Unveiling the Diversity and Virulence of Seedborne <i>Fusarium</i> Species in Lentil Production: Insights from a Two-Year Study in the Northern Great Plains
Bibliographic record
Abstract
Fusarium root rot/wilt caused by various Fusarium spp. significantly threatens lentil ( Lens culinaris Medikus) production in the Northern Great Plains (NGP) region. However, the specific composition of seedborne Fusarium spp. causing this disease is not well understood. To address this gap, we conducted a comprehensive study spanning 2019 and 2020, collecting lentil seeds from 75 commercial fields across Montana, North Dakota, Washington, Idaho, and Ontario. Our analysis focused on both externalized and internalized pathogens, with particular attention to Fusarium spp., employing morphological and molecular techniques for identification. In total, 486 and 228 Fusarium isolates were recovered in 2019 and 2020, respectively. Predominant species included F. equiseti, F. acuminatum, F. oxysporum, F. tricinctum, F. graminearum, F. proliferatum, F. redolens, F. avenaceum, and F. sporotrichioides. Virulence studies conducted in the greenhouse revealed varying levels of aggressiveness among Fusarium spp., with F. sporotrichioides, F. oxysporum, and F. graminearum demonstrating the highest virulence. Further investigation into pathogen internalization within seed lots revealed that incidence was highest in the seed coat, followed by the cotyledon, with the lowest occurrence in the embryo. F. avenaceum was prevalently isolated from the seed coat, cotyledon, and embryo. Additionally, Fusarium spp. isolated from the seed coat and cotyledon exhibited higher virulence and greater diversity compared with those from the embryo. This study reports the first comprehensive assessment of both externalized and internalized seedborne Fusarium spp. in the NGP region. The insights gained from our findings will inform the development of targeted management strategies for Fusarium root rot/wilt, ultimately aiding in the preservation of lentil crop health and productivity in the NGP and beyond.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".