Effects of Fertilizers and Soil Amendments on Soil Physicochemical Properties and Carbon Sequestration of Oat (Avena sativa L.) Planted in Saline–Alkaline Land
Bibliographic record
Abstract
The coastal tidal flat area of Jiangsu Province, China, is vast and has great potential for carbon sequestration. Planting oat in saline–alkaline land can increase carbon sequestration from the atmosphere into soil and, thus, improve soil quality. Harvesting oats can act as a biological desalination mechanism, and long-term planting may transform saline–alkaline land into high-quality arable land. Our experiment selected two oat varieties, Caesar (V1) and Menglong (V2), and used urea, organic fertilizer, microbial inoculant, and biochar as experimental factors to investigate the effects of fertilizers and soil amendments on soil improvement and carbon sequestration when cultivating oats. The results showed that when planting V1, the carbon sequestration of the farmland ecosystem was the highest with microbial inoculant and organic fertilizer treatments, and the soil salinity decreased the most with biochar treatment. When planting V2, the carbon sequestration of the farmland ecosystem was the highest with the urea + biochar treatment, the soil salinity decreased the most with organic fertilizer + microbial inoculant treatment, and the soil organic carbon content increased the most with organic fertilizer + biochar treatment. We found that the application of organic fertilizer and biochar significantly increased soil organic carbon (SOC) content by 22.03% compared to the control treatment. Additionally, the combined treatment of urea and biochar resulted in the highest agricultural carbon sink, with a 74.62% increase in oat carbon storage compared to conventional fertilization.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".