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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:

Comparative Study of Several Machine Learning Algorithms for Classification of Unifloral Honeys
Fernando Mateo, Andrea Tarazona, Eva M. Mateo
Foods (2021) Vol. 10, Iss. 7, pp. 1543-1543
Open Access | Times Cited: 19

Showing 19 citing articles:

Advanced evaluation techniques: Gas sensor networks, machine learning, and chemometrics for fraud detection in plant and animal products
Hamed Karami, Mohammed Kamruzzaman, James A. Covington, et al.
Sensors and Actuators A Physical (2024) Vol. 370, pp. 115192-115192
Closed Access | Times Cited: 12
Rapid identification and quantification of vegetable oil adulteration in raw milk using a flash gas chromatography electronic nose combined with machine learning
Huaixiang Tian, Di Wu, Bin Chen, et al.
Food Control (2023) Vol. 150, pp. 109758-109758
Closed Access | Times Cited: 27
Application of Spatial Offset Raman Spectroscopy (SORS) and Machine Learning for Sugar Syrup Adulteration Detection in UK Honey
M. A. Shehata, Sophie Dodd, Sara Mosca, et al.
Foods (2024) Vol. 13, Iss. 15, pp. 2425-2425
Open Access | Times Cited: 6
Grape Cultivar Identification and Classification by Machine Olfaction Analysis of Leaf Volatiles
Ali Khorramifar, Hamed Karami, A. D. Wilson, et al.
Chemosensors (2022) Vol. 10, Iss. 4, pp. 125-125
Open Access | Times Cited: 29
Multi-instrument spectroscopic study for authentication of curcumin content in commercial turmeric powders using machine learning algorithms
Rani Amsaraj, Rishi Ranjan, Bhanu Prakash Rachaiah, et al.
Journal of Food Composition and Analysis (2024) Vol. 134, pp. 106543-106543
Closed Access | Times Cited: 3
Highlighting the Potential of Attenuated Total Reflectance – Fourier Transform Infrared (ATR-FTIR) Spectroscopy to Characterize Honey Samples with Principal Component Analysis (PCA)
Alexandros-George Ioannou, Eftichia Kritsi, Vassilia J. Sinanoglou, et al.
Analytical Letters (2022) Vol. 56, Iss. 5, pp. 789-806
Closed Access | Times Cited: 16
Rapid identification and semi-quantification of adulteration in walnut oil by using excitation–emission matrix fluorescence spectroscopy coupled with chemometrics and ensemble learning
Xiaozhi Wang, Hai‐Long Wu, Tong Wang, et al.
Journal of Food Composition and Analysis (2022) Vol. 117, pp. 105094-105094
Closed Access | Times Cited: 11
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: 9
Classification of Monofloral Honeys by Measuring a Low-Cost Electronic Nose Prototype Based on Resistive Metal Oxide Sensors
Eduardo González María, Antonio Madueño Luna, Agustín Conesa-Celdrán, et al.
Agronomy (2023) Vol. 13, Iss. 8, pp. 2183-2183
Open Access | Times Cited: 5
The Effect of Climate Change on Organic Honey Efficiency in Türkiye via Machine Learning
Ayça Nur ŞAHİN DEMİREL
(2024)
Open Access | Times Cited: 1
Buzzing with Intelligence: Current Issues in Apiculture and the Role of Artificial Intelligence (AI) to Tackle It
Putri Kusuma Astuti, Bettina Hegedűs, Andrzej Oleksa, et al.
Insects (2024) Vol. 15, Iss. 6, pp. 418-418
Open Access | Times Cited: 1
A non-destructive testing method for early detection of ginseng root diseases using machine learning technologies based on leaf hyperspectral reflectance
Guiping Zhao, Yifei Pei, Ruoqi Yang, et al.
Frontiers in Plant Science (2022) Vol. 13
Open Access | Times Cited: 7
Combining multi-dimensional molecular fingerprints to predict the hERG cardiotoxicity of compounds
Weizhe Ding, Yang Nan, Juanshu Wu, et al.
Computers in Biology and Medicine (2022) Vol. 144, pp. 105390-105390
Open Access | Times Cited: 6
Prediction of Pakistani Honey Authenticity Through Machine Learning
Noureen Fatima, Ghulam Mujtaba, Adnan Akhunzada, et al.
IEEE Access (2022) Vol. 10, pp. 87508-87521
Closed Access | Times Cited: 5
Machine learning driven portable Vis-SWNIR spectrophotometer for non-destructive classification of raw tomatoes based on lycopene content
Arun Sharma, Ritesh Kumar, Nishant Kumar, et al.
Vibrational Spectroscopy (2023) Vol. 130, pp. 103628-103628
Open Access | Times Cited: 2
A Dataset for Kinship Estimation from Image of Hand Using Machine Learning
Sarah Fathi, Mazin H. Aziz
Iraqi Journal for Electrical And Electronic Engineering (2024) Vol. 20, Iss. 2, pp. 127-136
Open Access
Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment
Sigfredo Fuentes
Foods (2022) Vol. 11, Iss. 9, pp. 1192-1192
Open Access | Times Cited: 3
Classification of Monofloral Honeys by Measuring Electrical Impedance Based on Neural Networks
Eduardo González María, Antonio Madueño Luna, A. Ruiz-Canales, et al.
Agronomy (2022) Vol. 12, Iss. 8, pp. 1929-1929
Open Access | Times Cited: 3
Implementation of Artificial Intelligence in Food Science, Food Quality, and Consumer Preference Assessment
Sigfredo Fuentes
MDPI eBooks (2022)
Open Access
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