Evaluation of CIMMYT conventional and synthetic spring wheat germplasm in rainfed sub-tropical environments. II. Grain yield components and physiological traits

Field Crops Research 124 (2011) 195–204

Contents lists available at ScienceDirect

Field Crops Research journal homepage: www.elsevier.com/locate/fcr

Evaluation of CIMMYT conventional and synthetic spring wheat germplasm in rainfed sub-tropical environments. II. Grain yield components and physiological traits A.R. Rattey a,∗ , R. Shorter a,b , S.C. Chapman a a b

CSIRO Plant Industry, 306 Carmody Rd., St Lucia, QLD 4067, Australia CSIRO Plant Industry, Cooper Laboratory, P.O. Box 863, University of Queensland, Warrego Highway, Gatton, QLD 4343, Australia

a r t i c l e

i n f o

Article history: Received 3 September 2010 Received in revised form 3 February 2011 Accepted 16 February 2011 Keywords: Adaptive traits Biomass Dry weight stem−1 Canopy temperature depression Grain weight Hexaploid wheat Breeding and selection

a b s t r a c t CIMMYT hexaploid spring wheat (Triticum aestivum L.) germplasm has played a global role in assisting wheat improvement. This study evaluated four classes of CIMMYT germplasm (encompassing a total of 273 lines), along with 15 Australian cultivars (Oz lines) for grain yield, yield components and physiological traits in up to 27 environments in Australia’s north-eastern region, where terminal drought frequently reduces grain yield and grain size. Broadly-adapted CIMMYT germplasm selected for grain yield had greater yield potential and improved performance under drought stress, being up to 5% greater yielding in High-yielding (mean yield 429 g m−2 ) and 4–10% greater yielding than adapted Oz lines in Low-yielding environments (mean yield 185 g m−2 ). Whilst maintaining statistically similar harvest index and spikes m−2 compared to broadly-adapted Oz lines across all environments, sets of selected CIMMYT lines had greater canopy temperature depression (0.18–0.27 ◦ C), dry weight stem−1 (0.20–0.37 g), increased grains spike−1 (0.8–3.4 grains), grain number m−2 (ca. 20–800 grains), and maturity biomass (56–83 g m−2 ). Compared to selected Oz lines, broadlyadapted CIMMYT lines had a smaller reduction in Low compared to High-yielding environments for these traits, especially dry weight stem−1 , such that CIMMYT lines had ca. 25% and 10% greater dry weight stem−1 than the Oz lines in Low- and High-yielding environment groups, respectively. Broadly-adapted CIMMYT germplasm also had slightly higher stem water soluble carbohydrate concentration at anthesis (ca. 6 mg g−1 ), which contributed to their higher grain weight (ca. 0.5 mg grain−1 ), and maintained an agronomically appropriate time to anthesis and plant height. Thus current CIMMYT germplasm should be useful donor sources of traits to enrich breeding programs targeting variable production environments where there is a high probability of water deficit during grain filling. However, as multiple traits were important, efficient introgression of these traits in breeding programs will be complex. Crown Copyright © 2011 Published by Elsevier B.V. All rights reserved.

1. Introduction For more than 40 years, the International Maize and Wheat Improvement Centre (CIMMYT) in Mexico has bred high-yielding wheat lines for developing countries, and was particularly recognised for its role in the widespread adoption of semi-dwarf wheats (Triticum sp.) and developments in disease resistance that lead to the green revolution (Reynolds and Borlaug, 2006). CIMMYT lines are widely grown in developing countries (Smale et al., 2002; Ortiz et al., 2008), but they also benefit developed countries including Australia (Brennan and Fox, 1998). In Australia, the contribution of CIMMYT germplasm has been greatest in the north-eastern wheat

∗ Corresponding author. Current address: CSIRO Plant Industry, Building 73, Clunies Ross St., Acton, ACT 2601, Australia. Tel.: +61 2 62465474; fax: +61 2 62465399. E-mail address: [email protected] (A.R. Rattey).

belt (Brennan and Quade, 2006) in line with the strong genetic correlations observed between this region and CIMMYT’s main station in northern Mexico compared to other locations in Australia (Mathews et al., 2007). The last comprehensive studies of adaptation in Australia of a broad range of CIMMYT lines were conducted during the late 1980s/early 1990s (Cooper et al., 1997), and this study evaluates many more recent selections. Wheat grown in Australia’s north-eastern region, where rainfall is summer dominant, is typically sown in May/June and grown predominately on stored soil moisture with low in-crop rainfall, so that crops frequently experience water deficit during the grain filling period (Chapman, 2008). Other spring-wheat environments that experience similar drought patterns during the grain filling period include those classified by CIMMYT’s megaenvironment system (Rajaram et al., 1994; Trethowan et al., 2005) as being in non-irrigated regions of ME1 and ME4c and semi-arid to arid regions of ME5. CIMMYT lines from the Seri/Babax (SB)

0378-4290/$ – see front matter. Crown Copyright © 2011 Published by Elsevier B.V. All rights reserved. doi:10.1016/j.fcr.2011.02.006

196

A.R. Rattey et al. / Field Crops Research 124 (2011) 195–204

cross (Olivares-Villegas et al., 2007) were higher-yielding in the north-eastern region than locally adapted Australian bred cultivars (Rattey et al., 2009; Rattey and Shorter, 2010). Conventional CIMMYT hexaploid spring wheat lines from the older International Adaptation Trial test (IAT, Mathews et al., 2007) and newer spring wheat (SW) nurseries were adapted to both High- and Lowyielding environments in the region, although the SW wheats had better adaptation to the lower-yielding environments than the older IAT wheats (Rattey and Shorter, 2010). In the same trials, higher-yielding synthetic hexaploid spring wheat (SYN) lines from CIMMYT exhibited specific adaptation to Low-yielding environments. The improved performance in lower-yielding environments of newer CIMMYT germplasm classes (SW and SYN) relative to older CIMMYT germplasm classes (IAT) supports CIMMYT’s emphasis on increased testing in rainfed or managed drought environments (Trethowan et al., 2005; Ortiz et al., 2007). Across a range of environments, high grain yield has been associated with changes in expression of a range of traits, most often improved harvest index (Austin et al., 1989; Slafer et al., 1994; Shearman et al., 2005). The contribution of increased aboveground biomass to grain yield improvement is less consistent; some reports have shown no correlation (Austin et al., 1989; Slafer et al., 1994), whilst other more recent studies have shown positive correlations (Donmez et al., 2001; Shearman et al., 2005; Rattey et al., 2009). Greater concentrations of water soluble carbohydrates (WSC) stored in stems have been associated with increased grain yield and/or grain weight in both stressed and non-stressed environments (van Herwaarden et al., 1998; Shearman et al., 2005; Rebetzke et al., 2008). A shorter time to anthesis also has been shown to increase grain yield in many terminal-stress environments (Angus and van Herwaarden, 2001; Donmez et al., 2001). Generally, global improvements in grain yield have not been associated with increased individual grain weight (Donmez et al., 2001; Shearman et al., 2005; Peltonen-Sainio et al., 2007). However, more recent CIMMYT germplasm, including conventional spring wheats such as Baviacora 92 (Sayre et al., 1997), derived synthetics (Singh et al., 2007) and lines from the Seri/Babax population (Rattey et al., 2009) have combined high grain yield with higher grain weight (i.e. average weight of single grains). The aims of this study were to compare (i) grain yield adaptation differences across High- and Low-yielding environments of CIMMYT and Australian germplasm classes reported by Rattey and Shorter (2010) in terms of grain yield components and physiological traits, and (ii) evaluate trait differences between SYN germplasm sets that differed in either numbers of backcrosses to a conventional spring wheat after creation of the primary synthetic line, or in origin of recurrent parents (CIMMYT or Australian). Traits and trait combinations associated with improved adaptation for the range of environments encountered herein will be discussed. Commonalities in pedigrees of lines with high expression of these adaptive traits and trait combinations will be identified so as to be useful during breeding activities targeting these environment types.

