Comparative Analysis of Nitrogen Responsiveness in Spikelet Photosynthetic Performance Between Yellow and Black Oat ( <i>Avena sativa</i> ) Lemmas
Bibliographic record
Abstract
Spikelets play a crucial role in photosynthesis during seed formation. This study used two oat (Avena sativa) varieties with significantly different lemma colors, "Challenger" from Canada and "Qinghai444" from China, as experimental materials. Phenotypic, physiological, proteomic, and transcriptional analyses were conducted on oat glumes, lemmas, and paleas after nitrogen application during the grain-filling stage. Results indicated that glumes outperformed lemmas in photosynthetic efficiency. After nitrogen application, "Challenger" glumes exhibited increased stomatal area but decreased chlorophyll a content, maximum photochemical efficiency of photosystem II (Fv/fm), and the quantum yield of photosystem II in steady state (ΦPSII). Concurrently, chloroplast membrane structure was repaired, and the expression of CAO, PsbR, and genes encoding chlorophyll protein complexes (LHCs) was upregulated, enhancing net photosynthetic rate (Pn) and photosynthetic capacity. Conversely, "Qinghai444" glumes showed decreased stomatal area but increased chlorophyll a content, Fv/fm, ΦPSII, and non-photochemical quenching (NPQ). The chloroplast structure of glumes was improved, whereas that of the lemmas was damaged. The CP47 subunit of photosystem II (PSII) accumulated on the thylakoid lamella, and the expression of petA, PsbB, and PsbR genes was upregulated, with no change in Pn or photosynthetic capacity. This study revealed that photosynthetic responses to nitrogen varied among oat varieties and spikelet tissues, with "Challenger" showing more pronounced enhancements. The findings of this study elucidate the patterns of photosynthetic responses to nitrogen in oat spikelets, guiding nitrogen fertilizer use and supporting the breeding of high-yielding oat varieties.
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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 | 0.000 |
| 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 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".