LWT-FOOD SCIENCE AND TECHNOLOGY
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2020
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IF 4.006
Mengting Zhu,You Long,Yingjie Ma,Yi Chen,Qiang Yu,Jianhua Xie,Bin Li,Jinlong Tian
This study aimed to quantitatively screen and compare the chemical compounds including protein, lipid, sucrose , total phenolics (TPC), and total titratable acidity (TTA) along with the fatty acid profile of green coffee beans from various geographical origins (China, Indonesia, Ethiopia, Kenya, Guatemala, Honduras, Brazil, and Colombia). Meanwhile, partial least squares discriminant analysis (PLS-DA) was used to investigate whether the analyzed parameters’ data can be successfully applied to differentiate the geographical origins of green coffee beans. The levels of protein, lipid, sucrose , TTA, and TPC in all samples were in the range of 13.06–15.98 g 100 g −1 , 12.88–16.29 g 100 g −1 , 7.30–11.45 g 100 g −1 , 231.43–361.21 mL 0.1 mol L −1 NaOH 100 g −1 , and 37.56–50.57 mg GAE g −1 , respectively. The fatty acid composition was dominated by C 18:2 , C 16:0 , C 18:1, and C 18:0 . The major fatty acid group was unsaturated fatty acids (USFA), accounting for 51.66–54.28% of total fatty acids. Statistical analysis showed significant differences in the chemical and fatty acid composition of green coffee beans from eight geographical origins ( P ＜ 0.05 ). Moreover, the PLS-DA results revealed excellent discrimination between the different geographical origins of green coffee beans, highlighting lipid, C 24:0 , C 22:0 , C 18:3 , C 17:0 , C 18:0 , C 20:0 , C 16:0 , and protein as discriminatory features.
研究领域:
食品科学
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化学
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产品关联
DOI
高影响因子
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
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2025
·Vol. 26
·期 15
·7293
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IF 4.9
Yiqing Luo,Min Guo,Lei Hu,Jiaxin Yang,Junyu Xu,Muhammad Rafiq,Ying Wang,Chunsong Cheng,Shaohua Zeng
Viticis Fructus (VF), a fruit known for its unique flavor profile and various health benefits, demonstrates substantial quality variations depending on its area of production. Traditional methods of production area verification based on internal compound analysis are hampered by a number of technical limitations. This investigation systematically characterized the cuticular wax composition of VF sample from a diverse variety of production areas. Quantitative analyses were conducted to evaluate the spatial distribution patterns of the wax constituents. Significant regional variations were observed: Anhui sample exhibited the highest total wax content (21.39 μg/cm 2 ), with n-alkanes dominating at 76.67%. High-latitude regions showed elevated triterpenoid acid levels, with maslinic acid (0.53 μg/cm 2 ) and ursolic acid (0.34 μg/cm 2 ) concentrations exceeding those of their low-latitude counterparts by four- and three-fold, respectively. Altitudinal influence manifested in long-chain alcohol accumulation, as triacontanol reached 0.87 μg/cm 2 in high-altitude sample. Five key biomarkers demonstrated direct quality correlations: eicosanoic acid, n-triacontane, dotriacontanol, β-amyrin, and α-amyrin. This study established three novel origin identification protocols: single-component quantification, multi-component wax profiling, and wax ratio analysis. This work not only reveals the latitudinal dependence of VF wax composition, but also provides a scientific framework for geographical authentication. Our findings advance wax-based quality evaluation methodologies for fruit products, offering practical solutions for production area verification challenges in food raw materials.
研究领域:
食品科学
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分析化学
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植物生物化学
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地球化学
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农业科学
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产品关联
DOI
PubMed
高影响因子
Food Chemistry-X
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2025
·
IF 8.2
Chongxin Liu,Simona Grasso,Nigel Patrick Brunton,Qi Yang,Shaobo Li,Li Chen,Dequan Zhang
The origin traceability of lamb is a longstanding concern for consumers. Despite the widespread application of untargeted metabolomics in meat origin traceability, challenges remain in achieving rapid and accurate identification of biomarkers. This study utilized untargeted metabolomics to analyse five breeds of geographical indication lamb, obtaining profile data comprising a total of 4139 metabolites. Using random forest recursive feature elimination, 29 potential biomarkers were initially identified, which showed significant breed-specific and production environment-related variations. Upon further assessment, a refined panel of 14 metabolic biomarkers demonstrated optimal accuracy and robustness in tracing lamb origin. When combined with the Naive Bayes algorithm, these biomarkers yielded the highest classification accuracy among all evaluated machine learning methods. The random forest recursive feature elimination presents a practical approach for handling high-dimensional metabolomics datasets compared to previous analytical methods. These findings also provide valuable insights into the development of machine learning-based biomarker panels, greatly enhancing the breed-specific traceability of lamb.
