2 0 0 7 R E S E A R C H R E P O R T S 2007 Wheat Research ... · present, FHB and leaf diseases are mainly managed through fungicides application and cultural practices. Although

2 0 0 7 R E S E A R C H R E P O R T S

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2007 Wheat Research Review

A report of research projects advised by the Small Grains Research & Communications Committee

funded in part by the Minnesota Wheat Checkoff

and administered by the Minnesota Wheat Research & Promotion Council


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On the following pages, you will find a compilation of wheat research projects funded in part by the Minnesota Wheat Checkoff adminis-

tered by the Minnesota Wheat Research & Promotion Council.

Before these projects were funded, they were first discussed and rec-ommended by the Small Grains Research & Communications commit-tee. This committee has served in an advisory capacity to the state’s wheat and barley production sector since 1992. With a limited base of funds generated by our state’s wheat checkoff, we need to get the most out of any research that is funded and leverage those dollars with funds from other sources. That’s why we formed this group represent-ing producers, state and federal crop scientists, the media, and the agribusiness sector, to identify crop problems and industry challenges and prioritize research projects.

Researchers submit progress reports on projects funded partially or in full by the committee’s recommendation. Research progress is com-municated to the public. Crop scientists participate in a research re-porting session held each year that is open to the public. The Council feels this committee has been an efficient vehicle for not only prioritiz-ing wheat checkoff funds, but also in improving the dissemination of results.

Better practices to plant better wheat is our goal. To that end, we en-courage your input on this committee, and your feedback on the wheat research projects that are funded by the Minnesota Wheat Checkoff.

Information about the committee and previously funded research can be found online at www.smallgrains.org. Click on the Research tab.

Ken Asp, ChairmanMinnesota Wheat Research & Promotion Council


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2007 Small Grains Research & Communications Committee

David TorgersonMinnesota Wheat 2600 Wheat DrRed Lake Falls, MN 56750-4800Phone: 800-242-6118Fax: 218-253-4320E-mail: [email protected]

Marv ZutzMinnesota Barley2601 Wheat DrRed Lake Falls, MN 56750Phone: 218-253-4311Fax: 218-253-4320E-mail: [email protected]

Kenneth Asp 17880 – 170th St NW Thief River Falls, MN 56701 Phone: 218-681-3272 Fax: 218-681-3717 (attn: Key) E-mail: [email protected]

David Boehm Northern Plains Regional Mgr. AgriPro Wheat PO Box 5027 West Fargo, ND 58078 Phone: 701-298-0511 E-mail: [email protected]

Mike BruerMinnesota Wheat Council2663 – 570th AveAlberta, MN 56207-4648Phone: 320-324-7577Fax: 320-324-7576E-mail: [email protected] Doug Holen Regional Extension Service 223 West Cavour Ave Fergus Falls, MN 56537 Phone: 218-998-5792 Fax: 218-998-5798 E-mail: [email protected]

Carol Ishimaru U of M Dept of Plant Pathology495 Borlaug Hall1991 Upper Buford CircleSt. Paul, MN 55108Phone: 651-625-4705 Email: [email protected]

Ex-Officio Members

Members

Brian Jensen 41439 - 330th Ave NW Stephen, MN 56757-9591 Phone: 218-478-3397 Email: [email protected]

Mark Jossund1806 29th St Cir SMoorhead, MN 56560Phone: 218-233-1561E-mail: [email protected]

Brian Lacey 33157 – 320th Ave Wendell, MN 56590-9751 Phone: 218-458-2595 E-mail: [email protected]

Rhonda K Larson46518 - 110th St SWEast Grand Forks, MN 56721-9029Phone: 218-773-1602Cell: 218-779-7101E-mail: [email protected]

Richard Magnusson Minnesota Wheat 37605 State Hwy 11 Roseau, MN 56751-9079 Phone: 218-463-2374 Fax: 218-463-5034 E-mail: [email protected]

Dean Maruska Bayer CropScience 30736 - 290th Ave NW Argule, MN 56713 Phone: 218-437-6051 Fax: 218-686-0500 E-mail: [email protected]

Jim Murn Centrol Crop Consulting PO Box 367 Twin Valley, MN 56584-0367 Phone: 218-854-5107 E-mail: [email protected]

Brian SorensonNorthern Crops Institute1240 Bolley Drive, NDSUFargo, ND 58105-5184Phone: 701-231-6048E-mail: [email protected] Kyle Vig 45500 - 310th Ave SE Fosston, MN 56542-9730 Phone: 218-435-1368 E-Mail: [email protected]

Dr. Jochum Wiersma University of Minnesota 108 ARC Bldg Crookston, MN 56716-5001 Phone: 218-281-8629 Fax: 218-281-8603E-mail: [email protected]

Neil Wiese PO Box 11Humboldt, MN 56731-0011Phone: 218-379-3181E-mail: [email protected]


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Table of ContentsContinuation of a Regional Disease Forecasting System and Validation of the System at Wheat and Barley Farmer’s Fields Shaukat Ali, NDSU, Fargo................................................................................................Page 6

Accelerated Breeding for Resistance to Fusarium Head BlightKarl D. Glover, Plant Science Dept., South Dakota State University................................Page 9

Wheat Breeding and Genetics James A. Anderson, Department of Agronomy and Plant Genetics, U of M....................Page 13

Incorporation of New Resistance Genes for Tan Spot in Adapted Common Wheat and Durum Varieties P.K. Singh, Department of Plant Sciences, NDSU .........................................................Page 15

Development of Tools to More Accurately Predict In-Season Spring Wheat Nitrogen Needs for Yield and ProteinAlbert L. Sims, Northwest Research & Outreach Center, U of M....................................Page 20

Identifying High Hard Red Spring Wheat Cultivars with High Yield Potential to Meet Special End-uses Mohamed Mergoum, Department of Plant Sciences, NDSU...........................................Page 28

Soft Red Winter Wheat Germplasm Evaluation Jochum J. Wiersma, Northwest Research & Outreach Center, Crookston .....................Page 31

Red River Valley Winter Wheat Production & Responses of Management Inputs on Yield, Quality and EconomicsJochum J. Wiersma, Northwest Research & Outreach Center, Crookston .....................Page 32

Liquid vs Dry Phosphorus Fertilizer Formulations with Air Seeders Jochum J. Wiersma, Northwest Research & Outreach Center, Crookston .....................Page 34

Continuation of the Intensive Management of the State Variety Trials for Hard Red Spring Wheat Jochum J. Wiersma, Northwest Research & Outreach Center, Crookston .....................Page 35

Wheat Rotation EconomicsKent D. Olson, Department of Applied Economics, U of M..............................................Page 38

2007 Red River Valley On-Farm Disease Management TrialsCharla Hollingsworth, Northwest Research & Outreach Center, Crookston....................Page 40

2007 Spring Wheat and Barley Variety Performance in Minnesota...........................Page 45 (Preliminary Report)


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Continuation of a Regional Disease Forecasting System and Validation of the System at Wheat

and Barley Farmer’s Fields

Research Question

Can a regional Small Grain Wheat Disease Fore-casting System help growers increase productivity, crop quality, and profit margin?

Executive Summary

Wheat in North Dakota and Minnesota is grown on multi-millions acres every year. Spring wheat (Triti-cum aestivum) was grown on approximately 8 million acres in North Dakota and Minnesota in 2006. The crop is attacked by various leaf (tan spot, stagono-spra nodorum blotch, and leaf rust) and head (Fusar-ium head blight or scab) fungal pathogens, which can cause millions of dollars loss by affecting both quality and yield. For example, epidemics of Fusarium head blight (FHB) caused more than a billon dollars loss to wheat and barley growers and related industries in the Dakotas since 1993. These diseases can be managed through multiple practices, such as crop rotation with non-cereals, residue management, fun-gicides, and use of resistant cultivars. Application of fungicides and use of resistant cultivars seem to be more promising disease management strategies, as cultural practices such as crop rotation and burying crop residue are not practicable under some condi-tions. Currently, a few commercial cultivars with mod-erate resistance to head scab and leaf diseases are available; however, all wheat acreages in the states are not planted with these cultivars due to market-ing and other growers issues. It also is not desirable to plant vast areas with a small genetic diversity because an epidemic of another disease (For ex-ample leaf rust) can wipe out the crop, similar to the devastating 1970 southern corn blight epidemic. At present, FHB and leaf diseases are mainly managed through fungicides application and cultural practices.

Although fungicides are available to manage the diseases, there are two major constraints of using them: 1) increases in production costs and 2) work-ers and environment exposure to chemicals. A deci-sion system is needed to accurately predict when an economic threshold of disease will occur, so that wise decision can be made about fungicide application.

In response to growers need, a wheat disease forecasting system was developed at NDSU and deployed in 1999, and a forecast was provided for tan spot and Septoria leaf blotch for 17 locations. In the year 2000, the system was expanded for leaf rust and Fusarium head scab and the forecast was pro-vided for 24 locations. Currently, the forecast is pro-vided for 70 locations, 60 in North Dakota and 10 in Minnesota. The system predicts leaf diseases based on computer models that use primarily wet period hours and temperature suitable for the disease devel-opment, with the assumption that pathogen inoculum is always available in the field; whereas, computer models for the forecast of Fusarium head blight are based on weather conditions (temperature and amount of rain or humidity conducive for the disease development, present during the 10 days pre-flower-ing.. The forecast information is provided to the end users through the NDSU wheat disease forecasting website and a toll free 1-800 phone service.

The North Dakota State Board of Agriculture Re-search and Education (SBARE) has played major role in financing for the development of the forecast-ing system. Three graduate students and several undergraduate students have been fully and/or partially funded during the development and main-tenance of the system over the last seven years. In the last five years, results of yield responses to fungicides in replicated trials conducted by Dr. Marcia McMullen (NDSU Extension Plant Pathologist) at Fargo, Carrington, Minot, and Langdon corresponded well with disease risks indicated by the foliar disease forecasting models and confirm the system’s valida-tion. Similarly, the system correctly predicted scab disease risk. Adoption of the system by North Dakota

Shaukat Ali, NDSU, Fargo, ND

Final progress report on the continuation of the Regional Disease Forecasting System “NDSU Small Grain Disease Forecasting System”Submitted By Drs. Shaukat Ali and Marcia McMullen


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and Minnesota growers has been rapid and feedback has been positive. Every year, growers access the system several thousands of times to obtain fore-cast information. For example, in 2006, the disease forecasting web page was visited 7088 times during the crop season. The forecasts also were accessed a couple hundred times through the toll free 1-800 phone service treatments. Anecdotal information indicates that since the time that the NDSU Small Grains Disease Forecasting System was deployed, wheat growers in North Dakota and Minnesota have sprayed millions of acres of wheat with fungicides to manage leaf diseases and Fusarium head blight, when the forecasting system indicated fungicide use was warranted. Representatives on the SBARE wheat committee have seen positive results from us-ing the system and have expressed an interest in its continuation. Additionally, they supported the system for legislative action to allocate funds permanently for maintaining the system the in future. In 2007, the funds were made available by the ND legislative, Minnesota Wheat Research and Promotion Council, and a private chemical company (Bayer) to bear the operational costs of the system.

Projective Objectives

Two specific objectives of this project were: 1) de-velopment and deployment of a small grains disease forecasting system for multiple leaf diseases and Fusarium head scab, and 2) continue to main the existing NDSU Small Grains Disease Forecasting System.

Results

The results of the last seven years indicated: • The system accurately predicted the potential for leaf and head disease epidemics. • Yield responses to fungicides in replicated trials at Carrington, Fargo, Langdon, and Minot corre-sponded well with disease risks indicated by the foliar disease forecasting models. • Dr. Marcia McMullen trained every year cereal producers about use of the forecasting system at wheat workshops before the crop season. • In 2006 only, the disease forecasting web page was visited 7088 times. The forecasts also were ac-cessed a couple hundred times through the toll free 1-800 phone service. • Besides the traditional interest from spring wheat and durum producers, winter wheat and barley

industries and some chemical companies also are interested in the system. • In 2007, the system provided forecast for FHB and three leaf diseases of wheat for 60 locations in North Dakota and 10 in Minnesota. • In future, ND legislative will bear the operational cost of the system.

Application/Use

Profit margins in wheat production are not generally high, and often the use of fungicides for managing leaf and head diseases is thought to be a break-even proposition. Currently, some fungicides are available in the wheat market that provide promising leaf and head disease control and flexibility for wheat produc-ers, but growers still reluctant to increase their inputs cost during the season without some assurance of a good return. The NDSU Small Grain Disease Forecasting System provides scientifically sound support for that disease management decision. An ecdotal information from producers, the crop produc-tion industry, extension agents, and crop consultants indicates that individuals sprayed close to a million of wheat acres only in 2006 by watching the forecasts. Besides the traditional interest from spring wheat and durum producers, winter wheat and barley industries and some chemical companies also are interested in the system. Materials and Methods

In response to North Dakota and Minnesota wheat growers, the North Dakota Small Grain Disease Forecasting System was originally developed by Dr. Leonard Francl (late) and his graduate student Erick DeWolf at NDSU for two leaf diseases, tan spot and Stagonospora leaf blotch. It was deployed for fore-casts in North Dakota and in northwestern Minnesota in 1999. Subsequently, the system added leaf rust and Fusarium head blight to the forecasting models. The forecasts for FHB, leaf rust, Satgonospora blotch and tan spot, were based on computer models. Every 24 hours, models predicted the suitability for infec-tion; thus, these daily updates provided timely infor-mation about fungicide need. Leaf disease and FHB infection periods are determined based on weather information from the North Dakota Agricultural Net-work (NDAWN); the initial FHB forecasting system also had information about pathogen spore counts at multiple locations in ND and MN. The forecast in-formation is delivered through a toll free number and


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internet website. In 2004, the system was upgraded with an improved FHB forecast computer model and the Fusarium spore count component was omitted from the disease forecast. Although the spore count component was omitted from the system, correla-tion between spore counts and disease incidence was still studied at on NDSU Plant Pathology experi-mental area in Fargo in 2004 and 2005. The results of these two years experiments indicate that FHB incidence was significantly different under differ-ent inoculum level treatments, with higher inoculum levels generally resulting in higher FHB incidence. Currently, several risks assessments models for FHB are under development for further refinements in the presently used models.

Economic Benefit to a Typical 500 Acre Wheat Enterprise

Net return depends on the performance accuracy of the system, disease severity, and crop response to fungicide. At present the disease models for leaf and head disease forecast at NDSU are about 80% ac-curate in predictions. Not all wheat cultivars respond equally to fungicide application; however, on an aver-age, fungicide studies across ND have seen about a 20% yield response on popular, commercially grown cultivars. For example in 2007, with 80% accuracy, a 10 bushes yield increase at $9.12 per bushel market price, and a $13.50 fungicide application cost/acre, a net gain of $29,730 would occur, on average. More-over, if the system predicts no fungicide application required, the farmer would save $6,750.00 on 500 acres by avoiding unnecessary input. Related Research

This project was integrated with the North Dakota forecasting system to cover both sides of the Red River valley as well as other areas in North Dakota. Local funds were being sought primarily for annual operations.

Recommended Future Research

Dr. Shaukat Ali would maintain the system during 2008 crop season.


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Accelerated Breeding for Resistance to Fusarium Head Blight

Karl D. Glover, Plant Sciences Department, SDSU

Research Question

Complete resistance to Fusarium Head Blight (FHB) is unknown, yet genetic variability for resistance is well documented. Steady progress toward increasing resistance levels has been demonstrated by breeding programs through the implementation of repeatable screening procedures. Breeding programs must sus-tain efforts to simultaneously select resistant materi-als with desirable agronomic characteristics. The objective of this program is to use traditional plant breeding and selection techniques to develop hard spring wheat varieties that possess agronomic char-acteristics worthy of release in addition to acceptable levels of FHB resistance.

Results We have progressed to the point where most entries retained in our advanced yield trial (AYT) are thought to be at least moderately resistant to FHB. Entries that do not perform adequately are generally discarded after the first year of AYT observation. Our 2007 AYT results are presented in the appendix. Dur-ing the 2007 growing season, 42 entries were tested within the AYT. Twelve of these experimental entries had FHB disease index values that were less than the test average. Thirty-one of the 42 entries were found to have tombstone ratings that were less than average. Of the twelve entries with below average disease index values, eleven also had less than aver-age tombstone ratings. Ten of the eleven produced more grain than average and seven had test weights that were heavier than average. Finally, two of the seven also had above average protein concentra-tions. Specifically, these entries were SD4017 and SD4027. We have initiated the process of increasing each of these entries for potential release as soon as 2010. Of particular interest at this point, however, is SD3851. Over the past several testing years, SD3851 has become known as a line with very heavy test weight, good yield potential, early heading date, and perhaps the highest level of FHB resistance that we have identified (Tables 1 and 2). It is presently growing in an increase field for the second time in California. It will be further increased in South Dakota during 2008 in preparation for release to growers in 2009.

Application/Use

With the progression of time, increases in FHB resistance levels should help to prevent devastating loses to growers caused by severe FHB outbreaks.

Materials and Methods

Breeding efforts to increase resistance began within this program after the 1993 FHB epidemic in the spring wheat production region. Both mist-irrigated greenhouse and field screening nurseries were established and disease evaluation methods were developed. Breeding materials are evaluated for FHB resistance using three generations per year: two in the greenhouse and one in the field. We have the capacity to screen 4000 individual hills in each green-house season. We also have 4 acres in the field under mist-irrigation. Both the field and greenhouse nurseries are inoculated with grain spawn (corn and wheat that is infested with the causal fungus) and spore suspensions. Mist-irrigation is used to provide a favorable environment for infection. Approximately 25 percent of the experimental populations possess Fhb1 as a source of resistance. Most of what remains are crosses with various “field resistant” advanced breeding lines. Experimental materials are advanced through the program in the following fashion;

Year 1 Field Space planted F2 populationsYear 1 Fall greenhouse F2:3 hillsYear 1 Spring greenhouse F�:� hillsYear 2 Field F4:5 progeny rowsYear 2 Off-season Nursery F5:6 progeny rowsYear 3 Field F5:7 Yield Trials (1 replication, 2 locations)Year 4 Field F5:8 Yield Trials (2 replications, 5 locations)Year 5 Field Advanced Yield Trials (3 reps, 9 locations)

F2 populations are planted in the field and individual plants are selected. These are advanced to the fall screening greenhouse where seed from each plant is sown as individual F2:3 hills and evaluated for FHB re-sistance. Four plants from each of the top 25% of the hills are advanced to the spring greenhouse. They are sown as individual F�:� hills and evaluated for FHB resistance. Those with FHB resistance nearly


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equal to or better than ND2710 are advanced to the mist-irrigated field nursery as F4:5 progeny rows. They are evaluated again for resistance and general ag-ronomic performance. Plants are selected within the superior progeny rows and sent to New Zealand as F5:6 progeny rows for seed increase. A portion of seed from each selected plant is also grown in the fall greenhouse to confirm that the resistance is stable. If the FHB resistance of an F5:6 line is confirmed, then the respective progeny row is harvested in New Zealand. In the following South Dakota field season, the selected lines are tested in a two replication, multi-location yield trial. Those that have agronomic performance and yield similar to current varieties are included in more advanced multi-location, replicated yield trials the following year. In year 5, the lines advanced through this program are included in our

AYT along with entries from the traditional breeding program. Agronomic and FHB data collected from the 2007 AYT are presented in the appendix along with 2006 – 2007 averages of AYT entries which were common over the two years.


