Apple flavor and its effects on sensory characteristics and consumer preference
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The focus within the apple industry is to identify varieties most preferred by consumers. To help with this, it is necessary to emphasize the discovery of flavor perceptions responsible for consumer preference in apples. The present study aimed to determine which flavor attributes are associated with different apple varieties, determine which apple varieties consumers prefer, and to determine which flavor attributes are contributing to consumer preference. Over two subsequent years, a trained sensory panel ( n = 10, n = 15) evaluated 27 and 28 varieties, respectively. Intensity ratings of taste, flavor, and texture characteristics for each apple variety were recorded. This data was paired with an untrained consumer hedonic evaluation ( n = 226) using a subset of apple varieties ( n = 16). Results revealed that two large groups of apple consumers exist. Group 1 (29%) emphasized the importance of texture, while Group 2 (49%) was primarily driven by sweet taste, and honey and floral flavors with less focus on texture. Practical Applications The results of this research provide insight into the positive and negative preference drivers of apple consumers. By understanding flavors associated with consumer preference, the information can be used as a tool to aid breeding programs in the creation of consumer‐centric apples that will be commercialized. Additionally, through the creation of an external preference map, a point‐of‐reference has been created to serve as a predictor for upcoming apple varieties to the Ontario apple industry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| 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 it