Improved methods for measuring Fusarium-damaged kernels to select for resistance to deoxynivalenol accumulation and Fusarium Head Blight resistance in wheat

Authors: ACKERMAN, ARLYN - Clemson University; HOLMES, RYAN - Clemson University; GASKINS, EZEKIEL - Clemson University; JORDAN, KATHLEEN - Clemson University; HICKS, DAWN - Clemson University; FITZGERALD, JOSHUA - Virginia Tech; GRIFFEY, CARL - Virginia Tech; MASON, R. ESTEN - Colorado State University; HARRISON, STEPHEN - Louisiana State University; MURPHY, J. PAUL - North Carolina State University; Cowger, Christina; BOYLES, RICHARD - Clemson University

Submitted to: Agronomy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/17/2022
Publication Date: 2/21/2022
Citation: Ackerman, A.J., Holmes, R., Gaskins, E., Jordan, K.E., Hicks, D.S., Fitzgerald, J., Griffey, C.A., Mason, R., Harrison, S.A., Murphy, J., Cowger, C., Boyles, R.E. 2022. Improved methods for measuring Fusarium-damaged kernels to select for resistance to deoxynivalenol accumulation and Fusarium Head Blight resistance in wheat. Agronomy. 2:1. https://doi.org/10.3390/agronomy12020532.
DOI: https://doi.org/10.3390/agronomy12020532

Interpretive Summary: Fusarium head blight (FHB) is one of the most economically destructive diseases of wheat (Triticum aestivum L.), causing substantial yield and quality loss worldwide. Fusarium graminearum is the predominant causal pathogen of FHB in the U.S., and produces deoxynivalenol (DON), a mycotoxin that accumulates in the grain throughout infection. FHB results in kernel damage, a visual symptom that is quantified by a human observer enumerating or estimating the percentage of Fusarium-damaged kernels (FDK) in a sample of grain. To date, FDK estimation is the most efficient and accurate method of predicting DON content without measuring presence in a laboratory. For this experiment, 1266 entries collectively representing elite varieties and SunGrains advanced breeding lines encompassing four inoculated FHB nurseries were represented in the analysis. All plots were subjected to a manual FDK count, both exact and estimated, near-infrared spectroscopy (NIR) analysis, DON laboratory analysis, and digital imaging seed phenotyping using the Vibe QM3 instrument developed by Vibe imaging analytics. Among the FDK analytical platforms used to establish percentage FDK within grain samples, Vibe QM3 showed the strongest prediction capabilities of DON content in experimental samples, R2 = 0.63, and higher yet when deployed as FDK GEBVs, R2 = 0.76. Additionally, Vibe QM3 was shown to detect a significant SNP association at locus S3B_9439629 within major FHB resistance quantitative trait locus (QTL) Fhb1. Visual estimates of FDK showed higher prediction capabilities of DON content in grain subsamples than previously expected when deployed as genomic estimated breeding values (GEBVs) (R2 = 0.71), and the highest accuracy in genomic prediction, followed by Vibe QM3 digital imaging, with average Pearson’s correlations of r = 0.594 and r = 0.588 between observed and predicted values, respectively. These results demonstrate that seed phenotyping using traditional or automated platforms to determine FDK boast various throughput and efficacy that must be weighed appropriately when determining application in breeding programs to screen for and develop resistance to FHB and DON accumulation in wheat germplasms.

Technical Abstract: Fusarium head blight (FHB) is one of the most economically destructive diseases of wheat (Triticum aestivum L.), causing substantial yield and quality loss worldwide. In North America, Fusarium graminearum is the predominant causal pathogen of FHB and produces deoxynivalenol (DON), a mycotoxin that accumulates in the grain after infection. FHB results in kernel damage, a visual symptom that is quantified by visually determining the percentage of Fusarium-damaged kernels (FDK) in a sample of grain. To date, FDK estimation is the most efficient and accurate method of predicting DON content without measuring it in a laboratory. For this experiment, 1211 entries collectively representing elite varieties and SunGrains (http://Vibe.sungrains.lsu.edu/) advanced breeding lines spanning three inoculated FHB nurseries were represented in the analysis. All plots were subjected to a manual FDK count, both exact and estimated, near-infrared spectroscopy (NIR) analysis, DON laboratory analysis, and automated seed phenotyping using the Vibe QM3 instrument developed by Vibe imaging analytics (https://Vibe.Vibeia.com/). Among FDK analytical platforms used to create FDK traits, Vibe QM3 showed the strongest relationship with DON resistance to accumulation as shown by a phenotypic correlation of r=.81, genetic correlation of r=0.87, and correlation between trait GEBVs of r =.87. Vibe imaging was shown to detect a significant SNP association at locus S3B_9439629 within a major FHB resistance quantitative trait locus (QTL) ith a confidence level of -log10(p) of 6.35. Additionally, Vibe QM3 values were shown to have the highest accuracy in genomic prediction models compared to other phenotyping methods, with an average Pearson correlation of r=0.59 between observed and predicted values. These results show that automated seed phenotyping using the Vibe QM3 grain analyzer can be effectively applied to breeding programs to screen for and develop resistance to FHB and DON accumulation in wheat germplasms.