2. Materials and methods 2.1. Germplasm used, evaluation trials and traits measured Germplasm used in this study was described in detail by Rattey and Shorter (2010). Briefly, 273 lines originating from CIMMYT and introduced into Australia between 1999 and 2005 were grouped into four germplasm classes, with the first three classes being conventional hexaploid spring wheat: IAT, 22 lines selected following evaluation in multiple environments from the International Adaptation Trial test (Mathews et al., 2007) and considered herein to be of older CIMMYT origin; SW, 76 lines from seven CIMMYT

screening nurseries and selected from a single yield observation in north-eastern Australia and considered herein to be of newer CIMMYT origin; SB, 63 recombinant inbred lines chosen from the elite Seri/Babax population (Olivares-Villegas et al., 2007; Rattey et al., 2009), parental lines from this cross (Seri and Babax) were included in the IAT germplasm; and finally, SYN, 112 derivedsynthetic hexaploid spring wheat lines chosen from multiple series of targeted SYN introductions (Ogbonnaya et al., 2007) and CIMMYT screening nurseries based on limited yield trials conducted by CSIRO in the north-eastern region of Australia. The SYN lines were further partitioned in two ways: (a) by the number of crosses after creation of the primary synthetic line (one or two crosses, ≤SYN2, 68 lines versus three or more crosses, ≥SYN3+, 44 lines), or (b) origin of their pedigree (solely CIMMYT, SYN Cim, 41 lines versus those with an Australia parent used in the final cross, SYN Oz, 71 lines). In addition, 15 Australian cultivars (Oz lines) adapted to the north-eastern region were included. All Oz lines with the exception of EGA Stampede had been bred for both stringent milling grain quality and grain yield; EGA Stampede is a feed wheat bred for grain yield but not grain quality. As outlined by Rattey and Shorter (2010), grain yield (g m−2 ) data were collected from 27 environments spanning 4 years (2005–2008) and 12 locations across the north-eastern wheat belt of Australia. Standard crop management and fertiliser practices were followed at each trial with weed control applied as necessary. No fungicide was applied as foliar disease was not a factor in any of the trials. Data on single grain weight (grain weight, mg grain−1 ), screenings (percentage of grains passing through a 2 mm slotted screen) and grain number m−2 (estimated from grain yield and single grain weight) were also collected from all trials. In subsets of these environments, other trait data were collected (Table 1): time to anthesis (days) was recorded in 14 environments when 50% of spikes had anthers extruded (DC65 in the Zadoks et al. (1974) scale); plant height (cm) and grain protein (%) were measured in 17 and 18 environments, respectively. Bordered quadrat samples of 0.2–0.3 m2 were taken from each plot at maturity in 12 environments. These samples were then partitioned to estimate aerial biomass (maturity biomass, g m−2 ), dry weight stem−1 (g), grains spike−1 , harvest index and spike number m−2 . The water soluble carbohydrate concentration (WSC, mg g−1 dry weight) of aerial biomass samples at anthesis was estimated in seven environments by methods outlined in van Herwaarden et al. (1998). Canopy temperature depression (CTD, ◦ C) was determined by concurrently logging canopy temperature (CT, using a Micron infra-red thermometer) and ambient air temperature (AAT) and then estimated as CTD = CT − AAT. Across seven trials grown at four locations (one MET trial at Gatton in each of the years 2006–2008, Dalby (two trials in 2007), Billa Billa (one trial in 2007) and Duaringa (one trial in 2007), see Table 1 of Rattey and Shorter (2010) for more details), CTD was measured between once and five times per trial, for a total of 21 sets of observations. The CTD dataset was further partitioned into measurements taken during pre-anthesis (mid-vegetative stage to heading, 13 occasions), and post-anthesis (anthesis until prior to the initiation of leaf senescence, eight occasions) periods of crop growth. For all traits except WSC and CTD, data were collected from multiple location/year combinations within each of the Low-, Mediumand High-yielding environment groups assigned by Rattey and Shorter (2010). WSC data were collected only from the lowest- and highest-yielding environment groups (with four and three environments, respectively), whilst CTD data for lines were largely unbalanced between the highest-yielding environment group and the remaining environment groups. There was a strong association between the grain yield performance of sets of selected and discarded lines within each germplasm class for the Medium and High yielding environment groups (Fig. 1, Rattey and Shorter, 2010).

A.R. Rattey et al. / Field Crops Research 124 (2011) 195–204

197

Table 1 Overall mean, range among environment means, line (V(L)) and line × environment (V(LE)) variance components and line mean heritability for each trait from analyses across all lines and environments. All variance components are statistically different from zero at P = 0.01. Trait

Trait codea

Overall mean

Range among environments

V(L)

V(LE)

V(LE)/V(L)

h2

Anthesis (days) Canopy temp. depression (◦ C) Dry weight stem−1 (g)c Grains spike−1 Grain yield (g m−2 ) Harvest index Plant height (cm) Grain weight (mg) Maturity biomass (g m−2 ) Grain number (m−2 ) Spike number (m−2 ) Grain protein (%) Percent screenings WSC concentration (mg g−1 )

ant (14) CTD (21b ) DWstem (12) gps (12) gyp (27) hi (12) ht (17) kgw (27) mbi (12) mgn (27) msn (12) prot% (18) scr% (27) WSC (7)

92.8 0.87 1.96 40.1 313 0.39 79 30.3 883 10,605 278 13.8 5.8 130

81–105 0.32–2.29 1.27–2.82 24.6–50.7 109–662 0.31–0.48 63–101 20.3–39.6 447–1501 4475–25,127 167–409 11.7–16.1 1.5–15.1 84–217

3.9 0.04 0.05 11.4 121 0.0002 18.1 4.2 1120 495,707 679 0.19 1.6 83.9

3.2 0.08 0.01 12.6 276 0.0004 7.7 2.5 2744 503,264 511 0.10 1.6 66.8

0.8 2.1 0.3 1.1 2.3 2.1 0.4 0.6 2.5 1.0 0.8 0.5 1.0 0.8

0.77 0.51 0.74 0.57 0.61 0.36 0.84 0.90 0.27 0.78 0.55 0.84 0.84 0.46

a

The number of environments in which each trait was measured is provided in parenthesis. CTD was observed in seven trials for a total of 21 sets of observations. c During estimation of dry weight stem−1 , it was assumed that relative weight of rachis, awns (no awn-less lines were used in this study) and glumes to the remainder of the stem was relatively constant. This assumption was based on data from the Seri/Babax RIL population grown at Gatton in 2002, where the plot level correlation between dry weight stem−1 (estimated as described above) with a direct estimate of dry weight stem−1 at maturity (i.e. after removal of the spike) was 0.96 (P < 0.01) across 180 lines grown in a fully replicated trial (unpublished data). b

adaptation (selection based on means within their Low-, Mediumor High-yielding environment groups). Selection intensities were 50% for the IAT and Oz class (because of greater levels of previous selection in these classes), and 20–25% for the SB, SW and SYN classes. The final number of lines selected within each class was 11, 7, 16, 16 and 22 for the IAT, Oz, SB, SW and SYN classes, respectively. Means of traits considered in the present paper were calculated for the selected and discarded sets of lines in each germplasm class across all environments as well as within the Low- and Highyielding environment groups as defined in the current paper. Correlated selection response for each trait, following selection for grain yield, was estimated as 100 × [(trait mean of selected group − trait mean of all lines in the germplasm class)/trait mean of all lines in the germplasm class] (Falconer and Mackay, 1996). To avoid scale issues during estimation of correlated selection response for CTD, the weighted mean ambient air temperature across all observations (23.05 ◦ C), was added to observed CTD values. 2.2. Statistical analyses

Fig. 1. Biplot showing relationship among grain yield components and physiological traits with groups and selected and discarded sets of lines in each germplasm class across all environments. Note: see Table 1 for trait codes and units, and the number of environments in which each trait was measured; For each germplasm class, sets of selected and discarded lines are labelled (for example) IAT Sel and IAT Dis; the first and second principal components explained 32.7% and 23.8% of the total variation, respectively.

