Study of factors influencing the germination of Apera spica-venti (L.) P. Beauv. in controlled conditions
Bibliographic record
Abstract
Apera spica-venti (L.) P. Beauv., also said " silky bent grass" or "windgrass", is a common weed of cereal crops, especially of winter wheat.It is widely spread in Northern and Easthern Europe, Northern Asia, Siberia and Canada.The main problem is the competition for water, light, space and nutriment's elements between this weed and the cereal crop.This could involve important yield losses, sometimes reaching 30% ( 1 Massa, 2011 ; 2 Warwick et al., 1985).Given the ability of Apera spica-venti to grow and develop in cereal fields in Wallonia and the lack of scientific knowledge about its biology, 2 germination tests were performed.-a preliminary test in order to know the germination percentage of 37 populations and to chose 4 populations among these.-the main test in order to study three major factors influencing the germination of seeds: composition of the water solution, presence or absence of pre-chilling and temperature setup.This test was carried on according to the standards of the International Seed Testing Association (ISTA).Germination tests showed that a solution containing 2 g/L of KNO 3 and alternating temperature between night and day from 10°C and 30°C favorably influence the germination of Apera spica-venti.These results in controlled conditions are a premise for greenhouse and field tests. Study of factors influencing the germination of Apera spica-venti (L.) P. Beauv. in controlled conditions ConclusionsAs far as germination tests are concerned, the optimal factors levels favoring Apera spica-venti (L.) P. Beauv.germination are a 1030°C temperature and the presence of KNO 3 in the germination solution.None of the prechilling factor levels proved superior to the other.These results in controlled conditions are a premise for greenhouse and field tests.The results of these germination tests are very important to gain time to perform other tests and experiments.For example, seed dormancy mechanisms' tests, resistance test, test to know the physiology better, test on the speed of growing, etc.As germination of Apera spica-venti (L.) P. Beauv. is now improved in controlled conditions, we hope it can help other scientists to study further aspects of this species.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".