Anna Kicherer

964 total citations
32 papers, 658 citations indexed

About

Anna Kicherer is a scholar working on Plant Science, Food Science and Ecology. According to data from OpenAlex, Anna Kicherer has authored 32 papers receiving a total of 658 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Plant Science, 14 papers in Food Science and 11 papers in Ecology. Recurrent topics in Anna Kicherer's work include Horticultural and Viticultural Research (27 papers), Fermentation and Sensory Analysis (14 papers) and Remote Sensing in Agriculture (8 papers). Anna Kicherer is often cited by papers focused on Horticultural and Viticultural Research (27 papers), Fermentation and Sensory Analysis (14 papers) and Remote Sensing in Agriculture (8 papers). Anna Kicherer collaborates with scholars based in Germany, Australia and Austria. Anna Kicherer's co-authors include Reinhard Töpfer, Katja Herzog, Ribana Roscher, Heiner Kuhlmann, Lasse Klingbeil, Markus Wieland, Wolfgang Förstner, Ralf T. Voegele, Andreas Backhaus and Udo Seiffert and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and Frontiers in Plant Science.

In The Last Decade

Anna Kicherer

32 papers receiving 634 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anna Kicherer Germany 15 576 237 130 113 102 32 658
Katja Herzog Germany 14 537 0.9× 212 0.9× 123 0.9× 104 0.9× 82 0.8× 36 611
Vidyasagar Sathuvalli United States 16 762 1.3× 255 1.1× 170 1.3× 53 0.5× 110 1.1× 61 1.0k
Misha T. Kwasniewski United States 12 554 1.0× 218 0.9× 214 1.6× 143 1.3× 60 0.6× 28 720
Salvador Gutiérrez Spain 17 585 1.0× 251 1.1× 140 1.1× 304 2.7× 58 0.6× 43 811
Borja Millán Spain 19 758 1.3× 318 1.3× 168 1.3× 252 2.2× 43 0.4× 26 868
Md Sultan Mahmud United States 12 539 0.9× 145 0.6× 79 0.6× 127 1.1× 34 0.3× 29 751
Victor Partel United States 7 617 1.1× 304 1.3× 39 0.3× 88 0.8× 25 0.2× 10 824
Anastasia L. Lagopodi Greece 19 911 1.6× 197 0.8× 84 0.6× 93 0.8× 410 4.0× 45 1.1k
Sanaz Jarolmasjed United States 9 415 0.7× 276 1.2× 33 0.3× 147 1.3× 32 0.3× 10 609
David Bohnenkamp Germany 7 526 0.9× 318 1.3× 50 0.4× 341 3.0× 103 1.0× 8 760

Countries citing papers authored by Anna Kicherer

Since Specialization
Citations

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

Fields of papers citing papers by Anna Kicherer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna Kicherer

This figure shows the co-authorship network connecting the top 25 collaborators of Anna Kicherer. A scholar is included among the top collaborators of Anna Kicherer 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 Anna Kicherer. Anna Kicherer 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.
Herzog, Katja, et al.. (2025). High-throughput phenotyping in grapevine breeding research: technologies and applications. OENO One. 59(3). 1 indexed citations
2.
Schwander, Florian, et al.. (2024). Non-destructive quantification of key quality characteristics in individual grapevine berries using near-infrared spectroscopy. Frontiers in Plant Science. 15. 1386951–1386951. 1 indexed citations
3.
Schwander, Florian, et al.. (2023). Determination of Sugars and Acids in Grape Must Using Miniaturized Near-Infrared Spectroscopy. Sensors. 23(11). 5287–5287. 4 indexed citations
4.
Kicherer, Anna, et al.. (2022). Detection of Anomalous Grapevine Berries Using Variational Autoencoders. Frontiers in Plant Science. 13. 729097–729097. 8 indexed citations
5.
Kicherer, Anna, et al.. (2022). Behind the Leaves: Estimation of Occluded Grapevine Berries With Conditional Generative Adversarial Networks. Frontiers in Artificial Intelligence. 5. 830026–830026. 32 indexed citations
6.
Fischer, Benedikt, et al.. (2021). Phenoliner 2.0: RGB and near-infrared (NIR) image acquisition for an efficient phenotyping in grapevine research. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 57–67. 1 indexed citations
7.
Holtgräwe, Daniela, Katja Herzog, Florian Schwander, et al.. (2021). Transcriptomic analysis of temporal shifts in berry development between two grapevine cultivars of the Pinot family reveals potential genes controlling ripening time. BMC Plant Biology. 21(1). 327–327. 13 indexed citations
8.
Dini‐Andreote, Francisco, et al.. (2021). Interactive Effects of Scion and Rootstock Genotypes on the Root Microbiome of Grapevines (Vitis spp. L.). Applied Sciences. 11(4). 1615–1615. 25 indexed citations
9.
Kicherer, Anna, Andreas Backhaus, Udo Seiffert, et al.. (2020). Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards. Plant Methods. 16(1). 142–142. 31 indexed citations
10.
Backhaus, Andreas, Anna Kicherer, Michael Maixner, et al.. (2020). Detection of Two Different Grapevine Yellows in Vitis vinifera Using Hyperspectral Imaging. Remote Sensing. 12(24). 4151–4151. 28 indexed citations
11.
Herzog, Katja, et al.. (2019). An adaptable approach to automated visual detection of plant organs with applications in grapevine breeding. Biosystems Engineering. 183. 170–183. 36 indexed citations
12.
Kicherer, Anna, Katja Herzog, Andreas Backhaus, et al.. (2017). Phenoliner: A New Field Phenotyping Platform for Grapevine Research. Sensors. 17(7). 1625–1625. 36 indexed citations
13.
Herzog, Katja, Michael Fischer, Ralf T. Voegele, et al.. (2017). Effects of canopy architecture and microclimate on grapevine health in two training systems. Federal Research Centre for Cultivated Plants (Julius Kühn-Institut). 57(2). 53–60. 19 indexed citations
14.
Bhattarai, Surya P., et al.. (2017). Assessment of ‘hen and chicken’ disorder for marketable yield estimates of table grape using the ‘Berry Analysis Tool’. Acquire (CQUniversity). 57(1). 27–34. 2 indexed citations
15.
Kicherer, Anna, et al.. (2016). Towards Automated Large-Scale 3D Phenotyping of Vineyards under Field Conditions. Sensors. 16(12). 2136–2136. 59 indexed citations
16.
Kicherer, Anna, Maria Klodt, Sara Sharifzadeh, et al.. (2016). Automatic image-based determination of pruning mass as a determinant for yield potential in grapevine management and breeding. Australian Journal of Grape and Wine Research. 23(1). 120–124. 17 indexed citations
17.
Kicherer, Anna, Katja Herzog, Michael Pflanz, et al.. (2015). An Automated Field Phenotyping Pipeline for Application in Grapevine Research. Sensors. 15(3). 4823–4836. 49 indexed citations
18.
Kicherer, Anna, Ribana Roscher, Katja Herzog, et al.. (2015). BAT (Berry Analysis Tool): A high-throughput image interpretation tool to acquire the number, diameter, and volume of grapevine berries. Julius Kühn-Institut. 52(3). 129–135. 24 indexed citations
19.
Herzog, Katja, Anna Kicherer, & Reinhard Töpfer. (2015). OBJECTIVE PHENOTYPING THE TIME OF BUD BURST BY ANALYZING GRAPEVINE FIELD IMAGES. Acta Horticulturae. 379–385. 1 indexed citations
20.
Kicherer, Anna. (2015). High-throughput phenotyping of yield parameters for modern grapevine breeding. 7. 122. 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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