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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:

Detection of flaxseed oil multiple adulteration by near-infrared spectroscopy and nonlinear one class partial least squares discriminant analysis
Zhe Yuan, Liangxiao Zhang, Du Wang, et al.
LWT (2020) Vol. 125, pp. 109247-109247
Closed Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

A Review of Machine Learning for Near-Infrared Spectroscopy
Wenwen Zhang, Liyanaarachchi Chamara Kasun, Qi Jie Wang, et al.
Sensors (2022) Vol. 22, Iss. 24, pp. 9764-9764
Open Access | Times Cited: 88
Rapid and sensitive approaches for detecting food fraud: A review on prospects and challenges
Ramesh Sharma, Pinku Chandra Nath, Bibhab Kumar Lodh, et al.
Food Chemistry (2024) Vol. 454, pp. 139817-139817
Closed Access | Times Cited: 17
Review of NIR spectroscopy methods for nondestructive quality analysis of oilseeds and edible oils
Li Xue, Liangxiao Zhang, Yong Zhang, et al.
Trends in Food Science & Technology (2020) Vol. 101, pp. 172-181
Open Access | Times Cited: 128
The composition, extraction, analysis, bioactivities, bioavailability and applications in food system of flaxseed (Linum usitatissimum L.) oil: A review
Jing Yang, Chaoting Wen, Yuqing Duan, et al.
Trends in Food Science & Technology (2021) Vol. 118, pp. 252-260
Closed Access | Times Cited: 85
Advanced process analytical tools for identification of adulterants in edible oils – A review
E.J. Rifna, R. Pandiselvam, Anjineyulu Kothakota, et al.
Food Chemistry (2021) Vol. 369, pp. 130898-130898
Closed Access | Times Cited: 67
Mass spectrometry in food authentication and origin traceability
Xinjing Dou, Liangxiao Zhang, Ruinan Yang, et al.
Mass Spectrometry Reviews (2022) Vol. 42, Iss. 5, pp. 1772-1807
Closed Access | Times Cited: 64
Near infrared spectroscopy combined with chemometrics for quantitative analysis of corn oil in edible blend oil
Huan Zhang, Xiao Hu, Limei Liu, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2022) Vol. 270, pp. 120841-120841
Closed Access | Times Cited: 55
Application of near-infrared spectroscopy for the nondestructive analysis of wheat flour: A review
Shun Zhang, Shuliang Liu, Li Shen, et al.
Current Research in Food Science (2022) Vol. 5, pp. 1305-1312
Open Access | Times Cited: 51
Near infrared spectroscopic variable selection by a novel swarm intelligence algorithm for rapid quantification of high order edible blend oil
Xihui Bian, Rongling Zhang, Peng Liu, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2022) Vol. 284, pp. 121788-121788
Closed Access | Times Cited: 39
An Affordable NIR Spectroscopic System for Fraud Detection in Olive Oil
Candela Melendreras, Ana Soldado, José M. Costa‐Fernández, et al.
Sensors (2023) Vol. 23, Iss. 3, pp. 1728-1728
Open Access | Times Cited: 25
Rapid quantification of grapeseed oil multiple adulterations using near-infrared spectroscopy coupled with a novel double ensemble modeling method
Xihui Bian, Yuxia Liu, Rongling Zhang, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2024) Vol. 311, pp. 124016-124016
Closed Access | Times Cited: 14
Utilizing near infrared hyperspectral imaging for quantitatively predicting adulteration in tapioca starch
Duangkamolrat Khamsopha, Woranitta Sahachairungrueng, Sontisuk Teerachaichayut
Food Control (2020) Vol. 123, pp. 107781-107781
Closed Access | Times Cited: 54
Comparison of near infrared spectroscopy and Raman spectroscopy for the identification and quantification through MCR-ALS and PLS of peanut oil adulterants
Rafael C. Castro, David S.M. Ribeiro, João L.M. Santos, et al.
