Black spruce extracts reveal antimicrobial and sprout suppressive potentials to prevent potato (Solanum tuberosum L.) losses during storage
Bibliographic record
Abstract
Canadian forest residues, such as bark, are an abundant and accessible biomass currently burned to produce energy, therefore neglecting their great potential for various applications owing to their multiple biological properties. Potato storage constitutes a challenge for potato producers because of disease propagation and potato sprouting. Barks appear to be promising candidates in the research of greener alternatives to synthetic chemicals presently used to limit these problems. Hence, this study aimed to develop a bio-based ingredient from bark residues to prevent diseases and sprouting of potatoes during storage. First, forest extracts were produced from the bark of black spruce (Picea mariana Mill.), balsam fir (Abies balsamea L. Mill.) and yellow birch (Betula alleghaniensis Britton) by three different methods: water extraction, ethyl acetate fractionation of the water extract, and acid-base extraction. Then, in vitro screening of extracts and commercial essential oils was performed to determine their ability to inhibit potato soft and dry rot and potato sprouting. More specifically, Fusarium oxysporum, Fusarium graminearum, Fusarium sambucinum, Pectobacterium atrosepticum, Pectobacterium carotovorum, and Dickeya dianthicola were selected for antimicrobial assays. Two black spruce extracts, ethyl acetate extract and essential oil, showed promising antimicrobial and anti-sprouting properties. The black spruce ethyl acetate extract inhibited microorganism growth with minimum concentrations ranging from 1.37 × 10–3 to 3.00% (w/w) depending on the strain. Black spruce essential oil completely prevented potato sprouting in Colomba cv. at a minimal concentration of 25% (w/w). Furthermore, when mixed, both properties were maintained, and even showed a synergistic effect. Indeed, in antimicrobial assays, the fractional inhibitory concentration index obtained was lower than 0.50. Therefore, these two black spruce extracts can be formulated into one product with broad properties aimed at controlling potato post-harvest losses due to rot and sprouting.
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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) | 0.001 | 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".