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a CSIRO Plant Industry, P.O. Box 1600, Canberra ACT 2601 Australia
b Australian National Univ., P.O. Box 475, Canberra ACT 2601 Australia
* Corresponding author (G.Rebetzke{at}pi.csiro.au)
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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) in wheat (Triticum aestivum L.) suggest that selection of progeny with low may increase TE and aerial biomass under water-limited conditions. This study investigated how early generation, divergent selection for affected aerial biomass and grain yield among 30 low- and 30 high-, ‘Hartog’-like, BC2F4:6 progeny and the recurrent, high- parent Hartog. Lines were evaluated in nine environments varying for seasonal rainfall (235–437 mm) and hence grain yield (1.3–6.2 Mg/ha). Selection for low in early generation progeny was associated with significantly (P < 0.01) smaller , higher grain yield (+5.8%), aerial biomass (+2.7%), harvest index (+3.3%), and kernel size (+4.8%) in tested lines. Kernel number was the same for low- and high- selected groups. Grain yield advantage of the low group increased with reductions in environment mean yield (r = -0.89, P < 0.01) and total seasonal rainfall (r = -0.85, P < 0.01) indicating the benefit of low , and therefore high TE for genetic improvement of grain yield in lower rainfall environments. Narrow-sense heritability on a single-plot basis was much greater for (h2 = 0.63 ± 0.10) than for either aerial biomass (0.06 ± 0.05) or grain yield (0.14 ± 0.04). Strong genetic correlations between and both aerial biomass (r g = -0.61 ± 0.14) and grain yield (-0.58 ± 0.12) suggest could be used for indirect selection of these traits in early generations. Selection of low (high TE) families for the advanced stages of multiple-environment testing should increase the probability of recovering higher-yielding wheat families for water-limited environments. |
INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Genetic gain in grain yield may be achieved through targeting traits closely associated with improved plant adaptation to stress. A number of characteristics have been proposed as indirect selection criteria for genetic improvement of drought resistance in a breeding program (e.g., Ludlow and Muchow, 1990). Some characters enable plant survival under drought, while others afford temporal protection at critical periods in crop development (Richards, 1996). Although these characteristics may protect plants from dehydration stress, they may not improve yield under drought. Genotypic increases in wheat yields under drought should be associated with increases in aerial biomass (Fischer and Wood, 1979). Greater water use efficiency (WUE as aerial biomass/total water use) should provide more biomass for crops growing in water-limited conditions (Passioura, 1977). Transpiration efficiency (TE as aerial biomass/water transpired) is an important component of crop WUE especially in regions where stored soil water is a major component of crop water use (Condon and Richards, 1992). Repeatable genetic variation has been reported for TE in wheat (Condon et al., 1990; Ehdaie et al., 1991; Malik et al., 1999), yet its direct use for breeding has been constrained by the lack of a suitable screening methodology in large segregating populations.
Carbon isotope discrimination () is correlated negatively with TE in wheat (Farquhar and Richards, 1984; Ehdaie et al., 1991) and in other C3 species (see Hall et al., 1996). Selection for low may provide a useful method for indirect selection of TE and perhaps biomass and grain yield in cereal breeding programs for water-limited environments (Hall et al., 1996; Voltas et al., 1999). Plant has many features that make it desirable for implementation in a breeding program targeting increased yield. For example, leaf integrates TE over the period for which leaf tissue is formed, leaf tissue can be sampled rapidly on a large number of families, and repeatability for is high for leaf tissue formed in the absence of moisture stress (Condon and Richards, 1992).
Genotypic selection for low shows potential for improvement of TE of wheat (see Hall et al., 1996), yet its utility for indirect improvement of grain yield in an applied breeding program has not been investigated. The effectiveness of correlated genetic gain requires that the secondary trait have both a high narrow-sense heritability and strong additive genetic correlation with the primary trait (Falconer and Mackay, 1996). Previous reports for broad-sense heritability of in wheat were high when expressed on an entry-mean basis (Ehdaie et al., 1991; Condon and Richards, 1992). Phenotypic correlations between and grain yield are typically high (Condon and Richards, 1993), and either positive or negative, depending on the plant tissue analyzed and the yield potential of environments sampled. The objective of this study was to assess the effect of selection for on aerial biomass and grain yield in a backcross-derived population developed from a commercial wheat variety and divergently selected in early generations for low and high .
