Results 11 to 20 of about 402,101 (149)

Authoring courses with rich adaptive sequencing for IMS learning design [PDF]

, 2008
This paper describes the process of translating an adaptive sequencing strategy designed using Sequencing Graphs to the semantics of IMS Learning Design. The relevance of this contribution is twofold.
Gutierrez-Santos, Sergio, Pardo, A., Delgado Kloos, C.   +2 more
core   +9 more sources

Fingerprinting of Green Arabica Coffee Volatile Organic Compounds (VOCs): HS-GC-IMS Versus GC × GC-MS

International Journal of Food Science
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
Matteo Bordiga, Vincenzo Disca, Marcello Manfredi, Elettra Barberis, Francesca Carrà, Luciano Navarini, Valentina Lonzarich, Marco Arlorio   +7 more
doaj   +2 more sources

Chiral Trapped-Headspace GC-QMS-IMS: Boosting Untargeted Benchtop Volatilomics to the Next Level

Chemosensors
In the field of quality analysis of food and flavoring products, gas chromatography–quadrupole mass spectrometry–ion mobility spectrometry (GC-QMS-IMS) is a powerful technique for the simultaneous detection of volatile organic compounds (VOCs) by both ...
Lukas Bodenbender, Sascha Rohn, Simeon Sauer, Markus Jungen, Philipp Weller   +4 more
doaj   +3 more sources

Fast and Non-Destructive Profiling of Commercial Coffee Aroma under Three Conditions (Beans, Powder, and Brews) Using GC-IMS

Molecules, 2022
The flavor of coffee can be affected by the preparation parameters. In this investigation, the flavor profiles of three coffee brands under three conditions (bean, powder, and brew) were analyzed by gas chromatography—ion mobility spectrometry (GC-IMS ...
Yanping Chen, He Chen, Dandan Cui, Xiaolei Fang, Jie Gao, Yuan Liu   +5 more
doaj   +1 more source

GC-IMS data on the discrimination between geographic origins of olive oils

Data in Brief, 2022
Gas chromatography hyphenated with ion mobility spectrometry (GC-IMS) is an emerging benchtop technique for sensitive and selective detection of volatile organic compounds.
Joscha Christmann, Sascha Rohn, Philipp Weller   +2 more
doaj   +1 more source

Characterization of the Flavor Profile of Bigeye Tuna Slices Treated by Cold Plasma Using E-Nose and GC-IMS

Fishes, 2022
To avoid heat, treatment induces numerous physicochemical changes under severe conditions in the tuna, cold plasma (CP), as a non-thermal technology, possess objective potential on tuna processing.
Weicong Pan, Soottawat Benjakul, Chiara Sanmartin, Alessandra Guidi, Xiaoguo Ying, Lukai Ma, Xudong Weng, Jin Yu, Shanggui Deng   +8 more
doaj   +1 more source

Application of GC-IMS coupled with chemometric analysis for the classification and authentication of geographical indication agricultural products and food

Frontiers in Nutrition, 2023
Geographical indications (GI) are used to protect the brand value of agricultural products, foodstuffs, and wine and promote the sustainable development of the agricultural and food industries.
Hong Zhu, Dazhou Zhu, Junmao Sun
doaj   +1 more source

Discrimination of different edible vegetable oils based on GC-IMS and SIMCA

CyTA - Journal of Food, 2023
Ion mobility spectrometry coupled to gas-chromatographic (GC-IMS) is tested regarding their ability to analyze various refined edible vegetable oils, including sunflower seed, rapeseed, sesame, soybean, peanut, corn, camellia, linseed, walnut, coconut ...
Dechun Geng, Xinyu Chen, Daoli Lu, Bin Chen   +3 more
doaj   +1 more source

Comparative Analysis of Key Odorants and Aroma Characteristics in Hot-Pressed Yellow Horn (Xanthoceras sorbifolia bunge) Seed Oil Via Gas Chromatography–Ion Mobility Spectrometry and Gas Chromatography–Olfactory-Mass Spectrometry

Foods, 2023
Volatile compounds (VOCs) present in the oil extracted from yellow horn seeds were first analyzed using GC-IMS and GC-O-MS at varying roasting temperatures. A total of 97 VOCs were detected using GC-IMS, while 77 were tentatively identified using GC-O-MS.
Hui Gao, Mengkai Liu, Lili Zheng, Tingting Zhang, Xiuliang Chang, He Liu, Sen Zhou, Zhiran Zhang, Shengxin Li, Jie Sun   +9 more
doaj   +1 more source

Honeys biological origin by GC-IMS

, 2022
GC-IMS data set of authentic honeys from 3 biological origins: canola, acacia and honeydew. The files are in native .mea format and can e.g. be analyzed by our open source toolbox gc-ims-tools.
Weller, P
core   +2 more sources