Geographical origin of Chinese wolfberry (goji) determined by carbon isotope analysis of specific volatile compounds

A comparative UHPLC-QTOF-MS/MS-based metabolomics approach reveals the metabolite profiling of wolfberry sourced from different geographical origins

Wolfberry, known as Goji berry, is the fruit of Lycium barbarum L. (LB). As a famous functional food and TCM, the cost and efficacy of LB are closely linked to its geographical origin. The present study aimed to establish an effective method for distinguishing LB from different geographical origins. By employing UHPLC-QTOF-MS/MS combined with multivariate analysis, the metabolite profiling of LB (199 batches) obtained from Ningxia, Gansu, Qinghai, and Xinjiang, was evaluated. The results demonstrated that the method effectively distinguished LB from the four regions, with a total of 148 different metabolites being detected. Subsequent assessment using heat maps, Venn analysis, receiver operating characteristics curves and dot plots revealed 21 of these metabolites exhibited exceptional sensitivity and specificity, with under-curve values approaching 1, thus indicating their potential as biomarkers for LB. These findings strongly support the suitability of UHPLC-QTOF-MS/MS-based metabolomics as an effective approach to identify the source of LB.

A review of recent compound-specific isotope analysis studies applied to food authentication

Compound-specific stable isotope analysis (CSIA) of food products is a relatively new and novel technique used to authenticate food and detect adulteration. This paper provides a review of recent on-line and off-line CSIA applications of plant and animal origin foods, essential oils and plant extracts. Different food discrimination techniques, applications, scope, and recent studies are discussed. CSIA δ13C values are widely used to verify geographical origin, organic production, and adulteration. The δ15N values of individual amino acids and nitrate fertilizers have proven effective to authenticate organic foods, while δ2H and δ18O values are useful to link food products with local precipitation for geographical origin verification. Most CSIA techniques focus on fatty acids, amino acids, monosaccharides, disaccharides, organic acids, and volatile compounds enabling more selective and detailed origin and authentication information than bulk isotope analyses.. In conclusion, CSIA has a stronger analytical advantage for the authentication of food compared to bulk stable isotope analysis, especially for honey, beverages, essential oils, and processed foods.

Multidimensional isotope analysis of carbon, hydrogen, and oxygen as a tool for traceability of lactose in drug products

Lactose is one of the most commonly used pharmaceutical excipients. Depending on manufactures, the properties of lactose are very different, which could impact the pharmacokinetic behavior of drug products. Therefore, it is very important to trace the origin of pharmaceutical lactose in drug products which is valuable for prescription analysis. In this study, the carbon, hydrogen and oxygen isotope ratios (δ¹³C, δ²H and δ¹⁸O) of thirty-four lactose from seven manufacturers were analyzed by elemental analysis-stable isotope ratio mass spectrometry (EA-IRMS). One-way analysis of variance (ANOVA) and Duncan's test indicated significant differences in isotope ratios of lactose from different origins. To identify the lactose manufacturer, a discrimination model was generated through linear discriminant analysis (LDA). Based on this model, the manufacturers of lactose used in three drug products were successfully identified. Our results suggested that the multidimensional analysis of δ¹³C, δ²H and δ¹⁸O of lactose provided a fast and effective method to trace the lactose manufacturer. In conclusion, this method can be used to analyze the prescription of the drug product quickly, which could speed up the development of generic drug product.

Protected Geographical Indication Discrimination of Zhejiang and Non-Zhejiang Ophiopogonis japonicus by Near-Infrared (NIR) Spectroscopy Combined with Chemometrics: The Influence of Different Stoichiometric and Spectrogram Pretreatment Methods

This paper presents a method for the protected geographical indication discrimination of Ophiopogon japonicus from Zhejiang and elsewhere using near-infrared (NIR) spectroscopy combined with chemometrics. A total of 3657 Ophiopogon japonicus samples from five major production areas in China were analyzed by NIR spectroscopy, and divided into 2127 from Zhejiang and 1530 from other areas ('non-Zhejiang'). Principal component analysis (PCA) was selected to screen outliers and eliminate them. Monte Carlo cross validation (MCCV) was introduced to divide the training set and test set according to a ratio of 3:7. The raw spectra were preprocessed by nine single and partial combination methods such as the standard normal variable (SNV) and derivative, and then modeled by partial least squares regression (PLSR), a support vector machine (SVM), and soft independent modeling of class analogies (SIMCA). The effects of different pretreatment and chemometrics methods on the model are discussed. The results showed that the three pattern recognition methods were effective in geographical origin tracing, and selecting the appropriate preprocessing method could improve the traceability accuracy. The accuracy of PLSR after the standard normal variable was better, with R² reaching 0.9979, while that of the second derivative was the lowest with an R² of 0.9656. After the SNV pretreatment, the accuracy of the training set and test set of SVM reached the highest values, which were 99.73% and 98.40%, respectively. The accuracy of SIMCA pretreated with SNV and MSC was the highest for the origin traceability of Ophiopogon japonicus, which could reach 100%. The distance between the two classification models of SIMCA-SNV and SIMCA-MSC is greater than 3, indicating that the SIMCA model has good performance.

