2018-2019 field seasons of the Maize Genomes to Fields (G2F) G x E project

OBJECTIVES

This report provides information about the public release of the 2018-2019 Maize G X E project of the Genomes to Fields (G2F) Initiative datasets. G2F is an umbrella initiative that evaluates maize hybrids and inbred lines across multiple environments and makes available phenotypic, genotypic, environmental, and metadata information. The initiative understands the necessity to characterize and deploy public sources of genetic diversity to face the challenges for more sustainable agriculture in the context of variable environmental conditions.

DATA DESCRIPTION

Datasets include phenotypic, climatic, and soil measurements, metadata information, and inbred genotypic information for each combination of location and year. Collaborators in the G2F initiative collected data for each location and year; members of the group responsible for coordination and data processing combined all the collected information and removed obvious erroneous data. The collaborators received the data before the DOI release to verify and declare that the data generated in their own locations was accurate. ReadMe and description files are available for each dataset. Previous years of evaluation are already publicly available, with common hybrids present to connect across all locations and years evaluated since this project's inception.

The importance of dominance and genotype-by-environment interactions on grain yield variation in a large-scale public cooperative maize experiment

High-dimensional and high-throughput genomic, field performance, and environmental data are becoming increasingly available to crop breeding programs, and their integration can facilitate genomic prediction within and across environments and provide insights into the genetic architecture of complex traits and the nature of genotype-by-environment interactions. To partition trait variation into additive and dominance (main effect) genetic and corresponding genetic-by-environment variances, and to identify specific environmental factors that influence genotype-by-environment interactions, we curated and analyzed genotypic and phenotypic data on 1918 maize (Zea mays L.) hybrids and environmental data from 65 testing environments. For grain yield, dominance variance was similar in magnitude to additive variance, and genetic-by-environment variances were more important than genetic main effect variances. Models involving both additive and dominance relationships best fit the data and modeling unique genetic covariances among all environments provided the best characterization of the genotype-by-environment interaction patterns. Similarity of relative hybrid performance among environments was modeled as a function of underlying weather variables, permitting identification of weather covariates driving correlations of genetic effects across environments. The resulting models can be used for genomic prediction of mean hybrid performance across populations of environments tested or for environment-specific predictions. These results can also guide efforts to incorporate high-throughput environmental data into genomic prediction models and predict values in new environments characterized with the same environmental characteristics.

Meta-Analysis of Soybean Yield Response to Foliar Fungicides Evaluated from 2005 to 2018 in the United States and Canada

Random-effect meta-analyses were performed on data from 240 field trials conducted between 2005 and 2018 across nine U.S. states and Ontario, Canada, to quantify the yield response of soybean after application of foliar fungicides at beginning pod (R3) stage. Meta-analysis showed that the overall mean yield response when fungicide was used compared with not applying a fungicide was 2.7% (110 kg/ha). Moderator variables were also investigated and included fungicide group, growing season, planting date, and base yield, which all significantly influenced the yield response. There was also evidence that precipitation from the time of planting to the R3 growth stage influenced yield when fungicide was used (P = 0.059). Fungicides containing a premix of active ingredients from multiple groups (either two or three ingredients) increased the yield by 3.0% over not applying a fungicide. The highest and lowest yield responses were observed in 2005 and 2007, respectively. Better yield response to fungicides (a 3.0% increase) occurred when soybean crops were planted not later than 21 May and when total precipitation between planting and the R3 application date was above historic averages. Temperatures during the season did not influence the yield response. Yield response to fungicide was higher (a 4.7% increase) in average yield category (no spray control yield 2,878 to 3,758 kg/ha) and then gradually decreased with increasing base yield. Partial economic analyses indicated that use of foliar fungicides is less likely to be profitable when foliar diseases are absent or at low levels.

