Texture Prediction Models
Texture Prediction Models is a computational framework that belongs to the class of predictive modeling techniques in food science, specifically designed to quantitatively estimate the mechanical and sensory attributes of meat texture using physicochemical and instrumental input variables.
264
Publications
14.3K
Citations
967
Authors
363
Institutions
Publications per year
2017–2026
90
Parents
264
Correlation Between Cooked Rice Texture and Rapid Visco Analyser Measurements
Elaine T. Champagne, Karen L. Bett, Bryan T. Vinyard et al. · Cereal Chemistry · 1999 · 239 citations
1–5 of 264
967
University of Arkansas at Fayetteville, United States
8 publications · 291 citations
8
h-index
8
h-index
8
h-index
6
h-index
Teagasc - The Irish Agriculture and Food Development Authority, Ireland
6 publications · 391 citations
6
h-index
1–5 of 967
363

University of Arkansas at Fayetteville
Fayetteville, United States
11 h-index
27 publications
1.1K citations
University College Dublin
Dublin, Ireland
9 h-index
22 publications
1.3K citations

Universidad de Extremadura
Badajoz, Spain
8 h-index
37 publications
998 citations
KU Leuven
Leuven, Belgium
7 h-index
21 publications
2.1K citations

Royal Agricultural University
Cirencester, United Kingdom
6 h-index
14 publications
1K citations

National University of Ireland
Dublin, Ireland
6 h-index
13 publications
717 citations
Teagasc - The Irish Agriculture and Food Development Authority
Carlow, Ireland
6 h-index
14 publications
772 citations

Centre National de la Recherche Scientifique
Paris, France
6 h-index
11 publications
786 citations
1–8 of 363
25 publications · 1.4K citations
20
h-index
22 publications · 1.4K citations
19
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JFS · 15 publications · 661 citations
13
h-index
14 publications · 458 citations
12
h-index
7 publications · 480 citations
7
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1–5