Comparison of Lycium barbarum fruits polysaccharide from different regions of China by acidic hydrolysate fingerprinting-based HILIC-ELSD-ESI-TOF-MS combined with chemometrics analysis

INTRODUCTION

Lycium barbarum is an edible fruit widely used in herbal medicines and as a functional food. Polysaccharide is one of the most important active ingredients. Only L. barbarum grown in the Ningxia region of China are officially recognised as suitable for use in traditional Chinese medicine, but the systematic comparison of L. barbarum polysaccharide between Ningxia and the other growing regions of China has been rarely reported.

OBJECTIVE

To compare the difference of L. barbarum polysaccharide from different grown regions of China.

METHODS

A chemical fingerprint of L. barbarum polysaccharide hydrolysates was established based on controlled acidolysis combined with hydrophilic interaction liquid chromatography-evaporative light scattering detection-electrospray ionisation-time-of-flight-mass spectrometry (HILIC-ELSD-ESI-TOF-MS). Then, it was employed for the comparison of L. barbarum samples from different geographical origins of China combined with chemometrics analysis.

RESULTS

Six monosaccharides [rhamnose (Rha), xylose (Xyl), arabinose (Ara), mannose (Man), glucose (Glu), galactose (Gal)] were qualitatively and quantitatively determined and four glycoconjugates were preliminarily identified from the hydrolysates. Content determination for the polysaccharide and monosaccharide indicated obvious geographical features. The HILIC-ELSD fingerprint combined with partial least squares-discriminant analysis (PLS-DA) was able to differentiate L. barbarum samples from Ningxia, Xinjiang, Gansu and Qinghai regions with 89.19% classification accuracy. Orthogonal projection to latent structure discriminant analysis (OPLS-DA) was able to differentiate between samples from Ningxia and those from the other three growing regions, polysaccharide and Ara were the potential chemical markers.

CONCLUSIONS

These findings form the basis of a reliable method to trace the region of origin of L. barbarum sample and thereby, improve the quality control of L. barbarum therapeutic polysaccharides.

Evaluating the accuracy and reliability of compound-specific carbon isotopic analysis using gas chromatography-combustion-isotope ratio mass spectrometry with the addition of a reduction furnace

RATIONALE

Gas chromatography-combustion-isotope ratio mass spectrometry (GC/C/IRMS) is widely used for compound-specific carbon isotopic analysis. However, current isotopic analysis systems utilize the GC IsoLink combustion reactor, and independent reduction furnaces are not implemented. Therefore, whether this limitation in furnace use affects the precision of compound-specific carbon isotopic analysis needs to be evaluated.

METHODS

We attempted to add a separate reduction furnace to the GC IsoLink interface and compared the δ¹³ C values of n-alkanes (including C and H elements), fatty acid methyl ester (including C, H, and O elements), caffeine (USGS61 and USGS62, including C, H, O, and N elements), and 9-ethylcarbazole (including C, H, and N elements) before and after the addition of the reduction furnace using the GC IsoLink combustion reactor.

RESULTS

For n-alkanes and fatty acid methyl esters, the δ¹³ C differences between the measured values and their standard values were basically falling within 0.5‰ whether or not an independent reduction furnace was added. However, for the nitrogen-containing compounds (caffeine and 9-ethylcarbazole), the δ¹³ C differences between the measured values and their standard values were much larger without an independent reduction furnace (1.0-3.71‰ for USGS61, 1.78-2.19‰ for USGS62, and 0.39-1.13‰ for 9-ethylcarbazole) than with a reduction furnace (-0.31-0.68‰ for USGS61, -0.44-0.06‰ for USGS62, and -0.04-0.25‰ for 9-ethylcarbazole).

