Fusarium Head Blight Epidemics in Soft Red Winter Wheat Fields in Georgia from 2018 to 2019

Fusarium head blight (FHB) epidemics on wheat have caused significant yield and economic penalties in the United States since the early 1990s. This report documents FHB epidemics on soft red winter wheat in Georgia in 2018 and 2019. Forty-four wheat fields across 23 counties were assessed for FHB incidence (2019 only), Fusarium-damaged kernel, deoxynivalenol (DON) contamination, and thousand kernel weight. Higher levels of FHB were observed in 2019 compared to 2018. A significant correlation was observed between DON and 7-day pre-anthesis weather variables in 2019. FHB parameters were significantly correlated to post-anthesis weather variables at 10-day in both years and at 20 and 30-day in 2018 suggesting that post-anthesis rather than pre-anthesis weather had a greater impact on FHB in our study. The combination of hours of conducive temperature and relative humidity post-anthesis was consistently correlated with all FHB parameters in both years and could be the best predictor of FHB epidemics. FHB has emerged as the leading threat for soft red winter wheat production in Georgia. Planting moderately resistant wheat cultivars along with in-season management including proper fungicide application, by closely monitoring the national FHB forecasting system, would be the best integrated management strategies for Georgian wheat growers.

Predicting Fusarium Head Blight Resistance for Advanced Trials in a Soft Red Winter Wheat Breeding Program With Genomic Selection

Many studies have evaluated the effectiveness of genomic selection (GS) using cross-validation within training populations; however, few have looked at its performance for forward prediction within a breeding program. The objectives for this study were to compare the performance of naïve GS (NGS) models without covariates and multi-trait GS (MTGS) models by predicting two years of F4:7 advanced breeding lines for three Fusarium head blight (FHB) resistance traits, deoxynivalenol (DON) accumulation, Fusarium damaged kernels (FDK), and severity (SEV) in soft red winter wheat and comparing predictions with phenotypic performance over two years of selection based on selection accuracy and response to selection. On average, for DON, the NGS model correctly selected 69.2% of elite genotypes, while the MTGS model correctly selected 70.1% of elite genotypes compared with 33.0% based on phenotypic selection from the advanced generation. During the 2018 breeding cycle, GS models had the greatest response to selection for DON, FDK, and SEV compared with phenotypic selection. The MTGS model performed better than NGS during the 2019 breeding cycle for all three traits, whereas NGS outperformed MTGS during the 2018 breeding cycle for all traits except for SEV. Overall, GS models were comparable, if not better than phenotypic selection for FHB resistance traits. This is particularly helpful when adverse environmental conditions prohibit accurate phenotyping. This study also shows that MTGS models can be effective for forward prediction when there are strong correlations between traits of interest and covariates in both training and validation populations.

Impact of Nitrogen Rate in Conventional and Organic Production Systems on Yield and Bread Baking Quality of Soft Red Winter Wheat

Soft red winter wheat (SRW) is characterized by high yield and relatively low protein content. In Kentucky, there is growing demand from local artisan bread bakers for regionally produced flour, requiring production of grain with increased protein content and/or strength. The objective of this two-year field experiment was to evaluate the effect of nitrogen (N) management on five cultivars of winter wheat on yield and bread baking quality traits of modern and landrace SRW cultivars (Triticum aestivum L.). All five cultivars were evaluated using two N application rates in conventional and organic production systems. All traits measured were significantly affected by the agricultural production system and N rate, although plant height and other quality traits varied by study year. Significantly higher yields were achieved in the conventional system at a relatively low N rate (67.2 kg ha−1) in both study years (2017–2019) (p < 0.01). Results were variable by cultivar and a locally bred, high-yielding cultivar (Pembroke 2014) had the highest lactic acid solvent retention capacity score and thousand kernel weight of the cultivars evaluated. In addition, a landrace cultivar (Purple Straw) had the highest grain N and plant height. A French soft wheat, Soissons, had the highest sedimentation value and Pembroke 2016 achieved the highest yield. The findings from this study suggest the possibility of attaining a desirable grain with quality traits of SRW wheat that meets the needs of local bread wheat production in Kentucky through improving the optimization of cultivar selection, N management and specific considerations for conventional and organic systems.

