Nutrient management in potted Syngoniums using water soluble fertilizers and biofertilizers: effects on growth and soil fertility
Bibliographic record
Abstract
The global ornamental plant market has been providing economic stability to nations for decades. To achieve enhanced productivity of ornamental plants, it is necessary to develop effective nutrient management techniques. A 2-year study was conducted to develop efficient nutrient management protocols for Syngonium ( Syngonium podophyllum Schott.), a high-value, commercial-potential plant. The experiments were conducted in a completely randomized design with 11 nutrient management treatments, comprising different doses of water soluble fertilizer (WSF) alone or in combination with arbuscular mycorrhizal fungi (AMF) or phosphorus solubilizing biofertilizer (PSB), and these treatments were compared with commercial fertilizer as well as control. The results revealed that the integrated use of WSF with its higher dose (4 g kg−1 soil) and PSB (200 mg kg−1 soil) application significantly improved the plant height and the plant spread by 10.4%–25.2% and 5.7%–12.6%, respectively. Furthermore, the soil fertility and nutrient concentration in the leaves were also observed to be significantly improved due to the combined application of WSF and PSB. Likewise, the maximum leaf fresh (257.5 g) and dry weight (36.1 g) were recorded in treatment with WSF 4 g + PSB. However, WSF in conjunction with AMF resulted in the highest root fresh and dry weight over other nutrient combinations. In conclusion, it was found that for better foliage and root growth of Syngonium with improved soil fertility and plant nutrient content, integrated application of WSF with either PSB and (or) AMF is suitable.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".