Agro-Morphological Evaluation of Semi-Arid Wheat (Triticum aestivum L.) Genotypes for Grain Yield Improvement
Bibliographic record
Abstract
Wheat is widely cultivated cereal crop across diverse agro-climatic regions including Pakistan and serves as a staple food for billions of people. In the current study 17 wheat genotypes were evaluated from the semi-arid wheat yield trial (SAWYT) along with local check variety (NIA-Amber) at the Seed Production & Development Centre (SPDC), Tando-Jam, during the rabi season of 2024–2025 to assess agro-morphological traits associated with grain yield. The experiment, laid out in a randomized complete block design (RCBD) with three replications. It was revealed from the findings that all genotypes showed highly significant differences (P ≤ 0.01) for all traits studied. However, SAWYT-17 was the earliest genotype (58.66 days to heading) and recorded the highest harvest index (59.08%), while SAWYT-2 exhibited the tallest plant height (116.55 cm) and semi-dwarf types included SAWYT-9 and SAWYT-10. The longest spike was observed in SAWYT-8 (10.25 cm), and the maximum spikelets spike⁻¹ in SAWYT-16 (22.23). Grain yield per plot was highest in SAWYT-4 (2.23 kg), biological yield was maximum in SAWYT-8 (4.40 kg), and 1000-grain weight was maximum in SAWYT-7 (56.85 g), followed by SAWYT-6 (53.30 g). The largest flag leaf area was noted in SAWYT-10 (37.85 cm²). Overall, genotypes SAWYT-4, SAWYT-7, SAWYT-8, and SAWYT-17 were identified as promising genotypes for use in breeding programs to enhance wheat yield under semi-arid conditions in Pakistan.
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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 | 0.014 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".