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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cultivar Quarrion (PI 483063) was crossed in 1991 to the high- cultivar Hartog (PI 483052). Hartog is a grain quality reselection from ‘Pavon F76’ (PI 519847) (P. Brennan pers. comm., 1999). The F1 and harvested F2 seed were sown in the glasshouse in 1991. Two hundred resulting F2:3 families were sown with both parents in hills in a two-replicate, randomized complete block design (RCBD) at Condobolin, NSW, in May 1992. Soil moisture conditions up to, and including, the time of sampling were favorable for plant growth.
Leaf laminas of all plants in each hill were harvested at commencement of stem elongation and dried at 70°C for 3 d. Dried samples were ground to pass a 1-mm sieve and the carbon isotope composition of each family determined by mass spectrometry (Farquhar et al., 1989). The ratio of 13C/12C was expressed relative to that in carbon dioxide in the air to give , after Farquhar et al. (1989). The six families producing the smallest (18.7 ± 1.7
for the mean of the six families, cf. 18.9 ± 0.2 and 19.7 ± 0.2 for Quarrion and Hartog, respectively) were used as males in backcrossing to Hartog. Harvested BC1F1 seed was sown in the glasshouse in 1992 and a second backcross to Hartog was made. Harvested BC2F1 seed was sown in the glasshouse in 1993 to produce BC2F1:2 seed. The BC2F1:2 seed and Hartog were sown in 10-cm-deep trays in 1993 and BC2F2:3 seed harvested from all plants excepting those that differed from Hartog for plant height and anthesis date. One hundred selected BC2F2:3 families were advanced in the field to produce BC2F2:4 bulks. The BC2F2:4 bulks were sown at Condobolin, NSW, in a replicated study in 1994. All families were assessed as previously for , and at maturity, 9 to 12 plants were harvested at random from selected low- (= 17.1, 
G = 5.2) and high- (= 18.3, G = 4.8) bulks. These BC2F4:5 lines were sown as separate rows in a summer nursery, and the 30 highest-yielding, low- and 30 highest-yielding, high- families resembling Hartog for height and anthesis date selected to produce 60 BC2F4:6 lines for subsequent testing.
Experimental Conditions
The 30 low- and 30 high-, BC2F4:6 lines, and recurrent parent Hartog were sown into replicated plots in Australia at Condobolin, Moombooldool, and Wagga Wagga in NSW and Ginninderra Experiment Station, ACT, in 1995, 1996, 1997 and 1998 (Table 1). Plots at all sites were 6 m long and 10 rows wide with rows spaced at 0.18 m apart, except at Wagga Wagga where plots were 8 rows wide. Seeding rate was 150 (Moombooldool, Condobolin, Ginninderra) and 160 (Wagga Wagga) seeds m-2. A commercial fertilizer was applied which supplied adequate nutrients for crop growth in each environment. Crops relied on pre- and within-growing season rainfall at all sites except Ginninderra where two supplemental 25 mm irrigations were supplied during grain filling. Sowings were maintained as free of weeds and diseases as possible with appropriate application of herbicides and fungicides. Experimental design at each site was a RCBD with two replications of all lines except Hartog where four replications were augmented in each block.
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of each line was determined using mass spectrometry for leaf-lamina samples collected at commencement of stem elongation from five random environments (Condobolin 1996, Wagga Wagga 1996 and 1997, and Moombooldool 1997 and 1998). Anthesis date was recorded at all sites, and plant height determined at maturity as the distance from the soil surface to the top of the spike (awns excluded) of the tallest culms for each plot. Between 200 and 300 culms were hand-harvested at maturity, dried at 35°C for 3 d and then weighed before threshing. Harvest index of these culms was calculated as the ratio of grain to total culm weight. Plots were end-trimmed to approximately 5 m and the outside border rows removed before machine harvesting to obtain plot grain yields. Aerial biomass was then calculated as grain yield/harvest index. Kernel weight was determined for a 200-seed sample from each plot, and kernel number (m-2) estimated as grain yield/kernel weight.
Statistical and Genetic Analysis
Data were first subject to tests of homogeneity of error variance by the Fmax procedure of Sokal and Rohlf (1994). The relative ratio of the highest to lowest error mean square across environments was about 1 to 2 for all characteristics so data were not transformed. Combined analyses of variance and covariance across environments were performed by the multivariate analysis of variance option, MANOVA, of the SAS Generalized Linear Models procedure GLM (SAS, 1990). Statistical differences between low- and high- group means, and their comparison with the recurrent parent, Hartog, were obtained with single-degree of freedom contrasts. The least significant difference (LSD) for comparing the mean of a parameter for a BC2F4:6 line and that of recurrent parent Hartog was calculated after Cox et al. (1995).
