About Us | Help Videos | Contact Us | Subscriptions
 

Agronomy Journal - Article

 

 

This article in AJ

  1. Vol. 105 No. 6, p. 1695-1706
    unlockOPEN ACCESS
     
    Received: Apr 15, 2013
    Published: October 24, 2013


    * Corresponding author(s): brian.beres@agr.gc.ca
 View
 Download
 Alerts
 Permissions
Request Permissions
 Share

doi:10.2134/agronj2013.0192

A Canadian Ethanol Feedstock Study to Benchmark the Relative Performance of Triticale: I. Agronomics

  1. Brian Beres *a,
  2. Curtis Pozniakb,
  3. Francois Eudesa,
  4. Robert Grafa,
  5. Harpinder Randhawaa,
  6. Don Salmonc,
  7. Grant McLeoda,
  8. Yves Dione,
  9. Byron Irvinef,
  10. Harvey Voldengg,
  11. Richard Martinh,
  12. Denis Pageaui,
  13. Andre Comeauj,
  14. Ronald DePauwd,
  15. Sherrilyn Phelpsk and
  16. Dean Spanerl
  1. a Agriculture and Agri-Food Canada, Lethbridge Research Centre, 5403 1st Avenue South, Lethbridge, AB, Canada T1J 4B1
    b Crop Development Centre, Dep. of Plant Sciences, Univ. of Saskatchewan, 51 Campus Drive, Saskatoon, SK, Canada S7N 5A8
    c Alberta Agriculture, Field Crop Development Centre, 5030 50th Street, Lacombe, AB, Canada T4L 1W8
    e CÉROM Agronome, 740 chemin Trudeau, Saint-Mathieu-de-Beloeil, QC, Canada J3G 4S5
    f Agriculture and Agri-Food Canada, Brandon Research Centre, Box 1000A, R.R. 3, Brandon, MB, Canada R7A 5Y3
    g Agriculture and Agri-Food Canada, Eastern Cereal and Oilseed Research Centre, 960 Carling Ave., Ottawa, ON, Canada K1A 0C6
    h Agriculture and Agri-Food Canada, Crops and Livestock Research Centre, P.O. Box 1210, Charlottetown, PEI, Canada C1A 7M8
    i Agriculture and Agri-Food Canada, Research Farm, 1468 Saint-Cyrille St., Normandin, QC, Canada G8M 4K3
    j Agriculture and Agri-Food Canada, Research Station, 2560 Hochelaga, Sainte-Foy, QC, Canada G1V 2J3
    d Agriculture and Agri-Food Canada, Semi-arid Prairie Agricultural Research Centre, P.O. Box 1030, Swift Current, SK, Canada S9H 3X2
    k Saskatchewan Ministry of Agriculture, 1192-102nd Street, North Battleford, SK, Canada S9A 1E9
    l Dep. of Agricultural, Food, and Nutritional Sciences, Univ. of Alberta, 410 Ag/Forestry Building, Edmonton, AB, Canada T6G 2P5

Abstract

A need has been identified for alternative crop(s) with high grain yield, low grain protein concentration, and high starch for the ethanol industry. The objective of this study was to benchmark the relative performance of triticale (×Triticosecale ssp.) to wheat (Triticum aestivum L.) classes currently utilized for ethanol production. Sixteen cultivars—three triticale, four Canada prairie spring (CPS) wheat, three Canada western soft white spring wheat (CWSWS), two Canada western red spring (CWRS) wheat, and four Canada western general purpose (CWGP) candidate cultivars—were grown at 36 locations across western Canada from 2006 to 2009. The performance of these cereal classes can generally be summarized as triticale = Hoffman (CWGP) = CWSWS > CPS white > CPS red > CWRS for most variables. The triticale and white wheats produced 12 and 13% more grain, respectively, than the hard red spring wheats. Among the triticales, AC Ultima’s and Pronghorn’s yield potential were most notable because they exceeded the CWRS cultivars AC Barrie and AC Superb by an average of 32% and the CPS red cultivars 5700PR and AC Crystal by 18%. The triticales and Hoffman matured later than most other cultivars. Pronghorn consistently displayed low levels of fusarium head blight (FHB), Septoria nodorum blotch, and powdery mildew, but elevated ergot levels were observed for all triticales. We conclude that triticale would be superior to CPS and CWRS wheat and similar to CWSWS in many agronomic traits desired by ethanol fermentation plants and is superior for biomass production.


Abbreviations

    CPS, Canada prairie spring; CWGP, Canada western general purpose; CWRS, Canada western red spring; CWSWS, Canada western soft white spring wheat; DON, deoxynivalenol; FDK, fusarium-damaged kernels; FHB, fusarium head blight

Wheat production in the prairies of Canada has spanned almost 120 yr. The crop has served producers and end users well, as advancements in cultivar development have produced high-performing, well-adapted, premium quality cultivars. The bread wheat class, or Canada western red spring (CWRS), remains an important export commodity, but other classes of wheat such as Canada prairie spring (CPS) have been developed to serve markets with lower or alternative quality specifications. Some milling markets such as cookie and pastry flour specify low protein and higher starch, which resulted in the creation of the Canada western soft white spring (CWSWS) wheat class. The contrasting quality profiles mean that producers must first decide on a market class and then select cultivars within that class for cultivation. The lack of marketing choice, however, can jeopardize net returns if the wheat produced does not meet quality specifications and is downgraded to feed wheat status. The problem is compounded if the demand for a specific class diminishes due to competition or changes to customer dietary preferences. The latter occurred with the CWSWS class in southern Alberta: the market that once supported >200,000 ha has been reduced to 10,000 ha.

As the bioeconomy evolves, opportunities for dual grain markets are emerging. One example is the dramatic expansion of ethanol production in western Canada and the rising demand for a feedstock with high grain yield, low grain protein concentration, and high starch. There are currently seven ethanol plants operating in western Canada with a collective annual output capacity of 509,000,000 L (Collier et al., 2013). Today, a producer of CWSWS and CPS wheat, which are preferred wheat ethanol feedstocks, can now choose to either sell their wheat into a milling market or contract their production to an ethanol plant. This has shifted almost all production of CWSWS away from southern Alberta to nontraditional CWSWS areas in the prairies that are in close proximity to ethanol plants.

Globally, ethanol feedstock production from small grains primarily relies on corn (Zea mays L.) and wheat, but the consideration for a low-cost feedstock by ethanol plants has prompted the evaluation of a range of crops for ethanol fermentation suitability. In Canada, and particularly across the prairie landscape, small grains are best adapted to meet this demand. Corn production within Canada could not support the ethanol industry because corn grain production west of Manitoba is <50,000 ha. The expansion of corn grain production is currently constricted in the prairies because most areas are limited by accumulated requisite heat units and adequate soil moisture.

Within small grain cereals, alternatives to wheat are being investigated. Triticale is a cereal crop with low grain protein concentration and high grain yield and biomass potential, which are desirable traits in biorefinery processes that currently utilize wheat (Beres et al., 2010; Goyal et al., 2011). Moreover, triticale is reported to have higher yield potential than some wheat classes, is generally more competitive with weeds (Beres et al., 2010; Oettler, 2005), and displays better tolerance to drought and pests than its ancestral species (Darvey et al., 2000; Erekul and Köhn, 2006). Preliminary studies conducted in the Western Prairies of Canada have indicated that triticale does have potential as an ethanol feedstock (McLeod et al., 2010).

