Study on the extraction, purification and quantification of jasmonic acid, abscisic acid and indole‐3‐acetic acid in plants
Bibliographic record
Abstract
INTRODUCTION: Jasmonic acid (JA), abscisic acid (ABA) and indole-3-acetic acid (IAA) are important plant hormones. Plant hormones are difficult to analyse because they occur in small concentrations and other substances in the plant interfere with their detection. OBJECTIVE: To develop a new, inexpensive procedure for the rapid extraction and purification of IAA, ABA and JA from various plant species. METHODOLOGY: Samples were prepared by extraction of plant tissues with methanol and ethyl acetate. Then the extracts were further purified and enriched with C(18) cartridges. The final extracts were derivatised with diazomethane and then measured by GC-MS. The results of the new methodology were compared with those of the Creelman and Mullet procedure. RESULTS: Sequential elution of the assimilates from the C(18 )cartridges revealed that IAA and ABA eluted in 40% methanol, while JA subsequently eluted in 60% methanol. The new plant hormone extraction and purification procedure produced results that were comparable to those obtained with the Creelman and Mullet's procedure. This new procedure requires only 0.5 g leaf samples to quantify these compounds with high reliability and can simultaneously determine the concentrations of the three plant hormones. CONCLUSION: A simple, inexpensive method was developed for determining endogenous IAA, ABA and JA concentrations in plant tissue.
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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 | 0.001 | 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 | 0.000 |
| 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".