Mapping Soil Microbiome Shifts During Pythium Disease Development in Soybean Seeds and Seedlings Under Different Management and Soil Conditions

Progress report for GNE20-237

Project Type: Graduate Student
Funds awarded in 2020: $14,986.00
Projected End Date: 09/30/2022
Grant Recipient: The Pennsylvania State University
Region: Northeast
State: Pennsylvania
Graduate Student:
Faculty Advisor:
Paul Esker
The Pennsylvania State University
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Project Information


Seedling diseases are one of the top five most destructive soybean diseases in the Northern United States with an estimated 500,000 bushels lost in Pennsylvania in 2018 (Crop 2020). Pythium spp. is one important soilborne pathogen that can be suppressed by soil organisms like Trichoderma or increase in severity in the presence of other soilborne pathogens. This study’s objective is to further elucidate the microbiome’s role in Pythium disease development by assessing how microbiome composition shifts in bacterial and fungal abundance and diversity during Pythium disease development is predictive of disease severity in soybean. This interaction will be assessed under common management practices and soil conditions including fungicide seed treatments, soil pH, flooding, and soil sand/silt/clay content using a novel rhizobox design for non-destructive daily rhizosphere sampling in greenhouse and field experiments. Pythium qPCR, 16S-rRNA bacterial gene sequencing and ITS fungal gene sequencing using MiSeq will be used to visualize the abundances and diversity of fungal and bacterial microbiome members.

Mixed analyses including principal coordinates analysis, linear discriminant analysis, and correlation network analysis will identify treatment variations and relate microbiomes to disease severity. I hypothesize that certain management practices support a suppressive microbiome and that potential biocontrol organisms will be identified that can support sustainable agriculture. Results will be published in a peer-reviewed scientific journal, presented at professional and farmer meetings, and compiled with videos and photos from the experiments for public dissemination as factsheets, online educational resources, and extension teaching materials to promote adoption of sustainable management practices.

Project Objectives:

Objective 1: Determine how common PA soybean production management practices and field conditions such as fungicide seed treatments, soil pH, flooding, and soil sand/silt/clay content impact shifts in bacterial and fungal composition and diversity during pre- and post-emergence Pythium disease in soybeans up to two weeks after planting using both greenhouse and PA research field experiments.

Objective 2: Determine how shifts in soil microbiome fungal and bacterial diversity and abundance during Pythium disease development relate to the severity of disease after two weeks from planting.

Objective 3: Identify key fungal and bacterial taxa in the soil microbiome involved in synergism with or inhibition of Pythium disease development under the different management and soil conditions, supporting future studies delving into the pathogen-interaction mechanisms that can be developed into viable sustainable management options such as biocontrols.


The purpose of this project is to identify keystone species or microbial groups in the soil microbiome associated with increased Pythium disease severity under different soil conditions and management practices to determine the indirect effects of these practices on disease outcomes. This is approached by determining shifts in bacterial and fungal soil microbiome abundance and diversity during Pythium disease development in soybean grown during the initial two-week emergence period after planting. Results will inform the timing and choice of sustainable management tactics that reduce the impact of Pythium and other early seedling diseases.

Seedling diseases are regularly one of the top five most destructive soybean diseases in the Northern US and Ontario, Canada, with over 60 million bushels lost to these diseases in 2014 (Allen et al 2017). Pythium is a ubiquitous soilborne oomycete and one of several pathogens causing pre- and post-emergence damping off, or seedling death from root rot, in multiple economically important crops like corn and soybean. It is especially problematic in the Northern US due to the wet weather and cooler conditions at planting that promote disease development. Disease severity is also influenced by other soil organisms, such as suppression by Trichoderma or increased severity with Fusarium. Pythium is commonly treated using fungicide seed coatings; however, these do not always perform well and the reason is not completely clear. I hypothesize that the fungicide’s unintended impacts on the microbiome and natural beneficial soil organisms plays a role in why they fail; therefore, I will test these treatments as well as other soil and management conditions in this project. My research will improve knowledge on the unintended effects of fungicides and promote consistent efficacy for long-term use.