Triticale is unique because it is a “human-made” amphidiploid, created in the late 19th century by crossing common wheat with rye (Secale cereale L.). A comprehensive review of triticale development was provided by Oettler (2005). A crop that does not occur naturally in the ecosystem may be more attractive as a cereal platform technology and better received by society when gene transformation is used to enhance a plant trait that is exploited in a bioindustrial process. A cross-sectorial, multidisciplinary team formed the Canadian Triticale Biorefinery Initiative (CTBI) to position triticale as a cereal platform technology for bioindustrial end uses. Reports to date have not assessed triticale grain yield and ethanol production across an array of environments nor have they assessed the crop using modern fermentation technologies. Therefore, the objective of this study for the CTBI was to benchmark the relative performance of triticale to the wheat classes currently utilized for ethanol production.


MATERIALS AND METHODS

Experimental Design and Management

Sixteen cultivars: three triticale, four CPS, three CWSWS, two CWRS, and four Canada western general purpose (CWGP) candidate cultivars, were grown at 36 locations across western Canada from 2006 to 2009 (Tables 1 and 2; Fig. 1). Cultivars were chosen that best represented the corresponding market class. The proxy for these choices was to select cultivars that were mid- to long-term checks used in either cultivar trials or cooperative registration trials or both. For example, Superb is a check for the CWRS class for most regional cultivar trials as well as cooperative registration trials and was also the dominant cultivar in western Canada during the period of this study. Some cultivars were also chosen if they represented a contrasting yield or quality profile. For example, Hoffman was chosen because it is a high-yielding cultivar with agronomic and disease attributes, particularly in the context of cultivar suitability to general purpose end uses such as feed or ethanol. The experimental design chosen for this study was a randomized complete block with three replications.


View Full Table | Close Full ViewTable 1.

Description of locations for ethanol feedstocks study.

 
Location Agroecological zone Soil zone Years Growing season precipitation
Latitude Longitude
2006 2007 2008 2009
mm
Dawson Creek, BC Parkland Grey Wooded 2007, 2009 –† 438 240 55°48′ N 120°14′ W
Fort St John, BC Parkland Grey Wooded 2007, 2009 562 222 56°17′ N 120°50′ W
Donnelly, AB Parkland Grey Wooded 2007 270 55°43′ N 117°6′ W
Edmonton, AB Parkland Black 2007, 2008, 2009 181 159 147 53°33′ N 113°29′ W
Falher, AB Parkland Grey Wooded 2007, 2008, 2009 270 234 107 55°46′ N 117°10′ W
Killam, AB Parkland Black 2006, 2007 416 370 52°47′ N 111°51′ W
Kitscoty, AB Parkland Black 2006 469 53°20′ N 110°20′ W
Lacombe, AB Parkland Black 2007, 2008, 2009 357 230 279 52°29′ N 113°43′ W
Lethbridge, AB (dry) Western Prairies Dark Brown 2007, 2008, 2009 164 380 241 49°41′ N 112°50′ W
Lethbridge, AB (irrigated) Western Prairies Dark Brown 2007, 2008, 2009 291 456 343 49°41′ N 112°50′ W
Neapolis, AB Parkland Black 2007, 2009 472 114 51°40′ N 113°52′ W
Sexsmith, AB Parkland Grey Wooded 2007 537 55°21′ N 118°46′ W
Vermilion, AB Parkland Black 2007 397 53°21′ N 110°51′ W
Westlock, AB Parkland Grey Wooded 2007 278 54°9′ N 113°51′ W
Canora, SK Parkland Grey Wooded 2007 365 51°38′ N 102°26′ W
Indian Head, SK Eastern Prairies Black 2007, 2008, 2009 275 217 210 50°32′ N 103°39′ W
Lake Lenore, SK Parkland Black 2007, 2008 369 178 52°25′ N 104°58′ W
Lashburn, SK Parkland Black 2006 339 53°7′ N 109°36′ W
Melfort, SK Parkland Black 2007, 2008, 2009 351 190 243 52°52′ N 104°36′ W
Outlook, SK Western Prairies Dark Brown 2007 291 51°29′ N 107°3′ W
Redvers, SK Eastern Prairies Black 2007 283 49°34′ N 101°41′ W
Regina, SK Western Prairies Dark Brown 2007, 2008 267 228 50°26′ N 104°35′ W
Saskatoon, SK Western Prairies Dark Brown 2006, 2007, 2008, 2009 489 278 180 215 52°8′ N 106°38′ W
Scott, SK Western Prairies Dark Brown 2007, 2008, 2009 313 207 173 52°21′ N 108°49′ W
Swift Current, SK Western Prairies Brown 2007, 2008, 2009 152 337 199 50°18′ N 107°46′ W
Valparaiso, SK Parkland Grey Wooded 2006 489 52°51′ N 104°10′ W
Watrous, SK Western Prairies Dark Brown 2007, 2008, 2009 210 238 256 51°40′ N 105°27′ W
Arborg, MB Parkland Grey Wooded 2008 466 387 50°54′ N 97°13′ W
Brandon, MB Eastern Prairies Black 2007, 2008, 2009 257 367 241 49°50′ N 99°56′ W
Carberry, MB Eastern Prairies Black 2007, 2009 389 235 49°51′ N 99°21′ W
Melita, MB Eastern Prairies Black 2006, 2007, 2008, 2009 378 283 258 213 49°16′ N 100°59′ W
Minto, MB Eastern Prairies Black 2006 462 49°24′ N 100°1′ W
Neepawa, MB Parkland Grey Wooded 2006, 2007 462 477 49°24′ N 100°1′ W
Portage, MB Eastern Prairies Black 2007, 2009 395 209 49°58′ N 98°17′ W
Roblin, MB Parkland Grey Wooded 2007, 2008, 2009 445 308 287 51°13′ N 101°21′ W
Rosebank, MB Eastern Prairies Black 2007, 2008, 2009 388 315 274 49°22′ N 98°6′ W
Precipitation data not collected.

View Full Table | Close Full ViewTable 2.

Summary of cultivars evaluated and corresponding market class description.

 
Cultivar Classification Reference
AC Ultima spring triticale McLeod et al. (2001)
Pronghorn spring triticale Salmon et al. (1997)
Tyndal spring triticale Salmon et al. (2007)
AC Andrew Canada western soft white spring wheat Sadasivaiah et al. (2004)
AC Sadash Canada western soft white spring wheat Sadasivaiah et al. (2009)
Bhishaj Canada western soft white spring wheat Randhawa et al. (2011)
AC Barrie Canada western red spring wheat McCaig et al. (1996)
AC Superb Canada western red spring wheat Townley-Smith et al. (2010)
Ashby Canada western general purpose candidate not available
Chablis Canada western general purpose candidate not available
Chiraz Canada western general purpose candidate not available
AC Vista Canada prairie spring white wheat DePauw et al. (1998)
Snowhite475 Canada prairie spring white wheat DePauw et al. (2007)
5700PR Canada prairie spring red wheat AgriPro/Syngenta (unpublished data, 2000)
AC Crystal Canada prairie spring red wheat Fernandez et al. (1998)
Hoffman Canada eastern red spring wheat; Canada western general purpose candidate H. Voldeng (unpublished data, 2004)
Fig. 1.
Fig. 1.

Geographical distribution of three agroecological zones and test locations for the agronomic assessment of ethanol feedstocks in western Canada from 2006 to 2009.

 

Agroecological Zone Characterization

The locations were grouped into three agroecological zones of the Canadian prairie: Western (W.) Prairies, Eastern (E.) Prairies, and the Parkland (Table 1; Fig. 1). Data generated from each site (location × year combinations) varied from a single year to 4 yr, which generated up to 77 site-years of data.

The W. Prairie region has soil types that are generally Orthic Dark Brown Chernozem clay loam soils (Typic Borolls), with approximately 30 g kg–1 organic matter content, or Brown Chernozem loam soils (Aridic Borolls), with approximately 20 g kg–1 organic matter. The W. Prairies extend from the southwestern site of Lethbridge, AB (49°41′ N, 112°50′ W), north to Scott, SK (52°21′ N), and east to Regina, SK (105°35′ W) (Table 1). The W. Prairies region is considered semiarid, has soils with lower organic matter, and has lower overall disease pressure than humid regions. Growing season precipitation ranged from 152 (Swift Current, SK) to 380 mm (Lethbridge, AB).

