Nitrogen Application Improved Photosynthetic Productivity, Chlorophyll Fluorescence, Yield and Yield Components of Two Oat Genotypes under Saline Conditions
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Bibliographic record
Abstract
: Understanding the interaction between salinity and nitrogen (N) nutrition is of great economic importance to improve plant growth and grain yield for oat plants. The objective of this study was to investigate whether N application could alleviate the negative effect of salinity (NaCl) stress on oat physiological parameters and yield performance. Two oat genotypes with contrasting salt tolerance response (6-SA120097, a salt-tolerant genotype SA and 153-ND121147, salt-sensitive ND) were grown under four N rates (0, 100, 200, and 400 mg N pot−1) in non-saline and saline (100 mM NaCl) conditions. The results showed that salinity, N fertilization and their interaction significantly affected the photosynthetic rate, transpiration rate, agronomic nitrogen use efficiency (aNUE), physiological nitrogen efficiency (pNUE) and apparent nitrogen recovery (ANR), seed number, and grain yield. Saline stress reduced gas exchange rate, nitrogen use efficiency (NUE), grain yield, and yield components. N fertilization increased photosynthetic productivity and chlorophyll fluorescence, resulting in improved grain yields and yield components for both genotypes. On average, the photosynthetic rate was increased by 38.7%, 74.1%, and 98.8% for SA and by 49.8%, 77.6%, and 110% for ND, respectively, under the N rates of 100, 200, and 400 mg N pot−1, as compared with non-fertilized treatment. In addition, grain yield was increased by 80.6% for genotype SA and 88.7% for genotype ND under higher N application rate (200 mg N pot−1) in comparison with the non-nitrogen treatment. Our experimental results showed that an increase of N supply can alleviate the negative effects induced by salinity stress and improved plant growth and yield by maintaining the integrity of the photosynthesis and chlorophyll fluorescence processes of oat plants, which provides a valuable agronomic strategy for improving oat production in salt-affected soils.
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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