Proceedings

North American Barley Researchers Workshop

Madison, WI

October 26 -- 29, 2008

Contents

**Abstracts**

1.  Genetic variation for nitrogen uptake in spring barley. (Yadeta
    Anbessa, Patricia Juskiw, Allen Good and James Helm)

2.  Exploiting historical malting quality data from the Western Canadian
    Cooperative Two-row Barley trials using association mapping
    (Aaron D. Beattie, Brian G. Rossnagel and Michael J. Edney) (for
    full paper, see p 45)

3.  Illuminating the Biofuel Potential of Barley Straw (Victoria Carollo
    Blake and Thomas K. Blake)

4.  Barley Boulevard: A New Barley Information Portal on GrainGenes
    (Victoria Carollo Blake, David E. Matthews, Gerard L. Lazo, Olin D.
    Anderson)

5.  The Journey: From a Breeder\'s Cross to a Malting Barley Variety
    (A. D. Budde and K. P. Smith)

6.  A Comparison of Barley Malt Amylolytic Enzyme Activities and Malt
    Sugar Concentrations (Stanley H. Duke and Cynthia A. Henson)

7.  A Comparison of Barley Malt Quality Measurements and Malt Sugar
    Concentrations (Stanley H. Duke and Cynthia A. Henson)

8.  Osmolyte Concentration: A New Method for Determining Malt Quality
    (Stanley H. Duke and Cynthia A. Henson)

9.  Barley homogeneity: Measurement and importance for malting
    (Michael J. Edney, Aaron MacLeod, Steve Symons, John O\'Donovan,
    Kelly Turkington, and George Clayton)

10. The Impact of *qGPC6H* on Malting Quality, Grain Composition and
    Agronomic Performance (A. Fischer, G. Fischer, D. Parrott, A. Budde,
    V.C. Blake, T.K. Blake)

11. Net blotch quantitative trait loci - their practical application in
    barley breeding (Tajinder S. Grewal, Brian G. Rossnagel and
    Graham J. Scoles) (for full paper, see p 50)

12. Using genetics to advance breeding: donning the winter CAP (Hayes,
    P.M., A. Corey, A. Cuesta-Marcos, T. Filichkina, P. Szűcs, and J.
    VonZitzewitz)

13. Nitrogen effects on low-protein and semidwarf genotypes for malting
    barley production in western North Dakota (M.R. Hochhalter, R.D.
    Horsley, P.B. Schwarz; and R.J. Goos)

14. Evaluation of European barley genotypes for adaptation in the
    Northern Great Plains of the United States (R.D. Horsley, P.B.
    Schwarz, and S.M. Neate)

15. Understanding the genetics of barley β-glucan and diastatic power:
    ARS Aberdeen's initial steps toward marker-assisted selection in
    barley. (Eric Jackson, Don Obert, Juliet Windes, Gongshe Hu, Phil
    Bregitzer, Gerald Lazo, Harold Bockelman, and Mike Bonman)

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17. Stripe rust of barley and wheat in central Alberta (Kumar, K. K.
    Xi, T. K. Turkington, X.M. Chen, D. Salmon, J. Helm, P. Juskiw
    and J. Nyachiro)

18. Low phytate barley: The effect upon amino acid utilization during
    wort fermentation (Dennis E Langrell, Michael J Edney, William G
    Legge, and Brian G Rossnagel)

19. A new high-throughput screening method for measuring lipoxygenase in
    barley seed (Yin Li and Paul Schwarz)

20. Study of the effects of Pre-harvest Sprouting on the Storability and
    Malting quality of AC Metcalfe, CDC Kendall and CDC Copeland Barleys
    (Yueshu Li, Rob McCaig, Aleks Egi, Ken Sawatzky, and Deye Tian)

21. Nutritional and functional properties of whole grain barley bagels
    (C.Lukie, L. Malcolmson, A. Sarkar, and E. Sopiwnyk)

22. Screening for bird cherry-oat aphid resistance in barley (Do
    Mornhinweg and Harold Bockelman)

23. An overview of the barley coordinated agricultural project (Gary
    Muehlbauer)

24. Variation, causes, and significance of grain hardness in barley for
    food (Sindhu Nair, Byung-Kee Baik, and Steve Ullrich)

25. Waxy Barley: N Applications for Yield, Beta-glucan, and Protein (O.
    Steven Norberg, Brad Brown, Clint Shock, Andrew Ross, Pat Hayes, and
    Juan Rey)

26. Prediction of Deoxynivalenol (DON) content in grain using Near
    Infrared Reflectance Spectroscopy (NIRS) (Lori Oatway, James Helm
    and Kequan Xi)

27. Association mapping of malt quality QTL in the U of M barley
    breeding program: Detection, validation, and breeding (C.A. Powers,
    Paul Schwarz, Yin Li, K.P. Smith)

28. Distribution and Diversity of Russian Wheat Aphid (Homoptera:
    Aphididae) Biotypes in North America (Gary J. Puterka and Dolores W.
    Mornhinweg)

29. Fluorescence microplate readers as an alternative to flow injection
    analysis for determination of wort beta-glucan (Mark R. Schmitt and
    Allen D. Budde)

30. Let\'s get small: Miniaturized malt quality analysis for fun and
    profit (Mark R. Schmitt and Allen D. Budde)

31. Barley and oat grain and malt beta-glucan content measured by
    Calcofluor fluorescence in a microplate assay (Mark R. Schmitt and
    Mitchell Wise

32. Survey of Barley Producers in Idaho, Montana and North Dakota (Paul
    Schwarz)

33. Association mapping of Fusarium head blight QTL using contemporary
    barley breeding germplasm (Kevin P. Smith, Jon Massman, Blake
    Cooper, Rich Horsley, Stephen Neate, Ruth Dill-Macky, Shiaoman Chao,
    Yanhong Dong, and Paul Schwarz)

34. Progress towards predictive models for Fusarium Head Blight and DON
    in barley (J. Stein, K. Bondalapati, L. Osborne, S. Neate, and C.
    Hollingsworth) Poster or oral

35. Identification of a putative new barley leaf rust resistance gene
    (Y. Sun and S.M. Neate)

36. Barley Feed Quality - Is It Consistent Across Species? (Mary Lou
    Swift, James Helm, Tim McAllister, Fred Silversides, and Ruurd
    Zijlstra)

37. Expression analysis of ethylene biosynthesis and receptor genes from
    barley embryo and tissue culture (Neerja Tyagi and Lynn S. Dahleen)

38. Greenhouse and Field Demonstration of Microbial Suppression of
    Fusarium Head Blight in Barley (J.E. Van Cauwenberge, Schisler,
    D.A., Cooper, D., Smith, K. P)

39. β-Amylase activity and thermostability in wild and cultivated
    barleys with different *Bmy1* intron III alleles (Marcus A. Vinje,
    Stanley H. Duke, and Cynthia A. Henson)

40. Differential RNA expression of two barley β-amylase genes (*Bmy1*
    and *Bmy2*) in developing grains and their association with
    β-amylase activity (Marcus A. Vinje, David K. Willis, Stanley H.
    Duke, and Cynthia A. Henson)

41. Agronomic practices to improve winter hardiness of two-row winter
    malt barley "Charles" (Juliet Windes and Don Obert)

42. Tocol Content of Barley CAP germplasm, Preliminary Results
    (Mitchell L. Wise)

43. Validation of molecular markers for scald resistance in two-row
    barley (Zantinge J.L., Juskiw, P., Hartman, Z., and Xi K)

44. QTL Mapping and Molecular Marker Development for Seed Dormancy in
    Spring Barley (J.L. Zantinge, J Nyachiro, S. Xue, J. H. Helm, P. E.
    Juskiw and D. Salmon)

**Full Papers**

45\. Exploiting historical malting quality data from the Western
Canadian Cooperative two-row barley trials using association mapping.
Aaron D. Beattie, Brian G. Rossnagel, and Michael J. Edney.

50\. Net blotch quantitative trait loci -- Their practical application
in barley breeding. Tajinder S. Grewal, Brian G. Rossnagel, and Graham
J. Scoles.

**Genetic variation for nitrogen uptake in spring barley**

Yadeta Anbessa1\*, Patricia Juskiw1, Allen Good2 and James Helm1. Field
Crop Development Centre, Alberta Agriculture and Rural Development,
Lacombe, AB; Department of Biological Sciences, University of Alberta,
Edmonton, AB

\*Corresponding Author: (403) 782-8028, <yadeta.kabeta@gov.ab.ca>

Increased nitrogen uptake and utilization efficiencies are desirable to
reduce the negative effect of excessive N on the environment and cut the
need for expensive N fertilizer. As part of a venture to establish a
baseline for the nitrogen use efficiency (NUE) of barley, we assessed
the N uptake and biomass accumulation patterns of ten Canadian spring
barley cultivars during the 2007 and 2008 seasons in the field at
Lacombe, AB. Plant samples were taken from a 0.21 m2 area (three
replicates) at apex1, anthesis and maturity stages. For each plot
sample, plants were separated into leaves, stems and heads; dried; and
weighed. Then the tissues were sent for N content determination.
Analysis of variance revealed significant differences among cultivars in
leaf, stem and head dry weights. Also, significant differences were
found among cultivars in tissue N contents. Subsequently, the total
tissue N at physiological maturity varied widely among cultivars ranging
from 22 to 37 g m-2. This range in tissue N translated into differences
in NUE that indicates that there is a potential for genetic improvement
in NUE of spring barley.

**Exploiting historical malting quality data from the Western Canadian
Cooperative Two-row Barley trials using association mapping**

Aaron D. Beattie1\*, Brian G. Rossnagel1 and Michael J. Edney2

1Crop Development Centre, University of Saskatchewan, Saskatoon,
Saskatchewan, Canada S7N 5A8

2Grain Research Laboratory, Canadian Grain Commission, Winnipeg,
Manitoba, Canada R3C 3G8

\*Corresponding author: 306-966-8349, <aaron.beattie@usask.ca>

Association mapping (AM) is a method to detect significant correlations
between genotypic and phenotypic data using linkage disequilibrium (or
the non-random association between alleles). Unlike QTL analysis, AM
does not require production of a structured, experimental population,
but can be used with unrelated genotypes (or for which the relationships
between genotypes are taken into account). AM can exploit the larger
number of segregating loci in such populations and typically allows more
traits to be studied at once since there is more phenotypic variability.
In addition, historical phenotypic data (such as that typically
collected during collaborative testing) can be analyzed. A mixed-model
approach was used to study seven malting quality traits in 91 barley
genotypes from the 1994-2006 Western Canadian Co-operative Two-Row
Barley trials. These genotypes represent elite malting quality genotypes
from eight breeding programs, including the currently most popular
Canadian malting varieties (AC Metcalfe, CDC Copeland, CDC Kendall,
Harrington, Newdale) and newer varieties such as Calder, CDC Select, CDC
Aurora Nijo, CDC Reserve and CDC Meredith. DNA was extracted from the 91
genotypes and sent for DArT (Diversity Array Technology) whole genome
genotyping (Triticarte Pty. Ltd., Yarralumla, Australia) which
identified \>500 high quality markers. Analysis of the population using
unweighted pair-group method (UPGMA) clustering (based on the Dice
similarity coefficient) demonstrated genotypes from the same breeding
program tended to group together, but a significant amount of exchange
between programs was evident. This was also indicated by AMOVA which
determined that only 16% of the total genetic variation was distributed
between the breeding programs while most (84%) was distributed within
the breeding programs. Between two and four significant loci were
associated with each of the seven malting quality traits, including some
regions previously known to be associated with malting quality (e.g. the
lower distal region on chromosome 5H). The population will next be
genotyped using the Barley CAP BOPA1 SNP markers to identify candidate
genes associated with these traits.

**Illuminating the Biofuel Potential of Barley Straw**

Victoria Carollo Blake\* and Thomas K. Blake

Department of Plant Sciences and Plant Pathology,MontanaStateUniversity,
Bozeman,MT

Corresponding author: (406) 994-7229, <vblake@montana.edu>

As our need for biofuels to supplement petroleum-based fuels increases,
so will our need for feedstocks for ethanol production. Barley straw,
which to date has been an \`agricultural waste\' product in most
industrialized barley growing regions, should be a prime candidate for
ethanol production. The USDA Barley World Core Collection is a 1,917
member collection of *Hordeum* spp. representing barley accessions from
six continents and provides a wealth of genetic diversity. We have
screened this collection for three years for *in rumen* dry matter
digestibility (%DMD) and found barley straw to vary from 34% to 79%
digestible. Further analyses of the most digestible lines have revealed
that a select few of these accessions contain a significant soluble
carbohydrate concentration in the forage and straw. These soluble
carbohydrates are ready solubilized in 37ºC water and could potentially
enable the \`leftover\' straw from a barley crop to be efficiently used
in ethanol production. Association analysis with Illumina genotyping
data from 378 of the WCC lines and %DMD values have identified potential
QTL for the high DMD trait. Several of the high %DMD lines have already
been entered into the MSU barley breeding program, and fortunately,
lines that provided the highest levels of soluble carbohydrates are
already advanced in the breeding program. Characteristics of these lines
and their carbohydrate fraction will be discussed.

**Barley Boulevard: A New Barley Information Portal on GrainGenes**

Victoria Carollo Blake1\*, David E. Matthews2, Gerard L. Lazo3, Olin D.
Anderson3

1 Dept. of Plant Sciences and Plant Pathology, Montana State University,
Bozeman, MT 59717

2 USDA-ARS/Dept. of Plant Breeding and Genetics, Cornell University, 409
Bradfield Hall, Ithaca, NY 14853

3 USDA-ARS Western Regional Research Center, 800 Buchanan Street,
Albany, CA 94710

Corresponding author: (406) 994-7229, <vblake@montana.edu>

GrainGenes, the international database and web site for the Triticeae
and *Avena* (http://wheat.pw.usda.gov), has been a leading repository of
information on genetics and genomics since 1992. As the wealth of
information within the database and web site grows, so does our need to
continue to organize the data. Last year, GrainGenes launched Avena
Avenue (http://wheat.pw.usda.gov/GG2/Avena) as a shortcut to oat data on
GrainGenes and elsewhere. This portal was very well received by the oat
community and now the barley community has a similar tool. Barley
Boulevard (http://wheat.pw.usda.gov/GG2/Barley) has now been launched as
a web page to organize barley-related QuickQueries, external barley web
resources, barley-related meetings, newsletters, publications and barley
web sites of general interest. An overview of this new portal as well as
an update on new barley data in GrainGenes will be presented.

**The Journey: From a Breeder\'s Cross to a Malting Barley Variety.**

A. D. Budde\* and K. P. Smith. USDA ARS Cereal Crops Research Unit, 502
Walnut Street, Madison, WI 53726 and Dept. of Agronomy and Plant
Genetics, University of Minnesota - St. Paul.

\*Corresponding author 608-262-4483 (ph), 608-890-0302 (Fax),
<allen.budde@ars.usda.gov>

The process of generating a barley variety takes at least eight to ten
years from the time the cross is made until a new variety is released.
Each year 50 to 100 crosses are made each one producing hundreds of
progeny. Years later after cycles of inbreeding, selection, and
evaluation for numerous traits a couple of these progeny will make it
into the AMBA pilot malting evaluation program and possibly to plant
scale brewing tests before being released as a variety. The variety
"Rasmusson" has recently made this journey and is used to illustrate how
a line is evaluated as a potential malting barley. A timeline with
quality data documenting progress for advancing this line to malting
barley status is presented.