CONCLUSIONS

The addition of an independent reduction furnace had no significant effect on the δ¹³ C of n-alkanes and fatty acid methyl esters, but it had a significant effect on the δ¹³ C of nitrogen-containing compounds. It is suggested that GC IsoLink needs an independent reduction furnace to effectively eliminate the interference of NO_x on CO₂ isotopic determination to improve the accuracy of δ¹³ C for nitrogen-containing compounds.

Flavor components detection and discrimination of isomers in Huaguo tea using headspace-gas chromatography-ion mobility spectrometry and multivariate statistical analysis

Aroma components are one of the crucial factors in dynamic processes analysis, quality control, and origin traceability. Various categories of Huaguo Tea possessed different taste due to the generation of aroma. In this study, a comprehensive analysis of volatiles was conducted for five popular Huaguo Tea samples (Lemon Slices, Bitter Gourd Slices, Citri Reticulatae Pericarpium, Red Lycium Barbarum, and Black Lycium Barbarum) via gas chromatography-ion mobility spectrometry (GC-IMS) combining with multivariate statistical strategies. Comparison analysis was achieved with the properties of visually and intuitively by drawing of topography plots. A total of one hundred and eighty volatiles were distinguished. Aliphatic isomers were identified simultaneously by fingerprint spectra. Alcohols, aldehydes, esters, and ketones were the most abundant volatiles in Huaguo Tea samples. To characterize the Huaguo Tea precisely and establish an analysis model for their classification, multivariate statistical analysis was applied to distinguish different Huaguo Tea. Satisfied discrimination was obtained by principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) based on the HS-GC-IMS results with the robustness parameter (R²Y) of 99.4%, and prediction ability parameter (Q²) of 98.6%, respectively. The results provide a theoretical basis for aroma discrimination, isomer identification, and categories analysis of Huaguo Tea.

Effects of nitrogen input on soil bacterial community structure and soil nitrogen cycling in the rhizosphere soil of Lycium barbarum L

Lycium barbarum L., goji berry, is a precious traditional Chinese medicine and it is homology of medicine and food. Its growth is heavily dependent on nitrogen. The use of chemical fertilizers has significantly promoted the yield of goji berry and the development of the L. barbarum L. industry. However, crop plants are inefficient in the acquisition and utilization of applied nitrogen, it often leads to excessive application of nitrogen fertilizers by producers, which cause negatively impact to the environment ultimately. The exploration of an interaction model which deals with crops, chemical fertilizers, and rhizosphere microbes to improve nitrogen use efficiency, is, therefore, an important research objective to achieve sustainable development of agriculture greatly. In our study, we explored the effects of nitrogen input on soil microbial community structure, soil nitrogen cycling, and the contents of nutrients in L. barbarum fruits. The structure and composition of the bacterial community in the rhizosphere soil of L. barbarum were significantly different under different nitrogen supply conditions, and high nitrogen addition inhibited the diversity and stability of bacterial communities. Low nitrogen input stimulated the relative abundance of ammonia-oxidizing bacteria (AOB), such as Nitrosospira, catalyzing the first step of the ammonia oxidation process. The results of the GLMM model showed that the level of nitrogen fertilizer (urea) input, the relative abundance of AOB, the relative abundance of Bradyrhizobium, and their combinations had significant effects on the soil nitrogen cycling and contents of nutrients in L. barbarum fruits. Therefore, we believe that moderately reducing the use of urea and other nitrogen fertilizers is more conducive to improving soil nitrogen use efficiency and Goji berry fruit quality by increasing the nitrogen cycling potential of soil microorganisms.

Chemical and Biological Properties of Three Poorly Studied Species of Lycium Genus-Short Review

