Frank Will

2.6k total citations
83 papers, 2.0k citations indexed

About

Frank Will is a scholar working on Food Science, Biochemistry and Plant Science. According to data from OpenAlex, Frank Will has authored 83 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Food Science, 42 papers in Biochemistry and 42 papers in Plant Science. Recurrent topics in Frank Will's work include Phytochemicals and Antioxidant Activities (42 papers), Fermentation and Sensory Analysis (32 papers) and Horticultural and Viticultural Research (19 papers). Frank Will is often cited by papers focused on Phytochemicals and Antioxidant Activities (42 papers), Fermentation and Sensory Analysis (32 papers) and Horticultural and Viticultural Research (19 papers). Frank Will collaborates with scholars based in Germany, Austria and France. Frank Will's co-authors include Helmut Dietrich, C. Janzowski, Gerhard Eisenbrand, Matthias Baum, G. Dongowski, Achim Bub, Bernhard Watzl, Daniel Bonerz, Tanja Kautenburger and Selvaraju Veeriah and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Agricultural and Food Chemistry and Food Chemistry.

In The Last Decade

Frank Will

80 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Frank Will Germany 28 1.1k 763 722 557 342 83 2.0k
Neuza Mariko Aymoto Hassimotto Brazil 27 1.1k 1.0× 906 1.2× 754 1.0× 709 1.3× 362 1.1× 80 2.5k
Mark A. Kelm United States 9 1.4k 1.3× 608 0.8× 764 1.1× 518 0.9× 471 1.4× 11 2.2k
Rocío González‐Barrio Spain 23 995 0.9× 678 0.9× 534 0.7× 488 0.9× 677 2.0× 42 2.1k
Ireneusz Kapusta Poland 23 682 0.6× 789 1.0× 666 0.9× 482 0.9× 409 1.2× 119 2.0k
Mara Bacchiocca Italy 10 1.1k 1.0× 572 0.7× 612 0.8× 353 0.6× 272 0.8× 12 1.9k
Yoichi Nishiba Japan 22 661 0.6× 598 0.8× 557 0.8× 338 0.6× 425 1.2× 38 1.6k
Deng‐Jye Yang Taiwan 29 711 0.7× 518 0.7× 689 1.0× 582 1.0× 256 0.7× 63 2.3k
Xue‐Hui Su China 8 1.0k 1.0× 751 1.0× 595 0.8× 330 0.6× 222 0.6× 11 1.8k
Vesna Tumbas Serbia 25 943 0.9× 688 0.9× 959 1.3× 392 0.7× 260 0.8× 40 1.9k
Koan Sik Woo South Korea 23 451 0.4× 742 1.0× 797 1.1× 508 0.9× 492 1.4× 134 2.0k

Countries citing papers authored by Frank Will

Since Specialization
Citations

This map shows the geographic impact of Frank Will'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 Frank Will with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Will more than expected).

Fields of papers citing papers by Frank Will

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frank Will. 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 Frank Will. The network helps show where Frank Will may publish in the future.

