Effect of Conservational and Conventional Tillage Systems on Functional Soil Archaea Diversity in Wheat-Pea Rotation Field
Bibliographic record
Abstract
Soil borne archaea in agricultural systems is crucial for cycling of nutrient such as Nitrogen, Carbon and Sulphur. The objective of the study was to assess the effect of different tillage systems on functional archaea diversity in a 15 years cereal-legume rotation field using Illumina sequencing platform for archaea 16S rRNA gene. The treatments in the study included conventional tillage with stubble removed (T), no-till with stubble removed (NT), conventional tillage with stubble incorporated (TS) and no-till with stubble retained (NTS). The results showed that the dominant soil archaea phyla was Crenarchaeota (> 96%), followed by Euryarchaeota with a lower abundance of < 3% and then Parvarchaeota and other bacteria phyla made up < 1% across the treatments and depths. The treatment means were ranked as NT > NTS > TS > T for 16S rRNA number of OTUs, Shannon and Simpson indices calculated for the 0-10cm soil depth. Analysis of factor effect revealed that tillage but not stubble retention or their interaction significantly influenced (P < 0.01 and P < 0.05) 16S rRNA diversity. Non metric Multidimensional Scaling (NMDS) analysis clearly grouped the microbial communities according to depths. Linear Discriminant Analysis Effect Size (LEfSe) identified Crenarchaeota and Thaumarchaeota (to genus level) as significantly enriched clades in 0-10 cm depth of T while Euryarchaeota and Thermoplasmata were significantly enriched in TS. The conservational tillage systems (NT and NTS) promoted even distribution of archaea diversity while conventional tillage systems (T and TS) enriched the archaea communities identified in the study.
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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".