Attach to Form 990 or Form 990-EZ.
Information about Schedule A (Form 990 or 990-EZ) and its instructions is at www.irs.gov/form990.
| (i)Name of supported organization | (ii) EIN | (iii) Type of organization (described on lines 1- 9 above (see instructions)) | (iv) Is the organization listed in your governing document? | (v) Amount of monetary support (see instructions) | (vi) Amount of other support (see instructions) | |
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| Yes | No | |||||
| Total | ||||||
Calendar year (or fiscal year beginning in) ![]() |
(a) 2011 | (b) 2012 | (c) 2013 | (d) 2014 | (e) 2015 | (f) Total | |
|---|---|---|---|---|---|---|---|
| 1 | Gifts, grants, contributions, and membership fees received. (Do not include any unusual grants.) .... | 3,453,345 | 2,989,502 | 2,855,813 | 3,172,734 | 3,622,308 | 16,093,702 |
| 2 | Tax revenues levied for the organization's benefit and either paid to or expended on its behalf....... | 0 | |||||
| 3 | The value of services or facilities furnished by a governmental unit to the organization without charge.. | 0 | |||||
| 4 | Total. Add lines 1 through 3 | 3,453,345 | 2,989,502 | 2,855,813 | 3,172,734 | 3,622,308 | 16,093,702 |
| 5 | The portion of total contributions by each person (other than a governmental unit or publicly supported organization) included on line 1 that exceeds 2% of the amount shown on line 11, column (f).. | 0 | |||||
| 6 | Public support. Subtract line 5 from line 4. | 16,093,702 | |||||
Calendar year
(or fiscal year beginning in) ![]() |
(a) 2011 | (b) 2012 | (c) 2013 | (d) 2014 | (e) 2015 | (f) Total | |
|---|---|---|---|---|---|---|---|
| 7 | Amounts from line 4.. | 3,453,345 | 2,989,502 | 2,855,813 | 3,172,734 | 3,622,308 | 16,093,702 |
| 8 | Gross income from interest, dividends, payments received on securities loans, rents, royalties and income from similar sources... | 339 | 2,452 | 1,359 | 6,812 | 12,376 | 23,338 |
| 9 | Net income from unrelated business activities, whether or not the business is regularly carried on.. | ||||||
| 10 | Other income. Do not include gain or loss from the sale of capital assets (Explain in Part VI.).. | 0 | |||||
| 11 | Total support. Add lines 7 through 10. | 16,117,040 | |||||
Calendar year (or fiscal year beginning in) ![]() |
(a) 2011 | (b) 2012 | (c) 2013 | (d) 2014 | (e) 2015 | (f) Total | |
|---|---|---|---|---|---|---|---|
| 1 | Gifts, grants, contributions, and membership fees received. (Do not include any "unusual grants.") . | ||||||
| 2 | Gross receipts from admissions, merchandise sold or services performed, or facilities furnished in any activity that is related to the organization's tax-exempt purpose...... | ||||||
| 3 | Gross receipts from activities that are not an unrelated trade or business under section 513... | ||||||
| 4 | Tax revenues levied for the organization's benefit and either paid to or expended on its behalf... | ||||||
| 5 | The value of services or facilities furnished by a governmental unit to the organization without charge.. | ||||||
| 6 | Total. Add lines 1 through 5. | ||||||
| 7a | Amounts included on lines 1, 2, and 3 received from disqualified persons... | ||||||
| b | Amounts included on lines 2 and 3 received from other than disqualified persons that exceed the greater of $5,000 or 1% of the amount on line 13 for the year. | ||||||
| c | Add lines 7a and 7b.. | ||||||
| 8 | Public support. (Subtract line 7c from line 6.) | ||||||
Calendar year (or fiscal year beginning in) ![]() |
(a) 2011 | (b) 2012 | (c) 2013 | (d) 2014 | (e) 2015 | (f) Total | |
|---|---|---|---|---|---|---|---|
| 9 | Amounts from line 6... | ||||||
| 10a | Gross income from interest, dividends, payments received on securities loans, rents, royalties and income from similar sources.. | ||||||
| b | Unrelated business taxable income (less section 511 taxes) from businesses acquired after June 30, 1975. | ||||||
| c | Add lines 10a and 10b. | ||||||
| 11 | Net income from unrelated business activities not included in line 10b, whether or not the business is regularly carried on. | ||||||
| 12 | Other income. Do not include gain or loss from the sale of capital assets (Explain in Part VI.) .. | ||||||
| 13 | Total support. (Add lines 9, 10c, 11, and 12.).. | ||||||
| Section A - Adjusted Net Income | (A) Prior Year |
(B) Current Year (optional) |
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| 1 | Net short-term capital gain | 1 | ||||
| 2 | Recoveries of prior-year distributions | 2 | ||||
| 3 | Other gross income (see instructions) | 3 | ||||
