Consideration of Nonparametric Approaches for Assessing Genotype-by-Environment (G × E) Interaction with Disease Severity Data

Stability of Hybrid Maize Reaction to Gibberella Ear Rot and Deoxynivalenol Contamination of Grain

Trials were conducted to quantify the stability (or lack of G × E interaction) of 15 maize hybrids to Gibberella ear rot (GER; caused by Fusarium graminearum) and deoxynivalenol (DON) contamination of grain across 30 Ohio environments (3 years × 10 locations). In each environment, one plot of each hybrid was planted and 10 ears per plot were inoculated via the silk channel. GER severity (proportion of ear area diseased) and DON contamination of grain (ppm) were quantified. Multiple rank-based methods, including Kendall's concordance coefficient (W) and Piepho's U, were used to quantify hybrid stability. The results found insufficient evidence to suggest crossover G × E interaction of ranks, with W greater than zero for GER (W = 0.28) and DON (W = 0.26), and U not statistically significant for either variable (P > 0.20). Linear mixed models (LMMs) were also used to quantify hybrid stability, accounting for crossover or noncrossover G × E interaction of transformed observed data. Based on information criteria and likelihood ratio tests for GER and DON response variables, the models with more complex variance-covariance structures-heterogeneous compound symmetry and factor-analytic-provided a better fit than the model with the simpler compound symmetry structure, indicating that one or more hybrids differed in stability. Overall, hybrids were stable based on rank-based methods, which indicated a lack of crossover G × E interaction, but the LMMs identified a few hybrids that were sensitive to environment. Resistant hybrids were generally more stable than susceptible hybrids.

Efficacy and Economics of Integrating In-Field and Harvesting Strategies to Manage Fusarium Head Blight of Wheat

Fusarium head blight (FHB), a fungal disease of wheat caused by Fusarium graminearum, and its associated toxins, particularly deoxynivalenol (DON), are best managed by integrating multiple strategies. Experiments were established in 2011 and 2013 to evaluate the effects of integrating cultivar resistance, fungicide application, and grain harvesting strategy on FHB index (IND; field severity), DON, grain yield (YLD), and grain test weight (TW; weight per unit volume). Plots of two moderately resistant and two susceptible cultivars were either treated with 19% tebuconazole + 19% prothioconazole or left untreated, and then inoculated with F. graminearum. IND was rated as the mean percentage of diseased spikelets per spike. Separate subsets of the plots of each cultivar-treatment combination were harvested with one of two combine harvester configuration: C1 (the default, set at a fan speed of 1,375 rpm and a shutter opening of 70 mm) and C4 (modified, with the same fan speeds but a wider shutter opening of 90 mm). YLD and TW data were collected, and grain samples were rated for percent Fusarium-damaged kernels (FDK) and tested for DON. Results from linear mixed-model analyses showed that the cultivar-treatment interaction was significant for all FHB-related responses, with the magnitude of the difference in mean arcsine-square-root-transformed IND and FDK (arcIND and arcFDK) and log-transformed DON (logDON) between treated and untreated being higher for susceptible than moderately resistant cultivars. Plots harvested with the C4 combine configuration had significantly higher mean TW than those harvested with C1. Treated plots had significantly higher YLD and TW than untreated plots, regardless of cultivar and configuration. Relative to the reference management program (untreated, susceptible cultivar, harvested with C1), the greatest percent reduction in FDK and DON and increase in YLD was observed for programs that included moderate resistance and fungicide treatment. The greatest percent increase in TW relative to the reference was observed when C4 adjusted combine setting was integrated with resistance and fungicide. Overall, the most effective management programs all included fungicide treatment, two included moderate resistance, and two included C4 combine setting. Relative to the reference management program, these programs resulted in 30 to 51% reduction in total estimated price discount, $127 to 312 ha^-1 increase in gross cash income, and economic benefit of $31 to 272 ha^-1, depending on the level of FHB IND (5 to 15%), grain price ($118 to 276 metric ton^-1), and fungicide application cost ($40 to 96 ha^-1).

Stabilization of yield in plant genotype mixtures through compensation rather than complementation

BACKGROUND AND AIMS

Plant genotypic mixtures have the potential to increase yield stability in variable, often unpredictable environments, yet knowledge of the specific mechanisms underlying enhanced yield stability remains limited. Field studies are constrained by environmental conditions which cannot be fully controlled and thus reproduced. A suitable model system would allow reproducible experiments on processes operating within crop genetic mixtures.

METHODS

Phenotypically dissimilar genotypes of Arabidopsis thaliana were grown in monocultures and mixtures under high levels of competition for abiotic resources. Seed production, flowering time and rosette size were recorded.

KEY RESULTS

Mixtures achieved high yield stability across environments through compensatory interactions. Compensation was greatest when plants were under high levels of heat and nutrient stress. Competitive ability and mixture performance were predictable from above-ground phenotypic traits even though below-ground competition appeared to be more intense.

CONCLUSIONS

This study indicates that the mixing ability of plant genotypes can be predicted from their phenotypes expressed in a range of relevant environments, and implies that a phenotypic screen of genotypes could improve the selection of suitable components of genotypic mixtures in agriculture intended to be resilient to environmental stress.

Efficacy and Stability of Integrating Fungicide and Cultivar Resistance to Manage Fusarium Head Blight and Deoxynivalenol in Wheat

Integration of host resistance and prothioconazole + tebuconazole fungicide application at anthesis to manage Fusarium head blight (FHB) and deoxynivalenol (DON) in wheat was evaluated using data from over 40 trials in 12 U.S. states. Means of FHB index (index) and DON from up to six resistance class-fungicide management combinations per trial (susceptible treated [S_TR] and untreated [S_UT]; moderately susceptible treated [MS_TR] and untreated [MS_UT]; moderately resistant treated [MR_TR] and untreated [MR_UT]) were used in multivariate meta-analyses, and mean log response ratios across trials were estimated and transformed to estimate mean percent control ( ) due to the management combinations relative to S_UT. All combinations led to a significant reduction in index and DON (P < 0.001). MR_TR was the most effective combination, with a of 76% for index and 71% for DON, followed by MS_TR (71 and 58%, respectively), MR_UT (54 and 51%, respectively), S_TR (53 and 39%, respectively), and MS_UT (43 and 30%, respectively). Calculations based on the principle of treatment independence showed that the combination of fungicide application and resistance was additive in terms of percent control for index and DON. Management combinations were ranked based on percent control relative to S_UT within each trial, and nonparametric analyses were performed to determine management combination stability across environments (trials) using the Kendall coefficient of concordance (W). There was a significant concordance of management combinations for both index and DON (P < 0.001), indicating a nonrandom ranking across environments and relatively low variability in the within-environment ranking of management combinations. MR_TR had the highest mean rank (best control relative to S_UT) and was one of the most stable management combinations across environments, with low rank stability variance (0.99 for index and 0.67 for DON). MS_UT had the lowest mean rank (poorest control) but was also one of the most stable management combinations. Based on Piepho's nonparametric rank-based variance homogeneity U test, there was an interaction of management combination and environment for index (P = 0.011) but not for DON (P = 0.147), indicating that the rank ordering for index depended somewhat on environment. In conclusion, although the magnitude of percent control will likely vary among environments, integrating a single tebuconazole + prothioconazole application at anthesis with cultivar resistance will be a more effective and stable management practice for both index and DON than either approach used alone.