Growth Performance, Productivity and Carbon Sequestration of Wheat (Triticum assstivum)- Shisham (Dalbergia sissoo) based Agri-silviculture System with Especial Reference to Tree Pruning Intensities and Agronomic Practices
Bibliographic record
Abstract
The experiment was carried out at Akshayvat farm, Village- Arai, Block- Karchana, Allahabad during the year 2016- 2017. In agrisilviculture system, canopy management like pruning is an essential silvicultural management practice for reducing both above and below ground competition with associated crop. The experiment consists of five pruning intensities viz: no pruning, 20% pruning, 40% pruning, 60% pruning, 80% pruning and one open condition (no tree crop only) in main plot and three levels of fertilizer doses and seed rate viz; F1- recommended dose of fertilizer and seed rate, F2- 25% more nitrogen then recommended dose of fertilizer and F3- 25 % more seed rate than recommended dose of seed in sub plot under three replications. The results revealed that wheat under open condition recorded significantly higher germination percentage (86.30%), plant height (64.15cm),number of tillers (94.12), fresh wt. (954.49gm), dry wt.(372.19 gm), grain yield (25.03 q ha-1), fixed carbon (23.21%) and carbon sequestration (4.34.0 t ha-1) as compared to no pruning. In different levels of fertilizer doses and seed rate maximum plant height (64.08cm), number of tillers (92.02), fresh wt. (918.40gm), dry wt.(356.77 gm), grain yield (23.52 q ha-1) and carbon sequestration (3.57 t ha-1) was significantly higher under F2 (more nitrogen than recommended dose) as compared to F1 treatment. At age of 11 years, Dalbergia sissoo in 20% pruning gave higher tree height (11.64 m), basal area (0.089 m2), volume (0.49 m3 tree-1), and carbon sequestration (191.54 kg tree-1) as compared to other treatments. In agronomical management practices, 25% more nitrogen then recommended dose (F2) recorded significantly higher stand biomass (299.03 kg tree-1) over other treatments.
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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 | 0.001 |
| 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".