| 4 | Add lines 1 through 3 | 4 | ||||
| 5 | Depreciation and depletion | 5 | ||||
| 6 | Portion of operating expenses paid or incurred for production or collection of gross income or for management, conservation, or maintenance of property held for production of income (see instructions) | 6 | ||||
| 7 | Other expenses (see instructions) | 7 | ||||
| 8 | Adjusted Net Income (subtract lines 5, 6 and 7 from line 4) | 8 | ||||
| Section B - Minimum Asset Amount | (A) Prior Year |
(B) Current Year (optional) |
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| 1 | Aggregate fair market value of all non-exempt-use assets (see instructions for short tax year or assets held for part of year): | 1 | ||||
| a | Average monthly value of securities | 1a | ||||
| b | Average monthly cash balances | 1b | ||||
| c | Fair market value of other non-exempt-use assets | 1c | ||||
| d | Total (add lines 1a, 1b, and 1c) | 1d | ||||
| e |
Discount claimed for blockage or other factors (explain in detail in Part VI): |
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| 2 | Acquisition indebtedness applicable to non-exempt use assets | 2 | ||||
| 3 | Subtract line 2 from line 1d | 3 | ||||
| 4 | Cash deemed held for exempt use. Enter 1-1/2% of line 3 (for greater amount, see instructions). | 4 | ||||
| 5 | Net value of non-exempt-use assets (subtract line 4 from line 3) | 5 | ||||
| 6 | Multiply line 5 by .035 | 6 | ||||
| 7 | Recoveries of prior-year distributions | 7 | ||||
| 8 | Minimum Asset Amount (add line 7 to line 6) | 8 | ||||
| Section C - Distributable Amount | Current Year | |||||
| 1 | Adjusted net income for prior year (from Section A, line 8, Column A) | 1 | ||||
| 2 | Enter 85% of line 1 | 2 | ||||
| 3 | Minimum asset amount for prior year (from Section B, line 8, Column A) | 3 | ||||
| 4 | Enter greater of line 2 or line 3 | 4 | ||||
| 5 | Income tax imposed in prior year | 5 | ||||
| 6 | Distributable Amount. Subtract line 5 from line 4, unless subject to emergency temporary reduction (see instructions) | 6 | ||||
| Section D - Distributions | Current Year | |
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| 1 Amounts paid to supported organizations to accomplish exempt purposes | ||
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Amounts paid to perform activity that directly furthers exempt purposes of supported organizations, in excess of income from activity |
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| 3 Administrative expenses paid to accomplish exempt purposes of supported organizations | ||
| 4 Amounts paid to acquire exempt-use assets | ||
| 5 Qualified set-aside amounts (prior IRS approval required) | ||
| 6 Other distributions (describe in Part VI). See instructions | ||
| 7Total annual distributions. Add lines 1 through 6. | ||
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8
Distributions to attentive supported organizations to which the organization is responsive (provide details in Part VI). See instructions |
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| 9 Distributable amount for 2015 from Section C, line 6 | ||
| 10 Line 8 amount divided by Line 9 amount | ||
| Section E - Distribution Allocations (see instructions) |
(i) Excess Distributions |
(ii) Underdistributions Pre-2015 |
(iii) Distributable Amount for 2015 |
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Distributable amount for 2015 from Section C, line 6 |
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Underdistributions, if any, for years prior to 2015 (reasonable cause required--see instructions) |
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| 3 Excess distributions carryover, if any, to 2015: | ||||
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| e From 2014....... | ||||
| fTotal of lines 3a through e | ||||
| g Applied to underdistributions of prior years | ||||
| h Applied to 2015 distributable amount | ||||
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Carryover from 2010 not applied (see instructions) |
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| j Remainder. Subtract lines 3g, 3h, and 3i from 3f. | ||||
| 4Distributions for 2015 from Section D, line 7: | ||||
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| a Applied to underdistributions of prior years | ||||
| b Applied to 2015 distributable amount | ||||
| c Remainder. Subtract lines 4a and 4b from 4. | ||||
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5
