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Published online 6 May 2005
Published in Crop Sci 45:1107-1113 (2005)
© 2005 Crop Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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CROP BREEDING, GENETICS & CYTOLOGY

Selection for Water Use Efficiency Traits in a Cotton Breeding Program

Cultivar Differences

Warwick N. Stillera,*, John J. Readb, Gregory A. Constablea and Peter E. Reida

a CSIRO Plant Industry, Cotton Research Unit, Locked Bag 59, Narrabri NSW 2390, Australia
b USDA-ARS, Crop Science Research Lab., P.O. Box 5367, Mississippi State, MS 39762

* Corresponding author (warwick.stiller{at}csiro.au)


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Water stress adversely affects both yield and fiber quality of cotton (Gossypium hirsutum L.) and any improvement in components of water use efficiency (WUE) would be expected to partially reduce these adverse affects. Six field experiments in Australia and one in Texas using four Australian and three Texas cultivars determined genetic differences in physiological WUE parameters. Four of the experiments were grown under dryland conditions and three under irrigated conditions. Cultivar differences for net photosynthesis (A) were found in only 30% of comparisons, ratio of intercellular CO2 concentration to ambient CO2 concentration (Ci/Ca) in 20%, and carbon isotope 13C discrimination ({Delta}) in 69%. Cultivars Cascot 014 and Sicot 189 had significantly (P ≤ 0.05) higher A than Siokra 1-4 and Siokra L23 and these differences were consistent across experiments. A significant (P ≤ 0.05) cultivar x experiment interaction suggests Ci/Ca would be an environment specific measure enabling confident distinction of cultivar differences. Tamcot Sphinx and Cascot 014 had significantly higher {Delta} (P ≤ 0.001) than Siokra L23, with the ranking differing in only one irrigated experiment. Broad sense heritability estimates were 0.65, 0.68, and 0.56 for A, {Delta}, and lint yield, respectively. Cultivar variation for these physiological traits measured in single leaves of cotton, and related indirectly to plant WUE, indicate potential for genetic advancement through selection. Further studies to determine heritability of these physiological traits in segregating populations are needed to confirm their usefulness in a cotton-breeding program.

Abbreviations: A, net photosynthesis • Ci/Ca, ratio of intercellular CO2 concentration to ambient CO2 concentration • g, stomatal conductance to water vapor • TE, transpiration efficiency (net photosynthesis/transpiration) • {Delta}, carbon isotope discrimination


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
ONE AIM of our cotton-breeding program is to produce cultivars for dryland production systems that have high yield potential and enhanced water use efficiency in addition to tolerance to water stress. Traditionally, material from our irrigated cotton-breeding program is evaluated under dryland conditions to determine genotypes most suited to those conditions. However, with the increase in the area of cotton produced under dryland, we have expanded our breeding efforts to address specifically this production system and evaluate different selection criteria in screening breeding populations for enhanced WUE. In Australia, the soil types used for dryland cotton have a high water holding capacity (Chan and Hodgson, 1981), but rainfall can be unreliable (Stiller et al., 2004; Cull et al., 1981). Thus, a dryland cotton cultivar needs to withstand extended periods of water stress and then be able to utilize rain when it occurs. Late-maturing cultivars have been shown to best meet these requirements (Stiller et al., 2004), and those with the okra leaf trait have also been successful (Stiller et al., 2004; Thomson, 1994).

Physiological traits associated with water use efficiency or stress tolerance have rarely been used in plant breeding. This is due to difficulties associated with measuring these traits on large numbers of plants, low heritabilities, and complex relationships between these traits and yield (Hall et al., 1994). However, the demonstration that carbon isotope discrimination ({Delta}) could provide an indirect measure of plant transpiration efficiency (Farquhar et al., 1982; Farquhar and Richards, 1984) has renewed interest in breeding for physiological water use efficiency. Discrimination against 13CO2 in favor of 12CO2 during CO2 diffusion through the stomata and during photosynthesis in C3 plants is closely related to the transpiration efficiency integrated over the life of the plant material sampled (Farquhar and Richards, 1984; Condon et al., 1992). In recent times, selection for {Delta} in early generation progeny has increased the yield of wheat (Triticum aestivum L.) grown under dryland conditions (Rebetzke et al., 2002) and led to the subsequent release of a new cultivar (Anon., 2002).

