Cadmium concentration in durum wheat grain (<i>Triticum turgidum</i>) as influenced by nitrogen rate, seeding date and soil type
Bibliographic record
Abstract
BACKGROUND: Cadmium (Cd) is a trace element that has been associated with various human health problems. Cd enters plants, either by direct absorption through leaves or by uptake from soils, allowing Cd into the food chain. Nitrogen (N) fertilizer management is important in optimizing crop yield and protein content of durum wheat, but may influence Cd availability and hence Cd concentration in crops, with the effects being strongly influenced by environmental conditions and crop cultivar. RESULTS: In field studies, Cd and protein concentration in durum wheat grain differed between cultivars and were strongly affected by N application, with only minor effects of N occurring on concentration and uptake of P and Zn. Protein content increased significantly with N application in five of six site-years, with the response being generally independent of cultivar and seeding data. Cd concentration also increased with N application in five of six seeding dates, with the response being greater in AC Melita than Arcola in three of the six site-years. There were large differences in Cd concentration from year to year and with seeding date, indicating a strong environmental influence. CONCLUSIONS: This study shows that different cultivars accumulate different levels of Cd in the grain and that seeding date and nitrogen fertilizer management can influence grain Cd concentration, with the magnitude of effects varying with environmental factors. In the future we may be able to manipulate management practices to optimize protein concentration and minimize Cd concentration in durum wheat, which could help to address the health and safety concerns of consumers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".