Contents of labile carbon and nitrogen under different soil management practices in a vineyard in an extremely humid year
Bibliographic record
Abstract
Received: 2016-09-06 | Accepted: 2016-10-19 | Available online: 2017-03-31 http://dx.doi.org/10.15414/afz.2017.20.01.16-19 In a productive vineyard, the influence of different soil management practices on labile carbon and nitrogen and its dynamics of Rendzin Leptosol was studied. In 2006, an experiment of the different management practices in a productive vineyard was established in the locality of Nitra-Dražovce (part of the Nitra City), which is in the Nitra wine-growing area (Slovakia). The following treatments were established: 1. control Co (grass without fertilizers application), 2. T (tillage), 3. T + FM (tillage + farmyard manure), 4. G + NPK3 (grass + NPK 120-55-19 kg ha -1 ), 5. G + NPK1 (grass + NPK 80-35-135 kg ha -1 ). Soil samples were collected every month (0-20 cm), during the year 2010. The results showed that labile carbon content (C L ) fluctuated from 1820 to 2673 mg kg -1 and the soil management practices had a statistically significant influence on C L . The C L contents under T, T + FYM, G + NPK1 and G + NPK3 increased by 6  %, 11  %, 5  % and 13  %, respectively compared to Co treatment. During 2010, the dynamics of C L found no trend in all treatments. The highest N pot content was in Co treatment (90 mg kg -1 ) than in other soil management practices in a vineyard. On average, there was a smaller higher value of N pot in T + FM (78 mg kg -1 ) than in G + NPK3 (77 mg kg -1 ). During 2010, the dynamics of N pot found no trend in all treatments, except Co treatment. In Co, the N pot decline at an average speed of 4.18 mg kg -1 year -1 . The C L : N pot ratios were different and their values were significant correlated only with N pot (r = -0.854, P < 0.001). During 2010, the dynamics of C L : N pot ratio showed an increasing trend with time in Co treatment. Keywords: labile carbon, Rendzin Leptosol, potentially mineralizable nitrogen, vineyards, fertilizers application References Blair, G.J. et al. 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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".