Civic Intelligence

North Central Soybean Research Program

990 • Fiscal year 2016 • EIN 42-1394799

Oct 01, 2015 to Sep 30, 2016 • Filed on Dec 15, 2016

1255 Prairie Trail ParkwayAnkeny, IA 50023

(515) 251-8640

Siviq Scores

Precomputed percentiles for this filing year versus similar nonprofits in the same peer cohort.

Liabilities / Assets

76th percentile

0.43x

Higher debt load relative to assets than 76% of similar nonprofits.

2016 filings • 501(c)3 • $1M-$5M nonprofits • Source year 2016

Liabilities / Revenue

76th percentile

0.48x

Higher debt load relative to revenue than 76% of similar nonprofits.

2016 filings • 501(c)3 • $1M-$5M nonprofits • Source year 2016

Net Margin

11th percentile

-32%

Higher net margin than 11% of similar nonprofits.

2016 filings • 501(c)3 • $1M-$5M nonprofits • Source year 2016

Top Officer Pay

35th percentile

$0

Higher top officer pay than 35% of similar nonprofits.

Top officer pay equals 0.0% of source-year revenue.

2016 filings • 501(c)3 • $1M-$5M nonprofits • Source year 2016

Asset Growth

10th percentile

-13%

Faster asset growth than 10% of similar nonprofits.

2016 filings • 501(c)3 • $1M-$5M nonprofits • Annualized from 2015 to 2016

Revenue Growth

71st percentile

14%

Faster revenue growth than 71% of similar nonprofits.

2016 filings • 501(c)3 • $1M-$5M nonprofits • Annualized from 2015 to 2016

Assets

Down

$4,021,013

Down $584,439 (-13%) from 2015

Net Assets

Down

$2,291,542

Down $1,164,026 (-34%) from 2015

Liabilities

Up

$1,729,471

Up $579,587 (+50%) from 2015

Revenue

Up

$3,634,684

Up $455,138 (+14%) from 2015

Expenses

Up

$4,798,710

Up $4,590,502 (+2205%) from 2015

Net Income

Down

-$1,164,026

Down $4,135,364 (-139%) from 2015

Historical Trend

Balance Sheet Trend

The highlighted filing sits inside the broader history for assets, liabilities, and net assets.

$6.0M$4.0M$2.0M$0Assets 2010: $2,073,215Liabilities 2010: $1,906,197Net Assets 2010: $167,0182010Assets 2011: $3,426,376Liabilities 2011: $3,089,693Net Assets 2011: $336,6832011Assets 2012: $3,158,091Liabilities 2012: $2,327,232Net Assets 2012: $830,8592012Assets 2013: $2,755,586Liabilities 2013: $1,874,749Net Assets 2013: $880,8372013Assets 2014: $3,085,290Liabilities 2014: $2,601,060Net Assets 2014: $484,2302014Assets 2015: $4,605,452Liabilities 2015: $1,149,884Net Assets 2015: $3,455,5682015Assets 2016: $4,021,013Liabilities 2016: $1,729,471Net Assets 2016: $2,291,5422016Assets 2017: $3,051,153Liabilities 2017: $1,576,011Net Assets 2017: $1,475,1422017Assets 2018: $2,229,927Liabilities 2018: $0Net Assets 2018: $2,229,9272018Assets 2019: $2,090,649Liabilities 2019: $0Net Assets 2019: $2,090,6492019Assets 2020: $1,500,843Liabilities 2020: $0Net Assets 2020: $1,500,8432020Assets 2021: $1,947,025Liabilities 2021: $0Net Assets 2021: $1,947,0252021Assets 2022: $2,007,367Liabilities 2022: $0Net Assets 2022: $2,007,3672022Assets 2023: $1,250,047Liabilities 2023: $0Net Assets 2023: $1,250,0472023Assets 2024: $1,391,103Liabilities 2024: $0Net Assets 2024: $1,391,1032024Assets 2025: $2,328,941Liabilities 2025: $0Net Assets 2025: $2,328,9412025

Highlighted filing

2016

Assets$4,021,013
Liabilities$1,729,471
Net Assets$2,291,542

Operations Trend

Revenue, expenses, and net income across loaded years, with this filing highlighted.

$6.0M$4.0M$2.0M$0-$2.0MExpenses 2010: $2,930,1092010Expenses 2011: $3,537,1252011Expenses 2012: $2,959,5082012Expenses 2013: $2,941,9762013Revenue 2014: $2,857,172Expenses 2014: $3,253,779Net Income 2014: -$396,6072014Revenue 2015: $3,179,546Expenses 2015: $208,208Net Income 2015: $2,971,3382015Revenue 2016: $3,634,684Expenses 2016: $4,798,710Net Income 2016: -$1,164,0262016Revenue 2017: $3,280,752Expenses 2017: $4,097,152Net Income 2017: -$816,4002017Revenue 2018: $3,282,467Expenses 2018: $4,070,836Net Income 2018: -$788,3692018Revenue 2019: $3,706,023Expenses 2019: $3,845,301Net Income 2019: -$139,2782019Revenue 2020: $4,177,896Expenses 2020: $4,767,702Net Income 2020: -$589,8062020Revenue 2021: $3,288,352Expenses 2021: $2,842,170Net Income 2021: $446,1822021Revenue 2022: $3,793,482Expenses 2022: $3,733,140Net Income 2022: $60,3422022Revenue 2023: $4,737,897Expenses 2023: $5,495,217Net Income 2023: -$757,3202023Revenue 2024: $5,629,627Expenses 2024: $5,488,571Net Income 2024: $141,0562024Revenue 2025: $5,573,694Expenses 2025: $4,635,856Net Income 2025: $937,8382025

Highlighted filing

2016

Revenue$3,634,684
Expenses$4,798,710
Net Income-$1,164,026
Jump To
Filing Snapshot
Filing Period
Oct 1, 2015 to Sep 30, 2016
Signed
Dec 15, 2016
Return Version
2015v2.0
Gross Receipts
$3,634,684
Mission and Program Overview

