Impact of 5’ Adenosine Monophosphate, Potassium Chloride, and Glycine on the Physicochemical and Sensory Characteristics of Sodium-Reduced Chicken
Bibliographic record
Abstract
The demand for low-sodium products is growing worldwide and is compelled by the growing number of related illnesses. However, the quality of these products could be improved, likened to products produced with common salt (NaCL), because the replacement of sodium compromises the flavor of the product. Reducing sodium salts also poses an essential challenge for the meat industry, since sodium chloride (NaCl) fulfills essential technological functions. High sodium consumption has harmful health implications for cardiovascular and hypertension disorders. As a result, this study aimed to analyze the effect of KCl with Glycine and AMP on the physicochemical and sensory characteristics, purchase intent, and consumer perception of roasted chicken. NaCl/KCl replacement levels (0%, 25%, 50%, 75%, and 100%) were established, and consumer perception, liking, emotions, and purchase intent were evaluated. The different KCl levels, except for firmness, did not impact the physicochemical attributes. Even though higher replacement levels of KCl (75–100%) impacted chicken tenderness, it had no notable impact on panelists’ liking scores and purchase intent. Health claims about the sodium content in roasted chicken have also been shown to significantly increase purchase intent, based on enhancing consumer’s emotional responses. Regarding emotional responses, feelings of being unsafe and worried decreased their scores among the highest KCl replacement levels (75% and 100%). Positive emotional responses (feeling satisfied and pleased) were decisive consumer purchase intent predictors.
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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 | 0.001 |
| 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 | 0.001 |
| 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".