Canola and mustard response to short periods of temperature and water stress at different developmental stages
Bibliographic record
Abstract
Seed yield of Brassica crops in semiarid environments can be increased by minimizing the crops’ exposure to high temperature and water stress that often occurs during the growing season. A growth chamber study was conducted to determine the effect of short periods of high temperature and water stress at different developmental stages on seed yield and yield components of Brassica crops. Two canola-quality Brassica juncea ‘PC98-44’ and ‘PC98-45’, a Brassica napus canola ‘Quantum’, and a B. juncea oriental mustard ‘Cutlass’ were grown under 20/18°C day/night temperatures with photoperiod of 16/8 h light/dark. High (35/18°C) and moderate (28/18°C) temperature stress was imposed for 10 d during bud formation, flowering, and pod development. Low (90% available water) and high (50% available water) water stress was imposed in combination with the temperature treatments. On average, the 35/18°C stress reduced main stem pods by 75%, seeds pod-1 25%, and seed weight 22% from the control. Seed yield per plant was reduced by 15% when plants were severely (35/18°C) stressed during bud formation, 58% when stressed during flowering, and 77% when stressed during pod development. Plants stressed at earlier growth stages exhibited recovery, whereas stress during pod development severely reduced most of the yield components. Effect of water stress on seed yield was minimal regardless of crop developmental stage. The four Brassica cultivars responded similarly to water stress. In response to temperature stress, B. juncea produced greater number of pods per plant but had a great rate of pod infertility than B. napus. Seed yield of B. juncea in semiarid environments can be increased by improving pod fertility, whereas the seed yield of B. napus can be increased by improving pod pro duction and retention. Key words: Oilseed, yield components, Brassica species, moisture.
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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".