Georg Weingart

577 total citations
9 papers, 432 citations indexed

About

Georg Weingart is a scholar working on Molecular Biology, Food Science and Biomedical Engineering. According to data from OpenAlex, Georg Weingart has authored 9 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Food Science and 3 papers in Biomedical Engineering. Recurrent topics in Georg Weingart's work include Fermentation and Sensory Analysis (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers) and Advanced Chemical Sensor Technologies (3 papers). Georg Weingart is often cited by papers focused on Fermentation and Sensory Analysis (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers) and Advanced Chemical Sensor Technologies (3 papers). Georg Weingart collaborates with scholars based in Austria, Italy and Germany. Georg Weingart's co-authors include Fulvio Mattivi, Rainer Schuhmacher, Astrid Forneck, Ron Wehrens, Nora K. N. Neumann, Falk Liebner, Manuel Becker, Michaela Griesser, Курт Вармуза and Silvia Carlin and has published in prestigious journals such as Talanta, Plant Physiology and Biochemistry and Journal of Chromatography B.

In The Last Decade

Georg Weingart

9 papers receiving 423 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Georg Weingart Austria 8 211 195 144 59 52 9 432
Mingjie Chen China 17 273 1.3× 299 1.5× 230 1.6× 142 2.4× 31 0.6× 45 745
Antonia Spadafora Italy 9 235 1.1× 224 1.1× 88 0.6× 41 0.7× 17 0.3× 13 531
Xungang Gu China 10 232 1.1× 150 0.8× 103 0.7× 95 1.6× 24 0.5× 16 413
F.R. De Salvador Italy 14 355 1.7× 161 0.8× 64 0.4× 69 1.2× 46 0.9× 43 548
Mickael M. Maucourt France 11 320 1.5× 251 1.3× 143 1.0× 54 0.9× 34 0.7× 15 533
Henk Maarse Netherlands 8 155 0.7× 111 0.6× 221 1.5× 71 1.2× 80 1.5× 12 467
Joseph Lech United States 8 214 1.0× 108 0.6× 105 0.7× 39 0.7× 23 0.4× 11 340
Dániel Krüzselyi Hungary 12 118 0.6× 100 0.5× 78 0.5× 55 0.9× 11 0.2× 25 366
D. Mott Austria 9 110 0.5× 82 0.4× 118 0.8× 26 0.4× 135 2.6× 12 320
Asdrúbal Burgos Germany 13 386 1.8× 378 1.9× 57 0.4× 32 0.5× 22 0.4× 19 695

Countries citing papers authored by Georg Weingart

Since Specialization
Citations

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

Fields of papers citing papers by Georg Weingart

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Georg Weingart

This figure shows the co-authorship network connecting the top 25 collaborators of Georg Weingart. A scholar is included among the top collaborators of Georg Weingart 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 Georg Weingart. Georg Weingart is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
2.
Griesser, Michaela, Georg Weingart, Nora K. N. Neumann, et al.. (2015). Severe drought stress is affecting selected primary metabolites, polyphenols, and volatile metabolites in grapevine leaves (Vitis vinifera cv. Pinot noir). Plant Physiology and Biochemistry. 88. 17–26. 144 indexed citations
3.
Vrhovšek, Urška, Cesare Lotti, Domenico Masuero, et al.. (2014). Quantitative metabolic profiling of grape, apple and raspberry volatile compounds (VOCs) using a GC/MS/MS method. Journal of Chromatography B. 966. 132–139. 63 indexed citations
4.
Wehrens, Ron, Georg Weingart, & Fulvio Mattivi. (2014). metaMS: An open-source pipeline for GC–MS-based untargeted metabolomics. Journal of Chromatography B. 966. 109–116. 76 indexed citations
5.
Franceschi, Pietro, Nir Shahaf, Matthias Scholz, et al.. (2014). MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments. Frontiers in Bioengineering and Biotechnology. 2. 28 indexed citations
6.
Lawo, N.C., Georg Weingart, Rainer Schuhmacher, & Astrid Forneck. (2011). The volatile metabolome of grapevine roots: First insights into the metabolic response upon phylloxera attack. Plant Physiology and Biochemistry. 49(9). 1059–1063. 47 indexed citations
7.
Sulyok, Michael, Georg Weingart, Bernhard Kluger, et al.. (2011). Evaluation of settled floor dust for the presence of microbial metabolites and volatile anthropogenic chemicals in indoor environments by LC–MS/MS and GC–MS methods. Talanta. 85(4). 2027–2038. 18 indexed citations
8.
Weingart, Georg, Bernhard Kluger, Astrid Forneck, Rudolf Krska, & Rainer Schuhmacher. (2011). Establishment and Application of a Metabolomics Workflow for Identification and Profiling of Volatiles from Leaves of Vitis vinifera by HS‐SPME‐GC‐MS. Phytochemical Analysis. 23(4). 345–358. 33 indexed citations
9.
Weingart, Georg, Heidi Schwartz, Reinhard Eder, & Gerhard Sontag. (2010). Determination of geosmin and 2,4,6-trichloroanisole in white and red Austrian wines by headspace SPME-GC/MS and comparison with sensory analysis. European Food Research and Technology. 231(5). 771–779. 19 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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