**A Comparison of Barley Malt Amylolytic Enzyme Activities and Malt
Sugar Concentrations**

Stanley H. Duke\*, Department of Agronomy, University of Wisconsin,
Madison, WI; and Cynthia A. Henson, United States Department of
Agriculture-Agricultural Research Service, Cereal Crops Research Unit,
Madison, WI, and Department of Agronomy, University of Wisconsin,
Madison, WI

\*Corresponding author: 608-262-6527, <shduke@wisc.edu>

This study was conducted to test the hypothesis that barley malt
α-amylase activity would correlate better with malt sugar concentrations
than the activities of β-amylase, or limit dextrinase. Seeds of four
two-row and four six-row North American elite barley cultivars were
steeped and germinated in a micromalter for 6 days. At 24h intervals
throughout germination, green malt was removed and kilned. Malts were
assayed for individual amylolytic activities and malt sugars were
extracted and assayed. Increases in malt α- and β-amylase and limit
dextrinase activities were greatest between day 1 and day 2 of
germination. Over all days of germination, for all cultivars combined,
malt α-amylase activities correlated much better with total sugar
concentrations (*r*=0.830, *P*\<0.0001) than β-amylase activities
(*r*=0.665, *P*\<0.0001), and somewhat better than limit dextrinase
activities (*r*=0.785, *P*\<0.0001). Correlations of individual sugar
concentrations (glucose, maltose, sucrose, fructose, and the
maltodextrins maltotriose through maltoheptaose) for all cultivars
combined over all days of germination were greater with α-amylase
activities than with β-amylase or limit dextrinase activities (e.g.
glucose and maltose *r* value, respectively: α-amylase, *r*=0.872,
*P*\<0.0001, *r*=0.763, *P*\<0.0001; β-amylase, *P*=0.587, *P*\<0.0001,
*r*=0.679, *P*\<0.0001; and limit dextrinase, *r*=0.806, *P*\<0.0001,
*r*=0.733, *P*\<0.0001). Over all days of germination, individual
cultivar malt α-amylase activities correlated better with total sugar
concentrations (low to high, *r*=0.738, *P*\<0.0001 \[Harrington\] to
*r*=0.925, *P*\<0.0001 \[Legacy\]) than β-amylase activities (low to
high, *r*=0.446, *P=*0.064 \[Harrington\] to *r*=0.891, *P*\<0.0001
\[Legacy\]) or limit dextrinase activities (low to high, *r*=0.577,
*P=*0.012 \[Harrington\] to *r*=0.867, *P*\<0.0001 \[Lacey\]) .
Correlations of individual sugar concentrations for individual cultivars
over all days of germination, for the most part, were greater with
α-amylase activities than with β-amylase or limit dextrinase activities
(e. g. low to high *r* values for glucose: α-amylase, *r*=0.791,
*P*\<0.0001 \[Garnet\] to *r*=0.901, *P*\<0.0001 \[B1202\]; β-amylase,
*r*=0.619. *P=*0.0008 \[B1202\] to *r*=0.849, *P*\<0.0001 \[Garnet\];
limit dextrinase, *r*=0.763, *P=*0.0002 \[Harrington\] to *r*=0.890,
*P*\<0.0001 \[Merit\]). Overall, malt α-amylase activity correlated
better with sugar production during malting and a short period of
mashing than other malt amylolytic enzymes, supporting the tested
hypothesis.

**A Comparison of Barley Malt Quality Measurements and Malt Sugar
Concentrations**

Stanley H. Duke\*, Department of Agronomy, University of Wisconsin, WI
and Cynthia A. Henson, USDA-ARS, Cereal Crops Research Unit, Madison,
WI, and Department of Agronomy, University of Wisconsin, WI

\*Corresponding author: 608-262-6527, <shduke@wisc.edu>

This study was conducted to test two hypotheses: (1) that malt osmolyte
concentration (OC) values would be better correlated with malt sugar
concentrations than malt extract (ME) values and (2) that malt α-amylase
activity (α-AA) would be better correlated with malt sugar
concentrations than diastatic power (DP). Seeds of four two-row and four
six-row barley genotypes were steeped and germinated in a micromalter
for 6 days. At intervals of 24 hr throughout germination, green malt was
removed and kilned and then assayed for ME, OC, DP, α-AA, and sugar
concentrations. Sugars were extracted from milled malt in H2O at 70°C
for 30 min. Except for cv. Harrington, total sugars increased throughout
the entire 6 days of germination regime in two-row genotypes but either
declined or plateaued after 4 days of germination in the six-row
genotypes. Over all days of germination for all genotypes combined, OC
correlated much better than ME with total sugar concentrations (OC,
*r*=0.867, *P*\<0.0001; ME, *r*=0.589, *P*\<0.0001), strongly supporting
the first hypothesis. When correlating individual sugar concentrations
with ME and OC for all days of germination for all genotypes combined,
OC also correlated much better than ME with glucose, maltose, sucrose,
fructose, and the maltodextrins maltotriose through maltoheptaose \[e.g.
low to high *r* values for OC, *r*=0.642 (fructose) to *r*=0.924 and
0.928 (glucose and maltotetratose, respectively), *P*\<0.0001; low to
high *r* values for ME, *r*=0.282 (fructose) to *r*=0.723 (glucose),
*P*=0.0524 to \<0.0001\], strongly supporting the first hypothesis. The
increases in OC over six days (48 and 58%, respectively for 2- and
6-row) were reflected by increases in total malt sugars (48 and 66%,
respectively for 2- and 6-row). In contrast, increases in ME over the
same period (3.8 and 3.7%, respectively for 2- and 6-row) were far lower
than those for total sugars or ME. OC reflects the total number of
hydrolytic cleavages of oligosaccharides, whereas ME only reflects
hydrolytic gain (the insertion of H2O for each oligosaccharide
cleavage), which is slight in magnitude compared to increases in
osmolarity. For all genotypes combined, α-AA correlated slightly better
than DP with total sugar concentrations over all days of germination
(α-AA, *r*=0.743, *P*\<0.0001; DP, *r*=0.711, *P*\<0.0001), supporting
the second hypothesis. When correlating individual sugar concentrations
with α-AA and DP for all days of germination for all genotypes combined,
α-AA also correlated better than DP with most sugar concentrations
\[e.g. low to high *r* values for α-AA, *r*=0.517 (fructose) to
*r*=0.900 (glucose), *P*=0.0 002 to \<0.0001; low to high *r* values for
DP, *r*=0.412 (fructose) to *r*=0.792 (maltotetraose), *P*=0.0037 to
\<0.0001\], supporting the second hypothesis. Overall, malt OC
correlated better with malt sugar concentrations than ME, DP, or α-AA,
indicating that OC best predicts starch hydrolysis during malting and a
subsequent short mashing period.

**Osmolyte Concentration: A New Method for Determining Malt Quality**

Stanley H. Duke\*, Department of Agronomy, University of Wisconsin,
Madison, WI; and Cynthia A. Henson, United States Department of
Agriculture-Agricultural Research Service, Cereal Crops Research Unit,
Madison, WI, and Department of Agronomy, University of Wisconsin,
Madison, WI

\*Corresponding author: 608-262-6527, <shduke@wisc.edu>

The primary ASBC, IoB, and EBC methods for measuring malt quality,
although frequently modified, have basically remained the same for
decades and in some cases centuries. Recent studies have found that malt
osmolyte concentrations (OC) are excellent predictors of malt extract
(ME), diastatic power (DP), and ASBC method α-amylase activity (α-AA).
Also, OC has been found to correlate much better with malt sugars than
ME, DP, ASBC α-AA, Megazyme Ceralpha method α-AA, α-amylase activity, or
limit dextrinase activity. These observations would indicate that OC
better tracks the degradation of all soluble polymers such as starch,
proteins, and β-glucans that are important to maltsters and brewers. The
intrinsic nature of malt OC is that it measures the total molar
concentration of a solution and not the mass of material in solution as
does ME. This characteristic of OC lends it to be more discriminating as
to the composition of a malt or wort. For instance, the hydrolytic
cleavage of 1 mol of maltopentaose in solution to glucose would result
in a 500% increase in OC, but only a ca. 9.1% increase in ME. The
increase in ME is strictly due to hydrolytic gain resulting from the
insertion of a hydroxyl group and hydrogen from H2O with each hydrolytic
cleavage of glucose from maltopentaose, whereas the increase in OC is
due to the increase in osmolality of the solution due to cleavage of all
α-(1,4) bonds of maltopentaose. The simplicity, rapidity, cost
effectiveness, and accuracy of the OC method will be discussed.

**Barley homogeneity: Measurement and importance for malting**

Michael J. Edney\*, Aaron MacLeod, Steve Symons, *Grain Research
Laboratory, Canadian Grain Commission, Winnipeg, Canada*, John
O\'Donovan, Kelly Turkington, and George Clayton, *Lacombe Research
Station, Agriculture and Agri-Food Canada, Lacombe, Canada*

\*Corresponding author: (204) 983-8854,
<michael.edney@grainscanada.gc.ca>

Maltsters require homogeneous barley to achieve a top quality malt.
Barley with uniform kernel characteristics is easier to process and
should produce more evenly modified malt that will help avoid potential
problems in the brewery. Despite the importance of homogeneity, standard
malt and barley quality analyses are based on a bulk sample which
overlooks variation among kernels. The Single Kernel Characterization
System (SKCS) and Near Infrared Spectroscopy are two technologies that
can be used to quantify the homogeneity of barley. Germination Index is
a simple test that can be used to measure evenness of germination. The
uniformity of malt modification can be measured using standard EBC
methods for Friability and Calcofluor homogeneity.

These techniques were used to evaluate the quality of barley grown under
a range of agronomic conditions. Analysis by SKCS indicated a
significant decrease in the variation of kernel size with higher seeding
rate. By examining the near infrared spectra acquired using a common
grain analyzer it was also possible to measure differences in the
homogeneity of barley. Near infrared instrumentation capable of
processing single kernels offers the opportunity to measure variation in
protein content among individual grains, replacing the more traditional,
but much more laborious, method of single kernel combustion nitrogen
analysis.

Variation in the distribution of size, protein content, and germinative
vigour of individual barley kernels affected the consistency of water
uptake during malting leading to significant differences in uniformity
of modification in finished malt as measured with the Calcofluor
staining method.

Positive impacts of increased homogeneity on malt quality were clearly
demonstrated with decreased levels of wort beta-glucan, and improvements
in common modification indicators such as friability and Kolbach Index.
With several analytical methods available, homogeneity is a criteria
that should not be ignored when seeking a barley that will give maximum
performance in the malthouse.

**The Impact of *qGPC6H* on Malting Quality, Grain Composition and
Agronomic Performance**

A. Fischer, G. Fischer, D. Parrott, A. Budde, V.C. Blake, T.K. Blake\*

Dept. of Plant Sciences and Plant Pathology, Montana State University,
Bozeman, MT 59717

\*Corresponding author: 406-994-5055, <blake@montana.edu>

One of barley\'s more remarkable characteristics is its ability to
tolerate variation in seed composition. Selection for increased
percentage of one grain component (e.g. protein) can be accomplished by
reduction in the percentage of another component (e.g. starch). Starch
is the largest contributor to malt extract, and its negative correlation
with grain protein percentage is widely appreciated. We previously
identified a barley gene, *qGPC6H*, in which allelic variation
significantly impacted grain protein percentage. Similar variation was
observed in wheat, and the gene responsible for this variation was
recently cloned. This barley version of this gene, *HvNAM-1*, is a
transcription factor that has significant impact on the initiation of
plant senescence. In barley, the allele derived from the variety
\`Karl\' results in delayed plant senescence with no measurable impact
on flowering date. This allele also results in reduced grain protein
percentage. We backcrossed the \`Karl\' low grain protein percentage
allele into the 2-rowed barley variety \`Lewis\', producing four
independently-derived backcross (BC4) lines. We also backcrossed the
\`Lewis\' high grain protein percentage allele into Karl, producing four
independently-derived backcross lines. Dryland and irrigated replicated
yield trials were performed in 2006 and 2007 with these lines. We
measured grain composition from our trials in 2006 and malting quality
from our trials in 2007. In this report we demonstrate that transfer of
the \`Karl\' allele into the \`Lewis\' genetic background results in
plants with higher grain yield, higher grain starch content and higher
malt extract. Correspondingly, when the \`Lewis\' allele is backcrossed
into the Karl background, grain yield and starch percentage are reduced,
as is malt extract.

**Net blotch quantitative trait loci - their practical application in
barley breeding**

Tajinder S. Grewal, Brian G. Rossnagel\* and Graham J. Scoles. Crop
Development Centre/Department of Plant Sciences, University of
Saskatchewan, 51 Campus Drive, Saskatoon, SK, Canada S7N 5A8

\*Corresponding author: 306-966-4976, <brian.rossnagel@usask.ca>

Net blotch, caused by *Pyrenophora teres* Drechs., is an important
worldwide foliar barley disease. Resistant cultivars are the most
economic and eco-friendly control method. Quantitative trait loci (QTL)
associated with net blotch resistance were mapped in a doubled-haploid
barley population (CDC Dolly/TR251) using diversity arrays technology
(DArT®) markers. A major net-form net blotch (NFNB) seedling resistance
QTL, designated *Rpt6*, was mapped to chromosome 6H for isolates WRS858
and WRS1607. *QRpt6* was associated with adult-plant resistance in 2005
and 2006 field trials. A seedling resistance QTL (*QRpts4*) for the
spot-form net blotch (SFNB) isolate WRS857 was detected on chromosome 4H
as was a significant QTL (*QRpt7*) on chromosome 7H. Three QTL (*QRpt6*,
*QRpts4*, *QRpt7*) were associated with resistance to both net blotch
forms and lines with one or more of these demonstrated improved
resistance. Simple sequence repeat (SSR) markers tightly linked to
*QRpt6* and *QRpts4* were identified and validated in an unrelated
barley population (MEH#486/Harrington). *QRpt6* was further validated
for seedling and adult-plant NFNB resistance in another doubled-haploid
population (CDC Bold/TR251). Since the major 6H QTL, *QRpt6*, may
provide adequate NFNB field resistance in western Canada the practical
application plan for the Crop Development Centre barley breeding program
is to routinely utilize MMAS for *QRpt6* followed by normal field
screening in net blotch field nurseries to pick up the additional
resistance provided by the other QTL.

**Using genetics to advance breeding: donning the winter CAP**

Hayes, P.M.\*, A. Corey, A. Cuesta-Marcos, T. Filichkina, P. Szűcs, and
J. VonZitzewitz, Department of Crop and Soil Science, Oregon State
University, Corvallis, OR 97331, USA

\* Corresponding author: 541-737-5878. <Patrick.m.hayes@oregonstate.edu>

The winter hardiness of cereal crops is associated with low temperature
tolerance, vernalization, and photoperiod sensitivity. Understanding the
genetics of these traits, using agronomically relevant germplasm, will
provide new opportunities for sustainable and productive barley
production. Via the Barley CAP, we have created new generations of
germplasm, obtained massively parallel data sets, and are anticipating
new insights into the ancestral and derived conditions of our crop.
These insights will, optimistically, achieve the Barley CAP goal of
using fundamental genetics tools to leverage marker assisted selection
for variety development.