The E. Prairie region predominantly has Orthic Black Chernozem clay loam (Udic Boroll) soils, with 60 to 80 g kg–1 organic matter. The E. Prairies region accumulates the highest growing degree days of all regions and growing season precipitation intermediate to the W. Prairies and Parkland regions, and soils have high organic matter contents. Growing season precipitation ranged from 210 mm (Watrous, SK) to 462 mm (Minto, MB). The region has high yield potential but also has generally high disease pressure. The region is the least variable and occupies the smallest area, extending from the northwest site of Watrous, SK (50°32′ N, 103°39′ W), south to Melita, MB (49°16′ N), and east to Rosebank, MB (98°6′ W) (Table 1).

The Parkland region typically has Grey Wooded Luvisol soils in the northern regions (Boralfs and Udalfs) and Orthic Black Chernozem clay loam soils in southern and transitional regions of this zone. This region represented the largest physical area, with sites as far south as 49°16′ N (Neepawa, MB), up to the north and west boundary of Fort St. John, BC (56°17′ N, 120°50′ W), and east to Arborg, MB (97°13′ W) (Table 1). The Parkland has the shortest growing season and is the most humid, but rainfall accumulation can be variable. For example, severe drought occurred in this region in 2009, with growing season rainfall as low as 107 mm reported in Falher, AB, but as high as 562 mm in Fort St. John, BC, in 2007.

Experimental Measurements

Yield and Grain Quality

The plots were sown at a rate of 300 seeds m–2 using a plot seeder equipped with a cone splitter and zero-tillage double disk openers. Crop maturity was recorded at physiological maturity or when kernel moisture from the lower third of the spike was <400 g kg–1 and kernels could no longer be easily severed when pinched between the thumbnail and fingernail. If a differential in straw strength (lodging) was observed, plots were visually scored using a scale of 1 to 9 (1 = fully erect, 9 = flat on the ground). Each plot was harvested using a Wintersteiger Nurserymaster Elite plot combine (Wintersteiger AG) or comparable plot harvester equipped with a straight-cut header, pickup reel, and crop lifters. Aboveground whole-plant biomass was calculated by retaining all straw from the plot following grain harvest by attaching a tarpaulin blanket below and to the rear of the threshing case of the plot combine. Samples were weighed, suspended to dry at room temperature, and reweighed to determine the moisture content. Sample weights were corrected to zero moisture and are presented on a dry-weight basis (Mg ha–1). Grain yield, adjusted to 135 g kg–1 moisture content, was calculated from the entire plot area, and a 1000-seed subsample was retained to characterize seed weight.

Ten of the cultivars were selected to determine the differential response to three important field crop diseases. Disease nurseries near Charlottetown, PEI, and Ottawa, ON, were used to assess the cultivar response to fusarium head blight (caused by Fusarium graminearum Schwabe [teleomorph Gibberella zeae (Schwein.) Petch]). Each plot was spray-inoculated with a suspension of equal parts of four isolates of F. graminearum macroconidia three times, 6 to 7 d apart, starting when the first plots were at anthesis. The plots were rated with a visual rating index (incidence [0–10] × severity on infected heads [0–10], where 0 was disease free), taken approximately 3 wk after first inoculation or when symptoms were well developed (Cuthbert et al., 2007; Gilbert and Woods, 2006). Plots were harvested to collect grain samples for determination of fusarium-damaged kernels (FDK) on a weight-to-weight basis at Charlottetown and to measure grain levels of the mycotoxin deoxynivalenol (DON) at Charlottetown and Ottawa. The cultivar reactions to powdery mildew [Blumeria graminis (DC.) E.O. Speer] and Septoria nodorum blotch, caused by the fungus Septoria nodorum (teleomorph: Leptosphaeria nodorum) pathogens, were recorded from the agronomic field site near Charlottetown if cultivars expressed differential symptoms. Selected cultivars were also assessed for a differential response to ergot (caused by Claviceps purpurea). The only site to have a differential was Killam, AB, in 2008. Grain samples were visually scored on a scale of 1 to 5 (1 = no ergot, 5 = severe ergot contamination) based on the level of ergot contamination in the grain sample.

Statistical Analysis

Data were analyzed with the PROC GLIMMIX procedure of SAS (Littell et al., 2006; SAS Institute, 2005). The analysis of variance considered the effects of replicate and site (location × year combinations) as random and the cultivar effect as fixed. A Gaussian error distribution was used for the analysis. The SAS pdmix800 macro, developed by Saxton (1998), was used to summarize pairwise comparisons. The macro takes into account pairwise probabilities and converts them into letter groupings. A Bonferroni adjustment was used in conjunction with the macro to provide some protection against Type I errors. Variability for the cultivar effect among sites was assessed with a statistical test to determine if the variance estimates were significantly (P < 0.05) different from zero. Also, the relative size of the site × cultivar variance estimate was assessed by comparing it with the total variance associated with the site (main effect of site plus site × cultivar interaction).

The genotype × environment interactions also were assessed with a grouping methodology biplot, as described by Francis and Kannenberg (1978). The mean and CV were estimated for each cultivar across sites and replicates to explore average responses relative to variability for cultivars. Means were plotted against CV for each cultivar. The overall mean and CV were used in the plot to categorize the biplot data into four quadrants or categories: Group I—high mean, low variability (optimal); Group II—high mean, high variability; Group III—low mean, high variability (poor); and Group IV—low mean, low variability.

Multivariate analysis using a generalized form of principal components analysis, called multidimensional preference analysis, was performed to further explore the relationships among mean responses for the different crop traits (multivariate analysis of means). The analysis was conducted on a data matrix that included cultivar means as rows, while the columns were means for selected response variables. The analysis was conducted with the PRINQUAL procedure of SAS (SAS Institute, 2004) using an identity transformation. The results were summarized in a biplot, where the mean principal component scores for the cultivars were plotted as points in the ordination space. Eigenvectors (the correlation between the transformed and original data) for the crop responses were plotted as points at the end of vectors projecting from the origin into various positions in the ordination space. The coincidence of response variable vectors and entry points across the ordination space suggested crop response variable associations with the cultivars. The relative lengths of the vectors indicated the strength of these associations.


RESULTS

Entry and Class Differences

Analysis of variance indicated that the overall cultivar effect for agronomic variables was almost always highly significant (P < 0.01). The statistical test for the interaction effect of cultivar with agroecological zone was usually important (P < 0.05), with a few exceptions. The cultivar effect for stem lodging and aboveground biomass did not vary among agroecological zones. Means and mean comparison results are summarized across and by agroecological zones for all cereal responses (Tables 3–10).


View Full Table | Close Full ViewTable 3.

Cultivar height data collected in three western Canadian agroecological zones from 2006 to 2009.