The Change in Winter Wheat Response to Deoxynivalenol and Fusarium Head Blight Through Technological and Agronomic Progress

Fusarium head blight (FHB) in wheat causes yield loss, quality reduction, and mycotoxin contamination in temperate wheat production areas worldwide. The objective of this study was to quantify the progress of agronomic and FHB management strategies over the past two decades in FHB suppression and agronomic performance of winter wheat in environments favorable for FHB. Field experiments were conducted in environments typical of FHB epidemics to compare common agronomic and FHB management practices used in the 1996 era compared with those used in 2016. The experiments included a comparison of three different nitrogen (N) fertilizer application rates and six old (1996-era) and new (modern-era) winter wheat cultivars representing combinations of susceptibility and era to FHB, with and without a fungicide applied at flowering (pydiflumetofen + propiconazole). To mimic environments favorable for infection (similar to 1996 in Ontario, Canada), plots were challenged at 50% anthesis with F. graminearum macroconidia suspension followed by mist irrigation. The modern management strategy of using moderately resistant cultivars, a fungicide applied at flowering, and a high rate of N fertilizer reduced total deoxynivalenol by 67%, reduced Fusarium-damaged kernels by 49%, reduced FHB index by 86%, increased grain test weight by 11%, and increased grain yield by 31% compared with the standard management practice of seeding highly susceptible cultivars with no fungicide and a lower rate of N fertilizer recommended in the 1996 era. This study enabled a published economic assessment of the return on investment for the improvements in cultivars, fungicide, and N fertilizer applications since 1996.

Fusarium graminearum Mycotoxins in Maize Associated With Striacosta albicosta (Lepidoptera: Noctuidae) Injury

Western bean cutworm, Striacosta albicosta (Smith; Lepidoptera: Noctuidae) has become a key pest of maize, Zea mays (L.), in Ontario, Canada which is challenging to control due to its lack of susceptibility to most Bt-maize events. Injury by S. albicosta may exacerbate Fusarium graminearum (Schwabe; Hypocreales: Nectriaceae) infection through provision of entry points on the ear. The objectives of this study were to: investigate the relationship between injury by S. albicosta and deoxynivalenol (DON) accumulation; evaluate non-Bt and Bt-maize hybrids, with and without insecticide and fungicide application; and determine optimal insecticide-fungicide application timing for reducing S. albicosta injury and DON accumulation. The incidence of injury by S. albicosta and ear rot severity were found to increase DON concentrations under favorable environmental conditions for F. graminearum infection. Incidence of S. albicosta injury was more important than severity of injury for DON accumulation which may be due to larval consumption of infected kernels. The Vip3A × Cry1Ab event provided superior protection from the incidence and severity of S. albicosta injury compared to non-Bt or Cry1F hybrids. Insecticide application to a Vip3A × Cry1Ab hybrid did not reduce injury further; however, lower severity of injury was observed for non-Bt and Cry1F hybrids when pyrethroids or diamides were applied at early VT or R1 stages. DON concentrations were reduced with application of prothioconazole fungicide tank-mixed with insecticide at late VT (before silk browning) or when insecticide was applied at early VT followed by prothioconazole at R1. The application of an insecticide/fungicide tank-mix is the most efficient approach for maize hybrids lacking high-dose insecticidal proteins against S. albicosta and F. graminearum tolerance. Results demonstrate that reducing the risk of DON accumulation requires a strategic approach to manage complex associations among S. albicosta, F. graminearum and the environment.

The effect of artificial selection on phenotypic plasticity in maize

Remarkable productivity has been achieved in crop species through artificial selection and adaptation to modern agronomic practices. Whether intensive selection has changed the ability of improved cultivars to maintain high productivity across variable environments is unknown. Understanding the genetic control of phenotypic plasticity and genotype by environment (G × E) interaction will enhance crop performance predictions across diverse environments. Here we use data generated from the Genomes to Fields (G2F) Maize G × E project to assess the effect of selection on G × E variation and characterize polymorphisms associated with plasticity. Genomic regions putatively selected during modern temperate maize breeding explain less variability for yield G × E than unselected regions, indicating that improvement by breeding may have reduced G × E of modern temperate cultivars. Trends in genomic position of variants associated with stability reveal fewer genic associations and enrichment of variants 0–5000 base pairs upstream of genes, hypothetically due to control of plasticity by short-range regulatory elements.

Breeding has increased crop productivity, but whether it has also changed phenotypic plasticity is unclear. Here, the authors find maize genomic regions selected for high productivity show reduced contribution to genotype by environment variation and provide evidence for regulatory control of phenotypic stability.