Remaining underdistributions for years prior to 2015, if any. Subtract lines 3g and 4a from line 2 (if amount greater than zero, see instructions) |
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Remaining underdistributions for 2015. Subtract lines 3h and 4b from line 1 (if amount greater than zero, see instructions) |
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7 Excess distributions carryover to 2016. Add lines 3j and 4c. |
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| 8 Breakdown of line 7: | ||||
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| c Excess from 2013....... | ||||
| d From 2014....... | ||||
| e From 2015....... | ||||
| Facts And Circumstances Test |
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| Return Reference | Explanation |
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| Software ID: | 15000324 |
| Software Version: | 2015v2.0 |
Attach to Form 990 or 990-EZ.
Information about Schedule O (Form 990 or 990-EZ) and its instructions is at| Return Reference | Explanation |
|---|---|
| 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. |
| 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 estimated for soybean roots and leaves using pairs of soybean lines that differ for SDS resistance genes but are otherwise almost completely identical (these are called near isogenic lines or NILs).(4)Project Title: Exploiting Potential Bio-control Agents to Manage Seedling Diseases of SoybeanLead PI: Ahmad Fakhoury, Budget Amount and Project Year: $139,991 Year 2 Issue and Objectives: The long-term objective of the proposed research is to characterize the bio-control activity of a collection of fungal species isolated from soybean production fields. The ultimate goal is to use potential bio-control agents to improve the management of soybean diseases caused by pathogens present in the soil such as Fusarium spp., Phytophthora sojae, and Pythium spp. This could be achieved either by introducing these bio-control agents to soybean production fields, and/or by fine-tuning existing management practices to enhance the prevalence and activity of bio-control agents native to production fields. Our specific objectives are:Objective 1.Test the effect of a set of recently identified potential bio-control agents on soil-inhabiting fungal, oomycete, and nematode pathogens of soybeanObjective 2.Assess potential roles of these agents in eliciting defense mechanisms in soybean plants Objective 3.Test the effect of fungicidal seed treatments on these organismsObjective 4.Follow the effect of commonly used management practices on the distribution and activity of these organisms in the soil (activity planned for years 2&3 of the project)(5) Project Title: Identifying High-yield Genotypes in the USDA Soybean Germplasm Collection Principle Investigator and Co-PIs: George Graef, University of Nebraska, Kent Eskridge (Statistics, UNL), Randy Nelson (USDA, ARS, Illinois), Brian Diers (University of Illinois), Danny Singh (Iowa State University), Aaron Lorenz and Jim Orf (University of Minnesota), Andrew Scaboo (University of Missouri). Budget Amount and Project Year: $198,601, Year 2Brief Statement of Objectives: The overall objective is to identify the best soybean lines in the USDA collection that will increase soybean yields in the north central region. This research will develop ways to efficiently and effectively sample the over 17,000 introduced soybean accessions and identify the best ones to improve yield and quality in US commercial soybean varieties. Less than 20 PIs make up more than 86% of the parentage of modern US soybean cultivars. Effective use of the other 16,980 accessions becomes a sampling issue. So our approach makes use of the 50K SNP genotype information available on all accessions in the collection to evaluate differences among sampling methods related to genetic diversity, yield, and ability to identify genomic regions related to yield in this vast resource that we have available. We used three sampling methods a super saturated design (SSD), cluster method (CLU) and random selection (RAN) -- to choose PI accessions based on the 50K SNP genotype information. The SSD maximizes differences among all entries in the group, so our expectation is that the lines in the SSD group will have greater genetic variation, and a larger variance for yield and other traits that we measure in our evaluations. The ultimate end goal is to facilitate development of high-yielding soybean cultivars for producers by making efficient use of these genetic resources. |
