The Impact of Wheat Growth Stages on Soil Microbial Communities in a Rain-Fed Agroecosystem
Bibliographic record
Abstract
Wheat is the largest terrestrial agricultural crop globally. This study was conducted to determine the soil microbial biomass, soil CO2 evolution, and physiological profile in the rhizosphere of the winter wheat rain-fed Triticum aestivum along the development stages in a rain-fed semi-arid agro-ecosystem. The data show that a significant, over 100-fold increase in the utilization of four substrate groups (benzoic acid, amino acid, carbohydrates, and carboxylic acid) occurred in the wheat soil rhizosphere along the wheat growth phenology. After the stubble field stage, there was a notable decrease in the utilization of all four substrates. The occurrence of each substrate in the soil aligns with the below-ground rhythm of wheat plant biomass growth. The abundance of fine roots, categorizing wheat plant roots, in the soil at maturity and the stubble field stage may explain the heightened activity and diversity of copiotroph bacteria. This association suggests a potential link between the richness of fine roots and the increased activity and diversity of copiotroph bacteria in the soil. The findings clarify the impact of constraining abiotic factors, coupled with the phenological influences of wheat plants, and their combined effects on substrate utilization by microbial communities in a rain-fed Triticum aestivum wheat field.
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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".