Consequently, in the present paper, the Medium- and High-yielding environment groups of Rattey and Shorter (2010) were pooled, and designated “High” to obtain an adequate level of assessment for each trait across these higher yield levels. The mean grain yields of these Low and High environment groups in the present paper were 185 and 429 g m−2 estimated from 13 and 14 environments, respectively. The number of environments where each trait was measured is given in Table 1. Within each germplasm class, Rattey and Shorter (2010) applied selection for grain yield to identify lines with broad adaptation (selection based on means across all environments) or specific

Data analyses were undertaken across environments by applying a two stage process as outlined by Welham et al. (2006), and described in detail by Rattey and Shorter (2010). Briefly, best linear unbiased estimates (BLUEs) were obtained for each line by environment combination using customised script within the R software system (R Development Core Team, 2006) with appropriate modelling of spatial field trends (Gilmour et al., 1997). These within-environment line BLUEs, accompanied by appropriate weights (Smith et al., 2001), were then used in a combined analysis across environments. A homogenous genetic variance–covariance model was used initially to estimate relevant variance components and calculate line-mean heritability, h2 (Hanson, 1963). Subsequently, heterogeneous genetic variance–covariance structures were used to obtain across environment best linear unbiased predictors (BLUPs), where the factor analytic model with one multiplicative term or the uniform correlation model were usually found to be the most parsimonious by the Akaike information criterion (Akaike, 1974). For each trait, the balance of lines across environments was around 30%, and 35–41% for grain protein, WSC and CTD. During analyses of germplasm class effects and of selected and discarded sets of lines within each germplasm class, classes were considered to be fixed effects and BLUEs estimated, whilst lines within

198

A.R. Rattey et al. / Field Crops Research 124 (2011) 195–204

Table 2 Trait means for all lines in each germplasm class from analyses across all environments. Traita

IAT

Oz

SB

SW

SYN

lsd (P = 0.05)

ant CTD DWstem gps gyp hi ht kgw mbi mgn msn prot% scr% WSC

93.2 (90.7–97.8) 1.02 (0.74–1.32) 2.07 (1.66–2.46) 42.7 (34.7–48.1) 315 (287–329) 0.39 (0.38–0.40) 79.2 (69.3–85.4) 30.2 (26.4–33.3) 881 (828–959) 10,511 (10,220–10,841) 266 (231–312) 13.8 (13.4–14.6) 5.84 (4.1–9.0) 129 (121–141)

92.6 (87.8–95.7) 0.70 (0.42–1.02) 1.64 (1.27–1.92) 37.8 (31.9–43.5) 308 (296–329) 0.39 (0.36–0.42) 75.8 (68.7–79.8) 29.1 (25.3–31.3) 843 (806–914) 10,677 (10,203–11,144) 297 (266–358) 14.0 (12.9–14.7) 5.94 (5.0–10.0) 120 (106–137)

93.2 (89.4–96.7) 0.98 (0.70–1.10) 1.94 (1.44–2.37) 42.2 (35.1–49.6) 321 (300–345) 0.40 (0.37–0.42) 78.3 (71.6–83.5) 29.8 (26.6–33.9) 886 (790–975) 10,874 (10,022–11,427) 282 (233–329) 13.6 (13.0–14.4) 5.99 (3.3–10.0) 133 (112–146)

92.9 (89.3–98.5) 0.90 (0.59–1.32) 2.04 (1.52–2.57) 40.0 (33.7–45.0) 313 (299–336) 0.38 (0.37–0.41) 79.9 (72.8–85.5) 30.5 (27.6–34.6) 874 (837–974) 10,347 (10,058–11,094) 265 (221–322) 13.8 (12.9–14.9) 5.64 (3.6–9.5) 132 (118–148)

93.0 (87.0–98.3) 0.88 (0.60–1.28) 1.95 (1.43–2.62) 38.6 (31.2–46.6) 306 (275–326) 0.38 (0.36–0.41) 79.1 (69.6–87.7) 30.3 (26.1–37.9) 877 (795–958) 10,229 (10,018–11,000) 280 (236–346) 14.1 (13.2–15.3) 5.78 (3.3–10.5) 130 (115–153)

0.6 0.18 0.11 2.1 7 0.01 1.3 0.5 46 284 19 0.2 0.35 8

Note: The range among lines within each germplasm class is provided in parenthesis; the germplasm class with highest and lowest trait value is indicated in bold or underline, respectively. a See Table 1 for trait codes and units, and the number of environments in which each trait was measured.

each class and any relevant line × environment interactions were simultaneously modelled as random effects. Where appropriate, environment group or crop growth stage effects were considered to be fixed effects and BLUEs were estimated, whilst lines and relevant line × environment interactions were simultaneously modelled as random effects. A principal component analysis (PCA) was carried out using mean selected and discarded BLUEs from analyses across all environments for ten traits in each germplasm class. A two-dimensional biplot (Gabriel, 1971) of the first two principal components then was constructed using the R software system (R Development Core Team, 2006). For ease of interpretation, four traits (anthesis, height, percent screenings and grain protein) where differences among the germplasm classes generally were small and/or not significant were excluded from the PCA.

3. Results 3.1. Trait means across all lines and environments There was a wide range in environment mean values for all traits, being greater than three-fold for CTD, maturity biomass, grain number m−2 and percent screenings; between two- and three-fold for dry weight stem−1 , grains spike−1 , grain weight, spikes m−2 and WSC; and less than one-fold for anthesis, harvest index, plant height and grain protein (Table 1). Variances among lines and for line x environment interactions were significant for all traits (Table 1). The relative magnitudes of V(LE) (line × environment interaction) and V(L) (line) variance components varied with trait, and were largest for CTD, grain yield, harvest index and maturity biomass. Across all environments, h2 was high to moderately high (≥0.5) except for harvest index, maturity biomass and WSC (Table 1). 3.2. Performance of germplasm classes across all environments When all lines in each germplasm class were considered, statistically significant (P < 0.05) differences existed among classes for all traits except days to anthesis, maturity biomass and percent screenings (Table 2). The Oz group had the lowest CTD, dry weight stem−1 , grains spike−1 , height, grain weight and WSC as well as having the highest spikes m−2 . The SB class had the highest grain yield, harvest index, grain number m−2 and WSC but the lowest grain protein. The IAT class had the highest CTD, dry weight stem−1 and grains spike−1 . The SW and SYN classes had the highest grain

weight but lowest harvest index and grain number m−2 . Overall, the SYN class also had the lowest mean grain yield. Generally for each trait the SB, SYN and SW germplasm classes had greatest within class genetic variance among lines, whilst the IAT and Oz germplasm classes had the smallest within class line variance (data not shown). This is consistent with previous selection histories of the classes. 3.3. Performance of selected germplasm sets and direct and correlated selection responses across all environments As reported by Rattey and Shorter (2010), selection for broad adaptation based on grain yield across all environments revealed that selected SB, SW and SYN lines (CIMMYT classes) had considerably higher mean grain yield than all lines within these classes (Table 3). Selected SB and SW lines were significantly higher yielding than selected Oz lines. Selected lines were similar for plant height (78.1–79.8 cm) and for time to anthesis (92.0–93.1 days), except for SW lines which were slightly earlier (Table 3). Over all environments, selected lines within CIMMYT classes tended to have higher CTD, dry weight stem−1 , grains spike−1 , maturity biomass, spikes m−2 , and WSC, as well as lower percent screenings and grain protein compared to the selected Oz lines (Table 3). Selected SB lines had greatest harvest index and greatest selection response for this trait, whilst selected SW lines had the highest mean maturity biomass (Tables 2 and 3). Selected SB and SW lines had the highest grain number m−2 and selected SYN and Oz lines the lowest. Selected SYN lines had the highest mean grain weight (31.1 mg g−1 ) among all classes which tended to offset their lower grain number m−2 and so resulted in a relatively high mean grain yield. For spike number m−2 , reflective of tillering, the Oz class had the highest population mean of all lines (297 m−2 ) and the SW class the lowest (265 m−2 ) (Table 2). However, class means of lines selected as broadly adapted were statistically similar for spike number m−2 (274–288 m−2 ) as the Oz class had a large negative correlated selection response (−7.8%) whilst all CIMMYT classes had a positive correlated selection response (Table 3). Direct selection response for grain yield and correlated selection responses in other traits following selection for grain yield, based on line BLUPs across all environments, is shown in Table 3 for the nominated selection intensities within each germplasm class. The greatest direct selection responses for grain yield were in the SW, SYN and SB classes (5.4, 4.7 and 4.5%, respectively), reflecting in part the higher genetic variance among lines in these classes which is consistent with the previous selection histories of the classes. For harvest index, correlated selection was positive in all germplasm

