Influence of pulse–wheat crop rotations on aggregate size distribution dynamics in the brown soil zone in southern Alberta, Canada
Bibliographic record
Abstract
Diversification of conventional cereal-based cropping systems with pulse crops may aid producers to grow crops in an appropriate sequence and frequency with environmental, social, and economic benefits. This study examined the effects of including three pulse crops with different rooting depths (shallow- and deep-rooted) in wheat-based crop rotations on soil aggregate size distribution under semi-arid and rain-fed conditions. A 4 year cycle rotational study was established in Brooks, AB, using five selected treatments: continuous wheat, wheat alternately grown with lentil, field pea, or chickpea, or lentil and chickpea alternately grown with wheat. Soils were collected from 0–5 cm depth and dry-sieved to produce eight aggregate size classes, <0.053, 0.053–0.125, 0.125–0.149, 0.149–0.05, 0.05–1.0, 1.0–2.0, 2.0–6.35, and >6.35 mm. The continuous wheat treatment improved the macro-aggregates (>6.35 mm) development, whereas the rotations with pulse–wheat crops increased the micro- and meso-aggregates (0.50–1.0 and 0.15–0.5 mm) development. Soils sampled at 0–15 cm depth were used for soil organic matter and microbial analysis. The pulse–wheat rotations collectively had more light fraction organic matter (LFOM) than the continuous wheat, and chickpea alternated with wheat had the highest amount of LFOM in both years. All treatments had similar soil microbial biomass and microbial community composition. Our study underscores the contribution of pulse crops in cereal-based cropping systems in the formation of small aggregates.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".