Mission

Coordinate soybean research

Balance Sheet Detail
LineBeginningEndChange
Assets
Savings and Temporary Cash Investments$2,251,560$2,542,046▲ $290,486
Cash and Non-Interest-Bearing Accounts$2,157,805$1,318,113▼ $839,692
Accounts Receivable$191,573$158,211▼ $33,362
Other Notes and Loans Receivable, Net-$0-
Pledges and Grants Receivable-$0-
Receivable From Disqualified Prsn-$0-
Receivables From Officers Etc-$0-
Investments Other Securities-$0-
Investments Program Related-$0-
Investments in Publicly Traded Securities-$0-
Land, Buildings, and Equipment, Net-$0-
Intangible Assets-$0-
Inventories for Sale or Use-$0-
Prepaid Expenses and Deferred Charges-$0-
Total Assets$4,605,452$4,021,013▼ $584,439
Other Assets Total$4,514$2,643▼ $1,871
Liabilities
Accounts Payable and Accrued Expenses$1,149,884$1,729,471▲ $579,587
Total Liabilities$1,149,884$1,729,471▲ $579,587
Net Assets / Fund Balance
Unrestricted Net Assets$3,455,568$2,291,542▼ $1,164,026
Total Net Assets Fund Balance$3,455,568$2,291,542▼ $1,164,026
Total Liabilities and Net Assets / Fund Balance$4,605,452$4,021,013▼ $584,439
Compensation and Service Providers

Board Members and Trustees

NameTitle
Cliff MulderPresident
Gene StoelVice President
Cecil DemottDirector
Craig ConverseDirector
Dave RodibaughDirector
Ed CagneyDirector
Jerod HookerDirector
Keith KempDirector
Larry TonnigesDirector
Matt DanuserDirector
Ron OhldeDirector
Mike CernySecretary/Treas
Revenue and Support

Revenue Composition

Contributions and Grants
$3,622,308
Program Service Revenue
$0
Investment Income
$12,376
Other Revenue
$0
All Other Contributions
$3,622,308
Change in Net Assets
$-1,164,026
Expenses and Functional Allocation

Major Expense Lines

Line ItemAmount
Other Expenses$4,798,710
Grants and Similar Amounts Paid$0
Professional Fundraising Fees$0
Salaries, Compensation, and Employee Benefits$0
Total Fundraising Expense$0

Functional Expense Allocation

Line ItemProgramManagementFundraisingTotal
Other Expenses$4,655,256$143,454-$143,454
Total Functional Expenses$4,655,256$143,454$0$4,798,710
Fundraising, Events, and Gaming
Fundraising activities
No
Gaming activities
No
Professional fundraiser used
No

Fundraising and Gaming Totals

Line ItemAmount
Professional Fundraising Fees$0
Political and Lobbying Activity
Political campaign activity
No
Lobbying activity
No
Subject to proxy tax
No
Insider Transactions and Loans

Loans and Receivables

Line ItemBeginningEndChange
Receivables from Disqualified Persons-$0-
Receivables from Officers, Directors, Trustees, and Key Employees-$0-
Governance and Compliance

Governance Checklist

Compiled or reviewed by an accountant
No
Annual disclosure for covered persons
Yes
Audit committee
Yes
Backup withholding compliance
No
Business relationship with family members
No
Business relationship with organization members
No
Material changes to governing documents
No
Compensation from other sources disclosed
No
CEO compensation reviewed
No
Other officer compensation reviewed
No
Conflict-of-interest policy
Yes
Audited financial statements prepared
No
Key decisions subject to board approval
No
Management duties delegated
No

Governance Explanations

Form 990, Part VI, Line 11B: Form 990 Review Process

Presented to the board at the meeting held on december 6, 2016

Form 990, Part VI, Line 12C: Explanation of Monitoring and Enforcement of Conflicts

Annually the board is required to disclose conflicting interests. Board members are required to recuse themselves from any vote if there is a conflict.

Form 990, Part VI, Line 19: Other Organization Documents Publicly Available

Governing documents, conflict of interest policy and financial statements are available to the public upon request.

Filing and Contact Details

Filer

Filer Name
North Central Soybean Research Program
EIN
42-1394799
Phone
5152518640
Address
1255 Prairie Trail Parkway, Ankeny, IA 50023

Signing Officer

Name
Kirk Leeds
Title
Executive Director
Signed
2016-12-15
Discuss with paid preparer
Yes

Organization Details

Formed
1992
Legal Domicile
Ia
Voting Board Members
12
Independent Board Members
12
Employees
0
Volunteers
12

Preparer

Firm
Schnoes & Company
Address
520 Walnut Street, WAUKEE, IA 50263-9518
Preparer
Michael F Schnoes
Phone
5159879598
Supplemental Narrative

Additional Explanations

Program Descriptions (1) through (5)

