Improvement of soil properties and fruit yield of native lowbush blueberry by papermill sludge addition
Bibliographic record
Abstract
Combined primary and secondary papermill sludge (PS) is a good potential source of C and other nutrients to restore low organic matter sandy soils supporting native lowbush blueberry (Vaccinium angustifolium Ait.). A 3-yr field study was conducted to compare the effect of PS with mineral fertilizers (MF) on the blueberry yield and soil chemical properties and enzyme activities of a l’Afrique sand (Humo-Ferric Podzol) in the Saguenay-Lac Saint-Jean area (Quebec, Canada). The PS was applied in the spring of the sprout year at 0, 8.5, 17 and 34 Mg ha -1 and MF was applied at 0, 13, 26 and 52 kg N ha -1 . The highest fresh fruit yields were obtained at 8.5 and 17 Mg PS ha -1 . The 34 Mg PS ha -1 treatment produced berry yield comparable to the control. This PS rate reduced pH, but increased inorganic N, Mehlich-3 extractable P and Mn in the 0- to 15-cm soil layer. The NO 3 − -N content of the 15- to 30-cm and 30- to 60-cm soil layers was also increased by PS, suggesting leaching. The MF significantly affected soil inorganic N content only at 3 wk after its application in the first year. The PS rate linearly increased the soil acid phosphatase activity in the first year. The arylsulfatase activity was also higher in PS than in MF treatment, but was severely depressed by 34 Mg PS ha -1 in the last 2 yr. This study indicated that PS, when used at low rates, improves lowbush blueberry yield and the soil enzyme activity on this low fertility sand. Key words: Papermill sludge, lowbush blueberry, soil composition, soil enzyme
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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".