ANALYTICAL LETTERS
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2023
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IF 2
Xinlei Zhang,Wenbao Jia,Xinru Tang,Qing Shan,Qiyan Chen,Can Cheng,Jinfa Shao,Yongsheng Ling,Daqian Hei
Teas of the same type in a small growing area are generally similar, and identification of their detailed geographic origin is challenging and interesting. In this study, a convenient method for distinguishing Pu-erh teas from nearby locations was developed by combining two spectroscopic techniques with chemometric methods. The distinction was based on the difference in the mineral elements and organic metabolites from tea infusions. First, Pu-erh tea was infused with water at 90 °C for 30 min. Total reflection X-ray fluorescence and ultraviolet-visible (UV-Vis) spectroscopies were used to determine the elements (P, S, K, Ca, Mn, and Ni) and organic metabolites (caffeine and polyphenols), respectively. Chemometric methods were applied to classify the origin based on the component. The proposed method was used to test samples collected from 10 mutually adjacent high-altitude villages in Mengku, Lincang, Yunnan, China. The developed user-friendly method was successfully used for the rapid evaluation of the composition, enabling the identification of the geographic origins of Pu-erh tea. Mn, caffeine, and polyphenols were found to be the key origin markers. Compared to principal component analysis, linear discriminant analysis models exhibited high discrimination performance with 100% predictive ability to distinguish the geographic origins of Pu-erh teas over a small production area. This rapid and simple method may be used to solve classification problems in tea quality control and management.
研究领域:
食品科学
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分析化学
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DOI
高影响因子
JOURNAL OF CHROMATOGRAPHY A
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2024
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IF 3.8
Wenhui Lu,Chunli Ding,Mingshuo Zhu
The process of globalization and industrialization has resulted in a rise in the theft of coal and other related products, thereby becoming a focal point for forensic science. This situation has engendered an escalated demand for effective detection and monitoring technologies. The precise identification of coal trace evidence presents a challenge with current methods, owing to its minute quantity, fine texture, and intricate composition. In this study, we integrated machine learning with the identification of volatiles to accurately differentiate coal geographical origins through the application of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). The topographic distribution of volatiles in coals was visually depicted to elucidate the subtle distinctions through spectra and fingerprint analysis. Additionally, four supervised machine learning algorithms were developed to quantitatively predict the geographical origins of natural coals utilizing the HS-GC-IMS dataset, and these were subsequently compared with unsupervised models. Remarkable volatile compounds were identified through the quantitative analysis and optimal Random Forest model, which offered a rapid readout and achieved an average accuracy of 100 % in coal identification. Our findings indicate that the integration of HS-GC-IMS and machine learning is anticipated to enhance the efficiency and accuracy of coal geographical traceability, thereby providing a foundation for litigation and trials.
研究领域:
法医学
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分析化学
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数据科学
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DOI
PubMed
高影响因子
FOOD CHEMISTRY
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2022
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IF 9.231
Zhiqing Liu,Mantong Zhao,Xinwen Wang,Chuan Li,Zhongyuan Liu,Xuanri Shen,Dayong Zhou
The present study sought to analyze the lipid profiles of oyster Crassostrea gigas from Yellow Sea (YS), East China Sea, and South China Sea (SCS) through the untargeted lipidomics strategy based on UPLC-Q-Exactive Orbitrap mass spectrometry and multivariate statistics. The results elucidated that geographical differences had profound effects on the lipid content, composition, and lipid molecular profiles. Notably, oysters from the YS group contained the highest lipid content, including triacylglycerol, diacylglycerols, and the majority of phospholipid molecule species, while oysters from the ECS group contained most of the phosphatidylcholine species and the SCS group contained most of the sphingolipid species. Totally, 1155 lipid molecular species belonging to 21 subclasses were identified; of them, 45 lipid molecular species could serve as differential marker for lipid of oysters from different sea areas. Overall, lipidomics could be a potential approach for discrimination of lipid characters between marine shellfishes for geographical origin traceability.
研究领域:
海洋生物学
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分析化学
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食品科学
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DOI
高影响因子
FOOD CHEMISTRY
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2025
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IF 9.8
Minrui Zhou,Ting Li,Lingling Shen,Qisheng Zhong,Taohong Huang,Ting Zhou
This study introduces a method for authenticating organic milk and determining its geographic region using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Both lipids and peptides were analyzed, and their combined dataset significantly improved classification accuracy when integrated with machine learning models. To improve method reproducibility, a binary matrix composed of α-cyano-4-hydroxycinnamic acid and 2,5-dihydroxybenzoic acid, combined with a vacuum drying strategy, was implemented. This approach reduced the relative standard deviation by approximately 25 % compared to traditional matrices. Multivariate statistical analysis identified key lipids and peptides as markers for discriminating organic from conventional milk and for geographic region classification. Integrating the lipid-peptide dataset with machine learning achieved up to 100 % accuracy, outperforming models based on single-dataset. Additionally, two-way ANOVA revealed that farming system, geographic region and their interactions significantly influenced milk composition. This method demonstrates the potential of combining MALDI-TOF MS with machine learning to prevent organic milk fraud.
