Discrimination of authenticity of Fritillariae Cirrhosae Bulbus based on terahertz spectroscopy and chemometric analysis

An efficient artificial intelligence algorithm for predicting the sensory quality of green and black teas based on the key chemical indices

The key components dominating the quality of green tea and black tea are still unclear. Here, we respectively produced green and black teas in March and June, and investigated the correlations between sensory quality and chemical compositions of dry teas by multivariate statistics, bioinformatics and artificial intelligence algorithm. The key chemical indices were screened out to establish tea sensory quality-prediction models based on the result of OPLS-DA and random forest, namely 4 flavonol glycosides of green tea and 8 indices of black tea (4 pigments, epigallocatechin, kaempferol-3-O-rhamnosyl-glucoside, ratios of caffeine/total catechins and epi/non-epi catechins). Compared with OPLS-DA and random forest, the support vector machine model had good sensory quality-prediction performance for both green tea and black tea (F1-score > 0.92), even based on the indices of fresh tea leaves. Our study explores the potential of artificial intelligence algorithm in classification and prediction of tea products with different sensory quality.

Integration of untargeted and pseudotargeted metabolomics reveals specific markers for authentication and adulteration detection of Fritillariae Bulbus using tandem mass spectrometry and chemometrics

Authentication and adulteration detection of closely related herbal medicines is a thorny issue in the quality control and market standardization of traditional Chinese medicine. Taking Fritillariae Bulbus (FB) as a case study, we herein proposed a three-step strategy that integrates mass spectrometry-based metabolomics and multivariate statistical analysis to identify specific markers, thereby accurately identifying FBs and determining the adulteration level. First, an ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based untargeted metabolomics method was employed to profile steroid alkaloids in five sorts of FB and screen potential differential markers. Then, the reliability of the screened markers was further verified by the distribution in different FB groups acquired from ultra-high performance liquid chromatography triple quadrupole mass spectrometry-based pseudotargeted metabolomics analysis. As a result, a total of 16 compounds were screened out to be the specific markers, which were successfully applied to distinguish five FBs by using discriminant analysis model. Besides, partial least squares regression models based on specific markers allowed accurate prediction of three sets of adulterated FBs. All the models afforded good linearity and good predictive ability with regression coefficient of prediction (R2p) > 0.9 and root mean square error of prediction (RMSEP) < 0.1. The reliable results of discriminant and quantitative analysis revealed that this proposed strategy could be potentially used to identify specific markers, which contributes to rapid chemical discrimination and adulteration detection of herbal medicines with close genetic relationship.

Influence of heating temperatures and storage on the odor of duck meat and identification of characteristic odorous smell compounds

To clarify the characteristic odor of compounds present in duck meat, especially reheating after storage, the effect of duck breast cooked at three temperatures (90 °C, 100 °C, 105 °C) and reheating after 7 days of storage was studied. Electronic nose analysis and sensory evaluation revealed a significant increase (p < 0.05) in reheated duck meat odor after 7 days of storage. The 90 °C treatment group had the heaviest odor, which increased by 12.19 % after seven days of storage. Using headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), 60 volatile flavor compounds were identified across various groups. Although the volatile compounds were consistent among different groups, their relative contents varied. By combining the sensory evaluation results with the Relative Odor Activity Value (ROAV) of these flavor compounds, chemometric orthogonal partial least squares discriminant analysis (OPLS-DA) was used to identify the following 9 characteristic volatile compounds: 2-methylbutanal, pentanal, octanal, heptanal, hexanal, (E)-2-octenal, (E)-2-nonenal, and 2-pentyl furan.

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.

Optimizing the Solvent Selection of the Ultrasound-Assisted Extraction of Sea Buckthorn (Hippophae rhamnoides L.) Pomace: Phenolic Profiles and Antioxidant Activity

