Grain Yield, Starch Content and Activities of Key Enzymes of Waxy and Non-waxy Wheat (Triticum aestivum L.)
Bibliographic record
Abstract
Waxy wheat has unique end-use properties; however, its production is limited due mainly to its low grain yield compared with non-waxy wheat. In order to increase its grain yield, it is critical to understand the eco-physiological differences in grain filling between the waxy and non-waxy wheat. In this study, two waxy wheat and two non-waxy wheat cultivars were used to investigate the differences in starch-associated enzymes processes, sucrose and starch dynamics, yield components, and the final grain yield. The results indicated that the mean total grain starch and amylose content, the average 1000-kernel weight and grain yield of the waxy wheat were lower than those of the non-waxy wheat at maturity. The amylose content was significantly and positively correlated with the activity of GBSS (r = 0.80, p < 0.01). Significant positive correlation also exists among activities of AGPase, SSS, GBSS, and SBE, except for GBSS-SBE. In summary, our study has revealed that the reduced conversion of sucrose to starch in the late grain filling stage is the main cause for the low kernel weight and total starch accumulation of the waxy wheat. The reduced conversion also appears to be a factor contributing to the lower grain yield of the waxy wheat.
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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) | 0.001 | 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".