The presence of FHB inoculum within fields and favorable weather conditions are just two factors that heavily influence whether this disease will become problematic. Immediate economic benefits are there-fore difficult to assess. When conditions become fa-vorable for disease presence, however, varieties with elevated FHB resistance levels can help to reduce potentially serious losses for growers.

ENTRY FHB

DISINDEX

TOMB-STONE

(%)

GRAINYIELD

(BU/AC)

TESTWEIGHT(LB/BU)

HEADDATE

(D > 6/1)

PLANTHEIGHT

(INCHES)

GRAINPROTEIN

(%) SD3851 5.54 2.00 43.31 59.85 17.14 36.61 14.74 SD3942 16.15 2.67 48.86 58.77 18.36 34.40 13.77 SD3944 19.66 2.67 49.60 58.95 18.72 37.10 14.22 SD3976 19.71 3.83 43.20 60.02 18.92 36.84 15.41 SD3943 20.66 2.33 50.03 59.26 18.64 35.66 13.84 SD3948 24.98 5.00 45.65 59.66 17.86 36.78 14.72 SD3956 25.33 4.00 42.21 59.35 18.06 36.64 14.47 SD3868 25.99 30.83 47.17 56.95 18.89 37.77 13.97 KNUDSON 27.23 3.00 44.01 58.10 18.88 36.07 15.20 BRIGGS 27.46 3.33 45.78 58.54 18.89 36.27 15.20 SD3997 27.54 6.17 44.68 58.99 19.56 40.20 14.93 SD3965 27.77 3.67 45.16 57.82 19.31 38.30 14.02 ALSEN 28.61 11.67 36.28 57.28 21.92 35.16 15.41 SD3870 30.17 7.33 44.41 58.58 19.47 39.55 14.95 TRAVERSE 30.52 40.83 47.25 55.92 19.92 38.73 13.90 WALWORTH 30.70 4.33 41.08 57.13 19.76 36.32 14.70 GRANGER 32.17 9.50 46.17 58.61 20.67 39.90 14.55 RUSS 34.83 6.50 41.59 56.67 20.58 38.29 14.28 STEELE-ND 35.83 10.00 46.95 58.58 21.00 37.69 15.06 SD3983 36.59 3.33 46.06 58.51 20.00 37.18 14.05

Table 2. South Dakota State University advanced yield trial spring wheat entries ranked according to FHB disease index values (lowest to highest – collected at Brookings) presented along with agronomic data obtained from three replication tests conducted at eight test environments in both 2006 and 2007.

continued........


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Table 1. South Dakota State University advanced yield trial spring wheat entries ranked according to FHB disease index values (lowest to highest – collected at Brookings) presented along with agronomic data obtained from three replication tests conducted at eight test environments in 2007.

ENTRY FHBDIS

INDEX

TOMB-STONE

(%)

GRAINYIELD

(BU/AC)

TESTWEIGHT(LB/BU)

HEADDATE

(D > 6/1)

PLANTHEIGHT

(INCHES)

GRAINPROTEIN

(%) SD3851 0.42 1.67 42.87 59.21 16.44 36.35 13.97 SD4027 0.43 12.67 51.07 58.70 15.67 36.50 14.23 SD3942 22.47 3.00 49.98 56.49 17.61 33.97 13.51 SD3976 25.02 1.67 45.85 59.74 18.00 36.50 15.18 SD4017 25.98 8.67 48.33 57.37 18.72 36.14 14.52 SD3944 28.33 3.00 51.43 58.09 17.83 36.87 13.90 SD4011 29.00 4.33 47.67 56.59 18.33 34.53 15.13 SD3943 29.47 2.33 52.20 57.95 17.78 35.46 13.50 SD4023 35.33 5.67 47.71 57.86 20.11 33.55 13.77 SD3948 36.97 6.33 50.27 58.55 17.11 36.95 14.14 SD4073 37.83 41.67 48.56 55.12 20.33 35.97 14.07 SD3956 38.40 3.67 43.83 58.94 17.17 36.70 13.86 BRIGGS 38.80 2.33 49.43 57.67 17.89 36.35 14.75 ALSEN 39.50 8.33 37.77 56.72 20.78 34.71 15.11 SD4009 39.83 3.67 46.38 57.02 18.94 34.76 14.68 SD3868 40.67 55.00 45.87 56.04 18.11 37.28 13.43 SD4037 41.19 36.00 43.93 55.42 17.61 29.69 13.45 SD4033 41.33 16.67 47.87 58.60 19.56 34.18 13.80 KNUDSON 41.67 2.33 44.97 57.17 18.28 36.04 14.72 REEDER 42.00 9.33 32.67 54.36 20.78 35.49 14.09 SD3965 42.49 3.00 46.96 57.23 17.94 37.81 13.71 GRANGER 43.17 9.33 48.36 58.19 19.22 39.93 14.20

ENTRYFHBDIS

INDEX

TOMB-STONE

(%)

GRAINYIELD

(BU/AC)

TESTWEIGHT(LB/BU)

HEATDATE

(D>6/1)

PLANTHEIGHT

(INCHES)

GRAINPROTEIN

(%) SD3927 37.78 8.50 45.53 58.78 23.11 36.28 14.18 REEDER 38.83 13.00 35.95 55.78 22.69 35.34 14.47 KELBY 41.96 9.83 40.44 58.17 20.42 30.42 15.56 OXEN 42.73 27.50 40.06 56.01 20.11 34.05 14.32

MEAN 28.70 9.24 44.23 58.18 19.70 36.73 14.58LSD (0.05) 10.55 12.64 2.21 0.57 0.39 1.83 0.25CV % 29.86 107.36 8.30 2.12 7.42 5.69 3.71

continued........

Table 2. Continued....


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ENTRY FHBDIS

INDEX

TOMB-STONE

(%)

GRAINYIELD

(BU/AC)

TESTWEIGHT(LB/BU)

HEADDATE

(D>6/1)

PLANTHEIGHT

(INCHES)

GRAINPROTEIN

(%) SD4059 43.17 25.67 46.58 57.48 19.28 37.43 14.17 TRAVERSE 43.83 30.00 49.05 55.12 18.50 38.49 13.49 RUSS 44.17 5.67 41.57 55.40 19.28 37.83 13.91 SD4018 44.17 18.33 49.06 56.65 18.67 34.43 14.44 SD4029 44.33 58.33 45.89 54.51 19.61 34.15 13.68 SD4046 44.83 10.00 45.61 57.69 19.56 38.41 13.68 SD4072 45.33 10.00 48.69 56.29 19.28 35.61 14.06 SD4070 45.50 5.33 48.27 57.07 19.50 36.19 14.75 SD3997 45.50 3.67 46.57 58.77 18.50 40.08 14.75 WALWORTH 46.33 5.67 39.44 56.17 18.89 36.47 14.23 SD3870 46.67 10.33 44.07 57.52 18.50 38.89 14.30 SD4036 47.00 36.00 48.97 56.53 17.83 30.24 13.68 SD3983 47.33 3.00 47.33 57.77 18.56 36.85 13.67 STEELE-ND 47.67 8.33 48.82 58.20 19.67 37.43 14.76 SD4024 49.17 10.00 49.02 58.00 21.17 32.94 13.97 SD4007 50.17 4.33 49.02 57.00 18.17 34.63 14.79 SD4035 50.67 15.33 49.10 56.98 18.33 33.52 13.85 SD3927 52.17 8.67 46.74 58.70 21.72 35.94 13.64 KELBY 56.83 7.33 41.39 57.75 19.28 29.79 15.25 OXEN 57.17 38.33 39.65 54.96 18.67 33.85 14.00

MEAN 39.81 13.21 46.40 57.17 18.74 35.69 14.16LSD (0.05) 15.88 29.30 2.80 0.61 0.48 0.95 0.27CV % 14.13 116.22 8.67 2.22 5.87 7.06 3.53

Table 1. Continued...


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Research Question

The objectives of this proposal are to i) develop improved varieties and germplasm combining high grain yield, disease resistance, and end-use quality; and ii) provide performance data on wheat varieties adapted to the state of Minnesota.

Results

RB07 (MN99436-6) was released in 2007. RB07 is an early semi-dwarf with moderately strong straw. RB07 is highly resistant to prevalent races of leaf rust, resistant to stem rust, moderately resistant to other leaf diseases, and has moderate resistance to Fusarium head blight, intermediate between the levels of Alsen and Oklee. RB07 has high and consistent grain yields with average test weight and above average protein. An exclusive licensing agree-ment was reached for the wheat line MN00261-4 (MN95286/MN94155//Verde). MN00261-4 is a late semidwarf with moderately strong straw. MN00261-4 is moderately resistant to prevalent races of leaf rust, resistant to stem rust, moderately resistant to other leaf diseases, and is moderately resistant to Fu-sarium head blight, similar to Alsen. MN00261-4 has high grain yields and average test weight and protein.

During the 2006/2007 crossing cycle, 261 crosses were made. The Variety Trial, which contained 34 released varieties, 11 University of Minnesota ex-perimental lines, and 3 experimental lines from other programs and was grown at Crookston, Lamberton, Morris, Roseau, St. Paul, Stephen, and Waseca. During the 2007 growing season, 120 advanced experimental lines were evaluated in replicated advanced yield trials at Crookston, Morris, and St. Paul. A total of 370 preliminary yield trial lines were tested in unreplicated plots at Crookston, Morris, and St. Paul. Fusarium-inoculated, misted, replicated nurseries were established at Crookston, Morris, and St. Paul. A tan spot-inoculated, misted, replicated nurseries was established at St. Paul. The disease nurseries involve collaboration with agronomists and pathologists at Crookston and Morris and with per-sonnel from the Plant Pathology Department and the USDA-ARS. Data from the yield and scab nurseries are summarized and published in Prairie Grains and

Wheat Breeding and GeneticsJames A. Anderson, Dept. of Agronomy and Plant Genetics, U of M

the U of M Extension Service’s Minnesota Varietal Trials Results.

One advanced experimental line, MN01311-A-1, underwent seed increase during 2007 and is a candidate for release in 2007. MN01311-A-1 (97T-1003/Verde) has medium maturity, height, and straw strength. MN01311-A-1 has shown consistently high grain yields, especially in northern locations, moder-ate leaf rust resistance, and Fusarium head blight resistance comparable to Alsen. MN01311-A-1 has above average test weight and grain protein.

Application and Use

Experimental lines that show improvement over currently available varieties are recommended for release. Improved germplasm is shared with other breeding programs in the region. Scientific informa-tion related to efficiency of breeding for particular criteria is presented at local, regional, national, and international meetings and published.


All yield nurseries are grown in small, replicated plots (typically 40-50 sq. ft. harvested area per plot). Fusarium-inoculated nurseries at Crookston, Morris, and St. Paul consist of single 4 to 6 ft. rows, with 1 to 3 replications. Fusarium-infected corn seed or spray-applied macroconidia are used as inoculum. The plot areas are misted periodically to maintain a high humidity environment for at least three weeks after anthesis.


Choice of variety is one of the most important deci-sions growers make each year. The development of high-yielding varieties that are resistant to the prevalent diseases and have good end-use quality are necessary to increase grower profit and protect against constantly changing pathogens and pests. As an example, a new variety that yields 4% higher will produce two extra bushels in a field that averages 50 bu/A.


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Related Research

These funds provide general support for our breed-ing/genetics program. Additional monetary support for breeding-related research comes from the Min-nesota Agricultural Experiment Station and the U.S. Wheat and Barley Scab Initiative via USDA-ARS.

Our breeding project is a participant in a new USDA-CSREES project whose objectives are to discover DNA markers linked to pre-harvest sprout-ing resistance and use DNA markers associated with other key genes to increase the efficiency of the breeding project.

Publications

Anderson, J.A., G. Linkert, C. Springer, and J.J. Wiersma. 2006. Hard Red Spring Wheat. In Minne-sota Varietal Trials Results, University of Minnesota Extension Service. Anderson, J.A., G. Linkert, C. Springer, and J.J. Wiersma. 2006. Winter Wheat. In Minnesota Varietal Trials Results, University of Minnesota Extension Service. Anderson, J.A., R.H. Busch, D.V. McVey, J.A. Kol-mer, Y. Jin, G.L. Linkert, J.V. Wiersma, R. Dill-Macky, J.J. Wiersma, G.A. Hareland. 2007. Registration of ‘Ada’ wheat. Crop Sci. 47:434-435. Mergoum, M., P. K.Singh, S. Ali, E.M. Elias, J.A. Anderson, K.D. Glover, and T.B. Adhikari. 2007. Reaction of elite wheat genotypes from the northern Great Plains of North America to Septoria diseases. Plant Dis. 91:1310-1315. Pumphrey, M.O., R. Bernardo, J.A. Anderson. 2007. Validating the Fhb1 QTL for Fusarium head blight resistance in near-isogenic wheat lines devel-oped from breeding populations. Crop Sci. 47:200-206. Tsilo, T.J., Y. Jin, and J.A. Anderson. 2007. Micro-satellite markers linked to stem rust resistance allele Sr9a in wheat. Crop Sci. in press.


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Incorporation of New Resistance Genes for Tan Spot in Adapted Common Wheat

and Durum Varieties P.K.Singh, Department of Plant Sciences, NDSU

Research Question

1) To transfer the newly identified resistance to tan spot into common wheat and durum varieties.2) To determine the relationship between known re-sistance/susceptibility genes for tan spot in common and durum wheat.3) To determine the genetic basis for the differential response of P. tritici-repentis race 5, the commonly occurring race in the Northern Plains, in durum and common wheat.

Results

Study 1. Resistant and susceptible genotypes for tan spot of wheat were identified based on the results of a recently concluded research project entitled “Screening for Leaf Spot Resistance in Hard Red Spring (HRS) Wheat” funded in part by the Minne-sota Wheat Research and Promotion Council. Four adapted HRS cultivars ‘Trooper’, ‘Fryer’, ‘Oklee’, and ‘Knudson’ were found to be good sources of resis-tance to all virulent races of Pyrenophora tritici-re-pentis (cause of tan spot) found in the Northern Great Plains. These sources are also insensitive to the toxins produced by P. tritici-repentis fungus. These resistant sources have been hybridized with other adapted wheat cultivars in order to develop breed-ing populations. F� and F2 generations and advance population of these crosses are being developed and evaluated for agronomic and disease resistance in the wheat breeding programs at NDSU, Fargo in order to develop tan spot resistant cultivars.

Additionally, to broaden the genetic base of resis-tance to tan spot, the resistance from lines; Intros # 7, 2000 Spelt # 20, 92 MREHTR28B, and CIMMYT L # 18, is also being introgressed into the locally adapted germplasm. These un-adapted resistant sources were crossed with locally adapted high yield-ing germplasm and backcross population of these crosses are being developed, advanced, and evalu-ated for agronomic and disease resistance in the wheat breeding programs at NDSU, Fargo in order to develop tan spot resistant cultivars.

For the durum wheat, the resistance from Triticum turgidum # 283 (PI352519), found resistant to all virulent races of P. tritici-repentis occurring in North-ern Great Plains, was hybridized to locally adapted germplasm and both pedigree and backcross selec-tion is being attempted to develop tan spot resistant cultivars.

Study 2. A population of 98 recombinant-inbred lines (RIL) was developed from a cross between the resistant genotype Triticum turgidum # 283 (PI352519) and the susceptible durum cultivar Coulter. This RIL population was screened with races 3 and 5 and molecular mapping of the resistance gene(s) in this population was conducted. Addition-ally, the relationship between the resistance genes effective against races 3 and 5 was determined. The F2 and F4:5 generations of this population were also screened with the two races to determine the genetic control of resistance. Under controlled environmen-tal conditions, plants were inoculated at the two-leaf stage and disease reaction was assessed based on 1 to 5 lesion-type rating scale eight days after inoculation. Segregation analysis of the F2 genera-tion and the F4:5 and F6:7 families indicated that single recessive genes controlled resistance to necrosis induced by races 3 and 5. Analysis of the mapping data of the T. turgidum # 283/Coulter RIL population indicate that major genes, designated tsn2 and tsn5, controlling resistance to races 3 and 5, respectively, are located on the long arm of chromosome 3B. The molecular and phenotypic data confirm that the two resistance genes are closely linked. The resistance locus, tsn2, effective against race 3 is 2.7 cM distal to the SSR locus Xgwm285 while the resistance locus, tsn5, controlling necrosis induced by race 5 is 8.3 cM proximal to the tsn2 locus. The SSR locus Xgwm285 should be of great use for marker assisted selection, to introduce the resistance from T. turgidum # 283 into an adapted durum wheat background. Additional efforts are being made to identify closely linked flank-ing markers to these two tan spot resistance genes.