**Nitrogen effects on low-protein and semidwarf genotypes for malting
barley production in western North Dakota**

M.R. Hochhalter, R.D. Horsley\*, and P.B. Schwarz, Department of Plant
Sciences, North Dakota State University, Fargo, ND 58105; and R.J. Goos,
School of Natural Resources, North Dakota State University, Fargo, ND
58105

\*Corresponding author: 701-231-8142, <richard.horsley@ndsu.edu>

Malting barley production has moved from the eastern part of North
Dakota to the western part of the state in recent years mainly due to
the accumulation of high levels of the mycotoxin deoxynivalenol (DON)
produced by the fungus *Fusarium* *graminearum* Schwabe. When grown
under dryland conditions of western North Dakota, current malt barley
cultivars typically have excessive grain protein when fertilized
according to NDSU Extension guidelines. When grown under irrigation in
western North Dakota and eastern Montana, these same cultivars tend to
lodge. Barley cultivars specifically adapted for production in western
North Dakota are being developed as part of the North Dakota State
University (NDSU) Western Malting Barley Project. Improved cultivars for
dryland production will have gene(s) that reduce protein up to two
percentage units as compared to current cultivars. New cultivars for
irrigated production will have the semi-dwarf plant height so they are
less prone to lodge. In addition, lines with the low-protein and
semi-dwarf traits are being developed to determine if yields can be
significantly increased under irrigation. It is thought that increasing
N fertilizer of genotypes with the semi-dwarf and low-protein characters
would allow for maximizing of yield, without the usual consequences of
excessive lodging and grain protein. Research is being conducted to: 1)
determine if genotypes with the low-protein character have better
agronomic performance and malt quality than current cultivars under
dryland conditions when different N fertilizer rates are applied
pre-plant and 2) determine if genotypes with the semi-dwarf,
low-protein, or both characters have better agronomic performance and
malt quality than current cultivars under irrigated conditions when
different N fertilizer rates are applied pre-plant. This research is
being conducted under dryland and irrigated conditions. Twenty-five
barley genotypes, including Robust, Stellar-ND, Drummond, Lacey, Legacy,
Tradition, and Conlon; six conventional-height genotypes with the
low-protein character; six semi-dwarf genotypes with the
conventional-protein character; and six semi-dwarf genotypes with the
low-protein character are being evaluated. Each of these genotypes is
being subjected to four different fertility regimens and all pertinent
agronomic and malt quality data are collected. In addition, In addition,
biomass samples will be collected to determine the amount of residual N
in straw and grain to determine how the low-protein lines differ from
conventional protein lines with regards to N translocation in the
plants. Dryland experiments were conducted in 2005 and 2006, and
irrigated experiments were conducted in 2006 and 2007. Results from this
research will be presented.

**Evaluation of European barley genotypes for adaptation in the Northern
Great Plains of the United States**.

R.D. Horsley\* and P.B. Schwarz, Department of Plant Sciences, North
Dakota State University, Fargo, ND 58105; and S.M. Neate, Department of
Plant Pathology, North Dakota State University, Fargo, ND 58105

\*Corresponding author: 701-231-8142, <richard.horsley@ndsu.edu>

Since 2006 the North Dakota State University (NDSU) barley improvement
program has been evaluating two-rowed lines from the breeding companies
Saatzucht Breun and Saatzucht Ackerman in Germany, and Sejet in Denmark.
The collaboration between our program and the ones in Europe has been
facilitated by BayWa AG, located in Munich, Germany. The purpose of this
collaboration is to identify European malting barley lines adapted for
production in North Dakota. Evaluation of lines has been done in dryland
and irrigated yield trials in North Dakota and Sidney, MT that include
Midwest USA six- and two-rowed malting barley cultivars as checks.
European lines evaluated include the cultivars Scarlett, JB Flavour
(8125 d7), JB Umbrella (7571 f13), JB Mary, Marnie, Isotta, Jenuva,
Anaconda, Posada, Grace, Audrey, Marthe, Belana, and Ingmar; and
experimental lines. In general, many of these lines are competitive in
yield with the NDSU cultivar Conlon, but do suffer comparatively lower
yield and fewer plump kernels than Conlon under droughty conditions. In
comparison to Scarlett, a German cultivar that is currently on the
American Malting Barley Association\'s (AMBA) list of recommended
malting barley varieties, many of these lines have superior agronomic
performance. European lines tested for the first time in our program are
handled the same as NDSU developed entries in our Preliminary Yield
Trial. They are evaluated at North Dakota two locations and are advanced
for further testing in subsequent years if they have satisfactory
agronomic performance, disease resistance, and malt quality. Based on
agreement with our European partners and the AMBA, lines with acceptable
performance after three years of testing by our program will be entered
in the AMBA\'s Pilot Scale Evaluation Program. Results from the yield
trial, malt quality, and disease resistance testing of the European
lines and selected checks since 2006 will be reported.

**Understanding the genetics of barley β-glucan and diastatic power: ARS
Aberdeen's initial steps toward marker-assisted selection in barley**

Eric Jackson\*, Don Obert, Juliet Windes, Gongshe Hu, Phil Bregitzer,
Gerald Lazo, Harold Bockelman, and Mike Bonman.

\*Corresponding author (208) 397-4162 x 123, <eric.jackson@ars.usda.gov>

Two key objectives in the USDA ARS Aberdeen's barley breeding program
are improving β-glucan content in feed barleys and diastatic power,
defined as known enzymatic activity, in malt barleys. Although studies
have been done to investigate the genetics of barley beta glucan, the
populations used ('Steptoe/Morex', 'Harrington/TR206', and
'Blenheim'/E224/3) were developed with malting quality in mind.
Utilization of these populations could have resulted in the
identification of only allele(s)/allele combinations contributing to
moderate levels of β-glucan. In response to this potential problem, our
objective was to develop a new mapping population derived from two
six-rowed hulless lines: 'Azhul', the primary source of high β-glucan in
most commercial cultivars and breeding programs, and 'Falcon', a well
adapted variety to Idaho with moderate levels of β-glucan. The
Falcon/Azhul (FA) population will be used to study the genetics and
environmental effects on barley β-glucan over several location-years in
North America. We have developed a F~6:8~ recombinant inbred line (RIL)
population mapped with approximately 490 DArT and 100 previously
developed SSR markers. In addition, we have added approximately 50 new
EST-based SSR markers derived from the same contigs used for BOPA1 SNP
development. Mapping results and preliminary QTL analysis using β-glucan
measurement from seed grown in Yuma, AZ and Aberdeen, ID will be
reported.

A major impediment to improving malt quality in barley is the large
number of traits involved. For this reason, our objective is to identify
and study key traits affecting areas of malting quality which are
lacking in the Aberdeen breeding program. The first area targeted was
low enzymatic activity known as diastatic power (DP). To study this area
without compromising other key traits, we developed a mapping population
from a cross of 01Ab8219, an elite six-rowed line from the Aberdeen
breeding program, and 'Stellar', a six-rowed malting barley cultivar
developed by the North Dakota AES. 01AB8219 has a suitable malting
profile, except for low DP, while Stellar has a suitable malting
profile, with significantly higher levels of DP than 01Ab8219. We have
developed F~6~ RILs which are being mapped with SSR markers and being
increased for multi-location testing of F~6:8~ RILs in 2009. Mapping
results, multilocation testing plans, and new approaches to measure
expression of the two *alpha*-amylase enzymes (*Amy1*and *Amy2*), the
two *beta*-amylase enzymes (*Bmy1* and *Bym2*), and the
*alpha*-glucosidase enzyme (*Agl*) will be discussed.

We are also pursuing a third strategy to identify and mine novel alleles
associated with β-glucan and DP by intensively genotyping 376 accessions
from a subset of the NSGC barley core collection. To develop the
population, single plant selections have been made from each accession
and the resulting selections are being genotyped with 992 DArT and 48
SSR markers. Seed from each line is also being increased for
multi-location testing. Genetic analysis of population structure will be
presented and strategies for association mapping and allele mining from
the collection will be discussed.

**Stripe rust of barley and wheat in central Alberta**

K. Kumar^1\*^, K. Xi^1^, T. K. Turkington^2^, X.M. Chen^3^, D.
Salmon^1^, J. Helm^1^, P. Juskiw^1^ and J. Nyachiro^1^.

^1^Field Crop Development Centre, Alberta Agriculture and Food, 6000 C
and E Trail, Lacombe, AB T4L 1W1 Canada, ^2^Agriculure and Agri-Food
Canada, Lacombe Research Centre, 6000 C and E Trail Lacombe, AB T4L 1W1
Canada, ^3^USDA-ARS, 361 Johnson Hall, Washington State University, P.O.
Box 646430, Pullman, WA 99164-6430 USA

\*Corresponding author: 403-782-8880, <krishan.kumar@gov.ab.ca>

Spring barley is typically grown on over 4 million acres annually in
Alberta and accounts for approximately 45% of the total barley acreage
in western Canada. Stripe rust caused by *Puccinia striiformis* was
observed both on barley and wheat in central Alberta, with disease
severity and occurrence location being variable between the two cereal
hosts. Studies are being undertaken to compare the epidemiology of
stripe rust between barley and wheat. In the field experiment of the
2007 season, a trace level of stripe rust on a susceptible barley line
was present compared with 50 - 90% stripe rust severity on susceptible
spring wheat cultivars. Likewise, no stripe rust was observed in the
barley differentials but substantial levels of this disease was present
in the wheat differentials grown in the field plots. In the final
assessment for the 2008 season, susceptible barley lines showed 80 - 95%
stripe rust severity compared with 40 - 70% severity for a susceptible
spring wheat cultivar. In the same season, however, the barley
differentials showed a lower stripe rust severity than wheat
differentials grown in the field. The *P. striiformis* isolates
collected are being inoculated onto the differential sets under
controlled environmental conditions to differentiate between *P.
striiformis* f.sp. *hordei* and *P. striiformis* f.sp. *tritici*. These
isolates are also being analyzed for differentiation using the simple
sequence repeats procedure. The results in the identification of forma
specialis will be discussed in relation to the development of cereal
stripe rust in central Alberta.

**Low phytate barley: The effect upon amino acid utilization during wort
fermentation**

Dennis E Langrell\*, Michael J Edney, Grain Research Laboratory,
Canadian Grain Commission, Winnipeg, Canada, William G Legge, Brandon
Research Station, Agriculture and Agri-Foods Canada, Brandon, Canada and
Brian G Rossnagel, Crop Development Centre, University of Saskatchewan,
Saskatoon, Canada

\*Corresponding author: (204) 983-6154,
<dennis.langrell@grainscanada.gc.ca>

Zinc is known in the brewing industry for its stimulative effect upon
fermentation rate, based upon its function as a cofactor for several
enzymes involved in carbohydrate metabolism. It is also essential for
non-yeast enzymes involved in nitrogen metabolism such as L-glutamate
dehydrogenase and carboxypeptidase. Studies have shown that higher
levels of zinc can increase utilization of certain amino acids during
fermentation resulting in a better attenuated wort. Zinc levels are
naturally elevated in worts made from low-phytate barley malt as less
mineral is chelated by phytate and removed with the spent grain.

Effects of the low phytate trait on wort zinc levels and the use of
amino acids during fermentation was investigated with eight samples from
two separate low phytate populations, one based on AC Metcalfe and the
second on Harrington. The AC Metcalfe sample set included the two
parents, AC Metcalfe and a low phytate line, along with two bulked
segregates from the progeny, one bulk with normal phytate
characteristics and the other with reduced phytate characteristics. The
second set contained the parent Harrington and three low phytate lines.
Malted samples were brewed with the Canadian Malting Barley Technical
Centre\'s microbrewery and fermented in tall cylinder (1.5 L). Free
amino acids in wort and fermented wort were measured with the Waters®
UPLC system and the AccuTag Ultra® Amino Acid Analysis application. Zinc
and magnesium levels were also monitored in worts.

The low phytate samples showed acceptable malt quality but quality did
vary among the samples tested. All the low-phytate lines had
significantly higher levels of zinc and magnesium which resulted in
better fermentabilities. Low-phytate worts from the AC Metcalfe cross
used more amino acids than the normal phytate worts. There was a similar
tendency with the Harrington low-phytate lines but results were not as
consistent.

**A new high-throughput screening method for measuring lipoxygenase in
barley seed.**

Yin Li and Paul Schwarz\*. Department of Plant Sciences, North Dakota
State University. Fargo, North Dakota 58105-5051.

\*Corresponding author Paul Schwarz 701-231-7732 <Paul.Schwarz@ndsu.edu>

Lipoxygenase is regarded as an undesirable enzyme that affects the
flavor stability of beer, due to the enzymatic oxidation of linoleic
acid to yield trans-2-nonenal by LOX pathway. Elimination of
lipoxygenase from barley and malt will therefore greatly reduce the
formation of trans-2-nonenal, resulting in significantly increasing the
flavor stability of beer. Barley breeders are trying to identify barley
germplasm that lacks of lipoxygenase. The major obstacle is to set up a
fast and reliable lipoxygenase activity assay method. However,
lipoxygenase was very difficult to achieve high-throughput screening as
the reaction products (lipid hydroperoxides) are extremely unstable. In
this research work, we established a new high-throughput screening
method for lipoxygenase activity assay, which was based on the
determination of lipid hydroperoxides by ferrous oxidation-xylenol
orange (FOX) assay. The new method is able to measure over 100 samples
per day. We feel it will be of great interest to the barley breeders,
maltsters, and brewers.

**Study of the effects of Pre-harvest Sprouting on the Storability and**

**Malting quality of AC Metcalfe, CDC Kendall and CDC Copeland Barleys**

Yueshu Li\*, Rob McCaig, Aleks Egi, Ken Sawatzky and Deye Tian, Canadian
Malting Barley Technical Centre, 1365-303 Main Street, Winnipeg,
Manitoba, Canada R3C 3G7

\*Corresponding author: 204-984-0561, <yli@cmbtc.com>

Variations in germination and malting behaviors of AC Metcalfe, CDC
Kendall and CDC Copeland barley samples during storage were examined at
CMBTC. These barley samples have suffered different degrees of
pre-harvest sprouting damage (PHSD) at harvest, and were stored under
three different storage conditions during the course of this study.
During storage PHSD barley samples showed significant changes in
germination energy and water sensitivity than the sound barley (0%
PHSD). The higher the degree of PHSD the more variations in germination
energy were recorded. Although all the barley samples exhibited
gradually increase in water sensitivity with storage duration, the
samples with a higher degree of PHSD exhibited more changes than the
samples with a lower degree of PHSD. Barley samples kept at room
temperature showed more variations than the samples kept at a lower
storage temperature. Varietal difference in germination energy, water
sensitivity and their response to the storage condition were also
observed. In the micromalting trials, at steep barley samples with
higher degrees of PHSD showed a higher water uptake rate and lower
chitting rates than the sound barley samples. Variations in the chitting
rate showed a similar pattern as germination energy, barley samples with
a high degree of PHSD and being stored at a higher temperature exhibited
lower chitting rates. Some varietal differences in water uptake and
chitting variations were also recorded. Micromalting trial results
suggested that germination energy, water sensitivity, chitting rate,
friability, enzyme level and beta-glucan content were all sensitive to
PHSD and storage conditions. Changes in malt quality could be related to
characteristics of the samples prior to storage, subsequent changes in
barley quality during storage, and the interactions between pre-storage
barley quality and storage conditions. Both barley pre-harvest condition
and storage conditions largely determine the changes in germination and
overall maltability, as well as the resultant malt quality of the
barley.

