INSTRUMENTAL TEXTURE EVALUATION OF EXTRUDED SNACK FOODS: A REVIEW EVALUACIÓN INSTRUMENTAL DE TEXTURA EN ALIMENTOS EXTRUIDOS: UNA REVISIÓN
Bibliographic record
Abstract
Extrusion cooking technology is the most used technique for the production of snack foods. In such foods, texture is of major importance, with crispness being often a desirable attribute. Due to the high costs involved in sensory analysis, instrumental assessment of end-product texture, by fundamental and empirical techniques, has been a useful tool for food researchers and manufactures as it has been related to sensory evaluation. Among other tests, the texture analysis of expanded snacks has been performed through compression, penetration, acoustic procedures and texture profile analysis. Although this review has focused in instrumental techniques, texture evaluation of extruded snacks is a complex subject, where the combination of techniques involving sensory, instrumental and microstructure analysis would certainly be the best practice. From a practical perspective, empirical methods are suggested as an alternative to fundamental techniques, especially to food scientists and food manufactures interested in predict consumer perception of texture. La tecnologia de cocimiento por extrusión es la técnica mas utilizada para la producción de alimentos extruidos donde la textura es de especial importancia, siendo frecuentemente la crujibilidad el atributo más deseable. Debido a los altos costos del análisis sensorial, la evaluación instrumental de la textura en el producto final, utilizando técnicas fundamentales y empíricas, ha sido una herramienta útil para la investigación en alimentos y para la industria manufacturera ya que se ha correlacionado con la evaluación sensorial. Entre otras pruebas, el análisis de textura de alimentos extruidos se ha llevado a cabo por compresión, penetración, métodos acústicos y análisis de perfil de textura. Aunque esta revisión se enfoca a técnicas instrumentales, la evaluación de textura en alimentos extruidos es un problema complejo, donde la combinación de técnicas incluyendo análisis sensorial, instrumental y de microestructura podría ser la mejor forma de resolverlo. Desde un punto de vista práctico, los métodos empíricos se sugieren como una alternativa a las técnicas fundamentales, especialmente para científicos y productores de alimentos interesados en predecir la percepción de la textura por parte del consumidor. Palabras clave: Textura, extrusion, alimentos extruidos
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".