An advance population of recombinant-inbred lines (RIL) was developed from a cross between the


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resistant HRS wheat line ND-735 and the susceptible HRS cultivar Steele-ND. The F2 plants and RIL popu-lation of Steele-ND/ND735 were tested to determine the genetic control of resistance to P. tritici-repentis races 2 and 5 and their culture filtrates. Additionally attempt was made to determine the relationship between spore inoculation and culture filtrate in this HRS wheat population. The F2 generation and RILs of the population ND 735/Steele-ND segregated for single gene control for resistance/insensitivity when tested with spore inoculum and culture filtrate of P. tritici-repentis race 2. Similarly, single gene control for resistance/insensitivity was observed in the F2 generation and RILs of the population when chal-lenged with spore inoculum and culture filtrate of P. tritici-repentis race 5. All the 138 RILs gave exact reaction to spore inoculum and culture filtrate indicat-ing toxins Ptr ToxA and Ptr ToxB produced by race 2 and 5, respectively, are pathogenicity factors in the development of tan spot in this population. These results further reveal that culture filtrate of races 2 and 5 can be used as a surrogate to spore inocula-tion when screening for tan spot resistance. Prelimi-nary mapping work reveal that the resistance gene for resistance to P. tritici-repentis race 5 is located on the short arm of chromosome 2. Additional markers are being identified which are closely linked to the resistance gene so that marker assisted selection is effective and successful.

Study 3. A total of 20 cross populations were developed and studied for determining the genet-ics of resistance to tan spot of wheat. The genetic studies with race 5 between susceptible genotypes Coulter (tetraploid) and Katepwa (hexaploid) gave novel results. Coulter is susceptible to necrosis while Katepwa is susceptible to chlorosis caused by P. tritici-repentis, race 5. All F� plants of the cross Coulter/Katepwa were susceptible showing only necrotic symptoms. Plants of the F2 generation of this cross segregated for both necrosis and chlo-rosis. Rating plants for both necrosis and chlorosis components separately are error prone and hence disease scoring for resistant and susceptible (necro-sis and/or chlorosis) reaction was performed. The F2 generation of this inter-specific S/S cross segregated in a 3 resistant: 13 susceptible ratio indicating two different genes control susceptibility to race 5 in this cross. The F2:3 families of this cross segregated for 1 homozygous resistant: 15 susceptible (homozygous and heterozygous families) confirming that different genes control susceptibility to necrosis (tetraploid) and chlorosis (hexaploid) caused by P. tritici-repentis

race 5 in this cross. Results from this and previous study (study 2) reveal that two independent resis-tance genes, a single dominant gene for chlorosis in hexaploid wheat located on short arm of chromo-some 2B and a single recessive gene for necrosis in tetraploid wheat located on long arm of chromosome 3B, control resistance to tan spot induced by race 5.

Application/Use

The information on the genetics of resistance for tan spot in common and durum wheat and the resistant germplasm developed will provide vital information/resources to breeders in developing resistant varieties. This ongoing study on completion will determine the different resistance/susceptibility genes present in common and durum wheat and the potential of inter-specific transfer of tan spot resis-tance. The identification of resistant lines/genotypes possessing novel resistance genes and its use in development of resistant spring wheat varieties will provide efficient and economical management of leaf spots thus minimizing losses in grain yield and quality thereby improving the economic efficiency of wheat production. With durable and broad base resistant varieties the use fungicides, a practice not often environmentally safe and cost effective, would not be necessary.


Study 1. The resistant genotypes were selected based on the reaction of genotypes to different races of P. tritici-repentis tested under greenhouse condi-tion (Singh et al. 2006). Hybridization and develop-ment of breeding population is being carried in green-house/field. Backcross populations are developed to introgress resistance from un-adapted resistant sources. Pedigree and backcross selection is being performed in greenhouse and field to develop culti-vars resistant to tan spot.

Study 2. To determine the genetics of resistance to the necrosis induced by P. tritici-repentis, races 3 and 5 in tetraploid wheat, the F2 generation and F4:5 families of the cross TT283/Coulter were developed and screened. The F6:7 recombinant inbred lines (RIL) were also tested with races 3 and 5 to reconfirm the genetic study and provide phenotypic data for mapping analysis. All the F4:5 and F6:7 families were produced by single-seed descent.

To determine the genetics of resistance to the


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necrosis and chlorosis induced by P. tritici-repentis, races 2 and 5, respectively in hexaploid wheat, the F2 generation and RIL of the cross SteeleND/ND735 were developed and screened. The RILs were pro-duced by single-seed descent.

Single-spore cultures of isolates Ptr 86-124 (race 2), Ptr 331-9 (race 3) and Ptr DW13 (race 5) were used to produce the spore inoculum and induce disease. Plants were inoculated at the two-leaf stage under controlled environmental conditions and disease reaction was assessed eight days after inoculation based on a 1 to 5 lesion type rating scale. Disease development and evaluation was done following the procedures reported by Lamari and Bernier (1989a). Culture filtrate was produced by the procedure of Orolaza et al. (1995). Two week old seedlings were infiltrated with culture filtrate of Ptr 86-124 (race 2) and Ptr DW-13 (race 5), containing the toxins Ptr ToxA and Ptr ToxB, respectively. Four days later seedlings were rated as sensitive or insensitive based on presence or absence of necrosis/chlorosis at the site of infiltration. Data collected was analyzed using the chi-square test to determine goodness-of-fit of segregation ratios to determine the genetic control of insensitivity to culture filtrate.

Following the methods described by Del Blanco et al. (2003), DNA extraction was performed on a bulk of at least 12 plants per RIL for the two RIL popula-tions i) Tetraploid T. turgidum # 283/Coulter and ii) Hexaploid ND 735/Steele-ND. i) For the tetraploid T. turgidum # 283/Coulter popu-lation: Microsatellite markers; gwm, barc, and wmc previously mapped to chromosome 3B were used to screen the parental lines for polymorphisms. A total of 49 markers were screened on the parents Coulter and TT283. Of these 49 markers, 15 markers were found to be polymorphic on the parents and hence were run on the entire F6:7 RIL population. Linkage analysis and QTL mapping were performed with MapManager QTX. ii) For the hexaploid ND735/Steele-ND popula-tion: Microsatellite markers; gwm, barc, and wmc previously mapped to chromosome 2B were used to screen the parental lines for polymorphisms. Major-ity of markers screened were monomorphic in the ND735/Steele-ND population; however, 5 polymor-phic SSR markers located on short arm of chromo-some 2B were found linked to the gene controlling resistance to extensive chlorosis induced by race 5 in this population. Additional markers closely linked to the resistance gene are being identified.

Study 3. A total of twenty cross populations includ-ing 13 resistant/susceptible (R/S), five resistant/re-sistant (R/R), and two susceptible/susceptible (S/S), were studied using the 17 selected genotypes. These genotypes included, seven synthetic hexaploid wheat genotypes, Synthetic Hexaploid Elite (SHE) # 9, SHE # 25, SHE # 67, SHE # 85, SHE # 89, Altar Syn-thetic, and Septoria Synthetic # 57; seven hexaploid wheat genotypes, Kenyon, Katepwa, 98W1147, Erik, CIMMYT Line # 18, Intros Line # 7, and 92MREHTR 28B; one hexaploid spelt wheat, 2000 Spelt # 20; one tetraploid accession, T. turgidum # 283 (PI352519); and the durum cultivar Coulter. Each F� plant grown to produce F2 seed was harvested separately. The individual F2 populations of each cross were tested for disease reaction to eliminate non-hybrid popula-tions. The F2 plants were grown in the greenhouse to produce advance generations (F2:3 or F2:5) by single seed descent in each of the crosses studied including the inter-specific crosses Coulter/Katepwa. Disease induction and assessment was done similar to the study 2.


Leaf spots on average cause yield losses from 10-15% and cause loss in grain quality by grain shrivel-ing, dark smudge and black point. Previous genetic studies indicate of a narrow genetic base of resis-tance to tan spot (Anderson et al., 1999; Singh and Hughes, 2005). Development of new resistant durum and common wheat varieties, in conjunction with crop rotation, will provide an effective and environmentally safe means of controlling tan spot. Information and the germplasm developed from this study will aid plant breeders in development of durable resistant varieties. This will minimize the losses due to tan spot and improve the economic efficiency of wheat pro-duction. The genetic studies will identify novel genes for resistance to be utilized in broadening the genetic base of resistance in commercial varieties and thus reduce the possibility of existing resistance genes breaking down. Improved control of tan spot with resistant varieties should minimize losses in grains yield and quality thereby increasing opportunities for local value-added processing.

Related Research

Previous studies have involved screening for new sources of resistance to tan spot of wheat in greenhouse or field evaluations (Lamari and Bernier


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1989a, Singh et al. 2006a, Riede et al. 1996), inheri-tance of resistance (Anderson et al. 1999, Gamba and Lamari 1998, Gamba et al. 1998, Singh et al. 2006b) and race structure of the pathogens (Ali and Francl 2003, Lamari and Bernier 1989b, Singh et al. 2006b). Significant efforts have been made in iden-tifying molecular markers for the resistance genes (Faris et al. 1997, Friesen and Faris 2004, Singh et al. 2006) and in molecular biology of host-pathogen interaction (Ciuffetti and Tuori 1999; Strelkov and Lamari 2003).

To date, only three and four genes in common wheat and durum, respectively, confer resistance to one or more of the five races of P. tritici-repentis in North America (Gamba and Lamari, 1998; Gamba et al., 1998). A preliminary study by Anderson et al. (1999) revealed that both durum and common wheat possess the same gene for necrosis induced by races 1 and 2. The relationship between the other re-sistance genes is unknown. Recent studies in Europe have identified novel resistance genes for tan spot of wheat.

In a recently concluded research funded by Minne-sota Wheat Research and Promotion Council entitled ‘Screening for Leaf Spots Resistance in Hard Red Spring Wheat’ the reaction of the advanced durum and common wheat breeding lines to P. tritici-repen-tis was evaluated. A very high number of genotypes tested were susceptible to P. tritici-repentis. It was also observed that the elite wheat germplasm is most susceptible to P. tritici-repentis race 2 followed by race 5 and race 3. Although, majority of the 126 genotypes tested were susceptible, genotypes were resistant to all races of P. tritici-repentis were identi-fied.

References

Ali, S., and L.J. Francl 2003. Population race structure of Pyrenophora tritici-repentis prevalent on wheat and non-cereal grasses. Plant Dis. 87:418-422. Anderson, J.A., R.J. Effertz, J.D. Faris, L.J. Francl, S.W. Meinhardt, and B.S. Gill. 1999. Genetic analysis of sensitivity to a Pyrenophora tritici-repentis necrosis inducing toxin in durum and common wheat. Phyto-pathology 89:293-297. Ciuffetti, L.M., and R.P. Tuori. 1999. Advances in the characterization of the Pyrenophora tritici-repentis-wheat interaction. Phytopathology 89: 444-449. De Wolf, E.D., R.J. Effertz, S. Ali, and L.J. Francl.

1998. Vistas of tan spot research. Can. J. Plant Pathol. 20:349-370. Del Blanco, I.A., R.C. Frohberg, R.W. Stack, W.A. Berzonsky, and S.F. Kianian. 2003. Detection of QTL linked to Fusarium head blight resistance in Sumai 3-derieved North Dakota bread wheat lines. Theor. Appl. Genet. 106:1027-1031 Faris, J.D., J.A. Anderson, L.J. Francl, and J.G. Jor-dahl. 1997. RFLP mapping of resistance to chlorosis induction by Pyrenophora tritici-repentis. Theor. Appl. Genet. 94:98-103 Friesen, T.L., and J.D. Faris. 2004. Molecular map-ping of resistance to Pyrenophora tritici-repentis race 5 and sensitivity to Ptr ToxB in wheat. Theor. Appl. Genet. 109:464-471. Gamba, F.M. and L. Lamari, 1998. Mendelian inheri-tance of resistance to tan spot in selected genotypes of durum wheat. Can. J Plant Pathol. 20:408-414. Gamba, F.M., L. Lamari, and A. Brule-Babel. 1998. Inheritance of race-specific necrotic and chlorotic reactions induced by Pyrenophora tritici-repentis in hexaploid wheats. Can. J. Plant Pathol. 20:401-407. Lamari, L., and C.C. Bernier. 1989a. Evaluation of wheat lines and cultivars to tan spot (Pyrenophora tritici-repentis) based on lesion type. Can. J. Plant Pathol. 11:49-56. Lamari, L., and C.C. Bernier. 1989b. Virulence of isolates of Pyrenophora tritici-repentis on �� wheat cultivars cytology of differential host reactions. Can. J. Plant Pathol. 11:284-290. Orolaza, N.P., L. Lamari, and G.M. Ballance. 1995. Evidence of a host-specific chlorosis toxin from Pyre-nophora tritici-repentis, the causal agent of tan spot of wheat. Phytopathology 85:1282-1287. Riede, C.R., L.J. Francl, J.G. Jordahl, and S.W. Meinhardt. 1996. Additional sources of resistance to tan spot of wheat. Crop Sci. 36: 771-777. Singh, P.K., and G.R. Hughes. 2005. Genetic con-trol of resistance to tan necrosis induced by Pyre-nophora tritici-repentis, races 1 and 2, in spring and winter wheat genotypes. Phytopathology 95:172-177. Singh, P.K., M. Mergoum, S. Ali, T.B. Adhikari, E.M. Elias, J.A. Anderson, K.D. Glover, and W.A. Berzon-sky. 2006a. Evaluation of elite wheat germplasm for resistance to tan spot. Plant Dis. 90: 1320-1325. Singh, P.K., J.L. Gonzalez-Hernandez, M. Mer-goum, S. Ali, T.B. Adhikari, S.F. Kianian, E.M. Elias, and G.R. Hughes. 2006b. Identification and molecu-lar mapping of a gene in tetraploid wheat conferring resistance to Pyrenophora tritici-repentis race 3. Phytopathology 96: 885-889. Strelkov, S.E., and L. Lamari. 2003. Host-parasite interactions in tan spot [Pyrenophora tritici-repentis] of wheat. Can. J. Plant Pathol. 25:339-349.


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1. Additional molecular work is required to identify flanking molecular markers closely linked to the resistance genes identified for tan spot resistance in tetraploid and hexaploid wheat.2. Development and evaluation of advanced re-sistant material as a part of varietal development program.3. Evaluation of the advanced resistant material against other foliar diseases and FHB.

Publications

Singh, P.K., J.L. Gonzalez-Hernandez , M. Mer-goum, S. Ali, T.B. Adhikari, S.F. Kianian, E.M. Elias, and G.R. Hughes. 2006. Identification and molecular mapping of a gene in tetraploid wheat conferring resistance to Pyrenophora tritici-repentis race 3. Phytopathology 96: 885-889. Singh, P.K., M. Mergoum, J.L. Gonzalez-Hernan-dez, S. Ali, T.B. Adhikari, S.F. Kianian, E.M. Elias, and G.R. Hughes. 2007. Genetics and molecular mapping of resistance to necrosis inducing race 5 of Pyrenophora tritici-repentis in tetraploid wheat. Molecular Breeding (Online: DOI 10.1007/s11032-007-9129-3). Singh, P.K., M. Mergoum, S. Ali, T.B. Adhikari, and G.R. Hughes. 2007. Genetic analysis of wheat-Pyre-nophora tritici-repentis interactions. Phytopathology (Acceptable subject to revisions). Singh, P.K., and M. Mergoum. 2006. Genetic analysis of resistance to fungal inoculation and toxin infiltration of Pyrenophora tritici-repentis, race 5 in a hexaploid wheat population. Poster Presentation. ASA-CSSA-SSSA International Annual Meeting. November 12-16. Indianapolis, USA. Singh, P.K., J.L. Gonzalez-Hernandez, M. Mer-goum, S. Ali, T.B. Adhikari, S.F. Kianian, E.M. Elias, and G.R. Hughes. 2006. Genetic analysis of resis-tance to necrosis inducing Pyrenophora tritici-repen-tis races 3 and 5 in tetraploid wheat. Oral Presenta-tion. Joint Annual Meeting of APS/CPS. 29th July to 2nd August. Quebec City, Canada. Can. J. Plant Pathol. 2006, 28: 364-365 (Abs).


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Research Question Objectives:

1) Determine if light reflectance from the wheat canopy at one or more vegetative growth stages can be used to predict grain yield and grain protein.2) Identify the growth stage of hard spring wheat for obtaining maximum accuracy for prediction of grain yield and grain protein.

Results

General Information Fertilizer application and the wheat planting oc-curred in a timely manner at both locations. Wheat was planted April 26 at NWROC and May 3 at WCROC. Weather conditions were quite different between the two experimental sites. At WCROC, over an inch of precipitation fell within two days after planting. However, only about 3-inches of rain fell the entire growing season at WCROC. At NWROC, growing conditions were more favorable with about 10-inches of precipitation during the growing season. At both locations wheat emergence, stand, and plant vigor were good. Other than the dry conditions at WCROC no other yield limiting factors can be identified.

Grain Yield and Protein The effects of N rates and Varieties on spring wheat grain yield and protein were highly significant at both locations (Table 1). At NWROC there were significant interactions of N rate by Variety on grain yield. This indicates that varieties responded differently to the increasing N rates. Knudsen grain yields increased nearly 25 bu A-� over the range of N rates compared to about 10 bu A-� for Alsen (Fig 1). Nitrogen Source and a N rate by N Source interaction on grain yield were also significant. Within varieties, maximum yield occurred at approximately the same N rate re-gardless of N Source, but yields were always greater when ESN was applied compared to urea (Fig 1). At WCROC, there was no grain yield difference between

Development of Tools to More Accurately Predict In-Season Spring Wheat

Nitrogen Needs for Yield and ProteinAlbert L. Sims, University of Minnesota - NWROC

N Source and both varieties increased yield over the entire range of N rates (Fig 2). Nitrogen source had no effect on grain protein at either location, but protein tended to increase over the entire range of N rates (Fig 3). At both locations, Knudsen had greater grain yields and lower grain protein that Alsen, as expected. Grain yields were greater at NWROC compared to that at WCROC, but protein was greater at WCROC.

Greenseeker Readings Greenseeker (GS) readings were easier to do NWROC than WCROC due to distance. The NDVI calculated by the Greenseeker is related to green biomass which is related to the health, vigor, and growth development of the crop which is related to many factors not the least of which is nitrogen. Figure 4 shows NDVI relationships to urea-N rates for both varieties in the NWROC trial averaged over replications. Each line represents a different reading. NDVI of both varieties increased when N was applied suggesting increased green biomass with N, which is consistent with visual observations. As the wheat crop developed, NDVI increased (solid lines in Fig 4) until a maximum NDVI was reached on the June 12th reading. This corresponds to the flag leaf growth stage or Zadocks 37-39. The NDVI held relatively constant over the next week or two then began to decline (dashed lines in Fig 4). The June 15th GS reading at WCROC corresponded to a similar wheat growth stage as that on June 12th at NWROC. I rea-soned that if the GS and its calculated NDVI could be used to predict hard red spring wheat grain or protein yield, it should be able to do it by the flag leaf when NDVI maximum occurred.

