4.4 Article

TEMPERATURE- AND MOISTURE-BASED MODELING FOR PREDICTION OF STARCH GELATINIZATION AND CRUMB SOFTNESS DURING BREAD-BAKING PROCESS

Journal

JOURNAL OF TEXTURE STUDIES
Volume 45, Issue 6, Pages 462-476

Publisher

WILEY
DOI: 10.1111/jtxs.12097

Keywords

ALE; bread; moisture content; softness of bread; starch gelatinization; volume expansion

Funding

  1. Department of Science and Technology (DST), Government of India
  2. Council of Scientific and Industrial Research (CSIR), New Delhi

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Temperature, starch gelatinization, moisture content and softness of bread define the formation of crust and crumb regions during the baking process. A computational model was developed to study the volume expansion, temperature profile and moisture content of the bread during the baking process. An arbitrary Lagrangian-Eulerian method was applied to describe mesh movement during volume expansion. Model predictions were validated with experimental measurements of bread temperature, moisture content and volume expansion. Occurrence of two distinct zones having different moisture contents, i.e., crust (<10%) and crumb (approximate to 39%), was observed. Extent of starch gelatinization and browning of the bread surface was also studied using earlier published kinetic model. Moreover, softness development for the bread crumb was also modeled based on the degree of starch gelatinization. This study concluded that apart from heat and mass transfer, inclusion of volume expansion in the model predicts more accurate bread temperature, starch gelatinization and crumb softness. Practical ApplicationsCrumb softness and starch gelatinization of bread can be predicted based on temperature and moisture content of bread using computational modeling approach. A finite element model (FEM) is developed for the bread-baking process, accounting for heat and mass transfer along with the volume expansion of bread. FEM model is validated with the experimental measurements of temperature, moisture content and volume expansion during bread-baking process. This model helps in predicting the major quality attributes of the bread such as starch gelatinization, browning of the bread surface and crumb softness. Therefore, this model can be useful in predicting temperature, moisture along with other bread quality parameters. For the bakery industry, it will help to determine the baking time of bread with desired product quality based on oven temperature.

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