Long‐Term Manure Application and Forages Reduce Nitrogen Fertilizer Requirements of Silage Corn–Cereal Cropping Systems
Bibliographic record
Abstract
Assessment of the soil N supply capacity is essential to optimize fertilizer N use. We investigated soil N supply capacity and fertilizer N recovery for three cropping systems established in 1977: silage corn ( Zea mays L.)–cereal without (CC) and with 20 Mg ha −1 yr −1 manure (CCM), and silage corn–forage (3‐yr) with manure (CFM). During the present study (2005–2008), manure applications were suspended and a silage corn–silage corn–barley ( Hordeum vulgaris L.)–wheat ( Triticum aestivum L.) sequence was imposed to all systems. Fertilizer ( 15 NH 4 15 NO 3 , 3.1 atom % 15 N) was applied in 2005 to silage corn (160 kg N ha −1 ) and in 2007 to barley (80 kg N ha −1 ). The 15 N recovery in silage corn and barley ranged from 40 to 59%, with the lowest values measured in CFM. Compared to the CC systems (47 kg N ha −1 ) in 2005, soil‐derived N in silage corn was two times higher under CCM (98 kg N ha −1 ), and four times higher under CFM (208 kg N ha −1 ). These differences decreased over years, but were still noticeable at the end of the experiment. Twenty‐two to 58% of applied 15 N was recovered in the soil at harvest. More than 50% of this residual N was present in macroaggregates (>0.25 mm), whereas <20% was present in particulate organic matter (POM). Up to 75% of residual 15 N was lost during the winter period, and little residual N was transferred to the following crop. These findings indicate that soil macroaggregates may be a preferential sink for residual fertilizer N, but this N is not present in stable forms and is vulnerable to environmental loss.
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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".