Predictor Indices Three different Predictor Indices were calculated using the NDVI and compared to grain yield and protein. The three Prediction Indices are described in the Materials and Methods.

Index #1 Several index values using NDVI from various


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combinations of paired GS readings and the GDD ac-cumulating between those readings were calculated and compared to wheat grain yield or grain protein. These comparisons yielded scattered or vertical data alignment where many different yield or protein measurements occurred at the same or similar index values. There was no discernable pattern between the various calculated index values and grain yield or grain protein. Figure 5 illustrates various calculated index values and grain yield relationships.

Index #2 Comparisons of Index #2 to grain yield or protein revealed some patterns that may be useful. The data in Figure 6 used the index calculated from the June 12 and June 15 GS readings at NWROC and WCROC, respectively. Of the index values calcu-lated from various GSr readings, those from the June 12 and June 15 readings appeared to be the most promising for the reason stated above. At NWROC, an exponential function and a quadratic function best described the relationship between the index value and the grain yield or grain protein, respectively (Fig 6). However, it was clear that the function equations were quite different between the two varieties. At WCROC, similar functions were applied to the data (Fig 6). Though the WCROC data was more variable than at NWROC, probably partially caused by the extremely dry weather conditions, it is still obvious the function equations are different between the two varieties.

Index #3 As with Index #2, Index #3 values calculated from GS readings on June 12 and June 15 at NWROC and WCROC, respectively, had the strongest rela-tionship to grain yield or grain protein. The primary difference between Index #3 and Index #2 is the denominator. Index #2 uses GDD, which will some-what reflect climatic conditions from planting to the when the GS reading occurred. Index #3 uses DAP and will not directly reflect climatic conditions except those that might be normal for this time of year. Nev-ertheless, the relationships between the index value and grain yield or grain protein in Fig 7 are quite similar to those in Fig 6 (Index #2). Like Index #2, there are two distinctly different function equations for the two varieties in Index #3.

Application/Use

Previous research has clearly shown that sufficient preplant N application of N fertilizer is the most reli-

able management strategy for spring wheat produc-tion in Minnesota. However, N application is based on yield goal. If the N is applied to achieve a specif-ic and realistic yield goal, but yield potential exceeds that goal, is additional N necessary to maintain an acceptable grain protein level. My overall objective was to determine if the Greenseeker could be used to predict grain yield or perhaps grain protein at a time when growers could make the decision as to whether additional N fertilizer should be applied to improve the grain protein content. The data suggest the best potential for using the Greenseeker is at or around flag leaf to boot, which corresponds closely to when growers apply fungicide to control Fusarium Head Blight. The Greenseeker could be mounted on the sprayer unit and readings taken during the spraying operation.

I could find no potential predictive capability of Index #1 from this data due to little discernable relationships between the calculated index values and grain yield or grain protein. Indices #2 and #3 were quite similar in their discernable relationships between the calculated index values and grain yield or grain protein. However, neither of these indices was capable of distinguishing the grain yield or grain protein difference between the two varieties; each variety seemed to have its own best fit func-tion equation. Within varieties, there was a general increase in grain yield or grain protein as the index value increased. However, neither of these indices was capable of distinguishing the yield differences that occurred between the two N sources (Fig 1, Fig 6 and 7: open versed closed symbols for each variety) which were as much as 7 to 10 bu A-� at NWROC.

Growers and researchers are always striving to im-prove N fertilizer use efficiency to increase the ‘bang for the buck’ and to decrease the threat of excess N to the environment. At this time, I do not see the Greenseeker as a tool to increase N use efficiency in hard red spring wheat production systems in Northwest Minnesota or Eastern North Dakota. Perhaps a larger data set than I currently have avail-able would improve its chances. Taking GS readings is fairly easy and cheap so data can continue to be collected on other spring wheat experiments. But, I do not think further intensive and specific investiga-tions in this monitoring tool are warranted.


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Field experiments were established at two locations in western Minnesota, the University of Minnesota’s Northwest Research and Outreach Center near Crookston (NWROC) and West Central Research and Outreach Center near Morris (WCROC). Soy-bean was the previous crop at both locations.

The experiment design used in these experiments was randomized complete block with a 2 by 2 by 5 factorial treatment design and four replications. One factor included two hard red spring wheat varieties, Alsen and Knudsen. Alsen was selected for its high protein potential and Knudsen was selected for its high yield potential. The second factor was two nitrogen (N) sources. A product by Agrium Inc. called ESN, a slow release N source, was compared to urea. The final factor was six N rates in 20 lbs N A-� increments from 0 to 100 lbs N A-�.

A Greenseeker (GS) instrument was used to measure red and near infrared light reflectance from the wheat canopy. Each reading measures the reflectance of red and NIR light reflected from the crop canopy and compares this to that emitted from a source mounted in the GS instrument head and calculates a ratio of red and NIR reflected to red and NIR emitted. This ratio is referred to as the Normalized Difference Vegetative Index (NDVI) and is directly related to the green biomass of the crop. The hand held GS measures reflectance in an oblong oval shape and was adjusted so that the long axis of the oval was perpendicular to the direction of the wheat rows. Reflectance was measured by holding the instrument about 2 ft above the canopy of the center rows of the plot and walking at a steady gate over the entire length of the plot (about 25 ft). The GS typically takes 50 to 60 readings per plot depend-ing on walking speed. For this report I used average NDVI of the 50 to 60 readings per plot. Greenseeker readings were taken twice weekly, when possible, at NWROC starting at the tillering growing stage and continuing into early soft dough. Only four GS readings were taken at WCROC during these same growth periods.

Three separate Prediction Indices were calculated using the NDVI values calculated by the Greenseek-er at each GS reading. They are:

Index #1: [(T1+T2) NDVI/(T2-T1)GDD] where the NDVI calcu-

lated from two different GS readings were summed and divided GDD accumulated between those GS readings.

Index #2: [(T1)NDVI/GDD] where the NDVI calculated for at a single GS reading is divided by the GDD accumu-lated from planting to the time of the GS reading.

Index #3: [(T1)NDVI/DAP] where the NDVI calculated at a single GS reading is divided by DAP when the read-ing occurred.

Growing Degree Days (GDD) were calculated ac-cording to Wiersma and Ransom (2005). Maximum and minimum temperatures were obtained from weather recorders on the respective research and outreach centers. The NDVI Index was then related to final grain yields and protein produced in the plots.

Days After Planting (DAP) is the calendar days that have passed since the wheat crop was planted to the time the GS reading was taken.

The index values calculated using the three indices described above were compared to measured grain yield and grain protein from the individual plots. Vari-ous regression functions were applied to the index value and grain yield or grain protein relationship data starting with the exponential function, which was used by Raun et al. (2001). Additional regression functions were applied to the data in an attempt to improve the correlation coefficient (R2). The regres-sion function with the highest correlation coefficient is shown in each graph in Figures 5 through 7. Attempts were made to maintain the same regres-sion function for similar data comparisons at both locations. If, however, the correlations coefficient could be improved by more than 10% with a different function, then different functions were adapted to the data without regard to location.

Wheat was harvested with a small plot combine to determine wheat yield and an NRI instrument was used to determine grain protein.


None at this time


Page 23

Related Research

The wheat crop relies on fertilizer N and non-fertil-izer N sources such as residual soil N, climatic N deposition, and N mineralized from the soil organic matter. The magnitude of the wheat response to ap-plied fertilizer N greatly depends on the availability of non-fertilizer N sources. Residual soil N is measured with soil testing prior to planting, but climatic N de-position and N mineralization vary considerably from year to year and are difficult to predict. At any given point in time during the growing season the growth of the wheat crop is the result of integration of all the environmental factors the crop has been exposed to, including N availability. If the early season growth patterns can be used to estimate season ending grain yield and quality potential, then management decisions can be made as to how much N needs to be available to support that potential. The grower will know how much fertilizer N was applied prior to planting and how much residual soil N is available. Combining estimates of yield and quality potential and known N availability, the grower can now de-termine if additional fertilizer N should be applied to support that potential. Remote sensing of early season wheat canopy can be a tool that can be used to estimate grain yield and quality potential.

Remote sensing of wheat canopies can be done through many methodologies, but the reflectance of light from the canopy is the underlying principle in all of them. Technologies are available to measure in-coming red and near infrared light and compare that to the red and near infrared light reflected from the crop canopy. Through a series of algorithms, these measurements are used to develop a Normalized Dif-ference Vegetative Index (NDVI). The NDVI provides a relative quantity of biomass reflecting the light.

Plant biomass is a product of many factors affecting growing conditions of the plant. Nitrogen availability is one of those factors. Reeves et al. (1993) used direct in-season total N uptake (dry biomass X N con-centration) at Feekes growth stage 5 to predict winter wheat grain yields. Aase and Siddoway (1981) found a relationship between in-season NDVI and the final winter wheat grain yields. Smith et al (1995) re-ported that two in-season canopy reflectance read-ings combined through linear modeling improved the NDVI – Wheat grain yield relationship compared to only one NDVI reading. Raun et al (2001) measured NDVI at two growth stages of winter wheat soon after winter dormancy broke. They found that the aver-

age of the two NDVI readings divided by the growing degree days (GDD) accumulated between the two reading dates provided an estimated yield prediction that was highly correlated to the actual grain yield harvested.

References

Aase, J.K. and F.H. Siddoway. 1981. Assessing winter wheat dry matter production via spectral reflec-tance measurements useful in providing an estimate of residual production for erosion control and as a potential source for feed and energy. Remote Sens. Environ. 11:267-277. Raun, W.R., J. B. Solie, G.V. Johnson, M.L. Stone, E.V. Lukina, W.E. Thomason, and J.S. Schepers. 2001. In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron. J. 93:131-138. Reeves, D.W., P.L. Mask, C.W. Wood, and D.P. Delaney. 1993. Determination of wheat nitrogen status with hand-held chlorophyll meter: Influence of management practices. J. Plant. Nutr. 16:781-796. Smith, R.C.G., J. Adams, D.J. Stephens, and P.T. Hick. 1995. Forecasting wheat yields in Mediterra-nean-type environment from NOAA Satellite. Aust. J. Agric. Res. 46:113-125. Wiersma, J.. and J. Ransom. 2005. The Small Grains Field Guide. NDSU Extension Publication A290 or University of Minnesota Extension Service Publication 07488-S. North Dakota State University and University of Minnesota Extension Service.


The quest to improve N fertilizer use efficiency is an absolute necessity from both an economical and en-vironmental standpoint. Substantial increases in the cost of N fertilizer in recent years, and the likelihood it will continue to increase, makes this vitally important from a producer standpoint. How can the producer recover as much of his/her N fertilizer investment as possible? While substantial research has been done in the past, there are still many questions. Research to improve N fertilizer use efficiency should continue down various avenues. I do not recommend further specific investment in Greenseeker research to achieve this goal except perhaps as a rider on other experiments with their own specific objectives. I think there are other more promising avenues that should be researched. Polycoated urea may be one such avenue.


Page 24

NWROC Grain WCROC GrainSource of Variation Yield Protein Yield Protein

------ level of significance § ----N rate *** *** *** *** Linear (Lin) *** *** *** *** Quadratic (Quad) *** ns ns nsN Source *** ns ns nsVariety *** *** ** ***N rate by N Source ** ns ns ns Lin by Source *** ns ns ns Quad by Source ns ns ns nsN rate by Variety *** ns ns ns Lin by Variety *** ns ns ns Quad by Variety ns ns ns nsN Source by Variety ns ns ns ns

§ ***, **, *, and ns represent significant levels of PR>F of 0.001, 0.001, 0.05, and non-significant, respectively.

N rate (lbs. N A-�)

0 20 40 60 80 10055

60

65

70

75

80

85

90

95

100

N rate (lbs N A-�)

0 20 40 60 80 100

Grain yield (bu A

-�)

55

60

65

70

75

80

85

90

95

100

ESNUreaESN Urea

a. NWROC - Alsen b. NWROC - Knudsen

Y=59 + 0.469x - 0.003x2 R2=0.906

Y=60 + 0.293x - 0.002x2 R2=0.861

Y=67 + 0.497x - 0.002x2 R2=0.996

Y=67 + 0.475x - 0.003x2 R2=0.993

Figure 1. 2007 Grain yield response of two spring wheat varieties to N supplied by two N sources at NWROC.

Appendix

Table 1. Statistical analysis of spring wheat grain yield and protein response to N rates, N source, and variety at two locations in 2007.

Gra

in y

ield

(bu

A-�)


Page 25


0 20 40 60 80 10040

45

50

55

60

65

70

75

80

N rate (lbs N A-�)

0 20 40 60 80 100

Grain yield (bu A

-�)

40

45

50

55

60

65

70

75

80

ESNUreaESNUrea

a. WCROC - Alsen b. WCROC - Knudsen


0 20 40 60 80 100

Grain P

rotein (%) 11.0

11.5

12.0

12.5

13.0

13.5

14.0

14.5

15.0

15.5

16.0

Alsen - ESNAlsen - UreaKnudsen - ESNKnudsen - UreaAlsen avg over N sourceKnudsen avg over N source

N rates (lbs N A-�)

0 20 40 60 80 100

Grain protein (%

) 11.0

11.5

12.0

12.5

13.0

13.5

14.0

14.5

15.0

15.5

16.0

Figure 2. 2007 Spring wheat grain yield response of two spring wheat varieties to N supplied by two N sources at WCROC. A linear N rate response was highly significant with no significant difference between N sources. Linear regression was applied to individual treatment means with R2 values of 0.594 and 0.760 when N source was ESN and 0.762 and 0.990 when N source was urea for Alsen and Knudsen wheat varieties, respectively.

Figure 3. Spring wheat grain protein response to N rates, N sources, and varieties at two locations, NWROC (left) and WCROC (right) in the 2007 growing season.

Gra

in y

ield

(bu

A-�)

Gra

in P

rote

in (

%)


Page 26

Alsen

0.4

0.5

0.6

0.7

0.8

0.9

�

0 20 40 60 80 100

N rates (lbs N/A)

ND

VI

25-May�-Jun7-Jun12-Jun19-Jun26-Jun2-Jul��-Jul

Knudsen

0.4

0.5

0.6

0.7

0.8

0.9

�

0 20 40 60 80 100

N rates (lbs N/A)

ND

VI

25-May�-Jun7-Jun12-Jun19-Jun26-Jun2-Jul��-Jul

Figure 4. NDVI response to increasing rates of urea-N on two hard red spring wheat varieties on selected reading dates in the 2007 growing season at NWROC.

40.0

50.0

60.0

70.0

80.0

90.0

100.0

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045

(T1 + T2) NDVI/(T2-T1)GDD Index

Gra

in Y

ield

5/18 - 6/75/25 - 6/75/18 - 6/125/25 - 6/12

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004

(T1+T2)NDVI/(T2-T1)GDD

Gra

in Y

ield

5/31 - 6/155/31 - 6/286/15 - 6/28

Figure 5. Graphical representation of spring wheat grain yield compared to a Predictive Index #1 [ (T1+T2)NDVI/(T2-T1)GDD] in the 2007 growing season at NWROC (left) and WCROC (right). (T1+T2)NDVI is the sum of Greenseeker calculated NDVI from two GS readings taken at two points in time during the growing season. (T2-T1)GDD is the GDD accumulation the interval between the two GS readings.

y = 9.6439e3112.6x

R2 = 0.4935

y = 18.853e2324.9x

R2 = 0.7336

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

0.00045 0.0005 0.00055 0.0006 0.00065 0.0007

T1 NDVI/GDD Index

Gra

in Y

ield

(bu/

A)

Alsen-urea Alsen-ESN Knudsen-ureaKnudsen-ESN Expon. (Alsen-all) Expon. (Knudsen-all)

y = 12.691e2351.6x

R2 = 0.3812

y = 8.8296e3102.3x

R2 = 0.4792

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

0.00045 0.00055 0.00065 0.00075

T1 NDVI/GDD

Gra

in y

ield

(bu/

A)


Figure 6. Continued on next page


Page 27

y = 2E+08x2 - 178940x + 60.595R2 = 0.4394

y = 1E+08x2 - 111797x + 41.792R2 = 0.5956

10.0

11.0

12.0

13.0

14.0

15.0

16.0

0.00045 0.0005 0.00055 0.0006 0.00065 0.0007

T1 NDVI/GDD Index

Gra

in P

rote

in (%

)

Alsen-urea Alsen-ESN Knudsen-ureaKnudsen-ESN Poly. (Alsen-all) Poly. (Knudsen-all)

y = -4E+07x2 + 54134x - 5.402R2 = 0.2886

y = 3E+06x2 + 409.54x + 12.538R2 = 0.1175

12.0

12.5

13.0

13.5

14.0

14.5

15.0

15.5

16.0

0.00045 0.00055 0.00065 0.00075

T1 NDVI/GDD

Gra

in P

rote

in (%

)


Figure 6. Graphical representation of spring wheat grain yield (top) and protein (Bottom) compared to a Predictive Index #2 [ (T1)NDVI/GDD] in the 2007 growing season at NWROC (left) and WCROC (right). (T1)NDVI is the Greenseeker calculated NDVI on the June 12 (NWROC) and June 15 (WCROC) GS readings. GDD is the Growing Degree Days accumulated during the growing season to the date of the GS reading.

y = 9.6439e107.29x

R2 = 0.4935

y = 19.055e79.556x

R2 = 0.723

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

0.013 0.014 0.015 0.016 0.017 0.018 0.019 0.02

T1 NDVI/DAP Index

Gra

in Y

ield

(bu/

A)


y = 12.691e77.664x

R2 = 0.3812

y = 8.8296e102.46x

R2 = 0.4792

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

0.014 0.015 0.016 0.017 0.018 0.019 0.02 0.021 0.022 0.023

T1 NDVI/DAP Index

Gra

in Y

ield

(bu/

A)


y = 195172x2 - 6168x + 60.595R2 = 0.4394

y = 122313x2 - 3842x + 41.75R2 = 0.5812

10.0

11.0

12.0

13.0

14.0

15.0

16.0

0.013 0.014 0.015 0.016 0.017 0.018 0.019 0.02

T1 NDVI/DAP Index

Gra

in Y

ield

(bu/

A)


y = -38479x2 + 1787.8x - 5.402R2 = 0.2886

y = 3201x2 + 13.526x + 12.538R2 = 0.1175

12.0

12.5

13.0

13.5

14.0

14.5

15.0

15.5

16.0

0.014 0.015 0.016 0.017 0.018 0.019 0.02 0.021 0.022 0.023

T1 NDVI/DAP Index

Gra

in P

rote

in (%

)


Figure 7. Graphical representation of spring wheat grain yield (top) and protein (Bottom) compared to a Pre-dictive Index #3 [ (T1)NDVI/DAP] in the 2007 growing season at NWROC (left) and WCROC (right). (T1)NDVI is the Greenseeker calculated NDVI reading one the June 12 (NWROC) and June 15 (WCROC) GS readings. DAP is the Days After Planting the GS reading occurred.


