Gibberellins in developing wheat grains and their relationship to late maturity α-amylase (LMA)
Bibliographic record
Abstract
MAIN CONCLUSION: α-Amylase synthesis by wheat aleurone during grain development (late maturity α-amylase) appears to be independent of gibberellin unlike α-amylase synthesis by aleurone during germination or following treatment with exogenous GA. Late-maturity α-amylase (LMA) in wheat (Triticum aestivum L.) involves the synthesis of α-amylase by the aleurone tissue during grain development. Previous research identified a putative ent-copalyl diphosphate synthase gene, coding for an enzyme that controls the first step in gibberellin biosynthesis, that underlies the major genetic locus involved in variation in LMA phenotype. The reported results for gene transcript analysis, preliminary gibberellin analysis and the effects of DELLA mutants on LMA phenotype appeared to be consistent with involvement of gibberellin but did not provide definitive proof of a causal link. Conversely, several observations do not appear to be consistent with this hypothesis. In this current study, LMA phenotype, gibberellin profiles and ABA content were recorded for experiments involving susceptible and resistant genotypes, gibberellin biosynthesis inhibitors, genetic lines containing different LMA quantitative trait loci and treatment of distal halves of developing grains with exogenous gibberellin. The results suggested that gibberellin may not be a prerequisite for LMA expression and further that the mechanism involved in triggering α-amylase synthesis did not correspond to the model proposed for germination and gibberellin challenged aleurone of ripe grain. The results provide new insight into LMA and highlight the need to investigate alternate pathways for the induction of α-amylase gene transcription, the function of novel 1-β-OH gibberellins and other functions of DELLA proteins in developing grains.
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 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) | 0.001 | 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".