 
Cultivar Class-ification† Plant height
Western Prairies Eastern Prairies Parkland Overall
cm
AC Ultima TRIT 99 a‡ 105 bc 102 b 102 c
Pronghorn TRIT 102 a 112 a 108 a 107 a
Tyndal TRIT 102 a 108 abc 102 bc 104 bc
AC Andrew CWSWS 83 cd 87 efg 84 def 85 gh
AC Sadash CWSWS 86 bc 90 ef 88 d 88 e
Bhishaj CWSWS 86 bc 89 ef 87 d 87 ef
AC Barrie CWRS 91 b 99 cd 96 c 96 d
AC Superb CWRS 86 bc 92 de 87 d 88 e
Ashby CWGP 78 de 81 fg 81 efg 80 ijk
Chablis CWGP 78 de 83 efg 79 fg 80 jk
Chiraz CWGP 77 ef 81 fg 79 fg 79 k
Hoffman CWGP 101 a 110 ab 103 b 105 b
AC Vista CPS-W 83 cdf 90 def 86 de 86 efg
Snowhite475 CPS-W 83 bcde 85 efg 84 defg 84 fghi
5700PR CPS-R 77 e 82 g 80 g 80 k
AC Crystal CPS-R 80 de 87 efg 82 efg 83 hij
LSD(0.05)§ 3 4 2 2
Red¶ 83 90 86 89
White¶ 84 88 86 87
Triticale 101 108 104 105
P value <0.001 <0.001 <0.001 0.001
TRIT, spring triticale; CWSWS, Canada western soft white spring wheat; CWRS, Canada western red spring wheat; CWGP, Canada western general purpose candidate; CPS-W, Canada prairie spring white wheat; CPS-R, Canada prairie spring red wheat.
Means followed by the same letter in a column are not significantly different (P < 0.05; Bonferroni adjustment).
§LSD(0.05) can only be used to compare cultivar means.
Red includes CPS-R, CWRS, and CWGP (Hoffman); white includes CPS-W and CWSWS.

View Full Table | Close Full ViewTable 4.

Lodging means (on a scale of 1–9; 1 = erect, 9 = flat on the ground) for data collected in three agroecological zones across numerous locations in western Canada from 2006 to 2009.

 
Cultivar Class-ification† Lodging score
Western Prairies Eastern Prairies Parkland Overall
AC Ultima TRIT 2.1 abc‡ 1.5 a 1.3 a 1.6 abc
Pronghorn TRIT 2.2 abc 1.3 a 1.2 a 1.6 abc
Tyndal TRIT 1.8 abc 1.3 a 1.3 a 1.4 bc
AC Andrew CWSWS 1.5 bc 1.3 a 1.0 a 1.3 c
AC Sadash CWSWS 1.5 c 1.3 a 1.0 a 1.3 c
Bhishaj CWSWS 2.3 abc 1.7 a 1.4 a 1.8 ab
AC Barrie CWRS 2.1 abc 1.4 a 1.0 a 1.5 abc
AC Superb CWRS 1.7 bc 1.4 a 1.1 a 1.4 bc
Ashby CWGP 1.4 bc 1.1 a 1.0 a 1.2 bc
Chablis CWGP 1.9 abc 1.1 a 1.2 a 1.4 abc
Chiraz CWGP 2.1 abc 1.1 a 1.0 a 1.4 abc
Hoffman CWGP 2.7 a 1.8 a 1.7 a 2.1 a
AC Vista CPS-W 2.8 ab 1.5 a 1.5 a 1.9 abc
Snowhite475 CPS-W 2.2 abc 1.2 a
5700PR CPS-R 1.9 abc 1.3 a 1.1 a 1.4 bc
AC Crystal CPS-R 2.2 abc 1.3 a 1.1 a 1.5 bc
LSD(0.05)§ 0.6 0.7 0.6 0.3
Red¶ 2.0 # 1.6
White¶ 2.1 1.5
Triticale 2.0 1.5
P value <0.001 0.872 0.142 0.331
TRIT, spring triticale; CWSWS, Canada western soft white spring wheat; CWRS, Canada western red spring wheat; CWGP, Canada western general purpose candidate; CPS-W, Canada prairie spring white wheat; CPS-R, Canada prairie spring red wheat.
Means followed by the same letter in a column are not significantly different (P < 0.05; Bonferroni adjustment).
§LSD(0.05) can only be used to compare cultivar means.
Red includes CPS-R, CWRS, and CWGP (Hoffman); white includes CPS-W and CWSWS.
#Missing means indicate missing data or nonestimable functions.

View Full Table | Close Full ViewTable 5.

Aboveground biomass means collected in three agroecological zones across numerous locations in western Canada from 2006 to 2009.

 
Cultivar Class-ification† Mean aboveground biomass
Western Prairies Eastern Prairies Parkland Overall
Mg ha–1
AC Ultima TRIT 5.20 abc‡ 6.37 a 5.99 ab 5.85 abc
Pronghorn TRIT 5.32 ab 6.18 ab 6.14 a 5.88 ab
Tyndal TRIT 5.15 abc 6.04 ab 5.94 abc 5.71 abcd
AC Andrew CWSWS 4.75 abcd 6.16 ab 5.37 abcd 5.43 bcde
AC Sadash CWSWS 4.68 abcd 6.10 ab 5.25 abcd 5.34 cde
Bhishaj CWSWS 4.38 cd 5.92 ab 4.80 d 5.03 ef
AC Barrie CWRS 4.46 abcd 6.03 ab 5.19 abcd 5.22 abcdef
AC Superb CWRS 4.48 bcd 5.52 ab 4.90 d 4.97 ef
Ashby CWGP 4.18 bcd 4.55 ab 4.96 abcd 4.56 ef
Chablis CWGP 4.26 abcd 5.44 ab 4.86 abcd 4.85 def
Chiraz CWGP 3.74 d 5.05 ab 4.75 abcd 4.51 ef
Hoffman CWGP 5.46 a 6.09 ab 6.29 a 5.95 a
AC Vista CPS-W 4.35 abcd 5.10 ab 4.17 bcd 4.54 ef
Snowhite475 CPS-W
5700PR CPS-R 4.21 d 5.27 ab 4.77 d 4.75 f
AC Crystal CPS-R 4.11 d 5.11 b 4.92 cd 4.72 f
LSD(0.05)§ 0.52 0.99 0.74 0.45
Red¶ 4.36 5.38 5.08 5.10
White¶ 4.54 5.82 4.90 5.26
Triticale 5.22 6.20 6.02 5.81
P value <0.001 <0.001 <0.001 <0.001
TRIT, spring triticale; CWSWS, Canada western soft white spring wheat; CWRS, Canada western red spring wheat; CWGP, Canada western general purpose candidate; CPS-W, Canada prairie spring white wheat; CPS-R, Canada prairie spring red wheat.
Means followed by the same letter in a column are not significantly different (P < 0.05; Bonferroni adjustment).
§LSD(0.05) can only be used to compare cultivar means.
Red includes CPS-R, CWRS, and CWGP (Hoffman); white includes CPS-W and CWSWS.

View Full Table | Close Full ViewTable 6.

Grain yield means collected in three agroecological zones across numerous locations in western Canada from 2006 to 2009.

