Impacts of Zone Tillage and Red Clover on Corn Performance and Soil Physical Quality
Bibliographic record
Abstract
Despite extensive research, reduced corn ( Zea mays L.) performance is still encountered using conservation tillage on fine‐textured soils in cool humid temperate climates. These problems are intensified when corn is planted into residue from a previous crop such as winter wheat ( Triticum aestivum L.). The objective of this 4‐yr study was to determine the influence of fall zone tillage (ZT), no tillage (NT), and conventional moldboard plow tillage (CT) (fall plowing) on corn performance and soil physical quality under a winter wheat–corn–soybean ( Glycine max L. Merr.) rotation with and without red clover ( Trifolium pratense L.) (RC) underseeded in the wheat phase of the rotation. A randomized complete block design (3 × 2 factorial, 4 replicates) was established on three adjacent fields in the fall of 1996 on a Brookston clay loam soil (fine loamy, mixed, mesic, Typic Argiaquoll) at Woodslee, ON Canada, and measurements were collected during 1997 to 2000. Over both wet and dry growing seasons from 1998‐2000, zone tillage following underseeded RC produced average corn grain yields (7.23 Mg ha −1 ) that were within 1% of those obtained using conventional tillage (7.33 Mg ha −1 ), and 36% higher than those obtained using no tillage and RC (5.33 Mg ha −1 ). Zone tillage also improved soil quality as evidenced by generally lower soil strength than no tillage, and near‐surface soil physical quality parameters that were equivalent to, or more favorable than, those of the other treatments. It was concluded that corn production using zone tillage and RC underseeding is a viable option in Brookston clay loam soil, as it retains much of the soil quality benefit of conventional tillage but still achieves most of the yield benefit of conventional moldboard plow tillage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".