Identification of phosphate solubilizing bacteria and evaluation of their application with insoluble phosphorus fertilizers to soils from certified organic orchards affected by replant disease
Bibliographic record
Abstract
Replant disease (RD) affects the growth and establishment of young fruit trees in old orchard soils. Organic management strategies are needed as an alternative to chemical controls. Improved phosphorus (P) nutrition to stimulate root growth and improve tree establishment is a well-established strategy; however, only insoluble Rock Phosphate (RP) and Bone Meal (BM) inputs are available to Canadian organic growers. The ability of specific plant growth promoting rhizobacteria to solubilize phosphate may improve P availability and its uptake in young apple trees, replanted into inoculated orchards. In this study, 101 bacteria isolated from the roots of legumes from Saskatchewan soils were screened for P solubilization. Thirty-four of these bacteria were positive for P solubilization as measured by halo diameter production on calcium phosphate medium. Twelve isolates showing the largest halo diameters and three known P solubilizing bacteria (PSB) were compared on three media: calcium phosphate, Pikovskaya (PVK) and PVK with bromophenol blue. All twelve isolates previously identified as Pseudomonas, Rhanella, Serratia and Klebsiella spp. solubilized P on all media, although the halo diameters varied among media. The isolates were tested in liquid culture, where a marked decrease in the pH of the solution was observed and six isolates were identified for further testing in growth pouch assays in the presence of insoluble P. The root growth of apple seedlings inoculated with one of the six bacterial isolates, showed significant increases in total root length, surface area and the number of root tips compared to the control after four weeks of incubation. Three isolates were selected for greenhouse bioassays using five RD-affected soils collected from organic orchards. These isolates were inoculated onto apple trees, alone or in combination with RP or BM. Two field trials were simultaneously conducted in organic apple orchards, using iii the same treatments; however there were no significant effects of the isolate treatments in either set of experiments. Although the strongest P solubilizers did not enhance tree growth in the greenhouse and orchard trials, the in vitro work showed the potential of PSB as a tool to mitigate the impact of RD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".