The objectives of this study were (i) to measure a range of physiological traits on a selection of cotton cultivars originating from Australia and Texas, (ii) to determine the sensitivity of these measurements for differentiating between cultivars and the repeatability of the ranks obtained, and specifically (iii) to estimate heritability of the traits and to determine their associations with lint yield. Results are expected to provide information to utilize in a cotton-breeding program to improve the yield of cultivars for dryland production systems.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
A summary of experiments conducted in this study are shown in Table 1. All experiments were conducted with randomized complete block experimental designs with three replicates.


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  		Table 1. Details of experiments, measurements conducted and timing of measurements. Narrabri, NSW, Australia; Dalby, Qld, Australia; Pecos, TX, USA.

 
Details of these experiments are presented in Stiller et al. (2004) under the heading "diverse cultivar experiments." The Australian sites were prepared in a similar way, either being cropped to wheat the previous winter or cropped to grain sorghum [Sorghum bicolor (L.) Moench] the previous summer. The Pecos experiment was in a long fallow field following cotton two seasons previously. Nitrogen fertilizer was applied, usually as NH3, at rates between 60 and 80 kg N ha–1 for dryland experiments and 140 to 180 kg N ha–1 for the irrigated experiments. Trifluralin [(2,6-dinitro-N,N-dipropyl-4-(trifluoromethyl) benzenamine)] herbicide at 2.8 L ha–1 (400 g L–1) was incorporated in September each season before sowing in October and 3.5 L ha–1 of fluorometuron [N,N-dimethyl-N'-3-(trifluoromethyl)phenyl urea] herbicide (500 g L–1) was applied after sowing before crop emergence. Hand hoeing and interrow cultivation were used for all subsequent weed control. The crops were sown with a cone seeder on rows one meter apart to achieve a plant population of 60000 plants ha–1, except irrigated trials at Narrabri which were 120000 plants ha–1 and the Pecos experiment which had a population of 200000 plants ha–1. Furrow irrigation was applied to the irrigated crops as required during flowering and boll filling (three applications of approximately 100 mm in 1995–1996 and five in 1996–1997). The crops were sprayed by aircraft to control insect pests according to the Cotton Pest Management Guide (Shaw, 1999).

Detailed information on the soil and climate is given in Stiller et al. (2004). The soil types across the three sites were as follows: Narrabri, Typic Haplustert (USDA Classification, Soil Survey Staff, 1996), [Australian classification, Isbell, 1996, Self mulching vertisol; very fine (clay > 60%)]; Dalby, Typic Haplotorrert (USDA Classification, Soil Survey Staff, 1996) [Australian classification, Isbell, 1996, Self mulching vertisol; very fine (clay > 60%)]; and Pecos, Ustic Calciustoll (USDA Classification, Soil Survey Staff, 1996), [Australian classification, Isbell, 1996, Clayey tenesol (Clay > 35%)]. The Australian soils had a water holding capacity greater than 190 mm to a depth of 1500 mm (Chan and Hodgson, 1981).

Seven cultivars were chosen for these experiments to provide some contrast in plant type and maturity (Table 2). Siokra L23 was a successful dryland cultivar in Australia and has subsequently been shown to be water stress tolerant (Nepomuceno et al., 1998; Voloudakis et al., 2002). CS50 has erratic dryland performance and has subsequently been shown to be non-tolerant to water stress (Nepomuceno et al., 1998). Sicot 189 has some adaptation to dryland conditions, possibly because of disease resistance (Stiller et al., 2004). The cultivars Tamcot HQ95 and Tamcot Sphinx were chosen because they were being used in a similar series of experiments in Texas (Gerik et al., 1996b). These cultivars and Cascot 014 have typically not performed well under dryland conditions in Australia (Reid, unpublished data, 1995).


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  		Table 2. Summary of cultivars sampled in experiments; Leaf type: O = okra leaf, N = normal leaf; Maturity: E = early maturing, M = medium maturing, L = late maturing based on field observations.

