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. 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.
Highlights
Fusarium head blight (FHB) is one of the most economically destructive diseases of wheat (Triticum aestivum L.) worldwide, causing substantial yield and quality loss
Similar to near-infrared spectroscopy (NIR), Vibe QM3 Grain Analyzer (VIBE) was unable to estimate a sample as 0% Fusarium-damaged kernels (FDK), having an average error of 5.84% when analyzing the 0% FDK standard; VIBE had the second highest threshold for FDK
This study aims to build upon these concepts when deploying Vibe QM3 by ground truthing results against observed DON content of grain and evaluating digital imaging against other FDK platforms
Summary
Fusarium head blight (FHB) is one of the most economically destructive diseases of wheat (Triticum aestivum L.) worldwide, causing substantial yield and quality loss. In the United States, the principal species responsible for FHB is Fusarium graminearum Schwabe [1]. Because DON levels in commercial wheat are subject to advisory ceilings in an effort to control grain quality and safety, Fusarium infection and resulting damage to kernels (FDK, Fusarium-damaged kernels) can lead to a load of grain being downgraded or rejected at the point of sale [2]. Adding to the pressure of FHB on wheat in the United States is the increased acreage of maize (Zea mays L.), as F. graminearum’s teleomorph is a common disease of maize and persists on residue in the field [3]
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