Study of Site Specific Nutrients Management of Cowpea Seed Production and Their Effect on Soil Nutrient Status
Bibliographic record
Abstract
To produce anticipated output of any crop, the site specific nutrients management (SSNM) is essential for balance and adequate nutrients supply without impairing the inherent fertility status of soil. For cowpea seed production and to maintain soil nutrient status, a field experiment was conducted with nine treatments (nutrients combinations) to find out appropriate SSNM practice. Nutrients especially N, P, K, S, Zn and Bo requirement for cowpea seed production was estimated to 30, 60, 50, 30, 15 and 2.0 kg per hectare respectively and treated as 100% of SSNM. Growth and development parameters were significantly influenced with the treatments. Maximum plant height (61.9 cm) was recorded when crop was fed with 125 per cent of SSNM. However minimum plant height (54.8 cm) was recorded in case of SSNM-N. Leaf Area Index (LAI) at 60 DAS ranged from 3.37 to 3.91. Nodules dry weight was significantly influenced by boron treatments apart from nitrogen and other as well. Maximum seed yield was obtained (2237.2 kg /ha) in the plot fertilized with 125 per cent of SSNM and minimum (1343.5 kg/ha) was recorded in the plot fertilized with state recommendation. Highest and lowest gross ( 40270/- and 24183/-) was recorded with 125 per cent of SSNM and with state recommendation respectively. Application of 125 per cent of SSNM recorded maximum uptake of nitrogen (205.3 kg / ha) which is at par with 100 % of SSNM. None of the treatment influences significantly soil fertility and physico-chemical properties of the soil rather slight improvement were recorded in all the observed parameters though considerable build-up of available P and exchangeable K was noticed in plots fertilized with SSNM.
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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 | 0.000 | 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 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".