| 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 Central Region, yet current management options are limited. In addition, this disease is more severe when plants are stressed by heat and dry conditions. New fungicide programs and fungicide products are marketed to reduce plant stress, but these products and programs have not been evaluated to determine their impact on charcoal rot development and yield. The goal of this research is to understand under what conditions fungicides may reduce plant stress and yield loss due to charcoal rot so that we may improve our recommendations to farmers interested in using fungicides to mitigate plant stress and/or to manage charcoal rot.Research objectives:1. Determine efficacy of pre-emergence fungicide applications on M. phaseolinacolonization and soybean yield.2. Evaluate various foliar fungicides applied at different times for efficacy against M. phaseolina to determine optimum foliar fungicide use for charcoal rot management.3. Integrate research findings into NCSRP charcoal rot Extension materials(14)Project Title: Evaluation and Development of a Biological Control Product to Control Soybean Sudden Death Syndrome and White MoldPrinciple Investigator and Co-PIs: X.B. Yang, Iowa State UniversityShrishail Navi, Iowa State University Carl Alan Bradley, University of Illinois Youfu Zhao, University of IllinoisJames Kurle, University of MinnesotaBudget Amount and Project Year: $163,845, Year 3Brief Statement of Objectives: Sudden death syndrome (SDS) and white mold are two of the most important fungal diseases in soybean production in the US, affecting 40 - 50 million acres in the North Central Region. These two diseases threaten the sustainable production of soybean in the North Central Region. Biological control products are the future for disease management in row crops and private industry has made significant progress in development of biological fungicides for row crops. The goal of this proposal is to evaluate their effectiveness of potential biological control agent in other states of the North Central Region and develop the agent into a product for commercial use, which will provide reliable and cost-effective control of SDS and white mold of soybean. Project Objectives: oTo conduct multi-state field evaluation for fungal biological control agents that are found effective in reducing soybean sudden death syndrome and white mold.oTo investigate a wide-host-range bacterial bio-control agent that is effective in killing SDS and white mold pathogens for management of SDS and white mold in Illinois.oTo collect data of prototype product of the biological control agent for commercializationoTo determine if application of the biocontrol agent to crop residues of corn, alfalfa, or soybean can reduce inoculums production, infection, and disease caused by F. virguliforme and Sclerotinia. (15)Project Title: An integrated approach to enhance durability of SCN resistance for long-term, strategic SCN managementPrinciple Investigator and Co-PIs:Dr. Thomas Baum, Professor and ChairCo-PIs: Dr. Greg Tylka, ProfessorDr. Andrew Severin, Scientist IDr. Melissa Mitchum, Associate Professor Dr. Henry Nguyen, MSMC Endowed ProfessorDr. Andrew Scaboo, Assistant Research ProfessorDr. Matthew Hudson, Associate ProfessorDr. Brian Diers, Associate Head, ProfessorBudget Amount and Project Year: $593,260 Year 1Objective 1. Diversify the genetic base of SCN resistance in soybean oObjective 1.1: Develop and evaluate germplasm with new combinations of resistance genes in high yielding backgrounds. (Diers, Nguyen, Scaboo).oObjective 1.2: Determine resistance gene copy number in the experimental lines for more effective breeding. (Diers, Nguyen, Scaboo).Objective 2. Identify SCN virulence factors and better understand how the nematode adapts to resistance oObjective 2.1: Refine SCN genome assembly and its accessibility.?Objective 2.1.1: Improve genome assembly. (Hudson)?Objective 2.1.2: Genome curation and annotation. (Baum, Severin).oObjective 2.2: Conduct comparative population studies to identify genes associated with SCN virulence and evaluate utility as novel resistance targets. (Mitchum, Baum)oObjective 2.3: Determine unique resistance gene stacks that would be beneficial in rotations to enhance durability of SCN resistance. (Diers, Nguyen, Scaboo, Mitchum)Objective 3. Translate the results of objectives 1 and 2 to increase the profitability of soybean for producers (Tylka)oObjective 3.1: Educate growers on how SCN adapts to grow on resistant soybeans. oObjective 3.2: Inform growers on effective rotation schemes designed to protect our resistant sources. |