Variance and covariance components for genotype and genotype x environment interaction effects were estimated assuming lines and environments were random effects in the expected mean squares and cross-products (Schultz 1955). Broad-sense heritability (h2) was calculated on a single-plot and genotype-mean basis following Nyquist (1991) as h2Plot = 
and 
, where 2G, 2G.E, and 2Residual are estimates of the genotypic, genotype x environment, and residual variances, respectively, and e and r are the number of environments and replications per environment, respectively. Genotypic and environmental correlations and their standard errors were estimated after Falconer and Mackay (1996). The relative selection efficiency (RSE) of genetic gain for agronomic characteristics by selection for was calculated following Falconer and Mackay (1996) as RSE = CRX/RX = ihrX./iXhX, where CRX is the correlated genetic response in the primary trait X (e.g., grain yield or aerial biomass) due to selection for ; RX is the direct genetic response in trait X from direct selection for trait X; i and iX are selection intensities, assumed the same for X and ; rX. is the additive genetic correlation coefficient for traits X and ; and h and hX are square roots of the heritabilities for and X, respectively. Differences were statistically significant at P < 0.05, unless otherwise stated.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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affected grain yield and other agronomic traits. The environmental variance component was significantly different from zero for all measured traits (data not shown) indicating large differences between environments (Table 1). Environmental effects were largest on grain yield with a 4-fold range across all year–site combinations. Environmental effects were also large on kernel number and size but smallest for , harvest index, and plant height. Environmental correlations (re) were positive and significantly different from zero for , aerial biomass (re = 0.98 ± 0.28), and grain yield (0.94 ± 0.17). Increases in grain yield across environments were associated with greater aerial biomass (re = 0.95 ± 0.32), harvest index (0.85 ± 0.17), and kernel size (0.52 ± 0.10). Seasonal precipitation varied between 235 and 437 mm across environments. Increases in seasonal rainfall were positively correlated with increases in grain yield (r = 0.90, P < 0.01), aerial biomass (r = 0.82, P < 0.01), harvest index (r = 0.78, P < 0.05), and to a lesser extent, kernel size (r = 0.72, P < 0.05) and kernel number (r = 0.51, P > 0.05).
Experimental precision was high as indicated by the small coefficients of variation for all measured characteristics (Table 2). The BC2F4:6 lines selected for high did not differ from the recurrent parent Hartog for any characteristic measured (Table 2). The high phenotypic similarity between the high- selected group and Hartog indicated backcrossing was successful in recovering the genetic background of the recurrent parent. In contrast, the low- and high- selected groups did differ in most of the measured agronomic characteristics (Table 2). For example, the low- selected group had an average 0.4 lower than the high- selected group. Selection for low was also associated with significantly increased grain yield (+5.8%), aerial biomass (+2.7%), harvest index (+3.3%) and kernel size (+4.8%). Kernel number and plant height did not differ between the high- and the low- groups but selection for low was associated with a significantly earlier anthesis date of about a half day.
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selected group x environment interaction was significant for all characteristics except aerial biomass and harvest index (data not shown). This interaction was generally small with low- and high- groups maintaining their relative ranking across environments. For example, the low- selected group had a larger harvest index and kernel size in all eight environments while aerial biomass was greater in five of the eight environments. Kernel number was approximately the same for the low- and high- groups across all environments. An exception was Condobolin 1997 where a severe drought up until anthesis was associated with significantly more kernels (+6.1%) for the low- selected group. Grain yield of the low- group was significantly greater in eight of the nine environments (Fig. 1)
. However, this difference decreased linearly (r = -0.89, P < 0.01) with increases in environment mean yield (Fig. 1). Yield advantage for the low- group was greatest for 1 to 4 Mg ha-1 environments and decreased 1.65% for every 1 Mg ha-1 increase in environment mean yield. On the basis of the fitted regression for all environments, the low- group is predicted to maintain a yield advantage up to an environment mean yield of about 7.7 Mg ha-1. The proportional yield advantage of the low- group was closely related to seasonal rainfall (r = -0.85, P < 0.01), the yield advantage decreasing 0.35% with every 10-mm increase in rainfall (Fig. 2)
. Thus, low in this population was associated with greater water-use efficiency resulting in greater grain yield.