 
Cultivar Class-ification† Mean grain yield
Western Prairies Eastern Prairies Parkland Overall
Mg ha–1
AC Ultima TRIT 5.48 a‡ 5.12 ab 5.71 ab 5.44 a
Pronghorn TRIT 5.66 a 5.24 a 5.84 ab 5.58 a
Tyndal TRIT 5.11 abcd 4.66 abcd 5.39 bcd 5.05 bcd
AC Andrew CWSWS 5.49 a 4.78 abcd 5.78 ab 5.35 ab
AC Sadash CWSWS 5.50 a 4.74 abcd 6.14 a 5.46 a
Bhishaj CWSWS 5.46 a 4.84 abcd 5.81 ab 5.37 ab
AC Barrie CWRS 3.61 e 3.82 bcd 4.25 e 3.89 g
AC Superb CWRS 4.39 de 4.19 d 4.75 de 4.44 f
Ashby CWGP 5.33 abc 4.45 abcd 5.82 abc 5.20 abcd
Chablis CWGP 5.38 abc 4.71 abcd 5.86 abc 5.32 abc
Chiraz CWGP 4.54 bcde 4.00 abcd 5.38 abcd 4.64 def
Hoffman CWGP 5.27 ab 5.05 abc 6.06 a 5.46 a
AC Vista CPS-W 4.88 abcd 4.84 abcd 5.27 bcd 5.00 bcde
Snowhite475 CPS-W 4.82 abcde 4.35 abcd 5.14 bcde 4.77 cdef
5700PR CPS-R 4.51 cd 4.35 bcd 4.89 de 4.58 ef
AC Crystal CPS-R 4.66 bcd 4.28 cd 5.10 cd 4.68 def
LSD(0.05)§ 0.42 0.55 0.36 0.26
Red¶ 4.71 4.36 5.27 4.79
White¶ 5.23 4.71 5.63 5.39
Triticale 5.42 5.01 5.65 5.36
P value
Overall <0.001 <0.001 <0.001 0.010
Red vs. white <0.001 0.003 <0.001 <0.001
Triticale vs. red <0.001 <0.001 <0.001 <0.001
Triticale vs. white 0.498 0.068 0.004 0.539
TRIT, spring triticale; CWSWS, Canada western soft white spring wheat; CWRS, Canada western red spring wheat; CWGP, Canada western general purpose candidate; CPS-W, Canada prairie spring white wheat; CPS-R, Canada prairie spring red wheat.
Means followed by the same letter in a column are not significantly different (P < 0.05; Bonferroni adjustment).
§LSD(0.05) can only be used to compare cultivar means.
Red includes CPS-R, CWRS, and CWGP (Hoffman); white includes CPS-W and CWSWS.

View Full Table | Close Full ViewTable 7.

Kernel weight means collected in three agroecological zones across numerous locations in western Canada from 2006 to 2009.

 
Cultivar Class-ification† Mean kernel weight
Western Prairies Eastern Prairies Parkland Overall
g
AC Ultima TRIT 46.8 a‡ 42.7 a 45.2 a 44.9 a
Pronghorn TRIT 44.8 abc 41.3 ab 43.6 ab 43.2 bc
Tyndal TRIT 46.0 ab 42.4 a 44.8 a 44.4 ab
AC Andrew CWSWS 37.9 efh 34.0 egh 37.1 de 36.3 g
AC Sadash CWSWS 36.1 fhi 32.9 gh 35.3 ef 34.8 g
Bhishaj CWSWS 35.8 fhi 33.6 egh 35.2 ef 34.8 g
AC Barrie CWRS 35.9 fghi 35.1 cdegh 38.1 cde 36.4 g
AC Superb CWRS 40.9 e 37.4 cdf 40.5 c 39.6 def
Ashby CWGP 40.1 def 39.2 abcde 42.3 abc 40.5 def
Chablis CWGP 34.8 hi 32.8 efgh 35.8 ef 34.4 gh
Chiraz CWGP 32.2 i 30.3 h 32.9 f 31.8 h
Hoffman CWGP 44.3 abcd 41.2 a 45.1 a 43.6 ab
AC Vista CPS-W 41.6 cde 41.1 abc 41.2 bc 41.3 cd
Snowhite475 CPS-W 41.0 bcdef 40.3 abcd 42.1 abc 41.2 cde
5700PR CPS-R 40.3 e 37.6 bcdf 39.5 cd 39.2 ef
AC Crystal CPS-R 39.9 eg 36.3 deg 39.9 c 38.7 f
LSD(0.05)§ 1.9 2.4 1.6 1.2
Red¶ 38.5 36.2 39.3 40.3
White¶ 38.5 36.4 38.2 35.3
Triticale 45.9 42.1 44.5 44.2
P value <0.001 <0.001 <0.001 0.033
TRIT, spring triticale; CWSWS, Canada western soft white spring wheat; CWRS, Canada western red spring wheat; CWGP, Canada western general purpose candidate; CPS-W, Canada prairie spring white wheat; CPS-R, Canada prairie spring red wheat.
Means followed by the same letter in a column are not significantly different (P < 0.05; Bonferroni adjustment).
§LSD(0.05) can only be used to compare cultivar means.
Red includes CPS-R, CWRS, and CWGP (Hoffman); white includes CPS-W and CWSWS.

View Full Table | Close Full ViewTable 8.

Maturity means collected in three agroecological zones across numerous locations in western Canada from 2006 to 2009.

 
Cultivar Class-ification† Mean maturity
Western Prairies Eastern Prairies Parkland Overall
d
AC Ultima TRIT 115 abcd‡ 127 ab 123 bc 121 b
Pronghorn TRIT 117 a 127 ab 126 ab 123 a
Tyndal TRIT 118 a 128 a 127 a 124 a
AC Andrew CWSWS 115 abcd 125 ab 121 cdef 120 bc
AC Sadash CWSWS 115 abc 125 ab 123 cd 121 b
Bhishaj CWSWS 114 bcd 123 b 121 cdef 119 cd
AC Barrie CWRS 111 d 122 ab 120 cdef 118 cd
AC Superb CWRS 113 bcd 123 b 120 ef 119 cd
Ashby CWGP 118 a 127 ab 128 a 124 a
Chablis CWGP 117 ab 125 ab 124 abc 122 ab
Chiraz CWGP 115 abcd 123 ab 124 abc 120 bcd
Hoffman CWGP 116 ab 125 ab 123 bc 121 b
AC Vista CPS-W 112 cd 123 ab 119 def 118 d
Snowhite475 CPS-W 110 d 123 ab 118 f 117 cd
5700PR CPS-R 115 abcd 124 ab 122 cde 120 bc
AC Crystal CPS-R 113 bcd 124 ab 122 cd 120 bcd
LSD(0.05)§ 2 3 2 1
Red¶ 115 124 123 120
White¶ 113 124 120 120
Triticale 116 127 125 123
P value <0.001 <0.001 <0.001 0.023
TRIT, spring triticale; CWSWS, Canada western soft white spring wheat; CWRS, Canada western red spring wheat; CWGP, Canada western general purpose candidate; CPS-W, Canada prairie spring white wheat; CPS-R, Canada prairie spring red wheat.
Means followed by the same letter in a column are not significantly different (P < 0.05; Bonferroni adjustment).
§LSD(0.05) can only be used to compare cultivar means.
Red includes CPS-R, CWRS, and CWGP (Hoffman); white includes CPS-W and CWSWS.

View Full Table | Close Full ViewTable 9.

Cultivar response to fusarium head blight (FHB) infestation as mycotoxin deoxynivalenol (DON), fusarium-damaged kernels (FDK), and FHB index collected in an inoculated nursery in Charlottetown, PEI, from 2007 to 2009.

