Field studies were established on the alluvial floodplain soils in Louisiana, from 2013 to 2015, to evaluate the effect of silicate slag applications on productivity of wheat (Triticum aestivum), under sufficient and high nitrogen (N) application rates. Treatments were arranged in a randomized complete block design, with four replications consisting of twelve treatments: a factorial combination of two N (101 and 145 kg N ha⁻¹) and five silicate slag rates (0, 1, 2, 4.5, and 9 Mg ha⁻¹), and two control plots (with and without lime). Nitrogen had a greater impact on wheat productivity than silicate slag application. Wheat grain yield reached over 7000 kg ha⁻¹ with applications of 145 kg N, and 9 Mg silicate slag per ha for soil having Si level <20 mg kg⁻¹. Yield increases due to N or Si were attributed to the increase in number of spike m⁻² and grain number spike⁻¹. Silicate slag application effectively raised soil pH, and availability of several plant-essential nutrients, including plant-available N (nitrate, NO₃⁻), demonstrating the benefits of slag application are beyond increasing plant-available Si. The benefits of silicate slag application were clearly observed in wheat supplied with high N, and on soil with low plant-available Si.

Fusarium head blight (FHB), caused primarily by the fungus Fusarium graminearum, is one of the most damaging diseases of wheat, causing significant loss of yield and quality worldwide. Warm and wet conditions during flowering, a lack of resistant wheat varieties, and high inoculum pressure from corn stubble contribute to frequent FHB epidemics in the southern United States. The soft red winter wheat variety AGS 2060 is moderately susceptible (as opposed to susceptible) to FHB and regularly found in pedigrees of resistant breeding lines. AGS 2060 does not carry any known resistance genes or quantitative trait loci (QTL). A QTL mapping study was conducted to determine the location and genetic effect of its resistance using a doubled haploid mapping population produced from a cross between wheat varieties AGS 2060 and AGS 2035 (FHB susceptible). The population was genotyped using the Illumina iSelect single nucleotide polymorphism (SNP) array for wheat and phenotyped in Baton Rouge and Winnsboro, Louisiana and Newport, Arkansas in 2018 and 2019. The effect of genotype was significant for Fusarium damaged kernels (FDK) and deoxynivalenol (DON) content across all locations and years, indicating genetic variation in the population. The study detected 13 QTLs (one each on chromosome 1A, 1B, 1D, 2A, 2B, 6A, 6B, 7A, and 7B, and two each on 5A and 5B) responsible for the reduction of FDK and/or DON. Of these, nine QTLs for FHB resistance were identified in Winnsboro, Louisiana, in 2019. QTLs on chromosomes 2A and 7A could be valuable sources of resistance to both DON and FDK over several environments and were likely the best candidates for use in marker-assisted selection. Consistently expressed QTLs on chromosomes 5A, 6B, and 7A were potentially newly identified sources of resistance to FHB in soft red winter wheat.

Herbicides are an important component of weed management in wheat, particularly in the southeastern US where weeds actively compete with wheat throughout the winter for nutrients and reduce tillering and ultimately the yield of the crop. Some wheat varieties are sensitive to metribuzin, a low-cost non-selective herbicide, leading to leaf chlorosis, stand loss, and decreased yield. Knowledge of the genetics of herbicide tolerance in wheat is very limited and most new varieties have not been screened for metribuzin tolerance. The identification of genes associated with metribuzin tolerance will lead to the development of molecular markers for use in screening breeding lines for metribuzin tolerance. AGS 2035 and AGS 2060 were identified as resistant and sensitive to metribuzin in several previous field screening experiments as well as controlled condition screening of nine varieties in the present study. Genome-wide transcriptome profiling of the genes in AGS 2035 and AGS 2060 through microarray analysis identified 169 and 127 genes to be significantly (2-fold, P>0.01) up- and down-regulated, respectively in response to metribuzin. Functional annotation revealed that genes involved in cell wall biosynthesis, photosynthesis and sucrose metabolism were highly responsive to metribuzin application. (Semi)quantitative RT-PCR of seven selected differentially expressed genes (DEGs) indicated that a gene coding for alkaline alpha-galactosidase 2 (AAG2) was specifically expressed in resistant varieties only after one and two weeks of metribuzin application. Integration of the DEGs into our ongoing mapping effort and identification of the genes within the QTL region showing significant association with resistance in future will aid in development of functional markers for metribuzin resistance.

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.