JOURNAL OF FOOD SCIENCE
·
2026
·Vol. 91
·期 4
·e71036
·
IF 4.1
Xiaohong Yu,Lihui Chu,Rongqing Yang,Haoxiang Wang,Shuyan Yao,Xingyu Pan,Xingyue Wang,Xiaodong Chen
Monosaccharide pretreatment has been proposed as a strategy to modulate coffee aroma; however, its effects on volatile formation and sensory quality remain unclear. In this study, green Arabica Catimor coffee beans were soaked in arabinose, glucose, galactose, or mannose solutions (4% and 8%, w/w), then roasted and subjected to chemical and sensory analyses. Volatile compounds were characterized by SPME-GC-MS, and sensory evaluation followed the Specialty Coffee Association protocol. Thirty-five volatile compounds were identified, with furans as the predominant class. Monosaccharide pretreatment significantly altered volatile composition, notably increasing key furan derivatives such as 2-furanmethanol and 5-methyl-2-furancarboxaldehyde ( p < 0.05), while reducing phenolic compounds associated with smoky off-flavors. Arabinose treatment showed the most pronounced enhancement of desirable aroma compounds. Although pH values were minimally affected, color development was significantly enhanced. Sensory analysis demonstrated that arabinose pretreatment significantly improved sweetness, flavor, and overall acceptance compared with control samples ( p < 0.05). These results indicate that monosaccharide pretreatment, particularly with arabinose, is an effective approach for improving coffee aroma and sensory quality through modulation of volatile formation. This study proposes a viable method to modulate flavor compound formation in coffee, offering potential applications for targeted flavor optimization in the coffee industry.
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PubMed
高影响因子
Food Chemistry-X
·
2024
·
IF 6.5
Jianfeng Liang,Hailin Wu,Mingfei Lu,Ya Li
This study used headspace solid-phase microextraction-gas chromatography–mass spectrometry and multivariate statistical analysis to comprehensively analyze the volatile components in Liupao tea samples throughout fermentation. In total, 1009 volatile organic compounds were detected and identified, including terpenoids, heterocyclic compounds, esters, ketones, hydrocarbons, alcohols, aromatics, and acids. Principal component and hierarchical cluster analyses, characterize the volatile components of Liupao tea samples were characterized at various fermentation stages. Orthogonal partial least squares discriminant analysis identified 248 differentiating compounds (VIP ≥ 1, P < 0.05, and |Log 2 FC| ≥ 1.0) during fermentation. K-means clustering analysis showed that 11 metabolites increased significantly throughout the fermentation process, whereas 31 metabolites decreased continuously. Annotation of these differential compounds revealed significant changes in sensory flavor characteristics in “green, sweet, fruity, floral, and woody” flavors. The results demonstrated significant variations in the volatile components of Liupao tea fermentation, along with notable changes in flavor characteristics.
研究领域:
食品科学
·
分析化学
·
植物代谢
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DOI
PubMed
高影响因子
LWT-FOOD SCIENCE AND TECHNOLOGY
·
2025
·
IF 6.6
Yang-bo Xiao,Rongji Tian,Ying-ying Shen,Han Tang,Jian-an Huang,Wenliang Wu,Shu-guang Zhang,Xia Yin
Leaf grade is a critical factor influencing black tea aroma formation, yet the precise relationship between leaf grade and aroma characteristics, along with their key volatile compounds, remains unclear. This study employed sensory evaluation combined with headspace solid phase microextraction/gas chromatography-Mass spectrometry (HS-SPME/GC-MS), odor activity values (OAV), partial least squares (PLS) regression, and correlation analysis to investigate the association between leaf grades and aroma attributes, as well as their key volatile compounds. Sensory evaluation and quantitative analysis revealed that as fresh tea leaf grade decreased, the sweet aroma attribute gradually declined, while the floral aroma initially decreased before increasing. GC-MS and OAV analyses identified 22 and 23 differential aroma-active compounds in ‘Jinguanyin’ (JGY) and ‘Jinmudan’ (JMD) black teas of different grades, respectively. Furthermore, PLS modeling and correlation analysis determined that β-damascenone, β-myrcene, geraniol, linalool, and trans -β-ocimene were key compounds responsible for sweet aroma variations across leaf grades, whereas methyl jasmonate, β-ionone, and jasmine lactone were identified as critical compounds influencing floral aroma differences. This study deciphered the chemical basis of how leaf grades affect black tea aroma quality, providing theoretical guidance for precision processing of black tea.