 
Gas exchange measurements at Narrabri in 1994 and Pecos in 1996 were made with a LI-COR model LI-6200 portable photosynthesis system (LI-COR, Inc., Lincoln, NE) with a 1-L chamber. Measurements on all other experiments were made with a LI-COR model LI-6400 steady state (open-system) portable photosynthesis unit with a 6-cm2 chamber. Five leaves per plot were measured, with measurements on a portion of the youngest, fully expanded, fully sunlit leaf (usually four nodes from the terminal), held perpendicular to the sun and were taken within the period of three hours either side of solar noon.

Ten leaves per plot were combined for {Delta} analysis. Leaves that had been measured for gas exchange, or leaves from the same position on a different plant were harvested. Each leaf blade was removed from the petiole, inserted into a paper packet and placed immediately on ice to stop respiration. As soon as possible they were transferred to a fan forced dehydrator at 80°C for a minimum of 48 h. These samples were shipped to the Australian National University, Research School of Biological Sciences, Canberra. Each sample was ground in a Cyclotec model 1093 grinder (Foss Tecator, Höganäs, Sweden) with a 0.4-mm screen, to obtain a maximum particle size of 100 µm. Subsamples of 10 mg were removed and combusted to water and CO2 in a VG Isoprep 13 (VG Isogas Ltd., Cheshire, UK) combustion system. The effluent carbon dioxide was trapped in the liquid nitrogen-cooled glass tube supplied by the manufacturer and allowed to enter the inlet of a VG Micromass 602D ratio mass spectrometer (VG Instruments, Cheshire, UK), directly. An internal standard prepared from C3 sucrose (with {delta} relative to PeeDee Beleminite of –24.08o/oo) was periodically combusted to estimate variation in isotope ratios due to sample preparation. {Delta} of dry matter was calculated according to Hubick et al. (1986).

The center row of the three row plots, the center two rows of the four row plots, and both rows of the two row plots were machine harvested with a spindle picker and the seed cotton weighed. A subsample of approximately 400 g of seed cotton was taken from each plot. Subsamples were ginned to determine lint percentage and this value was used to calculate lint yield for each plot. A lint sample from each plot was evaluated for quality using a Spinlab High Volume Instrument (HVI) model 900 (Zellweger Uster, Knoxville, TN). Fiber characters measured were upper half mean length (mm), fiber length uniformity, strength (kN m kg–1), extension (%), and micronaire reading.

As the crop began to mature, four successive hand harvests were taken from 1 m of row in each plot of N94D, N95D, N96D, and N96I to determine cultivar maturity. The mean maturity date (MMD), a weighted mean harvest date based on the weight of lint in the successive hand harvests and calculated by the formula given by Christidis and Harrison (1955) was estimated for each cultivar.

Traits were subjected to analysis of variance with the Genstat 5 package (Lawes Agricultural Trust, IACR, Rothamstead, UK). Data for leaf gas exchange and {Delta} were analyzed statistically in three steps. First, for individual sample dates within each experiment; second, analysis was done across sample dates within each experiment; finally, a pooled analysis of data was done for A, Ci/Ca, and {Delta} across experiments using mean values for the different sample dates. For combined analyses, dates or experiments were considered as main plots in a split plot analysis of variance. Heterogeneity of variance was significant for some sample dates and experiments for A and Ci/Ca, so these combined analyses were log transformed. There was no heterogeneity of variance for {Delta}.

Estimates of broad sense heritability were obtained by equating expected mean squares from analyses of variance to genotypic , genotype x environment , and residual variances. The following relationships from Comstock and Robinson (1952) were used to estimate broad sense heritability on a genotype mean basis:

where e is the number of environments and r is the number of replicates.


   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Significant cultivar differences in A were detected in only three of 10 (30%) comparisons across experiments and sample dates (Table 3). The corresponding percentage was 30, 20, 20, 0, and 69% for g, A/g, Ci/Ca, TE, and {Delta}, respectively (data not shown). Thus, only {Delta} showed reasonable consistency in terms of detecting significant cultivar effects. For {Delta}, significant cultivar differences were found for all sampling dates (data not shown), consistent with this measure being an integral of a leaf's physiological condition over time rather than an instantaneous measure of leaf gas exchange. It was decided that further analyses would concentrate on A, as a measure of productivity and Ci/Ca and {Delta} as indicators of leaf WUE. Correlations among A, Ci/Ca, and {Delta} have been previously shown in cotton (Brugnoli et al., 1988). In field studies with cotton, {Delta} was also associated with changes in leaf gas exchange traits and plant dry matter-based WUE (Yakir et al., 1990; Gerik et al., 1996a).