Overall, this project contributes to agricultural sustainability by identifying best practices promoting a disease suppressive soil microbiome that can protect crops across growing seasons. I hypothesize that we will identify future biocontrol organisms that can be introduced into soils for long-term benefits and reduce farmer’s dependence on fungicide seed treatments. As soybean prices fluctuate from trade wars, weather losses, and changing demand the extra cost of approximately $10/acre for fungicide treatments are risky given their variable efficacy against Pythium and other soilborne organisms. Additionally, Pythium populations have been known to develop fungicide resistance, such as to metalaxyl, and rotating management strategies can decrease the risk of this occurring. It is important for the economic sustainability of the farm enterprise to have reliable alternatives for treating seedling diseases that reduce inputs while supporting productivity. Additionally, public health and environmental concerns and costs associated with fungicide use can be alleviated. Manipulating the soil microbiome is an environmentally conservative way to address soilborne seedling diseases like Pythium for the long term. Results from these studies will be disseminated to different stakeholders to improve understanding of the role of the microbiome in seedling disease development, I will create educational resources for farmers, extension, and scientists for use in presentations, to reference for management decisions, and for developing new research projects surrounding agricultural sustainability.


Materials and methods:

Objective 1

I hypothesize that under different management or soil conditions different fungal and bacterial microbiome compositions will be present and that throughout Pythium disease development, these compositions will change in both abundance and diversity. I expect to see commonalities among several key taxa across treatments that indicate a relationship with Pythium disease or host plant development. To test this, I conducted a greenhouse experiment to isolate individual plant associated soil microbiomes during Pythium disease development, which will be followed by a research field experiment to verify these interactions when plants exist in communities and soil microbes can migrate more freely in a less controlled environment.

There will be four different management or soil conditions that are present in PA soybean production systems considered: soil types, pH levels, soil saturation, and fungicide seed treatments. Each treatment will have four rhizobox replicates to verify that shifts seen are statistically similar across plants in each treatment; three of the replicates will have their soil sequenced and the fourth replicate sample will be left untouched unless needed for additional analysis later. 

Soils focused on in the final analysis are all unsterilized and inoculated with Pythium sylvaticum due to the nature of the study to preserve the inherent microbiome as closely as possible and observe microbiome changes under disease pressure; however, sterile inoculated and un-inoculated controls were also included for additional analysis later as needed. Soil for sterile controls was autoclaved at 121 degrees Celsius for 30 mins. Soil was collected into tubs from the top six inches of soil and mixed with sand to a volume ratio of 20:80 to prevent compaction in the greenhouse which could influence emergence unrelated to Pythium. Extra soil than required was collected for the experiment and stored in a cold room for later use as needed. 

  • For soil type comparison, a silty clay soil from Rock Springs Research Farm was compared to a sandy loam soil sourced from a production field owned by Patton Township, PA. Additionally, soil from two other fields were collected that were expected, based on historical tests, to have higher and lower pH values within the range that soybeans are grown for use as a pH treatment. All four soils underwent testing at the Penn State Agricultural Analytical Services Lab for fertility, OM and N content, and soil particle size testing to provide context for final results and treatment values. Actualized higher and lower pH values were 6.5 and 7.3. Soil from one field in Rock Springs was used for all the other treatments (fungicide and soil saturation).
  • The seed fungicide Allegiance was applied as directed and used to determine how fungicides impact non-target organisms in the soil microbiome that play a role in Pythium disease development so that more informed recommendations for seed treatment fungicide use are provided to farmers. 
  • Saturated soil, exacerbated in PA by climate change precipitation patterns, is both a plant stressor and a key abiotic driver behind Pythium disease development. It also plays a role in the fate of fungicides and their efficacy; therefore, saturated soil with and without fungicide treated seeds was considered. These treatments received daily watering to drip-through excess and soil moisture content data was collected with a probe to verify a difference between saturated and unsaturated treatments. 