Modeling effects of environment, insect damage, and Bt genotypes on fumonisin accumulation in maize in Argentina and the Philippines

Fumonisins are common contaminants of maize (Zea mays L.) grain products, especially in countries where maize is a major constituent of the diet and are harmful to human and animal health. There is a need to better define environmental conditions that favor fumonisin accumulation in the grain of maize. The impacts of biotic and abiotic factors, and hybrids containing the Cry1Ab protein from Bacillus thuringiensis (Bt), were associated with fumonisin accumulation in the grain of maize across contrasting environments in Argentina and the Philippines between 2000 and 2002. Average fumonisin concentrations in grain samples varied from 0.5 to 12 microg g(-1) across field locations in Argentina, and from 0.3 to 1.8 microg g(-1) across locations in the Philippines. The ratio of fumonisin B1 to fumonisin B2 was <3.0 in four of nine locations in Argentina, which proved to be due to a higher prevalence of Fusarium proliferatum in those locations. Most of the variability of total fumonisins among maize grain samples was explained by location or weather (47%), followed by insect damage severity in mature ears (17%), hybrid (14%), and with the use of Bt hybrids (11%). In Argentina, where conditions were more favorable for accumulation of fumonisin in the years considered, fumonisin concentrations were lower in Bt hybrids compared to their genetic isolines by an average of 40%. A model was developed to predict fumonisin concentration using insect damage to ears and weather variables as predictors in the model. Four periods of weather around silking were identified as critical for fumonisin concentrations at harvest. The model accounted for 82% of the variability of total fumonisin across all locations in 2 years of the study.

Effect of Bt-Corn Hybrids on Deoxynivalenol Content in Grain at Harvest

Concentrations of the mycotoxins deoxynivalenol (DON) and fumonisin B₁ in grain were compared among Bt-transformed corn hybrids and their non-Bt isolines on 102 commercial corn fields across Ontario from 1996 to 1999. Intensities of naturally occurring populations of Ostrinia nubilalis were assessed from tunneling measurements in the stalks of non-Bt isolines in 1996 and 1997. Mean concentrations of fumonisin B₁ across hybrids were <0.25 μg g^-1 in every year of the study. Relationships between the concentration of fumonisin B₁ and intensity of O. nubilalis or with the use of Bt corn hybrids could not be determined because the concentrations of fumonisin B₁ were below the lower limit of detection in most fields (<0.1 μg g^-1). However, DON was more prevalent with mean concentrations across fields from 0.42 μg g^-1 in 1997 to 1.12 μg g^-1 in 1999. The effect of Bt hybrids on reducing concentrations of DON was mainly dependent on the intensity of O. nubilalis in each field. Where a high intensity (stalk injury) of O. nubilalis was observed (>4 cm of tunnel per stalk in the non-Bt), the use of Bt hybrids reduced concentrations of DON by an average of 59% from concentrations in the non-Bt isoline. Where the intensity of O. nubilalis was low (<4 cm of tunneling per stalk), concentrations of DON were not different among Bt and non-Bt hybrids. Concentrations of DON were low and not different between events Bt11 and 176 among Bt hybrids. A quadratic relationship was developed showing that the concentration of DON increased with intensity of O. nubilalis feeding. This study cautiously supports the use of Bt corn to reduce the risk of high concentrations of DON at harvest in Ontario.

Using Weather Variables Pre- and Post-heading to Predict Deoxynivalenol Content in Winter Wheat

Substantial economic losses have occurred because of unacceptable concentrations of deoxynivalenol (DON) in wheat. Accurate predictions of DON in mature grain at wheat heading are needed to make decisions on whether a control strategy is needed. Our objective was to identify important weather variables, and their timing, for predicting concentrations of DON in mature grain at wheat heading. We measured the concentration of DON in 399 farm fields in southern Ontario, Canada, from 1996 to 2000. DON varied in field samples from undetectable to over 29 μg g^-1. Weather variables, such as daily rainfall, daily minimum and maximum air temperatures, and hourly relative humidity, were estimated for each field from nearby weather stations and were normalized to the date of 50% head emergence. Stepwise multiple regression procedures determined the most important weather variables and their timing around heading. DON was responsive to weather in three critical periods around heading. In the first period, 4 to 7 days before heading, DON generally increased with the number of days with >5 mm of rain and decreased with the number of days of <10°C. In the second period, 3 to 6 days after heading, DON increased with the number of days of rain >3 mm and decreased with days exceeding 32°C. In the third period, 7 to 10 days after heading, DON increased with number of days with >3 mm of rain. A relationship between relative humidity and DON was not detected. Overall, 73% of the variation in the concentration of DON was explained by using weather from all three critical periods. Concentrations of DON <2.0 μg g^-1 were predicted best; in fact, concentrations of DON of <1.0 μg g^-1 were predicted correctly on over 89% of the fields used to train the model.