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  		Table 3. Net photosynthesis (A- umolCO2m–2s–1), ratio of intercellular CO2 concentration to ambient CO2 concentration (Ci/Ca) and 13C-isotope discrimination ({Delta}- per mil) in leaves of seven cotton cultivars grown in different experiments.

 
Analysis across sample dates within each experiment indicated differences between cultivars for Ci/Ca and varied with sample date on one occasion as indicated by a significant cultivar x date interaction (P ≤ 0.05—N95D for Ci/Ca) (Table 3). The benefit of a pooled analysis was evident in N95D, as no significant cultivar effect was detected for Ci/Ca for individual sampling dates, but a significant (P ≤ 0.05) cultivar and cultivar x sample date interaction was obtained in a pooled analysis of variance (Table 3). One cultivar, Siokra 1-4 had relatively high Ci/Ca for the first sampling date but the lowest for both of the other dates (data not shown). Cultivar ranking for {Delta} was consistent across sample dates, as the cultivar x sample date interaction was not significant in any experiment.

Results of the pooled analysis across experiments indicated significant cultivar effects for A (P ≤ 0.05); no significant main effect of cultivar on Ci/Ca, although the ranking varied across experiments (P ≤ 0.01); and significant cultivar effects on {Delta} (P ≤ 0.001), also with a change in ranking across experiments (P ≤ 0.001) (Table 3). In regards to A, the ranking of cultivars was similar in only two experiments, N94D and T96I, suggesting a large number of experiments may be needed to obtain a useful ranking for A. Similarly, the cultivar x experiment interaction for Ci/Ca characterized by rank changes indicated this would not be a measure that enabled confident distinction between cultivars from single experiments or measurements. Although Siokra 1-4 had a higher mean Ci/Ca than Siokra L23 across experiments, this ranking was reversed in N95D (Table 3).

Cascot 014 and Sicot 189 had significantly (P ≤ 0.05) higher A than Siokra 1-4 and Siokra L23. These differences were consistent across experiments as evidenced by no significant cultivar x experiment interaction. In the experiments where significant differences were detected for A, there was an average 15% range in rates between low and high cultivars. Pettigrew and Meredith (1994) found a range of 11% within a group of 18 normal leaf cotton cultivars with differing maturity and regions of adaptation. Taking this into account, it appears our experiments contained similar genetic variability among cultivars for A.

Averaged across experiments, Tamcot Sphinx and Cascot 014 had significantly higher {Delta} than Siokra L23 (P ≤ 0.001) but not in N95I where these three cultivars were equal and CS 50 had the highest and Tamcot HQ95 the lowest {Delta}. Low {Delta} in leaves of Tamcot HQ95 is consistent with the findings of Faver et al. (1996) of greater CO2 assimilation capacity (as inferred from higher slope of the A:Ci response curve) and less reduction in leaf photosynthetic activity under water stress in this cultivar, as compared with another cultivar, G&P74+. The cultivar ranking for {Delta} was relatively consistent. Siokra L23 was lowest on nine of the 13 occasions and Tamcot Sphinx was either highest or second highest on eight of 13 occasions.

The low ranking of Siokra L23 for {Delta} is consistent with its high leaf WUE as measured by low Ci/Ca and also consistent with its water stress tolerance as measured by gas exchange and molecular response methods (Nepomuceno et al., 1998; Voloudakis et al., 2002). Cascot 014 also ranked high for {Delta}; however, neither Tamcot Sphinx nor Cascot 014 consistently ranked low for leaf Ci/Ca, a trait closely linked to changes in instantaneous leaf WUE, and hence {Delta} (Farquhar et al., 1982).

