(96) Sensory Evaluation of Alternative Pear Varieties for the U.S. West Coast
Bibliographic record
Abstract
Assessing consumer acceptance is an important aspect of cultivar evaluation. Since 2002, about 2700 consumers have participated in pear preference surveys. Surveys were conducted on multiple dates and at multiple venues from 2002 to 2005 in Oregon and northern California. Survey participants were asked to indicate their preference for pears based on size, appearance, taste, and overall preference. They were also asked to indicate what attributes they liked or disliked about their favorite and least favorite varieties and to indicate their level of purchase intent. Each survey consisted of four to six cultivars, including at least one standard commercial comparison; i.e., Bartlett, Bosc, or Anjou. Data was analyzed (RCBD; Friedman Analysis of Rank or ANOVA/Tukey's HSD) at the OSU Food Innovation Center Experiment Station using Compusense® five v.4.6 software (Guelph, Ont., Canada). Results indicated several alternative possibilities for both summer and winter sales. Among the most preferred cultivars (variable between states) were Anjou (commercial standard winter pear), Bartlett (commercial standard summer pear and most-consumed cultivar), Blake's Pride, Cinnamon, Concorde, and 71655-014. Other major findings were preference for large pears for adults and small for children, overall liking based on sweetness and flavor rather than skin color, and general lack of knowledge of many commercial pear cultivars. Sensory evaluation surveys will be continued in 2006 in California, with focus on differential harvest times for selected preferred cultivars. Consumer preference data is being combined with production and postharvest quality data in order to provide the pear industry a comprehensive data set on potential alternative cultivars.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".