Performing Department
(N/A)
Non Technical Summary
As agricultural production systems are confronted by unprecedented record-breaking flooding events that threaten crop growth and productivity, profitability, and sustainability of agricultural ecosystems and food security, three crucial questions emerge:1.How does flooding alter the functioning and structure of soil microbial communities that underpin plant and soil health.2. How does flooding impact corn plant growth and traits that putatively mediate plant and insect interactions.3. Can post-flooding nitrogen management recover lost yield potential and maintain crop productivity?This research addresses two Foundational Knowledge of Agricultural Production Systems priorities: 1) Determine how production systems can alter plant and soil microbiomes, the way alterations affect functions such as plant nutrient uptake, and resilience to insects and weather extremes associated with climate change and other stressors; and 2) Investigate how changes to cropping systems affect crop performance, soil health, and other outcomes beneficial to system resilience. This project will characterize the impacts of flooding and nitrogen management on soil microbiota, corn plant physiology and resilience, grain yield and nutritional quality, and defensive secondary metabolites - traits that are important mediators of plant and insect interactions. Nitrogen availability may be a strong determinant in plant recruitment of microbial communities and how they influence plant responses, such as ACC deaminase production, to flooding and final grain yields. Results will provide crucial foundational data about how soils, soil microbes, and corn plants are affected by flooding, which growers can use when making post-flood management decisions, thereby mitigating this stress for corn, America's most economically important crop.
Animal Health Component
50%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
(N/A)
Goals / Objectives
Overall Goal: To build critical foundational knowledge about plant and soil microbiome responses to flooding and evaluate how nutrient management shapes corn plant and soil microbiome responses and resilience during and after flooding. Specific Objectives:1. Characterize the impacts of flooding on the functioning and structure of soil microbial communities that underpin plant health.2. Characterize the impacts of flooding on corn plant growth and traits that putatively mediate plant and insect interactions (i.e., plant defensive secondary metabolites and nutritional quality).3. Determine how flooding impacts soil and fertilizer nitrogen cycling and availability for corn uptake and how post-flooding nitrogen management influences nutrient use efficiency and grain yield of corn.
Project Methods
This project involves both field experiments and laboratory experiments.Field Trials: The field experiments will be initiated at Champaign, Illinoison a field with a history of long-term corn-soybean rotation. The study will be a split-block replicated design, with replications (blocks) split by three different flooding regimes with eight independent sub-plots. The sub-plots will be a combination of four differing N management strategies applied to two commercial genotypes. The "No Flooding" treatment is representative of natural rainfall effects, serving as the negative control for response to flooding. Each flooding event will be applied using subsurface drip irrigation to maintain soil saturation in the top 15-inches of the soil profile for a period of seven -days. The four N applications serve to evaluate if in-season side-dress applications can mitigate N losses induced by early season flooding events, and what the optimum side-dress rate would be to maintain productivity.Plot Establishment and Treatment Application: Corn will be planted with a plot-planter at a target stand of 36,000 plants per acre. Plot rows one and eight will serve as plot borders while plot rows two through seven will serve as sampling rows. Flooding events and nitrogen applications will be initiated at the designated growth stages, and water will be metered through the Netafim irrigation system 1.5 inches per acre at a time until field saturation is met, followed by half-inch irrigation programs to maintain saturation for the seven day period.Sample and Data Collection: Sampling Dates: Sampling will be carried out at determined key dates during and after flooding and will coincide with the days when sampling for microbe determination is done. Sampling 1 will be conducted 15-25 days after planting, before the first flooding event, and will establish baseline data. Sampling 2 will be done 7 days after the first flooding event to establish the immediate impacts flooding has on defensive secondary metabolites and plant nutritional quality. Sampling 3 will be done 15 days after flooding event 1, but prior to the addition of nitrogen. Sampling 4 will be done 10 days after addition of nitrogen and before the second flooding event. Sampling 5 will be done 7 days after the second flooding event. Sampling 6 will be done 14 days after the second flooding event. Sampling 7 will be done 21 days after the flooding event is over.Objective 1: Characterize the impacts of flooding on the functioning and structure of soil microbial communities that