For control purposes, all soils with the exception of sterile uninoculated controls, were inoculated with pathogenic Pythium sylvaticum isolated previously from a PA soybean field to ensure pathogen presence. This organism was grown on half PDA agar for four days and two plugs taken from these plates were placed about an inch apart on either side of where the seed would be placed prior to filling the rhizoboxes and pots with the top soil and watering. Seeds were planted after a day of adding inoculum and a small layer (<1 cm) of sterilized perlite was put on top of all planted soil. A single soybean variety with untreated and fungicide treated seeds was grown in the rhizoboxes. Plants are grown for two weeks from planting in both the greenhouse and field experiment, held in May 2021 and April 2022 respectively.

Experiment Input & Moisture Test Photos

Soil in Probe
Soils in Probe
Pythium Cultures
Cultures of Pythium sylvaticum
Soil Moisture Test
Soil Moisture Tests of Pots & Rhizoboxes












Experiment Design

A total of 54 plants were grown in rhizoboxes for the greenhouse experiment. Each of the four soil types had three sterile uninoculated and three sterile inoculated controls for the first 24 boxes. Plants grown without Pythium provide a baseline for plant growth in a disease-free environment, while inoculated controls offer a comparison for disease severity and microbiome changes given no management practices. The rest of the rhizoboxes, used for the sequencing portion of this study, were comprised of four boxes per treatment (four different soils, fungicide, fungicide + water, and water only) with the exception of the soil type used for the latter three treatments which had six boxes. This soil can provide an additional treatment for comparison in the different management scenarios, particularly acting as the untreated seed treatment in the fungicide assessment.

Since Pythium causes pre-emergence issues and we wanted to ensure enough plants grew for post-emergence disease evaluation, each treatment also had one pot containing six seeds spaced about 2 inches apart so that in total 144 plants were grown for the greenhouse experiment. These pots also provide an additional point of comparison for field experiment results, where plants are also grown in close proximity to each other. 

Plants were randomly assigned to a new location in the greenhouse each day to avoid location bias, although all plants fit on a single table in the greenhouse and were in close proximity to each other regardless. Soil saturation treatment plants were watered daily and all other plants were watered at the same time as needed. Greenhouse conditions, such as relative humidity and temperature, were recorded continuously over the experiment timeframe using a Govee bluetooth device.

After final soil samples were collected and greenhouse plants were harvested, leftover soil was discarded and the rhizoboxes cleaned and bleached sterilized in preparation for the field experiment. Field plots will first be planted with soybean seeds before a slice of soil is removed for the rhizobox set with a single seed. Rhizoboxes will return to the same location each day after sampling. This simulates field conditions where plants grow in proximity to each other and microbes can move from the surrounding soil in and out of the rhizosphere. There is minimal control over environmental factors, although flooded treatments will receive water daily to maintain saturation.

There will be no sterilized controls for the field study; unaltered soil from the primary field that was used in the greenhouse experiment will act as the control with eight replicates. All treatments will have four rhizobox replicates. There is no soil type treatment proposed for the field experiment. Altogether, 28 plants will be grown in rhizoboxes for the field experiment. Several random pre-selected soybean plants outside of the rhizoboxes within the treatment plots will also be evaluated and have starting and ending microbiome samples collected. 

Greenhouse Experiment Setup Photos

Greenhouse Experiment Setup
Pots & Rhizoboxes in Greenhouse Experiment
Pot Inoculation
Pot Inoculation
Rhizobox Planted
Rhizobox Planted












Sample Collection

The novel use of rhizoboxes has the advantage of enabling multi-day non-destructive rhizosphere soil sample collection and use over multiple experimental runs with sterilization. Boxes were designed using Tinkercad and 3D printed at the Media Commons at the Penn State University Library. 3D printing the boxes allowed for personalization and uniformity of the final boxes and provides a template that can be easily utilized by other researchers. 

