Marco P. Morgenstern

2.3k total citations
54 papers, 1.7k citations indexed

About

Marco P. Morgenstern is a scholar working on Food Science, Nutrition and Dietetics and Complementary and Manual Therapy. According to data from OpenAlex, Marco P. Morgenstern has authored 54 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Food Science, 24 papers in Nutrition and Dietetics and 14 papers in Complementary and Manual Therapy. Recurrent topics in Marco P. Morgenstern's work include Sensory Analysis and Statistical Methods (22 papers), Temporomandibular Joint Disorders (14 papers) and Food composition and properties (13 papers). Marco P. Morgenstern is often cited by papers focused on Sensory Analysis and Statistical Methods (22 papers), Temporomandibular Joint Disorders (14 papers) and Food composition and properties (13 papers). Marco P. Morgenstern collaborates with scholars based in New Zealand, United States and Malaysia. Marco P. Morgenstern's co-authors include B.J. Dobraszczyk, John E. Bronlund, Kylie D. Foster, Duncan Hedderley, Arran Wilson, Scott C. Hutchings, Lidia Motoi, Bryony James, John Grigor and Jim R. Jones and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Food Research International and Journal of Food Engineering.

In The Last Decade

Marco P. Morgenstern

50 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marco P. Morgenstern New Zealand 23 1.1k 1.0k 202 166 165 54 1.7k
Maud Panouillé France 23 1.0k 0.9× 569 0.6× 158 0.8× 84 0.5× 208 1.3× 30 1.4k
John E. Bronlund New Zealand 31 1.3k 1.2× 624 0.6× 210 1.0× 89 0.5× 149 0.9× 133 2.8k
Christopher R. Daubert United States 36 2.5k 2.2× 790 0.8× 254 1.3× 87 0.5× 531 3.2× 86 3.3k
Jon F. Prinz Netherlands 18 885 0.8× 614 0.6× 51 0.3× 138 0.8× 239 1.4× 24 1.5k
Fumiyo Hayakawa Japan 19 441 0.4× 287 0.3× 150 0.7× 87 0.5× 119 0.7× 69 1.0k
Christoph Hartmann Germany 24 634 0.6× 313 0.3× 54 0.3× 127 0.8× 176 1.1× 64 1.5k
Isabelle Déléris France 20 686 0.6× 497 0.5× 51 0.3× 102 0.6× 221 1.3× 36 964
Sayaka Ishihara Japan 26 1.1k 1.0× 541 0.5× 504 2.5× 54 0.3× 65 0.4× 88 2.2k
Lisa M. Duizer Canada 32 1.3k 1.1× 1.1k 1.1× 303 1.5× 165 1.0× 347 2.1× 100 2.9k
Makoto Nakauma Japan 27 1.6k 1.4× 530 0.5× 766 3.8× 57 0.3× 83 0.5× 68 2.4k

Countries citing papers authored by Marco P. Morgenstern

Since Specialization
Citations

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

Fields of papers citing papers by Marco P. Morgenstern

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marco P. Morgenstern. 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 Marco P. Morgenstern. The network helps show where Marco P. Morgenstern may publish in the future.

Co-authorship network of co-authors of Marco P. Morgenstern

This figure shows the co-authorship network connecting the top 25 collaborators of Marco P. Morgenstern. A scholar is included among the top collaborators of Marco P. Morgenstern 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 Marco P. Morgenstern. Marco P. Morgenstern 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.
Leong, Sze Ying, Esther H.‐J. Kim, Marco P. Morgenstern, et al.. (2024). Texture Evaluation and In Vivo Oral Tactile Perceptions of Cooked Wheat Pasta Sheets Partially Substituted with Pea Protein. Foods. 13(23). 3798–3798.
2.
3.
Jones, Jim R., Marco P. Morgenstern, John E. Bronlund, et al.. (2023). Modelling mastication and aroma release from white rice during food oral processing. Journal of Food Engineering. 357. 111636–111636. 4 indexed citations
4.
5.
Kim, Esther H.‐J., Arran Wilson, Lidia Motoi, et al.. (2022). Chewing differences in consumers affect the digestion and colonic fermentation outcomes: in vitro studies. Food & Function. 13(18). 9355–9371. 7 indexed citations
6.
Agarwal, Deepa, et al.. (2022). Microstructure, rheological and water mobility behaviour of plant-based protein isolates (pea and quinoa) and locust bean gum mixtures. Food Research International. 164. 112311–112311. 19 indexed citations
7.
Jones, Jim R., Marco P. Morgenstern, John E. Bronlund, et al.. (2021). Modelling the role of oral processing on in vivo aroma release of white rice: Conceptual model and experimental validation. LWT. 141. 110918–110918. 26 indexed citations
8.
Herath, Thanuja D., Gunaranjan Paturi, Christine A. Butts, Catherine E. Sansom, & Marco P. Morgenstern. (2020). In vitro and in vivo effects of carrot on human blood platelet aggregation. International Journal of Food Science & Technology. 56(4). 1829–1836.
9.
Kim, Esther H.‐J., et al.. (2020). Subthreshold chemesthetic stimulation can enhance flavor lastingness of a soft chewable candy. Food Research International. 140. 109883–109883. 3 indexed citations
10.
Kim, Esther H.‐J., et al.. (2019). Dynamic flavor perception of encapsulated flavors in a soft chewable matrix. Food Research International. 123. 241–250. 15 indexed citations
11.
Foster, Kylie D., et al.. (2016). Exploring the Links Between Texture Perception and Bolus Properties Throughout Oral Processing. Part 2: Bolus Mechanical and Rheological Properties. Journal of Texture Studies. 47(6). 474–483. 10 indexed citations
12.
Selway, Nichola, et al.. (2016). Lubrication of chocolate during oral processing. Food & Function. 8(2). 533–544. 26 indexed citations
13.
Foster, Kylie D., et al.. (2016). Exploring the Links Between Texture Perception and Bolus Properties Throughout oral Processing. Part 1: Breakdown Paths. Journal of Texture Studies. 47(6). 461–473. 21 indexed citations
14.
Kim, Esther H.‐J., et al.. (2015). Oral Processing of Mixtures of Food Particles. Journal of Texture Studies. 46(6). 487–498. 22 indexed citations
15.
Larsen, Danaè S., et al.. (2015). Textural Complexity is a Food Property – Shown Using Model Foods. International Journal of Food Properties. 19(7). 1544–1555. 16 indexed citations
16.
Foster, Kylie D., Marco P. Morgenstern, John Grigor, et al.. (2014). The Application of Temporal Dominance of Sensations (TDS) for Oral Processing Studies: An Initial Investigation. Journal of Texture Studies. 45(6). 409–419. 28 indexed citations
17.
Foster, Kylie D., et al.. (2011). The Role of Oral Processing in Dynamic Sensory Perception. Journal of Food Science. 76(2). 139 indexed citations
18.
Corrigan, Virginia K., et al.. (2011). FUNDAMENTAL FRACTURE PROPERTIES ASSOCIATED WITH SENSORY HARDNESS OF BRITTLE SOLID FOODS. Journal of Texture Studies. 43(1). 49–62. 74 indexed citations
19.
Foster, Kylie D., et al.. (2010). Identification of multiple compartments present during the mastication of solid food. Archives of Oral Biology. 56(4). 345–352. 20 indexed citations
20.
Morgenstern, Marco P., Haotian Zheng, M. Ross, & Osvaldo H. Campanella. (1999). Rheological properties of sheeted wheat flour dough measured with large deformations. International Journal of Food Properties. 2(3). 265–275. 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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