Using Genomic Selection to Leverage Resources among Breeding Programs: Consortium-Based Breeding

Genomic selection has many applications within individual programs. Here, we discuss the benefits of forming a GS-based breeding consortium (GSC) among programs within the context of a recently formed a GSC of soft red winter wheat breeding programs. The GSC will genotype lines from each member breeding program (MBP) and conduct cooperative phenotyping. The primary GSC benefit is that each MBP can use GS to predict the local and broad value of all germplasm from all MBPs including lines in the early stages of testing, thus increasing the effective size of each MBP without significant new investment. We identified eight breeding aspects that are essential to GSC success and analyzed how our GSC fits those criteria. We identified a core of >5700 related lines from the MBPs that can serve in training populations. Germplasm from each MBP provided breeding value to other MBPs and program-specific adaption was low. GS accuracy was acceptable within programs but was low between programs when using training populations with little testing connectivity, but increased when using data from trials with high testing connectivity between MBPs. In response we initiated sparse-testing with a germplasm sharing scheme utilizing family relationship to connect our phenotyping of early-stage lines.

Phenotyping Anther Extrusion of Wheat Using Image Analysis

Phenotyping wheat (Triticum aestivum L.) is time-consuming and new methods are necessary to decrease labor. To develop a heterotic pool of male wheat lines for hybrid breeding, there must be an efficient way to measure both anther extrusion and the size of anthers. Five hundred and ninety-four soft red winter wheat lines in two replications of randomized complete block design were phenotyped for anther extrusion, a key trait for hybrid wheat production. A device was constructed to capture images using a mobile device. Four heads were sampled per line when anthesis was evident for half the heads in the plot. The extruded anthers were scraped onto a surface, their image was captured, and the area of the anthers was taken via ImageJ. The number of anthers extruded was estimated by counting the number of anthers per image and dividing by the number of heads sampled. The area per anther was taken by dividing the area of anthers per spike by the number of anthers per spike. A significant correlation (R=0.9, p<0.0001) was observed between the area of anthers per spike and the number of anthers per spike. This method is proposed as a substitute for field ratings of anther extrusion and to quantitatively measure the size of anthers.

Genome-wide association studies for Fusarium head blight resistance and it’s trade-off with grain yield in soft red winter wheat

Identification of quantitative trait loci for Fusarium head blight (FHB) resistance from different sources and pyramiding them into cultivars could provide effective protection against FHB. The objective of this study was to characterize a soft red winter wheat (SRWW) breeding population that has been subjected to intense germplasm introduction and alien introgression for FHB resistance in the past. The population was evaluated under misted FHB nurseries inoculated with Fusarium graminearum infested corn spawn for two years. Phenotypic data included disease incidence (INC), disease severity (SEV), Fusarium damaged kernels (FDK), FHB index (FHBdx), and deoxynivalenol concentration (DON). Genome-wide association studies by using 13,784 SNP markers identified twenty-five genomic regions at -logP ≥ 4.0 that were associated with five FHB-related traits. Of these 25, the marker trait associations that explained more than 5% phenotypic variation were localized on chromosomes 1A, 2B, 3B, 5A, 7A, 7B, and 7D, and from diverse sources including adapted SRWW lines such as Truman and Bess, and unadapted common wheat lines such as Ning7840 and Fundulea 201R. Furthermore, individuals with favorable alleles at the four loci Fhb1, Qfhb.nc-2B.1 (Q2B.1), Q7D.1, and Q7D.2 showed better FDK and DON scores (but not INC, SEV, and FHBdx) compared to other allelic combinations. Our data also showed while pyramiding multiple loci provides protection against FHB disease, it has significant trade-off with grain yield.