研究领域:
食品科学
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分析化学
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感官分析
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植物生物化学
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DOI
高影响因子
FOOD CHEMISTRY
·
2024
·
IF 8.5
Zhen Wang,Waqas Ahmad,Songguang Zhao,Afang Zhu,Shuhao Huo,Quansheng Chen
The precise changes in the flavor quality of green tea before and after the optimal consumption period remain elusive. This study used HS-SPME-GC–MS to carefully examine the volatile compounds of green tea samples from multiple storage periods and simultaneously detected changes in taste and color during tea infusion. Notably, 16 compounds with VIP > 1.5 were identified, highlighting their significance in the overall analysis profile. Among these components, nonanoic acid, octanoic acid and hexanal were identified as potential contributors to off-flavors and rancid oil flavors in tea after storage. The color of the tea broth becomes darker. Bitter flavor is associated with increased amino acid content. The PSO-SVM model showed excellent accuracy for predicting the storage duration of green tea. These findings provide critical theoretical understandings of green tea manufacturing and quality control.
研究领域:
食品科学
·
茶叶研究
·
分析化学
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DOI
PubMed
高影响因子
BIOPROCESS AND BIOSYSTEMS ENGINEERING
·
2020
·Vol. 43
·期 5
·831-838
·
IF 2.419
Liu Bin,Wang Xufeng,Zhao Jiahao,Qin Liehao,Shi Lei,Zhou Tao,Liu Shuang,Wang Chunling
Zygosaccharomyces rouxii referred as Yeast S is an important microorganism widely applied in traditional fermented food to accelerate flavor formation. Z. rouxii 3-2 referred as Yeast S 3-2 constructed previously is a new strain having higher salt tolerance than wild type. In this study, salt stress response of synthesis key flavor metabolites 3-methylthiopropanol, 2-phenylethyl alcohol, and isoamyl acetate in Yeast S and S 3-2 were investigated based on SPME–GC–MS and RT-qPCR. Analysis of GC–MS data showed that high salinity led to increase the contents of 3-methylthiopropanol and 2-phenylethyl alcohol both in Yeast S and Yeast S 3-2, while inhibited the synthesis of isoamyl acetate, and the induced effect on Yeast S 3-2 was more pronounced than Yeast S. Furthermore, the RT-qPCR results revealed that the salinity could enhance the genes expression of ARO10 and PDC1 , and stronger effect on Yeast S 3-2 than S. However, the gene expression of AFT1 was reduced in high-salt culture conditions, which was consistent with the results of GC–MS data. The results presented in this study can provide theoretical support of Z. rouxii 3-2 application during food fermentation.
