The Effect of Nitrogen and Phosphorus Ratios and Electrical Conductivity on Plant Growth
Bibliographic record
Abstract
Environmental concerns surround the use of plant growth retardants (PGRs) for plant height control, and non-chemical alternatives to PGRs can be labor intensive and expensive. Macronutrient modification is a little-studied, yet potentially effective method of controlling plant height. A number of studies have suggested that phosphorus (P) limitation may restrict plant height. Anecdotal evidence also suggests that using nitrate (NO3-), rather than ammonium (NH4+), as the principal nitrogen (N) source may help control plant height. The primary objective of this study was to evaluate different ratios of NO3-/ NH4+, NO3-/P and NH4+/P as well as electrical conductivity (EC) on plant height and growth. This was tested in a hydroponic system using marigolds, sunflowers and tomatoes. Initially, different ratios were tested at an EC of 1.2 dS·m-1, followed by using the same ratios at four ECs (0.6, 1.2, 2.2 and 4.0 dS·m-1) as a second objective. Although ratios did, at times, limit plant height, responses were season and species dependent, suggesting that modifications in plant nutrition, at the ratios used in this study, may not effectively control plant height in hydroponic systems. More consistent, yet species specific, height control was achieved by increasing EC level.
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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 | 0.001 |
| 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 | 0.001 |
| 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".