John C. Castura

2.2k total citations · 1 hit paper
48 papers, 1.7k citations indexed

About

John C. Castura is a scholar working on Food Science, Nutrition and Dietetics and Animal Science and Zoology. According to data from OpenAlex, John C. Castura has authored 48 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Food Science, 18 papers in Nutrition and Dietetics and 10 papers in Animal Science and Zoology. Recurrent topics in John C. Castura's work include Sensory Analysis and Statistical Methods (45 papers), Biochemical Analysis and Sensing Techniques (18 papers) and Meat and Animal Product Quality (9 papers). John C. Castura is often cited by papers focused on Sensory Analysis and Statistical Methods (45 papers), Biochemical Analysis and Sensing Techniques (18 papers) and Meat and Animal Product Quality (9 papers). John C. Castura collaborates with scholars based in Uruguay, Norway and Canada. John C. Castura's co-authors include Michael Meyners, Gastón Ares, B. Thomas Carr, Ana Giménez, Lucía Antúnez, Carolyn F. Ross, Letícia Vidal, Sara R. Jaeger, Florencia Alcaire and Tormod Næs and has published in prestigious journals such as Food Research International, Journal of Food Science and Food Quality and Preference.

In The Last Decade

John C. Castura

46 papers receiving 1.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Existing and new approaches for the analysis of CATA data

2013 347 citations Michael Meyners, John C. Castura et al. Food Quality and Preference profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John C. Castura Uruguay	22	1.5k	898	455	396	281	48	1.7k
Sok L. Chheang New Zealand	23	1.1k 0.7×	607 0.7×	425 0.9×	274 0.7×	118 0.4×	57	1.5k
Michael Meyners Germany	16	1.0k 0.7×	476 0.5×	242 0.5×	209 0.5×	214 0.8×	47	1.3k
Michael O’Mahony United States	28	1.6k 1.1×	1.1k 1.3×	615 1.4×	566 1.4×	246 0.9×	90	2.3k
Jeannine Delwiche United States	21	726 0.5×	778 0.9×	683 1.5×	287 0.7×	147 0.5×	43	1.6k
Denise C. Hunter New Zealand	24	820 0.6×	538 0.6×	315 0.7×	169 0.4×	98 0.3×	44	1.5k
Michel Visalli France	19	809 0.5×	462 0.5×	319 0.7×	280 0.7×	99 0.4×	60	1.0k
Michelle K. Beresford New Zealand	18	746 0.5×	459 0.5×	319 0.7×	150 0.4×	108 0.4×	22	1.1k
Bénédicte Pineau New Zealand	17	1.2k 0.8×	473 0.5×	354 0.8×	141 0.4×	127 0.5×	25	1.5k
Amy G. Paisley New Zealand	12	682 0.5×	429 0.5×	282 0.6×	116 0.3×	112 0.4×	14	931
Sylvie Cordelle France	12	723 0.5×	452 0.5×	200 0.4×	190 0.5×	176 0.6×	17	897

Countries citing papers authored by John C. Castura

Since Specialization

Citations

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

Fields of papers citing papers by John C. Castura

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John C. Castura. 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 John C. Castura. The network helps show where John C. Castura may publish in the future.

Co-authorship network of co-authors of John C. Castura

This figure shows the co-authorship network connecting the top 25 collaborators of John C. Castura. A scholar is included among the top collaborators of John C. Castura 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 John C. Castura. John C. Castura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Castura, John C., et al.. (2025). Comparison of Gins Using Temporal Dominance of Sensations (TDS), Temporal Check‐All‐That‐Apply (TCATA), and Temporal Ranking (TR). Journal of Sensory Studies. 40(2). 1 indexed citations

Castura, John C., et al.. (2024). Sugar Replacement in Chocolate-Flavored Milk: Differences in Consumer Segments’ Liking of Sweetener Systems Relate to Temporal Perception. Beverages. 10(3). 54–54. 1 indexed citations

Castura, John C., Terhi Pohjanheimo, Oskar Laaksonen, et al.. (2023). Screening respondents to increase data quality in consumer tests. Food Quality and Preference. 112. 105030–105030. 4 indexed citations

Castura, John C., Paula Varela, & Tormod Næs. (2023). Investigating paired comparisons after principal component analysis. Food Quality and Preference. 106. 104814–104814. 9 indexed citations

Castura, John C., Paula Varela, & Tormod Næs. (2023). Investigating only a subset of paired comparisons after principal component analysis. Food Quality and Preference. 110. 104941–104941.