A.R. Rattey et al. / Field Crops Research 124 (2011) 195–204

199

Table 3 Mean trait values and selection response (% population mean)a across all environments for sets of lines selected as broadly-adapted for grain yield within each germplasm class. Traitb

ant CTDd DWstem gps gyp hi ht kgw mbi mgn msn prot% scr% WSC

Trait value

lsd (P = 0.05)

IAT

Oz

SB

SW

SYN

93.1 1.04 2.04 41.7 320 0.39 78.4 30.4 906 10,628 280 13.6 5.88 128

93.0 0.77 1.67 38.5 311 0.40 78.1 30.1 831 10,445.1 274 14.0 6.03 127

92.9 1.03 1.87 41.9 335 0.41 78.5 30.1 887 11,264 288 13.5 5.98 134

92.0 1.00 1.98 40.6 330 0.39 79.1 30.6 914 10,881.1 282 13.4 5.93 134

92.6 0.95 1.98 39.3 321 0.38 79.8 31.1 903 10,461.7 281 13.8 5.87 132

1.0 0.30 0.17 3.5 11 0.02 2.2 0.8 75 465 31 0.21 0.57 13

Selection responsec IAT

Oz

SB

SW

SYN

−0.1% 0.1% −1.8% −2.3% 1.7% −1.1% −1.0% 0.7% 2.9% 1.1% 5.0% −1.7% 0.7% −0.8%

0.4% 0.3% 2.0% 1.8% 1.2% 1.7% 3.0% 3.5% −1.4% −2.2% −7.8% 0.1% 1.6% 5.2%

−0.4% 0.2% −3.3% −0.6% 4.5% 4.0% 0.2% 0.9% 0.1% 3.6% 2.3% −1.2% −0.3% 1.0%

−1.0% 0.4% −2.8% 1.4% 5.4% 0.3% −1.1% 0.3% 4.5% 5.2% 6.4% −2.8% 5.2% 1.3%

−0.5% 0.3% 1.8% 1.8% 4.7% 0.8% 0.9% 2.5% 3.0% 2.3% 0.5% −2.1% 1.4% 1.7%

Note: The germplasm class with highest and lowest trait value is indicated in bold or underline, respectively; Large positive and negative (>±2%) selection responses are noted in bold or underline, respectively. a Estimated as 100 × (trait mean of selected lines − trait mean of all lines)/trait mean of all lines; selection intensity for grain yield was 50% for IAT and Oz classes; 25% for the SB class and 20% for the SW and SYN classes. b See Table 1 for trait codes and units, and the number of environments in which each trait was measured. c Direct selection response for grain yield and correlated selection response for other traits. d Selection response for CTD was estimated using observed CTD + 23.05 to take out scale effect.

classes except the IAT, and was greatest in the SB class. There were positive correlated responses in grain number m−2 , maturity biomass, and maturity spike number m−2 in all CIMMYT germplasm classes, but negative correlated responses for these same traits in the Oz class. The correlated response in CTD was positive yet small for all germplasm classes, and the Oz class had large correlated responses for WSC and plant height. For dry weight stem−1 , the IAT, SB and SW classes had fairly large negative correlated responses (≤−1.8%), whilst the Oz and SYN classes had fairly large positive correlated responses (≥1.8%). All classes had a positive correlated response for grain weight (0.3–3.5%), being largest for the Oz and SYN classes. Variation in trait performance between germplasm classes is shown graphically in Fig. 1, with the joint depiction of performance of germplasm sets selected or discarded for broad adaptation for grain yield and loadings of, and relationships among, ten traits over all environments. In this biplot, the first and second principal components accounted for 32.7 and 23.8% of total variation, respectively. For each germplasm class, the selected set had higher values for all traits than the discarded set (Fig. 1). The SB and SW selections had high maturity biomass and harvest index and so greater grain yields than the other selected sets. Selected SYNs had higher individual dry weight stem−1 and grain weight but lower grain number than most other CIMMYT selections. The selected Oz lines had lower CTD, dry weight stem−1 , grains spike−1 , maturity biomass and lower grain yield than all selected CIMMYT groups. Across all germplasm classes, grain yield has the strongest association with harvest index and maturity biomass, the two components of grain yield, whilst dry weight stem−1 and maturity spikes m−2 were negatively correlated with each other and neither trait was correlated with grain yield (Fig. 1).

3.4. Performance of selected germplasm sets in High- and Low-yielding environment groups SB and SW lines selected for broad adaptation had significantly higher grain yield than the broadly-adapted Oz lines within both High- and Low-yielding environment groups (Table 4). Broadlyadapted SYN lines tended to be relatively higher yielding in Low-

compared to High-yielding environment groups (Table 4 and as reported by Rattey and Shorter (2010)). Broadly-adapted Oz lines had the greatest reduction in grain yield, maturity biomass and physiological traits from High- to Lowyielding environments of all germplasm classes (Table 4). Selected Oz lines had the greatest number of mature spikes m−2 in the Highyielding environments, but the lowest number of mature spikes m−2 in the Low-yielding environments, although differences were not significant. Other physiological traits for which selected Oz lines had the greatest reduction were in dry weight stem−1 , grains spike−1 and grain weight from High- to Low-yielding environments (Table 4). Among the CIMMYT germplasm classes, the SB and SYN lines had the smallest reduction in maturity biomass and spikes m−2 from High- to Low-yielding environments, and the IAT lines had the smallest reduction in dry weight stem−1 and grains spike−1 from High- to Low-yielding environments. Dry weight stem−1 of all CIMMYT classes were fairly similar and ca. 25% and 10% higher than the selected Oz lines in Low- and High-yielding environment groups, respectively. In High-yielding environments, Oz lines had lower dry weight stem−1 , grains spike−1 , grain weight and maturity biomass and than the CIMMYT classes, although these differences between classes were frequently not significant. The SB, SW and IAT classes of selected lines tended to have relatively higher grains spike−1 (47.0–48.4) than Oz and SYN classes (44.9–45.2), whilst IAT and SW lines had the highest maturity biomass (1267–1282 g m−2 ) and Oz lines the lowest (1167 g m−2 ). Broadly-adapted SB lines had the highest grain number (15,063 m−2 ) and SYN lines the lowest (14,062 m−2 ) at the higher yield levels (Table 4). In Low-yielding environments, the SB class had the largest CTD (0.85 ◦ C), being significantly greater than that for the Oz class (0.40 ◦ C); other CIMMYT classes still had relatively high CTD (0.69–0.76 ◦ C) (Table 4). The SB and IAT classes had significantly higher grains spike−1 (36.3 and 36.7, respectively) than the Oz class (31.7) whilst SW and SYN classes were intermediate (33.9 and 33.3, respectively). In Low-yielding environments, the range among classes in grain number was much narrower (6739–7126 grains m−2 ) with the SYN class having the smallest reduction from High- to Low-yielding environments (Table 4).