研究领域:
食品科学
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分析化学
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代谢组学
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机器学习
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畜牧学
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食品真实性鉴定
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产品关联
DOI
PubMed
高影响因子
Foods
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2025
·Vol. 14
·期 19
·3381
·
IF 5.1
Jiaqi Liu,Hao Duan,Li Wang,Rui Qin,Jiao Liu,Hong Liu,Shuyuan Bao,Wenjie Yan
This study aimed to systematically characterize the volatile organic compound (VOC) profiles of safflower (Carthamus tinctoriusL.) from eight major production regions, providing a scientific basis for quality evaluation and geographical traceability. VOC profiling was conducted using gas chromatography–ion mobility spectrometry (GC–IMS), and regional differences were assessed through multivariate statistical analyses, including Principal Component Analysis (PCA), Orthogonal Partial Least Squares Discriminant Analysis (OPLS–DA), Euclidean distance, and hierarchical clustering. Key differential compounds were identified by variable importance in projection (VIP) and relative odor activity value (ROAV) analyses, with aldehydes and esters emerging as the primary contributors to the discrimination of samples across regions. VOC fingerprints of safflower were further established, and a combined VIP–ROAV strategy was proposed for the screening of characteristic compounds. These findings provide a reliable reference for safflower quality control and offer practical guidance for its geographical authentication in the food industry.
研究领域:
植物化学
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代谢组学
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食品科学
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分析化学
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天然产物化学
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质量控制
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地理标志产品
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产品关联
DOI
PubMed
高影响因子
FOOD CONTROL
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2024
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IF 5.6
Yuean Chu,Mingyue Yu,Yunxing Li,Suoxian Yang,Hongyan Bi
Tracement of the origin of seafoods and aquatic products is an important issue for avoiding the falsification of production regions of aquatic products. Herein, by analyzing black tiger shrimp ( Penaeus monodon ) as a model of aquatic products, we demonstrated a method to trace the origin of aquatic products by analyzing the gut microbiome of black tiger shrimp ( Penaeus monodon ) collected from three commercial farms in China, via matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis. Multivariate analysis was executed on the obtained mass spectrometric datasets of bacteria extracted and collected from shrimp samples with different production regions. The gut microorganisms of black tiger shrimps can be identified by scoring the gut microbiota of black tiger shrimps collected from three producing areas. The black tiger shrimp from three production regions were found with distinguished characteristics of bacterial prevalence in their digestive gland microbiota. The dominant bacteria genus in digestive gland microbiota from black tiger shrimp samples from the three production regions are completely different. Single-blind shrimp samples with unknown production region was successfully screened by comparing the detected MS data in different ways. This strategy can trace the production region of the analyzed shrimp samples in a quick and efficient mode. The application of the present protocol was further demonstrated by analyzing the biometric species from gill tissue of Chinese mitten crab ( Eriocheir sinensis ) samples collected from crab-producing areas in Jiangsu Province (China), that is, Taihu Lake, Gaoyou Lake, and Hongze Lake for tracing their production area. It is expected to extend the presently developed method to provide clues for the origin traceability of other aquatic products.
研究领域:
水产养殖
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食品科学
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微生物学
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质谱分析
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产品关联
DOI
高影响因子
EUROPEAN FOOD RESEARCH AND TECHNOLOGY
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2025
·
IF 3.2
Liu Nan-nan,Ren Qing-dan,Li Long,Wang Li-na,Shi Guang-liang,Qin Shou-tao
Apis cerana honey from Changbai Mountain (CBS honey), produced in northeastern China, is a high-quality specialty honey that has long been recognized as a natural health product with medicinal properties. In this study, UPLC-MS/MS metabolomics and ultra-fast proteomics technologies were employed to analyze the differences in metabolites and proteins among Apis cerana honey samples collected from various Chinese regions, including Jilin, Sichuan, Hainan, Hubei, and Tibet. Through an integrated multi-omics analysis, we identified candidate characteristic compounds, including 12 potential characteristic metabolites and 13 characteristic proteins, to differentiate CBS honey from Apis cerana honeys produced in other regions. These findings provide foundational reference for the authentication and geographical origin traceability of CBS honey.