3D Printed Rhizoboxes

Video of rhizobox being printed at the Penn State Libraries Media Commons, from 3DPrinterOS

These opaque square boxes have small holes in the bottom for drainage, holes for twist-tie handles at the top to make handling easier, and holes in the sides for sampling. These holes also allow for microbial movement between the rhizobox and the surrounding soil in the field setting. Pieces of sterilized plastic straws cut in half and 'ribbed' in the middle were placed within the holes and were filled with soil. Each day of sampling a straw was taken, in the same order for each box, from the top to bottom of the box and the soil placed in a sterilized test tube. The seed was placed right between the top straws so that samples were collected from the relevant soil zone at the start and over time the roots grew down between and into the straws so that samples throughout the two weeks were taken from as close to the plant as possible. Boxes had a black plastic bag 'slip' pulled over the straws on the outside and held on by rubber bands to help hold in moisture and limit contamination from the external environment, especially once straws were removed for sample collection and open space/exposed roots were present within the rhizobox. 

To get an initial idea of what we might expect to see in the field when soybeans are grown in close proximity and microbe movement is more unhindered, pots for each treatment containing six soybean seedlings spaced approximately 2 inches apart were added to the original greenhouse experiment design. Samples for these were collected at the start and end timepoints only, which are expected to be the most important timepoints, with visual observations noted for these plants. Soil was collected off the roots of the plants at harvest, as well as from the bulk soil near the roots. 

Daily soil samples, environmental condition data (temperature, relative humidity, and soil moisture), and plant growth observations were collected over a period of 14 days in order to capture Pythium disease during early seedling development. This allows for determining the relative rate of soil microbiome changes and best sampling frequency that can be used for future studies. A soil sample was collected prior to planting to identify the original microbiome composition, then several hours post-planting when Pythium can start attacking seeds. Subsequent sampling occurred once per day until day 14 when seedlings in the rhizoboxes were harvested for visual disease assessment and plant growth parameters evaluated like root/shoot length and dry biomass. Samples for Days 1 to 14 were collected from straws and other samples were taken from bulk soil. Pots were harvested on Day 15 due to the volume of plants that needed to be harvested and assessed. 


Sequencing & Analysis

Initial sequencing is done for three replicates of each non-sterile treatment set, with other replicate samples untouched. One random replicate has samples sequenced for each day from 0 (post-inoculation, pre-planting) to 14 (harvest). The second replicate has samples sequenced for days 1, 3, 5, 7, 9, 11, 13, & 14. The third replicate has samples sequenced for days 1, 7, and 14. Pre-inoculation soil samples were sequenced from the pots to represent each treatment. 

This sampling scheme allows for sequence results at the timepoints hypothesized to be the most important across all replicates, balancing a manageable number of samples to sequence with what will allow for meaningful analysis. Replicates selected for each specific sequencing group, in terms of number of days sequenced, were selected using standardized selection parameters across treatments based on experiment plant growth and disease severity. Soil samples from un-sequenced days and the untouched replicates will be stored for future analysis as needed for statistical purposes. Overall, 17 samples are collected from each plant and a subset of these are initially analyzed. 

DNA extraction for each soil sample will be used to run three PCR sets including 16S-rRNA bacterial gene sequencing, ITS fungal gene sequencing and qPCR for Pythium to verify and quantify its presence in the microbiome. 16S-rRNA and ITS PCR products will be used for MiSeq sequencing at the Penn State Genomics Core Facility. Sequencing data will be processed using UPARSE and UCHIME in the open-source software Mothur. Principal coordinates analysis in R will be used to visualize soil microbiome compositions at each timepoint, with variation in initial soil physicochemical properties visualized using principal components analysis. AMOVA and significance tests will be used to understand differences between treatments. Altogether, this genomics data will be used to visualize the abundances and diversity of fungal and bacterial microbiome community members throughout Pythium disease development.