研究领域:
微生物学
·
食品科学
·
分子生物学
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DOI
PubMed
高影响因子
EUROPEAN JOURNAL OF LIPID SCIENCE AND TECHNOLOGY
·
2019
·Vol. 121
·期 6
·1800521
·
IF 1.852
Honglei Mu,Haiyan Gao,Hangjun Chen,Xiangjun Fang,Yongjun Zhou,Weijie Wu,Qiang Han
Walnut ( Carya cathayensis Sarg.) oil contains over 85% unsaturated fatty acids, which are easily oxidized during storage. As a result, a large number of volatile oxidation compounds (VOCs) are formed during oxidation. The qualitative composition of VOCs in walnut oil and quantitative prediction of the oxidation parameters (peroxide value [POV], acid value [AV], and p -anisidine value [ p -AnV]) by VOCs are investigated through SPME/GC-MS combined with partial least-squares (PLS) regression analysis. Eighteen VOCs including aldehydes, alcohols, and acids are detected by SPME/GC-MS. According to the comprehensive scores of principal component analysis (PCA), 2-octenal, hexanal, 2-heptenal, 1-octen-3-ol, hexanoic acid, and nonanal are the main products formed during oxidation. Then PLS regression is applied to developing quantitative prediction models of oxidation parameters (POV, AV, and p -AnV) by VOCs. The PLS prediction models have a good performance, with determination coefficients (R 2 p ) of 0.993–0.997 for the prediction sets of the three oxidation parameters. Practical Applications : The quantitative relationship between VOCs and oxidation parameters is developed in this study, which provided a new method for monitoring the quality of walnut oil. The SPME/GC-MS combined with PLSR is a feasible and potential method for simultaneous qualitative and quantitative analysis of oxidation process. This method is proven to have a precise predictive ability and provided a potential application in the quality assessment of other nut products. Volatile oxidation compounds (VOCs) are detected by SPME/GC-MS in oxidized walnut ( Carya cathayensis Sarg.) oil. Following this determination, partial least-squares regression (PLSR) is applied to developing quantitative prediction models of oxidation parameters by VOCs.
研究领域:
食品科学
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分析化学
·
植物学
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DOI
高影响因子
Journal of Food Measurement and Characterization
·
2026
·
IF 3.6
Zhao Xiaohan,Wang Liling,Yin Xianggang,Wu Linlin,Zheng Ying,Shao Qingsong,Zhou Yifeng,Huang Jun
Saffron ( Crocus sativus L. ) is a valuable perennial bulbous medicinal herb, often referred to as the “golden spice”. Although previous studies have investigated the non-volatile components and bioactive constituents in various parts of saffron, comprehensive profiles of its volatile organic compounds (VOCs) remained limited. This study employed headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) combined with cluster heatmaps, principal component analysis (PCA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) to analyze and compare the VOCs in seven parts of Zhejiang-cultivated saffron, namely stigma (SS), petal (SP), pollen (SPO), filaments (SF), corms (SC), buds (SB), and leaves (SL). A total of 72 VOCs of saffron were identified, comprising 10 alcohols, 7 esters, 19 ketones, 7 aldehydes, 17 alkenes, and 12 other compounds. Among these, fatty acid methyl esters were the predominant VOC components in SC, whereas safranal or isophorone exhibited relatively higher abundances in the other six parts, which were also enriched in trimethylcyclohexane or cyclohexene derivatives. Cluster heatmaps and PCA grouped the seven saffron parts into three major clusters: SS, SPO and the remaining five parts. Furthermore, 15 significantly differential compounds were screened using the scatter loading plot (S-plot) of the OPLS-DA model combined with variable importance in the projection (VIP) values. Isophorone, 2,2,6-trimethylcyclohexane-1,4-dione (DOIP), and 2,6,6-trimethyl-1,3-cyclohexadiene-1-carbaldehyde (safranal) were identified as common key discriminant compounds across all comparisons, and while SS, SP, SF, SB and SL each contain unique marker compounds. These findings provide a scientific foundation for the authentication, quality assessment and comprehensive utilization of saffron resources.