Sea buckthorn pomace (SBP) is a by-product of sea buckthorn processing that is rich in bioactive compounds. In this study, different active ingredients were extracted by using different solvents (water, methanol, ethanol, glycerol, ethyl acetate, and petroleum ether) combined with an ultrasonic assisted method. The correlation between the active ingredients and antioxidant properties of the extract was studied, which provided a research basis for the comprehensive utilization of SBP. This study revealed that the 75% ethanol extract had the highest total phenolic content (TPC) of 42.86 ± 0.73 mg GAE/g, while the 75% glycerol extract had the highest total flavonoid content (TFC) of 25.52 ± 1.35 mg RTE/g. The ethanol extract exhibited the strongest antioxidant activity at the same concentration compared with other solvents. The antioxidant activity of the ethanol, methanol, and glycerol extracts increased in a concentration-dependent manner. Thirteen phenolic compounds were detected in the SBP extracts using UPLC-MS/MS analysis. Notably, the 75% glycerol extract contained the highest concentration of all identified phenolic compounds, with rutin (192.21 ± 8.19 μg/g), epigallocatechin (105.49 ± 0.69 μg/g), and protocatechuic acid (27.9 ± 2.38 μg/g) being the most abundant. Flavonols were found to be the main phenolic substances in SBP. A strong correlation was observed between TPC and the antioxidant activities of SBP extracts. In conclusion, the choice of solvent significantly influences the active compounds and antioxidant activities of SBP extracts. SBP extracts are a valuable source of natural phenolics and antioxidants.

Profiling of Volatile Compounds in 'Muscat Hamburg' Contaminated with Aspergillus carbonarius before OTA Biosynthesis Based on HS-SPME-GC-MS and DLLME-GC-MS

Aspergillus carbonarius is known to produce the carcinogenic ochratoxin A (OTA) in grapes. The metabolism process before OTA biosynthesis influences the content and composition of the volatile compounds in grapes. In this study, a self-established method based on QuEChERS coupled with high-performance liquid chromatography-fluorescence detection (HPLC-FLD) was used to determine the OTA levels during a seven-day contamination period. The results showed that OTA was detected on the second day after contamination with A. carbonarius. Thus, the first day was considered as the critical sampling timepoint for analyzing the volatiles in grapes before OTA biosynthesis. Additionally, the volatile compounds in grapes were analyzed using headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) and dispersive liquid-liquid microextraction gas chromatography-mass spectrometry (DLLME-GC-MS). The corresponding data were evaluated via multivariate data analysis using projection methods, including PCA and OPLS-DA. The results indicated significant differences in the nine volatile compounds in grapes contaminated with A. carbonarius before OTA biosynthesis. The results of the Pearson correlation analysis showed positive correlations between ethyl acetate, styrene, 1-hexanol and OTA; (E)-2-hexenal and nerolic acid were negatively correlated with OTA. Overall, these findings provide a theoretical basis for the early prediction of OTA formation in grape and grape products using GC-MS technology.

Cryopreservation of highly extended pig spermatozoa remodels its proteome and counteracts polyspermic fertilization in vitro

BACKGROUND

Currently, high polyspermy remains a significant obstacle to achieving optimal efficiency in in vitro fertilization (IVF) and in vitro embryo production (IVP) systems in pigs. Developing strategies that would prevent polyspermy is essential in overcoming this challenge and maximizing the potential of this reproductive biotechnology. Previous results have demonstrated that using boar spermatozoa subjected to a high-extension and reconcentration procedure and then cryopreserved resulted in significant improvements in IVF/IVP systems with high rates of monospermy and penetration.

OBJECTIVE

The aim of the present study was to unveil the molecular mechanisms that may underlie the changes in fertilization patterns exhibited by highly extended and cryopreserved boar spermatozoa.

MATERIALS AND METHODS

To achieve this goal, we used quantitative proteomic analysis (LC-ESI-MS/MS SWATH) to identify differentially abundant proteins (DAPs) between highly extended (HE) and conventionally (control; CT) cryopreserved boar spermatozoa. Prior to the analysis, we evaluated the in vitro post-thawing fertilizing ability of the sperm samples. The results demonstrated a remarkable improvement in monospermy and IVF efficiency when using HE spermatozoa in IVF compared with CT spermatozoa.

RESULTS

At the proteomic level, the combination of high-extension and cryopreservation had a significant impact on the frozen-thawed sperm proteome. A total of 45 proteins (24 downregulated and 21 upregulated) were identified as DAPs (FC > 1 or ≤1; p < 0.05) when compared with CT spermatozoa. Some of these proteins were primarily linked to metabolic processes and the structural composition of sperm cells. The dysregulation of these proteins may have a direct or indirect effect on essential sperm functions and significantly affect spermatozoa-oocyte interaction and, therefore, the sperm fertilization profile under in vitro conditions. While these findings are promising, further research is necessary to comprehend how the disturbance of specific proteins affects sperm fertilization ability.