Objective 2

In this objective, my hypothesis is that abundance of particular fungal and bacterial taxa in the soil microbiome at different timepoints in Pythium disease development will be predictive of Pythium disease severity. To test this, Pythium will be first classified as pre- or post-emergence disease. Photos will be taken throughout the growth period to visualize disease development. After 14 days plants will be harvested, photographed, root and shoot length measured (centimeters), and shoot and root dry weight biomass (grams) determined to relate to disease severity.

Visual disease assessment is challenging and to limit bias two scales were used, 0 to 4 and 0 to 9, to capture differences in how the symptom severity is perceived.  Both roots and shoots were assessed for a total of 4 ratings per plant. Root symptoms for visual ratings include germination failure, lesions, brown discoloration, and necrosis, while seedling symptoms focused on brown spots, chlorosis, and wilting or lost leaves.

Root severity ratings are adapted from the literature and assessed for all plants on a scale of 0 to 9, where 0 = <10% of root exhibits symptoms or has no obvious symptoms, 1 = 10-20% of root exhibits symptoms, etc., 9 = symptoms fully present on root, plant dead or germination failure. The 0 to 4 scale ranges from 0 = no obvious root symptoms, 1 = < 25% root has symptoms, 2 = < 50%, 3 = < 75%, and 4 = symptoms fully present on root, plant dead or germination failure.

Post-emergence diseased plants are rated on a 5-point scale of presence of above-ground symptoms where 0 = no visual disease symptoms (healthy plant), 1 = few small lesions or light discoloration (< 25%), 2 = mid-sized or many small lesions, moderate discoloration (< 50%), 3 = large or many midsized lesions, severe discoloration and wilting occurring (< 75%), 4 = completely symptomatic, wilted or plant dead. The 0 to 9 scale ranges from 0 = <10% of shoot exhibits symptoms or has no obvious symptoms, 1 = 10-20% of shoot exhibits symptoms, etc., 9 = symptoms fully present on shoot, plant dead or germination failure. 

Shoot symptom ratings will be linked to the root severity ratings in analysis, with both ratings analyzed in relation to other observations like root and shoot length and biomass. Building off the statistical analysis under Objective 1, linear discriminant analysis and significance tests will be used to identify key taxa and their relative abundances at different timepoints related to final Pythium disease severity.

Disease Severity Photos

Harvested Plants from Water Saturation Treatment
Rhizobox Plant Treatment Comparison Set
Spots on Leaves
Example of Spot Leaf Symptoms
Root Photo
Example of Root with Some Discoloration












Objective 3

The hypothesis for this objective is that several key fungal and bacterial taxa in the soil microbiome will drive severity or suppression of Pythium disease. To test this, I will use results from Objective 1 to conduct a correlation and co-occurrence network analysis using a combination of the open-source software R, Netshift, and Cytoscape. These analyses identify highly interactive “hub” microbes and determine their potential for being keystone microbiome members during Pythium disease development by quantifying directional changes in individual taxa interactions. Results from this objective are important to provide insight into organisms that can be considered as future biocontrol options or alternative organisms to target with management practices to suppress Pythium disease severity.

Research results and discussion:

The greenhouse experiment, with added pots as a preliminary 'field' test, was conducted in May 2021 and the actual field experiment was moved to April 2022 to allow for time to reflect on the experimental design and make any necessary changes to ensure quality research results. Although sequencing is not complete for the greenhouse samples, observational data of differences between all the treatments were noted. These will be linked to the sequencing results to make final conclusions regarding the objectives. 


Preliminary Data

The high and low pH soils used in this experiment were selected based on expected characteristics from previous soils tests, as the results from the soil we sent to the lab were not received until after the experiment began. Although we ended up with a well-scaled pH range of 6.5 to 7.3 across all four soils, the experiment treatment labeled as low pH had a neutral pH and the sandy loam used in the experiment had the lowest pH. Based on the fertility tests, the sandy loam's pH of 6.5 is below optimum. 