The genus Lycium belongs to the Solanaceae family and comprises more than 90 species distributed by diverse continents. Lycium barbarum is by far the most studied and has been advertised as a “superfood” with healthy properties. In contrast, there are some Lycium species which have been poorly studied, although used by native populations. L. europaeum, L. intricatum and L. schweinfurthii, found particularly in the Mediterranean region, are examples of scarcely investigated species. The chemical composition and the biological properties of these species were reviewed. The biological properties of L. barbarum fruits are mainly attributed to polysaccharides, particularly complex glycoproteins with different compositions. Studies regarding these metabolites are practically absent in L. europaeum, L. intricatum and L. schweinfurthii. The metabolites isolated and identified belong mainly to polyphenols, fatty acids, polysaccharides, carotenoids, sterols, terpenoids, tocopherols, and alkaloids (L. europaeum); phenolic acids, lignans, flavonoids, polyketides, glycosides, terpenoids, tyramine derivatives among other few compounds (L. schweinfurthii), and esters of phenolic acids, glycosides, fatty acids, terpenoids/phytosterols, among other few compounds (L. intricatum). The biological properties (antioxidant, anti-inflammatory and cytotoxic against some cancer cell lines) found for these species were attributed to some metabolites belonging to those compound groups. Results of the study concluded that investigations concerning L. europaeum, L. intricatum and L. schweinfurthii are scarce, in contrast to L. barbarum.

Identification and Quality Evaluation of Velvet Antler by DNA Barcoding and Stable Isotope Techniques Combined with Chemometrics

This study aimed to identify Velvet antler and its counterfeits and to further evaluate their quality. Mitochondrial cytochrome b (Cytb) was used as a target gene to identify Velvet antler samples, and a DNA barcoding method was established for species origin identification in Velvet antlers. After identification, the stable isotope contents and ratios were adopted to evaluate the quality of different specifications of authentic Velvet antler in combination with chemometrics. Two stable isotope contents (C % and N %) and ratios (δ¹³C and δ¹⁵N) in three kinds of Velvet antler slices of different specifications, namely, wax slices, powder slices, and bone slices, were determined. Nine Velvet antler samples sold in the market were identified for label conformity. Only two samples were consistent with the labeled species, and the others were counterfeits. The three slices of Velvet antler of different specifications were clearly distinguished by principal component analysis and hierarchical cluster analysis. Then, the discriminant model of partial least squares discriminant analysis was established, and 100% discrimination accuracy was observed in this model. All the Velvet antler slice samples of different specification samples were grouped clearly according to their sources. In summary, it is feasible for the identification and quality grade evaluation of Velvet antler by DNA barcoding based on mitochondrial Cytb and stable isotope techniques combined with chemometric analysis. The establishment of this method also provided a reference for the evaluation of other animal-derived medicinal materials.

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.

An Endophytic Strain of Bacillus amyloliquefaciens Suppresses Fusarium oxysporum Infection of Chinese Wolfberry by Altering Its Rhizosphere Bacterial Community

Root rot disease is a serious infection leading to production loss of Chinese wolfberry (Lycium barbarum). This study tested the potential for two bacterial biological control agents, Bacillus amyloliquefaciens HSB1 and FZB42, against five fungal pathogens that frequently cause root rot in Chinese wolfberry. Both HSB1 and FZB42 were found to inhibit fungal mycelial growth, in vitro and in planta, as well as to promote the growth of wolfberry seedlings. In fact, a biocontrol experiment showed efficiency of 100% with at least one treatment involving each biocontrol strain against Fusarium oxysporum. Metagenomic sequencing was used to assess bacterial community shifts in the wolfberry rhizosphere upon introduction of each biocontrol strain. Results showed that HSB1 and FZB42 differentially altered the abundances of different taxa present and positively influenced various functions of inherent wolfberry rhizosphere bacteria. This study highlights the application of biocontrol method in the suppression of fungal pathogens that cause root rot disease in wolfberry, which is useful for agricultural extension agents and commercial growers.

Recent techniques for the authentication of the geographical origin of tea leaves from camellia sinensis: A review

Tea is one of the most important beverages worldwide, is produced in several distinct geographical regions, and is traded on the global market. The ability to determine the geographical origin of tea products helps to ensure authenticity and traceability. This paper reviews the recent research on authentication of tea using a combination of instrumental and chemometric methods. To determine the production region of a tea sample, instrumental methods based on analyzing isotope and mineral element contents are suitable because they are less affected by tea variety and processing methods. Chemometric analysis has proven to be a valuable method to identify tea. Principal component analysis (PCA) and linear discriminant analysis (LDA) are the most preferred methods for processing large amounts of data obtained through instrumental component analysis.

