Evaluation of Methods for Measuring Fusarium-Damaged Kernels of Wheat
Clemson University | North Carolina State University | USDA Agricultural Research Service | Virginia Tech | Colorado State University | Louisiana State University
Partner institutions
Clemson University
Clemson, SC, USA
A public land-grant research university in Clemson, South Carolina, with a leading small-grains breeding and genomics program.
North Carolina State University
Raleigh, NC, USA
A public land-grant research university in Raleigh, North Carolina, with major programs in crop and soil sciences.
USDA Agricultural Research Service
Multiple sites, USA
The chief in-house scientific research agency of the U.S. Department of Agriculture, conducting research across crop science, food safety, and agricultural technology nationwide.
Virginia Tech
Blacksburg, VA, USA
A public land-grant research university in Blacksburg, Virginia, with a leading small-grains breeding program.
Colorado State University
Fort Collins, CO, USA
A public land-grant research university in Fort Collins, Colorado, with programs in soil and crop sciences.
Louisiana State University
Baton Rouge, LA, USA
A public land-grant research university in Baton Rouge, Louisiana, with programs in plant, environmental, and soil sciences.
How Vibe analyzers were used
Comparing manual counting, near-infrared spectroscopy, visual scoring, and the Vibe QM3 grain analyzer for scoring Fusarium-damaged kernels across 1,266 wheat entries, the Vibe QM3 platform showed the strongest prediction of DON content (R² = 0.63, rising to 0.76 when deployed as genomic estimated breeding values).
Study overview
Fusarium head blight (FHB) reduces wheat grain quality and safety through the accumulation of deoxynivalenol (DON), a mycotoxin correlated with the proportion of Fusarium-damaged kernels (FDK) in a sample. This study compared manual FDK counting, near-infrared (NIR) spectroscopy, visual scoring, and digital imaging via the Vibe QM3 grain analyzer across 1,266 wheat entries from inoculated FHB nurseries, benchmarked against laboratory DON analysis. The Vibe QM3 platform showed the strongest prediction capability for DON content among the platforms compared (R² = 0.63), improving further when FDK scores were deployed as genomic estimated breeding values (R² = 0.76), outperforming NIR and matching or exceeding visual scoring for use in breeding selection.
Topics and keywords
Related crop analysis
Bibliographic details
Year: 2022
Publication: Agronomy
Institutions: Clemson University, North Carolina State University, USDA Agricultural Research Service, Virginia Tech, Colorado State University, Louisiana State University
More research using Vibe
Explore additional studies applying Vibe analyzers in grain and seed phenotyping workflows.
