Benoı̂t Rousseau

910 total citations
22 papers, 611 citations indexed

About

Benoı̂t Rousseau is a scholar working on Food Science, Nutrition and Dietetics and Experimental and Cognitive Psychology. According to data from OpenAlex, Benoı̂t Rousseau has authored 22 papers receiving a total of 611 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Food Science, 16 papers in Nutrition and Dietetics and 9 papers in Experimental and Cognitive Psychology. Recurrent topics in Benoı̂t Rousseau's work include Sensory Analysis and Statistical Methods (22 papers), Biochemical Analysis and Sensing Techniques (16 papers) and Multisensory perception and integration (9 papers). Benoı̂t Rousseau is often cited by papers focused on Sensory Analysis and Statistical Methods (22 papers), Biochemical Analysis and Sensing Techniques (16 papers) and Multisensory perception and integration (9 papers). Benoı̂t Rousseau collaborates with scholars based in United States, France and Japan. Benoı̂t Rousseau's co-authors include Michael O’Mahony, Michael O’Mahony, Michel Rogeaux, Daniel M. Ennis, John M. Ennis, Rie Ishii, Yasushi Kyutoku and Ippeita Dan and has published in prestigious journals such as Food Quality and Preference, Journal of Sensory Studies and Perception & Psychophysics.

In The Last Decade

Benoı̂t Rousseau

22 papers receiving 571 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benoı̂t Rousseau United States 14 557 403 176 134 90 22 611
Danielle van Hout Netherlands 14 447 0.8× 256 0.6× 107 0.6× 147 1.1× 73 0.8× 29 548
KWANG‐OK KIM South Korea 15 537 1.0× 294 0.7× 87 0.5× 84 0.6× 124 1.4× 22 627
Jean A. McEwan United Kingdom 17 785 1.4× 386 1.0× 180 1.0× 135 1.0× 239 2.7× 34 975
Thierry Worch Netherlands 17 504 0.9× 189 0.5× 75 0.4× 92 0.7× 104 1.2× 30 636
Michel Visalli France 19 809 1.5× 462 1.1× 280 1.6× 319 2.4× 99 1.1× 60 1.0k
Maud Lelièvre‐Desmas France 11 650 1.2× 324 0.8× 133 0.8× 119 0.9× 126 1.4× 13 723
Michel Rogeaux France 10 441 0.8× 212 0.5× 133 0.8× 151 1.1× 53 0.6× 16 626
M. O'MAHONY United States 11 243 0.4× 241 0.6× 92 0.5× 146 1.1× 33 0.4× 14 408
Pieter Punter Netherlands 16 373 0.7× 209 0.5× 51 0.3× 139 1.0× 199 2.2× 21 629
Sylvie Cordelle France 12 723 1.3× 452 1.1× 190 1.1× 200 1.5× 176 2.0× 17 897

Countries citing papers authored by Benoı̂t Rousseau

Since Specialization
Citations

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

Fields of papers citing papers by Benoı̂t Rousseau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benoı̂t Rousseau