Co-authorship network of co-authors of Frank Will

This figure shows the co-authorship network connecting the top 25 collaborators of Frank Will. A scholar is included among the top collaborators of Frank Will 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 Frank Will. Frank Will 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.
Albuquerque, Wendell, Martin Gand, Holger Zorn, et al.. (2025). Investigations into protein reduction in grape must and wine: Screening the efficacy of 21 peptidases and the effects of thermal treatments, ultrasound, and reducing agents. European Food Research and Technology. 251(7). 1935–1950.
3.
Ludwig, Michael, et al.. (2023). HS–SPME–GC–MS profiling and sensory analyses of juices from red-fleshed ‘Weirouge’ apples made with innovative and conventional dejuicing systems. European Food Research and Technology. 249(12). 3201–3216. 2 indexed citations
4.
Ludwig, Michael, et al.. (2023). Investigations into the stability of anthocyanins in model solutions and blackcurrant juices produced with various dejuicing technologies. European Food Research and Technology. 249(7). 1771–1784. 5 indexed citations
5.
Albuquerque, Wendell, Parviz Ghezellou, Frank Will, et al.. (2023). Mass Spectrometry-Based Proteomic Profiling of a Silvaner White Wine. Biomolecules. 13(4). 650–650. 3 indexed citations
6.
Albuquerque, Wendell, Parviz Ghezellou, Martin Gand, et al.. (2023). Composition, ζ Potential, and Molar Mass Distribution of 20 Must and Wine Colloids from Five Different Cultivars Obtained during Four Consecutive Vintages. Journal of Agricultural and Food Chemistry. 72(4). 1938–1948. 4 indexed citations
7.
Will, Frank, et al.. (2023). Additive and synergistic antifungal effects of copper and phenolic extracts from grape cane and apples. Pest Management Science. 79(9). 3334–3341. 6 indexed citations
8.
Albuquerque, Wendell, Parviz Ghezellou, Frank Will, et al.. (2022). Recombinant Thaumatin-Like Protein (rTLP) and Chitinase (rCHI) from Vitis vinifera as Models for Wine Haze Formation. Molecules. 27(19). 6409–6409. 4 indexed citations
9.
Albuquerque, Wendell, et al.. (2021). Haze Formation and the Challenges for Peptidases in Wine Protein Fining. Journal of Agricultural and Food Chemistry. 69(48). 14402–14414. 10 indexed citations
10.
Dietrich, Helmut, et al.. (2015). Influence of polysaccharides on wine protein aggregation. Food Chemistry. 200. 38–45. 40 indexed citations
11.
Will, Frank, et al.. (2015). Changes in anthocyanins and berry color of 'Plavac mali' grape during ripening. 65(3). 130–142. 2 indexed citations
12.
Teller, Nicole, Melanie Esselen, Ute Boettler, et al.. (2013). Apple procyanidins affect several members of the ErbB receptor tyrosine kinase family in vitro. Food & Function. 4(5). 689–689. 8 indexed citations
13.
Will, Frank, et al.. (2011). Transfer of substances during the alcoholic maceration of green walnuts (Juglans regia L.).. 61(3). 179–186. 1 indexed citations
14.
Bonerz, Daniel, Frank Will, Claus‐Dieter Patz, et al.. (2010). Anthocyanin aging in juices and concentrates of the Aroniabeere (Aronia melanocarpa).. Deutsche Lebensmittel-Rundschau. 106(10). 549–559. 1 indexed citations
15.
Bonerz, Daniel, Frank Will, Claus‐Dieter Patz, et al.. (2009). Anthocyanin changes in black currant juice and concentrates - Part 1: Kinetics of the decrease in anthocyanins during storage.. Deutsche Lebensmittel-Rundschau. 105(3). 176–182. 4 indexed citations
16.
Dietrich, Helmut, et al.. (2009). Production of red grape juice and anthocyanin extract from the marc of anthocyanin-rich grape varieties.. Deutsche Lebensmittel-Rundschau. 105(11). 695–702. 2 indexed citations
17.
Dongowski, G., et al.. (2006). Physiologische Wirkungen von Extraktionssäften aus Äpfeln, Weinbeeren und Roten Beten in vitro und am Menschen. Deutsche Lebensmittel-Rundschau. 102(8). 350–365. 4 indexed citations
18.
Patz, Claus‐Dieter, Frank Will, Helmut Dietrich, et al.. (2006). Characterization of juices of different apple cultivars. Deutsche Lebensmittel-Rundschau. 102(9). 426–435. 9 indexed citations
19.
Janzowski, C., et al.. (2006). Reduction of oxidative cell damage by an anthocyanin/polyphenolic rich fruit juice in an intervention study with patients on hemodialysis.. Cancer Epidemiology and Prevention Biomarkers. 15. 2 indexed citations
20.
Will, Frank, et al.. (2003). Enzymatic liquefaction of apple mash by a two step process. 13(6). 429. 1 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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