Soil residual water and nutrients explain about 30% of the rotational effect in 4-year pulse-intensified rotation systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Diverse crop rotations enable the best use of residual soil water and nutrients, thus decreasing necessary production inputs. Here, we determined the effect of cropping sequences on soil residual water and nutrients and the performance of subsequent wheat (Triticum aestivum L.). Nine rotation systems were evaluated at Swift Current, SK, and Brooks, AB, from 2010 to 2014. Pea (P, Pisum sativum L.) and lentil (L, Lens culinaris Medik.) as preceding crops before wheat (W) or the rotation systems with pea (P–P–P–W) or lentil (L–L–L–W) included more than once in the 4-yr rotations had the highest residual soil water and N in the 30–90 cm depth and continuous wheat (W–W–W–W) had the lowest. Preceding pea and lentil increased the grain yield of the subsequent wheat by 26% and 18%, respectively, as compared with continuous wheat. Variance partitioning of redundancy analysis revealed that soil residual water and residual N explained 12.4%–42.7% (average 30%) of the yield variation observed in the subsequent wheat, with the rest of the rotational benefits unexplainable by soil residual water and residual nutrients. Investigation of the factors other than soil water and nutrients that contribute to the succeeding wheat yield may further enhance the rotational effect.
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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 | 0.002 | 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 | 0.001 | 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 it