(1) Project Title: Breeding to improve resistance to SDS in soybean as a means to protect yield Delivering resistant varieties and linesPrincipal Investigador: Silvia R. Cianzio, Co-Pis: B. Diers, J. Orf. D. Wang, P. Chen, S. Kantartzi, G. Hartmann, J. Bond Budget Amount: $171,312 Year: 2015-2016Brief Statement of Objectives: Breeding high yield SDS-resistant soybean cultivars in Maturity Groups I to VI for farmers, and seed industry. Objectives that support Objective 1: 1) Identify new sources of resistance to SDS; 2) Evaluation of SDS-field resistance of public experimental linesBackground information. An ideal production approach for managing sudden death syndrome (SDS) is the planting of resistant cultivars. Development of soybean resistant cultivars is difficult and time consuming, since SDS genetic resistance is determined by numerous genes, each and every one interacting with the production environment. The number of SDS-resistant cultivars is presently limited. A group of soybean breeders already working on developing SDS resistant germplasm at different institutions was brought together to this project. (2)Project Title: Acceleration of Soybean Yield and Composition Improvement through Genomic SelectionPrinciple Investigator and Co-PIs: Brian Diers, Matt Hudson, Pat Brown, Randall Nelson, Katy Martin Rainey, Bill Beavis, Asheesh Singh, George Graef, Jim Specht, and Aaron LorenzBudget Amount and Project Year: Year , $315,642Brief Statement of Objectives:The overall objective of this project is to use results from the large, USB funded SoyNAM project to predict the performance of new experimental lines and to test whether these predictions result in the selection of better lines than traditional breeding methods. If these new methods are successful, this will increase the rate of genetic gain in breeding programs. Below are the specific project objectives. The first objective is to test genomic selection in breeding populations. This first step is to use the dataset from the SoyNAM project to optimize methods for using genetic markers to predict yield, protein concentration, and maturity of soybean lines (this is called genomic prediction and when plants or lines are selected with this method, it is call genomic selection). In this objective, predictions for the traits can be made and compared to trait data that is available. The second step is to conduct a breeding experiment using the optimized genomic selection approaches in populations of breeding lines developed by each cooperating breeder. Within each population, lines selected using genomic selection and traditional approaches will be compared to determine which method was the most successful. The second objective is to use of genomic data to decide what cross combinations should be made by breeders. We will develop methods for selecting specific combinations of parents for crossing in soybean breeding nurseries. Once these methods are developed, they will be used by breeders to help them decide what cross combinations to make(3)Project Title: Increasing profits through genetic resistance to SDSPrinciple Investigator and Co-PIs: Brian Diers, Osman Radwan, Glen Hartman, Jason Bond, James Orf, Dechun Wang Budget Amount and Project Year: Year 3 Total budget $162,545Brief Statement of Objectives:The overall objective of this research is to increase profits through improving yields with genetic resistance to SDS. The specific objectives of the project are:Objective 1. Map locations on chromosomes of genes that confer resistance to SDS. This mapping is being done in Minnesota and Michigan using two genetic populations in each state.Objective 2. Confirm and deploy SDS resistance genes. This is being done to determine if previously mapped genes are useful in different genetic backgrounds and environments.Objective 3. Identify genes involved in SDS resistance by gene expression profiling soybean roots and leaves. To complete this work, the level of gene expression was est

Program Descriptions (11) through (15)

(11)Project Title: Engineered resistance to soybean cyst nematode via induced gene silencing (RNAi)Principle Investigator and Co-PIs: Harold Trick (Project Leader), Tim Todd and Jiarui Li (Kansas State University), John Finer (The Ohio State University), Wayne Parrott (University of Georgia) and Lila Vodkin and Jack Widholm (University of Illinois); Budget Amount and Project Year: $136,177 Year 4Brief Statement of Objectives: The primary goal of this research project is to establish a new set of biotech traits that have durable resistance to soybean cyst nematode (SCN). Turning off genes by a process known as RNA interference (RNAi) has tremendous potential as a new strategy to increase nematode resistance. Past research with other nematode species has demonstrated the scientific merit of the technique. This project will investigate the opportunities to insert target gene sequences in the SCN that will provide durable genetic materials that will be lethal to SCN populations.The specific objectives of this project are to:Complete the production of stable transgenic soybean plants with traits that can silence specific nematode genes Perform bioassays with the engineered plants to confirm effectiveness of the SCN resistance; and Examine the durability of traits on single and diverse populations of SCN.Brief Statement of Expected Deliverables: It is anticipated this research will result in stable transgenic soybean lines expressing the RNAi constructions and that events with increased levels of SCN resistance will be identified. By the end of the funding cycle we intend to identify specific lines that have broad levels of resistance to several populations or HG types of soybean cyst nematodes. (12)Project Title: Disease Study Group: Focus on New and Emerging Soybean DiseasesPrinciple Investigator and Co-PIs: Kiersten Wise, Purdue University and Daren Mueller, Iowa State University, Loren Giesler, University of Nebraska, Carl Bradley, University of Illinois, Martin Chilvers, Michigan State University, Albert Tenuta, OMAFRA; Project contributor (no-cost): Damon Smith, University of WisconsinBudget Amount and Project Year: Project period 03/01/13 to 02/28/16; Year 2 of 3Total funding: $42,250 Year 3Brief Statement of Objectives:This project directly benefits soybean farmers in the North Central region by providing current and timely Extension material to aid in the identification and management of emerging diseases, and diseases lacking Extension information. The project improves awareness and stakeholder knowledge of emerging diseases using traditional mechanisms such as fact sheets and bulletins, as well as new technologies such as web-based videos and web content that are downloadable and viewable through new technology such as smartphones and tablet devices.Project objectives: 1. Provide information on emerging soybean diseases at multiple levels of Extension interface (print, web, video, etc.) to reach diverse groups of stakeholders.2. Create a platform to host and brand Extension material developed in conjunction with the North Central Soybean Research Program to facilitate updates and allow users to identify trusted sources of material through this branding partnership.3. Provide current research summaries on emerging diseases to direct and coordinate future research priorities thereby minimizing duplication, maximizing resources and increasing response time.(13)Project Title: Understanding the role of fungicide programs on soybean health and charcoal rot developmentPrinciple Investigator and Co-PIs: Kiersten Wise, Purdue University and Daren Mueller, Iowa State University, Emmanuel Byamukama, South Dakota State University, Martin Chilvers, Michigan State University, Chris Little and Doug Jardine, Kansas State University, Damon Smith, University of WisconsinBudget Amount and Project Year: $62,000 Year 2Brief Statement of Objectives:Charcoal rot, caused by Macrophomina phaseolina, is a disease of growing importance in the North

Program Descriptions (16) through (19)

