Effects of GA <sub>3</sub> Treatments on Fruit Vascular Structure and Water Transport of Grape
Bibliographic record
Abstract
Exogenous gibberellic acid was applied to regulate fruit growth of grapes to acquire high quality seedless berries. The vascular bundles provide the pathway of water and nutrient transport into the fruit and play an important role in berry growth and sugar accumulation. Therefore, changes in berry size and quality are closely related to the structure and function of the vascular tissue. In this study, 10-year-old “Shine Muscat” grape vines were treated with GA3 in grapevine production. Based on previous research and experimental environmental conditions, four treatments were applied: elongating cluster（5 mg L−1 GA3 on Apr. 28）+ seedless（25 mg L−1 GA3 on May. 24）+ expanding（50 mg L−1 GA3 on Jun. 7） (T1), seedless（25 mg L−1 GA3 on May. 24）+ expanding（50 mg L−1 GA3 on Jun. 7） (T2), expanding（50 mg L−1 GA3 on Jun. 7） (T3) and water (CK). Compared to CK, all fruits treated with GA3 had greater berry size. In addition, GA3 treated grapes had greater vascular bundle areas, including the areas of both phloem and xylem, as well as a greater number of vessels compared to control fruit. During the first rapid growth stage, water transport into the grape was rapid and did not differ among treatments. During veraison, the water transport rate among the four treatments differed, and the rank of speed was T2>T3>CK>T1. Therefore, we found that GA3 treatment can significantly promote the differentiation of vascular tissues and improve water transport capacity and phloem sugar unloading; T2 promoted the development of vascular bundles, enhanced water transport speed and phloem sugar unloading of fruit after veraison, and increased berry size.
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 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 | 0.000 | 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 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".