Transcriptomics of improved fruit retention by hexanal in ‘Honeycrisp’ reveals hormonal crosstalk and reduced cell-wall remodelling in the fruit-abscission zone
Bibliographic record
Abstract
Abstract Apples ( Malus domestica Borkh) are prone to pre-harvest fruit drop which is more pronounced in ‘Honeycrisp’. Using a transcriptomic approach, we analyzed the molecular mechanisms of fruit retention in ‘Honeycrisp’. A total of 726 differentially expressed genes (DEGs) were identified in the abscission zone of hexanal-treated and untreated fruit (FAZ). Hexanal down-regulated the genes involved in ethylene biosynthesis, such as S-adenosylmethionine synthase ( SAM2 ) and 1-aminocyclopropane-1carboxylic acid oxidases ( ACO3 , ACO4 and ACO4 - like ). Genes related to ABA biosynthesis ( FDPS and CLE25 ) were also down-regulated. On the contrary, gibberellic acid (GA) biosynthesis genes, gibberellin 20 oxidase1-like ( GA20OX - like ) and ent-kaurene oxidase ( KO ) were up-regulated. Further, hexanal down-regulated the expression of genes related to cell-wall remodelling enzymes such as polygalacturonase ( PG1 ), glucanases (endo-β-1,4-glucanase; EG) and expansins ( EXPA1 - like, EXPA6, EXPA8, EXPA10 - like, EXPA16 - like ). Hexanal also reduced ethylene, and abscisic acid (ABA) production at commercial harvest stage. Hexanal reduced ethylene production in fruits and thus reduced the sensitivity of FAZ cells to ethylene and ABA. Simultaneously, hexanal maintained the cell-wall integrity of FAZ cells by regulating genes involved in cell-wall modifications. Our findings show that fruit abscission is delayed by hexanal, by down regulating ABA through an ethylene-dependent mechanism. Highlight Hexanal, a naturally occurring plant compound, increased fruit retention in apples by decreasing ethylene and ABA production and maintaining the cell-wall integrity in the fruit abscission zone.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".