(16)PROJECT TITLE: Benchmarking soybean production systems in the North-Central Principal Investigators:Dr Patricio Grassini (Principal Co-Investigator)Dr. Shawn P. Conley (Principal Co-InvestigatorBudget Amount and Project Year: $433,081 Year 1PROJECT JUSTIFICATION AND RATIONALESoybean production is expected to increase to satisfy the increasing demand for food, biodiesel, and livestock feed, both in the USA and globally. Thus, it is crucial to reduce the yield gap, which is the difference between the attainable crop yield, as determined by the interactive effects of weather, soils, and genetics, and the actual crop yield attained by a producer. The North Central USA region includes these states: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. The 12 states combined produce 2,719 million bushels annually on 63 million harvested acres during 2010-2014, representing a respective 82 and 81% of total U.S. soybean production and acreage (USDA-NASS). Average soybean yield in the NC-USA region during 2010-2014 was 43 bushels/acre, yet some producers can consistently attain soybean yields near or greater than 80 bushels/acre (Specht et al., 1999, Grassini et al., 2014, VanRoekel and Purcell, 2014). This large gap between an average state yield and the very high yield obtained by some producers in that state needs to be explored and better understood. This project is targeted at identifying the factors - whether these are site-specific soil or weather conditions, or are less than optimal crop management practices - that prevent most producers from attaining yields closer to the high yields attained by other producers. Once those factors are identified, both the producer and his/her university research/extension specialist can focus on how to close the yield gap for that individual producer (and others like him or her).The most common approach to identify yield-limiting factors in producer fields involves conducting on-farm trials, in which researchers selectively apply different input levels or management practices in experimental trials conducted in multiple producer fields (e.g., Villamil et al., 2012), and then evaluate whether a particular input or management practice is statistically significant in improving yield, and of course, whether the degree of yield improvement justifies the cost of the input. An example of this approach is the USB-funded kitchen sink project that was just completed. An alternative method is the use of producer self-reported field yield and associated crop management practice data (e.g., Grassini et al., 2011, 2015). This approach can be used to (1) evaluate current on-farm management relative to recommended optimal practices, and (2) discern the yield impact of individual factors, and their relative importance, in the context of commercial-scale fields, in contrast to small experimental plots, and within the range of cost-effective management practices that are actually being used by producers. Indeed, when hundreds of such producer reports are available, the yield difference between various management practices and the interactions of those practices can be contextualized for a given weather-soil context. Such analysis of large-scale producer data can thus complement and maybe provide a focus for what treatments to evaluate in the more costly agronomic field trial evaluations (see FIGURE 1 below for an example of how producer self-reported data was used by Grassini et al relative to soybean planting date in Nebraska).(17)Project Title: Biology and control of sclerotinia stem rot of soybeanPrincipal Investigator: Mehdi Kabbage, University of Wisconsin-Madison, Co-Investigators:Damon Smith, University of Wisconsin-Madison, Daren Mueller, Iowa State University, Martin Chilvers, Michigan State University, Sydney Everhart, University of Nebraska-Lincoln, Budget Amount and Project Year: $88,700 Year 1III. Brief Project Justification an

Program Descriptions (20) through (23)

(20)Project Title: Improving our understanding of stem canker and how to manage it in soybean across the MidwestPrincipal Investigator: Damon Smith, University of Wisconsin-MadisonKiersten Wise, Purdue University; Daren Mueller, Iowa State University; Febina Mathew, South Dakota State UniversityBudget Amount and Project Year: $50,000 Year 1Brief Project Justification and Rationale Need, state-of-the-art, opportunity for farmers and the soybean industry:Objective: Several different diseases can cause similar symptoms on soybeans. An example of a disease that is easily misdiagnosed as early crop maturity, sudden death syndrome (SDS), Sclerotinia stem rot or charcoal rot in the North Central United States, is soybean stem canker. Symptoms of the disease can include main stem wilting and widespread plant death in areas of a field (Fig. 1). Closer examination of plants often reveals sunken cankers on main stems (Fig. 2). In recent years stem canker and other diseases caused by fungi in the same group, such as pod and stem blight, have become increasingly problematic in the North Central region. Severe stem canker epidemics can occur in wet springs, and with climate experts predicting wetter springs, it is possible that this disease will be more prevalent in coming years (Fernandez et al. 1999). In 2014, this disease was frequently observed and mentioned as the second most prevalent disease in the North Central region, behind SDS (NCERA137 reports).(21)Project Title: Initiation of a genomic selection pipeline for public soybean breeders in the North Central RegionContact Information: Aaron Lorenz (PI), University of MinnesotaBill Beavis, Iowa State University, Patrick Brown, University of Illinois, Urbana, Brian Diers (PI), University of Illinois, Urbana, George Graef, University of Nebraska, LincolnMatt Hudson, University of Illinois, Urbana, Alex Lipka, University of Illinois, Urbana, Leah McHale, The Ohio State University, Randall Nelson, USDA-ARS and Department of Crop Sciences, University of Illinois, Urbana, Henry Nguyen, University of Missouri, Katy Martin Rainey, Department of Agronomy, Purdue University, West Lafayette, IN 47907, 765-494-1212Andrew Scaboo, University of Missouri, William Schapaugh, Kansas State University, Grover Shannon, University of Missouri, Asheesh Singh, Iowa State University, Dechun Wang, Michigan State University, Budget Amount and Project Year: $368,739 Year 1Brief Project Justification and Rationale: Increases in soybean yield through breeding are slower than producers expect. There are several possible reasons for the reduced rate of gain in soybean grain yield, including limited genetic variation in the commercially used gene pool, amount of time required for each breeding cycle, size of the breeding populations, and accuracy of evaluations. Advances in genomics have made whole-genome genotyping less expensive than multi-location yield testing. A powerful approach to make use of this genomic information for selective breeding is through a method called genomic prediction and selection. Large datasets of genomic and phenotypic information are required to maximize the effectiveness of genomic prediction. Fortunately, a wealth of data already exists within the public soybean community that could be used to initiate a genomic prediction pipeline to assist soybean breeders to more effectively select for yield and introgress diversity into their breeding program. This pipeline will evolve into a service for soybean breeders that will help address all of the major restraints to soybean breeding progress. (22)Project Title: Seedling Diseases: Biology, Management and EducationPrincipal Investigators: Jason Bond, Southern IL. Univ. John Rupe, Univ. of ArkansasTony Adesemoye, UNMartin Chilvers, MSUSydney Everhart, UNAhmad Fakhoury, SIUChris Little, KSUDean Malvick, UMNFebina Mathew, SDSUGary Munkvold, ISUAlison Robertson, ISUKiersten Wise, PUUSB CollaboratorsLoren Giesler, UNHeather Kelly, UTLeonor Leandro