| 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 and Rationale Need, state-of-the-art, opportunity for farmers and the soybean industry:Sclerotinia sclerotiorum is a fungal pathogen with a worldwide distribution, causing disease on over 400 plant species and up to $252M in losses per year on sunflower, soybeans, dry edible beans, canola, and pulse crops (U.S. Canola Association, 2014). S. sclerotiorum causes considerable damage to soybean and has proven difficult to control (culturally or chemically), with host resistance to this fungus being mostly inadequate. In the temperate north central soybean production areas of the United States, Sclerotinia stem rot (SSR) can be a significant yield limiting disease, with reported losses more than 10 million bushels (270 million kg) per year (Peltier et al., 2012). These impacts on yield are significant and make SSR one of the most important diseases of soybean in the North Central U.S. Although US Congress has appropriations for the National Sclerotinia Initiative, only a small portion of that funding supports research directly related to soybean production in the NC States. Thus, the proposed project is designed to address: factors affecting fungicide efficacy in the NC States, soybean NADPH oxidases as a novel host resistance mechanism for soybean, fungicide resistance emergence, and to develop new outreach and disease management strategies.(18)Project Title: Developing an Integrated Management and Communication Plan for Soybean Sudden Death SyndromePrincipal Investigator: Dr. Daren Mueller, Iowa State UniversityCo-Investigators:Dr. Leonor Leandro, Iowa State UniversityDr. Greg Tylka, Iowa State UniversityDr. J. Arbuckle, Iowa State UniversityDr. Georgeanne Artz, Iowa State UniversityDr. Jamal Faghihi, Purdue UniversityDr. Kiersten Wise, Purdue UniversityDr. Damon Smith, University of WisconsinDr. Virginia Ferris, Purdue UniversityDr. Martin Chilvers, Michigan State UniversityDr. Febina Mathew, South Dakota State UniversityBudget Amount and Project Year: $100,000 Year 1Brief Project Justification and Rationale:The foundational management strategy for sudden death syndrome (SDS) is using resistant cultivars.However, in years such as 2010 when environmental conditions were favorable for disease development, it is evident that resistance alone does not provide adequate control or reduce farmer risk sufficiently, which provides us with an early education awareness opportunity. 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 providing farmers with maximum economic return on their investment even in unusually conducive SDS conditions.Objectives for Year)1:Objective 1. Determine how seed treatments in furrow and foliar fungicides will affect SDSObjective 2. Evaluate if soybean cyst nematode reproduction affects SDS developmentObjective 3. Study how cultural practices affect inoculum levels and SDS developmentObjective 4. Determine a Return On Investment (ROI) for SDS management strategiesObjective 5. Communicate research results with farmers, agribusinesses and other soybean stakeholders(19)Project Title: Development of soybean genotypes with enhanced capacity of nitrogen fixationPrincipal Investigator: Stella K. Kantartzi, Ph.D., Southern Illinois University CarbondaleBudget Amount and Project Year: $26,281 Year 1Brief Project Justification and Rationale Need, state-of-the-art, opportunity for farmers and the soybean industry:Soybean yield increase in the United States has been remarkable. In the last 30 years the rate has been 31.2 kg ha-1 on annual basis and the genetics has been claimed to be responsible for 80% of this gain (Specht et al., 1999). Despite the recent progress in yield potential of new soybean cultivars, many concerns have been raised regarding the capacity of current and future cultivars to meet their nitrogen (N) demand solely by the biological nitrogen fixation (BNF) and available soil N (Salvagiotti et al., 2008). Although soybean grows relying exclusively on its fixed and available soil N, soybean is one of the most N requiring crops (Sinclair and Wit, 1975). N removal in the harvested seeds is estimated to be 3.5 lb bu-1 for soybean (Salvagiotti et al., 2008), while only 0.78 lb bu-1 for corn. Therefore, farmers are more likely to face N shortage due to high N removals either by planting new high-yielding soybean cultivars or by not supplying the required N either with inorganic N fertilizer. In order to avoid a shortage of N supply affecting yield potential, the high yielding soybean cultivars grown in high quality environments require a continuous selection of more efficient Bradyrhizobium strains as well as genotypes with a higher capacity of BNF. This will allow meeting future soybean N demand without N fertilizer input (Nicols et al., 2002). |