Compared with leaf gas exchange traits, {Delta} of plant organic matter was more reliable in establishing differences between cultivars. Advantages of {Delta} are that measurement of this trait is very sensitive, accurate and repeatable, and able to detect extremely small differences between samples (Farquhar and Richards, 1984). Also, because {Delta} provides a temporally and spatially integrated estimate of leaf WUE (Hall et al., 1994), it may help to minimize the influences of any large fluctuations in environmental conditions. Gas exchange measurements, on the other hand, are influenced to a large degree by the prevailing environmental conditions, not only of the day, but also of the exact time of day when the measurement is taking place. Although we did not have a full orthogonal set of dryland and irrigated experiments, this data set raises the obvious suggestion that {Delta} should be measured under dryland conditions to distinguish genotypes with adaptations to water-limited conditions.

Consistent with previous dryland experiments in Australia (P. Reid, unpublished data), the four Australian cultivars had higher yield, higher lint percentage, and longer and stronger fibers than the three Texas cultivars when data were averaged across experiments (Table 4). The cultivars from Texas were earlier maturing and the relatively low adaptation of these cultivars to the Australian climate has been discussed in Stiller et al. (2004). Any potential advantages in the Texan cultivars arising from physiological traits were possibly outweighed by lesser adaptation in terms of maturity and growth habit. Leaf CO2 assimilation in cotton during the boll maturation stage explained only about 20% of the variability in lint yield of 18 field-grown cultivars (Pettigrew and Meredith, 1994). Hence, other factors besides leaf gas exchange influence yield, including fruiting rate and boll retention, assimilate partitioning, leaf type, and canopy leaf area (Turner et al., 1986).


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  		Table 4. Lint yield and fiber traits in seven cultivars averaged across six experiments: N94D, N95D, N95I, N96D, N96I, Q96D.

 
There was a significant (P ≤ 0.05), though relatively weak, negative association of A, Ci/Ca, and {Delta} with lint yield when data were pooled across experiments (r2 of 0.13, 0.17, and 0.26 respectively). Figure 1A shows this association between {Delta} and lint yield for the four dryland experiments. Within experiments, however, there was poor association between {Delta} and lint yield (Fig. 1B). In a study involving 70 cotton cultivars grown in water stressed field conditions, Lopez et al. (1993) also found no relationship between lint yield and leaf physiological WUE, A/g, or its components A and leaf conductance to water vapor (g). Multiple linear regression on the data across experiments (Fig. 1B) indicated yield increased about 303 kg lint ha–1 for every per mil decrease in leaf {Delta}. In contrast, Gerik et al. (1996b) demonstrated a consistent positive association between {Delta} and lint yield across a range of irrigated and dryland experiments, while Leidi et al. (1999) found inconsistent associations; no relationship where irrigation was withheld, and a positive relationship in one dryland experiment.



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  		Fig. 1. A; association between {Delta} and lint yield pooled across four dryland experiments between 1994 and 1997. B; association between {Delta} and lint yield within four dryland and three irrigated experiments between 1994 and 1997. A solid line indicates a significant association and a dashed line indicates a nonsignificant trend.

 
Although associations between the physiological traits and yield were significant when data were pooled across experiments, the range was not necessarily associated with differences between cultivars. So, although the results support the theory that in environments with limited soil water, enhanced WUE (low {Delta}, Ci/Ca and possibly A) can lead to water savings and thus support a greater yield potential in cotton, but the confidence in using any of the physiological traits as indirect selection for yield in a breeding program would be low.

Crop maturity, as indicated by mean maturity date (MMD), was measured on three dryland and one irrigated experiment: N94D, N95D, N96D and N96I. Multiple linear regression analysis showed a highly significant (R2 = 0.56; P ≤ 0.001) negative association between {Delta} and MMD, with all four experiments fitting the same trend. The analysis indicated that the crop was 13.4 d earlier on average per mil increase in {Delta}.

