Related Experiment Videos
COLLECTION AND CLASSIFICATION OF WORDS FOR DESCRIPTION OF FOOD TEXTURE: III: Classification by Multivariate Analysis.
S Yoshikawa1, S Nishimaru1, T Tashiro1
1Food Research Institute, Ministry of Agriculture, JapanInspection Office for Exporting Goods, Ministry of Agriculture, JapanChuo University, Tokyo, Japan.
Journal of Texture Studies
|April 4, 2017
Summary
This study identified key texture dimensions in 79 foods using multivariate analysis. The primary factors influencing food texture perception were hardness, temperature, moisture, and structural properties.
Area of Science:
- Food science
- Sensory analysis
- Multivariate statistics
Background:
- Understanding food texture is crucial for product development and consumer acceptance.
- Objective measurement of food texture relies on correlating instrumental and sensory data.
Purpose of the Study:
- To identify and quantify the fundamental dimensions of food texture.
- To establish a framework for texture profiling across a diverse range of food products.
Main Methods:
- Computed a correlation matrix from texture profile analysis (TPA) rating scores for 79 food items.
- Applied multivariate statistical techniques to identify orthogonal factors within the texture data.
Main Results:
- Eight significant orthogonal factors were extracted from the food texture data.
- The most influential dimensions identified were: hardness-softness, temperature (cold-warm), moisture (oily-juicy), and structural properties (elastic-flaky).
- Additional key factors included heaviness, viscosity, and smoothness.
Conclusions:
- Multivariate analysis effectively reduces complex texture profiles into a manageable set of key sensory dimensions.
- These identified factors provide a robust basis for describing and differentiating food textures.
- The findings can guide food product design and sensory evaluation protocols.