Effect of Farming Systems on the Spatial Variability of Soil Physical Properties and Soybean Yield
Bibliographic record
Abstract
In no-tillage (NT) and minimum tillage (MT) areas, spatial variability of soil physical properties may affect crop yield. The aim of this study was to assess the spatial distribution of soil physical properties, as well as the yield components and grain yield of soybean (GY), based on the mapping of areas under soil conservation farming systems. We assessed yield components, GY and the physical properties of an Oxisol, under NT and MT using the t-student test, and geostatistics to assess spatial variability. The largest population of NT plants showed no spatial dependence and did not influence GY, but the components related to plant height and soil properties differed between systems. From a spatial standpoint, the kriging maps demonstrated that mass of one thousand grains (MOG), total porosity (TP) and soil bulk density (BD) influenced GY under NT, whereas TP1 exerted the most influence under high soil moisture conditions and MT. The maps make it possible to assess the spatial distribution of soil physical properties and the influence on GY, making them an important tool for more accurate production planning in soil conservation systems.
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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 | 0.001 | 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".