Non‐invasive quantification of ethylene in attached fruit headspace at 1 p.p.b. by gas chromatography–mass spectrometry
Bibliographic record
Abstract
Summary Ethylene is a gaseous plant hormone involved in defense, adaptations to environmental stress and fruit ripening. Its relevance to the latter makes its detection highly useful for physiologists interested in the onset of ripening. Produced as a sharp peak during the respiratory burst, ethylene is biologically active at tens of nl L −1 . Reliable quantification at such concentrations generally requires specialized instrumentation. Here we present a rapid, high‐sensitivity method for detecting ethylene in attached fruit using a conventional gas chromatography–mass spectrometry ( GC ‐ MS ) system and in situ headspace collection chambers. We apply this method to melon ( Cucumis melo L.), a unique species consisting of climacteric and non‐climacteric varieties, with a high variation in the climacteric phenotype among climacteric types. Using a population of recombinant inbred lines ( RIL s) derived from highly climacteric (‘Védrantais’, cantalupensis type) and non‐climacteric (‘Piel de Sapo’, inodorus type) parental lines, we observed a significant variation for the intensity, onset and duration of the ethylene burst during fruit ripening. Our method does not require concentration, sampling times over 1 h or fruit harvest. We achieved a limit of detection of 0.41 ± 0.04 nl L −1 and a limit of quantification of 1.37 ± 0.13 nl L −1 with an analysis time per sample of 2.6 min. Validation of the analytical method indicated that linearity (>98%), precision (coefficient of variation ≤2%) and sensitivity compared favorably with dedicated optical sensors. This study adds to evidence of the characteristic climacteric ethylene burst as a complex trait whose intensity in our RIL population lies along a continuum in addition to two extremes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".