研究领域:
食品科学
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分析化学
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产品关联
DOI
PubMed
高影响因子
JOURNAL OF PHARMACEUTICAL AND BIOMEDICAL ANALYSIS
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2025
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IF 3.1
Xinyi Jiao,Rongrong Li,Simon Sani Ocholi,Haitao Wang,Tongcan Cui,Biying Chen,Liming Wang,Zhifei Fu,Erwei Liu,Fengchao Wang,Lifeng Han
Huanglian (HL) is a member of the Ranunculaceae family, including Coptis chinensis Franch., Coptis deltoidea C. Y. Cheng et Hsiao, or Coptis teeta Wall. The dried rhizomes are highly esteemed herbal medicine in Chinese pharmacopeia. However, the composition of HL is complex, and current identification technologies are insufficient for conducting a comprehensive analysis of HL, leading to major obstacles in quality control. Therefore, an in-depth exploration of the influence of species diversity and geographic provenance on the chemical profile of HL is imperative for its rational application and quality assurance. To comprehensively analyze compounds in HL samples from diverse geographical regions, this study employed an integrated approach combining offline two-dimensional ultra-high-performance liquid chromatography coupled with quadrupole-Orbitrap mass spectrometry (2D-LC-MS/MS) with online 2D-LC-MS/MS. This dual-platform strategy enabled detailed characterization of complex compound profiles. Additionally, the retention time prediction (RT-Ensemble Pred) models were utilized to predict and identify the retention times of unknown compounds, which particularly facilitated the differentiation of isomers. The comprehensive research resulted in the identification of 150 chemical constituents in HL, including 72 isomers. Furthermore, the compounds were analyzed and categorized according to mathematical classification models, allowing for distinction between various geographical origins. Based on unexposed data, the model demonstrated robust predictive capability, enabling the selection of 20 distinctive characteristic compounds with prominent features for use in geographical origin discrimination. Overall, this multidimensional investigation significantly enhanced our understanding of the chemical composition and inherent variability of HL plant resources, providing crucial technical underpinnings and methodological insights for the comprehensive exploitation and utilization of HL in biomedical and pharmaceutical applications.
研究领域:
中药学
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分析化学
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植物化学
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产品关联
DOI
PubMed
高影响因子
FOOD RESEARCH INTERNATIONAL
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2024
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IF 7
Haolei Han,Xiangxin Lin,Yuxuan Wu,Houru Li,Qi Jia,Changmin Hu,Yixuan Lin,Guangqin Liao,Yongzhong Qian,Jing Qiu
The Large Yellow Croaker (LYC) with rich lipids offers numerous health benefits, yet its lipid profile remains underexplored. Therefore, the lipids of LYC were comprehensively profiled and compared based lipidomics. Higher nutritional value of LYC was identified based on lipid and fatty acid assessment, particularly ovary and brain. A total of 963 lipid species belonging to 47 lipid subclasses were identified, exhibiting higher levels of glycerophospholipids (GPs) and sphingolipids (SPs) in the brain, as well as high levels of glycolipids (GLs) in the muscle. Furthermore, unique lipid subclasses were detected in the brain (Acylcarnitine (CAR), Alpha-hydroxy-N-stearoyl phytosphingosine (Cer-AP)) and ovary (N-arachidonoyl glycine (NAGly)). Notably, 8 lipid subclasses were selected as potential contributors for four tissues differentiation. Additionally, identification of LYC from various origins was achieved through lipidomics for the first time. LYC from Zhejiang and Fujian provinces could be distinguished by 100 lipid biomarkers. Most different lipids significantly negatively correlated with seawater pH and dissolved oxygen, but positively correlated with netting density, depth, environmental temperature and salinity. This comprehensive analysis provided valuable insights into LYC’s nutritional values and origin identified.
