Effect of Integrated Nutrient Management on Yield and Quality of Basmati Rice Varieties
Bibliographic record
Abstract
A 2-year study conducted to determine the effect of integrated nutrient management on yield and quality of basmati rice varieties in non-traditional area with 54 plots in split plot design. Variety HUBR 10-9 produced 18.8% higher mean grain yield and superior quality parameters than HUBR 2-1. Mean milling, head rice recovery, amylose content and alkali digestion value noted higher with HUBR 10-9 by 4.1%, 4.1%, 8.5% and 15.1% over HUBR 2-1, respectively. Addition of 75% recommended dose of fertilizers with 25% recommended dose of nitrogen as farmyard manure produced higher mean values by 3.1%, 4.2% and 4.0% for hulling, milling and head rice recovery respectively over 100% recommended dose applied as inorganic sources. Combined use of bio-inoculants (blue green algae plus Azospirillum) exhibited higher values for yield and quality parameters. HUBR 10-9 be grown using 75% recommended dose of fertilizers with 25% nitrogen as farmyard manure and blue green algae plus Azospirillum for enhancement in yield and quality in non-traditional areas of eastern Uttar Pradesh. Further investigation required under diverse conditions.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".