Classification and Authentication of Lonicerae Japonicae Flos and Lonicerae Flos by Using 1H-NMR Spectroscopy and Chemical Pattern Recognition Analysis

Lonicerae japonicae flos and Lonicerae flos are increasingly widely used in food and traditional medicine products around the world. Due to their high demand and similar appearance, they are often used in a confused or adulterated way; therefore, a rapid and comprehensive analytical method is highly required. In this case, the comparative analysis of a total of 100 samples with different species, growth modes, and processing methods was carried out by nuclear magnetic resonance (1H-NMR) spectroscopy and chemical pattern recognition analysis. The obtained 1H-NMR spectrums were employed by principal component analysis (PCA), partial least-squares discriminant analysis (PLS-DA), orthogonal partial least-squares discriminant analysis (OPLS-DA), and linear discriminant analysis (LDA). Specifically, after the dimensionality reduction of data, linear discriminant analysis (LDA) exhibited good classification abilities for the species, growth modes, and processing methods. It is worth noting that the sample prediction accuracy from the testing set and the cross-validation predictions of the LDA models were higher than 95.65% and 98.1%, respectively. In addition, the results showed that macranthoidin A, macranthoidin B, and dipsacoside B could be considered as the main differential components of Lonicerae japonicae flos and Lonicerae Flos, while secoxyloganin, secologanoside, and sweroside could be responsible for distinguishing cultivated and wild Lonicerae japonicae Flos. Accordingly, 1H-NMR spectroscopy combined with chemical pattern recognition gives a comprehensive overview and provides new insight into the quality control and evaluation of Lonicerae japonicae flos.

Evaluation and comparison of physicochemical properties, volatile substances, and microbial communities of leaf mustard (Brassica juncea var. multiceps) under natural and inoculated fermentation

Due to the uncontrolled fermentation process and unstable quality of naturally fermented leaf mustard, inoculated fermentation is receiving more attention. Here, the physicochemical properties, volatile compounds, and microbial community in leaf mustard under natural fermentation (NF) and inoculated fermentation (IF) were analyzed and compared. The contents of total acid, crude fiber, and nitrite of leaf mustard were measured. Headspace-solid phase microextraction-gas chromatography-mass spectrometry and orthogonal projection on latent structure-discriminant analysis were used to analyze the differences of volatile compounds in NF and IF leaf mustard. Moreover, Illumina MiSeq high-throughput sequencing technology was employed to reveal the composition of microbiota. The results showed that the nitrite content in leaf mustard after IF (3.69 mg/kg) was significantly lower than that after NF (4.43 mg/kg). A total of 31 and 25 kinds of volatile components were identified in IF and NF, respectively. Among the detected compounds, 11 compounds caused the differences between IF and NF leaf mustard. The results of inter-group difference analysis showed that there were significant differences in fungal flora between IF and NF samples. Saccharomycetes, Kazachstania, and Ascomycota were the landmark microorganisms in IF leaf mustard and the landmark microorganisms in NF were Mortierellomycota, Sordariomycetes, and Eurotiomycetes. The abundance of probiotics (such as Lactobacillus) in IF leaf mustard (51.22%) was higher than that in NF (35.20%) and the abundance of harmful molds (such as Mortierella and Aspergillus) was opposite. Therefore, IF leaf mustard showed the potential to reduce the content of nitrite and harmful molds and increase the beneficial volatile compounds and probiotics. PRACTICAL APPLICATION: Leaf mustard of inoculated fermentation (IF) showed better fermented characteristics than natural fermentation in terms of lower nitrite content, greater beneficial volatile substances, and better potential for increasing probiotics and reducing harmful molds. These results provided a theoretical basis for IF leaf mustard and contributed to the industrial production of fermented leaf mustard.

