A Model for Cotton Emergence Based on Thirty Years of Seed Treatment Trials Conducted by the National Cotton Seed Treatment Committee

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.

Authors

Institutions

Publication Details

Journal
Phytopathology
Published
2026-09-09
DOI
https://doi.org/10.1094/phyto-04-26-0137-r
Primary Topic
Research in Cotton Cultivation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

A Model for Cotton Emergence Based on Thirty Years of Seed Treatment Trials Conducted by the National Cotton Seed Treatment Committee

C. Rothrock, H. Kelly, M. Bragg, K. Lawrence et al.
Phytopathology
Research in Cotton Cultivation
article

A Model for Cotton Emergence Based on Thirty Years of Seed Treatment Trials Conducted by the National Cotton Seed Treatment Committee

C. Rothrock, H. Kelly, M. Bragg, K. Lawrence, T. Wheeler, T. Kirkpatrick, A. Rojas, T. S. Isakeit, T. H. Wilkerson, A. Strayer Scherer, M. Bayles, K. Bissonnette, Z. A. Noel, P. Price, T. Faske, C. A. Floyd, I. Small, R. Kemerait, T. W. Allen, T. Spurlock, E. Rogenkamp
article en

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.

Phytopathology
Oklahoma State University (US), University of North Florida (US), Louisiana State University Agricultural Center (US), North Carolina State University (US), University of Georgia (US), Texas A&M University System (US), Cotton (United States) (US), University of Arkansas System (US), Mississippi Delta Community College (US), University of Florida (US), University of Missouri System (US), University of Arkansas at Fayetteville (US), Auburn University (US), Michigan State University (US), Jackson College (US), Texas A&M University (US), Mississippi State University (US)
Openalex Percentile: Top 13%
Research in Cotton Cultivation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.