 
Cultivar Class-ification† DON
FDK
FHB index (0–100)
2007 2009‡ Overall 2007 2008 Overall 2007 2008 2009 Overall
μg g–1 % (w/w)
AC Ultima TRIT 22.9 abc§ 23.8 23.4 ab 14.0 ab 96.8 a 55.4 ab 11.7 a 31.0 a 21.0 ab 21.2 a
Pronghorn TRIT 13.9 c 45.6 29.7 ab 5.0 b 70.0 bc 37.5 c 5.0 a 15.0 b 5.3 c 8.4 d
Tyndal TRIT 15.5 c 25.1 20.3 b 6.5 b 64.7 c 35.6 c 7.3 a 24.7 ab 13.3 bc 15.1 abc
AC Andrew CWSWS 43.3 ab 56.3 49.8 a 27.4 ab 86.7 abc 57.1 ab 5.7 a 16.0 b 8.0 bc 9.9 cd
AC Sadash CWSWS 44.2 a 47.7 46.0 ab 26.8 ab 93.2 ab 60.0 a 7.3 a 16.0 b 7.7 bc 10.3 cd
Bhishaj CWSWS 31.5 abc 28.5 30.0 ab 22.7 ab 93.6 ab 58.2 ab 9.0 a 13.0 b 18.0 abc 13.3 bcd
AC Superb CWRS 13.8 bc 57.4 35.6 ab 28.4 ab 80.6 abc 54.5 ab 9.3 a 14.0 b 16.3 abc 13.2 bcd
Hoffman CWGP 25.8 abc 22.1 23.9 ab 18.5 ab 68.6 c 43.6 bc 6.3 a 13.3 b 6.3 c 8.7 cd
5700PR CPS-R 22.3 abc 46.7 34.5 ab 24.4 ab 68.6 c 46.5 abc 8.7 a 16.0 b 28.0 a 17.6 ab
AC Crystal CPS-R 26.4 abc 70.9 48.6 a 37.2 a 74.5 abc 55.8 ab 6.7 a 11.0 b 10.0 bc 9.2 cd
LSD(0.05)¶ 27.7 27.2 21.0 21.0 14.9 11.5 11.5 11.5 6.6
Red# 21.4 46.7 34.0 20.1 77.5 48.8 8.0 18.3 16.1 14.1
White# 20.2 37.0 28.6 19.2 79.6 49.4 8.6 17.2 15.9 13.9
Triticale 37.8 42.0 39.9 24.3 82.9 53.6 6.4 15.1 7.3 9.6
P value 0.002 0.018 <0.001 <0.001 0.038 0.692 <0.001 <0.001 <0.001
TRIT, spring triticale; CWSWS, Canada western soft white spring wheat; CWRS, Canada western red spring wheat; CWGP, Canada western general purpose candidate; CPS-W, Canada prairie spring white wheat; CPS-R, Canada prairie spring red wheat.
Data from the bulked composite of three replications; therefore, only means are reported for 2009.
§Means followed by the same letter in a column are not significantly different (P < 0.05; Bonferroni adjustment).
LSD(0.05) can only be used to compare cultivar means.
#Red includes CPS-R, CWRS, and CWGP (Hoffman); white includes CPS-W and CWSWS.

View Full Table | Close Full ViewTable 10.

Cultivar response to fusarium head blight (FHB) infestation as mycotoxin deoxynivalenol (DON) and FHB index collected in an inoculated nursery in Ottawa, ON, from 2007 to 2009.

 
Cultivar Class-ification† DON·
FHB index (0–100)
2007 2008 2009 Overall 2007 2008 2009 Overall
μg g–1
AC Ultima TRIT 17.9 bc‡ 33.1 ab 51.7 ab 34.2 bcd 75.0 a 33.3 bc 65.0 a 57.8 a
Pronghorn TRIT 11.1 c 20.2 b 19.6 b 17.0 e 8.3 c 13.0 d 21.3 c 14.2 e
Tyndal TRIT 18.4 bc 25.6 ab 39.7 ab 27.9 cde 41.7 b 40.0 bc 33.3 bc 38.3 c
AC Andrew CWSWS 19.4 abc 28.6 ab 58.5 ab 35.5 bc 41.7 b 38.3 bc 63.3 a 47.8 b
AC Sadash CWSWS 35.5 a 37.0 ab 79.9 a 50.8 a 65.0 a 46.7 b 36.7 bc 49.4 b
Bhishaj CWSWS 30.1 ab 48.7 a 66.1 ab 48.3 ab 76.7 a 31.7 bc 40.0 b 49.4 b
AC Superb CWRS 9.9 c 28.8 ab 40.2 ab 26.3 cde 30.0 b 36.7 bc 35.0 bc 33.9 c
Hoffman CWGP 17.8 bc 14.7 b 29.1 b 20.6 de 28.3 b 25.0 cd 21.7 c 25.0 d
5700PR CPS-R 16.3 bc 34.3 ab 49.2 ab 33.3 cd 41.7 b 40.0 bc 38.3 b 40.0 c
AC Crystal CPS-R 18.1 bc 30.2 ab 37.5 ab 28.6 cde 35.0 b 68.3 a 65.0 a 56.1 a
LSD(0.05)§ 13.5 21.2 38.4 14.3 11.3 13.2 13.1 6.5
Red¶ 15.5 27.0 39.0 27.2 33.8 42.5 40.0 38.8
White¶ 28.3 38.1 68.2 44.9 61.1 38.9 46.7 48.9
Triticale 15.8 26.3 37.0 26.4 41.7 28.8 39.9 36.8
P value 0.264 0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001
TRIT, spring triticale; CWSWS, Canada western soft white spring wheat; CWRS, Canada western red spring wheat; CWGP, Canada western general purpose candidate; CPS-W, Canada prairie spring white wheat; CPS-R, Canada prairie spring red wheat. ‡ Means followed by the same letter in a column are not significantly different (P < 0.05; Bonferroni adjustment).
§LSD(0.05) can only be used to compare cultivar means.
Red includes CPS-R, CWRS, and CWGP (Hoffman); white includes CPS-W and CWSWS.

For stem and straw characteristics, the triticales and Hoffman differed from most cultivars and classes (Tables 3–5). Overall, and in most agroecological zones, these cultivars were taller (at >100 cm) than the CPS red class and candidate cultivars Chablis, Chiraz, and Ashby by approximately 20% (Table 3). The tall attribute, however, also caused greater overall lodging for Hoffman and Pronghorn and other cultivars (Table 4). Straw accumulation (biomass) exceeded 6 Mg ha–1 in the humid E. Prairies and Parkland agroecological zones (Table 5). Similar to plant height, overall straw accumulation was greatest for the triticales and Hoffman, although the difference was not apparent in all agroecocological zones. The CPS red cultivars 5700PR and AC Crystal produced less biomass on average or were among the cultivars with the least straw accumulation for the W. Prairies and Parkland agroecological zones.

The triticale class always had grain yields that were among the greatest for all cultivars in all three agroecological zones (Table 6). Triticale yield was often greater than the hard red spring wheat classes but was always similar to the CWSWS class and Hoffman (Table 6). The triticale and white wheats produced 12 and 13% more grain, respectively, than the mean of the hard red spring wheats. Specifically, the overall yield of AC Ultima and Pronghorn exceeded that of the CWRS cultivars AC Barrie and AC Superb by an average of 32% and the CPS red cultivars 5700PR and AC Crystal by 18%. The other general purpose candidate cultivars, the CPS white wheat cultivars, and the triticale cultivar Tyndal displayed grain yield potential similar or intermediate to the highest yielding group. As a component of grain yield, the seed mass observed for the triticales and Hoffman was always among the group of cultivars with the heaviest seeds, and Chiraz was always among the group of cultivars with the least heavy seeds (Table 7). Bhishaj had similar kernel weight to Chiraz (within each agroecological zone) but had greater grain yield. This meant that other components of Bhishaj’s grain yield compensated for its smaller seed size relative to the higher yield group of cultivars. The superior grain yield observed for Pronghorn was partially a function of increased growing degree day requirements because it generally displayed the longest days to physiological maturity (Table 8). Tyndal, Hoffman, and the CWGP candidate lines Ashby and Chablis had similarly long maturity ratings when averaged across agroecological zones. The CWRS cultivar AC Barrie matured 5 to 6 d earlier than Pronghorn. AC Ultima required fewer days to maturity than Pronghorn and was similar to most of the CPS and CWSWS cultivars (Table 8).