94.7 0.69 1.67 33.3 195 0.38 69.5 29.3 567 6739 230 14.1 6.08 162

104% 98% 73% 74% 45% 99% 80% 91% 46% 48% 69% 104% 108% 178%

1.1 0.37 0.27 4.9 18 0.02 2.5 1.1 113 795 44 0.3 0.85 16.5

1.9 0.35 0.19 4.6 13 0.04 4.2 1.1 89 492 41 0.3 0.77 16.4

3.5. Partitioning of synthetic germplasm – all lines

Note: The germplasm class with lowest and highest reduction in trait value from High to Low yielding environments is indicated in bold or underline, respectively. a See Table 1 for trait codes and units, and the number of environments in which each trait was measured. b Relative value for CTD was estimated using observed CTD + 23.05 to take out scale effect.

91.2 1.28 2.29 45.2 435 0.39 86.9 32.2 1244 14,062 333 13.5 5.65 91.1 105% 98% 71% 72% 44% 96% 80% 92% 44% 47% 68% 104% 98% 183% 94.8 0.76 1.64 33.9 197 0.38 69.1 29.1 561 7038 230 13.6 6.01 165 90.4 1.32 2.31 47.0 452 0.39 85.9 31.7 1267 14,951 337 13.2 6.15 90.3 105% 98% 72% 75% 44% 97% 78% 93% 47% 47% 69% 105% 115% 186% 95.4 0.85 1.57 36.3 202 0.41 66.4 28.9 562 7126 231 13.7 6.44 167 90.7 1.31 2.19 48.4 457 0.42 84.8 31.2 1208 15,062 334 13.1 5.60 90.0 105% 97% 64% 70% 42% 97% 75% 89% 42% 46% 65% 106% 93% 199% 95.9 0.40 1.33 31.7 184 0.39 64.2 27.9 494 6854 221 14.3 5.80 159 ant CTDb DWstem gps gyp hi ht kgw mbi mgn msn prot% scr% WSC

104% 97% 75% 78% 43% 98% 79% 91% 43% 47% 66% 104% 110% 187% 95.8 0.74 1.72 36.7 192 0.39 67.4 28.8 553 6870 224 13.9 6.06 160 92.0 1.41 2.28 47.2 447 0.39 85.5 31.7 1282 14,580 339 13.4 5.51 85.3

91.3 1.19 2.05 44.9 435 0.41 85.2 31.2 1167 14,831 341 13.6 6.22 80.0

High Low High

SW

Low/High Low High

SB

Low/High High

Low Oz

High

Low/High Low IAT Traita

Table 4 Trait means for selected broadly adapted high yielding lines in each germplasm class from analyses within High and Low yield environment groups.

Low/High

SYN

Low

Low/High

High

Low

A.R. Rattey et al. / Field Crops Research 124 (2011) 195–204

lsd (P = 0.05)

200

Across all environments, SYNs with two or fewer doses of SW (SYN2) after creation of the initial primary synthetic had small but significantly greater grain yield, plant height and grain number m−2 , and were slightly quicker to anthesis (0.5%), with reduced grains spike−1 , harvest index and screenings than SYNs with three or more doses of SW (SYN3+) (Table 5). SYN2 lines also tended to have higher WSC than SYN3+ lines although the difference was not significant. Relative to SYN3+, SYN2 lines had lower trait expression in the Low- compared to the High-yielding environment groups for days to anthesis, dry weight stem−1 , grains spike−1 , percent screenings and WSC; the opposite trend was observed for plant height, grain number m−2 and spikes m−2 . In another partition, over all environments, SYNs with solely CIMMYT pedigree (SYN Cim) had significantly greater CTD, dry weight stem−1 grain yield, plant height, grain weight, maturity biomass and WSC, and significantly lower harvest index, grain number m−2 , spikes m−2 , percent screenings and grain protein than those SYNs with an Australian cultivar (SYN Oz) as a recurrent parent (Table 5). Relative to SYN Oz lines, SYN Cim lines had reduced grains spike−1 , WSC and grain protein in the Low- compared to the High-yielding environment groups; the opposite was observed for grain yield, plant height and spikes m−2 . 4. Discussion 4.1. Grain yield improvement Use of CIMMYT germplasm internationally has made large contributions to hexaploid wheat genetic gains via empirical breeding. In the period up until the mid 1980s, grain yield improvements from CIMMYT germplasm were largest in more favourable highpotential production environments, but over the past 15 years improving productivity in less favourable rainfed environments has received increased emphasis (Trethowan et al., 2005; Ortiz et al., 2007). The current CIMMYT wheat breeding strategy for drought-prone regions involves alternate screening and selection under water-stress and irrigation to improve adaptation in drier environments with the aim of retaining responsiveness to higher yielding conditions (Ortiz et al., 2007, 2008). This strategy increasingly involves incorporation of synthetic wheat germplasm to improve adaptation to drier environments (Trethowan et al., 2005), and the concurrent application of physiological breeding (Reynolds et al., 2009). For the selected broadly-adapted lines in the present study, mean grain yield advantages in a subset of 13 Low-yielding environments (mean yield 185 g m−2 ) of the CIMMYT classes of germplasm over the selected Oz class lines were almost twice as great (9.5, 7.2, 5.8, 4.1%) when compared to that in a subset of 14 High-yielding environments (5.0, 4.0, 0.1 and 2.9%, mean yield of 429 g m−2 ) for the SB, SW, SYN and IAT classes, respectively. Also, the large advantage of the selected SYN lines compared to the selected Oz lines in the Low- (5.8%) compared to the High- (0.1%) yielding environments reinforces the genetic potential of SYN wheats for improving productivity in lower-yielding environments. This suggests CIMMYT selection strategies and use of SYN germplasm targeting drought-prone regions globally appear to be potentially beneficial for Low-yielding, drought-stressed environments in northern Australia, similar to that previously documented in international environments (Trethowan et al., 2005). 4.2. Doses of spring wheat and their origin affected synthetic germplasm performance Previous results indicated that grain yield advantages of SYN lines compared to recurrent parents or local checks were due

A.R. Rattey et al. / Field Crops Research 124 (2011) 195–204

201

Table 5 Effect of partitioning of synthetic line group into number of crosses to a spring wheata or recurrent parent pedigreeb across all environments (“All”), and within low- (“Low”) or high- (“High”) yielding environment groups. Effect of SYN2/SYN3+a or SYN Cim/SYN Ozb is significantly different from 100% at *P = 0.05 and **P = 0.01. Traitc

ant CTDe DWstem gps gyp hi ht kgw mbi mgn msn prot% scr% WSC a b c d e

SYN2/SYN3+d

SYN Cim/SYN Ozd

All

Low

High

All

Low

High

99.5* 100.3 98.9 96.9* 101.3* 98.0* 103.8** 99.7 101.9 101.9* 102.6 99.7 95.8* 103.1

98.9** 100.2 97.5 93.4** 101.7* 97.7 107.8** 99.2 101.9 102.9* 104.7 99.5 93.4** 102.2

100.1 100.4 103.0 101.5 101.5 97.6* 102.6** 100.9 102.5 101.1 100.5 100.1 98.8 108.5*

99.7 100.8** 111.1** 98.5 102.3** 97.7* 106.7** 107.8** 103.9** 98.1* 96.6* 98.9* 96.1* 103.5*

99.5 100.6* 111.7** 94.4* 103.3** 97.5 110.9** 108.9** 105.3* 96.4** 97.9 97.6* 94.6* 101.9

100.1 100.9** 111.3** 103.3 100.5 98.1 105.4** 106.9** 103.4* 95.8** 94.3** 99.6 95.3* 107.0*

SYN2 is ≤2 crosses to a spring wheat after creation of primary synthetic hexaploids, SYN3+ is ≥3 crosses. SYN Cim or CSYN Oz means all CIMMYT or CIMMYT and Australian parents, respectively. See Table 1 for trait codes and units, and the number of environments in which each trait was measured. Ratio as a percentage. Relative value for CTD was estimated using observed CTD + 23.05 to take out scale effect.

