A Comparison of the Effects of Phycocyanin, γ-Aminobutyric Acid, Glycine Betaine, and Mycorrhizal Biostimulants of Non-Stressed Agrostis stolonifera
Bibliographic record
Abstract
Four biostimulants (phycocyanin, γ-aminobutyric acid (GABA), glycine betaine (GB), and the mycorrhizal fungus Rhizophagus intraradices) were applied foliarly to six cultivars of mature creeping bentgrass (Agrostis stolonifera) under non-stressed greenhouse conditions. Phycocyanin was most effective at increasing total shoot greenness, which was most consistent over time with the cultivars Penncross, T1, and Tyee. GABA was most effective at increasing total root fresh and dry weight, most strongly for Penncross and T1, respectively. GB was most effective at increasing total shoot fresh and dry weight, with both most strongly increased for Tyee. By comparison, R. intraradices had relatively low effectiveness for increasing any of these parameters. The appearance of the grass at the end of the experiment revealed that 007 and Focus generally showed the most and least growth benefit, respectively, with all four biostimulants. However, all cultivars showed increases in more than one parameter for each biostimulant, and thus, no cultivar was uniformly responsive or non-responsive to all the biostimulants. This research shows that phycocyanin, GABA, and GB may benefit multiple creeping bentgrass cultivars under non-stressed conditions, but each one tended to be more beneficial to a particular aspect of plant growth and quality. End users need to be aware of the importance of creeping bentgrass genotype when considering biostimulant application.
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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".