Impact of Growing Environment on Anthracnose Severity of Switchgrass Cultivars and Clones
Bibliographic record
Abstract
Anthracnose (caused by Colletotrichum navitas) has the potential to significantly reduce biomass yield of switchgrass (Panicum virgatum L.); however, limited information is available on the impact of growing environment on tolerance of switchgrass to anthracnose. Therefore, the major objectives of this study were to (i) examine genotype-environment (G × E) effects on anthracnose severity in populations of switchgrass cultivars and individual genotypes and (ii) determine clonal repeatability estimates and stability analysis of anthracnose tolerance on individual switchgrass genotypes. Two experiments were conducted at one prime and two marginal soil locations in New Jersey. In all, 14 switchgrass cultivars were established from seed in 2008 for experiment 1 and 50 replicated switchgrass clones were planted in 2009 for experiment 2 at all three locations. Anthracnose was rated visually in 2010 for experiment 1 and in 2010 and 2011 for experiment 2. Significant G × E interactions were detected for both experiments (P ≤ 0.05) and anthracnose severity varied by location and cultivar. Clonal repeatability estimates for disease tolerance among clones was 0.78 on a clonal basis and 0.32 on a single-plant basis. Lowland ecotypes exhibited less disease overall than upland ecotypes. Results from this study indicate that selection for improved tolerance to anthracnose should be conducted after evaluation across several environments over multiple years.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".