to combinations of increased grain weight (Gororo et al., 2002), biomass (Reynolds et al., 2007a), spikes m−2 (Dreccer et al., 2008), WSC and attributes associated with water extraction characteristics such as CTD (Reynolds et al., 2007a; Dreccer et al., 2008). Comparison of SYN2 with SYN3+ (Table 5) indicates that the expected theoretical dilution of the Ae. tauschii genome in the initial primary synthetic via repeated crossing to SW’s had little effect on CTD and grain weight, which contrasts with some of these earlier reports. Additional doses of SW did, however, result in decreased grain yield, plant height, grain number m−2 and WSC (in High-yielding environments only) and a trend to decreased spikes m−2 and maturity biomass which is in agreement with the previous studies cited above. The trend towards increased maturity biomass in SYN2 compared to SYN3+ lines may have been related to greater plant height in SYN2, although this may also contribute to their lower harvest index. Thus these and previous results suggest SYN wheats could contribute positively towards improvements in grain yield, grain number m−2 and WSC, although this contribution potentially decreases with additional crossing to hexaploid spring wheats. In the present study, SYN Cim lines had higher CTD, maturity biomass, grain yield, grain weight and WSC but also were taller with lower harvest index than SYN Oz lines. This may be because Australian breeders select for an ideotype that is shorter with a higher harvest index and these traits were realised when Oz lines were used as recurrent parents in development of derived synthetics. These observations highlight the importance of the choice of locally adapted recurrent parents and possible linkage blocks that may impede the efficient introgression of favourable alleles from CIMMYT primary synthetics into Australian wheat breeding programs, as suggested by Rattey and Shorter (2010). SYN germplasm as a whole and SYN CIM germplasm in particular appear to be a useful source for improving grain weight across the range of environments tested herein. 4.3. Traits associated with grain yield improvement Grain yield is the phenotypic response of a genotype interacting with the environment (which encompasses the weather, soil type, crop management, etc.) in which it is grown and can be described as the product of maturity biomass and harvest index. Selection among SB lines for high grain yield resulted in a yield increase of 4.5% which was associated with little change in matu-

rity biomass (0.1%) but a 4% correlated response increase in harvest index (and effects on grain number and size). A similar result with a different set of SB lines was reported by Rattey et al. (2009) and among a historical set of CIMMYT lines by Sayre et al. (1997). In contrast, selection for grain yield in SW and SYN classes gave yield increases of 5.4 and 4.7%, respectively, but these were associated with positive correlated responses in maturity biomass (4.5 and 2.9%, respectively) and only a small change in harvest index (0.3 and 0.8%, respectively). Sayre et al. (1997) reported that more recently released High-yielding CIMMYT cultivars at that time such as Bacanora 88 and Baviacora 92 tended to have higher biomass than older lines. Donmez et al. (2001) and Shearman et al. (2005) reported that grain yield improvements in more recent cultivars were generally associated with increases in grain number m−2 , maturity biomass and spikes m−2 , whilst harvest index increases were more apparent in older cultivars. Herein, sets of CIMMYT lines selected to be broadly adapted for grain yield had positive correlated selection responses for these traits; 1.1–5.2% for grain number m−2 , 0.1–4.5% for maturity biomass and 0.5–6.4% for spikes m−2 , respectively. Conversely, the higher-yielding broadly adapted Oz lines showed negative correlated selection responses for these traits (−1.4, −2.2 and −7.8%, respectively) (Table 3). In irrigated conditions, greater CTD (cooler canopies) has been associated with increased stomatal conductance and increased grain yield (Fischer et al., 1998) and with increased biomass independent of physiological stage of the crop or time of day (Olivares-Villegas et al., 2007). In water-limited environments, cooler canopies may indicate increased rooting depth and ability to extract moisture from deeper soil profiles (between 60 cm and 120 cm, Reynolds and Condon, 2007; Lopes and Reynolds, 2010). In the present study, CIMMYT germplasm had greater CTD than selected broadly-adapted Oz lines in all environments, with this advantage being greatest in Low-yielding environments. The selected CIMMYT germplasm also had 12–15% higher biomass than Oz lines in Low-yielding environments and 4–10% in High-yielding environments (Table 4). Thus in the deep soils with substantial storage capacity of this cropping region, elevated CTD of CIMMYT lines could indicate an enhanced ability to extract more water from the soil than Oz lines, especially at depth. This contributed to their higher maturity biomass, particularly in Low- yielding environments. Partitioning of CTD data into pre- and post-anthesis growth stages revealed that across all lines, correlated selection response for CTD was greater in the post- compared to the pre-anthesis

202

A.R. Rattey et al. / Field Crops Research 124 (2011) 195–204

Fig. 2. Mean dry weight stem−1 (g) for broadlya adapted sets of lines from each germplasm class in Low- and High-yielding environment groups plotted against maturity biomass. a Selection based on analysis across all environments. Note: for ease of plotting, maturity biomass has been divided by two in the High yielding environment group; labels are (for example) performance of broadly selected IAT lines in Low (“IAT L”) and High (“IAT H”) yielding environment groups.

period (0.31 versus 0.12 ◦ C). However, other physiological mechanisms, such as stay-green (Christopher et al., 2008), could also be an important influence on post-anthesis CTD and grain yield. Reynolds et al. (2009) have advocated cooler canopy temperature as a trait that should be targeted during breeding and early-stage selection aimed at increasing genetic gain for grain yield in water limited environments. One issue limiting the application of this technology to breeding programs is a possible spurious correlation between CTD and plant height. Across all germplasm in the present study, there was a significant phenotypic correlation between CTD and plant height (r = 0.4 across all lines and r = 0.5 across the broadly-adapted selected germplasm, P < 0.01), consistent with previous results (Olivares-Villegas et al., 2007; Rebetzke, pers. comm.). In the present study, all germplasm were semi-dwarf with the range in plant height among lines in each class being relatively small (Table 2), and well within the suggested ideal height range of 70–100 cm for these environments (Richards, 1992). Thus although there was a significant positive correlation between CTD and plant height, it should be possible to select lines with cooler canopies that also had agronomically acceptable plant height. In early stages of selection where variation in plant height is often large, this could be achieved by first eliminating lines with poor agronomic type for plant height or other attributes and then selecting for elevated CTD. However, there remains an imperative need to separate the effects of CTD and plant height for the most effective use of CTD in small-plot breeding programs. Research investigating physiological and/or aerodynamic (e.g. “boundary layer”) aspects of this association between plant height and CTD estimated in smallplots is being undertaken within our group. In the present study across all environments, compared to the selected Oz lines, sets of selected CIMMYT germplasm had higher dry weight stem−1 (Table 3, Fig. 2) and statistically similar plant height and spike number m−2 (Table 3), i.e. selected CIMMYT lines had thicker stems compared to selected Oz lines. The higher dry weight stem−1 of the CIMMYT classes compared to the Oz class was particularly evident in the Low-yielding environments (19–30%) (Table 4). The higher dry weight stem−1 of selected sets of CIMMYT lines was associated with higher maturity biomass (Fig. 2) as well as CTD and grains spike−1 than that in Oz lines at both yield levels, with the advantages being greater at the Low- compared to High-yielding environments for all traits (Table 4). This may have contributed to the selected CIMMYT germplasm exhibiting greater grain yield stability in stressed Low-yielding environments relative to more favourable High-yielding environments when compared to selected Oz lines. Further, some classes of CIMMYT germplasm (namely the SB, SW and IAT groups) were still able to respond