**Nutritional and functional properties of whole grain barley bagels**

C.Lukie\*, L. Malcolmson, A. Sarkar, and E. Sopiwnyk. Canadian
International Grains Institute, 1000-303 Main St., Winnipeg, MB, R3C
3G7, CANADA.

Corresponding Author: C. Lukie 204-984-1063 <clukie@cigi.ca>,

Interest in incorporating whole grains into the diet of North American
consumers has increased considerably due to reported health benefits
associated with their consumption. Barley is an underutilized grain in
food applications despite the recent health claim that is permitted for
foods containing barley and beta glucan from barley sources. Hulless
barley varieties have been developed which have an advantage in milling
since the hull is naturally removed prior to milling. This study was
undertaken to determine the functionality of whole grain barley flour
made from the Canadian hulless barley variety CDC McGwire in a bagel
application. Varying levels of whole grain barley flour were blended
with wheat flour to determine dough and end product quality. Water
absorption, volume, firmness, crumb structure and flavor were assessed.
Nutritional analysis was also determined based on reported nutrient
values. Results indicated that it was possible to create a whole grain
barley bagel with good end-product quality, and that a suitable blend of
whole grain barley and wheat achieved the soluble fiber health claim.

**Screening for bird cherry-oat aphid resistance in barley**

Do Mornhinweg USDA-ARS, 1301 N. Western, Stillwater, OK 74075 and Harold
Bockelman, USDA-ARS, PO Box 386, 1691 S. 2700 W, Aberdeen, ID 83210

\*Corresponding author: 405-624-4141, <Do.Mornhinweg@ars.usda.gov>

Bird cherry-oat aphid (BCOA), *Rhopalosiphum padi* (L.), has been
reported to cause yield loss in small grains both through its role as an
efficient vector of the PAV strain of Barley yellow dwarf virus (BYDV)
and by actual feeding damage to winter and spring small grains by
aviruliferous BCOAs. Barley accessions have been reported to have BCOA
resistance based on the antibiotic effect of seedlings on the aphids.
Whether this antibiosis translates to resistance in terms of grain yield
has yet to be shown. Screening for BCOA resistance at the seedling stage
has been difficult due to lack of visual symptoms on seedlings infested
with BCOA using traditional greenhouse screening methods. In an attempt
to develop a seedling screening technique for BCOA many variables were
evaluated including flat type, soil type, infestation date, infestation
rate, and screening conditions, (temperature and day length). In 2005,
78 barleys, reported to be antibiotic to BCOA, were screened with
aviruliferous BCOA using traditional seedling screening methods under
high temperature and long days and compared to non-infested controls.
Seedlings were rated on a newly defined visual scale of 1 to 7 (1=
resistant and 7= dead). Potential resistant and susceptible checks were
identified. A replicated (2X) screening of a 960 accession subset of the
Barley Core Collection was conducted using this technique. Seedlings
from 284 accessions survived screening and were transplanted to pots in
the greenhouse. Based on seedling survival percentages, the rating scale
appeared to be valid. Seedlings from the surviving accessions were
screened again in 2007 and an identical set of non-infested controls was
grown. Surviving seedlings and their respective non-infested controls
were rated, rescued, and transplanted to pots side by side in the
greenhouse. Plant height, yield and yield components were measured to
validate the rating scale.

**An overview of the barley coordinated agricultural project**

Gary J. Muehlbauer, Department of Agronomy and Plant Genetics,
University of Minnesota, St. Paul, MN55108.

\(612\) 625-6228 <muehl003@umn.edu>

Barley geneticists and breeders have been successful in identifying
hundreds of QTL that explain variation for yield, disease resistance,
malting quality, and other agronomic traits. However, various reasons
preclude the use of these QTL within breeding programs. The overall goal
of the barley CAP is to identify QTL within breeding program germplasm
and directly utilize the QTL in breeding efforts. The barley coordinated
agricultural project (CAP; [www.barleycap.org]{.underline}) is a
community-based project focused on integrating genomics into barley
breeding programs. Twenty-nine scientists from 19 institutions are
participating in the project. An international collaboration composed of
the Scottish Crop Research Institute, the German Institute of Plant
Genetics and Crop Plant Research, NSF funding to Timothy Close
(University of California, Riverside), and the barley CAP developed a
3,000 marker SNP genetic map and genotyping platform. The barley CAP QTL
discovery platform is based on ten U.S. barley-breeding programs each
submitting 96 F4 or more advanced breeding lines each year of the
project. Thus, over the four years of the project 3,840 lines will be
submitted. The allele at approximately 3,000 SNP loci and phenotypic
data on 40 traits will be collected on the breeding lines. All genotype
and phenotype data will be stored in The Hordeum Toolbox database. The
combined genotype and trait data provide the opportunity to use
association genetics approaches to identify loci that control important
traits. Results of some of the early association genetics analysis are
promising.

**Variation, causes, and significance of grain hardness in barley for
food**

Sindhu Nair, Byung-Kee Baik, and Steve Ullrich\*, Dept. of Crop and Soil
Sciences,WashingtonStateUniversity,Pullman,WA99164-6420.

\* Corresponding author: 509-335-4936, <Ullrich@wsu.edu>

There is increasing interest in nutritional benefits of consuming barley
food products, but experience in breeding of appropriate barley
cultivars and their processing for food uses is limited. Kernel hardness
(KH) of barley may influence post-harvest handling; pearling, rolling,
and milling; flour particle size distribution; and end use product
quality. There is limited understanding of genotypic variation and
environmental influence on barley KH, the biochemical and physical basis
of KH, and its significance in food processing. The objectives of this
study were to determine the effects of genotype (G) and environment (E)
on barley KH and the associations of KH with other kernel and food
processing traits. De-hulled grains of 959 diverse breeding lines
contributed by ten breeding programs in the USA as part of the
USDA-funded Barley CAP were evaluated for KH using the single kernel
characterization system (SKCS). Overall, KH varied from 30 to 92 units.
Hulled and hulless types ranged from 30 to 92 and 42 to 91,
respectively. Mean KH was 71 for winter and 62 for spring types. Overall
mean kernel weight (KW) and kernel diameter (KD) ranged from 25 to 54 mg
and 1.7 to 2.9 mm, respectively. Hulled lines exhibited wider variation
in KW and KD than hulless lines. Spring and winter types were similar in
KD distribution. The proportion of hull, determined by 80 sec abrasion,
ranged from 10 to 21%. G and E effects on KH were determined using 14
lines grown with 3 replications at 12 locations. G, E, and G x E were
significant with genotype playing the greatest role. Ten barley lines of
varying KH (30 - 91) were selected to determine associations of KH with
other kernel and food processing traits. KH showed no association with
kernel weight, diameter, density, crease dimensions, protein and
β-glucan contents, water absorption, and cooked barley texture. KH
negatively correlated with pearling rate (r = -0.87\*\*\*) and grain
vitreousness (r = -0.82\*\*) as measured by kernel brightness (L\*). KH
positively correlated with flour particles \>106 µm (r = 0.93\*\*\*) and
percent starch damage (r = 0.93\*\*\*).

**Waxy Barley: N Applications for Yield, Beta-glucan, and Protein**

O. Steven Norberg\*, Oregon State University, Malheur County Extension
Office; Brad Brown, University of Idaho, SW Idaho Research & Extension
Center, Parma; Clint Shock, Oregon State, Univ., Malheur Experiment
Station; Andrew Ross, Pat Hayes, and Juan Rey, Oregon State University,
Crop and Soil Science Dept. Corvallis, OR.

\*Corresponding author 541-881-1417, <steve.norberg@oregonstate.edu>

Nitrogen fertilizer (N) management was evaluated for growing irrigated
waxy barley for higher protein and beta-glucan soluble fiber content. A
local company has proposed the building of a barley fractionation plant
to capitalize on these value-added traits. Salute and Merlin, two spring
waxy barley cultivars, were fall-planted to compare yield and quality
under different N treatments applied in late winter and at heading and
to evaluate ethephon to reduce lodging. Fairly normal winter weather in
the Treasure Valley reduced stands by 60 to 70% in 2006 and required
replanting in the spring of 2007. In 2006, yield of Merlin and Salute
were not different and averaged 5.4 Mg ha-1. In 2007, Merlin yielded 6.6
Mg ha-1 whereas, Salute only yielded 4.5 Mg ha-1 and lodged heavily. In
2007, Salute had 30% lodging even where no late winter nitrogen was
applied and lodging increased to 98% with only 67 kg ha-1 of N. In 2007,
ethephon at the full labeled rate increased Salute yield by 1.3 Mg ha-1
and reduced lodging by 28%. Grain protein was influenced by year,
variety, N rate, N at heading and ethephon application. Grain protein
was 2.2 percent higher in 2006 than 2007. Merlin contained 0.8 percent
more protein than Salute. Increasing the N rate from 0 to 180 kg ha-1,
increased grain protein from 10.0 to 12.9 percent. The application of 45
kg ha-1 N at heading consistently increased protein 1 percent. Ethephon
decreased grain protein content by 0.4 percent. Flag leaf N at heading
was strongly related to grain protein (R2= 0.79). Ethephon influence on
beta-glucan was inconsistent over years. Averaged over years and
varieties, 45 kg ha-1 N at heading increased the beta-glucan from 5.4 to
5.7%.

**Prediction of Deoxynivalenol (DON) content in grain using Near
Infrared Reflectance Spectroscopy (NIRS).**

Lori Oatway\*, James Helm and Kequan Xi. Alberta Agriculture and Rural
Development, Field Crop Development Centre, 5030 - 50th Street, Lacombe,
AB Canada.

\*Corresponding author: 403-782-8048, <lori.oatway@gov.ab.ca>

As long as current agricultural practices cannot prevent Fusarium
infection in small grains, deoxynivalenol (DON) will continue to be a
critical issue in animal and human health. The purpose of this project
was to determine if near infrared reflectance spectroscopy (NIRS) can
predict DON concentrations in cereal grain. First, the NIRS absorption
spectrum of DON was isolated and used to develop a baseline calibration
using specific wavelength ranges and standard samples developed from
commercial flour and pure DON. The second part of this project
transferred the baseline calibration to naturally-infected samples of
ground wheat and barley. The best equation developed had a coefficient
of determination (R2) of 0.90, standard error of calibration (SEC) of
0.64 ppm, and standard error of cross validation (SECV) of 0.72 ppm. The
equations developed in this study demonstrate that NIRS can effectively
predict DON content in wheat and barley.

**Association mapping of malt quality QTL in the U of M barley breeding
program: Detection, validation, and breeding**

C.A. Powers1\*, Paul Schwarz2, Yin Li 2, K.P. Smith1. 1-Department of
Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall,
1991 Upper Buford Circle, St. Paul MN 55108. 2- Department of Plant
Sciences, Harris 201,North Dakota State University, Fargo ND 58105.

\*Corresponding author: 612-625-3151, <power134@umn.edu>

Recently published association mapping studies have focused on germplasm
collections, designed populations or varieties entered in national and
regional trials. Association mapping within a breeding program has the
potential to accelerate the translation of newly acquired genetic
information to application in breeding. We have used 182 lines from the
University of Minnesota barley breeding program to conduct association
mapping for an array of malting quality traits. Preliminary results
detected 13 QTL for eight traits (malt extract, alpha-amylase activity,
diastatic power, residual beta-glucanase activity, wort protein, wort
color, barley protein, and percent plump). Locations of the QTL were on
chromosomes 2H, 4H, 5H, and 6H. Two QTL regions were associated with
more than one trait. Validation using near-isogenic lines (NIL) has been
initiated using Midwest breeding lines that are heterozygous for target
QTL. To further characterize QTL, we assessed the pattern of linkage
disequilibrium (LD) at the target QTL, identified haplotype blocks, and
estimated the effects of QTL alleles. For example, we detected one QTL
for barley protein on chromosome 4H that is contained within a 2 cM
block of LD that includes nine markers. When considering only the seven
markers significantly associated with protein there are four haplotypes.
The least frequent haplotype (1.9%) contains the desirable allele that
reduces grain protein. We are now in a position to use marker assisted
selection to increase the frequency of this and other useful alleles in
our breeding program to develop improved malting quality varieties.

**Distribution and Diversity of Russian Wheat Aphid (Homoptera:
Aphididae) Biotypes in North America**

Gary J. Puterka\* and Dolores W. Mornhinweg, USDA Agricultural Research
Service, Plant Science Research Laboratory, Stillwater, OK 74075

\*Corresponding author: 405-533-1050, <gary.puterka@ars.usda.gov>

Wheat with Russian wheat aphid (RWA) resistance based on the *Dn4* gene
has been important in managing RWA since 1994. Currently, there are
eight biotypes (RWA1 - RWA5) of this aphid that have been described
based on their ability to differentially damage RWA resistance genes in
wheat. RWA2, RWA4 and RWA5 are of great concern because they can kill
wheat with *Dn4* resistance. In 2005, 365 RWA clone colonies were made
from collections taken from 98 fields of wheat or barley in Oklahoma,
Texas, New Mexico, Colorado, Kansas, Nebraska, and Wyoming to determine
their biotypic status. The biotype of each clone was determined through
its ability to differentially damage four resistant and two susceptible
wheat entries in two phases of screening. Only two biotypes, RWA1 and
RWA2, were identified in this study. The biotype composition across all
collection sites was 27.2% RWA1 and 72.8% RWA2. RWA biotype frequency by
state indicated that RWA2 was the predominant biotype and composed 73 -
95% of the biotype complex in Texas, Oklahoma, Colorado and Wyoming. Our
study indicated that RWA2 is widely distributed and has rapidly
dominated the biotype complex in wheat and barley within its primary
range from Texas to Wyoming. Wheat with the *Dn4* resistance gene will
have little value in managing RWA in the United States, based on the
predominance of RWA2. However, the two main sources of resistance in
barley, STARS 9301B and 9577B, remain resistant to the eight known RWA
biotypes.

**Fluorescence microplate readers as an alternative to flow injection
analysis for determination of wort beta-glucan.**

Mark R. Schmitt\* and Allen D. Budde. USDA Agricultural Research
Service, Cereal Crops Research Unit, 502 Walnut Street, Madison, WI
53726. USA.

\*Corresponding author (608) 262-4480 <mark.schmitt@ars.usda.gov>

Wort beta-glucan concentration is a critical malting quality parameter
used to identify and avoid potential brewhouse filtration problems. ASBC
method Wort-18 is widely used in malt analysis laboratories and
brewhouses to measure wort beta-glucan. However, the chemistry
underlying the method is suitable for other instrumentation, such as
fluorescence microplate readers. Fluorescent microplate readers are
significantly less expensive than commercial FIA systems and are widely
available in research laboratories. The microplate implementation of the
Calcofluor/beta-glucan method presented here is simple to execute, and
offers several advantages due to its high throughput, flexibility, and
low sample volume requirement. The latter consideration makes it well
suited to analysis of worts from limited-availability samples, such as
those from early-generation breeding lines.

**Let\'s get small: Miniaturized malt quality analysis for fun and
profit.**

Mark R. Schmitt\* and Allen D. Budde. USDA ARS Cereal Crops Research
Unit, 502 Walnut Street, Madison, WI 53726.

