Soybean Resistance to Field Populations of <i>Heterodera glycines</i> in Selected Geographic Areas
Bibliographic record
Abstract
Data were collected 2006 through 2008 from 527 soil samples to determine the current effectiveness of PI 88788 and other sources of Heterodera glycines resistance in three geographically separated areas of soybean production: Tennessee and Indiana/Illinois, USA, and Ontario, Canada. In Tennessee where PI 88788 source of resistance has been used since 1978, 93% of field populations reproduced on PI 88788 (≥10% of susceptible cultivar), and no HG Type 0 populations were found. In Indiana and Illinois, where resistance was used since the mid-1980s, from 56 to 88% of the populations reproduced on PI 88788 (≥10%). PI 548402 (Peking), PI 90763, and PI 437654 had low reproduction (≤10%) unlike Tennessee where 78% of the populations reproduced on PI 548402 (≥10%) and 93% reproduced on PI 90763 (≥10%). In Ontario, where cultivars with PI 88788 resistance were used after 1989, PI 88788 in 73% of the field populations had ≤10% reproduction. But 15% of Ontario populations reproduced on PI 548402 (≥10%) and 6% reproduced on PI 90763 (≥10%), two sources of resistance not generally present in commercial cultivars grown in Ontario. Accepted for publication 9 March 2010. Published 26 April 2010.
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 | 0.000 |
| 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) | 0.000 | 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".