Thinning `Fuji' Apple Blossoms with Synthetic Auxins (MCPB-ethyl or NAA) and Ethephon with or without Postbloom Thinning with Carbaryl
Bibliographic record
Abstract
Three experiments were conducted at two locations, two at Summerland, British Columbia, Canada and one at Corvallis, Ore., to evaluate synthetic auxins (MCPB-ethyl or NAA) and ethephon as blossom thinners for `Fuji' apple [ Malus sylvestris (L.) Mill var. domestica (Borkh.) Mansf.]. These experiments also involved application of carbaryl at 1000 mg·L -1 in the postbloom period. All blossom thinners were sprayed at 85% full bloom while carbaryl was applied at 11-mm fruit diameter. Within these experiments, MCPB-ethyl at up to 20 mg·L -1 or NAA at up to 21 mg·L -1 increased whole flower cluster removal linearly with rate; however, with the Corvallis experiment MCPB-ethyl failed to result in any thinning. Neither auxin treatment consistently reduced fruit set on the remaining clusters, resulting in “clustering”. Bloom-time application of ethephon at 100 mg·L -1 with NAA further reduced crop load. Carbaryl reduced total crop load by increasing both whole cluster removal and number of sites with a single fruit. Return flowering was not improved by the auxin treatments except where there was very excessive crop reduction. Ethephon or carbaryl promoted return flowering with the carbaryl effect being more pronounced. However, this carbaryl effect was significantly countered by the bloom-time auxin whereas ethephon overcame the negative effects of the auxin treatments. The combined use of ethephon and carbaryl was effective in terms of both crop reduction and return flowering benefits. Chemical names used: 1-naphthyl N-methylcarbamate (carbaryl); 2-chloroethylphosphonic acid (ethephon); ethyl 4-(4-chloro-2-methylphenoxy) butanoate (MCPB-ethyl); and 2-(1-naphthyl) acetic acid (NAA).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".