Influence of Biotic and Abiotic Factors on Dark Discoloration of Durum Wheat Kernels
Bibliographic record
Abstract
ABSTRACT Black point (BP, discoloration restricted to the germ end of cereal seed) and dark smudge (DS, discoloration mostly along the crease) are believed to be caused by fungal infection in grain exposed to high humidity, although it has also been reported that BP might result from abiotic stresses causing physiological changes in grain. The objective of this growth‐chamber study was to determine the effects of abiotic (temperature and high humidity) and biotic (infection by Cochliobolus sativus [Ito and Kurib.] Drechs. ex Dast. (anamorph Bipolaris sorokiniana [Sacc.] Shoemaker); or Alternaria alternata [Fr.] Keissl.) factors on the development of BP and DS in durum wheat (Triticum turgidum L. ssp. durum [Desf.] Husn.). Five treatments under two temperature regimes (Low T, 17°C day and 12°C night; or High T, 26°C day and 18°C night) were conducted: inoculation with A. alternata or C. sativus at mid‐milk with 30‐h incubation at 100% humidity; one exposure to 100% humidity at mid‐milk (HUMo); multiple exposures to 100% humidity from heading to maturity (HUMm); and no exposure to 100% humidity or fungal inoculum (DRY). Kernels were evaluated for incidence and extent of discoloration. The highest incidences of discoloration occurred in the C. sativus treatment, followed by the A. alternata treatment, with HUMm producing low incidences, and HUMo and DRY only occasional discoloration. In general, High T favored BP and Low T favored DS. In the C. sativus treatment, Low T also favored extent of discoloration. Whether fungal infection was promoted or unhindered by a primary effect of high humidity on the physiology of the kernel and its defenses could not be determined given that exposure to high humidity is a requirement for fungal infection.
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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".