Simone Rochfort

7.0k total citations
179 papers, 5.0k citations indexed

About

Simone Rochfort is a scholar working on Molecular Biology, Plant Science and Nutrition and Dietetics. According to data from OpenAlex, Simone Rochfort has authored 179 papers receiving a total of 5.0k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Molecular Biology, 55 papers in Plant Science and 31 papers in Nutrition and Dietetics. Recurrent topics in Simone Rochfort's work include Metabolomics and Mass Spectrometry Studies (22 papers), Plant and fungal interactions (19 papers) and Fatty Acid Research and Health (17 papers). Simone Rochfort is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (22 papers), Plant and fungal interactions (19 papers) and Fatty Acid Research and Health (17 papers). Simone Rochfort collaborates with scholars based in Australia, United States and New Zealand. Simone Rochfort's co-authors include Zhiqian Liu, Joe Panozzo, Germán Spangenberg, Vilnis Ezernieks, Mark O. Downey, Aaron Elkins, Ben Cocks, Frank R. Dunshea, A. J. Parker and V. Craige Trenerry and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Environmental Science & Technology.

In The Last Decade

Simone Rochfort

168 papers receiving 4.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simone Rochfort Australia 39 2.0k 1.3k 754 689 503 179 5.0k
Zohar Kerem Israel 37 1.5k 0.7× 2.9k 2.2× 791 1.0× 638 0.9× 203 0.4× 113 5.8k
Yvan Larondelle Belgium 51 2.6k 1.3× 3.1k 2.4× 1.7k 2.3× 1.3k 1.9× 315 0.6× 213 9.0k
Sjef Boeren Netherlands 53 5.9k 3.0× 3.1k 2.4× 1.3k 1.7× 1.2k 1.8× 290 0.6× 197 10.3k
Johanna Fink‐Gremmels Netherlands 49 1.8k 0.9× 3.3k 2.5× 1.2k 1.6× 597 0.9× 755 1.5× 203 8.0k
Michael Rychlik Germany 47 1.6k 0.8× 3.4k 2.6× 2.1k 2.8× 856 1.2× 133 0.3× 258 7.0k
Mitsuru Yoshida Japan 39 1.4k 0.7× 2.1k 1.6× 935 1.2× 520 0.8× 208 0.4× 161 5.1k
Mark A. Berhow United States 41 2.5k 1.3× 2.0k 1.6× 1.2k 1.5× 707 1.0× 133 0.3× 191 5.7k
Anna Stochmal Poland 38 2.1k 1.1× 2.2k 1.7× 1.1k 1.5× 422 0.6× 403 0.8× 237 5.6k
Mayumi Ohnishi‐Kameyama Japan 38 2.0k 1.0× 1.6k 1.2× 777 1.0× 378 0.5× 87 0.2× 129 5.1k
Corey D. Broeckling United States 39 2.4k 1.2× 2.2k 1.7× 492 0.7× 231 0.3× 221 0.4× 133 5.4k

Countries citing papers authored by Simone Rochfort

Since Specialization
Citations

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

Fields of papers citing papers by Simone Rochfort

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simone Rochfort

This figure shows the co-authorship network connecting the top 25 collaborators of Simone Rochfort. A scholar is included among the top collaborators of Simone Rochfort 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 Simone Rochfort. Simone Rochfort 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.
Sheedy, David B., H.M. Golder, Simone Rochfort, et al.. (2026). A large, multisite investigation into the lipidomics of survival in dairy cows. Journal of Dairy Science. 109(3). 2969–2988.
2.
Sheedy, David B., H.M. Golder, S.C. García, et al.. (2025). Associations among body condition score, body weight, and serum biochemistry in dairy cows. Journal of Dairy Science. 108(4). 4131–4148.
3.
Xiang, Ruidong, Edmond J. Breen, Sunduimijid Bolormaa, et al.. (2025). Integrating extensive functional annotations and multiomics of cattle enhances climate resilience prediction and mapping. Proceedings of the National Academy of Sciences. 122(49). e2514736122–e2514736122.
4.
5.
Quigley, Anita, et al.. (2024). Cannabinoids and Genetic Epilepsy Models: A Review with Focus on CDKL5 Deficiency Disorder. International Journal of Molecular Sciences. 25(19). 10768–10768. 3 indexed citations
6.
Plozza, Tim, Priyanka Reddy, Alessio Scalisi, et al.. (2024). Relationships of early season leaf metabolites to apple crop load and fruit quality at harvest. Acta Horticulturae. 337–342.
7.
Vassiliadis, Simone, et al.. (2023). Developing Prediction Models Using Near-Infrared Spectroscopy to Quantify Cannabinoid Content in Cannabis Sativa. Sensors. 23(5). 2607–2607. 12 indexed citations
8.
Vincent, Delphine, Vilnis Ezernieks, Saleh Shahinfar, et al.. (2022). A community resource to mass explore the wheat grain proteome and its application to the late-maturity alpha-amylase (LMA) problem. GigaScience. 12. 3 indexed citations
9.
Vincent, Delphine, Vilnis Ezernieks, Frank Bedon, et al.. (2022). Mining the Wheat Grain Proteome. International Journal of Molecular Sciences. 23(2). 713–713. 8 indexed citations
10.
Liu, Zhiqian, et al.. (2022). A Simplified Alkane Analysis Method for the Determination of Herbage Intake by Dairy Cows. Agronomy. 12(11). 2720–2720. 2 indexed citations
11.
12.
Vincent, Delphine, Keith W. Savin, Simone Rochfort, & Germán Spangenberg. (2020). The Power of Three in Cannabis Shotgun Proteomics: Proteases, Databases and Search Engines. Proteomes. 8(2). 13–13. 5 indexed citations
13.
Liu, Zhiqian, Vilnis Ezernieks, Priyanka Reddy, et al.. (2020). A Simple GC-MS/MS Method for Determination of Smoke Taint-Related Volatile Phenols in Grapes. Metabolites. 10(7). 294–294. 18 indexed citations
14.
Rochfort, Simone, et al.. (2020). A High-Throughput Method for the Comprehensive Analysis of Terpenes and Terpenoids in Medicinal Cannabis Biomass. Metabolites. 10(7). 276–276. 15 indexed citations
15.
Xiang, Ruidong, Irene van den Berg, Iona M. MacLeod, et al.. (2019). Quantifying the contribution of sequence variants with regulatory and evolutionary significance to 34 bovine complex traits. Proceedings of the National Academy of Sciences. 116(39). 19398–19408. 102 indexed citations
16.
Vincent, Delphine, Simone Rochfort, & Germán Spangenberg. (2019). Optimisation of Protein Extraction from Medicinal Cannabis Mature Buds for Bottom-Up Proteomics. Molecules. 24(4). 659–659. 15 indexed citations
17.
Rochfort, Simone, et al.. (2019). NMR Based Metabolomic Analysis of Health Promoting Phytochemicals in Lentils. Metabolites. 9(8). 168–168. 9 indexed citations
18.
Groef, Bert De, et al.. (2018). Bone marrow fat analysis as a diagnostic tool to document ante-mortem starvation. The Veterinary Journal. 243. 1–7. 4 indexed citations
19.
Vo, Quan V., et al.. (2017). Synthesis of aromatic and indole alpha-glucosinolates. Carbohydrate Research. 455. 45–53. 14 indexed citations
20.
Liu, Zhiqian & Simone Rochfort. (2014). Recent progress in polar metabolite quantification in plants using liquid chromatography–mass spectrometry. Journal of Integrative Plant Biology. 56(9). 816–825. 16 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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