Improved resilience and metabolic response of transplanted blackberry plugs using chitosan oligosaccharide elicitor treatment
Bibliographic record
Abstract
Transplanting of micropropagated blackberry plugs in the field during late summer and early fall is a common nursery practice for commercial blackberry production. During this field transition, blackberry plants generally experience different stresses in addition to transplanting shock coupled with sudden exposure to low night temperatures in the fall. Improving the stress resilience of field-transplanted blackberry plants by recruiting plant endogenous protective metabolic responses has significant merit. Therefore, the aim of this study was to improve stress resilience of newly transplanted ‘Chester Thornless’ blackberry in the field during fall transition through stimulation of phenolic antioxidant and proline-linked metabolic responses by using bioprocessed chitosan oligosaccharide (COS) as an elicitor treatment. Fourteen-week-old blackberry plugs were transplanted in the field in late July and COS was sprayed weekly in the run-off for a 6-wk period after transplanting. Total soluble phenolic content, total antioxidant activity, total proline content, proline dehydrogenase, and succinate dehydrogenase enzyme activity of blackberry shoots were evaluated weekly during and 1 wk after COS application. Improvement in total soluble phenolic content and antioxidant activity based on 2,2′-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) free radical scavenging assay was observed in field-transplanted blackberry at 6 and 7 wk with COS elicitation treatment.
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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".