Managing phosphorus for yield and quality of sweet corn grown on high phosphorus soils of Maryland's eastern shore
Bibliographic record
Abstract
Reducing P fertilization to address water quality problems has raised concerns among producers regarding crop yield and quality. A 3 yr study was conducted at three sites to examine whether reduction in P fertilization rate and/or use of a preceding rye cover crop affect the yield and quality (sugar concentration and ear weight) of sweet corn (Zea mays L.) grown on soils with “excessive” plant-available P. The experimental design was a split plot with four replications conducted on Norfolk soils. The main plots were no cover crop and a rye cover crop. The subplots were five P fertilizer treatments ranging from 0 to 60 kg P ha-1 at 15 kg P increments. With or without a preceding rye cover crop or P fertilization, postharvest soil test P (Mehlich-1) levels remained “excessive” to a depth of 40 cm. Also, yield of sweet corn was not affected by P fertilization and/or use of a preceding rye cover crop. Without cover cropping, sugar content and ear weight response to P fertilization was positive on site 2 for sugar, and on sites 2 and 3 for ear weight. Utilization of cover cropping positively influenced sweet corn sugar and ear weight sampled at early milk stage without affecting the final yield. In processing sweet corn production, profitability is determined mainly by the yield of marketable ears. Therefore, the small, inconsistent increases in sugar content and ear weight in response to P fertilization, without an increase in yield is not of a major significance to the farmer. On high P soils, P fertilization is unnecessary for the production of quality, high-yield processing corn. The use of a rye cover crop is suggested as a method of reducing the risk of P loss into the surrounding watershed. Key words: Sweet corn yield, sweet corn quality, P fertilization, rye cover crop, phosphorus management, high P soils
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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) | 0.000 | 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 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".