-DA) and variable importance in the projection (VIP) were used to screen potential characteristic chemical components (VIP > 1) in wild and cultivated agarwood, respectively. Finally, eight key chemical markers were putatively identified by two techniques to distinguish agarwood from different origins, which can be found that sesquiterpenes, aromatics, terpenoids, 2-(2-phenylethyl) chromones of the flidersia type (FTPECs) and tetrahydro-2-(2-phenylethyl) chromones (THPECs) are the most important metabolites. Summary, this research presented a comprehensive metabolomic variation between wild and cultivated agarwood on the basis of a multi-technology platform, which laid a foundation for distinguishing the two ecotypes of agarwood and was conducive to the quality control of this resource.

An untargeted metabolomics approach to identify markers to distinguish duck eggs that come from different poultry breeding systems by ultra high performance liquid chromatography-high resolution mass spectrometry

Untargeted metabolomics approach based on ultra high performance liquid chromatography coupled with high resolution mass spectrometry (UHPLC-HRMS) was used to investigate the differences in cage duck eggs and sea duck eggs that from different poultry breeding system, which could help to combat fraud within the egg industry. High dimensions and complex data collected by UHPLC-HRMS were analyzed by multivariate statistical analysis. Identification model of sea duck eggs based on was established. After matching with the chemical databases, four potential markers were putatively matched. Further analysis showed that three of them were confirmed by reference standards. All these three markers (n-behenoyl-d-erythro-sphingosine, 1,2-dipalmitoyl-sn-glycero-3-phosphocholine and n-nervonoyl-d-erythro-sphingosine) have higher content in sea duck eggs. The quantitative analysis showed that the content difference of three markers in farm samples were in highly consistent with the concentration changes measured in experimental samples, which indicate that these three markers are reliable.

Mutated Shiitake extracts inhibit melanin-producing neural crest-derived cells in zebrafish embryo

The ability of natural extracts to inhibit melanocyte activity is of great interest to researchers. This study evaluates and explores the ability of mutated Shiitake (A37) and wildtype Shiitake (WE) extract to inhibit this activity. Several properties such as total phenolic (TPC) and total flavonoid content (TFC), antioxidant activity, effect on cell and component profiling were conducted. While having no significant differences in total phenolic content, mutation resulted in A37 having a TFC content (1.04 ± 0.7 mg/100 ml) compared to WE (0.86 ± 0.9 mg/100 ml). Despite that, A37 extract has lower antioxidant activity (EC50, A37 = 549.6 ± 2.70 μg/ml) than WE (EC50 = 52.8 ± 1.19 μg/ml). Toxicity tests on zebrafish embryos show that both extracts, stop the embryogenesis process when the concentration used exceeds 900 μg/ml. Although both extracts showed pigmentation reduction in zebrafish embryos, A37 extract showed no effect on embryo heartbeat. Cell cycle studies revealed that WE significantly affect the cell cycle while A37 not. Further tests found that these extracts inhibit the phosphorylation of Glycogen synthase kinase 3 β (pGSK3β) in HS27 cell line, which may explain the activation of apoptosis in melanin-producing cells. It was found that from 19 known compounds, 14 compounds were present in both WE and A37 extracts. Interestingly, the presence of decitabine in A37 extract makes it very potential for use in the medical application such as treatment of melanoma, skin therapy and even cancer.

An Integrated Strategy for Rapid Discovery and Identification of Quality Markers in Gardenia Fructus Using an Omics Discrimination-Grey Correlation-Biological Verification Method

Background: Gardenia Fructus (GF), a traditional Chinese medicine of Gardenia Ellis in Rubiaceae family, has the potential to clear heat and purge fire and has been widely used to treat multiple infection-related diseases. However, the quality markers (Q-Markers) of GF have not been revealed comprehensively.

Methods: In this experiment, the transgenic zebrafish lines, Tg (l-fabp:EGFP) and Tg (lyz:EGFP), were used to evaluate two main kinds of traditional efficacies of GF, hepatoprotective and anti-inflammatory effects. All the GF samples from different production areas were tested their anti-liver injury and anti-inflammantory activities. High-performance liquid chromatography-quadrupole time-of-flight mass spectrometry method (HPLC-Q-TOF/MS) was employed for herbal metabonomic analysis of GF samples. Gray correlation analysis (GCA) was utilized to screen out the components closely associated with the activities. Finally, the zebrafish model was applied to verify the bioactivity of the crucial components to determine the Q-Markers of GF.

