Characteristics of Selected Silphium Species as Alternative Plants for Cultivation and Industry with Particular Emphasis on Research Conducted in Poland: A Review
Bibliographic record
Abstract
This article reviews the available research results of selected species of the genus Silphium L. (Asteraceae) as alternative plants for crops and industry. Silphium species have valuable qualities across a wide range of uses, which is very important in considering plant resources as a green alternative to a sustainable future. Species of the genus Silphium are tall perennials found in fields, prairies, open forests, and groves in the central and eastern parts of the United States and Canada. Various tribes of Native North American used Silphium for medicinal purposes. The cup plant Silphium perfoliatum L. is the most popular species of the genus Silphium due to its attractive ornamental, honey–giving, healing, and forage qualities. As the literature review shows, species of the genus Silphium are characterized by a high production potential in terms of yields and contain significant amounts of nutrients, i.e., carbohydrates, proteins, and L-ascorbic acid, as well as minerals and biologically active substances, e.g., terpenoids and essential oils, flavonoids, phenolic acids, and oleanosides. In addition, the research confirmed the possibility of using Silphium for fodder, as honeybee forage, phytoremediation plants, for reclamation of degraded land, as plants for energy purposes (biomass, biogas), and as plants that provide components with antimicrobial activity. This review largely takes into account many years of research experience conducted in Poland.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".