Balanced Nutrition and Crop Production Practices for Closing Sorghum Yield Gaps
Bibliographic record
Abstract
In order to study how diverse cropping system approaches influence grain sorghum productivity, field experiments were conducted in Topeka, KS at the Kansas River Valley Experiment Field; and in Ottawa, KS at the East Central Kansas Experiment Field. The primary objective of this study was to understand how to close yield gaps between the current on-farm yields and the maximum attainable yields. The factors that were tested include narrow row spacing; high and low plant population; balanced nutrition practices, including various timings of nitrogen, phosphorus, and potassium (N-P-K); micronutrient applications of iron and zinc (Fe and Zn); crop protection with fungicide and insecticide applications; plant growth regulator effects; and the use of precision agricultural technology for maximizing yields, including a GreenSeeker meter (Trimble Navigation, Westminster, CO) for more precisely determining N needs for sorghum. Grain sorghum yields ranged from 149 to 166 bu/a in Topeka, KS under irrigation, and from 78 to 100 bu/a in Ottawa, KS, under dryland conditions. At Ottawa, yield potential was limited by precipitation, 10.8 inch. Still, sorghum yield gap between the highest (treatment #2, “kitchen sink” but with low seeding rate) and lowest (treatment #10, “standard practice”) was 22 bushels per acre. The production practices that produced the highest yields varied between the two locations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".