\*Corresponding author (608) 262-4480 <mark.schmitt@ars.usda.gov>

Most common laboratory-scale micromalting and malt analysis procedures
are indeed micro-scaled compared to commercial-scale malting (the CCRU
standard 170 g malting is approximately 106 times smaller than a 6,000
bu Saladin box production malting run). While these amounts of grain are
insignificant for a malthouse or brewery where railcar quantities are
normally handled, the quantities needed for the micromalting and
standard analysis procedures may be problematic for both research and
breeding programs. The requirement for \>100 g of seed for
malting/analysis effectively precludes testing for important malting
quality attributes until relatively late in a breeding program, even
though meeting malting quality standards is one of the most critical
selection criteria. This means that many lines with inferior malting
quality must be carried through several generations before sufficient
grain is available for even a first round of malt QA testing that would
identify those lines with malting quality shortcomings, so that they
could be eliminated from the breeding program. Similarly, it becomes
much more difficult to analyze mapping and other special populations if
seed increases are needed to produce the \>100 gm of seed needed for
standard QA tests for each line of interest. Fortunately, it has
recently become possible to adapt traditional micromalting and malt
analysis procedures to much smaller scales, reducing the quantities of
grain needed to generate a malt quality profile similar to those from
traditional methods. The availability of the reduced-quantity malt
quality methods have greatly simplified analysis of genetically
interesting populations and could facilitate earlier-generation analysis
of malting quality in breeding programs when fully implemented. In
addition, several labs globally have adapted a number of related
research procedures to small-scale/high-throughput formats, facilitating
studies on basic research questions relating to modification of barley
carbohydrate, protein, and cell wall reserves. Examples of the modified
malting, mashing, and analytical procedures will be presented.

**Barley and oat grain and malt beta-glucan content measured by
Calcofluor fluorescence in a microplate assay.**

Mark R. Schmitt\* and Mitchell Wise. USDA Agricultural Research Service,
502 Walnut Street, Madison, WI 53726.

\*Corresponding author (608) 262-4480 <mark.schmitt@ars.usda.gov>

Beta-glucan levels in grains, particularly barley and oats, are
receiving increased interest in part due their recognized benefits to
human health. While a number of methods to determine grain beta-glucan
levels are available, each suffers from significant drawbacks for
routine implementation. Adaptation of a Calcofluor fluorescence method
to detection by a microplate fluorimeter results in a simple mechanism
for measuring beta-glucan, using inexpensive reagents, and affordable,
readily available instrumentation.

**Survey of Barley Producers in Idaho, Montana and North Dakota**

Paul Schwarz. Institute of Barley and Malt Sciences. North Dakota State
University. Fargo, ND 58105

\*Corresponding author: 701-231-7732, <Paul.Schwarz@ndsu.edu>

The supply of domestic malting barley in the USA is a serious concern,
and in fact, 2006 production was the lowest since 1933. In order to
address satisfaction and concerns with malting barley as a crop, the
Institute of Barley and Malt Sciences conducted a survey of 5000 barley
growers in Idaho, Montana, and North Dakota. The rate of response to the
survey was 32, 29, and 26% in Idaho, Montana, and North Dakota
respectively. Slightly more than 1400 responses were received. The
twelve question survey focused on production/economic issues and
informational needs. Production/economic questions focused on the past
10 years, and targeted factors influencing a producer\'s decision to
grow barley, the satisfaction or rank of barley relative to other crops
produced, and rate of barley acceptance . Informational questions
addressed the type of information that is of value to barley producers
and their current or desired sources of the information.

**Association mapping of Fusarium head blight QTL using contemporary
barley breeding germplasm**

Kevin P. Smith1\*, Jon Massman1, Blake Cooper2, Rich Horsley3, Stephen
Neate3, Ruth Dill-Macky4, Shiaoman Chao5, Yanhong Dong4, and Paul
Schwarz3

1University of Minnesota, Department of Agronomy and Plant Genetics

2Busch Agricultural Resources, Inc.

3North Dakota State University, Department of Plant Sciences

4University of Minnesota, Department of Plant Pathology

5USDA-ARS Biosciences Research Lab, Fargo, ND

\*Corresponding author: 612 624-1211, email: <smith376@umn.edu>

The serious impact of Fusarium head blight (FHB) on barley production in
the Midwest has prompted a substantial research effort to map
quantitative trait loci (QTL) that could be exploited in marker assisted
breeding. Previously described resistance QTL (identified in wide,
bi-parental mapping studies) are often associated with negative
agronomic traits such as late heading and taller plants, thus reducing
their overall utility. As part of the USDA-funded Barley Coordinated
Agricultural Project (CAP), we are using association mapping to identify
QTL segregating in contemporary breeding lines which should be free of
such associations. 768 breeding lines from four barley breeding programs
were each evaluated for resistance in four experiments in 2006 and 2007.
The lines were planted in a randomized complete block design with two
replications, inoculated, and mist irrigated to encourage disease
development. Each line was genotyped using 1,536 single nucleotide
polymorphism (SNP) markers, and QTL were mapped using a mixed-model
approach. Phenotypic variation among lines for disease severity was
significant (p\<0.0001) , but skewed toward resistant. Linkage
disequilibrium extended more than 10cM on average, indicating
association mapping should be feasible with the available marker
density. Population structure was accounted for using molecular marker
and pedigree data. Multiple QTL with generally small effects (R2 \< 5%)
were identified. Fewer QTL were identified in analyses using only
two-rowed breeding lines compared to six-rowed lines. Overall eight QTL
for DON and four QTL FHB were reproducibly identified. These loci should
be useful targets for immediate implementation of marker assisted
selection to improve disease resistance.

**Progress towards predictive models for Fusarium Head Blight and DON in
barley.**

J. Stein\*, K. Bondalapati, L. Osborne - Plant Science Department, South
Dakota State University, Brookings, SD; S. Neate - Department of Plant
Pathology, North Dakota State University, Fargo, ND, and C.
Hollingsworth -University of Minnesota Research and Outreach Center,
Crookston, MN.

\* Corresponding author, Ph: (605) 688-5540, E-mail:
<jeff.stein@sdstate.edu>

Fusarium head blight (FHB), caused by the fungus *Gibberella zeae*
(anamorph: *Fusarium graminearum*), continues to be a serious problem
for barley producers in the U.S. Northern Great Plains and elsewhere.
*G. zeae* can cause direct economic loss through a reduction in grain
yield and it also produces mycotoxins that can impact the marketability
of a crop, e.g. deoxynivalenol (DON). Management of FHB is accomplished
with agronomic practices that limit in-field inoculum (e.g. rotation)
and through the application of fungicides. The timing of application can
be critical and therefore a need exists for a risk-advisory system that
growers could use to make management decisions. The objective of this
research was to develop model(s) for such a system that predict FHB
and/or DON based on weather conditions. Varieties of regionally adapted
barley (both 2- and 6-row types) were grown at multiple locations in the
Northern Great Plains during the 2005-8 growing seasons. Crop stage was
monitored regularly and no additional inoculum was applied. The
incidence and severity of FHB was measured and environmental variables
were recorded. Correlation analysis was conducted to identify the
variables that were associated with high disease and/or DON events and
then logistic regression was used to develop predictive models.

Simple weather variables that explained general trends (e.g. mean hourly
temperature) tended to have the highest correlation coefficients and
were most predictive of high FHB/DON instances. In general, high levels
of disease and DON occurred at a location when the mean hourly
temperature and relatively humidity were both greater than 22C and 75%,
respectively, for the 9 days prior to full head emergence. A preliminary
model was developed that combined these variables. This model had true
positive and negative rates of \~90% when tested with the 2005-7 data
sets and was able to predict low disease in all of the 2008South Dakota
testing locations. Further analysis of model accuracy is ongoing.

**Identification of a putative new barley leaf rust resistance gene**

Yongliang Sun and Stephen M. Neate\*

Department of Plant Pathology, North Dakota State University, Fargo USA

\*Corresponding Author: 701-231-7078, <stephen.neate@ndsu.edu>

Resistance is the preferred means of controlling leaf rust of barley
caused by *Puccinia hordei* G. Otth. However, changing virulence in *P.
hordei* has rendered ineffective many of the known resistance genes. In
this study, isolates \`Race 8\', \`90-3\', \'90-15\', \`89-3\', and
\`Neth 202\' of *P. hordei* were used to differentiate resistance genes
in 82 selected barley lines. Putative new resistance was identified in
barley line \`C2-02-134-2-2\' and separated from *Rph15* also known to
be in that line. Based on disease reaction when challenged with isolate
\`Race 8\', the F2 population of a cross between \`C2-02-134-2-2\' and a
susceptible line \`ZA47\', segregated into a 15:1 resistant to
susceptible ratio (χ2=0.853) indicating the presence of more than one
gene. In the F2 generation, the *Rph15* phenotype (00;) separated from a
second resistance gene phenotype (0;12-). To isolate the gene which gave
the (0;12-) phenotype from *Rph15*, the 10 F2 plants bearing the (0;12-)
phenotype were transplanted and selfed, and the F2:3 families were
screened for homogeneity of disease reaction. To determine inheritance
and to undertake gene mapping using diversity array technology (DArT) a
new cross was made between \`Bowman\' and a plant from a homogeneous
family that showed the (0;12-) phenotype. The putative new gene was
mapped on barley chromosome 7H and when inoculated with a selected set
of *P. hordei* races showed different phenotypic reactions from *Rph3*
and *Rph19* known to be on the same chromosome. Allelism studies with
*Rph3* and *Rph19* are in progress.

**Barley Feed Quality - Is It Consistent Across Species?**

Mary Lou Swift\*1, James Helm1, Tim McAllister2, Fred Silversides3, and
Ruurd Zijlstra4. 1Field Crop Development Center, Alberta Agriculture and
Rural Development, 5030-50th Street, Lacombe, Alberta, Canada. T4L1W8. 2
Research Centre, Agriculture and Agri-food Canada, Lethbridge, Alberta.
T1J 4B1. 3Pacific Agri-food Research Centre, Agriculture and Agri-food
Canada, POB 1000, Agassiz, British Columbia, Canada. V0M 1A0;
4Department of Agricultural, Food and Nutritional Science, University of
Alberta, Edmonton, Alberta, Canada T6G 2P5.

\*Corresponding Author: 403-782-8693; <Mary-lou.Swift@gov.ab.ca>

Barley grain is primarily included in the diet of farm animals as a
source of digestible energy. Regardless of species fed, there is
variation in the feeding value of barley due to genetic and
environmental factors. However, there is little information published in
the scientific literature comparing the feeding value for different
livestock classes of a standard set of barley samples. The Field Crop
Development Centre together with university, government and industry
collaborators conducted a three-year study to collect data regarding the
nutritional value of barley for poultry, ruminants and swine. Fifty
samples of hulled barley were evaluated for ruminants using in-vitro gas
production, for swine using in-vitro 3-stage enzymatic digestion, and
for poultry using an animal bioassay. Data was entered into JMP Version
4 (SAS Institute Inc.) and correlation coefficients (r) calculated to
ascertain the relationships between the various measurements of feed
value for ruminant and swine and for swine and poultry.

The best relationship between ruminant and swine, as determined by
highest r value, was that of total ruminal volatile fatty acid
production (24h) and swine DE content (r=0.33). The relationship between
ruminal 24 h starch disappearance and swine DE was 0.12 and between
protein disappearance and DE was 0.18. Relationships between swine DE
values and poultry AME values were dependent on whether exogenous enzyme
had been added to the diet. Without enzyme, the relationship was
negative in nature (r= -0.21). With the addition of enzyme a positive
relationship (r = 0.14) was found. However, the relationship between
swine DE content and poultry performance was negative in nature,
regardless of enzyme addition. For example, the relationship between
swine DE and feed intake was -0.51 without enzyme and -0.22 with enzyme.
Similarly, r values for swine DE and average daily gain of broilers was
-0.47 and -0.09, without and with enzyme, respectively.

In summary, data from this study would indicate that selection of a
hulled barley variety based on higher swine DE content may result in
little or no improvement in the feeding value of that barley for the
ruminant animal. In addition, the selection of the same hulled barley
could well result in decreased broiler performance in terms of feed
intake and average daily gain. This analysis would indicate that the
design of plant breeding programs to enhance the feeding value of hulled
barley should incorporate variety evaluation across species. Further
study of the genetic linkages of these feed quality traits is needed.

**Expression analysis of ethylene biosynthesis and receptor genes from
barley embryo and tissue culture**

Neerja Tyagi and Lynn S. Dahleen\*. Plant Sciences Dept., North Dakota
State University and USDA Agricultural Research Service, Cereal Crops
Research Unit, 1307 18th St N, Fargo, ND 58105

\*Corresponding author: 701-239-1384, <lynn.dahleen@ars.usda.gov>

Ethylene affects regeneration of green plants from barley tissue
culture. With the availability of the HarvEST barley database and barley
GeneChip, genome-wide expression studies have focused on differential
development between Morex and Golden Promise at various stages of plant
growth. The data from these studies are available from the Barley Gene
Atlas and provide an excellent source for datamining genes of interest.
We used ethylene biosynthesis genes 1-aminocyclopropane-l-carboxylic
acid synthase (ACS) and ACC oxidase (ACO), and ethylene receptor 1
(ETR1) as search criteria and selected the respective unigenes and their
probes from HarvEST. The probes were used to examine the expression
results from embryo, coleoptile and radicle tissue in the Barley Gene
Atlas. The consensus sequences from a set of same unigenes as above were
used to design primers that were tested on RNA (cDNA) extracted from
Morex and Golden Promise at various tissue culture stages. The results
from datamining and cDNA experiments were compared. The different probes
from same unigene gave variable expressions in the two cultivars. The
cDNA experiment indicated that ACS-6923 was constitutively expressed in
both cultivars, while ACS-13017 and ACS-1108 showed differential
expression. Similar results were seen for ACO. The unigenes ACO-1780 and
ACO-1786 tested in Morex were differentially expressed in different
stages of tissue culture. In the Barley Atlas experiment, ACO-1781 was
the most differentially expressed ACO between the cultivars. The
expression of ACO-1784 varied considerably between tissues; 38% higher
in Morex embryos, 90% higher in Morex coleoptiles, but almost three
times higher in Golden Promise radicle tissue. cDNA expression of ETR1
was not studied and the data from Barley Gene Atlas indicates
constitutive expression. The dataming expression studies confirm our
findings but also show some interesting differences as the same unigenes
are represented by different probes and more than one probe exists for
some unigenes. In most cases the expression in Morex was higher than
Golden Promise, sometimes by as much as 90%. This variation in
expression could contribute to the differential performance of these
cultivars in tissue culture and can be used to modify the expression of
these genes to achieve higher regeneration.

**Greenhouse and Field Demonstration of Microbial Suppression of
Fusarium Head Blight in Barley.**

J.E. Van Cauwenberge\*1, Schisler, D.A. 1, Cooper, D.2, Smith, K. P.3
1Crop Bioprotection Research Unit, National Center for Agricultural
Utilization Research, Agricultural Research Service, United States
Department of Agriculture, Peoria, Il. 2Busch Agricultural Resources,
Inc., Fort Collins, Co. 3Department of Agronomy and Plant Genetics,
University of Minnesota, St. Paul, Mn.