研究领域:
食品科学
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代谢组学
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蛋白质组学
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分析化学
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产地溯源
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产品关联
DOI
高影响因子
LWT-FOOD SCIENCE AND TECHNOLOGY
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2022
·
IF 6.056
Huan Cheng,Wenyan Wu,Jin Chen,Haibo Pan,Enbo Xu,Shiguo Chen,Xingqian Ye,Jianle Chen
Black wolfberries ( Lycium ruthenicum Murray) establish various biological activities, owing to anthocyanins, polysaccharides, pectin and so on. However, minor appearance differences are found in black wolfberries from different geographical origins. Thus, in this study, total phenolic content (TPC), total flavonoid content (TFC) and total anthocyanin content (TAC) were determined in black wolfberries from four provinces in China (Xinjiang, Qinghai, Gansu, Ningxia Provinces) for obtaining a distinguishable chemical index. Compared with TPC and TFC, TAC largely was affected by environment conditions, and thus, it may be a good chemical marker for geographical origin identification. Then, anthocyanin profiles were analysed by ultra-performance liquid chromatography (UPLC) coupled with triple quadrupole (triple Q)-time-of-flight mass spectrometry (TOF-MS), and principal component analysis (PCA) was applied for geographical origin identification based on anthocyanin fingerprints. A total of 17 anthocyanins were tentatively determined including two new individual anthocyanins, delphinidin-3-rutinoside ( cis - p -coumaroyl)-5-O-diglucoside and delphinidin-3-rutinoside ( trans - p -coumaroyl)-5-O-diglucoside. PCA indicated that individual anthocyanin contents calculated according to HPLC data and raw HPLC data both allowed a clear separation of geographical origins of black wolfberry fruits, explaining more than 95% of information of the samples. The present study could provide a scientific guidance for distinguishing the black wolfberry from different geographical origins.
研究领域:
食品科学
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分析化学
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植物化学
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地理标志
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产品关联
DOI
高影响因子
TALANTA
·
2025
·
IF 6.1
Zixuan Zhang,Xiaogang Lu,Meng Jin,Runli Gao,Chengxin Pei,Hongmei Wang
Organophosphorus nerve agents (OPNAs), including G-agents, EGA (ethyltabun, phosphonamidic acid, P -cyano- N , N -diethyl-, ethyl ester) and V-agents, VM ( O -ethyl S -(2-diethylaminoethyl) phosphonothiolate), are highly toxic chemical warfare agents (CWAs) with severe risks to human health and environmental security. This study proposes a chemometric-driven framework for forensic tracing of their synthetic pathways using high-resolution GC × GC-TOFMS. By integrating advanced statistical analysis, we identified 160 synthesis-associated chemical attribution signatures (CAS) for EGA and 138 process-specific CAS for VM, with 11 overlapping markers, including ethoxyphosphates and diethylaminoethylamine derivatives. Key distinguishing features include sulfur-containing derivatives (e.g., phosphorothioates) for VM and cyanide byproducts for EGA. These data were visualized through innovative chord diagrams and heatmaps, offering unprecedented insights into compound-sample relationships critical for forensic traceability. Multivariate classification using Hierarchical Cluster Analysis (HCA) and Partial Least Squares Discriminant Analysis (PLS-DA) achieved exceptional accuracy—97.2 % for EGA and 100 % for VM via HCA, and 100 % for both agents via PLS-DA. Robust k-fold cross-validation (k = 5 and 10) further confirmed model reliability, with R 2 values approaching unity. This work establishes a comprehensive CAS database and a scalable analytical framework, advancing forensic capabilities from reactive detection to proactive, intelligence-driven prevention.
研究领域:
分析化学
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法庭科学
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化学计量学
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环境毒理学
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化学战剂
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数据科学
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产品关联
DOI
PubMed
高影响因子
FOOD CHEMISTRY
·
2022
·
IF 9.231
Yuan Pan,Hui-Wen Gu,Yi Lv,Xiao-Li Yin,Ying Chen,Wanjun Long,Haiyan Fu,Yuanbin She
Identifying geographical origins of red wines made in specific regions is of significance since the false claim of geographical origins has been frequently exposed in China's wine industry. In this work, an untargeted metabolomic approach based on UPLC-QTOF-MS was established to discriminate geographical origins of Chinese red wines. The principal component analysis (PCA) showed significant differences between wine samples from three famous geographical origins in China. The metabolites contributing to the differentiation were screened by orthogonal partial least squares-discriminant analysis (OPLS-DA) with pairwise modeling. 40 and 46 differential metabolites in positive and negative ionization modes were putatively identified as chemical markers. Furthermore, heatmap visualization and OPLS-DA models were constructed based on these identified markers and external verification wine samples from different regions were successfully discriminated, with recognition rate up to 96.7%. This study indicated that UPLC-QTOF-MS-based untargeted metabolomics has great potential for the geographical origin traceability of Chinese red wines.
研究领域:
食品科学
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分析化学
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代谢组学
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葡萄酒科学
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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）