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:

Ultraviolet–visible spectroscopy combined with machine learning as a rapid detection method to the predict adulteration of honey
Razie Razavi, Reza Esmaeilzadeh Kenari
Heliyon (2023) Vol. 9, Iss. 10, pp. e20973-e20973
Open Access | Times Cited: 13

Showing 13 citing articles:

Spectroscopic food adulteration detection using machine learning: Current challenges and future prospects
R. K. Goyal, Poonam Singha, Sushil Kumar Singh
Trends in Food Science & Technology (2024) Vol. 146, pp. 104377-104377
Closed Access | Times Cited: 29

Sugar detection in adulterated honey using hyper-spectral imaging with stacking generalization method
Madhusudan G. Lanjewar, Kamini G. Panchbhai, L. B. Patle
Food Chemistry (2024) Vol. 450, pp. 139322-139322
Closed Access | Times Cited: 7

Machine Learning-Assisted FT-IR Spectroscopy for Identification of Pork Oil Adulteration in Tuna Fish Oil
Anjar Windarsih, Tri Hadi Jatmiko, Ayu Septi Anggraeni, et al.
Vibrational Spectroscopy (2024) Vol. 134, pp. 103715-103715
Closed Access | Times Cited: 5

Fluorescence and ultraviolet–visible spectroscopy in the honey analysis
Kashif Ameer, Mian Anjum Murtaza, Guihun Jiang, et al.
Elsevier eBooks (2024), pp. 153-191
Closed Access | Times Cited: 1

Application of UV–vis spectrophotometry and chemometrics to investigate adulteration by glucose syrup in Brazilian polyfloral honey
Aline Nunes, Gadiel Zilto Azevedo, Beatriz Rocha dos Santos, et al.
Food and Humanity (2023) Vol. 2, pp. 100194-100194
Closed Access | Times Cited: 3

Rapid and accurate quantification of trypsin activity using integrated infrared and ultraviolet spectroscopy with data fusion techniques
Wen-xiu Zhi, Baorong Wang, Jie Zhou, et al.
International Journal of Biological Macromolecules (2024) Vol. 278, pp. 135017-135017
Closed Access

Comparative study of physiochemical properties in Iranian multi-floral honeys: Local vs. commercial varieties
Adel Hajian-Tilaki, Reza Esmaeilzadeh Kenari, Reza Farahmandfar, et al.
Heliyon (2024) Vol. 10, Iss. 17, pp. e37550-e37550
Open Access

Detection of adulteration in Iranian grape molasses added glucose/fructose/sugar beet syrups with 13C/12C isotope ratio analysis method
Vahid Jamali, Aryou Emamifar, Hadi Beiginejad, et al.
Food Science & Nutrition (2024) Vol. 12, Iss. 10, pp. 8432-8440
Open Access

Application of spectroscopic technology with machine learning in Chinese herbs from seeds to medicinal materials: The case of genus Paris
Yangna Feng, Xinyan Zhu, Yuanzhong Wang
Journal of Pharmaceutical Analysis (2024), pp. 101103-101103
Open Access

Detecting Honey Adulteration: Advanced Approach Using UF-GC Coupled with Machine Learning
Irene Punta-Sánchez, Tomasz Dymerski, José Luis P. Calle, et al.
Sensors (2024) Vol. 24, Iss. 23, pp. 7481-7481
Open Access

Detection Technologies, and Machine Learning in Food: Recent Advances and Future Trends
Qiong He, Heng-Yu Huang, Yuanzhong Wang
Food Bioscience (2024), pp. 105558-105558
Closed Access

UV-Vis spectralprint-based discrimination and quantification of sugar syrup adulteration in honey using the Successive Projections Algorithm (SPA) for variable selection
Luana Leal de Souza, Dâmaris Naara Chaves Candeias, Edilene Dantas Teles Moreira, et al.
Chemometrics and Intelligent Laboratory Systems (2024), pp. 105314-105314
Closed Access

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