Molybdenum‐induced effects on nitrogen uptake efficiency and recovery in wheat (<i>Triticum aestivum</i>L.) using<sup>15</sup>N‐labeled nitrogen with different N forms and rates
Bibliographic record
Abstract
Abstract Background: Molybdenum (Mo) is an essential microelement for higher plants and plays a significant role in nitrogen (N) metabolism, which includes nitrate reduction, assimilation, and efficient N acquisition. Its deficiency in soil may induce the reduction of N uptake and wheat yield. Aims: We aimed to explore the Mo‐induced effects on N uptake efficiency and recovery in Mo‐inefficient winter wheat cultivar using a15N isotope tracer under different N forms (Nf) and N rates (Nr). Methods: The experiment was conducted in greenhouse conditions, and the treatments included three Nf in the form of15NH4Cl as sole NH4+, Ca (15NO3)2as sole NO3−, and15NH415NO3) under two Nr [low (L) 0.05 and high (H) 0.25 g N kg–1soil], with (+Mo) in form of [(NH4)6Mo7O24∙ 4H2O] and without (–Mo) Mo application. The plant biomass, Mo content, total N uptake, fertilizer15N uptake, soil N uptake, as well as N uptake, agronomic and physiological efficiency were evaluated. Furthermore, the fertilizer15N recovery in various wheat organs was also studied. Results: The results revealed that Mo application increased N uptake efficiency in wheat to 38.26%, 68.24%, and 71.53% when the plants are treated with low rates of NH4+, NO3−, and NH4NO3, respectively. While at a high N rate, N uptake efficiency increases to 46.26% and 45.34% in the case of NO3−and NH4NO3treatments, respectively, and it was slightly reduced to 10.84% when plants were supplied with NH4+form. Mo supply increased15N recovery from fertilizer in grain organ under low N rate with all supplied Nf, that is, NH4+, NO3−, and NH4NO3, while at high N rate, Mo enhanced15N recovery in grains organ in case of NO3−and NH4NO3forms. Conclusion: This study shows that Mo fertilization may be a promising strategy to improve N uptake efficiency and recovery in wheat when nitrate is the main N form.
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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 | 0.001 |
| 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".