Evaluation of Methods for Measuring Fusarium-Damaged Kernels of Wheat

dc.contributor.authorAckerman, Arlyn J.en
dc.contributor.authorHolmes, Ryanen
dc.contributor.authorGaskins, Ezekielen
dc.contributor.authorJordan, Kathleen E.en
dc.contributor.authorHicks, Dawn S.en
dc.contributor.authorFitzgerald, Joshuaen
dc.contributor.authorGriffey, Carl A.en
dc.contributor.authorMason, Richard Estenen
dc.contributor.authorHarrison, Stephen A.en
dc.contributor.authorMurphy, Joseph Paulen
dc.contributor.authorCowger, Christinaen
dc.contributor.authorBoyles, Richard E.en
dc.date.accessioned2022-02-25T13:47:37Zen
dc.date.available2022-02-25T13:47:37Zen
dc.date.issued2022-02-21en
dc.date.updated2022-02-24T14:50:02Zen
dc.description.abstract<i>Fusarium</i> head blight (FHB) is one of the most economically destructive diseases of wheat (<i>Triticum aestivum</i> L.), causing substantial yield and quality loss worldwide. <i>Fusarium graminearum</i> 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 <i>Fusarium</i>-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, <i>R</i><sup>2</sup> = 0.63, and higher yet when deployed as FDK GEBVs, <i>R</i><sup>2</sup> = 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) <i>Fhb1</i>. 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) (<i>R</i><sup>2</sup> = 0.71), and the highest accuracy in genomic prediction, followed by Vibe QM3 digital imaging, with average Pearson&rsquo;s correlations of <i>r =</i> 0.594 and <i>r =</i> 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.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationAckerman, A.J.; Holmes, R.; Gaskins, E.; Jordan, K.E.; Hicks, D.S.; Fitzgerald, J.; Griffey, C.A.; Mason, R.E.; Harrison, S.A.; Murphy, J.P.; Cowger, C.; Boyles, R.E. Evaluation of Methods for Measuring Fusarium-Damaged Kernels of Wheat. Agronomy 2022, 12, 532.en
dc.identifier.doihttps://doi.org/10.3390/agronomy12020532en
dc.identifier.urihttp://hdl.handle.net/10919/108862en
dc.language.isoenen
dc.publisherMDPIen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectFusarium head blighten
dc.subjectFusarium-damaged kernelsen
dc.subjectdeoxynivalenolen
dc.subjectDON resistanceen
dc.subjectmanual sortingen
dc.subjectvisual estimationen
dc.subjectnear-infrared spectroscopyen
dc.subjectVibe QM3 digital imagingen
dc.titleEvaluation of Methods for Measuring Fusarium-Damaged Kernels of Wheaten
dc.title.serialAgronomyen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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