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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:

Adulteration identification in raw milk using Fourier transform infrared spectroscopy
Tatiane Barbosa Coitinho, Laerte Dagher Cassoli, Pedro Henrique Ramos Cerqueira, et al.
Journal of Food Science and Technology (2017) Vol. 54, Iss. 8, pp. 2394-2402
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Application of FTIR spectroscopy in dairy products: A systematic review
Rakendhu Saji, Akshay Ramani, Kamal Gandhi, et al.
Food and Humanity (2024) Vol. 2, pp. 100239-100239
Closed Access | Times Cited: 21
Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years
Abdo Hassoun, Ingrid Måge, Walter Schmidt, et al.
Foods (2020) Vol. 9, Iss. 8, pp. 1069-1069
Open Access | Times Cited: 123
Forensics in hand: new trends in forensic devices (2013–2017)
Luiza Pereira de Oliveira, Diego P. Rocha, William R. de Araújo, et al.
Analytical Methods (2018) Vol. 10, Iss. 43, pp. 5135-5163
Closed Access | Times Cited: 76
Application of Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy coupled with chemometrics for detection and quantification of formalin in cow milk
Biji Balan, Amit S. Dhaulaniya, Rahul Jamwal, et al.
Vibrational Spectroscopy (2020) Vol. 107, pp. 103033-103033
Closed Access | Times Cited: 63
From laboratory to industrial use: Understanding process variation during enzymatic protein hydrolysis with dry film Fourier-Transform Infrared spectroscopy
Bijay Kafle, Ingrid Måge, Sileshi Gizachew Wubshet, et al.
Food Control (2024) Vol. 164, pp. 110577-110577
Open Access | Times Cited: 6
Development and application of Fourier transform infrared spectroscopy for detection of milk adulteration in practice
Per Waaben Hansen, Stephen E. Holroyd
International Journal of Dairy Technology (2019) Vol. 72, Iss. 3, pp. 321-331
Open Access | Times Cited: 48
Application of 2D-COS-FTIR spectroscopic analysis to milk powder adulteration: Detection of melamine
Abdul G. Al Lafi, Isam AL-Naser
Journal of Food Composition and Analysis (2022) Vol. 113, pp. 104720-104720
Closed Access | Times Cited: 21
Portable Optical Instrument for Detection and Quantification of Milk Adulteration: A Study on Mixtures from different Species and Water Dilution
Cristina Allende-Prieto, Lucía Fernández, Pablo Rodríguez‐Gonzálvez, et al.
International Dairy Journal (2025), pp. 106186-106186
Closed Access
A Systematic Review of Spectroscopic Techniques for Detecting Milk Adulteration
Parsa Joolaei Ahranjani, Kamine Dehghan, Zahra Esfandiari, et al.
Critical Reviews in Analytical Chemistry (2025), pp. 1-32
Closed Access
Application of ATR-FTIR Incorporated with Multivariate Data Analysis for Discrimination and Quantification of Urea as an Adulterant in UHT Milk
Emeline Tan, Norliza Julmohammad, Wee Yin Koh, et al.
Foods (2023) Vol. 12, Iss. 15, pp. 2855-2855
Open Access | Times Cited: 9
Detection of meloxicam residues in milk using ATR- FTIR spectroscopy coupled with chemometrics
Rakendhu Saji, Kamal Gandhi, Rajan Sharma, et al.
Food Control (2024) Vol. 163, pp. 110491-110491
Closed Access | Times Cited: 3
Spectra data classification with kernel extreme learning machine
Wenbin Zheng, Hongping Shu, Hong Tang, et al.
Chemometrics and Intelligent Laboratory Systems (2019) Vol. 192, pp. 103815-103815
Closed Access | Times Cited: 29
Discrimination of bovine milk from non-dairy milk by lipids fingerprinting using routine matrix-assisted laser desorption ionization mass spectrometry
Philippa England, Wenhao Tang, Markus Kostrzewa, et al.
