Discrimination of Volatiles of Refined and Whole Wheat Bread Containing Red and White Wheat Bran Using an Electronic Nose
Bibliographic record
Abstract
UNLABELLED: The principal objective of this study was to evaluate the capability of electronic (E) nose technology to discriminate refined and whole wheat bread made with white or red wheat bran according to their headspace volatiles. Whole wheat flour was formulated with a common refined flour from hard red spring wheat, blended at the 15% replacement level with bran milled from representative samples of one hard red and 2 hard white wheats. A commercial formula was used for breadmaking. Results varied according to the nature of the sample, that is, crust, crumb, or whole slices. Bread crust and crumb were completely discriminated. Crumb of whole wheat bread made with red bran was distinct from other bread types. When misclassified, whole wheat bread crumb with white bran was almost invariably identified as refined flour bread crumb. Using crust as the basis for comparisons, the largest difference in volatiles was between refined flour bread and whole wheat bread as a group. When refined flour bread crust was misclassified, samples tended to be confused with whole white wheat crust. Samples prepared from whole bread slices were poorly discriminated in general. E-nose results indicated that whole wheat bread formulated with white bran was more similar in volatile makeup to refined flour bread compared to whole wheat bread made with red bran. The E-nose appears to be very capable to accommodate differentiation of bread volatiles whose composition varies due to differences in flour or bran type. PRACTICAL APPLICATION: Consumer preference of bread made using refined flour in contrast to whole wheat flour is partly due to the different aroma of whole wheat bread. This study used an electronic nose to analyze bread volatiles, and showed that whole wheat bread incorporating white bran was different from counterpart bread made using red bran, and was closer in volatile makeup to "white" bread made without bran. Commercial millers and bakers can take advantage of these results to formulate whole wheat flour with brans of preferred type in order to foster increased consumption of whole wheat products which confer many favorable health benefits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".