Effect of Cultivar and Site on Fruit Quality as Demonstrated by the NE-183 Regional Project on Apple Cultivars
Bibliographic record
Abstract
Cultivar and planting site are two factors that often receive minimal attention, but can have a significant impact on the quality of apple ( Malus × domestica ) produced. A regional project, NE-183 The Multidisciplinary Evaluation of New Apple Cultivars, was initiated in 1995 to systematically evaluate 20 newer apple cultivars on Malling.9 (M.9) rootstock across 19 sites in North America. This paper describes the effect of cultivar and site on fruit quality and sensory attributes at a number of the planting sites for the 1998 through 2000 growing seasons. Fruit quality attributes measured included fruit weight, length: diameter ratio, soluble solids concentration (SSC), titratable acidity (TA), flesh firmness, red overcolor, and russet. Fruit sensory characteristics rated included crispness, sweetness, and juiciness, based on a unipolar intensity scale (where 1 = least and 5 = most), and acidity, flavor, attractiveness, and desirability based on a bipolar hedonic scale (where 1 = dislike and 5 = like extremely). All fruit quality and sensory variables measured were affected by cultivar. The two-way interaction of cultivar and planting site was significant for all response variables except SSC, TA, russet, crispness, and sweetness ratings. The SSC: TA ratio was strongly correlated with sweetness and acidity sensory rating, but was weakly correlated with flavor rating. The results demonstrate that no one cultivar is ideally suited for all planting sites and no planting site is ideal for maximizing the quality of all apple 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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".