Castura, John C., Michael Meyners, Terhi Pohjanheimo, Paula Varela, & Tormod Næs. (2023). An approach for clustering consumers by their top‐box and top‐choice responses. Journal of Sensory Studies. 38(5). 2 indexed citations

Castura, John C., et al.. (2023). Identifying temporal sensory drivers of liking of biscuit supplemented with brewer’s spent grain for young consumers. Food Research International. 170. 113049–113049. 6 indexed citations

Castura, John C., et al.. (2022). Temporal ranking for characterization and improved discrimination of protein beverages. Journal of Sensory Studies. 37(4). 5 indexed citations

Mielby, Line Ahm, Yan Zeng, Yuanxia Sun, et al.. (2022). Investigating the temporality of binary taste interactions in blends of sweeteners and citric acid in solution. Journal of Sensory Studies. 37(6). 8 indexed citations

10.

Castura, John C., Douglas N. Rutledge, Carolyn F. Ross, & Tormod Næs. (2021). Discriminability and uncertainty in principal component analysis (PCA) of temporal check-all-that-apply (TCATA) data. Food Quality and Preference. 96. 104370–104370. 21 indexed citations

11.

Castura, John C.. (2020). Temporal Sensory Data Analysis [R package tempR version 0.9.9.16]. 2 indexed citations

12.

Castura, John C., et al.. (2018). How task instructions affect performance on the unspecified tetrad test. Journal of Sensory Studies. 33(3). 1 indexed citations

13.

Mitchell, Jessica, et al.. (2018). Application of TCATA to examine variation in beer perception due to thermal taste status. Food Quality and Preference. 73. 135–142. 21 indexed citations

14.

Castura, John C., et al.. (2017). Characterizing dynamic sensory properties of nutritive and nonnutritive sweeteners with temporal check‐all‐that‐apply. Journal of Sensory Studies. 32(3). 48 indexed citations

15.

Franczak, Brian C., John C. Castura, Ryan P. Browne, Christopher J. Findlay, & Paul D. McNicholas. (2016). Handling missing data in consumer hedonic tests arising from direct scaling. Journal of Sensory Studies. 31(6). 514–523. 3 indexed citations

16.

Ares, Gastón, Florencia Alcaire, Lucía Antúnez, et al.. (2016). Identification of drivers of (dis)liking based on dynamic sensory profiles: Comparison of Temporal Dominance of Sensations and Temporal Check-all-that-apply. Food Research International. 92. 79–87. 53 indexed citations

17.

Parente, Maria E., et al.. (2015). Dynamic sensory characterization of cosmetic creams during application using Temporal Check-All-That-Apply (TCATA) questions. Food Quality and Preference. 45. 33–40. 45 indexed citations

18.

Meyners, Michael, John C. Castura, & Thierry Worch. (2015). Statistical evaluation of panel repeatability in Check-All-That-Apply questions. Food Quality and Preference. 49. 197–204. 14 indexed citations

19.

Findlay, C.J., John C. Castura, & Isabelle Lesschaeve. (2006). Feedback calibration: A training method for descriptive panels. Food Quality and Preference. 18(2). 321–328. 25 indexed citations

20.

Castura, John C., C.J. Findlay, & Isabelle Lesschaeve. (2005). Monitoring calibration of descriptive sensory panels using distance from target measurements. Food Quality and Preference. 17(3-4). 282–289. 4 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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