\*Corresponding author: (309) 681-6011,
<jim.vancauwenberge@ars.usda.gov>

Fusarium head blight (FHB) is a disease of wheat and barley responsible
for extensive losses in quality and yield. The primary causative agent
for FHB is *Gibberella zeae* (anamorph = *Fusarium graminearum)* which
initially infects spikes to produce dark brown water soaked spots on
glumes of florets and ultimately can cause thin blighted kernels,
reduced test weights, and reduced grain quality. To determine the
feasibility of reducing FHB on barley using microbial antagonists, seven
strains of gram positive bacteria and yeasts previously described as
suppressive to FHB on wheat were examined. After production in liquid
culture, antagonists were sprayed onto barley heads at anthesis in both
greenhouse and field trials. Lacey and Tradition, six-rowed malting
varieties with high yield, good lodging resistance and kernel plumpness,
were used in all trials. In greenhouse studies, suspensions of
*Gibberella zeae* conidia were applied onto heads immediately after
antagonist suspensions. In field trials *Gibberella zeae* was grown on
cracked corn then broadcast over the test plot two weeks prior to
anthesis and application of microbial treatments. In at least one set of
duplicated greenhouse experiments, five microbial strains reduced FHB by
25-84% on Tradition and four strains reduced FHB by 52-71% on Lacey. In
field trials, four microbial strains reduced FHB by 10-23% on Tradition
while one strain reduced FHB by 17% on Lacey. Strain efficacy in the
greenhouse was not always predictive of field performance. Further
research to evaluate the potential of including microbial antagonists in
the integrated management of FHB on barley is justified.

**β-Amylase activity and thermostability in wild and cultivated barleys
with different *Bmy1* intron III alleles**

Marcus A. Vinje1, Stanley H. Duke1, and Cynthia A. Henson1, 2\*

1University of Wisconsin-Madison, Department of Agronomy, 2USDA-ARS,
Cereal Crops Research Unit

\*Corresponding author: 608-262-0377, <Cynthia.henson@ars.usda.gov>

The third intron of barley (*Hordeum vulgare* L.) β-amylase 1 (*Bmy1*)
is extremely polymorphic. The use of specific insertion/deletions
(indels), in the third intron as selective markers for cultivar
development, has been suggested based on associations with β-amylase
activity and thermostability. The third intron of *Bmy1* in 40 barley
accessions was sequenced and four alleles (*Bmy1.a*, *Bmy1.b*, *Bmy1.c*,
and *Bmy1.d*) were identified based on indels of 126-bp, 38-bp, 11-bp,
and 21-bp. β-Amylase activity and thermostability were assayed in 22
North American cultivars important to the malting and brewing community
and 12 wild barley accessions, which are a rich source of genetic
diversity. The cultivars were found to have the *Bmy1.a* and *Bmy1.b*
alleles with β-amylase activity ranges of 946-1723 and 1443-2146 U/g
flour, respectively, and β-amylase thermostability ranges of 4.1-36 and
22.5-26.3% residual activity, respectively. There were significantly
different activities among cultivars carrying either allele, according
to Fisher\'s least significant difference (LSD) analysis. Cultivars
carrying the *Bmy1.a* allele also had significantly different
thermostabilities. The wild barleys were found to carry *Bmy1.a*,
*Bmy1.b*, and *Bmy1.c* alleles with β-amylase activity ranges of
668-1124, 908-1554, and 628-1629 U/g flour, respectively, and β-amylase
thermostabilities of 26.6-33.3, 20.4-27.7, and 23.2-49.1% residual
activity, respectively. LSD analysis revealed significantly different
activities in accessions carrying any of the intron alleles and
significantly different thermostabilities in accessions carrying the
*Bmy1.b* or *Bmy1.c* alleles. These data suggest that the use of the
*Bmy1* intron III alleles as a marker to predict and select for
β-amylase activity and/or thermostability is unreliable.

**Differential RNA expression of two barley β-amylase genes (*Bmy1* and
*Bmy2*) in developing grains and their association with β-amylase
activity**

Marcus A. Vinje1, David K. Willis3, Stanley H. Duke1, and Cynthia A.
Henson1, 2\*

1University of Wisconsin-Madison, Department of Agronomy, 2USDA-ARS,
Cereal Crops Research Unit, 3USDA-ARS, Vegetable Crops Research Unit

\*Corresponding author: 608-262-0377, <Cynthia.henson@ars.usda.gov>

RNA expression from the barley β-amylase1 (*Bmy1*) gene was determined
during seed development in four genotypes (Legacy, Harrington, Ashqelon,
and PI 296897). The *Bmy1* transcript amount in Legacy and Harrington
was not significantly different at 17, 19, or 21 days after anthesis
(DAA). Ashqelon *Bmy1* expression is around three-fold higher than
Legacy and Harrington at 17, 19, and 21 DAA. The *Bmy1* expression in PI
296897 is around 40-fold lower than Legacy and Harrington at 17 and 21
DAA and around 24-fold lower than Legacy and Harrington at 19 DAA. PI
296897 had over 100-fold lower *Bmy1* RNA levels at 17 and 21 DAA and
76-fold lower *Bmy1* expression at 19 DAA than Ashqelon. β-Amylase
activity was measured to determine if the expression levels were
comparable to activity. Harrington had 2.9, 2.6, and 2.1-fold lower
activity at 17, 19, and 21 DAA than Legacy even though their *Bmy1*
transcript levels were the same. The β-amylase activity levels of Legacy
and Harrington in mature grain were the same. The peak expression of
*Bmy1* in Harrington was not ascertained because the *Bmy1* expression
at 19 DAA was statistically the same as the *Bmy1* expression at 21 DAA.
The discrepancy between β-amylase activity in Harrington at 21 DAA and
at maturity indicated that *Bmy1* transcript levels may peak later or
*Bmy1* is expressed over a longer time period than occurs in Legacy
and/or other genotypes. Ashqelon had three-fold higher *Bmy1* expression
than Legacy and Harrington and had higher β-amylase activity. PI 296897
had higher β-amylase activity at all developmental time points and at
maturity than Legacy and Harrington despite having between 24 and
44-fold lower *Bmy1* transcript levels. This discrepancy led us to
determine the RNA levels of *Bmy2*, which is known to be expressed in
early seed development. *Bmy2* expression is very low in Legacy and
Harrington at 17, 19, and 21 DAA indicating that it probably is not
contributing significantly to the total β-amylase activity. *Bmy2*
transcript levels in Ashqelon were not significantly different from
Legacy or Harrington. *Bmy1* expression seems to be the major
contributor to β-amylase activity in the time points measured for
Legacy, Harrington, and Ashqelon. PI 296897 has between 3 and 11-fold
higher *Bmy2* expression at 17, 19, and 21 DAA than the other three
genotypes. These data lead us to propose that the expression of *Bmy2*
is contributing more β-amylase activity in PI 296897 by being expressed
later in seed development.

**Agronomic practices to improve winter hardiness of two-row winter malt
barley \`Charles\'.**

Juliet M. Windes1\* and Don E. Obert2. 1University of Idaho, Idaho
Falls, ID 83402. 2USDA-ARS, Aberdeen, ID, 83210.

\*Corresponding author: 208-529-8376, <jwindes@uidaho.edu>

Yield improvement of quality malt varieties is a priority goal for
barley breeders. Winter varieties offer a substantial improvement on
yield potential compared to spring types, and the release of
\`Charles\', the first two-row winter malt variety, could mean increased
yields with less irrigation than spring types. Limiting the adoption of
Charles is its susceptibility to winter kill. Planting methods were
investigated to improve winter survival. Four replications of Charles
were planted in a split-split plot design with \`Eight-Twelve,\' a
winter feed barley with better winter hardiness than Charles. Both
varieties were planted in four-row plots, either drilled conventionally
or planted in a 4-inch deep furrow created by shanks placed ahead of
double disks. Randomized within planting method were six seeding rates,
varying from 200,000 seeds/A to 1.25 million seeds/A. Plots were planted
late, October 11, 2007, to increase potential for winter stress. Plots
were rated twice for spring stand, and data were collected for yield,
test weight, plumps and protein. Results show significant differences in
yield between varieties (P=0.0002), planting method (P\<0.0001), and
planting rate (P\<0.0001). There were significant differences in early
stand between varieties (P\<0.0001), planting method (P\<0.0001), and
planting rate (P\<0.0001), as well as in late stand between varieties
(P=0.0005), planting method (P\<0.0001), and planting rate (P\<0.0001).
Stand and yield of both varieties increased significantly when planted
in deep furrows. Averaged over variety and planting rate, conventionally
drilled barley yielded 58 bu/A and deep furrow-planted barley yielded
113 bu/A, and stand increased from 11 to 66%, respectively. With both
methods, significant increases in yield did not occur above the 400,000
seed/A planting rate. Over all planting rates, Charles yielded 7 bu/A
when conventionally drilled, and 84 bu/A when furrow-planted, while
Eight-Twelve yielded 109 bu/A and 141 bu/A, respectively. Significant
improvements in yield and stand can be achieved by deep-furrow planting,
but not as much or not at all by increasing seeding rate.

**Tocol Content of Barley CAP germplasm, Preliminary Results**

Mitchell L. Wise, USDA Agricultural Research Service, Cereal Crops
Research Unit, 502 Walnut St., Madison, WI 53726

608-262-4292, <mitchell.wise@ars.usda.gov>

Tocochromanols (tocols) is the collective term for vitamin E active
constituents found primarily in plants. These compounds have potent
anti-oxidant properties and are a recommended nutrient for human health.
Although the precise benefits of vitamin E are not known, diets
deficient in vitamin E appear to be associated with atherosclerosis.
Moreover, the tocotrienols, tocols incorporating a polyunsaturated
isoprene chain, are known to reduce cholesterol levels in several
experimental models, including humans. Barley provides a moderate source
for tocols compared to other grains such as wheat and rye, however, they
are relatively rich in the tocotrienols and they produce all eight
naturally occurring tocol congeners. Moreover, from the few published
accounts on barley tocol production, there appears to be significant
genotypic variation. The present study presents preliminary data from
analysis of tocol composition of the first two years of Barley
Coordinated Agriculture Project (Barley CAP).

**Validation of molecular markers for scald resistance in two-row
barley.**

Zantinge\* J.L., Juskiw, P., Hartman, Z., and Xi K. Field Crop
Development Centre, Alberta Agriculture and Food, 5030 - 50th Street,
Lacombe, AB., T4L 1W8, Canada.

\*Corresponding author (403)782-8692 <jennifer.zantinge@gov.ab.ca>.

www1.agric.gov.ab.ca/app21/rtw/selsubj.jsp

Scald (*Rhynchosporium secalis*) of barley is prevalent in central
Alberta, Canada and causes considerable yield and quality losses. Scald
can rapidly change in pathotype composition and frequency, thereby
making it difficult to develop durable scald resistance in barley. For
the past fifteen years in our two-row barley-breeding program at the
Field Crop Development Centre, we have been trying to incorporate
durable or multi-gene resistance to scald into lines with good malting
quality. It has proven to be illusive. Previous studies have however,
shown that the cultivar Seebe, a two-row feed barley, carries durable
genetic resistance (released in 1992 it still gets resistant ratings in
field evaluations), however, barley breeders have found this resistance
difficult to transfer into new barley lines with good malting quality.
Molecular marker analysis has identified that the SSR markers linked to
scald resistance from Seebe represent three putative QTLs. These QTLs
for scald resistance were identified to be on chromosomes 3HL, 4H
(centomeric region) and 5HL. This study was under-taken to validate the
utilization of these molecular markers for scald resistance; as well as,
investigate the relationship between the scald resistance from Seebe and
malting quality. While Seebe has proven to have durable resistance, it
does not modify well and has high beta-glucan levels in the malt. Four
crosses were made between Seebe and lines with malting quality. Lines
from these four crosses were advanced to the F5 using single seed
descent. In 2006, up to one hundred lines from each cross were assessed
for seedling resistance to a common *R. secalis* strain isolated from
the susceptible cultivar Harrington and markers for the Seebe scald
resistance genes. The F6 generation of these lines and up to an
additional 100 lines per cross were grown out in 2007 for marking of
Seebe scald resistance genes, assessment of field resistance to scald,
and malting quality determination using NIRS. Results from these two
years of study showing the relationship of seedling and field response
to *R. secalis*, Seebe scald resistance markers, and malting quality
will be presented.

**QTL Mapping and Molecular Marker Development for Seed Dormancy in
Spring Barley.**

J.L. Zantinge\*, J Nyachiro, S. Xue, J. H. Helm, P. E. Juskiw and D.
Salmon. Field Crop Development Centre, Alberta Agriculture, Food and
Rural Development, 5030 - 50 Street, Lacombe, AB T4L 1W8

\*Corresponding author (403)782-8692 <jennifer.zantinge@gov.ab.ca>

*\
*Wet field conditions just prior to harvest can cause pre-harvest
sprouting in barley (*Hordeum vulgare*) resulting in significant
economic losses especially in barley genotypes with low seed dormancy.
On-the-other-hand, too much dormancy can cause inconsistent germination,
creating problems in the malt house or during crop seeding. Seed
dormancy is defined as the failure of viable kernels to germinate under
optimum conditions of moisture, oxygen, and temperature. Selection for
sprouting resistance in a barley-breeding program is challenging because
the dormancy trait is influenced by the environment, and is controlled
by multiple genes, that are often linked to important quality traits.
Utilizing molecular markers linked to dormancy would be one method of
selecting for desirable levels of seed dormancy in barley without the
problem of environmental effects on expression, and could be used to
break up undesired linkage (repulsion) effects that reduce seed quality.
The objective of this study was to identify, map and develop molecular
markers linked to genes affecting dormancy from \`Samson\' barley.
Several recombinant inbred lines (RILs) were developed by crossing
\`Samson\' derived lines (high in dormancy) with \`TR118\' (a malt
variety from Dr. B. Harvey,Saskatoon). Dormancy levels were determined
using a weighted germination index (WGI) on this population of 239 RILs.
This phenotyped population was subsequently analysed with SSR markers
and several QTLs for dormancy were identified across the genome. Several
of the QTLs identified in this population, confirmed the locations of
previously identified QTLs found in other genetic populations. In
addition we also identified two new QTLs for seed dormancy on
chromosomes 2H and 4H.

**Exploiting historical malting quality data from the Western Canadian
Cooperative Two-row Barley trials using association mapping**

Aaron D. Beattie^1^, Brian G. Rossnagel^1^ and Michael J. Edney^2^

^1^Crop Development Centre, University of Saskatchewan, Saskatoon,
Saskatchewan, Canada S7N 5A8

^2^Grain Research Laboratory, Canadian Grain Commission, Winnipeg,
Manitoba, Canada R3C 3G8

Association mapping (AM) is a method to detect significant correlations
between genotypic and phenotypic data using linkage disequilibrium (or
the non-random association between alleles). Unlike QTL analysis, AM
does not require production of a structured, experimental population,
but can be used with unrelated genotypes (or for which the relationships
between genotypes are taken into account). AM can exploit the larger
number of segregating loci in such populations providing greater mapping
resolution and allowing more traits to be studied at once since there is
more phenotypic variability. In addition, historical phenotypic data
(such as that typically collected during cooperative/collaborative
testing) can be analyzed.