研究领域:
水产科学
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生物化学
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食品科学
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DOI
PubMed
高影响因子
JOURNAL OF FOOD COMPOSITION AND ANALYSIS
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2019
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IF 2.994
Yan Liu,Zhenzhen Xia,Liyun Yao,Yang Wu,Yan Li,Shan Zeng,Hao Li
Near-infrared spectroscopy (NIRS) combined with chemometric methods were used to discriminate the sesame oils from different Chinese provinces and determinate the lignans (sesamin and sesamolin) in these sesame oils. The geographic discriminant model was constructed by principal component analysis (PCA) combining with linear discriminant analysis (LDA), and the quantitative analysis models of lignans were built using partial least squares (PLS) regression. Multiplicative scatter correction (MSC) and competitive adaptive reweighted sampling (CARS) were adopted to optimize the regression models. It was found that the discriminant model could recognize the sesame oils from different Chinese provinces correctly, and the contents of sesamin and sesamolin calculated from the optimized models and high-performance liquid chromatography (HPLC) analysis are rather close. Reasonable results proved the feasibility of near-infrared spectroscopy (NIRS) combined with chemometric methods for geographic origin of sesame oils and quantitate analysis of lignans in sesame oils.
研究领域:
食品科学
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分析化学
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产品关联
DOI
高影响因子
MICROCHEMICAL JOURNAL
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2024
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IF 4.9
Fen Wang,Junfeng Fan,Yabin An,Guoliang Meng,Bingyu Ji,Yi Li,Caihong Dong
Ophiocordyceps sinensis (OS) is a unique and precious medicinal fungus endemic to the Tibetan Plateau, growing underground for the majority of its lifecycle. The mineral composition of OS is a distinctive feature, yet there is currently a lack of comprehensive mineral profiles. The concerns regarding excessive heavy metals and associated health risks significantly impact the development of the OS industry. Furthermore, OS samples from various production areas exhibit distinct qualities, resulting in significant price differences. Mineral profiles hold great potential for origin tracing. Consequently, there is an urgent need for quality evaluation, health risk assessment, and geographic origin tracing of OS by mineral element analysis. Here, 96 OS samples were collected from the representative producing areas in China to investigate their mineral profiles by inductively coupled plasma-optical emission spectrometry (ICP-OES) and inductively coupled plasma-mass spectrometry (ICP-MS). Potassium (K) was found to be the most abundant mineral in the OS samples, with a mean content of 10.73 g/kg. High levels of phosphor (P), sulfur (S) and magnesium (Mg) were also detected with concentrations exceeding 1 g/kg. The mean concentrations of total arsenic in all OS samples were determined to be 8.33 mg/kg. The OS from Nagqu exhibited a relatively high quality with lower levels of lead (Pb), cadmium (Cd) and arsenic. Health risk assessment based on the total target hazard quotient (THQ) value of heavy metals of Zn, Mn, Fe, copper (Cu), nickel (Ni), chromium (Cr), Pb and Cd indicated that consumption of OS from China did not pose an obvious risk to human health at the ingestion rate declared by the Chinese Pharmacopeia. Finally, three orthogonal partial least squares discriminant analysis (OPLS-DA) models were constructed using 75 samples to trace the geographic origins. These models successfully authenticated OS samples from six producing areas and confirmed by 21 blind test samples with 90.48 % accuracy. These results affirmed that OS from different regions possessed distinct metal profiles, which could be utilized to authenticate the geographic origins of O. sinensis .
研究领域:
药用真菌学
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环境科学
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公共健康
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产品关联
DOI
高影响因子
MOLECULES
·
2023
·Vol. 28
·期 5
·2216
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IF 4.6
Baohong Song,Wei Wang,Ruipeng Liu,Jinjin Cai,Yuanyuan Jiang,Xuemei Tang,Hongfei Wu,Hui Ao,Lu Chen
The rhizome ofAtractylodes lancea(RAL) is a well-known Chinese herbal medicine (CHM) that has been applied in clinical settings for thousands of years. In the past two decades, cultivated RAL has gradually replaced wild RAL and become mainstream in clinical practice. The quality of CHM is significantly influenced by its geographical origin. To date, limited studies have compared the composition of cultivated RAL from different geographical origins. As essential oil is the primary active component of RAL, a strategy combining gas chromatography-mass spectrometry (GC-MS) and chemical pattern recognition was first applied to compare the essential oil of RAL (RALO) from different regions in China. Total ion chromatography (TIC) revealed that RALO from different origins had a similar composition; however, the relative content of the main compounds varied significantly. In addition, 26 samples obtained from various regions were divided into three categories by hierarchical cluster analysis (HCA) and principal component analysis (PCA). Combined with the geographical