favourably to High-yielding environments (Table 4, Rattey and Shorter, 2010). In wheat, grain yield improvements generally have been attained without any real change in grain weight (size) (Donmez et al., 2001; Shearman et al., 2005; Peltonen-Sainio et al., 2007). Among the broadly adapted CIMMYT lines selected for high grain yield, four of the top five lines for grain weight were selections from the Vorobey cross (pedigree CROC 1/AE.SQUARROSA (224)//OPATA/3/PASTOR), and their grain weight was 16–18% higher than the mean of seven broadly adapted Oz lines (data not shown). Herein we found that selection for grain yield resulted in a positive correlated improvement in grain weight for all germplasm classes, although these changes were small (<1.0%) for all but the SYN and Oz classes (Table 3). These findings support those of Sayre et al. (1997) and Singh et al. (2007), who found that more recent improvements in grain yield were accompanied by increased grain weight. Significant genetic variation for grain weight (27.1–34.2 mg grain−1 , data not shown) existed among broadly adapted CIMMYT lines, indicating that additional gains via targeted selection are possible. Rattey et al. (2009) identified for SB lines that increased CTD, dry weight stem−1 and WSC were associated with high grain yield combined with high grain weight in different sets of SB lines. These associations also were found to contribute to grain yield and grain weight across the broader set of lines studied here, which further supports other findings (Rebetzke et al., 2008). However, reduced tillering (indicated by spikes m−2 herein), identified by Rattey et al. (2009) as being advantageous, was associated with decreased grain yield in this broader set of CIMMYT germplasm and regional environments. 4.4. Potential contributions of CIMMYT germplasm to breeding programs These results demonstrate that lines from various CIMMYT germplasm classes should be useful donors for traits to enrich breeding programs targeting variable production environments where the probability of water deficit during the grain filling period is high. These environments are typical of north-eastern region of Australia, and correlated international environments such as nonirrigated regions in CIMMYT’s mega-environments (Rajaram et al., 1994) ME1, ME4c and semi-arid to arid regions of ME5. Traits to target during introgression activities would include CTD and dry weight stem−1 associated with improvements in yield potential and stability, maturity biomass and grains spike−1 , the latter contributing to high grain number m−2 and harvest index, as well as WSC, which contributes to harvest index and grain weight. The “culmination attributes” of harvest index and maturity biomass previously have been associated with grain yield improvements in many environments (Austin et al., 1989; Slafer et al., 1994; Sayre et al., 1997; Donmez et al., 2001; Shearman et al., 2005), and as such, may have been considered selection targets for wheat breeding programs. However, these traits had poorer heritability (Table 1) and were poorly correlated herein (Fig. 1); this poor correlation between harvest index and maturity biomass is consistent with other reports (e.g. Reynolds et al., 2007b; Rattey et al., 2009). Across the large range of environments examined herein, compared to maturity biomass and harvest index, traits CTD, dry weight stem−1 , grains spike−1 and WSC had higher line-mean heritability (Table 1), which should make them more amenable to selection activities within plant breeding programs targeting the variable range of production environments encountered herein. Despite elevated CTD, grains spike−1 , dry weight stem−1 and WSC appearing to be associated with higher grain yield of sets of selected CIMMYT lines compared to Oz lines in both Low- (especially) and High-yielding environments, across all environments the direct association of these traits individually with grain yield was not high (Fig. 1).

A.R. Rattey et al. / Field Crops Research 124 (2011) 195–204

Therefore, genetic gain for any of these traits individually may not be associated with grain yield improvements, and improvement at this point requires simultaneous changes in several traits. Of CIMMYT lines selected as being broadly-adapted for grain yield, the parents Babax and Pastor were heavily represented in pedigrees of those lines with large CTD and dry weight stem−1 , whilst several selections from the Vorobey cross also had large CTD. Further, Babax, Pastor and Seri M82 were heavily represented in pedigrees of broadly-adapted CIMMYT lines with high grains spike−1 and WSC concentration. Among the broadly-adapted, High-yielding CIMMYT lines identified in this study, it was rare for any one line to be elite for all desirable traits. Hence it may be necessary to undertake a ‘sidecar’ crossing program of selected CIMMYT lines with contrasting traits to develop better parents prior to introgression into adapted Australian germplasm, as utilised in CIMMYT’s breeding program (Reynolds et al., 2009). However, given that multiple donor traits, with their different line-mean heritabilities and direct associations with grain yield, need to be simultaneously improved, simple (Henderson, 1963) or restricted selection indices (Kempthorne and Nordskog, 1959; Pesek and Baker, 1969) may be required during selection among fixed lines. As discussed by Rattey and Shorter (2010) and highlighted in discussion surrounding the partition of SYN lines based on origin of pedigree (SYN Cim and SYN Oz), crossing between CIMMYT and Oz germplasm is likely to impact on favourable linkage groups in each germplasm class, which may impede genetic progress. Hence, pre-breeding introgression activities need to target key traits, and be combined with high-throughput phenotypic and/or genotypic screening methods to efficiently capture the favourable genes offered by donor germplasm. These trait introgression activities must also be balanced with the necessity of favouring economically important attributes (e.g. grain quality, rust resistance) and alleles underpinning these attributes offered by the recurrent parent for their efficient utilisation in breeding programs. Acknowledgements We thank Philip van Drie, Terry Collins, Kevin Niemeyer and Laura Barnes for their excellent technical assistance with aspects of these experiments. We also thank Greg Roberts for crop management during conduct of trials at the CSIRO Cooper Laboratory facilities, as well as Fernanda Dreccer and Steve Milroy for discussions and review comments. The assistance of staff from the Queensland Primary Industries and Fisheries in sowing and harvesting some trials under contract is also appreciated as is the support of farmers in providing land for on-farm trials. Our appreciation extends also to the CIMMYT and the CAIGE projects which imported this germplasm; the CAIGE projects are by funded by the Grains Research and Development Corporation of Australia (GRDC). This research was jointly funded by CSIRO and GRDC. References Akaike, H., 1974. New look at statistical-model identification. IEEE Trans. Autom. Control AC19, 716–723. Angus, J.F., van Herwaarden, A.F., 2001. Increasing water use and water use efficiency in dryland wheat. Agron. J. 93, 290–298. Austin, R.B., Ford, M.A., Morgan, C.L., 1989. Genetic improvement in the yield of winter wheat – a further evaluation. J. Agric. Sci. 112, 295–301. Brennan, J.P., Fox, P.N., 1998. Impact of CIMMYT varieties on the genetic diversity of wheat in Australia, 1973–1993. Aust. J. Agric. Res. 49, 175–178. Brennan, J.P., Quade, K.J., 2006. Evolving usage of materials from CIMMYT in developing Australian wheat varieties. Aust. J. Agric. Res. 57, 947–952. Chapman, S.C., 2008. Use of crop models to understand genotype by environment interactions for drought in real-world and simulated plant breeding trials. Euphytica 161, 195–208.

