Impact of seed discolouration on emergence and early plant growth of durum wheat at different soil gravimetric water contents
Bibliographic record
Abstract
The effects of soil gravimetric water content on emergence and early growth of plants derived from durum wheat [T. turgidum L. ssp. durum (Desf) Husn.] with red smudge or black point/dark smudge symptoms were determined under controlled environmental conditions. Three soil gravimetric water content levels (1%, 5% and 20%) were used to simulate a range of field conditions which might occur in the spring in southern Saskatchewan. Plant emergence and growth were affected in a similar manner by the soil gravimetric water content, regardless of whether the seeds were affected by red smudge or black point/dark smudge. Lower soil gravimetric water content resulted in slower emergence of seedlings, reduced plant emergence and decreased development of above-ground and root tissue. Rate of emergence, number of plants emerged, and number of leaves were negatively affected by red smudge regardless of the soil gravimetric water content, while length of the longest seminal root and total plant dry weight were lower in the red smudge compared with the healthy treatment at the 20% soil gravimetric water content. A negative effect of black point/dark smudge on seedling emergence was observed only at the 1% soil gravimetric water content, while negative effects on the length of the longest leaf and total plant dry weight were observed in the black point/dark smudge treatment regardless of the soil gravimetric water content. We conclude that seed discolouration, especially red smudge, and soil gravimetric water content were important factors in the emergence and growth of durum wheat plants, with soil gravimetric water content compounding the negative effects of seed discolouration on plant emergence and growth.
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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".