Multi-year investigation on the rate, timing, and use of surfactant for thinning apples with post-bloom applications of metamitron
Bibliographic record
Abstract
Several experiments were conducted in Simcoe, Ontario, to evaluate the efficacy of metamitron (MET) as a post-bloom thinner for Ambrosia, Gala, and Honeycrisp apple trees. Trees were treated with rates of MET ranging from 165–480 mg·L −1 , as well as different timings ranging from 5–22 mm fruit diameter. The effect of including a non-ionic surfactant on thinning efficacy with MET was also evaluated. Treatments were compared with untreated trees and industry standard sprays of carbaryl, 1-naphthalene acetic acid (NAA), 6-benzyladenine (6-BA), or combinations thereof. Response to MET varied by cultivar and season. In six of the seven experiments MET reduced fruit set, but only in four experiments did MET reduce the number of fruit per tree or crop load compared with the untreated control trees. Petal fall (5–7 mm) applications of MET were less effective than later timings. Thinning response increased with higher rates of MET in four of the seven studies. For Honeycrisp and Ambrosia, 175 mg·L −1 MET was effective in reducing fruit set and crop load, while rates at or above 263 mg·L −1 MET were required to thin Gala. MET improved fruit size distribution into larger categories and caused minimal leaf phytotoxicity with or without a non-ionic surfactant. Environmental factors such as nighttime temperature and solar radiation largely could not account for the seasonal or application timings in thinning response to MET. Greater understanding of the carbon balance and interplay of solar radiation, nighttime temperature, cultivar and fruitlet size on thinning response is required to improve the predictive thinning response of apple to MET.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".