Program Descriptions (6) through (10)

(6) Project Title: Characterization and Enhancement of Soybean Genetic Resources for Soilborne Disease ResistancePrinciple Investigator and Co-PIs: (PIs) James Kurle, Xianjin Ma, (Co-PIs) Jim Orf, Nevin Young, Kate Rainey.Amount and Project Year: $185,237 Year 2Brief Statement of Objectives:Obj. 1. Evaluate of soybean germplasm for resistance or partial resistance to Phytophthora sojae, Pythium irregulare, P. ultimum, and Fusarium graminearum (Kurle & Orf)Obj. 2. Identify of QTLs underlying resistance to P. sojae, F. graminearum, P. irregulare, and P. ultimum by association mapping (Kurle & Young)Obj. 3. Fine mapping, isolation, and functional verification of two uncharacterized Rps genes conferring resistance to P. sojae (Ma&Rainey)Obj. 4. Develop highly adapted soybean cultivars or experimental lines with major resistance QTLs and Rps genes by marker-assisted selection (Rainey & Orf)Brief Statement of Expected Deliverables (max 250 words):Obj. 1. Relate new QTLs/genes to resistance and partial resistance to P. sojae, P. ultimum, F. graminearum identified in early maturity lines.Obj. 2. Initial results of statistical analysis and association mapping for P. sojae. Obj. 3. Fine mapping of RpsUN2 to a 64-kb region within 430 kb previously associated with marker for this gene.Obj. 4. Introgression of RpsUN1 and RpsUN2 to elite breeding lines developed by Purdue.(7)Project Title: Micronutrients for Soybean Production: A Position Paper for the North-Central RegionPrincipal Investigator: Antonio P. Mallarino, Iowa State UniversityBudget Amount and Project Year: Year 2, $15,241Brief Statement of Objectives: Soybean growers in the in the North Central region have been asking many questions concerning possible soybean yield loss due to deficiency of micronutrients. However, few extension publications address this issue based on recent research results, and often have divergent recommendations not clearly related to soil differences across states. Therefore, the goal of this multi-state project is to gather information across key states of the North Central regional and prepare a regional position paper on rational use of micronutrients for soybean production. The specific objectives are: 1. Find, analyze, and summarize published and unpublished land-grant university field response-based information about soybean need for micronutrients and the value of both soil and plant tissue analyses in the North Central region. 2. Prepare and publish a regional position paper addressing the most important issues concerning use of micronutrients for soybean production in the North Central region.(8)Project Title: Iron Deficiency Chlorosis: Getting to the root of the problemInvestigators/institutions: Phil McClean (Project Leader and Robert Stupar (University of Minnesota). Budget Amount & Project Year: $141.599 Year 6Projects Strategic Goal is to develop useful molecular markers that can identify IDC efficient genotypes and use state of the art genomic technologies to identify genes involved in IDC efficiency or inefficiency. The ultimate goal of the research is to isolate candidate genes and develop markers for these genes that will aid the soybean breeder in developing IDC resistant varieties.(9)Project Title: Developing an Integrated Management and Communication Plan for Soybean Sudden Death SyndromePrinciple Investigator: Daren MuellerBudget Amount and Project Year: $141,599, Year 3Brief Statement of Objectives:The foundational management strategy for sudden death syndrome (SDS) is using resistant cultivars. However, in years such as 2010 and 2014, when environmental conditions are favorable for disease development, it is evident that resistance alone does not provide adequate control or reduce farmer risk sufficiently. Also, SDS continues to move into new areas. Thus, the main goal of this project is to investigate management options that will help ensure resistant cultivars will be as effective as possible thereby reducing risk as well as pro

