Proceedings of the 47th Annual Meeting, Southern Soybean Disease Workers (March 4-5, 2020, Pensacola Beach, Florida)
Bibliographic record
Abstract
Contents Southern United States soybean disease loss estimates for 2019. TW Allen, K Bissonnette, CA Bradley, JP Damicone, NS Dufault, TR Faske, T Isakeit, RC Kemerait, A Koehler, HL Mehl, JD Mueller, GB Padgett, PP Price, EJ Sikora, IM Small, L Thiessen, and H Young Abstracts of presented papers Fungicide efficacy on target spot in Tennessee soybean. Ty Smith, H Kelly, and Z Hansen Temporal dynamics of Neohydatothrips variabilis, Frankliniella tritici, and Frankliniella fusca in South Central Wisconsin and the occurrence of Soybean vein necrosis virus. Cristina Zambrana-Echevarria, S Kaplan, RL Groves, and DL Smith Population distributions and densities of nematodes, and virulence phenotypes of soybean cyst nematode in Tennessee. Rufus Akinrinlola, and H Kelly Improving soybean white mold control by integrated management. Wade Webster, B Mueller, J Gaska, D Mueller, MI Chilvers, S Conley, and DL Smith Assessment of QoI sensitivity and frogeye leaf spot race of Cercospora sojina in Georgia soybean. Bennett Harrelson, A Culbreath, R Kemerait, Jr, and J Buck Reduction of Pythium damping-off in soybean by biocontrol seed treatment. Mirian F Pimentel, E Arnao, A Warner, N Elsharif, M Chilvers, A Robertson, J Bond, and A Fakhoury Understanding cercosporin self-resistance to identify novel tools to manage Cercospora leaf blight on soybean. Maria Izabel Costa de Novaes, CL Robertson, VP Doyle, and S Thomas-Sharma Evaluating the efficacy of soybean seed treatment on high and low vigor seed in Arkansas. Samantha Segalin, JC Rupe, JA Rojas, and R Holland Impact of wheat on soybean cyst nematode (Heterodera glycines I.) populations in a soybean double cropping system. Leonardo F Rocha, MF Pimentel, JP Bond, and AM Fakhoury Using unmanned aerial systems and multispectral imagery to assess sudden death syndrome of soybean. Lindsey McKinzie, AM Fakhoury, R Li, and JP Bond Soybean rust: Scourge of Alabama. Ed J Sikora, D Delaney, and K Connor Management of SCN and SDS with nematode-protectant seed treatments across multiple environments. Kaitlyn M Bissonnette, Y Kandel, M Chilvers, N Kleczewski, D Mueller, D Smith, D Telenko, and A Tenuta Determining inoculum density of Xylaria sp., the taproot decline pathogen, in soil under various crop rotation systems. Aline Bronzato-Badial, K Phillips, TH Wilkerson, and M Tomas-Peterson A new pathosystem to study the plant-fungal interactions underlying Cercospora leaf blight of soybean. Kona Swift and B Bluhm Impact of cultivar on soybean foliar and seed diseases in Arkansas. John C Rupe, RT Holland, and JA Rojas Thoughts on southern blight: Should we be concerned about southern blight? Tom W Allen, WL Solomon, and BA Burgess From plots to strips: Six years of fungicide trials. Terry N Spurlock, AC Tolbert, and RC Hoyle Meta-analysis of soybean yield response to foliar fungicides evaluated from 2005 to 2018 in the United States and Canada. Yuba K Kandel, C Hunt, K Ames, N Arneson, CA Bradley, E Byamukama, A Byrne, MI Chilvers, L Giesler, J Halvorson, DC Hooker, NM Kleczewski, DK Malvick, S Markell, B Potter, W Pederson, DL Smith, AU Tenuta, DEP Telenko, KA Wise, and DS Mueller On the road in Louisiana: Taking the research station to farms. Trey Price, MA Purvis, DA Ezell, GB Padgett, M Foster, and J Hebert The next super model: Development of a flexible framework for multiple disease models in soybean. Damon L Smith, J Willbur, M Chilvers, M Kabbage, SP Conley, D Mueller, and R Schmidt IPM implementation in Tennessee. Heather M Kelly, S Stewart, K Vail, D Hensley, S Steckel, A McClure, and T Raper Reproduction potential and survival of soybean nematodes in row rice. Travis Faske, K Brown, and N Bateman Initial research with peracetic acid as a disease management tool in soybeans and other legume crops. Vijay K Choppakatla FMC fungicide offerings update. Matthew Wiggins Abstracts for presented posters Extension efforts in disseminating nematode survey results. Rachel Guyer, R Akinrinlola, and H Young Assessing the role of weathering on the grain quality of soybean varieties in the Mississippi Delta. Tessie H Wilkerson, TW Allen, and BA Burgess Proceedings of the Southern Soybean Disease Workers are published annually by the Southern Soybean Disease Workers. Text, references, figures, and tables are reproduced as they were submitted by authors. The opinions expressed by the participants at this conference are their own and do not necessarily represent those of the Southern Soybean Workers. Mention of a trademark or proprietary products in this publication does not constitute a guarantee, warranty, or endorsement of that product by the Southern Soybean Disease Workers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.244 | 0.146 |
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".