Ecological impacts of the N-viro biosolids land-application for wild blueberry ( <i>Vaccinium angustifolium.</i> Ait) production in Nova Scotia
Bibliographic record
Abstract
Land application of biosolids from processed sewage sludge may deteriorate soil, water, and plants. We investigated the impact of the N-Viro biosolids land-application on the quality of the soil water that moved through Orthic Humo-Ferric Podzols soil of Nova Scotia (NS) at the Wild Blueberry Research Institute, Debert, NS Canada. In addition, the response of major soilproperties and crop yield was also studied. Wild blueberry (Vaccinium angustifolium. Ait) was grown under irrigated and rainfed conditions in 2008 and 2009. Four experimental treatments including (i) NI: N-Viro irrigated, (ii) NR: N-Viro rainfed, (iii) FI: inorganic fertilizer irrigated, and (iv) FR: inorganic fertilizer rainfed (control) were replicated 4 times under randomized complete block design. Soil samples were collected at the end of each year and analyzed for changes in cation exchange capacity (CEC), soil organic matter (SOM), and pH.Soil water samples were collected four times during the study period from the suction cup lysimeters installed within and below crop root zone at 20 and 40 cm depths, respectively. The samples were analyzed for a range of water quality parameters including conductance, hardness, pH, macro- and micronutrients, and the infectious pathogens Escherichia coli (E. coli) and salmonella. Berries were harvested for fruit yield estimates. Irrigation significantly increased CEC during 2008 and the soil pH decreased from 4.93 (2008) to 4.79 (2009). There were significant influences of irrigation, fertilizer, and their interaction, in some cases, on most of the soil water quality parameters except on the infectious bacteria. No presence of E. coli or salmonella were observed in soil and water samples, reflecting the absence of these bacteria in biosolids used in this experiment. Nutrient concentration in the soil water samples collected from the four treatments were higher in the sequence NI > NR > FI > FR. The irrigation treatment had significant effect on the unripe fruit yield. We conclude that the comparable performance of N-Viro biosolids and the increasing prices of inorganic fertilizers would compel farmers to use economically available N-Viro biosolids that, coupled with the supplemental irrigation, did not deteriorate the studied soil properties, soil water quality, and the wild blueberry yield during this experiment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".