Michel Visalli

1.5k total citations
60 papers, 1.0k citations indexed

About

Michel Visalli is a scholar working on Food Science, Sensory Systems and Nutrition and Dietetics. According to data from OpenAlex, Michel Visalli has authored 60 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Food Science, 22 papers in Sensory Systems and 22 papers in Nutrition and Dietetics. Recurrent topics in Michel Visalli's work include Sensory Analysis and Statistical Methods (55 papers), Biochemical Analysis and Sensing Techniques (22 papers) and Olfactory and Sensory Function Studies (22 papers). Michel Visalli is often cited by papers focused on Sensory Analysis and Statistical Methods (55 papers), Biochemical Analysis and Sensing Techniques (22 papers) and Olfactory and Sensory Function Studies (22 papers). Michel Visalli collaborates with scholars based in France, Argentina and Morocco. Michel Visalli's co-authors include Pascal Schlich, Mara V. Galmarini, Benjamin Mahieu, Chad Peltier, Gerry Jager, Markus Stieger, Carsten Lange, Hervé Cardot, Cees de Graaf and Christine Langé and has published in prestigious journals such as PLoS ONE, Journal of Food Science and Comprehensive Reviews in Food Science and Food Safety.

In The Last Decade

Michel Visalli

58 papers receiving 998 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michel Visalli France 19 809 462 319 280 154 60 1.0k
Michael Meyners Germany 16 1.0k 1.3× 476 1.0× 242 0.8× 209 0.7× 126 0.8× 47 1.3k
Egon Peter Köster Netherlands 9 548 0.7× 301 0.7× 365 1.1× 227 0.8× 148 1.0× 12 813
Line Ahm Mielby Denmark 17 435 0.5× 302 0.7× 208 0.7× 153 0.5× 107 0.7× 29 725
David Jin New Zealand 22 805 1.0× 487 1.1× 299 0.9× 209 0.7× 117 0.8× 48 1.3k
Sylvie Cordelle France 12 723 0.9× 452 1.0× 200 0.6× 190 0.7× 66 0.4× 17 897
Sok L. Chheang New Zealand 23 1.1k 1.3× 607 1.3× 425 1.3× 274 1.0× 177 1.1× 57 1.5k
Christina M. Roigard New Zealand 17 753 0.9× 335 0.7× 177 0.6× 207 0.7× 116 0.8× 29 986
Amy G. Paisley New Zealand 12 682 0.8× 429 0.9× 282 0.9× 116 0.4× 71 0.5× 14 931
Kwang-Ok Kim South Korea 19 702 0.9× 408 0.9× 198 0.6× 132 0.5× 90 0.6× 118 1.2k
Denise C. Hunter New Zealand 24 820 1.0× 538 1.2× 315 1.0× 169 0.6× 94 0.6× 44 1.5k

Countries citing papers authored by Michel Visalli

Since Specialization
Citations

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

Fields of papers citing papers by Michel Visalli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michel Visalli

This figure shows the co-authorship network connecting the top 25 collaborators of Michel Visalli. A scholar is included among the top collaborators of Michel Visalli 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 Michel Visalli. Michel Visalli 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.
2.
Galmarini, Mara V. & Michel Visalli. (2024). Sensory research and Temporal Descriptive Methods: Where is this relationship going?. Science Talks. 11. 100375–100375. 1 indexed citations
3.
Visalli, Michel, et al.. (2024). Temporal precision and resolution of TDS and TCATA used with consumers. Food Quality and Preference. 117. 105172–105172. 5 indexed citations
4.
Visalli, Michel & Mara V. Galmarini. (2024). Multi‐attribute temporal descriptive methods in sensory analysis applied in food science: A systematic scoping review. Comprehensive Reviews in Food Science and Food Safety. 23(1). e13294–e13294. 9 indexed citations
5.
Visalli, Michel, Sylvie Cordelle, Noëlle Béno, & Pascal Schlich. (2024). Product discrimination ability of temporal sensory evaluation methods used with consumers. Food Quality and Preference. 115. 105123–105123. 5 indexed citations
6.
Visalli, Michel, et al.. (2023). Indexes of individual repeatability and product discrimination in TDS and TCATA and their statistical inference. Food Quality and Preference. 110. 104929–104929. 5 indexed citations
7.
Visalli, Michel, Mara V. Galmarini, & Pascal Schlich. (2023). Use of temporal sensory evaluation methods with consumers: a position paper. Current Opinion in Food Science. 54. 101102–101102. 7 indexed citations
8.
Visalli, Michel, et al.. (2023). Analyzing temporal dominance of sensations data with categorical functional data analysis. Food Quality and Preference. 109. 104893–104893. 7 indexed citations
9.
Visalli, Michel, et al.. (2023). Assessment of the validity and reliability of temporal sensory evaluation methods used with consumers on controlled stimuli delivered by a gustometer. Food Quality and Preference. 110. 104942–104942. 9 indexed citations
10.
Buche, Patrice, et al.. (2023). PO2/TransformON, an ontology for data integration on food, feed, bioproducts and biowaste engineering. npj Science of Food. 7(1). 47–47. 7 indexed citations
11.
Visalli, Michel, et al.. (2023). Hedonic valence of descriptive sensory terms as an indirect measure of liking: A preliminary study with red wines. Food Quality and Preference. 108. 104861–104861. 7 indexed citations
12.
Visalli, Michel, Benjamin Mahieu, & Pascal Schlich. (2023). A dataset on concurrent and immediate retrospective measures of sensory perception and preferences of dark chocolates. Data in Brief. 49. 109314–109314. 1 indexed citations
13.
Visalli, Michel, Hélène Labouré, Isabelle Andriot, et al.. (2022). Automatic pretreatment and multiblock analysis of flavor release and sensory temporal data simultaneously collected in vivo. Journal of Chemometrics. 38(5). 6 indexed citations
14.
15.
Visalli, Michel, et al.. (2022). A dataset of sensory perception of chocolates, guacamoles, ice teas and crisps collected with consumers using six temporal methods. Data in Brief. 45. 108708–108708. 3 indexed citations
16.
Wijk, René A. de, Daisuke Kaneko, Garmt Dijksterhuis, et al.. (2022). A preliminary investigation on the effect of immersive consumption contexts on food-evoked emotions using facial expressions and subjective ratings. Food Quality and Preference. 99. 104572–104572. 10 indexed citations
17.
18.
Salles, Christian, et al.. (2022). Construction of a Generic and Evolutive Wheel and Lexicon of Food Textures. Foods. 11(19). 3097–3097. 6 indexed citations
19.
Visalli, Michel & Mara V. Galmarini. (2022). Multi-attribute temporal descriptive methods in sensory analysis applied in food science: Protocol for a scoping review. PLoS ONE. 17(7). e0270969–e0270969. 11 indexed citations
20.
Peltier, Chad, et al.. (2018). Using temporal dominance of emotions at home. Impact of coffee advertisements on consumers’ behavior and methodological perspectives. Food Quality and Preference. 71. 311–319. 13 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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