For disease assessments, the cultivar effect was significant or highly significant for all diseases except FHB and the field severity index (FSI) in Charlottetown and DON assessments in Ottawa in 2007 (Tables 9–11). At both locations, Pronghorn, along with various other cultivars, generally displayed lower symptoms of FHB in the field (FSI rating) and lesser levels of FDK and DON in grain samples (Tables 9 and 10). The exception to this occurred at Charlottetown in 2009, where levels of DON for Pronghorn were similar to cultivars with greater DON levels. Hoffman and Tyndal also displayed lower symptoms, but differences compared with Pronghorn were less consistent. AC Ultima, unlike other triticales, was consistently prone to greater FHB infection in the field and in grain (Table 9). Pronghorn, Tyndal, and Hoffman also displayed lower levels of septoria and powdery mildew infection (Table 11). Pronghorn septoria and powdery mildew infections were consistently least along with a group of various cultivars, but Tyndal and Hoffman appeared more susceptible to both diseases in 2009. AC Ultima had septoria susceptibility similar to the red and white wheat cultivars (Table 11); however, AC Ultima, other triticales, and various other cultivars, also displayed less powdery mildew infection. There were no other notable responses observed, as the other cultivars displayed similar responses to FHB, septoria, and powdery mildew for most years at Ottawa and Charlottetown (Tables 10 and 11). Elevated symptoms for ergot occurred for all the triticales, with Pronghorn and Tyndal having greater ergot contamination than the hard red spring cultivars AC Barrie and 5700PR (data not shown). There were no class differences for ergot noted, as the lowest contamination was observed for Hoffman, Bhishaj, AC Vista, and AC Crystal, which represent three classes of wheat.


View Full Table | Close Full ViewTable 11.

Cultivar response to septoria and powdery mildew infestations collected from a field site in Charlottetown, PEI, in 2007 to 2009.

 
Cultivar Classification† Septoria
Powdery mildew
2007 2008 2009 Overall 2007 2008 Overall
% infection
AC Ultima TRIT 52.1 abc‡ 13.7 b 31.2 bc 32.4 bcd 4.2 b 0.0 a 2.1 b
Pronghorn TRIT 6.2 c 5.9 b 12.7 c 8.3 d 4.1 b 0.0 a 2.0 b
Tyndal TRIT 7.8 c 15.6 b 61.0 ab 28.1 cd 4.1 b 0.0 a 2.0 b
AC Andrew CWSWS 47.9 abc 35.2 ab 77.7 ab 53.6 ab 91.4 a 37.9 a 64.7 a
AC Sadash CWSWS 58.9 abc 15.6 b 83.1 a 52.5 abc 61.4 a 42.1 a 51.7 a
Bhishaj CWSWS 36.5 abc 74.4 a 93.4 a 68.1 a 77.1 a 47.9 a 62.5 a
AC Superb CWRS 60.4 abc 23.8 ab 91.1 a 58.4 a 56.0 a 20.0 a 38.0 a
Hoffman CWGP 9.4 bc 9.2 b 76.1 ab 31.6 bcd 4.7 b 0.0 a 2.3 b
5700PR CPS-R 63.5 ab 9.7 b 93.9 a 55.7 ab 86.9 a 13.4 a 50.2 a
AC Crystal CPS-R 86.7 a 45.8 ab 84.6 a 72.4 a 83.1 a 27.5 a 55.3 a
LSD(0.05)§ 45.4 45.4 39.3 25.1 43.8 43.8 31.0
Red¶ 52.1 18.8 55.6 42.2 44.6 10.2 27.4
White¶ 38.7 20.0 79.0 45.9 45.7 22.6 34.2
Triticale 34.9 37.9 81.9 51.6 52.5 26.7 39.6
P value <0.001 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001
TRIT, spring triticale; CWSWS, Canada western soft white spring wheat; CWRS, Canada western red spring wheat; CWGP, Canada western general purpose candidate; CPS-W, Canada prairie spring white wheat; CPS-R, Canada prairie spring red wheat.
Means followed by the same letter in a column are not significantly different (P < 0.05; Bonferroni adjustment).
§LSD(0.05) can only be used to compare cultivar means.
Red includes CPS-R, CWRS, and CWGP (Hoffman); white includes CPS-W and CWSWS.

Performance Stability and Variance

The random effect of site captured the variability among sites (location × year combinations) not explained by agroecological zones. The site × cultivar variance estimate was always highly significant (P < 0.01) (Table 12). For those cultivar responses where the site × cultivar variance estimate was significantly different from zero, the percentage of the total site variance accounted for by this interaction rarely exceeded 10%. The site × cultivar variance for lodging accounted for about 30% of the total variance associated with site.


View Full Table | Close Full ViewTable 12.

Variance estimates associated with the random effect of site (location × year combinations) for data collected across numerous locations in western Canada from 2006-2009.

 
Effect Variance estimate
Height Lodging Days to Maturity Aboveground biomass Yield Kernel wt.
Site 76.7** 0.522** 271** 6.86** 2.58** 37.8**
Site × cultivar 7.8** 0.234** 4** 0.20** 0.27** 4.9**
Site × cultivar, %† 9 31 2 3 10 11
**Significant at P < 0.01.
Percentage of the total variance associated with the effect of site.

Mean vs. CV biplots were used to explore and understand cultivar response variability relative to the mean responses (Fig. 2). The CPS white class tended to consistently mature in less time than the other classes, largely because of early and less variable days to maturity for the cultivar Snowhite475. The CPS red, CPS white, and CWRS classes were always positioned in lesser yielding (grain yield) categories relative to the triticales, the CWSWS cultivars, and Hoffman (Fig. 2). The red classes of wheat, especially CPS red, were more variable than the other classes (CWSWS, CPS white, triticale, and Hoffman), which were often positioned in the least variable quadrats. Biplots for aboveground biomass indicated two distinct groups, CPS white cultivars and other cultivars and classes (Fig. 2). The CPS white yield was always the least variable group, but moving from W. Prairies to Parkland there was a tendency for CPS white yield to decrease. Also, CPS red was in the lesser aboveground biomass yield quadrant, whereas Hoffman and the triticales were in the greater biomass producing quadrat. Pronghorn and the triticales, in general, produced high and stable levels of grain yield overall and in the E. Prairies and Parkland. There was greater variability observed in the W. Prairies, where the CWSWS cultivars and Hoffman produced consistently high grain yield (Fig. 2).

Fig. 2.
Fig. 2.

Biplot (mean on y axis vs. CV on x axis) summarized across and by agroecological zone for response variables of yield (Mg ha–1), aboveground biomass (Mg ha–1), and days to maturity in three agroecological zones collected at locations in western Canada from 2006 to 2009. In addition to cultivar estimates (filled circles), crop class estimates are also provided for, Canada western soft white spring wheat (CWSWS, star), Canada western red spring wheat (CWRS, ×), Canada prairie spring white wheat (CPS White, ▲), and Canada prairie spring red wheat (CPS Red, +). Grouping categories for each quadrat of biplot: Group I—high mean, low variability; Group II—high mean, high variability; Group III—low mean, high variability; Group IV—low mean, low variability.

 

A multivariate representation of the means was used to further explore associations among the cultivars and select response variables (Fig. 3). Multivariate representations for the W. Prairies and especially the Parkland ecological zone most closely corresponded with the representation across agroecological zones (Fig. 3). The representation for the E. Prairies indicated that the responses were more polarized than across agroecological zones. All variables deflected away from the origin in the same direction, which indicates that all variables in the biplot were growth related. There was also close association among all the agronomic variables and the cultivars Hoffman and the triticales. In all three agroecological zones and overall, these cultivars displayed greater growth and yield potential (height, kernel weight, aboveground biomass, and yield), but were slower to mature relative to the other cultivars. Additionally, AC Vista, Hoffman, AC Barrie, and Bhishaj in the E. Prairies often tended to lodge more than the other cultivars. The red class and corresponding cultivars tended to be the least productive (Fig. 3).

Fig. 3.
Fig. 3.

Biplot of agronomic responses of cultivars generated with multidimensional preference analysis for data collected at locations within three agroecological zones in western Canada from 2006 to 2009. The percentage of the variance explained by each component (x axis = first component and y axis = second component) is indicated on the respective axes.