Scientific Reports (2020) Vol. 10, Iss. 1
Open Access | Times Cited: 24
Rapid detection of acid neutralizers adulteration in raw milk using FGC E-nose and chemometrics
Huaixiang Tian, Bin Chen, Xinman Lou, et al.
Journal of Food Measurement & Characterization (2022) Vol. 16, Iss. 4, pp. 2978-2988
Closed Access | Times Cited: 14
Opportunities for fraudsters: When would profitable milk adulterations go unnoticed by common, standardized FTIR measurements?
Yuzheng Yang, Kasper Hettinga, Sara W. Erasmus, et al.
Food Research International (2020) Vol. 136, pp. 109543-109543
Open Access | Times Cited: 21
Non-targeted detection of food adulteration using an ensemble machine-learning model
Teresa Chung, Issan Yee San Tam, Nelly Yan Yan Lam, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 10
On-line identification of silkworm pupae gender by short-wavelength near infrared spectroscopy and pattern recognition technology
Yue Ma, Yichao Xu, Hui Yan, et al.
Journal of Near Infrared Spectroscopy (2021) Vol. 29, Iss. 4, pp. 207-215
Closed Access | Times Cited: 13
Prevalence of Milk Fraud in the Chinese Market and its Relationship with Fraud Vulnerabilities in the Chain
Yuzheng Yang, Liebing Zhang, Kasper Hettinga, et al.
Foods (2020) Vol. 9, Iss. 6, pp. 709-709
Open Access | Times Cited: 13
Food Fraud Vulnerabilities in the Supply Chain: An Industry Perspective
Christophe Cavin, Geoffrey Cottenet, Christophe Fuerer, et al.
Elsevier eBooks (2018), pp. 670-678
Closed Access | Times Cited: 14
Identification of tea varieties by mid‐infrared diffuse reflectance spectroscopy coupled with a possibilistic fuzzy c‐means clustering with a fuzzy covariance matrix
Xiaohong Wu, Jing Zhou, Bin Wu, et al.
Journal of Food Process Engineering (2019) Vol. 42, Iss. 8
Closed Access | Times Cited: 13
Spectral Profiling (Fourier Transform Infrared Spectroscopy) and Machine Learning for the Recognition of Milk from Different Bovine Breeds
Anna Antonella Spina, Carlotta Ceniti, Rosario De Fazio, et al.
Animals (2024) Vol. 14, Iss. 9, pp. 1271-1271
Open Access | Times Cited: 1
Detection of flunixin residues in milk using ATR- FTIR spectroscopy coupled with chemometrics
Rakendhu Saji, Kamal Gandhi, Rajan Sharma, et al.
Journal of Food Measurement & Characterization (2024) Vol. 18, Iss. 8, pp. 6736-6746
Closed Access | Times Cited: 1
Cost-Effective Multispectral Sensor and Artificial Neural Networks for the Detection of Starch Adulteration in Raw Milk
Yeliz Durgun, Mahmut Durgun
Applied Sciences (2024) Vol. 14, Iss. 21, pp. 9800-9800
Open Access | Times Cited: 1
Silver-modified nitrogen-doped graphene quantum dots as a sensor for formaldehyde in milk using headspace micro-extraction on a single-drop of aqueous nanoparticles dispersion
Juliana da S. Padilha, Marlin J. Pedrozo‐Peñafiel, Marcelo Folhadella M. F. Azevedo, et al.
Analytica Chimica Acta (2022) Vol. 1232, pp. 340479-340479
Closed Access | Times Cited: 7
Quick vacuum drying of liquid samples prior to ATR‐FTIR spectral collection improves the quantitative prediction: a case study of milk adulteration
Hüseyin Ayvaz, Riza Temizkan
International Journal of Food Science & Technology (2018) Vol. 53, Iss. 11, pp. 2482-2489
Closed Access | Times Cited: 6
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