Selina C. Wang

2.3k total citations
105 papers, 1.8k citations indexed

About

Selina C. Wang is a scholar working on Organic Chemistry, Food Science and Biochemistry. According to data from OpenAlex, Selina C. Wang has authored 105 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Organic Chemistry, 34 papers in Food Science and 28 papers in Biochemistry. Recurrent topics in Selina C. Wang's work include Edible Oils Quality and Analysis (52 papers), Phytochemicals and Antioxidant Activities (23 papers) and Spectroscopy and Chemometric Analyses (21 papers). Selina C. Wang is often cited by papers focused on Edible Oils Quality and Analysis (52 papers), Phytochemicals and Antioxidant Activities (23 papers) and Spectroscopy and Chemometric Analyses (21 papers). Selina C. Wang collaborates with scholars based in United States, Spain and Germany. Selina C. Wang's co-authors include Dean J. Tantillo, Xueqi Li, Hilary S. Green, Hanjiang Zhu, Charles F. Shoemaker, Roberto J. Avena‐Bustillos, Hefei Zhao, Alegría Carrasco‐Pancorbo, Mendel Friedman and Lucía Olmo‐García and has published in prestigious journals such as Journal of the American Chemical Society, Angewandte Chemie International Edition and SHILAP Revista de lepidopterología.

In The Last Decade

Selina C. Wang

102 papers receiving 1.8k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Selina C. Wang United States 27 947 518 388 375 352 105 1.8k
Lorenzo Cecchi Italy 27 785 0.8× 670 1.3× 336 0.9× 263 0.7× 531 1.5× 89 1.6k
Aleksandra Szydłowska‐Czerniak Poland 22 596 0.6× 509 1.0× 188 0.5× 297 0.8× 649 1.8× 80 1.7k
Wenceslao Moreda Spain 25 1.0k 1.1× 478 0.9× 556 1.4× 373 1.0× 257 0.7× 63 1.7k
María del Camino Spain 29 1.3k 1.4× 769 1.5× 597 1.5× 525 1.4× 541 1.5× 98 2.6k
Qi Zhou China 27 632 0.7× 793 1.5× 184 0.5× 469 1.3× 455 1.3× 100 2.1k
Noelia Tena Spain 19 558 0.6× 467 0.9× 455 1.2× 303 0.8× 388 1.1× 37 1.4k
Cristiano Augusto Ballus Brazil 21 275 0.3× 502 1.0× 231 0.6× 203 0.5× 450 1.3× 66 1.3k
Vassilis Dourtoglou Greece 24 544 0.6× 608 1.2× 171 0.4× 575 1.5× 417 1.2× 69 1.8k
Renzo Bortolomeazzi Italy 22 396 0.4× 582 1.1× 129 0.3× 423 1.1× 366 1.0× 46 1.7k
Paola Zunin Italy 27 272 0.3× 453 0.9× 317 0.8× 321 0.9× 424 1.2× 64 1.4k

Countries citing papers authored by Selina C. Wang

Since Specialization
Citations

This map shows the geographic impact of Selina C. Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Selina C. Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Selina C. Wang more than expected).

Fields of papers citing papers by Selina C. Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Selina C. Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Selina C. Wang. The network helps show where Selina C. Wang may publish in the future.

