Corn and soybean root traits improved by preceding perennial forage crops
Bibliographic record
Abstract
Abstract Background and aims Benefits for soil health associated with crop rotations can improve plant aboveground biomass, although the effect on root traits is unclear. The aim of this study was to measure the legacy effect of crop rotations typical of dairy farms on root traits of subsequent forage corn ( Zea mays L.) and soybean ( Glycine max [L.] Merr.). Methods On a silty clay in eastern Canada, six rotations were compared, varying in crop species (perennials and/or annuals) and fertilizer sources (dairy cattle slurry and/or mineral fertilizer) for 5 years. Roots of subsequent corn and soybean were sampled by coring (0–45 cm), washed, and digitized for image analysis. Results Crop rotations including perennial crops rather than only annual crops resulted in greater total net annual productivity in corn (+ 20%) and soybean (+ 21%), corn root biomass (+ 31%) and length density (+ 106%), and proportion of fine roots. Compared to the alfalfa-grass mixture, grass-only mixtures resulted in a greater corn root biomass (+ 23%) and length density (+ 54%). A longer duration (5 vs. 3 years) of the alfalfa-grass mixture improved corn root length density (+ 37%) and corn and soybean fine root proportion at depth, suggesting benefits from maintaining perennial forage stands over time. Mineral fertilizer versus slurry improved root traits of subsequent corn and soybean when applied to perennial but not annual crops. Conclusion Our results highlight the positive response of corn and soybean root traits to the presence, species composition, and duration of perennial forage crops, extending further their benefits within rotations.
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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".