| 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, ISUBerlin Nelson, NDSUAlbert Tenuta, Ontario Min. of Ag.Budget Amount and Project Year: $269,501 Year 1Brief Project Justification and Rationale: Soilborne seedling and root diseases of soybean significantly reduce yields in the North Central region of the United States. Seedling diseases rank among the top 4 pathogen threats to soybean, because their insidious nature makes them difficult to diagnose and control. It is nearly impossible to predict when they will take a heavy toll, until it happens. The challenges and failures of managing soilborne diseases and pathogens of soybean and other crops are based in part on limitations in knowledge and methods. This project will address critical limitations in identifying and managing seedling diseases. Producers and industry will see benefits in the form of rapid diagnostics and management recommendations. This benefit will also help industry in their assessments in pesticides and germplasm development. Producers will also see their check-off funding being maximized by the synergy of this team, the USB seedling disease project and the USDA-NIFA oomcyete project. This project complements the USB seedling disease project. (23)Project Title: Soybean Entomology in the North Central Region: Management and Outreach for New and Existing PestsPrincipal Investigator: Kelley Tilmon, The Ohio State University. Brian Diers, University of Illinois, Glen Hartman, USDA-ARS at University of Illinois, Christian Krupke, Purdue University, Punya Nachappa, Indiana University- Purdue University Fort Wayne, Matt ONeal, Iowa State University, Erin Hodgson, Iowa State University, Brian McCormack, Kansas State University, Deborah Finke, University of Missouri, George Heimpel, University of Minnesota, Bruce Potter, University of Minnesota, Robert Koch, University of Minnesota, Tom Hunt, University of Nebraska, Robert Wright, University of Nebraska, Deirdre Prischmann, North Dakota State University, Janet Knodel, North Dakota State University, Andy Michel, Ohio State University, Budget amount and Project Year: $427,192 Year 1Brief Description of Proposed Research: The Extension and Outreach component of this proposal is to ensure that the research results generated by the other three Program Areas are delivered to soybean producers and other stakeholders in a user-friendly format, in a coordinated fashion. In an era of shrinking extension systems and budgets and reduced extension staff, we believe a coordinated approach to NCSRP content delivery is an efficient use of project resources. Our entomology team has a good track record of providing such deliverables. For example, in our previous project we produced the NCSRP Soybean Aphid Field Guide (with 17,500 hard copies distributed in the region, and a free download available on NCSRPs Soybean Research and Information Initiative website); the Visual Guide to Counting Soybean Aphids field scouting card (4000 copies distributed, plus free download); a 3-part webinar series on soybean aphid management for the Plant Management Network (open-access presentations available any time); an award-winning a 3-part animated video series to educate producers on aphid-resistant soybean varieties; a postcard with flash drive to distribute multiple NCSRP publications while reducing printing costs (2000 copies distributed); an NCSRP multistate research field event in the summer of 2014; and an outreach booth at the 2015 Commodity Classic where we distributed outreach material and made approximately 2,000 direct stakeholder contacts. |