Authentication of berries and berry-based food products

Berries represent one of the most important and high-valued group of modern-day health-beneficial "superfoods" whose dietary consumption has been recognized to be beneficial for human health for a long time. In addition to being delicious, berries are rich in nutrients, vitamins, and several bioactive compounds, including carotenoids, flavonoids, phenolic acids, and hydrolysable tannins. However, due to their high value, berries and berry-based products are often subject to fraudulent adulteration, commonly for economical gain, but also unintentionally due to misidentification of species. Deliberate adulteration often comprises the substitution of high-value berries with lower value counterparts and mislabeling of product contents. As adulteration is deceptive toward customers and presents a risk for public health, food authentication through different methods is applied as a countermeasure. Although many authentication methods have been developed in terms of fast, sensitive, reliable, and low-cost analysis and have been applied in the authentication of a myriad of food products and species, their application on berries and berry-based products is still limited. The present review provides an overview of the development and application of analytical chemistry methods, such as isotope ratio analysis, liquid and gas chromatography, spectroscopy, as well as DNA-based methods and electronic sensors, for the authentication of berries and berry-based food products. We provide an overview of the earlier use and recent advances of these methods, as well as discuss the advances and drawbacks related to their application.

Construction of IsoVoc Database for the Authentication of Natural Flavours

Flavour is an important quality trait of food and beverages. As the demand for natural aromas increases and the cost of raw materials go up, so does the potential for economically motivated adulteration. In this study, gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) analysis of volatile fruit compounds, sampled using headspace-solid phase microextraction (HS-SPME), is used as a tool to differentiate between synthetic and naturally produced volatile aroma compounds (VOCs). The result is an extensive stable isotope database (IsoVoc—Isotope Volatile organic compounds) consisting of 39 authentic flavour compounds with well-defined origin: apple (148), strawberry (33), raspberry (12), pear (9), blueberry (7), and sour cherry (4) samples. Synthetically derived VOCs (48) were also characterised. Comparing isotope ratios of volatile compounds between distillates and fresh apples and strawberries proved the suitability of using fresh samples to create a database covering the natural variability in δ¹³C values and range of VOCs. In total, 25 aroma compounds were identified and used to test 33 flavoured commercial products to evaluate the usefulness of the IsoVoc database for fruit flavour authenticity studies. The results revealed the possible falsification for several fruit aroma compounds.

Untargeted and Targeted Discrimination of Honey Collected by Apis cerana and Apis mellifera Based on Volatiles Using HS-GC-IMS and HS-SPME-GC-MS

Fraudulent acts regarding honey authenticity that use Apis mellifera honey as a substitute for Apis cerana honey have garnered considerable concern in China and triggered a trust crisis from consumers. In this study, untargeted metabolomics analysis was carried out based on volatile fractions in honey from A. cerana and A. mellifera using headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS). Honey from A. cerana and A. mellifera was discriminated by HS-GC-IMS profiling, principal component analysis, and orthogonal partial least-squares discrimination analysis. Tentative markers were identified from p-values and the variable importance in projection analysis and confirmed using the retention index, mass fragments, and reference standards by gas chromatography-mass spectrometry (GC-MS). A targeted method was established using the headspace solid phase coupled with microextraction GC-MS (HS-SPME-GC-MS) to quantitate the markers. The results demonstrated that the developed untargeted and targeted metabolomics approach performed well when discriminating honey from A. cerana and A. mellifera.

Perilla frutescens Britton: A Comprehensive Study on Flavor/Taste and Chemical Properties During the Roasting Process

This study investigated changes of volatile compounds, sniffing test-assisted sensory properties, taste associated-constituent and free amino acid compositions, taste description by electronic-tongue, and chemical characteristics in Perilla frutescens Britton var. acuta Kudo after roasting at 150 °C for 0–8 min. A total of 142 volatile compounds were identified, among which methyl benzoate and limonene were predominant, regardless of roasting time, and these were also detected as the major compounds in the sniffing test by GC-olfactometry. For constituent amino acids analyzed by the acid hydrolysis method using hydrochloric acid (HCl), the concentration of glutamic acid, aspartic acid, and leucine showed an increase pattern with increased roasting time, which results in umami taste, sour taste, and bitter taste, respectively. For free amino acids, valine and hydroxylysine eliciting bitter and bitter and sweet tastes, respectively, also tend to increase by roasting. The pattern of amino acid concentration by roasting was readily matched to the taste description by electronic-tongue but that of sweetness and sourness by electronic-tongue did not coincide with the amino acid composition. For the chemical properties, total phenolic content, antioxidative capacity, and browning intensity tend to increase with roasting but decreased by 8 min. The results of this study provide fundamental information on perilla in both the food industry and cooking environment for the sake of increasing the utilization of perilla as a food source and ingredient.