Sesquiterpene α-Farnesene Synthase: Partial Purification, Characterization, and Activity in Relation to Superficial Scald Development in Apples
Bibliographic record
Abstract
To decipher the relation between α-farnesene metabolism and the development of superficial scald in apples, trans,trans -α-farnesene synthase, the enzyme that catalyzes the conversion of farnesyl pyrophosphate to α-farnesene, was partially purified from skin tissue of `Delicious' apples ( Malus × domestica Borkh.) and characterized. Total and specific activities of the enzyme were higher in the cytosolic fraction than in membrane fractions. α-Farnesene synthase was purified 70-fold from the cytosolic fraction by ion exchange chromatography and gel permeation, and the native molecular weight was estimated to be 108,000. The enzyme had optimal activity at a pH of 5.6 and absolutely required a divalent metal ion such as Mg 2+ or Mn 2+ for activity. It exhibited allosteric kinetics, S (0.5) for farnesyl pyrophosphate being 84±18 μmol·L -1 , and a Hill coefficient (n H ) of 2.9, indicating the number of subunits to be two or three. Enzyme activity was highest between 10 and 20 °C, while 50% of the maximal activity was retained at 0 °C. In vivo α-farnesene synthase activity was minimal at harvest, then increased rapidly during 16 weeks storage in air at 0 °C, and decreased during further storage. Activity of α-farnesene synthase, α-farnesene content, and conjugated triene alcohol (the putative scald-causing oxidation product of α-farnesene) content in skin tissue were not correlated to the inherent nature of scald susceptibility or resistance in 11 apple cultivars tested.
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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 | 0.000 |
| 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 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".