“AROOJ-22” a versatile climate resilient high yielding bread wheat variety recommended for irrigated and rainfed areas of Punjab Pakistan
Bibliographic record
Abstract
Arooj-22 is a bread wheat variety released by Wheat Research Institute (WRI), for irrigated and rainfed areas of Punjab-Pakistan. It was selected during 2016-17 from 24th Semi-Arid Wheat Yield Trial (SAWYT) from CIMMYT, Mexico. It was evaluated for yield stability in regular, provincial and national yield trials with the genotype code; V-17179 from 2017-2021. It delivered superior against the check variety Faisalabad-08, over 28 locations (22 irrigated and 6 rainfed) throughout the province of Punjab and produced 14.7% more grain yield in provincial yield trial. In national yield trial during 2019-20; V-17179 produced 13.4%, 17% and 18% higher yield than check varieties (Ghazi-19, Pak-13, local check) under 20 irrigated locations while produced 11.48%, 15.95% and 17.21% more grain yield than same check varieties under 6 rain-fed locations. Moreover, in national yield trial during 2020-21; V-17179 produced 2.1% and 5.1% more grain yield under 21 irrigated locations as compared to check (Ghazi-19 and Pak-13), while under 6 rain-fed locations V-17179 produced 3.5%, 8.2% and 10% more grain yield than check varieties (Ghazi-19, Pak-13 and local check). Rust resistance index was very good as 8.4 for leaf rust while it was in the acceptable range of 5.67 against yellow rust. The quality parameters were also found worthy regarding protein (12.9%), starch (53.3%), gluten (23%) and test weight (71.1 kg/hl). Arooj-22 delivered best consecutively in two-years (2019-20 and 2020-21) when sown at 1st forth-night during November, with the seed rate of 100 kgha-1 along with the dose fertilizer of 120-90-60 N-P-K (kgha-1). The DNA fingerprinting report showed that Arooj-22 has diverse genetic background from previously registered genotypes. The variety Arooj-22 was recommended/approved in 2021 for the general cultivation in irrigated and rainfed areas of Punjab
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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 | 0.000 | 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) | 0.000 | 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".