Efficiency of protein as a nitrogen source for wheat and morphological changes in roots exposed to high protein concentrations
Bibliographic record
Abstract
Rasmussen, J., Gilroyed, B. H., Reuter, T., Badea, A., Eudes, F., Graf, R., Laroche, A., Kav, N. N. V. and McAllister, T. A. 2014. Efficiency of protein as a nitrogen source for wheat and morphological changes in roots exposed to high protein concentrations. Can. J. Plant Sci. 94: 603–613. Proteins of animal origin can enter the environment through application of agricultural by-products to arable or pastured land. In this study, wheat (Triticum aestivum cv. AC Andrew) was exposed to treatments with nitrogen (N) supplied as animal protein (bovine serum albumin; BSA), inorganic N or a combination of these sources at different iso-nitrogenous concentrations. Plant growth was assessed by monitoring both wet and dry mass of shoots and data showed that protein treatments did not differ (P>0.05) from controls lacking N. Analysis of N also showed that plants supplied with protein N displayed lower N (1.2–2.4%) concentration as compared with those supplied with inorganic N (up to 12.4%) with N remaining <2.4% even when the supply of protein was increased. Root morphology was altered in plants exposed to protein N concentrations >71 mM, with the development of knob-like outgrowths with unknown function or significance. This study provides evidence that wheat plantlets grown under sterile conditions are unable to utilize BSA as efficiently as NH4NO3 as a N source, but their roots exhibit a morphological response to protein.
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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 | 0.001 | 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".