Grain Yield, Nutrient Accumulation and Fertilizer Efficiency in Bread Wheat under Variable Nitrogen and Phosphorus Regimes
Why this work is in the frame
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Bibliographic record
Abstract
Balanced crop nutrition is one of the important tools necessary for sustaining crop productivity, maintaining soil fertility and ensuring food security worldwide. Nitrogen and phosphorus are essential plant macronutrients, nevertheless, most of the Pakistani soils exhibit moderate to severe deficiency of these nutrients. Furthermore, considerable genetic variations exist among wheat genotypes for nutrient acquisition and utilization which illustrate their differential nutrient requirements to produce higher yields. A field experiment was conducted in order to formulate balanced fertilizer recommendations for newly evolved wheat genotype SD-998 to achieve maximum yield potential. Ten treatments viz., 0-0 (control), 90-23, 90-45, 90-70, 120-30, 120-60, 120-90, 150-40, 150-75 and 150-110 kg N-P2O5 ha-1 were applied according to randomized complete block design with three replications. Analysis of variance revealed that growth, yield and yield related attributes as well as nutrient accumulation were significantly (P ? 0.05) influenced by varying N and P rates. The maximum plant height (100.8 cm), number of tillers per plant (10), spike length (10.3 cm), number of grains per spike (66), 100-grain weight (4.10 g) and grain yield (4990 kg ha-1) was recorded in treatment having 150-110 kg N-P2O5 ha-1. The highest P recovery efficiency (20.8 %), agronomic N efficiency (19.4 kg kg-1) and agronomic P efficiency (36.8 kg kg-1) were attained at 120-30, 90-70 and 150-40 kg N-P2O5 ha-1, respectively. However, the highest total N accumulation (140.8 kg ha-1), P accumulation (21.0 kg ha-1), N recovery efficiency (71.1 %) and profit (Rs. 73625 ha-1) were noticed at 150 kg N plus 110 kg P2O5 ha-1. Thus, 150-110 kg N-P2O5 ha-1 (N:P2O5 in 4:3 ratio) was suggested as the most balanced and economical dose for the tested wheat genotype.
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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 | 0.000 |
| 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 it