Results: The zebrafish models were established by inducing with hydrogen peroxide or copper sulfate and applied to quickly evaluate the hepatoprotective effect and inflammation of GF samples. 27 potentially active components for liver protection and 21 potentially active components with anti-inflammatory properties were identified by herbal metabolomic analysis based on HPLC-Q-TOF/MS. The GCA result showed that five of the 27 components were highly correlated with liver protection, 15 of the 21 components were highly correlated with anti-inflammatory activity. Among them, geniposide and crocin-1 were confirmed their bioactivities on zebrafish experiment to be responsible for the protective effects of GF against liver injury, and genipin-1-β-D-gentiobioside, quinic acid, gardenoside, d-glucuronic acid, l-malic acid, mannitol, rutin, and chlorogenic acid were confirmed to be responsible for the anti-inflammatory effects. Finally, according to the screening principles of Q-Markers, genipin-1-β-D-gentiobioside, geniposide, and gardenoside were preliminarily identified to be the Q-Markers of GF.

Conclusion: This study established an effective research strategy of “Omics Discrimination-Grey Correlation-Biological Verification,” which enabled the rapid identification of key pharmacological components of GF. These markers have provided a scientific basis for constructing a modern quality evaluation system for GF.

Simple sequence repeats drive genome plasticity and promote adaptive evolution in penaeid shrimp

Simple sequence repeats (SSRs) are rare (approximately 1%) in most genomes and are generally considered to have no function. However, penaeid shrimp genomes have a high proportion of SSRs (>23%), raising the question of whether these SSRs play important functional and evolutionary roles in these SSR-rich species. Here, we show that SSRs drive genome plasticity and adaptive evolution in two penaeid shrimp species, Fenneropenaeus chinensis and Litopenaeus vannamei. Assembly and comparison of genomes of these two shrimp species at the chromosome-level revealed that transposable elements serve as carriers for SSR expansion, which is still occurring. The remarkable genome plasticity identified herein might have been shaped by significant SSR expansions. SSRs were also found to regulate gene expression by multi-omics analyses, and be responsible for driving adaptive evolution, such as the variable osmoregulatory capacities of these shrimp under low-salinity stress. These data provide strong evidence that SSRs are an important driver of the adaptive evolution in penaeid shrimp.

An origin identification model for labeling of shiitake (Lentinula edodes)

With the increasing globalization of the food trade across countries and continents, reliable identification of the geographical origin of products is critical. In this study, we describe the limitations of the current origin labeling system for non-soil-based agricultural products and suggest alternative strategies for the identification of the geographical origin of such products. An origin identification model based on stable isotope ratio analysis combined with discriminant analysis is used to evaluate the similarities and dissimilarities between domestic and foreign shiitake mushrooms, including Chinese inoculated sawdust blocks and Chinese origin. The results show a classification sensitivity of 92.0%, classification specificity of 91.5%, and overall accuracy of 93.5%. In particular, δ¹⁵N was the most important isotope marker for the identification of the origin of shiitake mushrooms. Hence, the current origin labeling system for mushroom species has to be revised to establish fair trade and avoid improper origin labeling in the global shiitake market.

Rapid Geographical Origin Identification and Quality Assessment of Angelicae Sinensis Radix by FT-NIR Spectroscopy