Quantitative analysis method of Panax notoginseng based on thermal perturbation terahertz two-dimensional correlation spectroscopy

This paper proposes a Panax notoginseng (P. notoginseng) quantitative analysis based on terahertz time-domain spectroscopy and two-dimensional correlation spectroscopy (2DCOS). By imposing temperature perturbation combined with 2DCOS, the one-dimensional absorbance spectra were transformed into 2DCOS synchronous spectra, which reflected the differences in characteristic information between different P. notoginseng contents more clearly. Then, the feature information of P. notoginseng contents was extracted from the 2DCOS synchronous spectra by a competitive adaptive reweighted sampling (CARS) method and was used to build a quantitative model combined with a support vector regression machine (SVR), called 2DCOS-CARS-SVR. We obtained a more accurate analysis result than the commonly used principal component analysis (PCA)-partial least squares regression (PLSR) and PCA-SVR. The prediction set correlation coefficient and root mean square error reached 0.9915% and 0.8160%, respectively.

Comparative Analysis of the Physicochemical Properties and Metabolites of Farinose and Crisp Lotus Roots (Nelumbo nucifera Gaertn.) with Different Geographical Origins

Lotus roots are widely consumed vegetables because of their great taste and abundant nutrients, but their quality varies with the environments and cultivar. This study systematically compared farinose (Elian No. 5) and crisp (Elian No. 6) lotus root cultivars from three geographical origins. Pasting and texture characteristics verified that Elian No. 5 possessed lower hardness and lower ability to withstand shear stress and heating during cooking compared with Elian No. 6. Untargeted metabolite profiling was first performed using ultrahigh-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) combined with a Zeno trap. In total, 188 metabolites were identified based on the matching chemistry database. Multivariate analysis demonstrated that lotus roots from different cultivars and origins could be adequately distinguished. Sixty-one differential metabolites were identified among three Elian No. 5 samples, and 28 were identified among three Elian No. 6 samples. Isoscopoletin, scopoletin, and paprazine were the most differential metabolites between Elian No. 5 and Elian No. 6. These results can inform future research on the discrimination and utilization of lotus roots.

Classification of Black Mahlab seeds (Monechma ciliatum) using GC-MS and FT-NIR and simultaneous prediction of their major volatile compounds using chemometrics

The identification of geographical origin is an important factor in assessing the quality of aromatic and medicinal seeds such as Black Mahlab (Monechma ciliatum). However, at present, there are no studies concerning Black Mahlab Seeds (BMSs). To identify the geographical origin of BMSs, we have used gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared spectroscopy (FT-NIR) combined with chemometrics. Chemometrics analysis showed that FT-NIR and GC-MS can be used to discriminate the geographical origin of BMSs. FT-NIR coupled with the partial least squares regression (PLSR) was applied to develop the calibration models. The calibration models had a coefficient of determination (R_c²) of 0.82 for coumarin and 0.81 for methyl salicylate. The prediction model (R_p²) values ranged from 0.83 for coumarin to 0.77 for methyl salicylate. Overall, the chemometrics presented correct classification, and PLSR accurately predicted the volatiles, with an RMSEP range of 0.9 to 0.16 for the two volatiles targeted.

Rapid discrimination of the identity of infant formula by triple-channel models

Infant formula is related to children's life and health. However, the existing identification methods for infant formula are time-consuming, costly and prone to environmental pollution. Therefore, a simple, efficient and less polluting identification method for infant formula is urgently needed. The aim of this study was to distinguish between goat and cow infant formula using HS-SPME-GC-MS and E-nose combined with triple-channel models. The results indicated that the main difference of them attributed to thirteen volatile compounds and three sensor variables. Based on this, the linear discriminant and partial least squares discriminant analyses were conducted, and a multilayer perceptron neural network model was constructed to identify the commercial samples. There was a high percentage of correct classifications (>90%) in samples. Together, our work demonstrated that the volatile compounds of infant formula combined with chemometric analysis were effective and rapid for detecting two infant formulas.

Serum steroid metabolome on the day of oocyte retrieval in women with polycystic ovarian syndrome and its association with pregnancy outcome of in vitro fertilization

