Nitrogen Management of Brown Midrib Sorghum × Sudangrass in the Northeastern USA
Bibliographic record
Abstract
Brown midrib (BMR) forage sorghum [ Sorghum bicolor (L.) Moench.] × sudangrass ( Sorghum sudanense Piper) hybrids (S × S) have been considered as a possible forage alternative to maize silage ( Zea mays L.) where maize planting is delayed due to wet soil conditions. Our objective was to determine the most economic rate of nitrogen (MERN) for BMR S × S grown in a two‐cut management system with a split application of N. Six field trials were conducted in New York in 2003 and 2004. One trial followed a grass–legume sod; a second trial had received liquid manure 19 mo before S × S planting. The remaining four followed S × S, silage maize, and/or a small grain crop. The MERN ranged from 137 to 192 kg N ha −1 cut −1 with dry matter (DM) yield ranging from 7.8 to 9.7 Mg ha −1 at the sites without additional N input. At the sites with prior N inputs, yield was higher (10.4–13.8 Mg ha −1 ) and MERN lower. The apparent nitrogen recovery (ANR) at the MERN was highest (61–73%) for the sites with prior N inputs. Nitrogen application rates > 145 kg N ha −1 cut −1 decreased nitrogen use efficiency (NUE) to <15 kg DM kg −1 N, while the ANR became <45%. We concluded that the MERN for BMR S × S grown in New York in a two‐cut system following maize, small grains, or forage S × S is 125 to 145 kg N ha −1 cut −1 . For sites that follow sod plow‐down or recent manure application, N application rates should not exceed 40 to 60 kg N ha −1 cut −1
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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 | 0.000 | 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 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".