Impacts of Zone Tillage and Red Clover on Corn Performance and Soil Physical Quality
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
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.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it