This figure shows the co-authorship network connecting the top 25 collaborators of Benoı̂t Rousseau. A scholar is included among the top collaborators of Benoı̂t Rousseau 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 Benoı̂t Rousseau. Benoı̂t Rousseau 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.
Ishii, Rie, et al.. (2019). Biases in paired preference tests: Cross‐cultural comparison of Japanese and American consumers. Journal of Sensory Studies. 34(3). 3 indexed citations
2.
Rousseau, Benoı̂t. (2019). Commentary on Meyners, Carr, and Hasted: “To replicate or not to replicate, or when did we start to ignore the concept of statistical power?”. Food Quality and Preference. 79. 103661–103661. 1 indexed citations
3.
Rousseau, Benoı̂t. (2015). Sensory discrimination testing and consumer relevance. Food Quality and Preference. 43. 122–125. 13 indexed citations
4.
Ennis, John M., Benoı̂t Rousseau, & Daniel M. Ennis. (2014). Sensory Difference Tests as Measurement Instruments: a Review of Recent Advances. Journal of Sensory Studies. 29(2). 89–102. 30 indexed citations
5.
Ennis, Daniel M. & Benoı̂t Rousseau. (2014). A Thurstonian model for the degree of difference protocol. Food Quality and Preference. 41. 159–162. 2 indexed citations
6.
Rousseau, Benoı̂t, et al.. (2013). Transitioning from proportion of discriminators to a more meaningful measure of sensory difference. Food Quality and Preference. 32. 77–82. 18 indexed citations
7.
Rousseau, Benoı̂t & John M. Ennis. (2013). Importance of Correct Instructions in the Tetrad Test. Journal of Sensory Studies. 28(4). 264–269. 12 indexed citations
8.
Rousseau, Benoı̂t, et al.. (2011). Internal preference mapping and the issue of satiety. Food Quality and Preference. 24(1). 67–74. 14 indexed citations
9.
Rousseau, Benoı̂t. (2007). SIMULTANEOUS ESTIMATIONS OF MULTIPLE PRODUCT SIMILARITIES USING A NEW DISCRIMINATION PROTOCOL. Journal of Sensory Studies. 22(5). 533–549. 3 indexed citations
10.
O’Mahony, Michael, et al.. (2005). Relating consumer and trained panels’ discriminative sensitivities using vanilla flavored ice cream as a medium. Food Quality and Preference. 18(1). 89–96. 41 indexed citations
11.
Rousseau, Benoı̂t, et al.. (2004). Are three-sample tasks less sensitive than two-sample tasks? Memory effects in the testing of taste discrimination. Perception & Psychophysics. 66(3). 464–474. 49 indexed citations
12.
Ennis, Daniel M. & Benoı̂t Rousseau. (2004). MOTIVATIONS FOR PRODUCT CONSUMPTION: APPLICATION OF A PROBABILISTIC MODEL TO ADOLESCENT SMOKING. Journal of Sensory Studies. 19(2). 107–117. 8 indexed citations
13.
Rogeaux, Michel, et al.. (2003). Corroborating the 2-AFC and 2-AC Thurstonian models using both a model system and sparkling water. Food Quality and Preference. 15(6). 501–507. 41 indexed citations
14.
Rousseau, Benoı̂t & Daniel M. Ennis. (2002). The multiple dual-pair method. Perception & Psychophysics. 64(6). 1008–1014. 11 indexed citations
15.
Rousseau, Benoı̂t, et al.. (2002). Investigating more powerful discrimination tests with consumers: effects of memory and response bias. Food Quality and Preference. 13(1). 39–45. 54 indexed citations
16.
Rousseau, Benoı̂t. (2001). THE β‐STRATEGY: AN ALTERNATIVE AND POWERFUL COGNITIVE STRATEGY WHEN PERFORMING SENSORY DISCRIMINATION TESTS. Journal of Sensory Studies. 16(3). 301–318. 27 indexed citations
17.
Rousseau, Benoı̂t & Michael O’Mahony. (2001). INVESTIGATION OF THE DUAL‐PAIR METHOD AS A POSSIBLE ALTERNATIVE TO THE TRIANGLE AND SAME‐DIFFERENT TESTS. Journal of Sensory Studies. 16(2). 161–178. 24 indexed citations
18.
Rousseau, Benoı̂t & Michael O’Mahony. (2000). Investigation of the effect of within-trial retasting and comparison of the dual-pair, same-different and triangle paradigms. Food Quality and Preference. 11(6). 457–464. 35 indexed citations
19.
Rousseau, Benoı̂t, Michel Rogeaux, & Michael O’Mahony. (1999). Mustard discrimination by same–different and triangle tests: aspects of irritation, memory and τ criteria. Food Quality and Preference. 10(3). 173–184. 59 indexed citations
20.
Rousseau, Benoı̂t & Michael O’Mahony. (1997). SENSORY DIFFERENCE TESTS: THURSTONIAN AND SSA PREDICTIONS FOR VANILLA FLAVORED YOGURTS. Journal of Sensory Studies. 12(2). 127–146. 62 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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