Modelling of colour development in the fruit of <i>Actinidia chinensis</i> ‘Hort16A’
Bibliographic record
Abstract
Abstract Colour development in fruit of Actinidia chinensis var. chinensis ‘Hort16A’, the new yellow‐fleshed cultivar produced commercially in New Zealand, was monitored during three seasons in four kiwifruit‐producing districts of New Zealand. Fruit were destructively harvested to measure flesh colour between flowering and harvest. Flesh colour of the outer pericarp remained green (115° hue angle) until c. 140 days after mid bloom (DAMB). Then flesh colour changed following a sigmoid like pattern to a yellow hue (97–100° hue angle) by 220 DAMB. The change in hue angle is shown to be well represented by the complementary log‐log function. The scale parameter describing this transition was independent of site and season, whereas timing of the transition between the upper and lower asymptote was dependant on both site and season because of a small dependence on the average of the maximum temperature over the period of 100–150 DAMB. Each degree C increase in maximum temperature during the 100–150 DAMB delays colour development by c. 3 days. Distribution of individual hue angles about the mean value was best described by a constrained beta distribution defined by two parameters, which in turn uniquely specify the average hue angle and variance of the population at that time. For hue angles near the mid range, which occurs before harvest maturity, this beta distribution is well approximated by a Normal distribution with the same mean and variance, but at harvest maturity a beta distribution is a better description. When the average hue angle is 103°, the difference between the 97.5 percentile on the Normal approximation and the beta distribution is c. 0.6. This difference rises rapidly as the hue angle drops further.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".