Steroid hormone level is a crucial factor affecting the outcomes of in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI). The purpose of this study was to evaluate serum steroid metabolome on the day of oocyte retrieval in women with polycystic ovarian syndrome (PCOS) and explore whether specific steroids can be potential indicators to improve the prediction of pregnancy outcomes in PCOS patients undergoing IVF/ICSI. In this study, the serum levels of 21 steroids in 89 women with PCOS and 73 control women without PCOS on the day of oocyte retrieval of the first IVF/ICSI treatment cycle were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS). All patients subsequently received good-quality embryo transfer, and the correlation between their steroid profiles and pregnancy outcomes of the first embryo transfer (ET) was retrospectively analyzed. We found PCOS patients had aberrant levels of 11 out of 21 steroid hormones compared to control individuals, with androgen steroid hormones being considerably enhanced. Enzyme activity evaluation indicated that PCOS women might have abnormal activity of CYP17A1, CYP21A2, CYP11B2, CYP19A1, HSD3B, HSD11B, and HSD17B. Additionally, the level of 18-hydroxycorticosterone (p = 0.014), corticosterone (p = 0.035), and 17-hydroxypregnenolone (p = 0.005) were markedly higher in live birth group than in non- live birth group for PCOS women following frozen embryo transfer (FET). Multiple logistic regressions indicated that 18-hydrocorticosterone and 17-hydroxypregnenolone were independently associated with live birth outcomes of PCOS women following FET. Receiver operating characteristic (ROC) curve analysis revealed that 0.595ng/mL for 18-hydrocorticosterone level (AUC: 0.6936, p = 0.014).and 2.829ng/mL for 17-hydroxypregnenolone level (AUC: 0.7215, p = 0.005) were the best cutoff values to predict live birth outcomes of PCOS. In conclusion, the blood steroid metabolome was closely related to the IVF/ICSI outcomes of PCOS patients. 18-hydroxycorticosterone and 17-hydroxypregnenolone might be potential indicators to predict pregnancy outcomes of PCOS undergoing IVF/ICSI treatment. AVAILABILITY OF DATA AND MATERIALS: The data used in the current study are available from the database of Women's Hospital, School of Medicine, Zhejiang University on reasonable request.

Quality changes of HHP orange juice during storage: Metabolomic data integration analyses

High hydrostatic pressure (HHP) is a non-thermal method of sterilizing orange juice. However, knowledge of the quality variation during its storage is limited. This study aimed to comprehensively analyze metabolite variations during HHP orange juice storage using gas chromatography-mass spectrometer and liquid chromatography-mass spectrometry. Fifty-seven volatiles and 49 non-volatiles were identified. Partial least square analysis results showed that 21 days was a dividing point for metabolites highly varied. Results of relative odor activity value showed nonanal, methyl butanoate, and ethyl butanoate decreased after six days, which might reduce fruity flavor. After 21 days, over 60 % of metabolites such as linalool, α-pinene, and ascorbic acids decreased while α-terpineol and limonin increased, which would likely result in a change of coniferous, tarry, and bitter, as well as decreased organoleptic quality and antioxidative activities. This study provides a theoretical basis to optimize the shelf-life of HHP orange juice and advice for consumers' choices.

Variations in the morphological and chemical composition of the rhizomes of Polygonatum species based on a common garden experiment

Polygonatum species have great potential in fighting chronic and hidden hunger. In this study, five Polygonatum species collected from different populations were cultivated in a common garden for 4 years. The species mainly differed in yield, saponin and polysaccharide contents, stem diameter, leaf width, inflorescence length, and floret inflorescence length. P. cyrtonema (PC) provides high-quality yield when planted in Zhejiang, with output as high as 7.5 tons per hectare and a promising breeding potential. Moreover, stem diameter can be used as an indicator of the harvest in the screening of varieties. In addition, the formation of plant genetic traits from different provenances is affected by the climatic factors of the origin. Furthermore, near-infrared spectroscopy combined with chemometrics for polysaccharide and saponin quantitation provides a rapid assessment of PC quality. Our findings provide a scientific basis for the development and sustainable utilization of PC as a high-yielding and high-quality forest crop.

Non-destructive preservation state estimation of waterlogged archaeological wooden artifacts