Page 28

Identifying High Hard Red Spring Wheat Cultivars with High Yield Potential to

Meet Special End-usesMohamed Mergoum, Department of Plant Sciences, NDSU

Research Question

1) To evaluate and identify elite HRSW lines with high yield potential.2) To initiate breeding efforts to select high yielding cultivars by screening HRSW germplasm based on yield potential at early breeding stages.

Introduction

In the HRSW breeding programs, we tend to select in general, for yield, but a high level of quality param-eters has to be maintained. Therefore, in the selec-tion process many genotypes with high yield potential can be discarded based on their poor quality. This is one reason yield increases in the region over the past decades have been modest, even though rain-fall has generally been favorable toward increasing production.

In 2006, an initiative was launched by the HRSW breeding programs in the spring wheat region (MN, SD, and ND) with the support of the Minnesota Wheat Research and Promotion Council (MNRPC) to identify high yielding HRSW elite lines among existing wheat germplasm. Preliminary results were promising. Wheat lines which yielded significantly higher than commonly grown cultivars could be identified among the NDSU, SDSU, and the U of MN wheat germplasm. This initiative was seen to be an excellent way to bring the breeding programs of the spring wheat region to collaborate together to focus on breeding for high yield wheat cultivars. Therefore, the MNRPC has taken the leadership to support this initiative and a grant of $11,700/year was awarded to our breeding program as the first step to start evalu-ating our elite HRSW germplasm for high yield and initiate some breeding activities toward achieving this purpose.

Results

Part 1: Field evaluation and identification of elite HRSW lines with high yield potential The 2007 data are still being processed for the

three locations conducted in ND. At the moment, only some agronomic data such as grain yield, test weight and heading date are available. The preliminary data shows that grain yield was in general high given the relatively good conditions that prevailed across the state and the region. At Carrington, where irrigation was available to supplement the normal rainfall, the grain yield was very variable and ranged between 72.2 bu/ac regis-tered for the NDSU elite line ND05-13-119 and 52.8 bu/ac scored by the NDSU line ND05-13-28 while the average of the trial was 62.3 bu/ac. This shows that among the NDSU HRSW germplasm, there is a tremendous genetic variability that we can exploit to increase yield in the future. Among the released culti-vars, Faller, the most recently released NDSU HRSW (2007), was the highest yielding cultivar with 70.7 bu/ac. Among the high yielding cultivars/genotypes, we have the NDSU durum Mountrail, the NDSU HRSW line ND05-14-323, the SDSU experimental line SD3868, and the MN lines MN05209 and MN03098. At Prosper, the yield average was relatively low due to the late dry conditions that prevailed in many parts of ND. The average yield score varied between 54.4 bu/ac registered by the AgriPro cultivar Knud-son and 28.7 bu/ac scored by Hoffman, a variety from Canada. The average yield trial was 43.2 bu/ac. Similar high yield to Knudson was achieved by the NDSU HRSW line ND06-14-279 (52.5 bu/ac), Faller (50.8 bu/ac), and ND05-13-119 (50.2 bu/ac). At the Grand Forks trial, yields were in general very high ranging from 54.5 to 84.1 bu/ac scored on the NDSU durum cultivar Grenora and once more the elite line ND05-13-119, respectively. Other genotypes that showed high yielding performance included Agripro line 01S0202-2S, SDSU line SD 3623, and Tritical 118 with yield levels of 83.1, 82, and 81.6 bu/ac, respectively. Faller was among the top high yield-ing group as well with an average yield of 79.1 bu/ac.

Overall three locations, the NDSU elite line ND05-13-119 was the highest yielding genotypes followed by NDSU HRSW cultivar Faller and SD3623 with an average grain yield of 69, 66.8, 65.6 bu/ac, respec-tively. Therefore, the NDSU elite line ND05-13-119 seems to have a great potential as high yielding


Page 29

cultivar. Further field test for yield as well as quality performances are however, needed to confirm the superiority of this line. The results regarding Faller were not surprising. Indeed, Faller was reported to be consistently high yielding across all MN and most of the ND regions in 2007 crop season (J. Wiersma/J. Anderson and M. Mergoum; data not published). In previous years, Faller was the highest yielding lines that meet the quality standard of our program. This certainly is a very promising result, as Faller is a released cultivar that meets not only its promises in yield performance, but also it has met all the quality requirements needed by the industry and end-users in general.

Part 2. Initiation of breeding efforts to select high yielding cultivars The second part of this project is to initiate crosses involving high yielding genotypes in order to incor-porate or pyramid genes for high yield. Grain yield is one of the –if not the – most genetically complex traits that breeders have to face. In addition to its ge-netic complexity, it is very much influenced by other genetic traits such as biotic and abiotic stresses, environmental factors including the climatic condi-tions, soil type, and most importantly, the interactions between grain yield and these factors.

In the spring of 2007, many crosses involving the highest yielding cultivars such as Faller, Knudson, Traverse and many of our NDSU elite lines and lines from SDSU and MN were initiated. The F� generated from these crosses are being grown in the green-houses this Fall 2007. The F2 populations, F� and F� families will be grown in the spring, summer, and Arizona winter nursery, respectively. Selection in the segregation generations will be based on the pheno-typic appearances of the plant such as vigor, height, lodging, and diseases reactions. By using winter nurseries, we hope to start doing early generation testing for yield in the summer of 2010.

Application/Use

The information on the performances of the elite wheat and triticale cultivars and germplasm in our region is crucial for the future breeding activities on grain yield. The genetic variability for grain yield in our elite adapted wheat germplasm will provide vital information/resources to the breeders in the spring wheat region to develop high yielding wheat cultivars adapted to ND and MN, in particular. This ongoing study will determine the potential wheat cultivars

possessing high yields or potential adapted parent that will be used in the development of high yielding spring wheat varieties. Consequently, this will provide improvements in the economy of the wheat growers and industry.


Three field experiments were conducted in 2007 at sites in ND. These sites include the Carrington Research Center where irrigation is available, Pros-per, and Langdon, two ND eastern locations where high rainfall usually prevails. In total, 40 genotypes (HRSW, Durum, and triticale) developed by the NDSU, SDSU, the U of MN, other breeding programs in the region, and Canada were included in these trials. These trials were also conducted by other col-leagues in many other locations in MN and SD. The experiment was laid out in a randomized complete bloc design (RCBD) with four replicates. The plot size was 6 rows 30 cm apart and 5 m long, similar to the NDSU HRSW elite and advanced yield trials. In order to allow these genotypes to express their yield potential, prior to seeding, fertilizer were applied at a non-limiting rate (based on soil tests). An additional amount of N were applied during tillering based on crop requirements to achieve maximum yields. At Carrington, the experiments were irrigated to meet the water needs of the crop to achieve high yields. A full weed, disease and insect control program are employed so that no known manageable factor will constrain yield. Yield, yield components, and other agronomic and quality traits will be measured.


The development of highly productive cultivars with resistance to the main pests in the region, in con-junction with adequate fertilization and crop rotation, will provide an effective and environmentally sound way to increase the farmers’ income and benefits the wheat industry and end-users in general. With recent favorable prices for wheat worldwide, if maintained, the grain yield will certainly become the driving force in the breeding programs. By focusing on grain yield, the MNRPC has shown that its vision to the future of wheat industry was on the right path as the compe-tition for the grain product between the traditional end-users and the ‘new’ end users such as ‘Bio-fuel’ sector is just in the beginning. Therefore, developing high yielding cultivars in wheat will be paramount for our spring wheat growers.


Page 30

Related Research

The yield data currently available reflects the overall performance of these cultivars, including the qual-ity and environmental effects. In our recent studies in ND, data shows, that genetic progress has been made in many agronomic traits, including grain yield in NDSU HRSW germplasm since 1986 (Underdahl et al., 2007). Most importantly, the progress in grain yield was made while maintaining high quality stan-dards and increasing resistance into newly released NDSU HRSW cultivars. Elsewhere, yield potential research on varieties developed in Mexico for an irri-gated environment found that breeders had achieved gains in yield potential of about 1.1% per year during the period 1950 to 1982 with little evidence that yield potential had reached a plateau (Waddington et al., 1986). Improvements in grain yield were associated with increases in grain number per unit area and grains per spike, but not in kernel weight. Biomass increases and greater grain survival were the main factors contributing to increased yield in the most recently released cultivars of those evaluated in this study. Periodic evaluation of genetic improvement in hard red spring wheat is essential for understanding yield-limiting factors for major economic traits, il-lustrating the importance of plant breeding to stake-holders and the public, and identifying traits or target environments that might require additional research (Cox et al., 1988). Evaluation of wheat germplasm for given traits, such as yield potential, is necessary to allow us to detect genetic variation in traits associ-ated with advances in crop productivity. Determin-ing where genetic gain has been made or lacking in the past can lead researchers to new strategies for future improvements in crop productivity (Donmez et al., 2001). In 2006, an initiative was launched by the HRSW wheat breeding programs in the spring wheat area (MN, SD, and ND) with the support of the Min-nesota Wheat Research and Promotion Council to identify high yielding HRSW elite lines among exist-ing wheat germplasm. Preliminary results are prom-ising. Wheat lines which yielded significantly higher than commonly grown cultivars could be identified among the NDSU, SDSU, and the MN wheat germ-plasm.

References

Cox, T.S., J.P. Shoyer, Liu Ben-Hui, R.G. Sears, and T.J. Martin. 1988. Genetic improvement in agronom-ic traits of hard red winter wheat cultivars from 1919 to 1987. Crop Sci. 28:756-760.

Deckard, E.L., B.J. Stolz, and R.C. Frohberg. 1987. Effects of past breeding efforts on productivity of hard red spring wheat. N.D. Farm Research. 45(1):3-7. Donmez, E., R.G. Sears, J.P. Shroyer, and G.M. Paulsen. 2001. Genetic gain in yield attributes of win-ter wheat in the great plains. Crop Sci. 41:1412-1419. North Dakota Wheat Commission, Montana Wheat and Barley Committee, Minnesota Wheat Research and Promotion Council, South Dakota Wheat Com-mission, and U.S. Wheat Associates. 2003. U.S. hard red spring wheat regional quality report. Underdahl, J., M. Mergoum, and J. K. Ransom. 2007. Agronomic traits improvement and associa-tions in hard red spring wheat cultivars released in North Dakota from 1968 to 2006. Crop Science. (In press: CROP-2007-01-0018-ORA) Waddington, S.R., J.K. Ransom, M. Osmanzai, and D.A. Saunders. 1986. Improvement in yield potential of bread wheats adapted to North-west Mexico. Crop Science 26:698-703.


1. Development of additional genetic population and advance of the existing population.2. Screening of the segregating population in order to determine the genetics progress in grain yield.3. Evaluation of advanced material as a part of varietal development program.


Page ��

Soft Red Winter Wheat Germplasm Evaluation Jochum J. Wiersma, Northwest Research and Outreach Center, Crookston

Research Question

Evaluate the agronomic performance of a limited number of winter wheat varieties from the eastern USA and Europe.

Results

All but the hard red winter wheat varieties Roughrid-er and Jerry, included as checks, suffered 80 to 100% winterkill this past winter. The cold snap imme-diately prior to Easter is largely debit to the demise of the trials. No useful yield data was collected in 2007. Agronomical observations indicated that the Euro-pean germplasm tended to have a very late maturity, making their adaptation to Minnesota questionable.

Based on this past season’s results, different germ-plasm was requested of the cooperating breeders. For 2008, the entries include new material from the Crop Development Centre winter wheat breeding program at the University of Saskatchewan andRussian winter wheat accessions.

Application/Use

HRSW producers operate on tight economic mar-gins. This research will determine if growers should consider using liquid P sources to enhance HRSW grain yields instead of dry P sources, especially when applied with air seed-ers using broad band or ribbon seed-ing patterns. Optimizing and potentially reducing the annual P fertilizer gift can improve the profit margins for HRSW by reducing input cost and/or increas-ing grain yields.

This research also has broader environmental implications; as public opinion and political pressure mount to reduce production agriculture’s im-pact on the environment, research as described in this proposal can lay the foundation on which sound, sciencebased, policy recommendations can be made.


One winter triticale, three winter barley, four soft red winter wheat, and four German winter wheat cultivars were planted in Crookston, St. Paul, and Lamberton on October 2nd, 2006, using a randomized complete block design with 3 replicates.


None to date

Photo 1. Overview of the soft red winter wheat screening nursery no-till planted on

September 28, 2007, in soybean stubble near Crookston on October 26, 2007.


Page 32

Red River Valley Winter Wheat Production and Responses of Management Inputs

on Yield, Quality and EconomicsResearch Question

Evaluate the need and profitability of crop inputs commonly used in spring wheat in winter wheat production.

Results

No-till planting occurred on September 1, 14, and 28 in Fergus Falls, Casselton, and Crookston. The trial in Lamberton was planted on September 6, 21, and October 11. Nitrogen was top-dressed to treat-ments 1 and 4 after each planting date. Rain followed each planting date and mild temperatures resulted in rapid emergence and excellent initial stands. Plant population differences are detectable and were captured with stand counts. The mild temperatures in September extended through much of October. Growth and development of three planting dates are well ahead of the long-term average as a lack of cold temperatures through much of October hasn’t forced dormancy yet. Tan spot is prevalent across the sites and worst in the early planting.

Application/Use

Winter wheat can be an important component of the cropping systems in Minnesota and North Dakota. The primary constraint to winter wheat production in both states has been stand loss and winter injury. Newer varieties and production practices havereduced this risk, making winter wheat a more viable option. Winter wheat is very well suited for no-till cropping systems in which standing residue traps snow and reduces winter kill by insulating the crop from lethal temperatures.

Winter wheat can spread out the demands of labor and equipment on the farm as it is planted and harvested when there are few management activi-ties occurring in other crops. As a component of the cropping system, winter wheat can reduce soil losses from wind during the winter months and runoff in the spring. Furthermore, winter wheat can be highly

productive and profitable as it has higher yield poten-tial than spring wheat. The evaluation of crop inputs commonly used in spring wheat in winter wheat will help ensure that the full yield potential and profitabil-ity of winter wheat can be realized.


Seeding date is as whole plot treatment using four replications. Using a so-called ‘drop-out’ treatment design, other crop inputs combinations are applied as split plots. Jagalene and Jerry are use as the split split plots. T. Next to seeding date, inputs thatwill be considered are the standard versus an in-creased seeding rate, the use of a seed treatment, application of all N requirements pre-plant versus a split application, and the use of fungicides at the 4-5 leaf stage, flag leaf emergence, and to suppress FHB at flowering.

The ‘drop-out’ treatment design allows evaluation of the efficacy of individual crop input decisions in a much more efficient manner compared to a full or fractional factorial design. An underlying assump-tion, however, is that all crop inputs considered are additive in nature. Using two different cultivars as the split-split-plot treatment allows evaluation of the cultivar by treatment interactions.


None to date

Jochum J. Wiersma, Northwest Research and Outreach Center, Crookston


Page ��

Appendix

Photo 1. Stand of winter wheat no-till planted September 14, 2007, in standing spring wheat stubble near Crookston on October 26, 2007.

Photo 2. Stand of winter wheat no-till planted September 28, 2007, in standing spring wheat stubble near Crookston on October 26, 2007.


Page ��

Liquid vs Dry Phosphorus Fertilizer Formulations with Air Seeders


Research Question

The objective of this research is to compare HRSW biomass, P accumulation, and grain yield response to various rates of preplant broadcast and band (with the seed) applications of liquid (10-34-0) and dry (11-54-0) P fertilizer sources when the seed is banded in 4 inch wide bands with an air seeder.

Results

A preliminary analysis showed no difference in grain yield in response to liquid compared to the dry source of P-fertilizer. A more detailed analysis, including the whole plant uptake of P have not been completed.

Application/Use

HRSW producers operate on tight economic mar-gins. This research will determine if growers should consider using liquid P sources to enhance HRSW grain yields instead of dry P sources, especially when applied with air seeders using broad band or ribbon seeding patterns. Optimizing and potentially reduc-ing the annual P fertilizer gift can improve the profit margins for HRSW by reducing input cost and/or increasing grain yields.

This research also has broader environmental implications; as public opinion and political pressure mount to reduce production agriculture’s impact on the environment, research as described in this pro-posal can lay the foundation on which sound, sciencebased, policy recommendations can be made.


The experiment consisted of 20 treatments repli-cated 4 times for a total of 80 plots at each location using a randomized complete block design. The research was conducted at two sites near Crookston rated low for phosphorus using the Olsen soil test.

One set of plant samples was taken from each plot at about soft dough to determine total biomass production and total P accumulation in the plant. The

plots were harvested with a small plot combine at maturity and grain was analyzed for yield, protein, and test weight.


At this point in time it is unclear whether liquid sources of P-fertilizer provide any advantage over dry sources of P-fertilizer on the soils common in the Red River Valley Basin.

Appendix

Lombi, E., M.J. McLaughlin, R.D. Armstrong, and R.E. Holloway. 2004. Mobility and labibility of phos-phorus from granular and fluid monoammonium phosphate differs in a calcareous soil. Soil Sci. Soc. Am. J. 68:682-689.


