WholeTree Substrate and Fertilizer Rate in Production of Greenhouse-grown Petunia (Petunia ×hybrida Vilm.) and Marigold (Tagetes patula L.)
Bibliographic record
Abstract
A substrate component ( WholeTree ) made from loblolly pine ( Pinus taeda L.) was evaluated along with starter fertilizer rate in the production of greenhouse-grown petunia ( Petunia × hybrida Vilm. ‘Dreams Purple’) and marigold ( Tagetes patula L. ‘Hero Spry’). Loblolly pine from a 12-year-old plantation were harvested at ground level, chipped, and further processed through a hammer mill to pass a 0.64-cm screen. The resulting WholeTree (WT) substrate was used alone or combined with 20% (WTP2) or 50% (WTP5) (by volume) Canadian sphagnum peatmoss and compared with an industry standard peat-lite (PL) mix of 8 peatmoss : 1 vermiculite : 1 perlite (by volume). Substrates were amended with 1.78 kg·m −3 dolomitic lime, 0.59 kg·m −3 gypsum [CaSO 4 -2(H 2 O)], 0.44 kg·m −3 Micromax, 1.78 kg·m −3 16N–2.6P–9.9K (3- to 4-month release), and 1.78 kg·m −3 16N–2.6P–10.8K (5- to 6-month release). A 7N–1.3P–8.3K starter fertilizer (SF) was added to each substrate at 0.0, 1.19, 2.37, or 3.56 kg·m −3 . Container capacity (CC) was greatest for PL and decreased as the percentage of peatmoss in the substrate decreased with WT having 35% less CC than PL. Conversely, air space (AS) was greatest for the WT and decreased as percentage of peatmoss increased with PL containing 33% less AS than WT. In general, petunia dry weight was greatest for any substrate containing peatmoss with a SF rate of 2.37 kg·m −3 or greater. The exception was that petunia grown in WT at 3.56 kg·m −3 SF had similar dry weight as all other treatments. Marigold dry weight was similar for all substrates where at least 2.37 kg·m −3 SF was used.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".