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 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".