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高影响因子
LWT-FOOD SCIENCE AND TECHNOLOGY
·
2023
·
IF 6
Quanzeng Wei,Juntao Sun,Jiaqi Guo,Xiaofei Li,Xiaohua Zhang,Fugang Xiao
The adulteration of the honey industry is serious, especially the syrup adulteration method is difficult to detect. To develop the detection technology of chaste honey adulteration with high fructose corn syrup (HFCS), the condition of headspace solid-phase micro-extraction (HS-SPME) was optimized for extracting the volatile compounds of chaste honey. HS-SPME conditions were selected for optimization using Plackett Burman, steepest ascent and Box-Behnken. Volatile compounds from chaste honey adulterated with HFCS were analyzed by gas chromatography-mass spectrometry (GC-MS). M/Z RT pairs data from differences in chaste honey contents in HFCS-adulterated samples were analyzed by linear discriminant analysis (LDA), principal component analysis (PCA), and artificial neural network (ANN). The results indicated distinguished adulterated chaste honey at different proportions was not ideal using LDA and PCA. A back propagation (BP) artificial neural network （ANN）model was constructed based on m/z RT pair data. Correlation coefficients of training, verification, testing and comprehensive data of BP-ANN were 0.994, 0.945, 0.968 and 0.979, respectively, indicating good accuracy of the BP-ANN prediction model. The present study discusses a new strategy that determined the chaste honey contents in HFCS-adulterated samples as well as did not rely on the identification of volatile compounds.
研究领域:
食品科学
·
分析化学
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高影响因子
Journal of Food Measurement and Characterization
·
2019
·Vol. 14
·期 1
·535-547
·
IF 1.415
Al-Dalali Sam,Zheng Fuping,Sun Baoguo,Chen Feng,Wang Peng,Wang Wenping
Zhengrong vinegar is one of the renowned popular condiments in China, which has been consumed around Hebei province for about 136 years. Its different processing steps are considered as important and critical steps that are responsible for the generation of representative flavors besides the acetic acid. An HS-SPME coupled with GC–MS method was used to evaluate the changes of the volatiles of the vinegar that were generated during the different processing steps including before adding salt (BAS), after adding salt (AAS), after filtration (AF) and final product (FP). In addition, aroma-active volatiles of the final vinegar product were characterized by GC-O coupled with detection frequency technique (modified frequency, MF%) that is a combination of aroma intensity and aroma frequency values that can be used to improve the description of a reliable data from GC-O. Among the 42 detected volatiles, 38 of them were positively identified by their corresponding authentic compounds. Besides, 24 volatiles were recognized as aroma-active volatiles. On the other hand, the content of individual volatile groups was decreased along with the continuation of the fermentation process from the BAS step to FP step, except the aldehydes group that displayed a slight increase. Of which, 2-pentylfuran and ethyl heptanoate disappeared in the AF and FP samples. The main contributors to the Zhengrong aroma profile that had MF (%) > 80 included isovaleric acid, 2-acetoxy-3-butanone, hexanoic acid, ethyl hexanoate, 3-(methylthio)propyl acetate, decanal and 2-phenyl-2-butenal, while the volatile compounds that had a middle MF in a range between 70 and 80 were 2-methylbutanoic acid, tetramethylpyrazine, nonanal, 1,2-dimethoxybenzene, 4-ethylphenol, ethyl benzoate, ethyl benzeneacetate, 2-phenylethyl acetate and 4-ethylguaiacol.
研究领域:
食品科学
·
分析化学
·
风味化学
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DOI
高影响因子
FLAVOUR AND FRAGRANCE JOURNAL
·
2026
·
IF 2.5
Wenjie Ye,Hongwei Lu,Han Chen,Naidong Chen,Li Zhang
Jin'an crispy peach is a famous geographical indication product widely grown in Lu'an City. In this study, four representative cultivars, including ‘Chunxue’, ‘Nanguohong’, ‘Chunmi’, and ‘Huangjinmi’, were selected to analyse their volatile compounds, and the headspace solid-phase microextraction (HS-SPME) method was employed. Fifty-eight volatile compounds were identified by gas chromatography–mass spectrometry (GC–MS), with 31, 24, 24, and 16 compounds detected in ‘Nanguohong’, ‘Chunxue’, ‘Chunmi’ and ‘Huangjinmi’, respectively. Principal component analysis (PCA) revealed strong correlations among five major compounds ( E )-2-hexenal, benzaldehyde, nonadienol, heptanoic acid and nonanoic acid in different cultivars. Odour activity value (OAV) analysis showed that 2-trans-4-trans-decadienal and β-damascenone exhibited the highest OAVs and together contributed to the primary flavour of the “Nanguohong” cultivar. In the “Chunxue” cultivar, ( E )-2-nonenal and 2,4-nonadien-1-al contributed to its grassy and green vegetable-like aromas. In the “Chunmi” and “Huangjinmi” cultivars, 2-ethyl-1-hexanol and phenylethyl alcohol were the predominant odour-active compounds and imparted a sweet aroma to the peaches. This research not only enhances our understanding of the flavour characteristics of Jin'an crispy peach but also lays a foundation for its further development and utilisation.