Talanta (2021) Vol. 230, pp. 122373-122373
Closed Access | Times Cited: 43
Analytical approaches for the determination of adulterated animal fats and vegetable oils in food and non-food samples
Nayab Kanwal, Syed Ghulam Musharraf
Food Chemistry (2024) Vol. 460, pp. 140786-140786
Closed Access | Times Cited: 7
Discrimination of tea seed oil adulteration based on near-infrared spectroscopy and combined preprocessing method
Lingfei Kong, Chengzhao Wu, Hung‐Wing Li, et al.
Journal of Food Composition and Analysis (2024) Vol. 134, pp. 106560-106560
Closed Access | Times Cited: 6
Rapid detection of sesame oil multiple adulteration using a portable Raman spectrometer
Xue Li, Du Wang, Fei Ma, et al.
Food Chemistry (2022) Vol. 405, pp. 134884-134884
Closed Access | Times Cited: 28
Extraction of physicochemical properties from the fluorescence spectrum with 1D convolutional neural networks: Application to olive oil
Francesca Venturini, Michela Sperti, Umberto Michelucci, et al.
Journal of Food Engineering (2022) Vol. 336, pp. 111198-111198
Open Access | Times Cited: 24
Support vector machine-based rapid detection and quantification of butter yellow adulteration in mustard oil using NIR spectra
Rani Amsaraj, Sarma Mutturi
Infrared Physics & Technology (2023) Vol. 129, pp. 104543-104543
Closed Access | Times Cited: 15
Accurate quantification of TAGs to identify adulteration of edible oils by ultra-high performance liquid chromatography-quadrupole-time of flight-tandem mass spectrometry
Hailian Wei, Dandan Yang, Jin Mao, et al.
Food Research International (2023) Vol. 165, pp. 112544-112544
Closed Access | Times Cited: 14
Comparing data driven soft independent class analogy (DD-SIMCA) and one class partial least square (OC-PLS) to authenticate sacha inchi (Plukenetia volubilis L.) oil using portable NIR spectrometer
J.P. Cruz-Tirado, Daniela Muñoz-Pastor, Ingrid Alves de Moraes, et al.
Chemometrics and Intelligent Laboratory Systems (2023) Vol. 242, pp. 105004-105004
Closed Access | Times Cited: 13
QCM Sensor Arrays, Electroanalytical Techniques and NIR Spectroscopy Coupled to Multivariate Analysis for Quality Assessment of Food Products, Raw Materials, Ingredients and Foodborne Pathogen Detection: Challenges and Breakthroughs
David K. Bwambok, Noureen Siraj, Samantha Macchi, et al.
Sensors (2020) Vol. 20, Iss. 23, pp. 6982-6982
Open Access | Times Cited: 33
Adulteration Detection in Cactus Seed Oil: Integrating Analytical Chemistry and Machine Learning Approaches
Said El Harkaoui, Clint Audrey A. Dela Cruz, Aaron Roggenland, et al.
Current Research in Food Science (2025) Vol. 10, pp. 100986-100986
Open Access
Application of Vis/NIR and FTIR Spectroscopy combined with Chemometrics for the Authentication of Red fruit oil from Coconut oil
Mustika Erlinaningrum, Abdul Rohman, Agustina Ari Murti Budi Hastuti
Research Journal of Pharmacy and Technology (2025), pp. 1237-1243
Closed Access
Authentication of rapeseed variety based on hyperspectral imaging and chemometrics
Junjun Gong, Xinjing Dou, Du Wang, et al.
Applied Food Research (2025), pp. 100941-100941
Open Access
Rapid detection and quantification of adulteration in Chinese hawthorn fruits powder by near-infrared spectroscopy combined with chemometrics
Xuefen Sun, Huiling Li, Yi Yuan, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2020) Vol. 250, pp. 119346-119346
Closed Access | Times Cited: 30
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