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IRS990ScheduleO/SupplementalInformationDetail/ExplanationTxt0PRESENTED TO THE BOARD AT THE MEETING HELD ON DECEMBER 6, 2016
IRS990ScheduleO/SupplementalInformationDetail/ExplanationTxt1ANNUALLY THE BOARD IS REQUIRED TO DISCLOSE CONFLICTING INTERESTS. BOARD MEMBERS ARE REQUIRED TO RECUSE THEMSELVES FROM ANY VOTE IF THERE IS A CONFLICT.
IRS990ScheduleO/SupplementalInformationDetail/ExplanationTxt2Governing documents, conflict of interest policy and financial statements are available to the public upon request.
IRS990ScheduleO/SupplementalInformationDetail/ExplanationTxt3(1) Project Title: Breeding to improve resistance to SDS in soybean as a means to protect yield Delivering resistant varieties and linesPrincipal Investigador: Silvia R. Cianzio, Co-Pis: B. Diers, J. Orf. D. Wang, P. Chen, S. Kantartzi, G. Hartmann, J. Bond Budget Amount: $171,312 Year: 2015-2016Brief Statement of Objectives: Breeding high yield SDS-resistant soybean cultivars in Maturity Groups I to VI for farmers, and seed industry. Objectives that support Objective 1: 1) Identify new sources of resistance to SDS; 2) Evaluation of SDS-field resistance of public experimental linesBackground information. An ideal production approach for managing sudden death syndrome (SDS) is the planting of resistant cultivars. Development of soybean resistant cultivars is difficult and time consuming, since SDS genetic resistance is determined by numerous genes, each and every one interacting with the production environment. The number of SDS-resistant cultivars is presently limited. A group of soybean breeders already working on developing SDS resistant germplasm at different institutions was brought together to this project. (2)Project Title: Acceleration of Soybean Yield and Composition Improvement through Genomic SelectionPrinciple Investigator and Co-PIs: Brian Diers, Matt Hudson, Pat Brown, Randall Nelson, Katy Martin Rainey, Bill Beavis, Asheesh Singh, George Graef, Jim Specht, and Aaron LorenzBudget Amount and Project Year: Year , $315,642Brief Statement of Objectives:The overall objective of this project is to use results from the large, USB funded SoyNAM project to predict the performance of new experimental lines and to test whether these predictions result in the selection of better lines than traditional breeding methods. If these new methods are successful, this will increase the rate of genetic gain in breeding programs. Below are the specific project objectives. The first objective is to test genomic selection in breeding populations. This first step is to use the dataset from the SoyNAM project to optimize methods for using genetic markers to predict yield, protein concentration, and maturity of soybean lines (this is called genomic prediction and when plants or lines are selected with this method, it is call genomic selection). In this objective, predictions for the traits can be made and compared to trait data that is available. The second step is to conduct a breeding experiment using the optimized genomic selection approaches in populations of breeding lines developed by each cooperating breeder. Within each population, lines selected using genomic selection and traditional approaches will be compared to determine which method was the most successful. The second objective is to use of genomic data to decide what cross combinations should be made by breeders. We will develop methods for selecting specific combinations of parents for crossing in soybean breeding nurseries. Once these methods are developed, they will be used by breeders to help them decide what cross combinations to make(3)Project Title: Increasing profits through genetic resistance to SDSPrinciple Investigator and Co-PIs: Brian Diers, Osman Radwan, Glen Hartman, Jason Bond, James Orf, Dechun Wang Budget Amount and Project Year: Year 3 Total budget $162,545Brief Statement of Objectives:The overall objective of this research is to increase profits through improving yields with genetic resistance to SDS. The specific objectives of the project are:Objective 1. Map locations on chromosomes of genes that confer resistance to SDS. This mapping is being done in Minnesota and Michigan using two genetic populations in each state.Objective 2. Confirm and deploy SDS resistance genes. This is being done to determine if previously mapped genes are useful in different genetic backgrounds and environments.Objective 3. Identify genes involved in SDS resistance by gene expression profiling soybean roots and leaves. To complete this work, the level of gene expression was est
IRS990ScheduleO/SupplementalInformationDetail/ExplanationTxt4(11)Project Title: Engineered resistance to soybean cyst nematode via induced gene silencing (RNAi)Principle Investigator and Co-PIs: Harold Trick (Project Leader), Tim Todd and Jiarui Li (Kansas State University), John Finer (The Ohio State University), Wayne Parrott (University of Georgia) and Lila Vodkin and Jack Widholm (University of Illinois); Budget Amount and Project Year: $136,177 Year 4Brief Statement of Objectives: The primary goal of this research project is to establish a new set of biotech traits that have durable resistance to soybean cyst nematode (SCN). Turning off genes by a process known as RNA interference (RNAi) has tremendous potential as a new strategy to increase nematode resistance. Past research with other nematode species has demonstrated the scientific merit of the technique. This project will investigate the opportunities to insert target gene sequences in the SCN that will provide durable genetic materials that will be lethal to SCN populations.The specific objectives of this project are to:Complete the production of stable transgenic soybean plants with traits that can silence specific nematode genes Perform bioassays with the engineered plants to confirm effectiveness of the SCN resistance; and Examine the durability of traits on single and diverse populations of SCN.Brief Statement of Expected Deliverables: It is anticipated this research will result in stable transgenic soybean lines expressing the RNAi constructions and that events with increased levels of SCN resistance will be identified. By the end of the funding cycle we intend to identify specific lines that have broad levels of resistance to several populations or HG types of soybean cyst nematodes. (12)Project Title: Disease Study Group: Focus on New and Emerging Soybean DiseasesPrinciple Investigator and Co-PIs: Kiersten Wise, Purdue University and Daren Mueller, Iowa State University, Loren Giesler, University of Nebraska, Carl Bradley, University of Illinois, Martin Chilvers, Michigan State University, Albert Tenuta, OMAFRA; Project contributor (no-cost): Damon Smith, University of WisconsinBudget Amount and Project Year: Project period 03/01/13 to 02/28/16; Year 2 of 3Total funding: $42,250 Year 3Brief Statement of Objectives:This project directly benefits soybean farmers in the North Central region by providing current and timely Extension material to aid in the identification and management of emerging diseases, and diseases lacking Extension information. The project improves awareness and stakeholder knowledge of emerging diseases using traditional mechanisms such as fact sheets and bulletins, as well as new technologies such as web-based videos and web content that are downloadable and viewable through new technology such as smartphones and tablet devices.Project objectives: 1. Provide information on emerging soybean diseases at multiple levels of Extension interface (print, web, video, etc.) to reach diverse groups of stakeholders.2. Create a platform to host and brand Extension material developed in conjunction with the North Central Soybean Research Program to facilitate updates and allow users to identify trusted sources of material through this branding partnership.3. Provide current research summaries on emerging diseases to direct and coordinate future research priorities thereby minimizing duplication, maximizing resources and increasing response time.