Impact of inoculation of the sap collection system with three <i>Pseudomonadota</i> strains on maple syrup microbial and organoleptic quality
Bibliographic record
Abstract
As it flows through the collection system, maple sap is likely to be contaminated by microorganisms that colonize the tubing, potentially compromising its quality in terms of physicochemical properties, microbial load, and flavor. This study investigates the effect of microbial inoculation, as protective cultures, on the sap collection system to improve maple syrup quality. The research explored how inoculating collection tubing with specific bacterial strains influences the microbial composition, physicochemical properties (pH, Brix, conductivity, sugars, and organic acids content), and sensory attributes of both maple sap and syrup. Three strains selected for their capacity to produce biofilm on plastic tubing and their impact on maple syrup production from inoculated sap, Pseudomonas sp. MSB2019, Janthinobacterium lividum 100-P12-9, and Pseudomonas fluorescens ATCC 17926, were inoculated to independent sap collection system throughout two sugaring seasons. A non-inoculated system was included. Pseudomonas sp. MSB2019 treatment resulted in a distinct bacterial composition in sap and impact the organoleptic properties of syrup by the end of second flow season, particularly the maple and overall flavor intensity scores were higher. While sap yield and primary microbial load remained unaffected, inoculation treatments corresponded to shifts in flavor attributes of the syrup. These findings indicate that inoculating sap collection systems with targeted strains can positively influence maple syrup quality, particularly in enhancing desirable flavor profiles, suggesting promising applications for syrup production.
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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 | 0.000 | 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 | 0.001 |
| 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".