The effect of auxins on amelioration of heat stress‐induced wheat (<i>Triticum aestivum</i> L.) grain loss
Why this work is in the frame
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Bibliographic record
Abstract
Abstract High temperature stress during the reproductive growth stage of wheat ( Triticum aestivum L.) can cause extensive yield losses. As the plant hormone auxin is a key regulator of reproductive development, we studied the effect of auxins on grain yield in five wheat lines exposed to moderate heat stress (34–35°C) for 6 h per day for 6 days during early flowering (booting stage to anthesis). ‘CDC Go’, a semi‐dwarf ( Rht ‐ B1b ) cultivar, responded to auxin application (1 µM) by producing higher grain number and yield under control and heat stress conditions. The effect of five different auxins on grain yield in ‘CDC Go’ was dependent on spike developmental stage at application and position within the spike, with 4‐Cl‐IAA at 1 µM being the most effective auxin treatment. The presence of Rht dwarfing mutant alleles of Rht ‐ B1 and Rht ‐ D1 alone did not increase auxin‐induced grain yield when tested in lines isogenic for these alleles. In the field, 4‐Cl‐IAA (1 µM) increased grain yield by 6%–8% only in ‘CDC Go’, one of six hard red spring wheat cultivars tested over two growing seasons in the western Canadian prairies. When 4‐Cl‐IAA application increased grain yield and number, the grain protein content was not affected; when it maintained grain yield in plants with lower biomass, grain protein content was reduced. Our field results suggested that both genotype and environment affect auxin‐induced enhancement of wheat grain yield. We recommend testing target environments with heat stress as a focus of a breeding programme along with further testing of auxin as a crop enhancement tool.
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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 | 0.001 |
| 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 it