chewR : An Open‐Source R Package for Quantifying Masticatory Performance With Applications in Oral Processing Research

Masticatory performance is a measure of oral physiology that affects food breakdown and eating behavior. Existing methods to quantify masticatory performance rely on labor-intensive procedures (e.g., sieving expectorated samples), or proprietary software (e.g., ViewGum), limiting adoption and reproducibility. In this cross-sectional methods validation study, we: (1) examine the convergent validity of chewR, a user-friendly R package that quantifies masticatory performance in a 2-color gum mixing task via automated image analysis, and (2) examine how chewR based masticatory performance measures relate to other oral processing behaviors. Adults (n = 47, 601% female) completed a laboratory visit with a 2-colored gum mixing task, stimulated salivary flow, and eating rate objectively measured using Tang's carrot test. Chewed gum samples were flattened with a standardized method, scanned, and resulting images were analyzed using ViewGum and chewR. ViewGum generates a score based on the gum color mixing, with lower scores indicating greater masticatory performance. chewR produces a raw score based on gum color mixing; from this, a transformed chewR Masticatory Performance Score was calculated, with higher values indicating greater masticatory performance. chewR measures showed strong convergent validity with ViewGum Score: the raw chewR score and transformed chewR Masticatory Performance Score were each strongly correlated with ViewGum Score (r's = ±0.81, p < 0.00001), with signs in expected directions. Regarding predictive validity, the transformed chewR Masticatory Performance Score was weakly associated with carrot eating rate (r = 0.12), self-reported eating rate (r = 0.20), and stimulated salivary flow (r = 0.21); the same associations were similarly weak for ViewGum Score. These findings support chewR as an open-source alternative to ViewGum to quantify masticatory performance in a gum mixing task.

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Publication Details

Journal
Journal of Texture Studies
Published
2026-09-01
DOI
https://doi.org/10.1111/jtxs.70112
Primary Topic
Temporomandibular Joint Disorders
Type
article
Field-Weighted Citation Impact
0.00

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article

chewR : An Open‐Source R Package for Quantifying Masticatory Performance With Applications in Oral Processing Research

John W. Long, John E. Hayes, Elsbeth Akanzinge
Journal of Texture Studies
Temporomandibular Joint Disorders
article

chewR : An Open‐Source R Package for Quantifying Masticatory Performance With Applications in Oral Processing Research

John W. Long, John E. Hayes, Elsbeth Akanzinge
article en

Abstract

Masticatory performance is a measure of oral physiology that affects food breakdown and eating behavior. Existing methods to quantify masticatory performance rely on labor-intensive procedures (e.g., sieving expectorated samples), or proprietary software (e.g., ViewGum), limiting adoption and reproducibility. In this cross-sectional methods validation study, we: (1) examine the convergent validity of chewR, a user-friendly R package that quantifies masticatory performance in a 2-color gum mixing task via automated image analysis, and (2) examine how chewR based masticatory performance measures relate to other oral processing behaviors. Adults (n = 47, 601% female) completed a laboratory visit with a 2-colored gum mixing task, stimulated salivary flow, and eating rate objectively measured using Tang's carrot test. Chewed gum samples were flattened with a standardized method, scanned, and resulting images were analyzed using ViewGum and chewR. ViewGum generates a score based on the gum color mixing, with lower scores indicating greater masticatory performance. chewR produces a raw score based on gum color mixing; from this, a transformed chewR Masticatory Performance Score was calculated, with higher values indicating greater masticatory performance. chewR measures showed strong convergent validity with ViewGum Score: the raw chewR score and transformed chewR Masticatory Performance Score were each strongly correlated with ViewGum Score (r's = ±0.81, p < 0.00001), with signs in expected directions. Regarding predictive validity, the transformed chewR Masticatory Performance Score was weakly associated with carrot eating rate (r = 0.12), self-reported eating rate (r = 0.20), and stimulated salivary flow (r = 0.21); the same associations were similarly weak for ViewGum Score. These findings support chewR as an open-source alternative to ViewGum to quantify masticatory performance in a gum mixing task.

Journal of Texture StudiesVol. 57(5)
Pennsylvania State University (US)
U.S. Department of Agriculture, Pennsylvania State University, National Institute of Food and Agriculture
Zero hunger
Openalex Percentile: Top 8%
Temporomandibular Joint Disorders
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