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高影响因子
ANALYTICAL CHEMISTRY
·
2023
·
IF 7.4
Yue Liu,Dianlong Ge,Jijuan Zhou,Yajing Chu,Xiangxue Zheng,Li Ke,Pan Li,Yan Lu,Xue Zou,Lei Xia,Yawei Liu,Chaoqun Huang,Chengyin Shen,Yannan Chu
The investigation of volatile organic compounds (VOCs) in human metabolites has been a topic of interest as it holds the potential for the development of non-invasive technologies to screen for organ lesions in vivo. However, it remains unclear whether VOCs differ among healthy organs. Consequently, a study was conducted to analyze VOCs in ex vivo organ tissues obtained from 16 Wistar rats, comprising 12 different organs. The VOCs released from each organ tissue were detected by the headspace-solid phase microextraction-gas chromatography-mass spectrometry technique. In the untargeted analysis of 147 chromatographic peaks, the differential volatiles of rat organs were explored based on the Mann–Whitney U test and fold change (FC > 2.0) compared with other organs. It was found that there were differential VOCs in seven organs. A discussion on the possible metabolic pathways and related biomarkers of organ differential VOCs was conducted. Based on the orthogonal partial least squares discriminant analysis and receiver operating characteristic curve, we found that differential VOCs in the liver, cecum, spleen, and kidney can be used as the unique identification of the corresponding organ. In this study, differential VOCs of organs in rats were systematically reported for the first time. Profiles of VOCs produced by healthy organs can serve as a reference or baseline that may indicate the presence of disease or abnormalities in the organ’s function. Differential VOCs can be used as the fingerprint of organs, and future integration with metabolic research may contribute to the development of healthcare.
研究领域:
分析化学
·
代谢组学
·
医学诊断
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产品关联
DOI
PubMed
高影响因子
LWT-FOOD SCIENCE AND TECHNOLOGY
·
2023
·
IF 6
Zhichao Xiong,Wanzhen Feng,Dongzhou Xia,Jixin Zhang,Yuming Wei,Tiehan Li,Junlan Huang,Yujie Wang,Jingming Ning
The authenticity of the geographical origin of agricultural products has received widespread attention. Tea tree varieties, processing processes and origins influence the quality and price of raw pu-erh tea (RPT). This study distinguished RPT from 10 different production areas through headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) combined with orthogonal partial least squares–discriminant analysis (OPLS-DA) model and machine learning algorithms. Among the thirty-five types of common volatiles identified, pentanal, heptanal, naphthalene, cedrol, and 2,6-di- tert -butylbenzoquinone were considered the key differential compounds distinguishing the 10 different production areas of the RPT samples through the screening of variable importance in projection values of the OPLS-DA and coefficient weights of the linear discriminant analysis function. Among them, heptanal and 2,6-di- tert -butylbenzoquinone had the highest content in West of Bingdao and the lowest content in Nannuoshan. The random forest algorithm achieved a discrimination accuracy of 98.4% based on the discrimination of five key compounds in 63 RPT samples. The random forest model was demonstrated to be reliable and valid by using receiver operating characteristic curves (area under the curve = 0.7603). The study results serve as a reference for the differentiation of 10 production areas of RPT.
研究领域:
食品科学
·
分析化学
·
机器学习
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高影响因子
危险品化学品经营许可证（带存储）