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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Chemical characterization of aromas in beer and their effect on consumers liking
Claudia Gonzalez Viejo, Sigfredo Fuentes, Damir D. Torrico, et al.
Food Chemistry (2019) Vol. 293, pp. 479-485
Closed Access | Times Cited: 97

Showing 1-25 of 97 citing articles:

Development of a low-cost e-nose to assess aroma profiles: An artificial intelligence application to assess beer quality
Claudia Gonzalez Viejo, Sigfredo Fuentes, Amruta Godbole, et al.
Sensors and Actuators B Chemical (2020) Vol. 308, pp. 127688-127688
Closed Access | Times Cited: 155
Predicting and improving complex beer flavor through machine learning
Michiel Schreurs, Supinya Piampongsant, Miguel Roncoroni, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 41
Emerging Extraction Strategies in Analytical Chemistry
Frederik André Hansen, Stig Pedersen‐Bjergaard
Analytical Chemistry (2019) Vol. 92, Iss. 1, pp. 2-15
Closed Access | Times Cited: 104
Factors influencing the choice of beer: A review
María Isabel Noreña Betancur, Kosuke Motoki, Charles Spence, et al.
Food Research International (2020) Vol. 137, pp. 109367-109367
Open Access | Times Cited: 100
Impact of non-Saccharomyces yeasts derived from traditional fermented foods on beer aroma: Analysis based on HS-SPME-GC/MS combined with chemometrics
Kaixin Cao, Junrui Wu, Xiujuan Wan, et al.
Food Research International (2024) Vol. 187, pp. 114366-114366
Closed Access | Times Cited: 8
Enhancing beer authentication, quality, and control assessment using non‐invasive spectroscopy through bottle and machine learning modeling
Natalie Harris, Claudia Gonzalez Viejo, Jane Zhang, et al.
Journal of Food Science (2025) Vol. 90, Iss. 1
Open Access | Times Cited: 1
Emerging Technologies Based on Artificial Intelligence to Assess the Quality and Consumer Preference of Beverages
Claudia Gonzalez Viejo, Damir D. Torrico, Frank R. Dunshea, et al.
Beverages (2019) Vol. 5, Iss. 4, pp. 62-62
Open Access | Times Cited: 72
Beer volatile fingerprinting at different brewing steps
Vera L. Alves, João Gonçalves, José A. Figueira, et al.
Food Chemistry (2020) Vol. 326, pp. 126856-126856
Open Access | Times Cited: 59
Volatile Compounds Content, Physicochemical Parameters, and Antioxidant Activity of Beers with Addition of Mango Fruit (Mangifera Indica)
Alan Gasiński, Joanna Kawa‐Rygielska, Antoni Szumny, et al.
Molecules (2020) Vol. 25, Iss. 13, pp. 3033-3033
Open Access | Times Cited: 58
New Approaches for the Fermentation of Beer: Non-Saccharomyces Yeasts from Wine
Vanesa Postigo, Ana Sánchez-Arroyo, Juan Mariano Cabellos, et al.
Fermentation (2022) Vol. 8, Iss. 6, pp. 280-280
Open Access | Times Cited: 30
Modeling and Optimization of Triticale Wort Production Using an Artificial Neural Network and a Genetic Algorithm
Milana Pribić, Kamenko Ilija, Saša Despotović, et al.
Foods (2024) Vol. 13, Iss. 2, pp. 343-343
Open Access | Times Cited: 7
Fruit beers, beers with or without a co-fermentation step with fruits
Alejandro P Croonenberghs, Dries Bongaerts, Arne Bouchez, et al.
Current Opinion in Biotechnology (2024) Vol. 86, pp. 103081-103081
Open Access | Times Cited: 6
Advances in yeast alcoholic fermentations for the production of bioethanol, beer and wine
Kevy Pontes Eliodório, Gabriel Caetano de Góis e Cunha, Caroline Müller, et al.
Advances in applied microbiology (2019), pp. 61-119
Closed Access | Times Cited: 45
Maltose-Negative Yeast in Non-Alcoholic and Low-Alcoholic Beer Production
Selin YABACI KARAOĞLAN, Rudolf Jung, Matthew Gauthier, et al.
Fermentation (2022) Vol. 8, Iss. 6, pp. 273-273
Open Access | Times Cited: 27
Effect of Hanseniaspora vineae and Saccharomyces cerevisiae co-fermentations on aroma compound production in beer
Jose Aguiar-Cervera, Federico Visinoni, Penghan Zhang, et al.
Food Microbiology (2024) Vol. 123, pp. 104585-104585
Open Access | Times Cited: 5
Beer Aroma and Quality Traits Assessment Using Artificial Intelligence
Claudia Gonzalez Viejo, Sigfredo Fuentes
Fermentation (2020) Vol. 6, Iss. 2, pp. 56-56
Open Access | Times Cited: 33
Quality Traits of Sourdough Bread Obtained by Novel Digital Technologies and Machine Learning Modelling
Claudia Gonzalez Viejo, Natalie Harris, Sigfredo Fuentes
Fermentation (2022) Vol. 8, Iss. 10, pp. 516-516
Open Access | Times Cited: 20
Biotransformation of wort components for appearance, flavour and health
Mei Zhi Alcine Chan, Shao‐Quan Liu
Elsevier eBooks (2025), pp. 311-323
Closed Access
Exploring beer culture dissemination and quality perception through different media: the craft beer experience
Riccardo N. Barbagallo, Chiara Alessandra Carmen Rutigliano, Valeria Rizzo, et al.
Food and Humanity (2025) Vol. 4, pp. 100522-100522
Closed Access
Unravelling the key flavor components of beer based on a new online recombination olfactometry of mixed targeted compounds
Qing Yang, Ning Liang, S. Chen, et al.
Food Chemistry (2025) Vol. 479, pp. 143702-143702
Closed Access
Use of non-conventional yeasts for enhancing the sensory quality of craft beer
Antonino Pirrone, Vincenzo Naselli, Ignazio Maria Gugino, et al.
Food Research International (2025) Vol. 208, pp. 116164-116164
Closed Access
Nutritional and functional aspects of European cereal-based fermented foods and beverages
Tolulope Joshua Ashaolu, László Varga, Babett Greff
Food Research International (2025) Vol. 209, pp. 116221-116221
Open Access
A Portable Electronic Nose Based on Convolutional Neural Network for Beer Identification
Zhencheng Liu, Zhenyu Liu, Jilong Wu, et al.
Food Control (2025), pp. 111371-111371
Closed Access
Development of a stir bar sorptive extraction method to study different beer styles volatile profiles
José E. Ruvalcaba, Enrique Durán, Carmelo Garcı́a Barroso, et al.
Food Research International (2019) Vol. 126, pp. 108680-108680
Closed Access | Times Cited: 33
Prediction of flavor and retention index for compounds in beer depending on molecular structure using a machine learning method
Yutang Wang, YANG Zhaoxia, Zan-Hao Piao, et al.
RSC Advances (2021) Vol. 11, Iss. 58, pp. 36942-36950
Open Access | Times Cited: 26
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