Non-destructive preservation state estimation is an essential prerequisite for the preservation and conservation of waterlogged archaeological wooden artifacts. Herein, Near Infrared (NIR) spectroscopy coupled with orthogonal partial least squares discriminant analysis (OPLS-DA) were applied to assess sixty-four waterlogged archaeological woods collected from seven excavation sites in the period range of 2900 BCE-1912 CE, aiming at developing a non-destructive, accurate and rapid preservation state estimation methodology. The role of non-decayed recent wood of relevant species on preservation state estimation was studied in prior, showing the use of non-decayed recent wood could not improve the predictive ability. Besides, the high variability in terms of chemical structure between archaeological softwoods and archaeological hardwoods did affect the preservation state estimation. Thus, a simple OPLS-DA model of non-destructively distinguishing archaeological hardwoods from softwoods, R²X_cum of 0.659, R²Y_cum of 0.836 and Q²_cum of 0.763, was established to avoid and overcome destructive approach for wood identification. Then, the well-defined three grouped separations of slightly-decayed, moderately-decayed and severely-decayed waterlogged archaeological woods were revealed in OPLS-DA models, providing R²X_cum of 0.793, R²Y_cum of 0.738, Q²_cum of 0.680, and R²X_cum of 0.780, R²Y_cum of 0.901, Q²_cum of 0.870, for waterlogged archaeological hardwoods and waterlogged archaeological softwoods respectively. Potential predictive wood spectral bands were screened and tentatively identified as hydroxyls of crystalline cellulose, acetyl groups of hemicelluloses, C-H bands of lignin, which guaranteed the elimination of non-structural compounds, such as water and inorganic components interference. Furthermore, the developed NIR methodology was validated by an extensively used destructive method consisting of anatomical characteristics, maximum water content and basic density analyses. The results indicated that NIR coupled to chemometrics could non-destructively and accurately predict the preservation states of waterlogged archaeological wooden artifacts and avoid the interference of water and inorganic deposits.

Authenticity and species identification of Fritillariae cirrhosae: a data fusion method combining electronic nose, electronic tongue, electronic eye and near infrared spectroscopy

This paper focuses on determining the authenticity and identifying the species of Fritillariae cirrhosae using electronic nose, electronic tongue, and electronic eye sensors, near infrared and mid-level data fusion. 80 batches of Fritillariae cirrhosae and its counterfeits (including several batches of Fritillaria unibracteata Hsiao et K.C. Hsia, Fritillaria przewalskii Maxim, Fritillaria delavayi Franch and Fritillaria ussuriensis Maxim) were initially identified by Chinese medicine specialists and by criteria in the 2020 edition of Chinese Pharmacopoeia. After obtaining the information from several sensors we constructed single-source PLS-DA models for authenticity identification and single-source PCA-DA models for species identification. We selected variables of interest by VIP value and Wilk's lambda value, and we subsequently constructed the three-source fusion model of intelligent senses and the four-source fusion model of intelligent senses and near-infrared spectroscopy. We then explained and analyzed the four-source fusion models based on the sensitive substances detected by key sensors. The accuracies of single-source authenticity PLS-DA identification models based on electronic nose, electronic eye, electronic tongue sensors and near-infrared were respectively 96.25%, 91.25%, 97.50% and 97.50%. The accuracies of single-source PCA-DA species identification models were respectively 85%, 71.25%, 97.50% and 97.50%. After three-source data fusion, the accuracy of the authenticity identification of the PLS-DA identification model was 97.50% and the accuracy of the species identification of the PCA-DA model was 95%. After four-source data fusion, the accuracy of the authenticity of the PLS-DA identification model was 98.75% and the accuracy of the species identification of the PCA-DA model was 97.50%. In terms of authenticity identification, four-source data fusion can improve the performance of the model, while for the identification of the species the four-source data fusion failed to optimize the performance of the model. We conclude that electronic nose, electronic tongue, electronic eye data and near-infrared spectroscopy combined with data fusion and chemometrics methods can identify the authenticity and determine the species of Fritillariae cirrhosae. Our model explanation and analysis can help other researchers identify key quality factors for sample identification. This study aims to provide a reference method for the quality evaluation of Chinese herbs.

Application of Analytical Technologies in the Discrimination and Authentication of Herbs from Fritillaria: A Review

Medicinal plants of Fritillaria are widely distributed in numerous countries around the world and possess excellent antitussive and expectorant effects. In particular, Fritillariae Bulbus (FB) as a precious traditional medicine has thousands of years of medical history in China. Herbs of Fritillaria have a high market value and demand while limited by harsh growing circumstances and scarce wild resources. As a consequence, fraudulent behaviors are regularly engaged by the unscrupulous merchants in an attempt to reap greater profits. It is of an urgent need to evaluate the quality of Fritillaria herbs and their products using various analytical instruments and techniques. This review has scrutinized approximately 160 articles from 1995 to 2022 published on the investigation of Fritillaria herbs and related herbal products. The botanical classification of genus Fritillaria, types of counterfeits, technologies applied for differentiating Fritillaria species were comprehensively summarized and discussed in the current review. Molecular and chromatographic identification were the dominant technologies in the authentication of Fritillaria herbs. Additionally, we brought some potential and promising technologies and analytical strategies into attention, which are worthy attempting in the future researches. This review could conduce to excellent reference value for further investigations of the authenticity assessment of Fritillaria species.