location and chemical composition analysis, the producing regions of RAL were classified into three areas. The main compounds of RALO vary depending on the production areas. Furthermore, a one-way analysis of variance (ANOVA) revealed that there were significant differences in six compounds, including modephene, caryophyllene, γ-elemene, atractylon, hinesol, and atractylodin, between the three areas. Hinesol, atractylon, and β-eudesmol were selected as the potential markers for distinguishing different areas by orthogonal partial least squares discriminant analysis (OPLS-DA). In conclusion, by combining GC-MS with chemical pattern recognition analysis, this research has identified the chemical variations across various producing areas and developed an effective method for geographic origin tracking of cultivated RAL based on essential oils.Keywords:Atractylodes lancea;GC-MS;essential oil;chemical pattern recognition analysis;geographic origin
研究领域:
中药学
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分析化学
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植物化学
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产品关联
DOI
PubMed
高影响因子
Food Chemistry-X
·
2025
·
IF 8.2
Yiqing Luo,Lei Hu,Kai Chen,Junyu Xu,Mengting Xiao,Shimeng Li,Yiying Yang,Ying Wang,Zhaoqi Xie,Shaohua Zeng,Chunsong Cheng
Schisandra sphenanthera fruit, a popular wild berry widely used for beverages industrial material in northeast Asian regions, urgently requires origin tracing technologies for adapting to the market rule of ‘better quality, better price’. This study first employed gas chromatography–mass spectrometry to analyze the cuticular wax of S. sphenanthera fruits from three main ecologically distinct production areas in China. The results showed that high levels of fatty acids (FA) and long-chain primary alcohols (LPA, C ≥ 26) were detected in the southwestern region (FA: 2.66 μg/cm 2 and LPA: 2.02 μg/cm 2 ); The highest aldehyde (2.12 μg/cm 2 ) and lowest sterol (0.50 μg/cm 2 ) content were detected from the central region; The lowest total wax (14.52 μg/cm 2 ) and higher sterol content (0.16 μg/cm 2 ) were detected in the eastern region. This study provided five indicative wax tracers firstly that serve as geographical indicators, enhancing knowledge of their ecological adaptability while establishing traceable chemical markers for geographical origin tracing.
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产品关联
DOI
高影响因子
FOOD CHEMISTRY
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2024
·
IF 8.5
Tianyue Liu,Yining Li,He Cheng,Ruixuan An,Xinglin Hou,Yasong Zhang,Jieyu Zhao,Hao Zhang,Jingsheng Tian,Zhiyi Yao
Metal ions (MIs) identification is essential for the safety assessment, traceability and authentication of food. Most current approaches for detecting MIs are difficult to reconcile the simplicity, sensitivity and stability simultaneously. In this work, we proposed a novel strategy for discriminating MIs based on fluorescent supramolecular nanoaggregates (SNAs). In the presence of MI, perylene diimide derivatives (PDI)-based SNAs could be formed through the multiple non-covalent interactions between them including electrostatic, coordination and π-π interactions. With the assistance of discriminant analysis (LDA), different MIs (Hg 2+ , Ag + , Cd 2+ , Fe 3+ , Cr 3+ , Fe 2+ , Zn 2+ , Cu 2+ and Pb 2+ ) were successfully identified at three different concentration levels. It featured good quantitative sensing abilities in buffer solutions and practical samples. Furthermore, a water-quality evaluation model was successfully constructed for the distinction of different sources of drinking water, and the fluorescence array sensor technology was applied for the first time to the geographical traceability of apples.
研究领域:
分析化学
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环境科学
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食品科学
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材料科学
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DOI
PubMed
高影响因子
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
·
2022
·
IF 4.831
Wanjun Long,Zikang Hu,Liuna Wei,Hengye Chen,Tingkai Liu,Siyu Wang,Yuting Guan,Xiaolong Yang,Jian Yang,Haiyan Fu
Near-infrared spectroscopy technique is a prevailing tool for quality control of foods and traditional Chinese medicines. However, it usually faced the problems of severe peak overlap, low classification accuracy and poor specificity. In this work, the potential of carbon dot-tetramethoxyporphyrin nanocomposite-based nano-effect near-infrared spectroscopy sensor combined with chemometric method was investigated for the accurate identification lily from different geographical origins. Partial least squares-discriminant analysis (PLS-DA) was used for differentiating geographical origins of lily based on the collected traditional and nano-effect near-infrared spectroscopy. Compared with traditional near-infrared spectroscopy, the nano-effect near-infrared spectroscopy obtains superior classification performance with 100% accuracy on the training and test set. The results showed that the proposed method based on near-infrared spectroscopy combined with nanocomposites and chemometrics could be considered as a promising tool for rapid discrimination of the authenticity of food and traditional Chinese medicine in the future.
研究领域:
分析化学
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传统中药研究
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产品关联
DOI
PubMed
高影响因子
危险品化学品经营许可证（带存储）