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classes were significant for all traits measured (Table 3). For example, the range in within low- and high- groups was 1.1 and 0.9, respectively (Table 2). Twenty of the 30 low- selections had significantly lower than the recurrent parent Hartog (Table 3), while eight of the 30 high- selected lines had larger values than Hartog. Evidence of lines significantly greater for than recurrent parent Hartog suggests transgressive segregation for high . In the low- group, 14 of the 30 lines produced significantly greater grain yield than the recurrent parent compared with six of the high- selected derivatives. Of the 14 higher-yielding, low- lines, 11 had significantly lower than Hartog and all high aerial biomass lines were low- selections (Table 3). The frequency of BC2F4-derivatives with significantly higher harvest index and kernel number was similar for the two groups. However, there were substantially greater numbers of lines with a significantly larger kernel size for the low- group than for the high- group (cf., 17 and 7).
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was sampled (Table 4). Genotype x environment interactions and error variances were also significantly different from zero for all traits indicating that lines did not perform consistently across environments and across replicates within environments. The relatively larger genotype x environment and error variances for grain yield, aerial biomass and harvest index reduced broad-sense heritability on a single-plot and genotype-mean basis. In contrast, the greater relative size of the genetic to non-genetic variance for and kernel size increased heritability for both traits.
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and measured agronomic traits among the group of BC2F4:6 lines (Table 4). Genetic correlations were generally negative with the exception of kernel number and , which did not differ from zero. The strong, negative genetic correlation between and aerial biomass suggested that lines with smaller generally produced greater aerial biomass. In turn, lines with smaller had larger grain yield, harvest index and kernel size. A lack of genetic correlation for and kernel number suggested that these two traits are under independent genetic control in this population. Genotypic differences in grain yield were associated with significant increases in aerial biomass (rg = 0.77 ± 0.12), harvest index (0.70 ± 0.11), kernel size (0.38 ± 0.15), but not kernel number (0.24 ± 0.19).
Heritability and genetic correlation estimates were used to determine the potential of indirect selection for increased aerial biomass and grain yield through to be assessed in this wheat breeding population. The variance among BC2F4:6 sibs contains almost no dominance genetic effect (Nyquist, 1991), indicating broad- and narrow-sense heritability estimates to be approximately equal. Similarly, genetic correlations should be additive owing to largely additive genetic covariance effects. Assuming the same level of selection intensity for and the target trait grain yield, genetic gain through selection for would be 24% less efficient than direct selection for grain yield when families are evaluated on a mean basis in replicated plots across multiple environments (i.e., RSE.X, Table 4). However, relative efficiency increased by 22% when was used as a surrogate for selection of grain yield on a single-plot basis (i.e., when genotypes are unreplicated in a single environment). The small heritability for aerial biomass suggests that selection for lower would produce 103% greater genetic gain for aerial biomass than direct selection for aerial biomass per se on a single-plot basis. An equivalent genetic gain would be expected on a genotype-mean basis. Smaller genetic correlations between and harvest index, kernel size, and kernel number reduced relative efficiencies of indirect selection to less than 100% for both single-plot and genotype-mean estimates of line performance.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Divergent selection of BC2F2:4 families into low- and high- groups produced yield increases for the low-, BC2F4:6 lines in all of the sampled environments. This yield advantage was largest in drier, lower-yielding environments but was maintained, to a lesser extent, in wetter, higher-yielding environments. It is conceivable that even at high yield levels, the yield advantage of low- lines reflects an ability to buffer against intermittent moisture stresses that may occur during the growing season. The yield advantage of low- selected lines was associated with increases in aerial biomass, and greater partitioning of dry matter to grain. Together these increased kernel size while kernel number remained unaffected. Given that kernel number was the same for the low- and high- groups and that kernel number is largely determined up to anthesis, increased TE did not appear to compromise development of grain yield potential up to anthesis. Indeed, the low- group was better able to realize this yield potential through the development of larger kernels.
Transpiration efficiency was not measured in this study. Previous studies in wheat and other species have shown genetic reductions in were commonly associated with greater TE (see Hall et al., 1996). Similarly, Read et al. (1993) reported divergent selection for in crested wheatgrass (Agropyron desertorum L.) produced significant increases in TE of half-sib progeny derived from low- parents. In our study, sampling of lines derived from low- bulks produced correlated genetic gain in aerial biomass and grain yield. Our results support those of other studies where of genetically unrelated lines was associated with greater grain yield and aerial biomass under water-limited conditions (Wright et al., 1988; Ehdaie et al., 1991; Condon and Richards, 1993; Voltas et al., 1999). However, our study extends these findings to confirm the potential influence of leaf on aerial biomass and grain yield among related, backcross-derived wheat sibs.