underpin plant health.Microbiome Analysis: Our approach is based on the evaluation of known traits of plant growth promoting rhizobacteria (PGPR) (Fierer et al, 2021).qPCR. A high-throughput microfluidics quantitative PCR (qPCR) approach for detecting and quantifying genes that contribute to plant health and stress tolerance will be used. This will enable evaluation of the presence and abundance of a suite of microbial genes responsible for PGPR traits on up to 96 samples at once. We will evaluate a suite of PGPR genes from samples collected in at each time point and identify those microbial traits that vary in presence or abundance in response to flooding treatments or management interventions. Presence, abundance, and diversity of the target functional genes will be correlated with data collected on soil chemical and physical factors, crop phenology, and management strategy.Amplicon-based sequencing. We will also carry out high throughput DNA sequencing on bacterial and fungal communities using conserved primers for prokaryotic 16S V4 region and fungal ITS2, in a multiplexed assay design using the Fluidigm Access array, followed by sequencing on the Illumina NovaSeq platform. DNA services will be performed by the Keck Center for Functional Genomics at the University of Illinois campus.Bioinformatics. Barcoded Illumina amplicon sequencing reads will be demultiplexed, paired reads will be merged and filtered for sequence quality, and sequences will be further processed using bioinformatics pipelines commonly used in the Kent lab.Objective 2: Characterizing the impacts of flooding on maize plant growth and traits that putatively mediate plant and insect interactions (i.e., plant defensive secondary metabolites and nutritional quality.Determining the Impact of Flooding on Corn Plant Defensive Secondary Metabolites (Leaf and Root Metabolite Analysis): Maize plant defensive secondary metabolites determination will be done at the University of Illinois at Urbana Champaign Metabolomics Facility. Five biological replicates will be used for each treatment. Untargeted LC/MS root and leaf metabolite profiling will be done.Leaf Total Phenolic Content: The content of total phenolic compounds will be determined colorimetrically using the Folin-Ciocalteu reagent, as described in Ainsworth and Gillespie, 2007.Determining the Impact of Flooding on Corn Plant Aboveground and Belowground Growth and Nutritional Quality: Six replicates per treatment will be used. We will measure plant protein content with a Bradford assay and the non-structural carbohydrate content using the phenol-sulphuric acid method following the protocol of Dubois et al. (1956) and Deans et al. (2018). Total carbon and nitrogen contents will be determined with an elemental analyzer following standard protocols by Chen et al. (2015).Objective 3. Determine how flooding impacts soil and fertilizer nitrogen cycling and availability for corn uptake and how post-flooding nitrogen management influences nutrient use efficiency and grain yield of corn. Crop Emergence and Standability: At emergence, plot stand of yield rows will be calculated to establish plant population prior to flooding. Prior to the second flooding event, the plot stands will be re-tallied to determine if the initial flooding event reduced the final crop population. A final plant stand will be evaluated at physiology maturity to assess seasonal impacts of treatment effects on plant stand.Crop Nutrient Uptake, Biomass Accumulation, and Grain Yield: Plant samples will be collected at the soil surface at the V6, V10, VT, and R6 growth stages and evaluated for total biomass and tissue nutrient concentrations to calculate total plant nutrient uptake following the flooding events and nitrogen applications. Following crop maturity, the plot rows six and seven will be mechanically harvested with a rotatory plot combine for determination of final grain yields standardized to 15.5% moisture. Subsamples of harvested grain will be used for determining grain protein, oil, and starch concentrations using a NIT grain analyzer.Data analysis: Multivariate ordinations performed in the R statistical environment will be used to evaluate patterns in composition and abundance of microbial abundance and identify taxa and functional groups associated with agronomic treatments. FUNGuild will be used to assign fungal OTUs to ecological classifications, allowing us to compare the relative abundance of fungi that potentially contribute positively or negatively to soil health. Ecological functions will be assigned to soil bacterial communities using Functional Annotation of Prokaryotic Taxa Significance tests on functional pathway abundance will be performed using ANOVA-Like Differential Expression (ALDEx2). Metabolite data will be analyzed using protocols by Das et al. (2017). Phenolic content, plant growth and nutrition data will be analyzed using ANOVA. Crop nutrient uptake, biomass accumulation and grain yield data will be analyzed with a linear mixed model using PROC MIXED of SAS and means separation will be determined using the LSMEANS statement with the PDIFF option. Multivariate approaches will be implemented from data across all three objectives to determine patterns and collinearity among measured factors, and to discover patterns in the data set.