Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Rapid and Low-Cost Quantification of Adulteration Content in Camellia Oil Utilizing UV-Vis-NIR Spectroscopy Combined with Feature Selection Methods
Qiang Liu, Zhongliang Gong, Dapeng Li, et al.
Molecules (2023) Vol. 28, Iss. 16, pp. 5943-5943
Open Access | Times Cited: 10

Showing 10 citing articles:

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: 3
Grade Classification of Camellia Seed Oil Based on Hyperspectral Imaging Technology
Yuqi Gu, Jianhua Wu, Yijun Guo, et al.
Foods (2024) Vol. 13, Iss. 20, pp. 3331-3331
Open Access | Times Cited: 1
A fast and highly efficient strategy for detection of Camellia Oil adulteration using Machine Learning Assisted SERS
Peipei Xu, Qingling Nie, Runbing Huang, et al.
LWT (2024), pp. 117069-117069
Open Access | Times Cited: 1
Determination of Bioactive Compounds in Buriti Oil by Prediction Models Through Mid-infrared Spectroscopy
Braian Saimon Frota da Silva, Nelson Rosa Ferreira, Renan Campos Chisté, et al.
Food Analytical Methods (2024) Vol. 17, Iss. 9, pp. 1359-1372
Open Access | Times Cited: 1
Adulteration identification of Hainan camellia (Camellia oleifera Abel.) oil based on comprehensive two‐dimensional gas chromatography and quadrupole time‐of‐flight mass coupled with chemometrics spectrometry
Xiaoyan Zheng, Shanying Zhang, Binling Ai, et al.
International Journal of Food Science & Technology (2024) Vol. 59, Iss. 4, pp. 2305-2317
Closed Access
A Fast and Highly Efficient Strategy for Detection of Camellia Oil Adulteration Using Machine Learning Assisted Sers
Peipei Xu, Qingling Nie, Runbing Huang, et al.
(2024)
Closed Access
Trends in authentication of edible oils using vibrational spectroscopic techniques
Banu Özen, Çağrı Çavdaroğlu, Figen Tokatlı
Analytical Methods (2024) Vol. 16, Iss. 26, pp. 4216-4233
Open Access
Detection and quantification of groundnut oil adulteration with machine learning using a comparative approach with NIRS and UV–VIS
John‐Lewis Zinia Zaukuu, Manal Napari Adam, Abena Amoakoa Nkansah, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Discriminating moisture content in Fraxinus mandshurica Rupr logs using fusion of 2D GADF spectral images and 1D NIR spectra
Qiang Liu, Jiawei Zhang, Shuyang Lin, et al.
Microchemical Journal (2024) Vol. 208, pp. 112394-112394
Closed Access
Quantitatively Detecting Camellia Oil Products Adulterated by Rice Oil and Corn Oil Using Raman Spectroscopy: A Comparative Study Between Models Utilizing Machine Learning Algorithms and Chemometric Algorithms
Henan Liu, Sijia Ma, Ni Liang, et al.
Foods (2024) Vol. 13, Iss. 24, pp. 4182-4182
Open Access
Page 1

Scroll to top