Root Distribution and N Acquisition in an Alfalfa and Corn Intercropping System
Bibliographic record
Abstract
Little attention has been paid to root distribution in combined perennial legume and annual cereal crops. The main objectives of this study were to explore the regularity of root distribution and the influence on nitrogen (N) acquisition in different alfalfa (Medicago sativa L.) and corn (Zea mays L.) intercropping patterns. A three year (2007–2009) field experiment studied four intercropping patterns of alternating alfalfa and corn rows with alfalfa:corn rows sown at 2:2, 3:2, 4:2, and 5:2. Sole crops of corn and alfalfa were used as controls. Roots were sampled over 3 consecutive years by auger sampling method in the prime filling stage of corn from different soil depth, and the root length density (RLD) was used to describe the root spatial distribution of intercropped alfalfa and corn. The results showed that the alfalfa/corn intercropping system had the greater RLD values compared to the sole cropped alfalfa or corn. In addition, the root mass centre of intercropped alfalfa descended into deeper soil layers with advancing stand age, and likewise proliferated laterally towards associated corn rows. Whereas the corn root mass spread at relative shallow soil profile, and also more deployed laterally to neighboring alfalfa root zone. The gap between alfalfa and corn rows was the highest colonized area with greater intermingling and the highest RLD of both species root. The complementary and compatibility of the root spatial distribution of component crops in alfalfa/corn community were the essential cause for better biomass yield.
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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".