Organic Amendment History and Crop Rotation Effects on Soil Nitrogen Mineralization Potential and Soil Nitrogen Supply in a Potato Cropping System
Bibliographic record
Abstract
Crop management practices influence readily and potentially available N in soil. In this study, we evaluated the effects of organic amendment history and crop rotation on potentially mineralizable N (N 0 ), mineralizable N pools, and field estimates of soil N supply in potato ( Solanum tuberosum L.) production, and evaluated a suite of N availability measures to detect changes in these parameters. Preplant soil samples (top 15‐cm) were collected from the potato year of a rotation trial in Maine during 2004 and 2005. Treatments included three crop rotations, with and without a history of organic amendment [solid beef ( Bos taurus ) manure] application: PB, potato‐barley ( Hordeum vulgare L.); PSPB, potato‐soybean [ Glycine max (L.) Merr.]‐potato‐barley; and PSBA/T, potato‐soybean‐barley‐alfalfa ( Medicago sativa L.)/timothy ( Phleum pratense L.). The N 0 and mineralizable N pools were determined by aerobic incubation at 25°C and periodic leaching for 24 wk with a fixed‐ k approach. On average, historically amended soil had 35% higher values of N 0 , and an 8% higher proportion of mineralizable N partitioned to the stable mineralizable N pool, compared with nonamended soil. Lower values of N 0 , mineralizable N pools and some measures of N availability were measured in PSBA/T compared with PB and PSPB rotations. All tested measures of N availability detected management‐induced changes in N 0 and mineralizable N pools. The preplant nitrate, UV absorbance of 0.01 M NaHCO 3 extract at 205 nm and particulate organic matter (POM)‐N were the best predictors of field‐based indices of soil N supply ( r 2 = 0.50 to 0.73). Management‐induced changes in the size and quality of mineralizable N should be considered in developing best N management programs through organic amendment application and crop rotations.
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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".