Alleviation of Chilling Injury in Postharvest Sweet Basil (Ocimum basilicum L.) with Silicon and Abscisic Acid Applications
Bibliographic record
Abstract
Sweet basil (Ocimum basilicum L.) is highly susceptible to chilling injury (CI), resulting in the development of CI symptoms during cold storage that reduce postharvest quality and shelf life. This study evaluated whether silicon (Si) and abscisic acid (ABA) applications can mitigate these symptoms. In Trial 1, basil plants had a Si solution (189 mg/L Si from potassium silicate) or deionised water (control) applied during cultivation via rootzone irrigation or foliar spray. Some plants were also foliar sprayed with ABA (1000 mg/L) before harvest. In Trial 2, wollastonite was added to the growing media (0, 1, 2, 3, 4, 5 mL/L) as the Si source. Applying the Si solution using either method reduced leaf necrosis, fresh weight loss, and electrolyte leakage, extending shelf life to at least 14 days. There were also no negative impacts on plant performance during cultivation (chlorophyll content, shoot height, and canopy width). The ABA solution, alone or in combination with Si solution, reduced symptoms but less effectively, extending shelf life up to 8 days. Wollastonite had no positive effects. These findings suggest that Si solution applications are a promising strategy to alleviate CI during postharvest cold storage of basil at 3.5 °C.
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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 | 0.000 |
| 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".