Pathogenicity and Genetic Diversity of Fusarium oxysporum Causing Soybean Root Rot in Northeast China
Bibliographic record
Abstract
Soybean is an important edible legume cultivated around the world. However, soybean production is seriously impacted by the widespread of root rot disease. In this study, genetic diversity and pathogenicity of Fusarium oxysporum associated with root rot of soybean in Heilongjiang province, China, were examined. A total of 50 F. oxysporum strains were isolated from diseased soybean plants grown in Harbin, Heihe, Jixi, Jiamusi and Qiqihar of Heilongjiang province. Pathogenicity study indicated that all F. oxysporum strains were able to induce root rot disease on soybean in which 28% of the isolates were highly aggressive, 42% were moderately aggressive, and 30% were weakly aggressive. Aggressiveness of the isolates did not appear to be associated with geographic location or plant age of isolation. Genomic DNA of the isolates was analyzed by polymerase chain reaction using eight amplified fragment length polymorphism (AFLP) primers that generated 1728 bands, of which 99% were polymorphic. Cluster analysis using UPGMA showed that the similarity values ranged from 0.15 to 0.47. At a similarity coefficient of 0.2, the isolates were separated into 7 groups. Analysis of molecular variance indicated that about 92% of the genetic variation resided within populations. No correlation was found between genetic diversity and aggressiveness or the geographic origin of the isolates. Results of the study indicate that pathogenic F. oxysporum are commonly associated with root rot of soybean with various aggressiveness and they are genetically diverse.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".