 


DISCUSSION

The agronomic performance (responses for most variables) of triticale in this study can generally be summarized as triticale = CWSWS = Hoffman > CPS white > CPS red > CWRS. These findings correspond to other studies conducted in the Parkland and the southern region of Alberta, Canada (Beres et al., 2010; Goyal et al., 2011). For example, Beres et al. (2010) reported that Pronghorn yield exceeded the yield for the CPS red cultivar AC Crystal by 58% and CWRS cultivar AC Barrie by 40%. The magnitude of difference was even greater in the study of Goyal et al. (2011), who also reported that AC Ultima produced 65 and 44% more grain than the two respective wheat cultivars. The differences observed in the Parkland region reinforce the conclusions drawn from our study that Pronghorn, and the triticale class in general, produced maximum and stable grain yield in this region; however, greater instability for the triticales in the brown and dark brown soils of the W. Prairie region indicates poorer adaptation to lower organic matter soils and semiarid conditions. The margin of the yield advantage for triticales relative to CWRS and CPS red was not lower in our study, but it has been lower in other studies reporting results from brown and dark brown semiarid regions (Beres et al., 2010). The issue of instability may also relate to maturity; the onset of aridity in July in this region can be synchronous with the flowering period of triticales, as opposed to earlier maturing wheat classes that flower before the onset of aridity (Oettler, 2005).

The higher relative kernel weights for triticale observed in this study also agree with other contemporary studies (Beres et al., 2010; Goyal et al., 2011) where the importance for higher kernels per spike and kernel weight were identified as important yield components relative to spikes per plant or spikes per unit area (Beres et al., 2010). The lesser importance of the latter yield components may be attributed to lower relative tillering capacity. Reduced kernel weights and shriveled seed in triticale were identified as the cause for similar or even lower grain yield than wheat in earlier studies (Morey, 1979), which also caused higher levels of protein in triticales. Greater levels of protein may not be desirable in an ethanol feedstock because high starch content is preferred over protein concentration. The fact that kernel weights have been significantly improved in modern triticale germplasm is an indication that starch concentration in triticale may be comparable to wheat ethanol feedstocks (Collier et al., 2013).

Although there were some differences noted in the W. Prairie region, there was general consistency for most variables across agroecological zones. Moreover, the relatively small variance estimates for the site × cultivar effect indicated that the responses, for the most part, were consistent. A study assessing genotype × region interactions for two-row barley (Hordeum vulgare L.) in Canada also reported that there was no notable adaptation to subregions and that the responses across all of W. Canada were similar. In that study, regional adaptation did not appear until the area expanded to include eastern Canada in addition to western Canada (Atlin et al., 2000). Therefore, the agronomic potential of triticale that we observed probably would be observed in most of western Canada. The one exception would be straw strength or lodging. Lodging is generally sensitive to environmental variation, particularly to high precipitation or irrigated environments. Although tall in stature, the triticales did display good resistance to lodging in all agroecological zones. This is a critically important attribute because lodging could prolong maturity and slow harvesting operations, which would be a major production constraint in the short growing season of western Canada. Lodging could be an issue with the spring wheat cultivar Hoffman because it had weaker straw strength, which would detract from its high yield and biomass potential. Hoffman was not recommended for registration in western Canada in 2010 based on susceptibility to stem rust. Lodging and disease problems affecting Hoffman may ultimately mean that it will not be utilized as an ethanol feedstock in western Canada.

Implications for Ethanol Production

Similar to grains used as feed, the emphasis for ethanol production will be on low raw material costs with a high volume of supply. From an agronomic perspective, this requires a feedstock with stable and high yield potential with minimal crop input requirements. A yield benchmark of 7.4 Mg ha–1 has been established in the UK for wheat ethanol feedstocks (Smith et al., 2006). This level was not observed in our study, but comparable yield has been observed for spring and winter triticale in other reports (Beres et al., 2012a, 2010). The mean vs. CV biplots can be used as a proxy for risk assessment of ethanol feedstock production. The CPS red and CWRS cultivars were more variable and lower yielding, making them a less desirable feedstock from an agronomic perspective. In addition to the triticale cultivars AC Ultima and Pronghorn, Hoffman and CWSWS often were greater yielding with less variability. The maturity of triticales could pose a production risk in some areas because Tyndal and Pronghorn displayed consistently longer days to maturity; however, AC Ultima does not appear to pose any additional risk with regard to maturity over the CWSWS class, which is currently grown as an ethanol feedstock in all three agroecological zones.

The feature of high but variable biomass produced for triticales and Hoffman could be a benefit even in grain production. Multiple studies suggest that when differences due to cultivar height are evident, short cultivars tend to be less competitive than tall cultivars (Beres et al., 2010; Blackshaw, 1994; Harker et al., 2009; Lemerle et al., 2001; Mason et al., 2008). Mason et al. (2008) reported that the height of spring wheat cultivars accounted for a small amount of variation in low-weed environments but increased in importance as weed pressure increased. Bertholdsson (2005) reported that earlier crop biomass accumulation and potential allelopathic activity significantly contributed to the competitiveness of barley and wheat cultivars. Therefore, the increased competitive ability of tall triticales with lodging resistance may reduce the need for full herbicide applications, thereby reducing input costs and increasing net returns in an ethanol feedstock production system. Pesticide applications may be further reduced because disease resistance was often greater for triticales than wheats. Producers, however, prefer a short-stature plant type for ease of harvest (faster ground speeds with the harvester) and residue management. If yield is comparable to the CWSWS class, triticale production may not increase until the ecological benefit of increased competitiveness and reduced herbicides is fully appreciated. The advantages of triticale, therefore, may only be fully realized when a complete agronomic package is developed that includes improvements to the rate of genetic gain such that yield potential and ethanol production exceeds that of wheat. Newer cultivar releases of triticale in Canada carry improvements to ergot susceptibility and overall grain yield potential (Beres et al., 2012b; McLeod et al., 2012). Improved straw management practices for triticale are starting to occur that will augment the advantages from triticale. For example, producers in the west-central Great Plains are shifting to stripper-header harvesters that remove only the spikes of the plants at harvest in an effort to minimize soil erosion and evapotranspiration rates (Vigil et al., 2012).

In conclusion, triticale and CWSWS appear to have similar agronomic potential as an ethanol feedstock in major agroecological zones in western Canada. Furthermore, these conclusions may extend to other semiarid environments in the northern Great Plains. There is greater perceived risk, however, in growing triticale due to diseases such as ergot, a lack of information regarding the fermentation efficacy of triticale, and the fact that crop insurance programs in Canada will not ensure triticale at a rate similar to CWSWS (Keith Rueve, personal communication, 2011). Parity with respect to crop insurance programs and additional ethanol production data for triticale is needed to cause a paradigm shift of the ethanol feedstock area sown to CWSWS over to triticale. A companion study (Beres et al., 2013) addresses issues concerning ethanol production from a triticale feedstock in regions across Canada.

Acknowledgments

Special thanks to Craig Stevenson for statistical analyses of data presented in this manuscript, and to Ryan Dyck, Shannon Chant (Saskatchewan Ministry of Agriculture), Sheree Daniels, Ryan Beck, Dan Yagos, and Steven Simmill for trial coordination. The laborious nature of this work could not have been completed without the expertise provided by the technical teams at each of the author and co-author research facilities as well as the many applied research associations that participated in this project. This study was funded through Agriculture and Agri-Food Canada’s Agricultural Bioproducts Innovation Program, the Saskatchewan Agricultural Food Council, and Saskatchewan Ministry of Agriculture. This article is LRC Contribution no. 387-13023.

 

References

Footnotes


Comments
Be the first to comment.



Please log in to post a comment.
*Society members, certified professionals, and authors are permitted to comment.