All four soils had levels of the trace element sulfur below the normal range found in PA soils. All but the sandy loam had less copper than is typically found in PA soils. The low pH soil had both magnesium and potassium levels below optimum. Both the high pH soil and silty clay soil had magnesium levels above optimum, while the sandy loam had phosphorus levels above optimum. The primary soil used in the experiment had low phosphorus, potassium and zinc. The levels of some of these nutrients outside their optimal or typical range could explain some of the symptoms seen in the experiment across treatments. The impact of these different soil characteristics will be evaluated in later analyses with sequencing results. 

Soil Characteristics Data


Overall, for the pots and rhizoboxes combined, no clear differences or patterns are seen in shoot and root lengths and dry weight between treatments. Based on Tukey tests, the only significant difference in the non-sterile soils was seen between the silty clay and sandy loam treatments for shoot weight. This may be because the experiment was only run over a two week period and significant differences in these variables across treatments could take longer to develop.

Biomass and Length Data

Based on Tukey tests, for the root high and low score the sterile uninoculated sandy loam soil was significantly different across a range of treatments and compared to the sterile inoculated sandy loam soil.

For the shoot high and low scores a variety of treatments were significantly different than each other. For example, the soil saturation treatment was rated significantly lower than any of its controls. Furthermore, the water treatment enhanced the the effect of the fungicide treatment by lowering the shoot severity rating. All three other soils scored significantly lower than the silty clay treatment and further analyses on soil and microbiome characteristics may define more precisely why this difference was seen.  

Not all sterile controls were significantly different than their corresponding treatments and some scored poorly. Microbes can assist plants in various ways such as with nutrient uptake and growth and their absence in the sterile soils could cause deficiencies. Particularly, soybeans benefit from nitrogen-fixing rhizobia in the soil microbiome and rhizobia nodules were not noted in the sterile soils but were observed on non-sterile plants. A clearer understanding of the microbiome associated with early soybean development will be determined with the analysis of sequencing results. 

Disease Severity Ratings Data

Research conclusions:

The greenhouse experiment was conducted and visual differences between treatments were observed; however, research conclusions related to the objectives will be made once sequencing is complete. The field experiment will be conducted in April 2022 and data from that experiment will strengthen any final conclusions. 

Participation Summary

Education & Outreach Activities and Participation Summary

1 Webinars / talks / presentations

Participation Summary:

5 Number of agricultural educator or service providers reached through education and outreach activities
Education/outreach description:

A major goal of this project is to provide the scientific community fundamental knowledge of how management practices impact the soil microbiome compositional shifts during Pythium disease development and to identify keystone taxa with potential to either suppress or increase disease severity. These results are important to support in-depth studies of these alternative microbe-pathogen interactions and biocontrol mechanisms while also promoting sustainable management production practices. Most educational and outreach aspects of this project will be completed in 2022, as outlined in the original project timeline. 

This research has been presented as part of the Penn State Department of Plant Pathology and Environmental Microbiology Departmental Lecture Series, which is open to the public and other researchers in-person and via Zoom, in April 2021 and another seminar will be given as part of this series at the end of the project. Project information and results distribution will also occur via a Penn State News article at the end of the project, which is regularly received by all members of the university. Results from this research will be submitted to a peer-reviewed journal for publication and published as an abstract to present at the 2022 Annual Meeting of the American Phytopathological Society (APS). 

Photos of the treatment replicates and experimental design will be used in educational materials to illustrate the methodology to support future research on Pythium disease development stages and severity. Additionally, videos will be taken of various experimental processes such as sample collection to teach students and researchers on new methodologies and experimental design, as well as to educate the farmers and public who are typically disconnected from the off-farm side of research on scientific methods. Adobe products such as InDesign, Illustrator, & Premiere Pro will be used for editing and compilation into polished videos, factsheets, and pamphlets. Most outreach materials will be developed in 2022, after the field and greenhouse experiments are completed and data is analyzed.

