Nitrogen use efficiencies of spring barley grown under varying nitrogen conditions in the field and growth chamber
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Bibliographic record
Abstract
BACKGROUND AND AIMS: Nitrogen-use efficiency (NUE) of cereals needs to be improved by nitrogen (N) management, traditional plant breeding methods and/or biotechnology, while maintaining or, optimally, increasing crop yields. The aims of this study were to compare spring-barley genotypes grown on different nitrogen levels in field and growth-chamber conditions to determine the effects on N uptake (NUpE) and N utilization efficiency (NUtE) and ultimately, NUE. METHODS: Morphological characteristics, seed yield and metabolite levels of 12 spring barley (Hordeum vulgare) genotypes were compared when grown at high and low nitrogen levels in field conditions during the 2007 and 2008 Canadian growing seasons, and in potted and hydroponic growth-chamber conditions. Genotypic NUpE, NUtE and NUE were calculated and compared between field and growth-chamber environments. KEY RESULTS: Growth chamber and field tests generally showed consistent NUE characteristics. In the field, Vivar, Excel and Ponoka, showed high NUE phenotypes across years and N levels. Vivar also had high NUE in growth-chamber trials, showing NUE across complex to simplistic growth environments. With the high NUE genotypes grown at low N in the field, NUtE predominates over NUpE. N metabolism-associated amino acid levels were different between roots (elevated glutamine) and shoots (elevated glutamate and alanine) of hydroponically grown genotypes. In field trials, metabolite levels were different between Kasota grown at high N (elevated glutamine) and Kasota at low N plus Vivar at either N condition. CONCLUSIONS: Determining which trait(s) or gene(s) to target to improve barley NUE is important and can be facilitated using simplified growth approaches to help determine the NUE phenotype of various genotypes. The genotypes studied showed similar growth and NUE characteristics across field and growth-chamber tests demonstrating that simplified, low-variable growth environments can help pinpoint genetic targets for improving spring barley NUE.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it