(13)Project Title: Understanding the role of fungicide programs on soybean health and charcoal rot developmentPrinciple Investigator and Co-PIs: Kiersten Wise, Purdue University and Daren Mueller, Iowa State University, Emmanuel Byamukama, South Dakota State University, Martin Chilvers, Michigan State University, Chris Little and Doug Jardine, Kansas State University, Damon Smith, University of WisconsinBudget Amount and Project Year: $62,000 Year 2Brief Statement of Objectives:Charcoal rot, caused by Macrophomina phaseolina, is a disease of growing importance in the North
IRS990ScheduleO/SupplementalInformationDetail/ExplanationTxt5(16)PROJECT TITLE: Benchmarking soybean production systems in the North-Central Principal Investigators:Dr Patricio Grassini (Principal Co-Investigator)Dr. Shawn P. Conley (Principal Co-InvestigatorBudget Amount and Project Year: $433,081 Year 1PROJECT JUSTIFICATION AND RATIONALESoybean production is expected to increase to satisfy the increasing demand for food, biodiesel, and livestock feed, both in the USA and globally. Thus, it is crucial to reduce the yield gap, which is the difference between the attainable crop yield, as determined by the interactive effects of weather, soils, and genetics, and the actual crop yield attained by a producer. The North Central USA region includes these states: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. The 12 states combined produce 2,719 million bushels annually on 63 million harvested acres during 2010-2014, representing a respective 82 and 81% of total U.S. soybean production and acreage (USDA-NASS). Average soybean yield in the NC-USA region during 2010-2014 was 43 bushels/acre, yet some producers can consistently attain soybean yields near or greater than 80 bushels/acre (Specht et al., 1999, Grassini et al., 2014, VanRoekel and Purcell, 2014). This large gap between an average state yield and the very high yield obtained by some producers in that state needs to be explored and better understood. This project is targeted at identifying the factors - whether these are site-specific soil or weather conditions, or are less than optimal crop management practices - that prevent most producers from attaining yields closer to the high yields attained by other producers. Once those factors are identified, both the producer and his/her university research/extension specialist can focus on how to close the yield gap for that individual producer (and others like him or her).The most common approach to identify yield-limiting factors in producer fields involves conducting on-farm trials, in which researchers selectively apply different input levels or management practices in experimental trials conducted in multiple producer fields (e.g., Villamil et al., 2012), and then evaluate whether a particular input or management practice is statistically significant in improving yield, and of course, whether the degree of yield improvement justifies the cost of the input. An example of this approach is the USB-funded kitchen sink project that was just completed. An alternative method is the use of producer self-reported field yield and associated crop management practice data (e.g., Grassini et al., 2011, 2015). This approach can be used to (1) evaluate current on-farm management relative to recommended optimal practices, and (2) discern the yield impact of individual factors, and their relative importance, in the context of commercial-scale fields, in contrast to small experimental plots, and within the range of cost-effective management practices that are actually being used by producers. Indeed, when hundreds of such producer reports are available, the yield difference between various management practices and the interactions of those practices can be contextualized for a given weather-soil context. Such analysis of large-scale producer data can thus complement and maybe provide a focus for what treatments to evaluate in the more costly agronomic field trial evaluations (see FIGURE 1 below for an example of how producer self-reported data was used by Grassini et al relative to soybean planting date in Nebraska).(17)Project Title: Biology and control of sclerotinia stem rot of soybeanPrincipal Investigator: Mehdi Kabbage, University of Wisconsin-Madison, Co-Investigators:Damon Smith, University of Wisconsin-Madison, Daren Mueller, Iowa State University, Martin Chilvers, Michigan State University, Sydney Everhart, University of Nebraska-Lincoln, Budget Amount and Project Year: $88,700 Year 1III. Brief Project Justification an
IRS990ScheduleO/SupplementalInformationDetail/ExplanationTxt6(20)Project Title: Improving our understanding of stem canker and how to manage it in soybean across the MidwestPrincipal Investigator: Damon Smith, University of Wisconsin-MadisonKiersten Wise, Purdue University; Daren Mueller, Iowa State University; Febina Mathew, South Dakota State UniversityBudget Amount and Project Year: $50,000 Year 1Brief Project Justification and Rationale Need, state-of-the-art, opportunity for farmers and the soybean industry:Objective: Several different diseases can cause similar symptoms on soybeans. An example of a disease that is easily misdiagnosed as early crop maturity, sudden death syndrome (SDS), Sclerotinia stem rot or charcoal rot in the North Central United States, is soybean stem canker. Symptoms of the disease can include main stem wilting and widespread plant death in areas of a field (Fig. 1). Closer examination of plants often reveals sunken cankers on main stems (Fig. 2). In recent years stem canker and other diseases caused by fungi in the same group, such as pod and stem blight, have become increasingly problematic in the North Central region. Severe stem canker epidemics can occur in wet springs, and with climate experts predicting wetter springs, it is possible that this disease will be more prevalent in coming years (Fernandez et al. 1999). In 2014, this disease was frequently observed and mentioned as the second most prevalent disease in the North Central region, behind SDS (NCERA137 reports).