These resources will be actively shared through extension, social media platforms, and scientific communities such as APS. Results and educational materials from this project will be presented to soybean farmers through the PA Soybean On-Farm Network, a program with annual workshops for soybean farmers. A free peer-reviewed publication in the APS online journal, The Plant Health Instructor, will focus on an educational overview of how the soil microbiome supports or suppresses Pythium disease given different management and soil conditions. I will also publish educational articles in Field Crop News from Penn State Extension and the Field and Forage Crops Group. Most publications will be submitted in 2022, after the field and greenhouse experiments are completed and data is analyzed.

Project Outcomes

Project outcomes:

This project is still in progress; this section will be updated after sequencing analysis has been completed for both experiments. I expect that the knowledge generated from this project will help farmers make educated management decisions such as related to reducing fungicide usage which has economic, environmental, and social benefits. Additionally, I expect to identify potential biocontrol candidates and characterize a Pythium suppressive soil microbiome that can limit disease in soybean fields long-term with limited inputs. 

Knowledge Gained:

This project is still in progress; this section will be updated after sequencing analysis has been completed for both experiments. At this stage, I have a better understanding of the skills required for and challenges involved with microbiome research. I acknowledge that research to support sustainable agriculture requires a multi- and inter-disciplinary approach and connectivity between various studies. This also needs to be complemented with farmer peer feedback and support, which can be gained by conducting these studies via on-farm research programs, to promote stakeholder buy-in for implementing sustainable agriculture practices. Overall, I also recognize that shifting toward sustainable agriculture will take time and requires a dedicated team effort.

I am very interested in pursuing interdisciplinary research in my future career because I enjoy the refreshing experience of seeing the same research project from different perspectives and integrating those perspectives to develop and conduct successful research endeavors. I am particularly interested in working at the nexus of food and animal agriculture, with a focus on food safety and security under sustainable agriculture production. I want to be involved in science communication with non-scientists as well as science policy to support sustainable agriculture.

Assessment of Project Approach and Areas of Further Study:

The rhizobox sampling method generally worked well; in some cases roots were growing directly in the sampling straw so one knew that soil was being collected as close to the roots as possible. After the straws were removed, often the holes would be left open (the soil didn't always collapse in) which may have influenced plant growth or outside microbiome contamination. Some plants had losses in biomass due to leaves dropping from symptoms or accidently torn off when removing covers. Additionally, root losses may have occurred when extracting plants at harvest from boxes and soil. 

Preparation, particularly, of the straws was rather tedious and time-consuming and the initial set up and harvesting for the experiment was a bit overwhelming for the small team available during the pandemic (PI, plus 1-2 graduate students at times). Not all plants grew during tests of the rhizobox design, which was expected due to germination failure or disease, so additional plants were added in the greenhouse experiment via pots to ensure enough data was available related to post-emergence disease. However, very nearly all plants (over 140) emerged during the actual greenhouse experiment, leading to significantly more effort required at harvest than was expected. 

Root disease severity is challenging to visually rate and personally I found the 0-4 rating scale easier to use than the 0-9 scale. Photos were taken of the roots and shoots against a blue background that can be used for computer-based disease severity rating later on to add confidence to the manual assessment. The fact that nearly all plants emerged and had comparable root and shoot biomass and lengths across treatments and controls suggests that Pythium inoculation may have not been successful. Of note, May 2021 was exceptionally warm (70s-90s in Fahrenheit) during the early part of the experiment and this could be why plants grew well, as Pythium prefers cool temperatures. Plants primarily exhibited leaf symptoms, such as chlorosis and brown spots, which were not necessarily related to Pythium disease. Some nutrients were identified as outside the normal or optimal range for each soil type in the soils analysis, which could in part explain leaf symptoms. When sequencing analysis is completed, even if Pythium inoculation and disease was not successful, this experiment provides valuable insight into the soil microbiome's association with early soybean seedling development and how it is impacted by the various management scenarios to observable ends (i.e. root/shoot length, etc).

Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.