The potential of a barley genotype to produce good malt is evaluated for
a range of traits such as alpha amylase, beta-glucan, diastatic power,
fermentable extract, free amino nitrogen, germination energy and Kolbach
index. These indicators are used in various ways to predict
fermentability, the most valuable characteristic of malt. For example,
Evans et al. (2005) determined that a combination of alpha-amylase,
beta-amylase, limit dextrinase and heat stable beta-amylase correlated
well with fermentability.

Malting quality traits are time consuming to measure and are assessed at
the final stages in barley breeding programs on a limited number of
selections. Identifying molecular markers associated with these traits
would allow screening of larger number of genotypes earlier in the
breeding cycle to ensure important malting-related loci are maintained.
Malting analysis would then be valuable to help select the best
remaining lines which may be segregating for loci affecting malting
quality which have not yet been identified.

A number of studies have identified malting quality regions of the
genome using QTL analysis. These studies have tended to use populations
derived crosses between a good malting genotype and a poor one (such as
a feed genotype). For example, the Steptoe x Morex (Hayes et. al. 1993)
and Harrington x TR306 (Mather et. al. 1997) populations were used to
identify QTLs across all seven chromosomes. Typical of QTL studies, poor
mapping resolution results from the limited number of segregating
markers in biparental crosses and further work is required to refine the
location of trait-associated loci. For example, Gao et. al. (2004) fine
mapped an important region near the telomere on the short arm of
chromosome 4H which had been previously identified by Hayes et. al.
(1993). These studies have done a good job identifying genomic regions
that differentiate very good malting genotypes from poor, however its
likely that most good malting barley selections within breeding programs
already incorporate these positive alleles.

Rather than using a collection of genotypes which include a wide range
of malting quality, this study used only elite malting quality barley
genotypes from the Western Canadian Co-operative Two-Row Barley Trials
to determine if novel loci could be identified which may differentiate
good from very good malting genotypes. In addition, a greater degree of
mapping resolution should be possible using the AM approach making
subsequent molecular marker-assisted selection (MMAS) more accurate.

**Material and Methods**

Ninety-one two-row barley genotypes from the 1994-2006 Western
Co-operative Two-Row Barley trials were collected from participating
breeding programs or the Plant Gene Resources Centre of Canada --
Agriculture and Agri-Food Canada (AAFC; Saskatoon, SK). These genotypes
represent elite malting genotypes from eight different breeding
programs, including the currently most popular malting varieties (AC
Metcalfe, CDC Copeland, CDC Kendall, Harrington, Newdale) and newer
varieties such as Calder, CDC Select and CDC Aurora Nijo, CDC Reserve
and CDC Meredith. DNA was extracted and sent for DArT (Diversity Array
Technology) whole genome genotyping. Malting quality data was collected
by the Grain Research Lab (Canadian Grain Commission).

Population clustering was analyzed by unweighted pair-group method
(UPGMA) clustering (based on the Dice similarity coefficient) using
NTSYSpc v. 2.2 to provide a visual representation of the relatedness of
the AM population. Genetic variation within and among breeding programs
was evaluated by an analysis of molecular variance (AMOVA) and described
using Wright's fixation index (F~ST~). Pairwise F~ST~ comparisons were
made between the breeding programs to describe genetic diversity.
Arlequin v. 3.11 was used for these calculations

. Kinship information (generated with SPAGeDi v. 1.2) and population
structure (generated with Structure v. 2.2) was incorporated into a
mixed-model for AM.

Significance levels were adjusted for multiple testing using the
Bonferroni correction.

True loose smut (*Ustilago nuda*) resistance (controlled by a single
gene) ratings collected on the 91 lines as part of the trials was
analyzed to evaluate the robustness of the AM methods employed in the
study.

**Results and Discussion**

Approximately 500 high quality, polymorphic DArT markers were used to
analyze the AM population. Clustering demonstrated that genotypes from
the same breeding program tended to group together, but a significant
amount of exchange between programs was evident. Most of the Agricore
United (AU)/Coors/Cargill genotypes grouped together while Crop
Development Centre, University of Saskatchewan and AAFC, Brandon
genotypes were intermingled. The Busch Agricultural Resources Inc.
(BARI) and AAFC, Lethbridge genotypes clustered more strongly by
breeding program (Figure 1). Consistent with the dendrogram, F~ST~
values were low between the CDC and AAFC Brandon genotypes and high
between the AU/Coors/Cargill genotypes and most others (Table 1). AMOVA
determined that 16.7% of the genetic variation was distributed between
the breeding programs with 83.3% within, indicating a large pool of
common shared alleles.

DArT markers bPb-1959 to bPb-6065 on chromosome 1H were highly
correlated with true loose smut resistance (Table 2). These markers
encompass the region previously identified with resistance (Eckstein et.
al. 2002) and confirmed the validity of the AM methods.

Twenty genomic regions, predominantly located on chromosomes 2H, 5H and
7H, were significantly associated with the seven malting quality traits
evaluated (Table 2). Some regions, such as the telomeric end on the long
arm of chromosome 5H, have already been associated with malt quality.
This raises the question as to whether these are the same alleles
previously identified which differentiate good from poor malting
genotypes, or if these are alleles which distinguish good from very good
genotypes. Numerous potentially new loci which need to be validated were
also identified (Table 2). These regions are being analyzed for
candidate genes using rice synteny and barley CAP BOPA1 SNP markers
which have been mapped and integrated with barley DArT markers using the
Oregon Wolfe Barley population. The population will also be genotyped
using the Barley CAP BOPA1 SNP markers to facilitate future candidate
gene discovery. This study demonstrates the power of AM to extract
information from large historic datasets and provides potential new
markers for marker-assisted selection.

Eckstein PE, Krasichynska N, Voth D, Duncan S, Rossnagel BG, Scoles GJ
(2002) Development of PCR-based markers for a gene (*Un8*) conferring
true loose smut resistance in barley. Can. J. Plant Pathol. 24: 46-53.

Evans DE, Collins HM, Eglinton JK, Wilhelmson A (2005) Assessing the
impact of the level of diastatic power enzymes and their thermostability
on the hydrolysis of starch during wort production to predict malt
fermentability. J. Am. Soc. Brew. Chem. 63: 185-198.

Gao W, Clancy JA, Han F, Jones BL, Budde A, Wesenberg DM, Kleinhofs A,
Ullrich SE, North American Barley Genome Project (2004) Fine mapping of
a malting-quality QTL complex near the chromosome 4H S telomere in
barley. Theor. Appl. Genet. 109: 750-760.

Hayes PM, Liu BH, Knapp SJ, Chen F, Jones B, Blake T, Franckowiak J,
Rasmusson D, Sorrells M, Ullrich SE, Wesenberg D, Kleinhofs A (1993)
Quantitative trait locus effects and environmental interaction in a
sample of North American barley germ plasm. Theor. Appl. Genet. 87:
392-340.

Mather DE, Tinker NA, LaBerge DE, Edney M, Jones BL, Rossnagel BG, Legge
WG, Briggs KG, Irvine RB, Falk DE, Kasha KJ (1997) Regions of the genome
that affect grain and malt quality in a North American two-row barley
cross. Crop Sci. 37: 544-554.

Figure 1. Dendrogram produced by UPGMA clustering based on the Dice
similarity coefficient. AU: Agricore United, BARI: Busch Agricultural
Resources Inc., CDC: Crop Development Centre, AAFC: Agriculture and
Agri-Food Canada, AAFRD: Alberta Agriculture, Food and Rural
Development.

![](media/image1.wmf){width="6.009722222222222in"
height="5.863194444444445in"}

+------------+-----+------+------+------+------+------+-------+------+
| Table 1.   |     |      |      |      |      |      |       |      |
| Pairwise   |     |      |      |      |      |      |       |      |
| Wright's   |     |      |      |      |      |      |       |      |
| fixation   |     |      |      |      |      |      |       |      |
| index      |     |      |      |      |      |      |       |      |
| (F~ST~)    |     |      |      |      |      |      |       |      |
| values     |     |      |      |      |      |      |       |      |
| describing |     |      |      |      |      |      |       |      |
| genetic    |     |      |      |      |      |      |       |      |
| diversity  |     |      |      |      |      |      |       |      |
| among the  |     |      |      |      |      |      |       |      |
| breeding   |     |      |      |      |      |      |       |      |
| programs.  |     |      |      |      |      |      |       |      |
+------------+-----+------+------+------+------+------+-------+------+
|            | AU  | C    | Car  | BARI | CDC  | AAFC | AAFC  | A    |
|            |     | oors | gill |      |      |      |       | AFRD |
|            |     |      |      |      |      | Bra  | Lethb |      |
|            |     |      |      |      |      | ndon | ridge | Lac  |
|            |     |      |      |      |      |      |       | ombe |
+------------+-----+------+------+------+------+------+-------+------+
| AU         | \-  | 0    | 0    | 0    | 0    | 0    | 0.119 | 0    |
|            |     | .087 | .000 | .170 | .334 | .246 |       | .061 |
+------------+-----+------+------+------+------+------+-------+------+
| Coors      | 0.  | \-   | 0    | 0    | 0    | 0    | 0.212 | 0    |
|            | 061 |      | .025 | .284 | .411 | .319 |       | .155 |
+------------+-----+------+------+------+------+------+-------+------+
| Cargill    | 0.  | 0    | \-   | 0    | 0    | 0    | 0.135 | 0    |
|            | 380 | .378 |      | .255 | .333 | .256 |       | .071 |
+------------+-----+------+------+------+------+------+-------+------+
| BARI       | 0.  | 0    | 0    | \-   | 0    | 0    | 0.116 | 0    |
|            | 000 | .001 | .000 |      | .291 | .185 |       | .107 |
+------------+-----+------+------+------+------+------+-------+------+
| CDC        | 0.  | 0    | 0    | 0    | \-   | 0    | 0.196 | 0    |
|            | 001 | .000 | .001 | .000 |      | .035 |       | .141 |
+------------+-----+------+------+------+------+------+-------+------+
| AAFC       | 0.  | 0    | 0    | 0    |      | \-   | 0.101 | 0    |
| Brandon    | 000 | .000 | .000 | .004 |      |      |       | .075 |
+------------+-----+------+------+------+------+------+-------+------+
| AAFC       | 0.  | 0    | 0    | 0    | 0    | 0    | \-    | 0    |
| Lethbridge | 021 | .011 | .023 | .002 | .000 | .000 |       | .027 |
+------------+-----+------+------+------+------+------+-------+------+
| AAFRD      | 0.  | 0    | 0    | 0    | 0    | 0    | 0.144 | \-   |
| Lacombe    | 030 | .001 | .038 | .000 | .000 | .000 |       |      |
+------------+-----+------+------+------+------+------+-------+------+
| F~ST~      |     |      |      |      |      |      |       |      |
| values     |     |      |      |      |      |      |       |      |
| above      |     |      |      |      |      |      |       |      |
| diagonal,  |     |      |      |      |      |      |       |      |
| *P* values |     |      |      |      |      |      |       |      |
| below      |     |      |      |      |      |      |       |      |
| diagonal.  |     |      |      |      |      |      |       |      |
|            |     |      |      |      |      |      |       |      |
| AU:        |     |      |      |      |      |      |       |      |
| Agricore   |     |      |      |      |      |      |       |      |
| United,    |     |      |      |      |      |      |       |      |
| BARI:      |     |      |      |      |      |      |       |      |
| Busch      |     |      |      |      |      |      |       |      |
| Ag         |     |      |      |      |      |      |       |      |
| ricultural |     |      |      |      |      |      |       |      |
| Resources  |     |      |      |      |      |      |       |      |
| Inc., CDC: |     |      |      |      |      |      |       |      |
| Crop       |     |      |      |      |      |      |       |      |
| D          |     |      |      |      |      |      |       |      |
| evelopment |     |      |      |      |      |      |       |      |
| Centre,    |     |      |      |      |      |      |       |      |
| AAFC:      |     |      |      |      |      |      |       |      |
| A          |     |      |      |      |      |      |       |      |
| griculture |     |      |      |      |      |      |       |      |
| and        |     |      |      |      |      |      |       |      |
| Agri-Food  |     |      |      |      |      |      |       |      |
| Canada,    |     |      |      |      |      |      |       |      |
| AAFRD:     |     |      |      |      |      |      |       |      |
| Alberta    |     |      |      |      |      |      |       |      |
| Ag         |     |      |      |      |      |      |       |      |
| riculture, |     |      |      |      |      |      |       |      |
| Food and   |     |      |      |      |      |      |       |      |
| Rural      |     |      |      |      |      |      |       |      |
| De         |     |      |      |      |      |      |       |      |
| velopment. |     |      |      |      |      |      |       |      |
+------------+-----+------+------+------+------+------+-------+------+