The increased harvest index of low- progeny has not been reported previously and may reflect slowed water use in these lines. Reduced in the low- parent, Quarrion, is partly associated with lower leaf conductance (Condon et al., 1990). Lower stomatal conductance in winter-sown crops should slow leaf transpiration to reduce crop water loss, thereby conserving soil moisture for later grain growth (Passioura, 1977). Any extra post-anthesis water use of wheat crops growing largely on stored moisture reserves should result in an increased kernel size through continued remobilization or maintenance of assimilation to fill kernels and increase harvest index (Richards, 1991). Increased kernel size not only benefits growers by increasing yield, but also reducing the incidence of shriveled grain and subsequent downgrading of grain quality in environments experiencing terminal droughts.
Single-plot and genotype-mean heritability estimates for were high, consistent with previous estimates in wheat (Ehdaie et al., 1991; Condon and Richards, 1992) and other grass species (e.g., Read et al., 1993; Asay et al., 1998). This high heritability partly reflects large genotypic variation for in the sampled population, and the early growth stage at which was sampled (Condon and Richards, 1992). In contrast, relatively large non-genetic effects reduced heritability for grain yield and aerial biomass. For these traits, significant genotype x environment interactions reduced the correlation between phenotype and genotype to reduce confidence in phenotypic selection of high-yielding lines. In turn, gain from selection would be slowed for grain yield and biomass as previously reported for screening wheat under rainfed conditions (Fischer and Wood, 1979; Nachit et al., 1992). Empirical selection in water-limited environments is slow and costly as large genotype x environment interactions necessitate testing in multiple years and sites (Calhoun et al., 1994). Different traits and therefore different genes may affect changes in grain yield across environments, slowing genetic progress from selection (Richards, 1991; Nachit et al., 1992). Screening for single traits with large average adaptive effects on grain yield would be desirable. Given that water predisposes plant adaptation in water-limited environments, traits affecting water use and grain yield such as TE may produce reasonable genetic gain over a range of water-limited environments (Richards et al., 2002).
The larger heritability for and its negative genetic correlation with aerial biomass and grain yield suggests that may be useful for indirect selection of either trait under water-limited conditions where transpiration is a major component of water use. First, selection for genes associated with low and therefore high TE may enable genetic increases in aerial biomass, whereas aerial biomass has remained relatively unchanged in selection of high-yielding bread wheats (e.g., Fischer et al., 1998; Siddique et al., 1989). In comparisons among wheat varieties grown under drought, Fischer and Wood (1979) highlighted the importance of genetic increases in aerial biomass in order to increase grain yield under drought. Second, high relative selection efficiencies for and both aerial biomass and grain yield indicate that could enable culling of large populations prior to more expensive multienvironment yield and grain-quality testing. This is particularly true in early generations where selection for grain yield typically reflects performance in unreplicated plots. There is greater confidence in selection for in the absence of replication owing to relatively smaller residual and genotype x environment interaction effects for this trait. Moreover, a preponderance of additive genetic effects for both (Ehdaie and Waines, 1994) and TE (Malik et al., 1999) suggests that early generation selection for should produce concomitant genetic gain in inbred families.
In conclusion, divergent selection for resulted in greater aerial biomass and increased grain yield in backcross-derived, low- selections evaluated under rainfed conditions. Yield advantage in low- lines was greatest for drier, lower-yielding environments of 1 to 4 Mg ha-1, but then declined linearly with increases in seasonal rainfall. Higher heritabilities for and strong genetic correlations with aerial biomass and grain yield, indicate that might be useful for indirect selection in a breeding program targeting increased aerial biomass and grain yield in water-limited environments. In preliminary screening for yield in early generations, populations could be selected for lower and hence greater yield under drought before evaluation in expensive multienvironment testing. Further work is needed to confirm the benefits of selection for in other wheat populations and in other environments.
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ACKNOWLEDGMENTS |
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Received for publication September 1, 2001.
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REFERENCES |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
LOW 
, genotype x environment 
, and residual 
variance components; narrow-sense heritability values on a single-plot 
and genotype-mean 
basis; genotypic correlations (rg) and relative selection efficiencies (RSE