Effect of biochar amended with beneficial microbes on establishment and growth of cranberry («Vaccinium macrocarpon L.») cuttings under controlled conditions
Bibliographic record
Abstract
Sustainable production of cranberry (Vaccinium macrocarpon) in Quebec fields requires the adoption of best management practices. A promising approach is the application of biochar combined with beneficial microbes as soil amendment, leading to a faster establishment of cranberry fields and reduced use of agrichemicals. This study was undertaken in order to determine whether the application of maple bark biochar amended with selected plant growth promoting rhizobacteria (PGPR) would stimulate vegetative growth of “Stevens” cranberry cuttings under controlled growth bed conditions and also to evaluate biochar effect on microbial populations present in the potting mix. Biochar was added at 1% (w/w) and used directly or mixed with three selected bacterial strains known to stimulate plant growth compared to treatments in which biochar was not added. Shoot and root dry weights increased upon the addition of 1% biochar and beneficial microbes at both harvesting dates compared to those in potting mix fortified with full dose of Actisol®. Under lower dose of Actisol®, biochar and bacteria amendment significantly increased root dry weight at 120 days after transplanting. Depending on the date of harvesting, the addition of 1% biochar and beneficial microbes significantly (P < 0.05) increased the total abundance of microbes present in the rhizosphere and bulk soil of cranberry cuttings. In particular, there was an increase in the abundance numbers of fungal and Actinomycets phyla in bulk soil. Quantitative-PCR assays using species-specific primers showed that DNA copy numbers of PGPR and ericoid mycorrhiza in soil and in roots of cranberry cuttings varied with date of harvesting and with the type of biological sample tested. Under the above conditions, our results indicate that the application of maple bark biochar yielded variable results and may not be the best-suited type of biochar for cranberry production in conjunction with selected beneficial microbes
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".