Authors
Z A Noel, T W Allen, M Bragg, M Bayles, K Bissonnette, T Faske, C A Floyd, T S Isakeit, H Kelly, R Kemerait, T Kirkpatrick, K Lawrence, P Price, E Rogenkamp, A Rojas, C Rothrock, I Small, T Spurlock, A Strayer Scherer, T Wheeler, T H Wilkerson
Published in
Phytopathology. Sep 09, 2026. Epub Sep 09, 2026.
Abstract
Over 30 years, the National Cotton Council's National Cottonseed Treatment program has conducted coordinated seed treatment trials across the U.S., resulting in a comprehensive dataset of over 500 field trials. After data curation compiled from annual reports published in the Cotton Beltwide Proceedings, we used data from 409 field trials to develop beta regression models for upland cotton (Gossypium hirsutum L.) seedling emergence that integrates environmental and pathogen variables and to evaluate the efficacy of seed treatments. The minimum air temperature nine days post-planting and the cumulative precipitation three days post-planting were identified as key environmental predictors of emergence. The successful isolation of Pythium spp. from cotton roots was significantly associated with reduced emergence. Seed treatments containing at least three active ingredients targeting both true fungi and oomycetes improved emergence by an average of 10.2% and significantly reduced the risk of falling below the critical threshold of 35,000 emerged plants per hectare, often cited as the population to maintain yield. The resulting model introduces a benchmark tool with an associated error rate of approximately 16 to 20%, enabling future refinement. These findings highlight the long-term value of multi-state field trials and support the development of data-driven tools to guide planting or scouting decisions and optimize seed treatment strategies.
PMID:
42714210
Bibliographic data and abstract were imported from PubMed on 09 Sep 2026.
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