Growth and physiological response of canola (Brassica napus L.) to interactive effect of temperature, moisture and nitrogen stresses under controlled environment
Bibliographic record
Abstract
Present atmospheric limits growth of C3 crop plants, which show response to elevated CO2 via reduced photorespiration and enhanced photosynthetic rates thereby increased growth and yield. Global research on plant responses to raising atmospheric CO2 has primarily focused on C3 species, advancing our understanding of processes underlying C3 plant acclimation and response. Therefore extensive research has been conducted to project the potential impacts of global warming on agriculture productivity through laboratory by using crop and global climate models. Canola is one of the world’s most important oilseed crops and the most profitable commodity for Canadian farmers. As a C3 cool season crop, it is more susceptible to heat stress than other C3 and C4 field crops (Wu and Ma, 2018). High temperature significantly changes the rate of plant metabolic processes that ultimately reduces biomass accumulation and grain formation. A field study in Eastern Canada reported that seed yield reduced as much as 40% in 2012 due to severe heat and drought stress over normal years (Ma and Herath, 2016). High or warm temperature has been shown to induce the floral sterility or pollen abortion and shorten seed filling duration and subsequently reduce inflorescence size in canola plants. Even high temperature could alter the partitioning of photoassimilates to roots and suppress root growth extension or change root system architecture. Late seeded canola plants often produced a smaller root system, due to higher temperature and or drought stress encounters during the crop development. Keeping these facts trial was conducted under controlled condition to know the response of canola to drought stress, elevated CO2 and temperature.
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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) | 0.001 | 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 | 0.001 |
| 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".