Stationary soil steaming to combat invasive plant species for soil relocation
Bibliographic record
Abstract
Abstract Eradication of alien invasive species in the soil with steam as an alternative to chemical fumigation may allow contaminated soil to be reused. We have investigated steam disinfestation of soil to combat invasive plant species in three experiments including different temperatures and exposure durations using a prototype stationary soil-steaming device. The experiments included effects on seed germination of bigleaf lupine ( Lupinus polyphyllus Lindl.), ornamental jewelweed ( Impatiens glandulifera Royle), and wild oat ( Avena fatua L.; one population from Poland and one from Norway), as well as effects on sprouting rhizome fragments of Canada goldenrod ( Solidago canadensis L.) and Bohemian knotweed ( Reynoutria x bohemica Chrtek & Chrtková). In Experiment 1, we tested four different soil temperatures of 64, 75, 79, and 98 C with an exposure duration of 90 s. In Experiments 2 and 3, we tested exposure durations of 30, 90, and 180 s and 90, 180, and 540 s, respectively, at 98 C. Seed pretreatment of 14 d cooling for L. polyphyllus and I. glandulifera , no seed pretreatment and 12-h moistening for A. fatua populations, and 5- and 10-cm cutting size for R . x bohemica were applied. Our results showed germination/sprouting was inhibited at 75 C for I . glandulifera (for 90 s) and 98 C for the other species; however, longer exposure duration was needed for L . polyphyllus . While 30 s at 98 C was enough to kill A . fatua seeds and S . canadensis and R . x bohemica rhizome fragments, 180-s exposure duration was needed to kill L . polyphyllus seeds. The results showed promising control levels of invasive plant propagules in contaminated soil by steaming, supporting the steam treatment method as a potential way of disinfecting soil to prevent dispersal of invasive species.
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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".