(21)Project Title: Initiation of a genomic selection pipeline for public soybean breeders in the North Central RegionContact Information: Aaron Lorenz (PI), University of MinnesotaBill Beavis, Iowa State University, Patrick Brown, University of Illinois, Urbana, Brian Diers (PI), University of Illinois, Urbana, George Graef, University of Nebraska, LincolnMatt Hudson, University of Illinois, Urbana, Alex Lipka, University of Illinois, Urbana, Leah McHale, The Ohio State University, Randall Nelson, USDA-ARS and Department of Crop Sciences, University of Illinois, Urbana, Henry Nguyen, University of Missouri, Katy Martin Rainey, Department of Agronomy, Purdue University, West Lafayette, IN 47907, 765-494-1212Andrew Scaboo, University of Missouri, William Schapaugh, Kansas State University, Grover Shannon, University of Missouri, Asheesh Singh, Iowa State University, Dechun Wang, Michigan State University, Budget Amount and Project Year: $368,739 Year 1Brief Project Justification and Rationale: Increases in soybean yield through breeding are slower than producers expect. There are several possible reasons for the reduced rate of gain in soybean grain yield, including limited genetic variation in the commercially used gene pool, amount of time required for each breeding cycle, size of the breeding populations, and accuracy of evaluations. Advances in genomics have made whole-genome genotyping less expensive than multi-location yield testing. A powerful approach to make use of this genomic information for selective breeding is through a method called genomic prediction and selection. Large datasets of genomic and phenotypic information are required to maximize the effectiveness of genomic prediction. Fortunately, a wealth of data already exists within the public soybean community that could be used to initiate a genomic prediction pipeline to assist soybean breeders to more effectively select for yield and introgress diversity into their breeding program. This pipeline will evolve into a service for soybean breeders that will help address all of the major restraints to soybean breeding progress. (22)Project Title: Seedling Diseases: Biology, Management and EducationPrincipal Investigators: Jason Bond, Southern IL. Univ. John Rupe, Univ. of ArkansasTony Adesemoye, UNMartin Chilvers, MSUSydney Everhart, UNAhmad Fakhoury, SIUChris Little, KSUDean Malvick, UMNFebina Mathew, SDSUGary Munkvold, ISUAlison Robertson, ISUKiersten Wise, PUUSB CollaboratorsLoren Giesler, UNHeather Kelly, UTLeonor Leandro
IRS990ScheduleO/SupplementalInformationDetail/ExplanationTxt7(6) Project Title: Characterization and Enhancement of Soybean Genetic Resources for Soilborne Disease ResistancePrinciple Investigator and Co-PIs: (PIs) James Kurle, Xianjin Ma, (Co-PIs) Jim Orf, Nevin Young, Kate Rainey.Amount and Project Year: $185,237 Year 2Brief Statement of Objectives:Obj. 1. Evaluate of soybean germplasm for resistance or partial resistance to Phytophthora sojae, Pythium irregulare, P. ultimum, and Fusarium graminearum (Kurle & Orf)Obj. 2. Identify of QTLs underlying resistance to P. sojae, F. graminearum, P. irregulare, and P. ultimum by association mapping (Kurle & Young)Obj. 3. Fine mapping, isolation, and functional verification of two uncharacterized Rps genes conferring resistance to P. sojae (Ma&Rainey)Obj. 4. Develop highly adapted soybean cultivars or experimental lines with major resistance QTLs and Rps genes by marker-assisted selection (Rainey & Orf)Brief Statement of Expected Deliverables (max 250 words):Obj. 1. Relate new QTLs/genes to resistance and partial resistance to P. sojae, P. ultimum, F. graminearum identified in early maturity lines.Obj. 2. Initial results of statistical analysis and association mapping for P. sojae. Obj. 3. Fine mapping of RpsUN2 to a 64-kb region within 430 kb previously associated with marker for this gene.Obj. 4. Introgression of RpsUN1 and RpsUN2 to elite breeding lines developed by Purdue.(7)Project Title: Micronutrients for Soybean Production: A Position Paper for the North-Central RegionPrincipal Investigator: Antonio P. Mallarino, Iowa State UniversityBudget Amount and Project Year: Year 2, $15,241Brief Statement of Objectives: Soybean growers in the in the North Central region have been asking many questions concerning possible soybean yield loss due to deficiency of micronutrients. However, few extension publications address this issue based on recent research results, and often have divergent recommendations not clearly related to soil differences across states. Therefore, the goal of this multi-state project is to gather information across key states of the North Central regional and prepare a regional position paper on rational use of micronutrients for soybean production. The specific objectives are: 1. Find, analyze, and summarize published and unpublished land-grant university field response-based information about soybean need for micronutrients and the value of both soil and plant tissue analyses in the North Central region. 2. Prepare and publish a regional position paper addressing the most important issues concerning use of micronutrients for soybean production in the North Central region.(8)Project Title: Iron Deficiency Chlorosis: Getting to the root of the problemInvestigators/institutions: Phil McClean (Project Leader and Robert Stupar (University of Minnesota). Budget Amount & Project Year: $141.599 Year 6Projects Strategic Goal is to develop useful molecular markers that can identify IDC efficient genotypes and use state of the art genomic technologies to identify genes involved in IDC efficiency or inefficiency. The ultimate goal of the research is to isolate candidate genes and develop markers for these genes that will aid the soybean breeder in developing IDC resistant varieties.(9)Project Title: Developing an Integrated Management and Communication Plan for Soybean Sudden Death SyndromePrinciple Investigator: Daren MuellerBudget Amount and Project Year: $141,599, Year 3Brief Statement of Objectives:The foundational management strategy for sudden death syndrome (SDS) is using resistant cultivars. However, in years such as 2010 and 2014, when environmental conditions are favorable for disease development, it is evident that resistance alone does not provide adequate control or reduce farmer risk sufficiently. Also, SDS continues to move into new areas. Thus, the main goal of this project is to investigate management options that will help ensure resistant cultivars will be as effective as possible thereby reducing risk as well as pro
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Balance SheetOperations
YearAssetsLiabilitiesNet AssetsRevenueExpensesNet Income
2025Detailed filing. Detailed filing data is available for this year.$2.33$0.00$2.33$5.57$4.64$0.94
2024Detailed filing. Detailed filing data is available for this year.$1.39$0.00$1.39$5.63$5.49$0.14
2023Detailed filing. Detailed filing data is available for this year.$1.25$0.00$1.25$4.74$5.50$0.76
2022Detailed filing. Detailed filing data is available for this year.$2.01$0.00$2.01$3.79$3.73$0.06
2021Detailed filing. Detailed filing data is available for this year.$1.95$0.00$1.95$3.29$2.84$0.45
2020Detailed filing. Detailed filing data is available for this year.$1.50$0.00$1.50$4.18$4.77$0.59
2019Detailed filing. Detailed filing data is available for this year.$2.09$0.00$2.09$3.71$3.85$0.14
2018Detailed filing. Detailed filing data is available for this year.$2.23$0.00$2.23$3.28$4.07$0.79
2017Detailed filing. Detailed filing data is available for this year.$3.05$1.58$1.48$3.28$4.10$0.82
2016Detailed filing. Detailed filing data is available for this year.$4.02$1.73$2.29$3.63$4.80$1.16
2015Detailed filing. Detailed filing data is available for this year.$4.61$1.15$3.46$3.18$0.21$2.97
2014Detailed filing. Detailed filing data is available for this year.$3.09$2.60$0.48$2.86$3.25$0.40
2013Facts available. Structured filing facts are available, but richer extracted sections are limited.$2.76$1.87$0.88$2.94
2012Facts available. Structured filing facts are available, but richer extracted sections are limited.$3.16$2.33$0.83$2.96
2011Facts available. Structured filing facts are available, but richer extracted sections are limited.$3.43$3.09$0.34$3.54
2010Facts available. Structured filing facts are available, but richer extracted sections are limited.$2.07$1.91$0.17$2.93