Effect of Different Levels of Zinc on the Growth and Yield of Cotton (Gossypium hirsutum L) Crop
Bibliographic record
Abstract
An experiment was conducted to determine the effect of different levels of zinc on the yield and growth of cotton in the field of Agronomy section ARI, Tandojam during the Kharif Season 2014. Seeds of cotton were sown in rows 75 x 30 cm in row and plant spacing in soil with four replications in Randomized Complete Block Design. Six zinc levels i.e. untreated 0.0, 5.0, 7.5, 10.0, 12.5 and 15.0 kg ha-1 were evaluated. The results reveals that plant height, number of sympodia plant-1, number of productive bolls plant-1, fibre length, G.O.T (%) and seed cotton yield kg ha-1 affected significantly by the zinc levels, while plant population and number of monopodial branches were not affected. Application of zinc from 5.00 to 15.00 showed similar effect. However, control resulted different in taller plants (130.55 in), while application of 15.00 kg zn ha-1 produced maximum sympodia (16.35 plant-1) however productive bolls were more at 10.00 kg zn ha-1 (50.30 plant-1). The staple length was maximum (27.00 mm) at 7.5 kg zn ha-1, while G.O.T% was greater (38.28%) at 5.00 kg zn ha-1, whereas maximum seed cotton yield was recorded at 7.5 kg zn ha-1 (2556.70 kg ha-1). For the trait of seed cotton yield plant1, there was no any difference between applications of zinc sulphates 5.00 to 7.5kg ha1.
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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) | 0.001 | 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".