Co-authorship network of co-authors of Selina C. Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Selina C. Wang. A scholar is included among the top collaborators of Selina C. Wang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Selina C. Wang. Selina C. Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Kim, Y., et al.. (2025). Synergistic antimicrobial activities of phenolic-rich extract derived from olive pomace and UV-A light against bacterial pathogens and their biofilms. Current Research in Food Science. 10. 101071–101071. 2 indexed citations
3.
Hennebelle, Marie, et al.. (2024). Oil polyunsaturated fatty acid composition but not tocopherol levels determine oxylipin formation in plant and algae oils during pan-frying. Journal of Food Composition and Analysis. 136. 106739–106739. 2 indexed citations
4.
Yarnes, Christopher T., et al.. (2023). Bulk and Compound-Specific Stable Isotope Analysis for the Authentication of Walnuts (Juglans regia) Origins. Journal of Agricultural and Food Chemistry. 1 indexed citations
5.
Sbodio, Adrian, Duoduo Wang, Graham B. Seymour, et al.. (2023). Double CRISPR knockout of pectin degrading enzymes improves tomato shelf‐life while ensuring fruit quality. Plants People Planet. 6(2). 330–340. 12 indexed citations
6.
7.
Ampofo, Josephine, et al.. (2022). Oxidative Stability of Walnut Kernel and Oil: Chemical Compositions and Sensory Aroma Compounds. Foods. 11(19). 3151–3151. 10 indexed citations
8.
Girelli, Chiara Roberta, et al.. (2022). Geographical Origin Assessment of Extra Virgin Olive Oil via NMR and MS Combined with Chemometrics as Analytical Approaches. Foods. 11(1). 113–113. 40 indexed citations
9.
Li, Xueqi, Talwinder S. Kahlon, Selina C. Wang, & Mendel Friedman. (2021). Low Acrylamide Flatbreads from Colored Corn and Other Flours. Foods. 10(10). 2495–2495. 9 indexed citations
10.
Green, Hilary S., et al.. (2021). Analysis and Authentication of Avocado Oil Using High Resolution NMR Spectroscopy. Molecules. 26(2). 310–310. 34 indexed citations
11.
Wang, Selina C., et al.. (2021). Walnut (Juglans regia L.) Volatile Compounds Indicate Kernel and Oil Oxidation. Foods. 10(2). 329–329. 41 indexed citations
12.
Li, Xueqi, Talwinder S. Kahlon, Selina C. Wang, & Mendel Friedman. (2021). Low Acrylamide Flatbreads Prepared from Colored Rice Flours and Relationship to Asparagine and Proximate Content of Flours and Flatbreads. Foods. 10(12). 2909–2909. 6 indexed citations
13.
Liu, Yan, et al.. (2020). Potential development of non-synthetic food additives from orange processing by-products—a review.. Food Quality and Safety. 5. 18 indexed citations
14.
Kahlon, Talwinder S., et al.. (2019). Acrylamide Content of Experimental and Commercial Flatbreads. Journal of Food Science. 84(3). 659–666. 24 indexed citations
15.
Wang, Selina C., et al.. (2019). Comparative Study of Four Analytical Methods for the Routine Determination of Acrylamide in Black Ripe Olives. Journal of Agricultural and Food Chemistry. 67(46). 12633–12641. 16 indexed citations
16.
Green, Hilary S., Xueqi Li, Mauro De Pra, et al.. (2019). A rapid method for the detection of extra virgin olive oil adulteration using UHPLC-CAD profiling of triacylglycerols and PCA. Food Control. 107. 106773–106773. 46 indexed citations
17.
Carrasquilla‐Garcia, Noelia, et al.. (2019). Analysis of Microsatellites (SSRs) in Processed Olives as a Means of Cultivar Traceability and Authentication. Journal of Agricultural and Food Chemistry. 68(4). 1110–1117. 7 indexed citations
18.
Li, Xueqi & Selina C. Wang. (2018). Shelf Life of Extra Virgin Olive Oil and Its Prediction Models. Journal of Food Quality. 2018. 1–15. 35 indexed citations
19.
Paradisi, Francesca, et al.. (2018). β-Glucosidase Discovery and Design for the Degradation of Oleuropein. ACS Omega. 3(11). 15754–15762. 12 indexed citations
20.
Avena‐Bustillos, Roberto J., Ivana Sedej, Dirk M. Holstege, et al.. (2016). Evaluation of thermal processing variables for reducing acrylamide in canned black ripe olives. Journal of Food Engineering. 191. 124–130. 26 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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