| 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 providing farmers with maximum economic return on their investment even in unusually conducive SDS conditions. Objective 1. Evaluate if soybean root health can be improved to reduce SDS or be used as an indicator of SDS risk.Objective 2. Determine how shifts in soybean production practices affect the risk of SDS development.Objective 3. Communicate research results with farmers, agribusinesses.Examined the effect of glyphosate on SDS. Study has been published in Plant Disease. Study of effect of interaction between herbicide and seed treatment on SDS is ongoing. We collected and analyzed the first year data. Completed a multi-lab study evaluating performance of six qPCR assays developed for F. virguliforme. The manuscript was submitted for publication to Phytopathology. In this study, we compared the strengths and weakness of all six assays under different research facilities in terms of their specificity, sensitivity, and consistency and also identified an effective protocol for better diagnosis and quantify SDS pathogen. To summarize, assays differed in their performances and also the performance of the same assay varied among the laboratories. An assay developed in Chilvers lab showed the highest sensitivity and the second highest specificity, and thus is suggested as the most useful qPCR assay for F. virguliforme. This assay is currently being used for quantifying F. virguliforme population in root and soil in other objectives. Identified seed treatments to reduce SDS foliar symptoms. We completed a study evaluating planting date and seed treatment effect on SDS development. Manuscripts are being written to peer-reviewed journals. To summarize, ILeVO seed treatment reduced disease severity and increased yield nearly in all plantings and cultivars, with a maximum yield response up to 21% (Roland Iowa). Effect of planting date on foliar SDS symptoms was inconclusive. Although Mid-June plantings did not have higher disease than early plantings it yielded lower grain up to 19 bu/A compared to early May plantings.Evaluated different fungicide products and application methods to see if any would complement cultivar resistance Manuscript is being written for publication in peer-reviewed journal. We are continuing this study in 2015 replacing some products and foliar applications with new chemical and biological products. From this study, the main conclusion was that ILeVO seed treatment and Luna Privilege in-furrow were effective at reducing SDS severity in many different environments compared to the control. Foliar applications of any chemicals had no effect on SDS. Collected SCN, SDS and yield data from all participating states and data analysis is being done. We will continue this experiment in 2015 as well. However, so far we found varieties with Peking source of resistance for SCN had lowest SDS in many environments and varieties with no resistance to SDS and SCN had the highest disease. Presented our preliminary research at professional meetings, on Plant Management Network, gave national and international seminars, media interviews, talk in field days and conferences for farmers and also published in state newsletter articles, 20+ media releases etc. To communicate with researchers, we also published or are in the process of publishing in peer-reviewed journals. We also had several press releases, including some jointly with NCSRP, based on results from this project (e.g., glyphosate study, ILeVO study).(10)Project Title: Accelerating soybean yield improvement by utilizing yield genes from soybean wild relativesPrinciple Investigator and Co-PIs: Randall Nelson (PI), USDA-ARS, University of Illinois, Jianxin Ma, Purdue University, Matthew Hudson, Patrick Brown and Brian Diers, University of Illinois, Ram Singh, USDA-ARS, Urbana; George Graef, University of Nebraska-Lincoln.Budget Amount and Project Year: $181,875, Year 2Brief Statement of Objectives:Our objective is to identify and genetically characterize high-yielding lines derived from the wild relatives of soybean that can be used to infuse unique and highly productive yield genes into new soybean varieties. We have three sub-objectives that will help us achieve this goal. First, using the highest yielding experimental lines derived from crossing Dwight by PI 441001 (G. tomentella), we will genetically map the location of the genes/chromosomal regions responsible for these large yield increases. Secondly, using large populations of the inbred lines derived from crosses of the soybean variety, Williams 82, with the wild soybean accessions PI 483916 and PI 479752, we will precisely map agronomically important genes associated with the major differences between soybean and wild soybean. Finally, we will yield test experimental lines derived from up to eight wild soybean accessions and identify chromosomal regions from the wild soybean parent that are adjacent to (but do not contain) the genes that condition the wild soybean plant type. This will put a prio |
| Software ID: | 15000324 |
| Software Version: | 2015v2.0 |