Page 35

Continuation of the Intensive Management of the State Variety Trials for Hard Red Spring Wheat


Research Question

Due to the increased use of fungicides in wheat in Minnesota, we have implemented an additional vari-ety trial in which fungicides are applied at the time of herbicide application (Feekes 5), flag leaf emergence (Feekes 9), and at the onset of flowering (Feekes 10.51). The practice of three fungicide applications during the growing season is not recommended. This fungicide regime was implemented to measure the varieties performance when fungal diseases were controlled to the maximum extent possible. Grower’s decisions regarding fungicide applications should be based on the available decision support systems, and only if and when disease levels are forecasted to reach economic damaging levels.

Results

The additional performance evaluations were car-ried out adjacent to the conventional (no fungicides applied) trials. The trials were conducted in Lamber-ton, Morris, Crookston, and Roseau. Yield data of both the conventional and intensive management trials are summarized in Table 1. In 2007, the fungi-cide regime as applied in these trials increased grain yield across varieties 8.5 to 10 bu/A. The 2 and 3 year comparisons showed 5 to 7.5 bu/A, indicating that disease pressure was substantial higher this past season in comparison to the previous two years. Rather than the average increases in grain yield, the response of individual varieties provide the most use-ful information; varieties like Oxen, Marshall, Trooper that are rated susceptible to leaf rust, stripe rust, and powdery mildew benefited most from fungicide applications.

Application/Use

The results of the analysis of variance are in line with the previously reported results in the literature (Guy et al. 1989; Jorgenson et al. 1994; Puppala et al. 1998). Beuerlein et al. (1991) indicated that, because of the numerous cultivar x management in-teractions, it was difficult to formulate useful manage-ment guidelines for individual cultivars. Rather than

formulating management guidelines, a simpler ap-proach is to test varieties under both the conventional and intensive management approach and report both sets of yield data, giving producers the ability to review both sets of yield data.


The HRSW yield trials at the Research and Out-reach Centers in Morris and Crookston and the Magnusson Research Farm in Roseau were n which the whole plot treatments were two management systems for the yield trial and the split block were the entries in the variety trial. The two management ap-proaches were the current system of conducting yield trials in which insects and fungal pathogens are not controlled and a second management approach that included the use of a fungicide at Feekes 5 in combi-nation with a fungicide treatments at Feekes 9 andFeekes 10.51 as well as the use of an insecticide to control aphids. The two management approaches were labeled ‘intensive’ and ‘conventional’.

For the applications at Feekes 10.51, the labeled rate of 292 ml/ha of Folicur 3.6F (tebuconazole) (Bay-er CropScience, Alexander Drive, Research Triangle Park, NC 27709, USA) was used. The EPA section 18 label of Folicur 3.6F limits the use to 292 ml/ha in a single growing season (Bayer CropScience, Alexander Drive, Research Triangle Park, NC 27709, USA). Thus, for the applications at Feekes 5 and Feekes 9 two other broad spectrum fungicides were used. For the application at Feekes 9, the labeled rate of 292 ml/ha of Tilt (propiconazole) (Syngenta Crop Protection , Inc. Greenburo, NC 27419, USA) was used. For the application at Feekes 5, Stratego (Bayer CropScience, Alexander Drive, Research Triangle Park, NC 27709, USA), a mixture of 11.4% trifloxystrobin and 11.4% propiconazole, was used. Based on the recommendations for early season fun-gicide applications in the UK, one half of the labeled rate or 366 ml/ha of Stratego was applied (Home Grown Cereal Authority, 2000). Fungicide applica-tions were made using a tractor mounted sprayer that was equipped with 8002 TwinJet nozzles (Spraying Systems Co., North Avenue, Wheaton, IL 60188,


Page 36

USA) delivering 150 L/ha at 275 kPA. Fungicides were applied either in the morning or early evening to reduce drift. The timing of each application was based on the growth stage of the individual plots.


The economic benefit to a typical 500 acre wheat enterprise will vary greatly depending on the sea-son’s growing conditions. Using the average grain yield across the state for conventional and intensive management as reported in Table 1, Oxen could have yielded an extra 20 bushels with timely use of a fungicide this past season. This, combined with the record prices earlier this fall, equates to a differ-ence of over $150.- /A or $75,000.- for a typical 500 acre wheat enterprise.. The underlying cause for the significant yield increase is for a large part Oxen’s susceptibility to leaf rust. As stated in the Minnesota Variety Trials Bulletin, leaf rust continues to be a yearly problem on varieties with ratings of 5 or worse. Varieties with ratings of 4 or better should not experi-ence economic levels of damage to this fungus in most years.

Appendix

Beuerlein, J.E., Oplinger, E.S., and Reicosky, D. 1991. Yield and agronomic characteristics of soft red winter wheat as influenced by management. J. Prod. Agric. 4: 124-131. Guy, S.O., Oplinger, E.S., Wiersma, D.W., and Grau, C.R. 1989. Agronomic and economic response of winter wheat to foliar fungicides. J. Prod. Agric. 2:68-73. Home Grown Cereal Authority (HGCA). 2000. Wheat disease management guide. HGCA, Caledonia House, London, UK. Jorgenson, L.N., Secher, B.J.M., and Welling, B. 1994. Resistance in cereal cultivars and the need for fungicide treatments. Annals of Applied Biology 40: 267-275. Puppala, V., Herman, T.J., Bockus, W.W., and Loughin, T.M. 1998. Quality response of twelve hard red winter wheat cultivars to foliar fungicides across four locations in central Kansas. Cereal Chemistry 75: 94-99.


Page 37

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Page 38

Wheat Rotation Economics Kent D. Olson, Dept of Applied Economics, U of M

Research Question

The objective of this research is to determine wheth-er enterprise financial data can be linked to rotation history to evaluate crop rotation economics.

Results

Data has been collected from previous year’s crops showing present and previous crop yield and gross sales figures from a cropping unit. Preliminary analysis from the 362 data points collected, indicated a positive response of rotating wheat to either dry beans or sugar beets in comparison to following soy-bean, sunflower, or wheat (Figure 1). Cursory analy-sis further reveals that these differences are not just a function of higher grain yield but also differences in input costs as illustrated by the difference in return per acre between wheat following soybeans ver-sus wheat following sugar beets. Similar contrasts are observed for soybean (Figure 2).

Application/Use

Looking at whole farm cropping rotations rather than just enterprise analy-sis may offer insight into the economics of the rota-tions and why there may be economic benefits for including wheat in the crop rotation. This research should help producers make better crop rotational choices.

Figure 1. Effect of previous crop on grain yield and return per acre of wheat in northwest Minnesota.

0

20

40

60

80

100

120

Dry Bea

ns

Fallow

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Soybea

ns

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eets

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wers

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t

Previous Crop

Ret

urn

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10

20

30

40

50

60

70

Gra

in Y

ield

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A team of Northland College Farm Business Management instructors agreed to assist with the collection of crop and financial data through their normal collection for Finpak. We developed a key for participating farmers to complete that linked their crop history and financial data and analyzed the data to look for differences in yield and profitability due to previous crop rotation history.


Page 39

Figure 2. Effect of previous crop on grain yield and return per acre of soybean in northwest Minnesota.

0

10

20

30

40

50

60

70

80

90

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Page 40

2007 Red River Valley On-Farm Disease Management Trials

Charla R. Hollingsworth, Northwest Research and Outreach Center, Crookston

Research Question

During 2007, which spring wheat variety and dis-ease management combination was the most profit-able in the Red River Valley?

Results

Wheat fields that had epidemics of tan spot were few and far between this year. Leaf rust arrived in the Valley and was established before the crop headed in some locations, but disease develop-ment stalled on most varieties and at most locations until the grain filling stages when it became severe. Prevalence of Fusarium head blight was generally low across the Valley, but a few localized epidemics were reported. Weather conditions varied substan-tially between test locations near Oklee and Fergus Falls. The test at Fergus Falls had statistically lower grain test weights, kernel protein, and FHB disease than Oklee. No other data were significantly differ-ent due to the location effect. Deoxynivalenol (DON, vom, vomitoxin) levels in grain, caused by Fusarium graminearum infection, were miniscule at Fergus Falls (=0.1 ppm). DON data aren’t available, as yet, for the Oklee test but are expected to be low. Variety and disease management strategy had significant effects on yield, test weight, protein, FHB incidence, FHB severity, FHB index, and net revenue returned (P<0.05). When averaged over both locations, Sam-son, Ulen, Steele-ND, and Oklee had the most se-vere FHB symptoms, while Bigg Red, Alsen, Glenn, and Knudson had the least. Since FHB wasn’t a lim-iting factor for production this year, varieties known for their susceptibility to the disease had the best yields. Knudson (77.8 bu/a), Samson (77.6 bu/a), and Steele-ND (74.9 bu/a) had the highest yields, while Bigg Red (62.4 bu/a) and Alsen (63.3 bu/a) had the lowest. When averaged across all fungicide treatments, Knudson ($611.27/a), Samson ($608.26/a), and Steele-ND ($591.48/a) brought in the largest net returns, while Bigg Red ($482.89/a) and Alsen ($497.13/a) had the smallest (P<0.05). Yield, pro-tein, and test weights were significantly increased with disease management strategies #3, #4, and #5, compared with the nontreated control, strategy #1

(Table 1). Statistically, disease management strategy #4 resulted in the largest net returns when averaged across all varieties (P<0.05). Fungicide seed treat-ment increased estimated net revenue for about half the number of the varieties. Numerically, net revenues resulting from the fungicide seed treatment were greater than the nontreated control for Freyr (2%), Steele-ND (3%), Knudson (3%), Glenn (3%), Alsen (4%), and Samson (8%).Leaf rust caused yield reductions of up to 22% in susceptible varieties (Appendix). In general, yield limitations associated with disease were offset by timely fungicide application. Varieties responded well to this year’s growing environment, producing excel-lent yields of high quality grain. However, fungicide application increased net returns compared with the no fungicide treatment for many varieties even during a year of relatively low disease pressure. Economi-cally-speaking, those producers benefitting the most during 2007 grew FHB susceptible varieties, but those who the best better during the growing season grew more resistant varieties.

Application/Use

Maximizing wheat yield and quality is critical in obtaining the largest return for every input dollar. Producers need disease management information that is linked to economic outcomes in order to make informed disease management decisions during the growing season. Information from this research proj-ect supports disease management decision-making from planting to the elevator.


Treatments were replicated four times at each of two experiment locations. Planted into soybean resi-due, the first site was located near Oklee in northwest Minnesota and the second was near Fergus Falls in west central Minnesota. The Oklee site was planted on 27 April and the Fergus Falls site on 2 May 2007. Spring wheat cultivars included Ada, Alsen, Banton, Bigg Red, Briggs, Freyr, Glenn, Knudson, Oklee, Samson, Steele-ND, Ulen, and Walworth. Varieties were exposed to one of six disease management


Page ��

strategies (Table 1). The test areas were neither misted nor inoculated. Split spilt-plot analyses using PROC GLM in SAS were made where ‘location’ represented the whole plot, ‘fungicide’ the subplot, and ‘cultivar’ the sub-subplot. Transformations were conducted on data that had non-normal distributions. Factor means (location, fungicide, and variety) were compared us-ing LSD mean comparisons while targeted groups of varieties (susceptible vs. resistant) or fungicide treat-ments (fungicide vs. no fungicide) were compared using contrasts.


This information is important in determining which varieties and disease management strategy combi-nations have the greatest potential for profitability in the Red River Valley. For example, a producer could have increased his/her net revenue by about $117.00 per acre by protecting Bigg Red against soil-borne disease and leaf rust by applying three fungicides compared to just treating with a seed treatment. Knowing the most appropriate disease management strategy for Bigg Red meant a potential estimated net revenue increase of about $18,800 from a 160 acre field. However, an entirely different management strategy was needed for Glenn. There were only two disease management strategies that numerically

resulted in increased net returns compared to the no fungicide treatment for that variety. Acknowledgement and Disclaimer

We would like to thank the Minnesota Wheat Research and Promotion Council, the U.S. Wheat and Barley Scab Initiative, and WestBred LLC for supporting this research; BASF Corp., Bayer Crop-Science, and Syngenta for supplying fungicide products; AgriPro Wheat, Trigen Seed, and WestBred for supplying seed; and the University of Minnesota Mycotoxin lab for providing DON results; Tom and Deb Jennen (Fergus Falls) and Ray and Barbara Sw-enson (Oklee) for cooperating with us. Collaboration with Doug Holen, Fergus Falls Regional Extension Educator, contributed to the success of this research.

This material is based upon work supported by the U.S. Department of Agriculture, under Agreement No. 59-0790-3-080. This is a cooperative project with the U.S. Wheat & Barley Scab Initiative. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the U.S. Department of Agriculture.

This research represents single year information. Environmental conditions and disease pressures can vary substantially from year to year.

Application Strategy Product Active ingredient Rate* Timing

1 Nontreated control.. -- -- --

2 Dividend Extreme.. difenoconazole & mefenoxam 3 fl. oz./100 lbs. seed applied

3 Headline................. pyraclostrobin 3 fl. oz./a 4-5 leaf Folicur/Proline....... tebuconazole & prothioconazole 3 + 3 fl. oz./a early flower

4 Dividend Extreme.. difenoconazole & mefenoxam 3 fl. oz./100 lbs. seed applied Headline................. pyraclostrobin 3 fl. oz./a 4-5 leaf Folicur/Proline....... tebuconazole/prothioconazole 3 + 3 fl. oz./a early flower

5 Dividend Extreme.. difenoconazole & mefenoxam 3 fl. oz./100 lbs. seed applied Folicur/Proline....... tebuconazole & prothioconazole 3 + 3 fl. oz./a early flower

6 Folicur/Proline....... tebuconazole & prothioconazole 3 + 3 fl. oz./a early flower

*Treatments 3 through 6 included 0.125% Induce, a nonionic surfactant.

Table 1. Disease management strategies tested during 2007 at two test locations in the Red River Valley.


Page 42

12: APPENDIX

VarietyFungicide

TimingProtein

(%)Test Wt.(lb/bu)

Yield(bu/a)

Premium/ Discount2

Cash price

Fung appl. cost $/a3

Est. Return ($/a)

Ada S, L, F 14.3 62.9 80.7 $-0.02 $8.06 $26.51 $623.49F 14.2 62.1 75.8 $-0.03 $8.05 $17.40 $592.52S, F 14.2 62.3 76.0 $-0.04 $8.04 $21.38 $590.10S 13.8 62.2 70.2 $-0.06 $8.02 $3.98 $558.58L, F 14.4 62.6 71.2 $-0.03 $8.05 $22.53 $551.45None 13.6 62.6 66.7 $-0.10 $7.98 $0.00 $533.38Mean 14.1 62.5 73.4 $-0.05 $8.03 $15.30 $574.92

Alsen F 14.6 61.6 65.6 $0.01 $8.09 $17.40 $513.75L, F 14.6 61.9 65.8 $0.01 $8.09 $22.53 $510.09S, L, F 14.8 61.4 64.6 $0.02 $8.10 $26.51 $497.36S 14.8 61.4 61.7 $0.03 $8.11 $3.98 $495.81S, F 14.6 61.7 63.2 $0.02 $8.10 $21.38 $490.39None 14.4 61.5 58.8 $0.00 $8.08 $0.00 $475.37Mean 14.6 61.6 63.3 $0.02 $8.10 $15.30 $497.13

Banton L, F 14.6 62.7 77.5 $0.02 $8.10 $22.53 $604.81S, F 14.6 62.8 73.7 $0.02 $8.10 $21.38 $575.67S, L, F 14.6 62.6 73.3 $0.02 $8.10 $26.51 $566.75None 14.4 62.7 69.8 $0.00 $8.08 $0.00 $564.16S 14.5 62.5 70.0 $0.00 $8.08 $3.98 $561.86F 14.4 62.8 69.5 $0.00 $8.08 $17.40 $544.14Mean 14.5 62.7 72.3 $0.01 $8.09 $15.30 $569.57

Bigg Red S, L, F 14.2 62.6 70.5 $-0.01 $8.07 $26.51 $542.24L, F 13.8 62.7 67.7 $-0.08 $8.00 $22.53 $519.17F 14.0 63.2 64.9 $-0.03 $8.05 $17.40 $504.77S, F 13.7 63.1 63.6 $-0.07 $8.01 $21.38 $488.33None 12.5 62.2 55.3 $-0.24 $7.84 $0.00 $433.79S 12.7 62.5 54.4 $-0.21 $7.87 $3.98 $424.44Mean 13.5 62.7 62.7 $-0.11 $7.97 $15.30 $485.46

Briggs S, L, F 15.0 61.7 75.4 $0.03 $8.11 $26.51 $584.81None 14.8 61.2 70.8 $0.02 $8.10 $0.00 $573.90S 15.0 61.3 71.2 $0.02 $8.10 $3.98 $572.84L, F 14.8 61.9 73.4 $0.01 $8.09 $22.53 $570.65S, F 14.5 61.5 69.1 $-0.02 $8.06 $21.38 $535.79F 14.9 61.6 67.6 $0.03 $8.11 $17.40 $530.55Mean 14.8 61.5 71.3 $0.02 $8.10 $15.30 $561.42

Freyr L, F 14.5 61.1 76.3 $0.02 $8.10 $22.53 $595.53S, L, F 14.1 61.5 76.6 $-0.03 $8.05 $26.51 $590.85S 14.1 61.3 71.8 $-0.03 $8.05 $3.98 $574.38

continued........


