Evaluation of Planter Errors Associated with Twin‐Row Soybean Production in Mississippi
Bibliographic record
Abstract
Core Ideas The number of planter errors is associated with twin‐row planters. Whole planter error reduced soybean yield compared with None on both soil textures. Single and separate planter error did not reduce yield. Replanting a soybean crop for any planter error is not economically beneficial. Twin‐row planting of soybean [ Glycine max (L.) Merr.] has become a popular practice in Mississippi and in much of the midsouthern United States. With the use of twin‐row planters, there is the potential for a number of planter errors. However, there is little information on the effect of twin‐row planter errors on soybean growth, seed yield, and replant decisions. Field experiments were conducted in 2016 and 2017 in Mississippi to evaluate the effects of planter errors for four soybean varieties of different relative maturity groups (4.2, 4.7, 4.9, and 5.4) on soybean seed yield, canopy closure, and replant decisions for two soil textures (clay and sandy loam) commonly used for soybean production in Mississippi. Four planter errors associated with the twin‐row planting system included a control (None) consisting of the full intended stand with two normal twin rows within a bed, one single row from a twin‐row pair missing (Single), one row of a twin row pair missing in two adjacent rows (Separate), and both twin rows within a row missing (Whole). Whole planter error reduced soybean yield compared with None by 11 and 12% on clay and sandy loam soils, respectively. However, Single and Separate planter error did not reduce yield compared with None. Results indicate that it would not be economically beneficial to replant a soybean crop for any planter error at current soybean prices.
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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".