203

Christopher, J.T., Manschadi, A.M., Hammer, G.L., Borrell, A.K., 2008. Developmental and physiological traits associated with high yield and stay-green phenotype in wheat. Aust. J. Agric. Res. 59, 354–364. Donmez, E., Sears, R.G., Shroyer, J.P., Paulsen, G.M., 2001. Genetic gain in yield attributes of winter wheat in the great plains. Crop Sci. 41, 1412–1419. Cooper, M., Stucker, R.E., DeLacy, I.H., Harch, B.D., 1997. Wheat breeding nurseries, target environments, and indirect selection for grain yield. Crop Sci. 37, 1168–1176. Dreccer, M.F., Chapman, S.C., Ogbonnaya, F.C., Borgognone, M.G., Trethowan, R.M., 2008. Crop and environmental attributes underpinning genotype by environment interaction in synthetic-derived bread wheat evaluated in Mexico and Australia. Aust. J. Agric. Res. 59, 447–460. Falconer, D.S., Mackay, T.F.C., 1996. Introduction to Quantitative Genetics. Addison Wesley Longman Limited, Harlow, Essex. Fischer, R.A., Rees, D., Sayre, K.D., Lu, Z.M., Condon, A.G., Saavedra, A.L., 1998. Wheat yield progress associated with higher stomatal conductance and photosynthetic rate, and cooler canopies. Crop Sci. 38, 1467–1475. Gabriel, K.R., 1971. Biplot graphic display of matrices with application to principal component analysis. Biometrika 58, 453–467. Gilmour, A.R., Cullis, B.R., Verbyla, A.P., 1997. Accounting for natural and extraneous variation in the analysis of field experiments. J. Agric. Biol. Environ. Stat. 2, 269–293. Gororo, N.N., Eagles, H.A., Eastwood, R.F., Nicolas, M.E., Flood, R.G., 2002. Use of Triticum tauschii to improve yield of wheat in low-yielding environments. Euphytica 123, 241–254. Hanson, W.D., 1963. Heritability. In: Hanson, W.D., Robinson, H.F. (Eds.), Statistical Genetics and Plant Breeding. National Academy of Sciences – National Research Council Publication 982, Washington, DC, pp. 125–139. Henderson, C.R., 1963. Selection index and expected genetic advance. In: Hansen, W.D., Robinson, H.F. (Eds.), Statistical Genetics and Plant Breeding. National Academy of Sciences – National Research Council Publication 982, Washington, DC, pp. 141–163. Kempthorne, O., Nordskog, A.W., 1959. Restricted selection indices. Biometrics 5, 10–19. Lopes, M.S., Reynolds, M.P., 2010. Partitioning of assimilates to deeper roots is associated with cooler canopies and increased yield under drought in wheat. Funct. Plant Biol. 37, 147–156. Mathews, K.L., Chapman, S.C., Trethowan, R., Pfeiffer, W., Ginkel, M., Crossa, J., Payne, T., DeLacy, I., Fox, P.N., Cooper, M., 2007. Global adaptation patterns of Australian and CIMMYT spring bread wheat. Theor. Appl. Genet. 115, 819–835. Ogbonnaya, F.C., Ye, G.Y., Trethowan, R., Dreccer, F., Lush, D., Shepperd, J., van Ginkel, M., 2007. Yield of synthetic backcross-derived lines in rainfed environments of Australia. Euphytica 157, 321–336. Olivares-Villegas, J.J., Reynolds, M.P., McDonald, G.K., 2007. Drought-adaptive attributes in the Seri/Babax hexaploid wheat population. Funct. Plant Biol. 34, 189–203. Ortiz, R., Braun, H.J., Crossa, J., Crouch, J.H., Davenport, G., Dixon, J., Dreisigacker, S., Duveiller, E., He, Z.H., Huerta, J., Joshi, A.K., Kishii, M., Kosina, P., Manes, Y., Mezzalama, M., Morgounov, A., Murakami, J., Nicol, J., Ferrara, G.O., Ortiz-Monasterio, J.I., Payne, T.S., Pena, R.J., Reynolds, M.P., Sayre, K.D., Sharma, R.C., Singh, R.P., Wang, J.K., Warburton, M., Wu, H.X., Iwanaga, M., 2008. Wheat genetic resources enhancement by the International Maize and Wheat Improvement Center (CIMMYT). Genet. Resour. Crop Evol. 55, 1095–1140. Ortiz, R., Trethowan, R., Ferrara, G.O., Iwanaga, M., Dodds, J.H., Crouch, J.H., Crossa, J., Braun, H.J., 2007. High yield potential, shuttle breeding, genetic diversity, and a new international wheat improvement strategy. Euphytica 157, 365–384. Peltonen-Sainio, P., Kangas, A., Salo, Y., Jauhiainen, L., 2007. Grain number dominates grain weight in temperate cereal yield determination: evidence based on 30 years of multi-location trials. Field Crops Res. 100, 179–188. Pesek, J., Baker, R.J., 1969. Desired improvement in relation to selection indices. Can. J. Plant Sci. 49, 803–804. R Development Core Team, 2006. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Rajaram, S., Van Ginkel, M., Fischer, R.A., 1994. CIMMYT’s wheat breeding megaenvironments (ME). In: Proceedings of the 8th International Wheat Genetics Symposium, Beijing, People’s Republic of China, pp. 1101–1106. Rattey, A., Shorter, R., 2010. Evaluation of CIMMYT conventional and synthetic spring wheat germplasm in rainfed sub-tropical environments. I. Grain yield. Field Crops Res. 118, 273–281. Rattey, A., Shorter, R., Chapman, S., Dreccer, F., van Herwaarden, A., 2009. Variation for and relationships among biomass and grain yield component traits conferring improved yield and grain weight in an elite wheat population grown in variable yield environments. Crop Pasture Sci. 60, 717–729. Rebetzke, G.J., van Herwaarden, A.F., Jenkins, C., Weiss, M., Lewis, D., Ruuska, S., Tabe, L., Fettell, N.A., Richards, R.A., 2008. Quantitative trait loci for water-soluble carbohydrates and associations with agronomic traits in wheat. Aust. J. Agric. Res. 59, 891–905. Reynolds, M.P., Borlaug, N.E., 2006. Impacts of breeding on international collaborative wheat improvement. J. Agric. Sci. 144, 3–17. Reynolds, M.P., Condon, A.G., 2007. Quantifying potential genetic gains in wheat yield using a conceptual model of drought adaptation. Wheat production in stressed environments. In: Buck, H.T., Nisi, J.E., Salomon, N. (Eds.), Proceedings of the 7th International Wheat Conference, 27 November–2 December 2005, mar del Plata, Argentina. Springer, Dordrecht, The Netherlands, pp. 331–340. Reynolds, M., Dreccer, F., Trethowan, R., 2007a. Drought-adaptive traits derived from wheat wild relatives and landraces. J. Exp. Bot. 58, 177–186.

204

A.R. Rattey et al. / Field Crops Research 124 (2011) 195–204

Reynolds, M., Saint Pierre, C., Saad, A., Vargas, M., Condon, A.G., 2007b. Evaluating potential genetic gains in wheat associated with stress-adaptive trait expression in elite genetic resources under drought and heat stress. Crop Sci. 47, 174–189. Reynolds, M., Manes, Y., Izanloo, A., Langridge, P., 2009. Phenotyping approaches for physiological breeding and gene discovery in wheat. Ann. Appl. Biol. 155, 309–320. Sayre, K.D., Rajaram, S., Fischer, R.A., 1997. Yield potential progress in short bread wheats in northwest Mexico. Crop Sci. 37, 36–42. Richards, R.A., 1992. The effect of dwarfing genes in spring wheat in dry environments. I. Agronomic characteristics. Aust. J. Agric. Res. 43, 517–527. Shearman, V.J., Sylvester-Bradley, R., Scott, R.K., Foulkes, M.J., 2005. Physiological processes associated with wheat yield progress in the UK. Crop Sci. 45, 175–185. Singh, R.P., Huerta-Espino, J., Sharma, R., Joshi, A.K., Trethowan, R., 2007. High yielding spring bread wheat germplasm for global irrigated and rainfed production systems. Euphytica 157, 351–363. Slafer, G.A., Satorre, E.H., Andrade, F.H., 1994. Increases in grain yield in bread wheat from breeding and associated physiological changes. In: Slafer, G.A. (Ed.), Genetic Improvement of Field Crops. Marcel Dekker Inc., New York, pp. 1–68.

Smale, M., Reynolds, M.P., Warburton, M., Skovmand, B., Trethowan, R., Singh, R.P., Ortiz-Monasterio, I., Crossa, J., 2002. Dimensions of diversity in modern spring bread wheat in developing countries from 1965. Crop Sci. 42, 1766– 1779. Smith, A., Cullis, B., Gilmour, A., 2001. The analysis of crop variety evaluation data in Australia. Aust. N. Z. J. Stat. 43, 129–145. Trethowan, R., Hodson, D., Braun, H.J., Pfeiffer, W.H., 2005. Wheat breeding environments. In: Dubin, M.A.L., Morris, M.L. (Eds.), Impacts of International Wheat Breeding Research in the Developing World, 1988–2002. CIMMYT, Mexico, DF, pp. 4–11. van Herwaarden, A.F., Angus, J.F., Richards, R.A., Farquhar, G.D., 1998. ’Haying-off’, the negative grain yield response of dryland wheat to nitrogen fertiliser – II. Carbohydrate and protein dynamics. Aust. J. Agric. Res. 49, 1083–1093. Welham, S.J., Gogel, B.J., Smith, A.B., Thomson, R., Cullis, B., 2006. Evaluation of models for late-stage variety evaluation trials. In: Australasian GenStat/StatGen Conference, Victor Harbour, Australia, p. 44. Zadoks, J.C., Chang, T.T., Konzak, C.F., 1974. A decimal code for the growth stages of cereals. Weed Res. 14, 415–421.