Page ��

VarietyFungicide

TimingProtein

(%)Test Wt.(lb/bu)

Yield(bu/a)

Premium/ Discount2

Cash price

Fung appl. cost $/a3

Est. Return ($/a)

F 14.1 61.0 72.2 $-0.02 $8.06 $17.40 $564.22None 13.8 60.5 70.0 $-0.06 $8.02 $0.00 $562.19S, F 14.4 61.1 70.3 $0.00 $8.08 $21.38 $546.29Mean 14.2 61.1 72.9 $-0.02 $8.06 $15.30 $572.24

Glenn S, L, F 15.0 62.3 73.5 $0.04 $8.12 $26.51 $570.24S 15.3 62.3 67.4 $0.06 $8.14 $3.98 $544.14None 15.0 61.8 65.0 $0.04 $8.12 $0.00 $528.64F 14.8 62.5 67.4 $0.02 $8.10 $17.40 $528.04S, F 14.9 62.2 67.2 $0.03 $8.11 $21.38 $524.28L, F 15.1 62.3 67.1 $0.05 $8.13 $22.53 $523.08Mean 15.0 62.2 67.9 $0.04 $8.12 $15.30 $536.40

Knudson S, L, F 14.0 62.1 82.1 $-0.03 $8.05 $26.51 $634.76S 13.9 62.2 78.8 $-0.05 $8.03 $3.98 $629.36F 14.2 61.5 79.1 $0.00 $8.08 $17.40 $621.30None 13.7 61.9 76.5 $-0.07 $8.01 $0.00 $612.86L, F 14.2 61.7 77.1 $-0.01 $8.07 $22.53 $599.10S, F 14.0 61.7 73.5 $-0.04 $8.04 $21.38 $570.22Mean 14.0 61.9 77.9 $-0.03 $8.05 $15.30 $611.27

Oklee S, L, F 14.8 62.4 72.9 $0.02 $8.10 $26.51 $564.09L, F 14.8 61.9 70.5 $0.01 $8.09 $22.53 $547.97None 14.6 62.6 67.0 $0.01 $8.09 $0.00 $542.63S 14.9 62.6 67.1 $0.03 $8.11 $3.98 $539.55S, F 14.8 62.9 66.7 $0.00 $8.08 $21.38 $518.01F 15.3 62.1 65.6 $0.06 $8.14 $17.40 $516.42Mean 14.9 62.4 68.3 $0.02 $8.10 $15.30 $538.11

Samson F 14.0 61.7 81.6 $-0.05 $8.03 $17.40 $638.45S, L, F 14.2 62.0 81.5 $-0.02 $8.06 $26.51 $630.84S 13.6 61.4 78.5 $-0.08 $8.00 $3.98 $624.57L, F 14.0 61.8 77.9 $-0.05 $8.03 $22.53 $604.36S, F 13.9 61.5 74.9 $-0.05 $8.03 $21.38 $579.87None 13.4 61.3 71.5 $-0.11 $7.97 $0.00 $571.50Mean 13.9 61.6 77.7 $-0.06 $8.02 $15.30 $608.27

Steele-ND

S, L, F 14.6 62.5 79.6 $0.00 $8.08 $26.51 $617.04

S 14.9 62.4 75.2 $0.03 $8.11 $3.98 $605.91F 14.5 61.7 75.6 $0.00 $8.08 $17.40 $593.70None 14.6 62.2 72.8 $0.01 $8.09 $0.00 $589.10

continued........


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VarietyFungicideTiming

Protein (%)

Test Wt. (lb/bu)

Yield (bu/a)

Premium/Discount2

CashPrice

Fung. Appl.Cost $/a3

Est.Return

($/a)S, F 14.6 62.2 74.4 $0.02 $8.10 $21.38 $580.97L, F 14.7 62.7 77.1 $0.02 $8.10 $22.53 $562.15Mean 14.7 62.3 75.8 $0.01 $8.09 $15.30 $591.48

Ulen S, L, F 14.9 61.9 74.3 $0.04 $8.12 $26.51 $576.51F 14.7 61.9 73.0 $0.01 $8.09 $17.40 $573.88S, F 14.3 62.1 73.0 $-0.01 $8.07 $21.38 $568.01L, F 14.7 61.8 71.9 $0.01 $8.09 $22.53 $559.61None 14.4 61.8 68.6 $-0.01 $8.07 $0.00 $554.34S 14.4 61.5 67.7 $-0.01 $8.07 $3.98 $542.23Mean 14.6 61.8 71.4 $-0.01 $8.07 $15.30 $562.43

Walworth L, F 14.7 61.2 75.5 $0.01 $8.09 $22.53 $588.58S, L, F 14.4 61.0 74.4 $-0.02 $8.06 $26.51 $573.39F 14.6 60.8 68.6 $0.01 $8.09 $17.40 $537.53S 14.1 61.0 67.3 $-0.04 $8.04 $3.98 $536.97None 14.2 61.1 66.0 $-0.02 $8.06 $0.00 $531.92S, F 14.5 61.1 67.2 $-0.01 $8.07 $21.38 $521.13Mean 14.4 61.0 69.8 $-0.01 $8.07 $15.30 $548.25

GRAND MEAN 14.4 61.9 71.1 $-0.01 $8.07 $15.30 $558.23

1 Fungicide treatment product, rate and timing: None= No fungicide treatment; S= Dividend Extreme, 3 oz/100 lbs as a seed treatment; F= Folicur and Proline 3 fl oz each/a at early flower; L, F= Headline, 3 fl oz/a at the 4-5 leaf stage and tank mix of Folicur and Proline 3 fl oz each/a at early flower; S, F= Dividend Ex-treme, 3 oz/100 lbs as a seed treatment and tank mix of Folicur and Proline 3 fl oz each/a at early flower; S, L, F= Dividend Extreme, 3 oz/100 lbs as a seed treatment followed by Headline, 3 fl oz/a at the 4-5 leaf stage and tank mix of Folicur and Proline 3 fl oz each/a at early flower.

NOTE: Both the Headline treatment and Folicur + Proline (tank-mixed) treatment included 0.125% Induce, a nonionic surfactant.

2 On 31 Oct. 2007, analysis started with a cash base price of $8.08/bu. Protein premiums based up 1 per 1/5. Protein discounts based down 3 per 1/5. Protein adjustments were averaged across two locations each hav-ing four replications.

3 Fungicide costs based on Dividend Extreme at $170/gal, Headline at $219/gal, Folicur at $79/gal after rebate, Proline at $450/gal and early flower application cost of $5/a. Fungicide costs translate to Dividend Extreme $3.98/a; Headline $5.13/a; Folicur + Proline $12.40/a. No additional cost for application was added for seed treatment as it was treated at time of drill filling and the 4-5 leaf application would be made in combi-nation with herbicide application.

Appendix continued....


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UNIVERSITY OF MINNESOTA EXTENSION SERVICEUNIVERSITY OF MINNESOTA – U.S. DEPARTMENT OF AGRICULTURE

COLLEGE OF FOOD, AGRICULTURAL AND NATURAL RESOURCE SCIENCESST. PAUL, MINNESOTA 55108

Preliminary Report 24

2007 Spring Wheat and Barley Variety Performance in MinnesotaPreliminary Report

Preface

Worries about the drought extending into the 2007 growing season preoccupied many producers throughout the fall and winter. Adequate snowfall and some timely rains early in the spring alleviated those worries. By the second week of April, topsoil moisture was rated adequate for most of Minnesota; likewise, subsoil mois-ture was rated adequate for all but the northeastern 1/3 of the State.

Temperatures in the first half of April were unseasonably cool. The cold snap just prior to Easter that affected winter wheat throughout the Great Plains also damaged Minnesota’s winter wheat crop as it broke dormancy. The average temperatures rebounded very slowly with the average temperature in the second week of April being 7oF lower at 34oF.

Field work did not start in earnest until the fourth week of April. By April 22nd, only 4% of spring wheat, barley, or oats had been planted. Planting picked up pace with 20% of wheat planted by the end of April as tempera-tures increased from well below average to well above average. This was well behind the last year’s mark of 90% completed by the end April. Warm weather and favorable conditions continued in the first half of May and by May 14th, spring wheat, barley and oats planting passed the 90% mark, jumping ahead of the 5-year average by 20%.

Crop development also benefited from the warm weather with emergence being equal to or slightly ahead of 2006 as well as the 5-year average. The rapid crop development continued during the second half of May. Timely rains at the end of May and beginning of June relieved concerns about adequate soil moisture in many parts of the State. Unfortunately, the southern half of the Red River Valley received excess precipitation that led to temporary flooding and ultimately drowned out fields.

The warmer than normal weather continued for much of the month of June pushing crop development well ahead of 2006 and the 5-year average. On June 24th, USDA reported that 93% of the spring wheat crop had jointed compared to 87% in 2006 and 72% for the 5-year average. Nearly half the spring wheat was heading compared to just over 30% for the 5-year average. USDA estimated that the pace of heading was about 7 days ahead of the average.

Despite rapid development and above normal temperatures, USDA forecast Minnesota’s hard red spring wheat yield to average 48 bushes per acre on July 1. In the September Small Grain Summary, Minnesota’s spring wheat yield was adjusted down to an average of 47 bushels per acre, the same as in 2006. Variabil-ity within Minnesota, however, was much greater than in previous years with the southern Red River Valley reporting average yields well below the State’s average.

The overall quality of the crop was excellent with little to no concerns about contamination with DON, the mycotoxin associated with Fusarium head blight. Disease problems, in general, were minimal. The notable exception was leaf rust. Leaf rust appeared in early June and caused significant damages when left untreated in winter and spring wheat varieties that were rated susceptible to leaf rust. A cause for concern is that variet-ies previously rated as resistant showed significantly higher levels of leaf rust infections. This indicates that some of the commonly used leaf rust resistance genes no longer may prove to be effective.

Despite market pressure last fall and winter that favored corn, wheat acreage remained stable at 1.75 mil-


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lion acres planted and 1.65 million acres harvested. Winter wheat acreage jumped another 50% to 60,000 acres statewide. The average winter wheat yield declined 12 bushels per acre to 48 bushels per acres. Barley acreage rebounded some 20%, from the historical low of 90,000 acres largely due to more favorable contract prices and drought concerns. Oats acreage declined with 60,000 acres to 180,000 acres.

It should be noted that during harvest and immediately following harvest, world and U.S. grain markets reached historical highs. Strong export demands, a weak dollar, and a tightening of world stocks created a perfect storm that pushed prices as high as $9.60 a bushel on the Chicago Board of Trade in the final days of September. Unlike some previous market runs, many farmers were able to catch this ‘train’ with grain to sell.

Introduction

Successful small grain production begins with selecting the best varieties for a particular farm or field. For that reason, varieties are compared in trial plots on the Minnesota Agricultural Experiment Station (MAES) sites at St. Paul, Rosemount, Waseca, Lamberton, Morris, and Crookston. In addition to the six MAES loca-tions, trials are also planted with a number of farmer cooperators. These plots are handled such that the fac-tors affecting yield and performance are as identical for all entries at each location as is possible.

The MAES 2006 Wheat, Barley and Oat Variety Performance in Minnesota Preliminary Report is presented under authority granted by the Hatch Act of 1887 to the Minnesota Agricultural Experiment Station to conduct performance trials on farm crops and interpret data to the public.

The MAES and the College of Food, Agricultural and Natural Resource Sciences (CFANS) grants permis-sion to reproduce, print, and distribute the data in this publication - via the tables, only in their entirety, without rearrangement, manipulation, or reinterpretation. Permission is also granted to reproduce a maturity group sub-table provided the complete table headings and table notes are included.

Use and reproduction of any material from this publication must credit the MAES and the CFANS as its source.

Variety Classifications

Varieties are listed in the tables by heading date from earliest to latest. No other distinction or classification is used to group varieties. Seed of tested varieties can be eligible for certification, and use of certified seed is encouraged. However, certification does not imply a recommendation. Registered and certified seed is available from seed dealers or from growers listed in the ‘Minnesota Crop Improvement Association 2008 Directory’, available at through the Minnesota Crop Improvement Association office in St. Paul or online at http://www.mncia.org/publications.html.

Interpretation of the Data

The presented data are the preliminary variety trial information for single (2007) and multiple year (2005-2007) comparisons in Minnesota. The yields are reported as a percentage of the location mean, with overall mean (bu/A) listed below. Two-year and especially one-year data are less reliable and should be interpreted with caution. Similarly, averages across multiple environments, whether they are different years and/or locations, provide a more reliable estimate of mean performance. The least significant difference or LSD is a statistical method to determine whether the observed yield differences between two varieties are due to true, genetic differences between the varieties or to interactions with other variables such as a difference in soil fertility or experimental error. If the difference in yield between two varieties equals or exceeds the LSD value, the higher yielding one was indeed superior in yield. If the difference is less, the yield difference may have been due to chance rather than genetic differences, and we are unable to distinguish between the two variet-ies. The 5% unit indicates that with 95% confidence, the observed difference is indeed a true difference in performance. Lowering this confidence level will allow more varieties to appear different from each other, but also increases the chances that false conclusions are drawn.


Page 47

The Authors and Contributors

This report is written, compiled, and edited by Dr. Jochum Wiersma, Small Grains Specialist. The contributing authors/principal investigators are:

Dr. James Anderson, Wheat Breeder, Department of Agronomy & Plant Genetics; Dr. Kevin Smith, Barley Breeder, Department of Agronomy & Plant Genetics; Dr. Ruth Dill-Macky, Plant Pathologist, Department of Plant Pathology; Dr. Charla Hollingsworth, Extension Plant Pathologist, Department of Plant Pathology; Dr. Brian Steffenson, Plant Pathologist, Department of Plant Pathology; Dr. James Kolmer, USDA-ARS, Cereal Disease Laboratory, St. Paul; Dr. Yue Jin, USDA-ARS, Cereal Disease Laboratory, St. Paul; Dr. John Wiers-ma, Agronomist, Northwest Research & Outreach Station, Crookston.

Robert Bouvette, James Cameron, Mark Hanson, Tom Hoverstad, Gary Linkert, Jill Miller-Garvin, George Nel-son, Steve Quiring, Edward Schiefelbein, Catherine Springer, Galen Thompson, and Donn Vellekson super-vised fieldwork at the various sites.

Special thanks are also due to all cooperating producers.

SPRING WHEAT

James Anderson, Jochum Wiersma, Gary Linkert, Catherine Springer, John Wiersma, George Nelson, Ruth Dill-Macky, James Kolmer, Charla Hollingsworth, and Yue Jin

The results of the state yield trials are summarized in Tables 1 through 6. The average yield across the south-ern testing locations (St. Paul, Waseca, Lamberton and Morris) was 57 bu/A in 2007. This compares to an average of 77 bu/A in 2006 and a three-year average of 55 bu/A. The northern locations (Crookston, Stephen and Roseau) averaged 65 bu/A in 2007 compared to 76 bu/A last year and a three-year average of 70 bu/A.

Tables 2, 3, and 4 present the relative grain yield of tested varieties in 1, 2, and 3-year comparisons. ‘Faller’, the 2007 release from NDSU, was the top yielding cultivar in both the northern and southern testing locations in 2007. In the 2-year comparisons Traverse and Faller share the high mark for grain yield. Based on 3 years of trial comparisons, ‘Briggs’, ‘Granger’, ‘Howard’, ‘Knudson’, ‘RB07’, and ‘Steele-ND’ continue to do well across the State. The varietal characteristics are presented in Tables 1, 5, and 6. Losses and damages due to Fusarium head blight (FHB) were minimal in 2007. Yield losses due to leaf rust, however, were significant. Vigilance toward FHB remains paramount while closer attention should be given to the leaf rust resistance ratings. Variet-ies that are rated 4 or better for FHB are considered the best hedge against the diseases. The continuous change in leaf rust virulence resulted in a breakdown of some of our more common leaf rust resistance genes. Briggs, Glenn, Steele-ND, and Faller maintained a 1 rating for leaf rust. Carefully consider a variety’s rating to leaf and stripe rust, and plan to use a fungicide if a variety is rated 5 or higher to either leaf rust or stripe rust and disease levels warrant treatment. Varieties rated 4 or better should not experience economic levels of damage to either of these two fungi in most years. The foliar disease rating represents the total com-plex of leaf diseases other than the rusts, and includes the Septoria complex and tan spot. Although varieties may differ for their response to each of those diseases, the rating does not differentiate among them. Excep-tions are ‘Ada’, ‘Hat Trick’, and ‘Trooper’ which are rated susceptible to powdery mildew, and ‘Granite’ which is rated susceptible to bacterial leaf blight. Therefore, the rating should be used as a general indication and only for varietal selection in areas where these diseases historically have been a problem or if the previous crop is wheat or barley. Control of leaf diseases with fungicides may be warranted, even for those varieties with an above average rating. Fungicides, however, have no activity against bacterial leaf blight

Leading varieties in Minnesota, based on acres planted in 2007, include Freyr, Oklee, and Knudson, each with around 14% of the acres. Glenn, Briggs, and Alsen form the second tier of varieties with around 8% of the acres each. The flood of new release continues with six new entries in the state variety trials. Tested for the first time this year were ‘Blade’, ‘Cromwell’, ‘Kuntz’, ‘Hot Shot’, ‘Norwell’, ‘Sampson’, and ‘Vantage’.


Page 48

Variety selection for 2007 continues to be a balance between yield potential, disease responses, and grain quality. Freyr and Glenn are proven varieties that provide the best available genetic resistance to FHB and should be considered as hedges against this disease. Faller, Briggs, Traverse, and RB07 impress as high yielding HRSW across the state. Steele-ND, Howard, and Ulen are balanced varieties that combine yield potential with grain protein content.

BARLEY

Kevin Smith, John Wiersma, Ruth Dill-Macky, Jochum Wiersma, Brian Steffenson, Charla Hollingsworth, and Ed Schiefelbein

Yield averages for barley in Minnesota were 56 bu/A compared to 60 bu/A in 2007 resulting in production of about 6.2 million bushels. Robust had the highest acreage planted at 45.5 percent followed by Lacey (36.5%), Tradition (5.8%), and Stellar-ND (4.3%). Growing conditions were generally dry across the five test locations for barley variety trials in Minnesota. Precipitation early in the season and the lack of precipitation later in the season resulted in the nearly complete absence of disease. The highest yields were in Stephen and the lowest in Roseau (Table 7). FHB was essentially absent presumably due to unfavorable conditions for disease development.

The yield data in Table 7 were collected from the yield trials that contained the important varieties for the region planted in five locations in the state. Tradition, Legacy, Stander, and Lacey were the highest yielding varieties based on three year state averages (Table 7). Drummond is the most lodging resistant of the group (Table 8). The two-rowed variety Conlon had the plumpest grain while Legacy was a little thinner than the other varieties. All of the more recent varieties (Lacey, Drummond, Legacy, Tradition, and Stellar-ND) are shorter than Robust.

