Morphological changes and color development during cookie baking—Kinetic, heat, and mass transfer considerations
Bibliographic record
Abstract
Color and shape are important quality attributes in baked goods, particularly cookies. Composition and processing conditions determine and influence color development and morphological changes in these baked goods. The objective of this study was to systematically evaluate the evolution of color and shape during baking to determine useful correlations that can be implemented during the assessment and modeling of the baking process. Cookies (AACC-I standard protocol 10-53.01) were baked at 185, 205, and 225°C. Moisture content, water activity, surface temperature, characteristic dimensions (radius and thickness), and color indexes (lightness, redness, blueness, and browning index [BI]) were monitored at different locations on the cookie surface and baking times. Relationships among the tested conditions were explored using correlation analysis. The cookies' dimensions and color indexes were strongly correlated with changes in moisture content over time, and those relationships were characterized using empirical models. The temperature dependence of the kinetic parameters of the changes in lightness and BI was also described and deemed independent of the location on the cookie surface. This study provides insights into the influence of heat and mass transfer on the physical and physicochemical changes of cookies during baking. The kinetic and secondary models developed in this study can serve as important components for establishing a comprehensive approach for coupling heat transfer, mass transfer, and reaction kinetics to estimate and optimize cookie-baking processes. PRACTICAL APPLICATION: The findings from this study provide valuable information for better understanding the morphological changes and color developments during the cookie-baking process. The quantitative data and models generated in this study will allow identifying baking conditions for better quality development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".