Vibrational Spectroscopy Combined with Chemometrics in Authentication of Functional Foods

Many foods have both edible and medical importance and are appreciated as functional foods, preventing diseases. However, due to unscrupulous vendors and imperfect market supervision mechanisms, curative foods are prone to adulteration or some other events that harm the interests of consumers. However, traditional analytical methods are unsuitable and expensive for a broad and complex application. Therefore, people urgently need a fast, efficient, and accurate detection method to protect self-interests. Recently, the study of target samples by vibration spectrum shows strong qualitative and quantitative ability. The model established by platform technology combined with the stoichiometric analysis method can obtain better parameters, which it has good robustness and can detect functional food efficiently, quickly and nondestructive. The review compared and prospect five different vibrational spectroscopic techniques (near-infrared, Fourier transform infrared, Raman, hyperspectral imaging spectroscopy and Terahertz spectroscopy). In order to better solve some of the actual situations faced by certification, we explore and through relevant research and investigation to appropriately highlight the applicability and importance of technology combined with chemometrics in functional food authentication. There are four categories of authentication discussed: functional food authenticated in source, processing method, fraud and ingredient ratio. This paper provides an innovative process for the authentication of functional food, which has a meaningful reference value for future review or scientific research of relevant departments.

A Study on the Time-Effect and Dose-Effect Relationships of Polysaccharide from Opuntia dillenii against Cadmium-Induced Liver Injury in Mice

The purpose of this study was to evaluate the protective effect of Opuntia dillenii (Ker-Gaw) Haw. polysaccharide (ODP) against cadmium-induced liver injury. Cadmium chloride (CdCl2) was used to construct a mice evaluation model, and the indicators chosen included general signs, liver index, biochemical indicators, blood indicators, and pathological changes. A dose of 200 mg/kg ODP was applied to the mice exposed to cadmium for different lengths of time (7, 14, 21, 28, and 35 days). The results showed that CdCl2 intervention led to slow weight growth (reduced by 13−20%); liver enlargement; significantly increased aspartate aminotransferase (AST, 45.6−52.0%), alanine aminotransferase (ALT, 26.6−31.3%), and alkaline phosphatase (ALP, 38.2−43.1%) levels; and significantly decreased hemoglobin (HGB, 13.1−15.2%), mean corpuscular hemoglobin (MCH, 16.5−19.3%), and mean corpuscular hemoglobin concentrations (MCHC, 8.0−12.7%) (p < 0.01). In addition, it led to pathological features such as liver cell swelling, nuclear exposure, central venous congestion, apoptosis, and inflammatory cell infiltration. The onset of ODP anti-cadmium-induced liver injury occurred within 7 days after administration, and the efficacy reached the highest level after continuous administration for 14 days, a trend that could continue until 35 days. Different doses (50, 100, 200, 400, and 600 mg/kg) of ODP have a certain degree of protective effect on cadmium-induced liver injury, showing a good dose−effect relationship. After 28 days of administration of a 200 mg/kg dose, all pathological indicators were close to normal values. These findings indicated that ODP had positive activity against cadmium-induced liver injury and excellent potential for use as a health food or therapeutic drug.

Screening of specific quantitative peptides of beef by LC-MS/MS coupled with OPLS-DA

A rapid, simple, and efficient analysis methodology for screening specific quantitative peptides of beef was established based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) coupled with orthogonal partial least squares-discriminant analysis (OPLS-DA). The OPLS-DA model was built to select species-specific peptides that make a significant contribution to classification. Peptides with statistical significance were selected based on the variable importance in the projection (VIP) values and univariate P values. After the workflow of the statistical process, three specific quantitative peptides were identified by using homemade products with different beef contents. A quantification method for selected specific quantitative peptides was established by using LC-MS/MS. The quantitative results were applied to commercialized beef products. The developed method has high sensitivity, specificity, and repeatability. The results of this study proved that the integration of LC-MS/MS coupled with OPLS-DA is an efficient method for screening specific quantitative peptides and identification of the authenticity of meat products.