Table 9 describes the reaction of the currently grown varieties to the five major diseases in the region. Dis-ease reaction is based on at least three years of data and scored from 1 – 9 where 1 is most resistant and 9 is most susceptible. While there are some small differences among the varieties for resistance to some of these diseases, these differences are small and should not be the primary basis for selection among the different varieties.


Page 49

Variety Agent/Orgin 1Year of Release

Days to Heading 2 Plant Height 2

Straw Strength 3

-- days-- -- inches --Rush WestBred 2006 53 29 v. strongUlen MN 2005 53 32 mediumKelby AgriPro 2006 53 28 strongBriggs SDSU 2002 53 32 mediumTrooper WestBred 2004 53 29 v. strongSamson WestBred 2007 53 29 –Traverse SDSU 2006 54 �� mediumBanton Trigen 2004 54 32 strongGlenn NDSU 2005 54 �� strongOklee MN 2003 54 �� mediumGranger SDSU 2004 54 35 mediumOxen SDSU 1996 54 �� m. strongNorwell Thunder Seed 2006 54 �� –Steele-ND NDSU 2004 55 �� mediumFreyr AgriPro 2004 55 32 mediumHoward NDSU 2006 55 32 mediumKuntz AgriPro 2007 55 29 –Alsen NDSU 2000 55 32 strongKnudson AgriPro 2001 55 30 m. strongFBC-Dylan NPSAS/FBC 2006 55 �� mediumAda MN 2006 55 �� m. strongBlade WestBred 2007 55 �� –RB07 MN 2007 55 30 m. strongBigg Red WestBred 2004 55 �� mediumFaller NDSU 2007 56 32 m. strongHat Trick Trigen 2006 56 30 strongCromwell Thunder Seed 2007 57 �� –Granite WestBred 2002 57 29 v. strongFireball N. Star G. 2006 57 29 strongMarshall MN 1982 58 30 strongVantage WestBred 2007 58 29 v. strongHot Shot N. Star G. 2007 58 30 –Polaris N. Star G. 2003 61 �� v. strongBakker Gold N. Star G. 2006 61 �� v. strong

Mean 55.4 31.1

Table 1. Origin and agronomic characteristics of Hard Red Spring Wheat varieties in Minnesota in single year (2007) and multiple year comparisons (2005-2007).

� Abbreviations: MN = Minnesota Agricultural Expt. Stn.; NPSAS/FBC = Northern Plains Sustainable Agricul-ture Society/Farmer Breeder Club; N. Star G. = North Star Genetics; NDSU = North Dakota State University Research Foundation; SDSU = South Dakota Agricultural Expt. Stn.; Trigen = Trigen Seed Services LLC.2 2007 data. � 2005-2007 data.


Page 50

Table 2. Relative grain yield of Hard Red Spring Wheat varieties in southern locations in Minnesota in single year (2007) and multiple year comparisons (2005-2007).

Lamberton Morris St. Paul WasecaVariety 1 yr 2 yr 3 yr 1 yr 2 yr 3 yr 1 yr 2 yr 3 yr 1 yr 2 yr 3 yr

--------------------------------------------------------% of mean----------------------------------------------------Rush 92 90 – 93 88 – 96 93 – 95 89 –Ulen 101 100 105 97 103 102 105 107 109 108 �� 119Kelby 102 94 – 94 84 – �� 117 – 116 106 –Briggs 123 115 116 107 108 �� 105 105 101 102 104Trooper 71 73 73 105 106 108 83 99 100 74 82 81Samson 108 – – 106 – – 103 – – 108 – –Traverse 116 122 135 �� 115 120 100 105 103 121 117 122Banton 91 88 96 97 90 96 116 107 105 95 93 96Glenn 104 96 94 86 82 84 101 93 103 102 94 102Oklee 88 91 100 94 95 97 112 103 100 118 109 ��Granger 120 116 118 112 105 105 99 97 97 124 116 129Oxen 87 89 85 96 106 96 116 �� 99 85 95 97Norwell 92 – – 95 – – 109 – – 100 – –Steele-ND �� 109 115 106 �� 107 �� 105 �� 119 108 ��Freyr 101 102 109 103 109 109 �� 106 100 95 98 99Howard �� 109 112 98 107 106 116 109 112 121 109 117Kuntz 103 – – 107 – – 100 – – 98 – –Alsen 90 93 90 91 89 94 93 92 95 95 99 97Knudson 126 117 108 112 109 110 87 94 105 99 101 101FBC-Dylan 82 87 – 94 105 – 101 98 – 85 91 –Ada 106 108 �� 105 99 101 80 92 87 61 79 89Blade 109 – – 102 – – 104 – – 104 – –RB07 107 108 �� 88 100 95 �� 106 101 98 97 103Bigg Red 93 97 – 99 99 – 101 98 – 105 101 –Faller �� 123 – 120 115 – 107 109 – 119 �� –Hat Trick 112 103 – 101 105 – 81 87 – 115 107 –Cromwell 86 – – 97 – – 98 – – 89 – –Granite 103 104 109 97 91 94 103 99 97 107 107 101Fireball 88 89 – 90 97 – 95 92 – 89 91 –Marshall 64 71 60 69 83 71 72 87 73 47 72 58Vantage 98 – – 97 – – 80 – – 89 – –Hot Shot 73 – – 82 – – 77 – – 68 – –Polaris 86 97 84 89 105 99 59 76 83 66 89 83Bakker Gold

79 93 – 91 95 – 58 77 – 70 88 –

Mean (Bu/A)

76.7 46.7 42.2 70.8 68.9 58.6 59.9 75.9 66.8 52.0 59.8 52.5

LSD (0.05) 17.5 16.8 19.3 10.7 17.3 16.1 18.4 19.3 23.7 21.0 24.2 22.6


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Crookston Roseau 1 Stephen On-FarmVariety 1 yr 2 yr 3 yr 1 yr 2 yr 1 yr 2 yr 3 yr 1 yr 2 yr 3 yr

---------------------------------------------------------% of mean--------------------------------------------------Rush 90 88 – 108 94 93 97 – 97 94 -Ulen 97 98 98 105 107 98 102 97 103 101 101Kelby 101 102 – 120 102 97 93 – 94 98 -Briggs 103 110 105 127 �� 102 104 100 104 109 105Trooper 92 99 98 100 89 105 94 97 92 98 97Samson �� – – 109 – 117 – – �� -Traverse �� 116 119 117 112 115 112 119 118 -Banton 97 97 97 104 101 94 95 97 94 101 97Glenn 100 96 98 98 105 90 94 99 102 102 101Oklee 96 96 100 103 96 94 95 96 98 101 100Granger 95 94 102 105 105 91 97 103 100 107 105Oxen 97 102 101 79 92 97 103 104 95 96 94Norwell 97 – – 84 – 93 – – 90 - -Steele-ND 101 103 102 106 109 96 102 99 �� 108 105Freyr 109 103 106 103 101 101 99 106 108 103 103Howard 100 105 106 107 109 110 107 105 - - -Kuntz �� – – 95 – 99 – – 112 - -Alsen 89 92 94 80 93 90 93 92 93 95 94Knudson 109 108 �� 109 106 112 109 110 �� 109 107FBC-Dylan 93 95 – 87 96 91 95 – 95 - -Ada 95 96 100 103 100 97 92 95 101 99 98Blade 101 – – 106 – 107 – – 107 - -RB07 110 109 110 86 90 106 �� 110 109 109 109Bigg Red 93 94 – 73 88 93 92 – 86 95 -Faller �� 118 – 127 120 126 �� – 118 - -Hat Trick 93 87 – 89 89 117 98 – 106 103 -Cromwell 101 – – 118 – 98 – – 107 - -Granite 96 99 102 94 92 108 97 99 92 94 89Fireball 98 94 – 85 96 88 92 – 93 94 -Marshall 72 85 87 73 83 83 82 80 63 74 -Vantage 102 – – 91 – 104 – – 95 - -Hot Shot 83 – – 73 – 92 – – 84 - -Polaris 85 88 100 90 98 93 98 �� 92 92 94Bakker Gold 89 88 – 93 101 104 101 – 97 94 -

Mean (Bu/A 76.7 76.3 71.8 49.1 63.9 69.0 69.5 72.8 77.7 69.4 68.8LSD (0.05) 11.2 14.4 13.5 12.5 21.5 12.6 17.0 19.0 9.9 14.3 13.1

Table 3. Relative grain yield of Hard Red Spring Wheat varieties in northern locations in Minnesota in single year (2007) and multiple year comparisons (2005-2007).

� Roseau was abandoned in 2005 due to flooding.


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State North SouthVariety 1 yr 2 yr 3 yr 1 yr 2 yr 3 yr 1 yr 2 yr 3 yr

-----------------------------------------------------% of mean------------------------------------------------No. Environments 7 �� 20 � 6 8 � 8 12Rush 95 91 – 97 93 – 94 90 –Ulen 102 104 105 100 102 97 103 106 109Kelby 109 100 – 106 99 – �� 100 –Briggs 110 108 107 110 109 103 110 107 109Trooper 90 92 93 99 94 97 83 90 90Samson 109 – – �� – – 106 – –Traverse �� 115 118 �� 115 120Banton 99 96 98 98 98 97 100 95 98Glenn 97 94 97 96 98 99 98 91 96Oklee 101 98 101 98 96 98 103 99 103Granger 107 104 109 97 99 103 �� 109 112Oxen 94 100 97 91 99 103 96 101 94Norwell 96 – – 91 – – 99 – –Steele-ND 108 107 108 101 105 101 �� 108 112Freyr 103 103 105 104 101 106 103 104 104Howard 109 108 110 105 107 105 �� 109 112Kuntz 102 – – 102 – – 102 – –Alsen 90 93 94 86 93 93 92 93 94Knudson 108 106 107 110 108 110 106 105 106FBC-Dylan 90 95 – 90 95 – 91 95 –Ada 92 95 97 98 96 97 88 94 97Blade 105 – – 105 – – 105 – –RB07 101 103 106 101 104 110 101 103 103Bigg Red 94 96 – 86 91 – 99 99 –Faller 123 116 – 128 117 – 120 115 –Hat Trick 101 97 – 100 92 – 102 101 –Cromwell 98 – – 106 – – 93 – –Granite 101 98 100 99 96 101 103 100 100Fireball 90 93 – 90 94 – 90 92 –Marshall 68 80 71 76 83 83 63 78 65Vantage 94 – – 99 – – 91 – –Hot Shot 78 – – 83 – – 75 – –Polaris 81 93 93 89 95 106 75 92 87Bakker Gold 84 92 – 95 97 – 75 88 –

Mean (Bu/A) 60.3 65.8 64.0 65.0 70.0 70.0 56.8 65.8 55.0LSD (0.05) 9.6 6.6 6.1 12.2 8.8 9.3 13.9 9.2 10.0

Table 4. Relative grain yield of Hard Red Spring Wheat varieties in Minnesota in single year (2007) and multiple year comparisons (2005-2007).


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Test Weight Protein 1 Baking Quality 2

Pre-Harvest Sprouting 3Variety 1 yr 2 yr 1 yr 2 yr

----------lbs/bu------- ---------------%----------Rush 61.6 61.5 14.7 14.7 med.-high 2Ulen 60.0 60.5 14.8 14.7 med. 5Kelby 61.1 61.0 14.9 14.8 med. 2Briggs 61.3 61.4 15.0 14.6 med. 2Trooper 61.6 61.7 13.8 13.9 med.-high 2Samson 59.6 – 13.9 – – ��

Traverse 58.1 58.6 13.8 13.6 low �Banton 62.2 62.3 14.7 14.6 high-med. �Glenn 63.2 63.4 15.7 15.2 high �Oklee 60.8 61.0 14.8 14.8 low-med. �Granger 60.8 61.0 14.5 14.5 med. �Oxen 57.8 59.1 14.3 14.3 high-med. 2Norwell 60.6 – 14.2 – – ��

Steele-ND 61.4 61.7 15.3 14.9 high 2Freyr 60.0 60.5 14.4 14.3 med. �Howard 61.5 61.7 15.0 14.8 med.-high �Kuntz 60.2 – 14.0 – – 2�

Alsen 60.8 61.2 15.2 14.9 high 2Knudson 60.8 60.9 14.1 14.0 med.-high �FBC-Dylan 59.9 60.6 14.1 14.1 med.-low �Ada 61.4 61.7 14.3 14.3 med.-high 2Blade 62.6 – 14.9 – – 5�

RB07 60.4 60.6 15.2 14.9 med.-high 2Bigg Red 61.9 62.1 13.4 13.4 med.-low �Faller 60.9 60.7 14.3 14.0 med. 2Hat Trick 61.2 61.5 14.1 14.1 med.-low �Cromwell 61.6 – 14.8 – – ��

Granite 62.0 62.1 15.3 15.2 med.-low 25

Fireball 58.2 58.8 15.8 15.5 med. 5Marshall 57.3 58.7 13.5 13.4 low 2Vantage 61.8 – 15.3 – – 2�

Hot Shot 58.6 – 12.9 – – ��

Polaris 58.4 59.1 13.3 13.3 med. �Bakker Gold 58.5 59.2 13.4 13.4 low �

Mean 60.5 60.8 14.4 14.4

Table 5. Grain quality characteristics of Hard Red Spring Wheat varieties in Minnesota in single year (2007) and multiple year comparisons (2005-2007).

� 12% moisture basis. 2 2001-2006 crop years. � 1-9 scale in which 1 is best and 9 is worst. Values of 1-3 should be considered as resistant. � These ratings are based on one years’ data (2007). The rating may change by as much as 1 after additional data is collected.5 This variety’s Falling Numbers are typically 25-50 seconds (on a scale to 400) less than other varieties.


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VarietyLeaf Rust

Stripe Rust

Stem Rust 2

Other Leaf Diseases � Scab

Rush 5 – � 5 –Ulen � � � 6 6Kelby � – � � –Briggs � � 2 � 5Trooper 6 7 � 8� 6Samson 5 – – – –Traverse 5 – 2 5 –Banton � � � 5 5Glenn � � � � �Oklee 5 � � 5 5Granger � � � � 5Oxen 7 � � 7 8Norwell 7 – – 7 –Steele-ND � � � � 6Freyr � � � � �Howard � – � � –Kuntz � – – � –Alsen 5 � � 6 �Knudson 2 � � � 6FBC-Dylan 7 – � 7 –Ada � � 2 �� 6Blade 2 – – – –RB07 � � � � 5Bigg Red 8 – 2 7 �Faller � – � � –Hat Trick � – � 5� –Cromwell 5 – – – –Granite 6 � � 55 6Fireball 5 – � � –Marshall 8 � � 7 7Vantage � – – – –Hot Shot 7 – – 7 –Polaris 6 � 8 � 7Bakker Gold 5 – 7 5 –

Table 6. Disease reactions� of Hard Red Spring Wheat varieties in Minnesota in multiple year comparisons (2005-2007).

� 1-9 scale where 1=most resistant, 9=most susceptible.2 Stem rust levels have been very low in production fields in recent years, even on susceptible varieties. � Includes tan spot, septoria, bacterial leaf blight, and powdery mildew.� These varieties are more susceptible to powdery mildew. 5 This variety is more susceptible to bacterial leaf blight.


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Crookston Morris Stephen St. Paul Roseau StateVariety 1 yr 3 yr 1 yr 3 yr 1 yr 2 yr � 1 yr 2 2 yr � 1 yr 2 yr� 1 yr 3 yr

--------------------------------------------------------% of mean------------------------------------------------Robust 100 96 96 96 81 90 -- 104 103 104 95 98Stander 110 99 94 104 97 92 -- 102 �� 112 103 102MNBrite 93 98 98 95 97 92 -- 97 109 90 99 96Lacey 106 100 116 107 106 106 -- 100 101 92 107 102Drummond 102 98 92 98 105 98 -- �� 94 102 98 100Stellar ND 103 102 93 90 101 100 -- 93 103 102 100 97Legacy 100 101 112 108 112 110 -- �� 107 103 108 106Tradition 95 102 100 108 102 108 -- 99 90 107 97 105Conlon 92 103 99 94 100 103 -- 84 79 89 92 95

Mean (bu/A) 86 94 82 74 96 93 -- 96 53 82 79 87LSD (0.05) 12 7 16 �� 16 �� -- 8 17 �� 8 5

Table 7. Relative grain yield of barley varieties at several locations in Minnesota in single year (2007) and multiple year comparisons (2005-2007).

� Only two years of data, 2006 and 2007.2 No yield data for 2007.� Only two years of data, 2005 and 2006.

Variety Type UseDays to Heading

Plant Height Lodging Plump Protein

-- days -- -- inches -- -- % -- -- % --No. Environments 26 23 12 23 20Robust 6-row Malt 56 35 med. 84 13.3Stander 6-row Feed 57 32 strong 86 12.8MNBrite 6-row Feed 56 35 med. 83 14.3Lacey 6-row Malt 56 32 strong 85 13.3Drummond 6-row Malt 56 �� v. strong 82 13.2Stellar ND� 6-row Malt 57 32 strong 86 12.7Legacy 6-row Malt 57 �� med. 78 12.8Tradition2 6-row Malt 57 �� med. 85 13.4Conlon2 2-row Malt 57 �� med. 93 13.3

Table 8. Agronomic characteristics of barley varieties in Minnesota in multiple year comparisons (2000-2007).

� Only four years of plump and protein data, 2000-2001 and 2005-2006.2 Only four years of plump and protein data, 2003-2005.


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VarietyFusarium Head

Blight Net Blotch Spot Blotch

Septoria Speckled Leaf

Blotch Stem RustRobust 8 8 2 9 �Excel 8 8 2 9 �Stander 9 8 2 9 �MNBrite 6 6 � 9 �Lacey 8 8 2 9 �Drummond 8 7 2 9 �Legacy 7 5 2 9 �Tradition 8 7 2 9 �

Table 9. Disease reaction� of barley varieties in Minnesota in multiple year comparisons (2001-2005).

� Most Resistant = 1, Most Susceptible = 9.


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Minnesota Wheat Research & Promotion Council2600 Wheat Drive • Red Lake Falls, MN 56750

Ph: 218-253-4311 or 800-242-6118 • Fax: 218-253-4320www.smallgrains.org • [email protected]

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2 0 0 7 R E S E A R C H R E P O R T S 2007 Wheat Research ... · present, FHB and leaf diseases are mainly managed through fungicides application and cultural practices. Although