Poultry manure effects on soil nitrogen processes and nitrogen accumulation in red raspberry
Bibliographic record
Abstract
This study examined the effects of solid poultry layer manure addition on soil N processes and on dry matter and N accumulation in red raspberry (Rubus idaeus L.). In trials conducted in two years, approximately 50% of the 400 kg total N ha −1 applied as manure was recovered as soil inorganic N 1 mo after manure application when manure was incorporated within 4 h of application. Three trials were conducted in two commercial raspberry fields: one with no history of manure use and one other with a history of heavy annual applications of poultry manure. Treatments included 55 kg N ha −1 as NH 4 NO 3 , 100 or 200 kg total N ha −1 as manure, and a control that received no manure or fertilizer N. Soil inorganic N to 60 cm depth was measured throughout the growing season. Berry yield was estimated, and dry matter and N accumulation was determined in floricanes at first berry ripening and in primocanes at the end of the growing season. Few significant effects of N fertilization were measured for any crop yield, growth or N accumulation parameter. This was attributed to the large (>150 kg N ha −1 ) supply of N to the crop in the unamended soil, primarily from soil N mineralization. Dry matter accumulation in the fruiting clusters was strongly correlated to estimated berry yield, and may provide a simple means for assessing relative yield within experiments. Soil nitrate measured in August after berry harvest may serve as a "report card" to assess N management in the current growing season, to refine fertilizer N management for subsequent growing seasons, and as an index of the risk of nitrate leaching over the following fall and winter in south coastal British Columbia. Key words: Nitrogen mineralization, nitrate leaching, manure N availability, Rubus idaeus
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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 | 0.001 |
| 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".