Angelicae Sinensis Radix is a widely used traditional Chinese medicine and spice in China. The purpose of this study was to develop a methodology for geographical classification of Angelicae Sinensis Radix and determine the contents of ferulic acid and Z-ligustilide in the samples using near-infrared spectroscopy. A qualitative model was established to identify the geographical origin of Angelicae Sinensis Radix using Fourier transform near-infrared (FT-NIR) spectroscopy. Support vector machine (SVM) algorithms were used for the establishment of a qualitative model. The optimum SVM model had a recognition rate of 100% for the calibration set and 83.72% for the prediction set. In addition, a quantitative model was established to predict the content of ferulic acid and Z-ligustilide using FT-NIR. Partial least squares regression (PLSR) algorithms were used for the establishment of a quantitative model. Synergy interval-PLS (Si-PLS) was used to screen the characteristic spectral interval to obtain the best PLSR model. The coefficient of determination for calibration (R2C) for the best PLSR models established with the optimal spectral preprocessing method and selected important spectral regions for the quantitative determination of ferulic acid and Z-ligustilide was 0.9659 and 0.9611, respectively, while the coefficient of determination for prediction (R2P) was 0.9118 and 0.9206, respectively. The values of the ratio of prediction to deviation (RPD) of the two final optimized PLSR models were greater than 2. The results suggested that NIR spectroscopy combined with SVM and PLSR algorithms could be exploited in the discrimination of Angelicae Sinensis Radix from different geographical locations for quality assurance and monitoring. This study might serve as a reference for quality evaluation of agricultural, pharmaceutical, and food products.

Rapid authentication of agarwood by using liquid extraction surface analysis mass spectrometry (LESA-MS)

INTRODUCTION

Agarwood is a highly valuable fragrant resinous wood which is widely used as traditional Chinese medicines, perfumes, incense and decorations. Due to its high economic value and excessive demand, this leads to a rising price and proliferation of fake commodities. Thus, strict authenticity identification and quality evaluation of agarwood are of great significance.

OBJECTIVE

To establish a simple, rapid and non-destructive technique for identifying the authenticity of agarwood.

METHODS

Liquid extraction surface analysis mass spectrometry (LESA-MS) was firstly proposed to identify the authenticity of 62 agarwood samples without sample preparation. In addition, multivariate statistical models and thin-layer chromatography (TLC) method were used to analyse and verify the results of LESA-MS.

RESULTS

Representative compounds of agarwood were detected by LESA-MS. A characteristic 2-(2-phenylethyl)chromone compound (m/z 319.1) was treated as a key chemical marker to identify agarwood and its counterfeits rapidly. Several other chromones ions were identified and used as additional evidence for authentic samples. A total of 62 samples were visually discriminated as two groups by principal component analysis (PCA) and orthogonal projection to latent structures discriminant analysis (OPLS-DA), and the specific characteristic marker was highlighted. Moreover, the qualitative results of the conventional TLC method were in agreement with the LESA-MS approach.

CONCLUSION

The proposed LESA-MS method was successfully applied in the direct qualitative analysis of agarwood from different sources. This study indicated great feasibility and practicality of LESA-MS in the rapid identification of agarwood, and provided a non-destructive and meaningful preliminary screening tool for the agarwood industry.

Comparisons of Chemical Profiles and Gastroprotective Effects of Citri Sarcodactylis Fructus Pre- and Poststeam Processing

BACKGROUND

Citri Sarcodactylis Fructus (CSF) is widely used as folk medicine in traditional Chinese medicine (TCM). The dried and steam-processed CSF (SCSF) has been employed for harmonizing the stomach over thousands of years under the guidelines of TCM theory. However, little is known about the differences in chemical compositions between CSF and SCSF. Moreover, the gastroprotective effects of CSF and SCSF on ethanol-induced gastric mucosal injuries in rats have yet to be investigated. Consequently, the present study aimed to investigate the chemical differences and gastroprotective effects of CSF and SCSF, providing some experimental framework for the development of CSF and SCSF.

METHODS

The chemical compositions of CSF and SCSF extracts were determined using an ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometer (UPLC-Q-TOF-MS), and their gastroprotective effects of different doses were assessed in rats with ethanol-induced gastric injuries on the levels of oxidative stress and inflammatory cytokines.

RESULTS

A total of 42 components were identified in CSF and SCSF, and most of them were flavonoids, limonoids, coumarins, and glycosides. There were no differences in the compositions between CSF and SCSF, but the relative contents of the components were different. Among them, nine screened compounds were considered as potential discriminating markers responsible for the differences between CSF and SCSF. Besides, pretreatments with CSF and SCSF markedly improved the gastric mucosal injuries in rats for their antioxidant and anti-inflammatory properties. And SCSF exhibited a better gastroprotective effect than CSF.

