Identification of variability in phenological responses in canola-quality Brassica juncea for utilisation in Australian breeding programs
Bibliographic record
Abstract
Canola-quality Brassica juncea is a potential alternative crop species in lower rainfall Australian environments due to its superior heat and drought tolerance, disease resistance, and pod-shatter resistance compared with the currently grown B. napus species. Canola-quality types of B. juncea that are adapted to flower and mature before water deficits and high temperatures significantly limit yield potential are currently being developed. In this study, the variability in phenological characteristics in canola-quality B. juncea is assessed, with a view to identifying the potential for including a range of genetic phenological controls on the development of the crop to assist with adaptation. Vernalisation response was compared among 17 lines of B. juncea and 3 of B. napus, using a cold treatment of 2.6°C for 25 days. Leaf number, and duration to first flower and maturity were compared in response to the vernalisation treatments. To assess day length response, the same 20 genotypes were sown at five locations with a range of sowing times, and one controlled environment, where day length was artificially extended. Development stages were assessed and the duration of particular phenological phases determined in relation to time, thermal time, and photoperiod. The major factor controlling flowering in canola-quality B. juncea genotypes was day length, with only small responses to vernalisation detected. There was sufficient variability in these traits and in thermal time to flowering under long days (intrinsic earliness) within the current canola-quality germplasm in Australia to select early flowering genotypes with potential adaptation to low-rainfall environments.
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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 | 0.007 | 0.003 |
| 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 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".