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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:

Near-infrared spectroscopy with chemometrics for identification and quantification of adulteration in high-quality stingless bee honey
Muna E. Raypah, Loh Jing Zhi, Lim Zi Loon, et al.
Chemometrics and Intelligent Laboratory Systems (2022) Vol. 224, pp. 104540-104540
Closed Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

A comprehensive review on unethical honey: Validation by emerging techniques
Dilpreet Singh Brar, Kirty Pant, Reshma Krishnan, et al.
Food Control (2022) Vol. 145, pp. 109482-109482
Closed Access | Times Cited: 41
Non-destructive detection of single corn seed vigor based on visible/near-infrared spatially resolved spectroscopy combined with chemometrics
Wenxi Liu, Bin Luo, Kai Kang, et al.
Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy (2024) Vol. 312, pp. 124089-124089
Closed Access | Times Cited: 11
Adulteration quantification of cheap honey in high-quality Manuka honey by two-dimensional correlation spectroscopy combined with deep learning
Xi-Jun Wu, Baoran Xu, Hao Luo, et al.
Food Control (2023) Vol. 154, pp. 110010-110010
Closed Access | Times Cited: 21
Development of PCA-MLP Model Based on Visible and Shortwave Near Infrared Spectroscopy for Authenticating Arabica Coffee Origins
Agus Dharmawan, Rudiati Evi Masithoh, Hanim Zuhrotul Amanah
Foods (2023) Vol. 12, Iss. 11, pp. 2112-2112
Open Access | Times Cited: 20
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
Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months
Nur Aisyah Syafinaz Suarin, Kim Seng Chia, Siti Fatimah Zaharah Mohamad Fuzi
Knowledge-Based Systems (2024) Vol. 295, pp. 111817-111817
Closed Access | Times Cited: 4
Development of FTIR-ATR Spectra and PLS Regression Combination Model for Discrimination of Pure and Adulterated Acacia Honey
Rafieh Fakhlaei, Arman Amani Babadi, M.A. Naziruddin, et al.
Food Control (2024) Vol. 169, pp. 110996-110996
Closed Access | Times Cited: 4
Application of subspace ensemble radical basis function networks to quantitative analysis of near-infrared and mid-infrared spectroscopy
Hui Chen, Chao Tan, Zan Lin
Microchemical Journal (2025), pp. 113354-113354
Closed Access
Volatilomic with chemometrics: a toward authentication approach for food authenticity control
Mohammad Noshad, Behrooz Alizadeh Behbahani, Ioannis K. Karabagias
European Food Research and Technology (2023) Vol. 249, Iss. 9, pp. 2215-2226
Closed Access | Times Cited: 9
Non-Targeted Detection and Quantification of Food Adulteration of High-Quality Stingless Bee Honey (SBH) via a Portable LED-Based Fluorescence Spectroscopy
Diding Suhandy, Dimas Firmanda Al Riza, Meinilwita Yulia, et al.
Foods (2023) Vol. 12, Iss. 16, pp. 3067-3067
Open Access | Times Cited: 9
Investigating Eucalyptus essential oil: classification and prediction of volatile compounds using GC-FID and FT-MIR spectroscopy combined with chemometric techniques
Abdennacer El Mrabet, Aimen El Orche, Abderrahim Diane, et al.
Vegetos (2024) Vol. 37, Iss. 2, pp. 683-694
Closed Access | Times Cited: 3
Reflectance spectra for identifying stress in different parts of leaf: a case study on oil palm seedlings
Muna E. Raypah, Muhammad Imran Mohd Nasru, Muhammad Hazeem Hasnol Nazim, et al.
International Journal of Remote Sensing (2024) Vol. 45, Iss. 3, pp. 954-980
Closed Access | Times Cited: 3
Classification and quantification of adulterants in Alaska pollock based on fourier transform near-infrared spectroscopy with chemometrics
Shijia Feng, Shou Qi, Chen Chen, et al.
Food Bioscience (2024) Vol. 59, pp. 104003-104003
Closed Access | Times Cited: 2
Geographical and entomological differentiation of Philippine honey by multivariate analysis of FTIR spectra
Jeb Reece Grabato, Karl Ezra Pilario, Jose Rene L. Micor, et al.
Journal of Food Composition and Analysis (2022) Vol. 114, pp. 104853-104853
Open Access | Times Cited: 10
Condiment recognition using convolutional neural networks with attention mechanism
Jiangong Ni, Yifan Zhao, Zhigang Zhou, et al.
Journal of Food Composition and Analysis (2022) Vol. 115, pp. 104964-104964
Closed Access | Times Cited: 8
Discrimination of the Specific Gravity of Urine Using Spectrophotometry by the Parallel Connection of Two Modified Feature Selection Methods
Chengbo Yang, Zhilong Cai, Qingzhi Li, et al.
Analytical Letters (2024) Vol. 57, Iss. 18, pp. 3022-3036
Closed Access | Times Cited: 1
Detection of Fusarium spp. infection in potato (Solanum tuberosum L.) during postharvest storage through visible–near-infrared and shortwave–near-infrared reflectance spectroscopy
Eko Prasetyo, Hanim Zuhrotul Amanah, Ibnu Farras, et al.
Open Agriculture (2024) Vol. 9, Iss. 1
Open Access | Times Cited: 1
Non-invasive prediction of maca powder adulteration using a pocket-sized spectrophotometer and machine learning techniques
John‐Lewis Zinia Zaukuu, Zeenatu Suglo Adams, Nana Ama Donkor-Boateng, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Estimation of peanut quality based on free fatty acids and peroxide value by application of FTNIR and chemometrics approach
Rakesh Kumar Raigar, Shubhangi Srivastava, Hari Niwas Mishra
Food Chemistry Advances (2024) Vol. 4, pp. 100735-100735
Open Access | Times Cited: 1
A comprehensive introduction to honey adulteration
Dilpreet Singh Brar, Vikas Nanda
Elsevier eBooks (2024), pp. 63-91
Closed Access | Times Cited: 1
Research of 2D-COS with metabolomics modifications through deep learning for traceability of wine
Zhuo-Kang Wang, Na Ta, Haicheng Wei, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Development of automatic tuning for combined preprocessing and hyperparameters of machine learning and its application to NIR spectral data of coconut milk adulteration
Agustami Sitorus, Ravipat Lapcharoensuk
Food Chemistry (2024) Vol. 457, pp. 140108-140108
Closed Access | Times Cited: 1
Detection of adulterations in native stingless bees honey from Argentina using UV–Vis spectroscopy coupled with chemometrics
Karenina Marcinkevicius, Gerardo P. Gennari, Virginia Salomón, et al.
Journal of Food Measurement & Characterization (2024) Vol. 18, Iss. 9, pp. 7283-7294
Closed Access | Times Cited: 1
Accurate Traceability of Stable C, H, O, N Isotope Ratios and Multi-Element Analysis Combined with Chemometrics for Chrysanthemi Flos ‘Hangbaiju’ from Different Origins
Xiuyun Bai, Hengye Chen, Wanjun Long, et al.
Chemosensors (2022) Vol. 10, Iss. 12, pp. 529-529
Open Access | Times Cited: 4
Spectral response to early detection of stressed oil palm seedlings using near-infrared reflectance spectra at region 900-1000 nm
Muna E. Raypah, Muhammad Imran Mohd Nasru, Muhammad Hazeem Hasnol Nazim, et al.
Infrared Physics & Technology (2023) Vol. 135, pp. 104984-104984
Closed Access | Times Cited: 2
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