{"title":"绿阿拉比卡咖啡挥发性有机物(VOCs)指纹图谱:HS-GC-IMS对比GC × GC- ms","authors":"Matteo Bordiga, Vincenzo Disca, Marcello Manfredi, Elettra Barberis, Francesca Carrà, Luciano Navarini, Valentina Lonzarich, Marco Arlorio","doi":"10.1155/ijfo/1302823","DOIUrl":null,"url":null,"abstract":"<p><p>This study compared two nontargeted analytical techniques-headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC-MS)-to fingerprint the volatile organic compounds (VOCs) of green <i>Coffea arabica</i> beans from Ethiopia, Brazil, Nicaragua, and Guatemala. HS-GC-IMS enabled rapid differentiation of samples, detecting VOC signal regions that effectively clustered samples by origin with minimal preparation. GC × GC-MS offered higher chemical resolution, identifying 98 compounds, including methoxypyrazines, aldehydes, and alcohols, which significantly contributed to interorigin variability. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) confirmed the capacity of both methods to distinguish geographical origins, with hierarchical clustering highlighting region-specific VOC patterns. HS-GC-IMS proved efficient for high-throughput screening, while GC × GC-MS provided molecular insights into potential aroma precursors. Together, these platforms offer a complementary approach to green coffee authentication and quality control.</p>","PeriodicalId":14125,"journal":{"name":"International Journal of Food Science","volume":"2025 ","pages":"1302823"},"PeriodicalIF":3.1000,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12396915/pdf/","citationCount":"0","resultStr":"{\"title\":\"Fingerprinting of Green Arabica Coffee Volatile Organic Compounds (VOCs): HS-GC-IMS Versus GC × GC-MS.\",\"authors\":\"Matteo Bordiga, Vincenzo Disca, Marcello Manfredi, Elettra Barberis, Francesca Carrà, Luciano Navarini, Valentina Lonzarich, Marco Arlorio\",\"doi\":\"10.1155/ijfo/1302823\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study compared two nontargeted analytical techniques-headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC-MS)-to fingerprint the volatile organic compounds (VOCs) of green <i>Coffea arabica</i> beans from Ethiopia, Brazil, Nicaragua, and Guatemala. HS-GC-IMS enabled rapid differentiation of samples, detecting VOC signal regions that effectively clustered samples by origin with minimal preparation. GC × GC-MS offered higher chemical resolution, identifying 98 compounds, including methoxypyrazines, aldehydes, and alcohols, which significantly contributed to interorigin variability. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) confirmed the capacity of both methods to distinguish geographical origins, with hierarchical clustering highlighting region-specific VOC patterns. HS-GC-IMS proved efficient for high-throughput screening, while GC × GC-MS provided molecular insights into potential aroma precursors. Together, these platforms offer a complementary approach to green coffee authentication and quality control.</p>\",\"PeriodicalId\":14125,\"journal\":{\"name\":\"International Journal of Food Science\",\"volume\":\"2025 \",\"pages\":\"1302823\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2025-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12396915/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Food Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/ijfo/1302823\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"FOOD SCIENCE & TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Food Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/ijfo/1302823","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"FOOD SCIENCE & TECHNOLOGY","Score":null,"Total":0}
Fingerprinting of Green Arabica Coffee Volatile Organic Compounds (VOCs): HS-GC-IMS Versus GC × GC-MS.
This study compared two nontargeted analytical techniques-headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC-MS)-to fingerprint the volatile organic compounds (VOCs) of green Coffea arabica beans from Ethiopia, Brazil, Nicaragua, and Guatemala. HS-GC-IMS enabled rapid differentiation of samples, detecting VOC signal regions that effectively clustered samples by origin with minimal preparation. GC × GC-MS offered higher chemical resolution, identifying 98 compounds, including methoxypyrazines, aldehydes, and alcohols, which significantly contributed to interorigin variability. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) confirmed the capacity of both methods to distinguish geographical origins, with hierarchical clustering highlighting region-specific VOC patterns. HS-GC-IMS proved efficient for high-throughput screening, while GC × GC-MS provided molecular insights into potential aroma precursors. Together, these platforms offer a complementary approach to green coffee authentication and quality control.
期刊介绍:
International Journal of Food Science is a peer-reviewed, Open Access journal that publishes research and review articles in all areas of food science. As a multidisciplinary journal, articles discussing all aspects of food science will be considered, including, but not limited to: enhancing shelf life, food deterioration, food engineering, food handling, food processing, food quality, food safety, microbiology, and nutritional research. The journal aims to provide a valuable resource for food scientists, food producers, food retailers, nutritionists, the public health sector, and relevant governmental and non-governmental agencies.