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.

Field studies were conducted in 2010 and 2011 at two locations in Michigan to examine the effect of row width and herbicide combination on weed suppression and yield in the new Type II black bean variety ‘Zorro.' Black bean was planted in 38- and 76-cm rows. Six weed control strategies were examined:S-metolachlor + halosulfuron (PRE),S-metolachlor (PRE) followed by (fb) bentazon + fomesafen (POST), halosulfuron (PRE) fb clethodim (+ fomesafen at one site in one year) (POST), imazamox + bentazon (POST), a weed-free control, and a nontreated control. Weed control and crop injury were evaluated throughout the growing season. In addition, weeds were counted by species in late July, and weed biomass was harvested and weighed at the end of the season. Black bean yield was obtained by direct harvest. Narrow rows reduced weed populations in two of the four site–year combinations (referred to hereafter as site–years), reduced weed biomass in three of the four site–years, and often improved control of upright broadleaf weeds. All herbicide combinations generally reduced weed populations and biomass, but control of specific weeds was variable. Crop injury was generally slight and transient. Yield was greater in narrow rows in two of the four site–years. All herbicide combinations increased yield compared with the nontreated control and resulted in similar yields to one another. Yield and weed suppression was often maximized in narrow rows, while herbicide performance varied by year and weed spectrum.