+-------+-------------------+------------+----------+-----------------+
| Table |                   |            |          |                 |
| 2.    |                   |            |          |                 |
| DArT  |                   |            |          |                 |
| ma    |                   |            |          |                 |
| rkers |                   |            |          |                 |
| assoc |                   |            |          |                 |
| iated |                   |            |          |                 |
| with  |                   |            |          |                 |
| seven |                   |            |          |                 |
| ma    |                   |            |          |                 |
| lting |                   |            |          |                 |
| qu    |                   |            |          |                 |
| ality |                   |            |          |                 |
| t     |                   |            |          |                 |
| raits |                   |            |          |                 |
| and   |                   |            |          |                 |
| true  |                   |            |          |                 |
| loose |                   |            |          |                 |
| smut  |                   |            |          |                 |
| r     |                   |            |          |                 |
| esist |                   |            |          |                 |
| ance. |                   |            |          |                 |
+-------+-------------------+------------+----------+-----------------+
| Trait | Marker            | Chromosome | Position | *P* Value       |
|       |                   |            | (cM)     |                 |
+-------+-------------------+------------+----------+-----------------+
| AA    | bPb-7039          | 2H         | 71       | 1.4x10^-4^      |
+-------+-------------------+------------+----------+-----------------+
|       | bPb-9868 to       | 5H         | 184-190  | 4.8x10^-6^ to   |
|       | bPb-7292          |            |          | 7.31x10^-11^    |
+-------+-------------------+------------+----------+-----------------+
|       | **bPb-8084\***    | 7H         | 5        | 4.2x10^-4^      |
+-------+-------------------+------------+----------+-----------------+
| BG    | **bPb-6194\***    | 2H         | 102      | 2.8x10^-4^      |
+-------+-------------------+------------+----------+-----------------+
|       | bPb-5766 to       | 5H         | 188-190  | 2.4x10^-5^ to   |
|       | bPb-7292          |            |          | 3.7x10^-6^      |
+-------+-------------------+------------+----------+-----------------+
| DP    | bPb-0615 to       | 2H         | 11-16    | 1.4x10^-4^ to   |
|       | bPb-5519          |            |          | 2.0x10^-5^      |
+-------+-------------------+------------+----------+-----------------+
|       | bPb-9868 to       | 5H         | 184-190  | 2.7x10^-5^ to   |
|       | bPb-7292          |            |          | 3.6x10^-9^      |
+-------+-------------------+------------+----------+-----------------+
|       | **bPb-6821 to     | 7H         | 50       | 3.3x10^-4^      |
|       | bPb-5091\***      |            |          |                 |
+-------+-------------------+------------+----------+-----------------+
|       | bPb-1737          | 7H         | 158      | 5.9x10^-5^      |
+-------+-------------------+------------+----------+-----------------+
| FExt  | **bPb-3056 to     | 2H         | 70       | 2.6x10^-5^ to   |
|       | bPb-6881\***      |            |          | 2.7x10^-6^      |
+-------+-------------------+------------+----------+-----------------+
|       | bPb-0351          | 5H         | 21       | 1.7x10^-4^      |
+-------+-------------------+------------+----------+-----------------+
|       | bPb-5766 to       | 5H         | 188-190  | 3.8x10^-4^      |
|       | bPb-7292          |            |          |                 |
+-------+-------------------+------------+----------+-----------------+
| Friab | bPb-6821 to       | 7H         | 50       | 1.6x10^-4^ to   |
|       | bPb-5091          |            |          | 9.4x10^-5^      |
+-------+-------------------+------------+----------+-----------------+
|       | **bPb-3394\***    | 7H         | 79       | 1.3x10^-4^      |
+-------+-------------------+------------+----------+-----------------+
|       | **bPb-7781\***    | 7H         | 103      | 8.0x10^-5^      |
+-------+-------------------+------------+----------+-----------------+
| Prot  | **bPb-2055 to     | 1H         | 13-16    | 2.4x10^-5^ to   |
|       | bPb-9414\***      |            |          | 9.1x10^-6^      |
+-------+-------------------+------------+----------+-----------------+
|       | **bPb-9632 to     | 5H         | 31       | 3.8x10^-4^ to   |
|       | bPb-0050\***      |            |          | 1.1x10^-4^      |
+-------+-------------------+------------+----------+-----------------+
|       | **bPb-4219 to     | 7H         | 74       | 2.3x10^-4^ to   |
|       | bPb-7952\***      |            |          | 9.1x10^-5^      |
+-------+-------------------+------------+----------+-----------------+
| SP    | **bPb-1986\***    | 2H         | 147      | 1.0x10^-5^      |
+-------+-------------------+------------+----------+-----------------+
|       | bPb-4809 to       | 5H         | 186-190  | 1.4x10^-5^ to   |
|       | bPb-7292          |            |          | 2.5x10^-14^     |
+-------+-------------------+------------+----------+-----------------+
| LS    | bPb-1959 to       | 1H         | 133-136  | 1.2x10^-5^ to   |
|       | bPb-6065          |            |          | 9.4x10^-13^     |
+-------+-------------------+------------+----------+-----------------+
| AA:   |                   |            |          |                 |
| alpha |                   |            |          |                 |
| amy   |                   |            |          |                 |
| lase, |                   |            |          |                 |
| BG:   |                   |            |          |                 |
| be    |                   |            |          |                 |
| ta-gl |                   |            |          |                 |
| ucan, |                   |            |          |                 |
| DP:   |                   |            |          |                 |
| dias  |                   |            |          |                 |
| tatic |                   |            |          |                 |
| p     |                   |            |          |                 |
| ower, |                   |            |          |                 |
| FExt: |                   |            |          |                 |
| f     |                   |            |          |                 |
| ermen |                   |            |          |                 |
| table |                   |            |          |                 |
| ext   |                   |            |          |                 |
| ract, |                   |            |          |                 |
| F     |                   |            |          |                 |
| riab: |                   |            |          |                 |
| f     |                   |            |          |                 |
| riabi |                   |            |          |                 |
| lity, |                   |            |          |                 |
| Prot: |                   |            |          |                 |
| pro   |                   |            |          |                 |
| tein, |                   |            |          |                 |
| SP:   |                   |            |          |                 |
| so    |                   |            |          |                 |
| luble |                   |            |          |                 |
| pro   |                   |            |          |                 |
| tein, |                   |            |          |                 |
| LS:   |                   |            |          |                 |
| loose |                   |            |          |                 |
| smut. |                   |            |          |                 |
|       |                   |            |          |                 |
| **\*  |                   |            |          |                 |
| Pote  |                   |            |          |                 |
| ntial |                   |            |          |                 |
| new   |                   |            |          |                 |
| malt  |                   |            |          |                 |
| qu    |                   |            |          |                 |
| ality |                   |            |          |                 |
| loc   |                   |            |          |                 |
| us.** |                   |            |          |                 |
+-------+-------------------+------------+----------+-----------------+

**Net blotch quantitative trait loci -- their practical application in
barley breeding**

Tajinder S. Grewal, Brian G. Rossnagel and Graham J. Scoles. Crop
Development Centre/Department of Plant Sciences, University of
Saskatchewan, 51 Campus Drive, Saskatoon, SK, Canada S7N 5A8

Barley net blotch, caused by *Pyrenophora teres* Drechs. \[anamorph:
*Drechslera teres* (Sacc.) Shoemaker\] is an important foliar disease in
Canada (Tekauz 1990) and elsewhere (Steffenson 1997). Two types of leaf
symptoms occur: the net form (NFNB), caused by *P. teres* f. *teres*,
which causes a dark brown reticulate venation pattern that sometimes
turns chlorotic; and the spot form (SFNB), caused by *P. teres* f.
*maculata*, which results in dark brown circular or elliptical spots
accompanied by chlorosis of the surrounding leaf tissue (Khan and Tekauz
1982). The most effective and economic method to control this disease is
the use of resistant cultivars; however, most commonly grown barley
cultivars are susceptible to most isolates of *P. teres* (Tekauz 1990,
2000). The variability observed in *P. teres* and lack of lines
resistant to all isolates suggests breeding for resistance should
emphasize pyramiding resistance genes to develop broad-based durable
resistance. Molecular markers allow breeders to rapidly introgress and
pyramid resistant genes into elite lines.

Here we report the mapping of net blotch resistance quantitative trait
loci (QTL) in a doubled-haploid (DH) barley population using Diversity
Arrays Technology (DArT®) markers; identification of SSR markers linked
to major QTL; validation in other barley populations and potential use
in molecular-marker assisted selection (MMAS) in the Crop Development
Centre (CDC) barley breeding program.

**Materials and methods**

One hundred and fifty DH lines from the cross CDC Dolly/TR251 were
screened at the seedling stage with NFNB isolates WRS858 and WRS1607 and
SFNB isolate WRS857 in the Phytotron at the University of Saskatchewan.
For details on planting, inoculation and infection assessment see Grewal
et al. (2008). The 150 DH lines were also screened at the adult-plant
stage in the CDC NFNB field disease-screening nursery at Melfort, SK in
2005 and 2006. Analysis of variance was performed using PROC Mixed of
SAS 9.1 (SAS Institute Inc. 2005). Least significant differences (LSD)
for mean comparisons were calculated (*P* = 0.05) for each test.
Heritability was calculated for each test using variance estimates
derived from PROC Mixed. The phenotypic variance was σ^2^~DH\ lines~ +
σ^2^~residual~/replications.

DArT mapping and QTL analysis was as described in Grewal et al. (2008).
"*QRptt*" indicates a QTL for resistance to *P. teres* f. *teres* (NFNB)
and "*QRptm*" indicates a QTL for resistance to *P. teres* f. *maculata*
(SFNB). "*QRpt*" indicates a QTL for resistance to *P. teres*, i.e.,
effective against both NFNB and SFNB. "*QRpt*" is followed by "s" or "a"
if effective only at the seedling or adult-plant stage and followed by
the barley chromosome onto which the QTL was mapped.

To determine the effect of individual QTL and their combinations on net
blotch resistance, the mean infection response (IR) of all lines with
the resistance allele for each QTL or their combinations was calculated
and compared with the mean of lines having the susceptible allele for
that particular QTL. *T*-tests (*P* = 0.05) were performed to determine
statistical significance.

Simple sequence repeat (SSR) markers linked to major net blotch
resistance QTL were identified and validated in other barley
populations. One hundred and fifty DH lines from the CDC Bold/TR251
population were screened at the seedling stage with NFNB isolates WRS858
and WRS1607 and SFNB isolates WRS857 and LO233. This population was also
screened at the adult plant stage in the CDC NFNB field
disease-screening nursery at Melfort, SK in 2006, 2007 and 2008.
Eighty-nine lines from this population were mapped using DArT, AFLP and
SSR markers (Li et al. 2008). QTL analysis was performed as described in
Grewal et al. (2008). Four populations (MEH#486/Harrington, McLeod/CDC
Helgason, KXN/TLN 147/CDC Helgason, SB01045/TR02367) were screened with
SSR markers HVM74 and HVM03 linked to *QRpt6* and *QRpts4*,
respectively. MMAS selected lines were screened at the seedling stage in
the Phytotron and at the adult-plant stage in the field to determine the
effectiveness of MMAS for net blotch screening.

**Results and Discussion**

A major NFNB seedling resistance QTL, designated *QRpt6*, was mapped to
chromosome 6H for isolates WRS858 and WRS1607 (Fig. 1) in the CDC
Dolly/TR251 population. *QRpt6* was associated with adult-plant
resistance in 2005 and 2006 field trials. These results confirm earlier
reports of a major QTL or gene on chromosome 6H (Steffenson et al. 1996;
Manninen et al. 2000; Cakir et al. 2003; Gupta et al. 2004; Friesen et
al. 2006). Additional QTL for NFNB seedling resistance to the more
virulent isolate WRS858 were identified on chromosomes 2H, 4H, and 5H. A
seedling resistance QTL (*QRpts4*) for the SFNB isolate WRS857 was
detected on chromosome 4H as was a significant QTL (*QRpt7*) on
chromosome 7H. Three QTL (*QRpt6*, *QRpts4*, *QRpt7*) were associated
with resistance to both net blotch forms and lines with one or more of
these demonstrated improved resistance. SSR markers tightly linked to
*QRpt6* and *QRpts4* were identified.

*QRpt6* was further validated in the CDC Bold/TR251 population for
seedling resistance to NFNB isolates WRS858 and WRS1607 and adult-plant
resistance in 2006, 2007 and 2008 field trials. The major seedling and
adult plant resistance QTL/gene on 6H in TR251 may be sufficient to
provide adequate field resistance to NFNB and could be selected for
based on Phytotron screening or using molecular markers. High
heritability for different tests indicated that selection based on
molecular markers is feasible.

![](media/image2.png){width="7.842361111111111in"
height="5.126388888888889in"}

Fig. 1 Multiple-QTL model (MQM) LOD scans of chromosomes where QTL were
detected for NFNB resistance in the CDC Dolly/TR251 DH population.
Vertical lines indicate significance threshold for each experiment,
estimated from 1000 permutations. One QTL on 4H associated with NFNB
(WRS858) resistance. A major QTL on 6H associated with seedling (WRS858,
WRS1607) and adult-plant (Field 2005, field 2006) resistance.

Screening the parents of 22 barley populations with SSR markers linked
to *QRpt6* and *QRpts4* identified several polymorphic populations,
indicating these SSR markers could be used for practical MMAS in the CDC
barley breeding program. Four populations were screened with SSR markers
HVM74 and HVM03 to select lines resistant to both net blotch forms.

Screening selected barley lines from MEH#486/Harrington population at
the seedling stage in the Phytotron and at the adult-plant stage in the
field demonstrated that MMAS selected resistant lines showed
significantly better resistance (Table 1). Selection based on marker
HVM74 (*QRpt6*) alone showed better resistance than no marker and
similar to selecting for the both markers, proving selection based on
*QRpt6* alone could select resistance to both net blotch forms. This was
further confirmed in populations McLeod/CDC Helgason, KXN/TLN 147/CDC
Helgason, SB01045/TR02367.

Table 1. Average infection response of lines from the MEH#486/Harrington
population with or without major net blotch resistance QTL (*QRpt6*,
*QRpts4*)

+--------------+-------+--------+------+-----+-----+--------+-----+
| QTL/Test     |       | # NFNB |      |     |     | SFNB   |     |
+--------------+-------+--------+------+-----+-----+--------+-----+
|              | ^b^A  | ^c^    | F    | Fi  | Fi  | ^c^    | ^d  |
|              | llele | WRS858 | ield | eld | eld | WRS857 | ^\# |
|              |       |        | 2006 | 2   | 2   |        | of  |
|              |       |        |      | 007 | 008 |        | li  |
|              |       |        |      |     |     |        | nes |
+--------------+-------+--------+------+-----+-----+--------+-----+
| *QRpt6*      | R     | 4      | 3.0  | 2   | 2   | 5      | 79  |
|              |       | .0\*\* | \*\* | .7\ | .8\ | .7\*\* |     |
|              |       |        |      | *\* | *\* |        |     |
+--------------+-------+--------+------+-----+-----+--------+-----+
|              | S     | 6.8    | 4.5  | 4.0 | 3.8 | 6.8    | 69  |
+--------------+-------+--------+------+-----+-----+--------+-----+
| *QRpts4*     | R     | 5.0    | 3.6  | 3.  | 3.2 | 6.0    | 62  |
|              |       |        |      | 0\* |     |        |     |
+--------------+-------+--------+------+-----+-----+--------+-----+
|              | S     | 5.6    | 3.8  | 3.6 | 3.4 | 6.4    | 83  |
+--------------+-------+--------+------+-----+-----+--------+-----+
| *QRp         | R     | 3      | 2.8  | 2   | 2   | 5      | 25  |
| t6*+*QRpts4* |       | .4\*\* | \*\* | .4\ | .8\ | .4\*\* |     |
|              |       |        |      | *\* | *\* |        |     |
+--------------+-------+--------+------+-----+-----+--------+-----+
|              | S     | 7.1    | 4.8  | 4.5 | 4.0 | 6.9    | 32  |
+--------------+-------+--------+------+-----+-----+--------+-----+

^b^ Resistance (R) or susceptible (S) allele at a particular QTL
locus/loci.

^c^*Pyrenophora teres* isolate

^d^ Total number of lines with R or S allele at particular QTL.

\*Significant (*P* \<0.05) or \*\*highly significant (*P* \<0.01) using
T-test at particular QTL or their combinations.

The results demonstrate that MMAS resistant lines had significantly
lower infection than susceptible lines, indicating that MMAS for net
blotch resistance is practical. Since the major 6H QTL, *QRpt6*, may
provide adequate NFNB field resistance in western Canada, the practical
application plan for the Crop Development Centre barley breeding program
is to routinely utilize MMAS for *QRpt6* followed by normal field
screening in field net blotch nurseries to identify additional
resistance provided by resistance genes associated with other QTL.
Resources permitting the CDC program has implemented routine MMAS for
*QRpt6* and recommends this approach to other breeding programs.

**Selected references**

Cakir, M., S. Gupta, G.J. Platz, G.A. Ablett, R. Loughman, L.C. Embiri,
D. Poulsen, C.D. Li, R.C.M. Lance, N.W. Galwey, M.G.K. Jones, and R.
Appels. 2003. Mapping and validation of the genes for resistance to
*Pyrenophora teres* f. *teres* in barley (*Hordeum vulgare* L.). Aust.
J. Agric. Res. 54:1369-1377.

Grewal, T.S., B.G. Rossnagel, C.J. Pozniak, and G.J. Scoles. 2008.
Mapping quantitative trait loci associated with barley net blotch
resistance. Theor. Appl. Genet. 116:529-539.

Steffenson, B.J. 1997. Net blotch. In: Mather DE (ed) Compendium of
barley diseases, 2nd edn. American Phytopathological Society, St. Paul,
MN, pp 28--31.

Tekauz, A. 1990. Characterization and distribution of pathogenic
variation in *Pyrenophora teres* f. *teres* and *P. teres* f. *maculata*
from western Canada. Can. J. Plant Pathol. 12:141--148.