CONCLUSION

The compositions of CSF were unchanged after steam-processing, while the relative contents of their components were changed. These changes may be the major reasons for the differentiation of their efficacies. In addition, CSF and SCSF could alleviate ethanol-induced gastric mucosal injury through the enhancement of antioxidant and anti-inflammatory activities. SCSF exhibited a better gastroprotective effect than CSF, which emphasized the necessity of steam processing.

Fatty Acids and Stable Isotope Ratios in Shiitake Mushrooms (Lentinula edodes) Indicate the Origin of the Cultivation Substrate Used: A Preliminary Case Study in Korea

Shiitake mushroom (Lentinula edodes) is commonly consumed worldwide and is cultivated in many farms in Korea using Chinese substrates owing to a lack of knowledge on how to prepare sawdust-based substrate blocks (bag cultivation). Consequently, issues related to the origin of the Korean or Chinese substrate used in shiitake mushrooms produced using bag cultivation have been reported. Here, we investigated differences in fatty acids (FAs) and stable isotope ratios (SIRs) in shiitake mushrooms cultivated using Korean and Chinese substrates under similar conditions (strain, temperature, humidity, etc.) and depending on the harvesting cycle. The total FA level decreased significantly by 5.49 mg∙g⁻¹ as the harvesting cycle increased (p < 0.0001); however, no differences were found in FAs between shiitake mushrooms cultivated using Korean and Chinese substrates. Linoleic acid was the most abundant FA, accounting for 77–81% of the total FAs during four harvesting cycles. Moreover, the SIRs differed significantly between the Korean and Chinese substrates, and the harvesting cycles resulted in smaller maximum differences in SIR values compared to those of the cultivation substrate origins. Our findings contribute to the identification of the geographical origin of shiitake mushrooms and may have potential applications in international shiitake-mushroom markets.

Effect of unsaturated fatty acids on glycation product formation pathways (Ⅰ) the role of oleic acid

Research on advanced glycation end-products (AGEs) and their formation pathways in food processing has gradually increased because AGEs are associated with human health, especially with involvement of lipids. In this study, radicals and glycation products were detected via electron spin resonance (ESR) and ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) respectively. The correlation of important intermediates was used to explain the effect of oleic acid (OA) on the glycation products and pathways. The results indicated OA participation decreased the content of stable radicals and glycosyl compounds in Maillard Reaction (MR). The oxidation of OA produced active radicals, and electron transfer caused lysine to transform radical form. These radicals participated in the formation of fructosyllysine (FL) with glucose (Glc) via the MR. The participation of OA is acted as inhibiting the way of Glc autoxidation and promoting the glycation pathway from FL to 3-deoxyglucosone (3-DG) to fluorescent-AGEs. Orthogonal projection to latent structures discriminant analysis results indicated that 3-DG, D-glucosone and methylglyoxal are key products in discriminating the glycation reaction.

Discrimination of Milk from Different Animal Species by a Foodomics Approach Based on High-Resolution Mass Spectrometry

An untargeted foodomics strategy based on ultra-high-performance liquid chromatography coupled with quadrupole orbitrap and chemometrics was used to observe subtle differences in the molecule profiles of raw milk from different animal species (cow milk, goat milk, and water buffalo milk), which could prevent the fraud activities in the dairy industry. In data-dependent acquisition (DIA), spectra for all precursor ions facilitated the comprehensive identification of unknown compounds in untargeted foodomics. Chemometrics techniques were used to analyze large amounts of complex data to observe the separation of different sample groups and find the potential markers of sample groups. Finally, five markers were putatively identified by the potential marker identification workflow. The quantification results showed that β-carotene was found only in cow milk; ergocalciferol was found only in water buffalo milk; and the contents of nonanoic acid, decanoic acid, and octanoic acid were higher in goat milk than those in cow milk and water buffalo milk. The quantification of β-carotene enabled the detection of cow milk with a sensitivity threshold of 5% (w/w). This work provided an efficient approach for the discrimination of cow milk, goat milk, and water buffalo milk. Compared with proteomics and genomics, the simpler analytical procedures, lower costs, and higher speed of this work make it of great benefit for routine operations.