Timing of Macronutrient Supply during Cutting Propagation of Petunia
Bibliographic record
Abstract
The objective was to quantify the effect of the timing of macronutrient applications on nutrient uptake, growth, and development of Petunia × hybrida Hort. Vilm.-Andr. ‘Supertunia Royal Velvet’ during vegetative propagation. Starting with unrooted cuttings (Day 0), fertigation was applied continuously at three time intervals (Day 0 to 7, Day 8 to 14, or Day 15 to 21) using either a “complete” (C) water-soluble fertilizer containing (in mg·L −1 ) 75 NO 3 -N, 25 NH 4 -N, 12 phosphorus (P), 83 potassium (K), 20 calcium (Ca), 10 magnesium (Mg), 1.4 sulfur (S), 2 iron (Fe), 1 manganese (Mn), 1 zinc (Zn), 0.5 copper (Cu), 0.5 boron (B), and 0.2 molybdenum (Mo) or a micronutrient fertilizer (M) containing (in mg·L −1 ) 1.4 S, 2 Fe, 1 Mn, 1 Zn, 0.5 Cu, 0.5 B, and 0.2 Mo in a complete factorial arrangement. With constant fertigation using the C fertilizer, plant dry weight (DW) doubled from Day 0 (sticking of unrooted cuttings) to Day 7 (0.020 g to 0.047 g), root emergence was observed by Day 4, and by Day 7, the average length of primary roots was 2.6 cm. During any week that the M fertilizer was substituted for the C fertilizer, tissue N–P–K concentrations decreased compared with plants receiving the C fertilizer. For example, plants receiving the M fertilizer between Day 0 and 7 had 20% lower tissue-N concentration at Day 7 compared with those receiving the C fertilizer. Although both shoot DW and leaf count increased once macronutrient fertilization was resumed after Day 7, final shoot DW and leaf count were lower than plants receiving C fertilizer from Day 0 to 21. Time to first root emergence was unaffected by fertigation. Constant application of C resulted in a higher shoot-to-root ratio at Day 21 than all other treatments. Results emphasize the importance of early fertigation on petunia, a fast-rooting species, to maintain tissue nutrient levels within recommended ranges.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".