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Record W4408551161 · doi:10.3390/agriculture15060643

Alleviation of Chilling Injury in Postharvest Sweet Basil (Ocimum basilicum L.) with Silicon and Abscisic Acid Applications

2025· article· en· W4408551161 on OpenAlexafffund
Vivian Ly, Youbin Zheng

Bibliographic record

VenueAgriculture · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSilicon Effects in Agriculture
Canadian institutionsUniversity of Guelph
FundersMitacs
KeywordsBasilicumOcimumSweet BasilAbscisic acidPostharvestHorticultureBiologyBotany

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.204
Teacher spread0.200 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes2
Has abstractyes

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