Strong negative associations have been obtained between {Delta} and time to anthesis in cereals (Craufurd et al., 1991; Ehdaie et al., 1991; Acevedo, 1993; Richards and Condon, 1993), common bean (Phaseolus vulgaris L.) (White, 1993), and cowpea [Vigna unguiculata (L.) Walp.] (Hall et al., 1993). Richards and Condon (1993) proposed that this association might have arisen from unconscious selection by breeders for faster growth in genotypes of short duration. Faster growth may be required to achieve high yields as it compensates for any yield penalty associated with short duration. However, when we investigated the growth rates of Siokra L23 (low {Delta}) and Cascot 014 (high {Delta}), we found no evidence that this was the case (data not shown). This relationship could be the reason for the positive association found in the Texas studies between {Delta} and lint yield Gerik et al. (1996b), where adapted, early maturing cultivars with high {Delta} had higher yield. Regardless of the reason for the association, selection for low {Delta} would be desirable in terms of maturity, assuming the traits are linked, as late maturing cultivars have shown an advantage under dryland conditions in Australia (Stiller et al., 2004).

Estimates of broad sense heritability were calculated. The reference population for heritability when calculated among cultivars is not a breeding population per se but a statistic that examines manipulation of WUE by breeding and selection. Cultivar mean heritability across five experiments were 0.65 for A and 0.56 for Ci/Ca, while estimates for {Delta} across the complete set of seven experiments averaged 0.68 (Table 5). Reported broad sense heritabilities for gas exchange traits in various crops range from 0.2 to 0.8 (Asay et al., 1974; Crosbie et al., 1977; Quail et al., 1989; Abdullaev et al., 1990; Donovan and Ehleringer, 1994), our estimates being in the higher end of this range. Heritability for {Delta} in cereals has usually been observed to be higher; Condon and Richards (1992) reported heritabilities for wheat as high as 0.95, when common cultivars were grown in numerous environments. However, heritability of {Delta} has been reported to be low in common bean (White et al., 1994) and in cowpea (Menendez and Hall, 1995). In most cases, heritabilities were higher when measured on cultivars than on breeding populations.


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  		Table 5. Broad sense heritability estimates for leaf net photosynthesis (A), ratio of intercellular CO2 concentration to ambient CO2 concentration (Ci/Ca), 13C-isotope discrimination ({Delta}), lint yield and fiber properties determined from seven diverse cotton cultivars. Experiments used to estimate heritability of A and Ci/Ca were N94D, N95D, N95I, N96D, T96I; {Delta}, N94D, N95D, N95I, N96D, N96I, Q96D, T96I; yield; and quality traits, N94D, N95D, N95I, N96D, N96I, Q96D.

 
Lint yield had a heritability of 0.56, toward the high end of the literature range of 0 to 0.6 (Manning, 1954; Al-Jibouri et al., 1958; Murray and Verhalen, 1969; Thomson, 1973). Heritability estimates for fiber quality and lint percentage traits ranged from 0.68 for length uniformity to 0.98 for fiber extension and lint percentage (Table 5). Medium to high heritabilities have generally been reported for lint percentage and fiber traits. Heritabilities for fiber length range from 0.7 to 0.9, fiber strength 0.6 to 0.9 (Stith, 1956; Al-Jibouri et al., 1958; Miller et al., 1958; Murray and Verhalen, 1969) and micronaire reading 0.4 to 0.5 (Murray and Verhalen, 1969; Thomson, 1973). May (1999) reviewed the genetic variation in fiber quality and concluded that selection for most parameters in a breeding program should be effective.

While heritability estimates for physiological traits appear reasonably high, they are of a similar magnitude to yield, and all are less than that for fiber quality (Table 5). In addition, these estimates are based on variance components of a contrasting set of cultivars and the heritability estimates provide an indication of the repeatability of the measurements.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
Of the gas exchange traits, A proved the most sensitive for detecting differences between cultivars. However, a confident ranking of cultivars for A would require a number of experiments, possibly greater than four. Differences between cultivars for {Delta} were found in all experiments, and a relatively small cultivar x experiment interaction for {Delta} suggests a confident ranking of cultivars can be obtained with few experiments. We conclude that to rank cultivars for {Delta}, measurements should be taken from dryland experiments and on at least two sampling dates on each—between the mid-squaring to mid-flowering stages of development. Associations between physiological traits and lint yield were found only when data were pooled across experiments. So although the associations conformed to theory, our results indicate there would be little confidence in using any of the physiological traits as indicators of yield in a given environment. Heritability of the physiological traits was encouraging, but no single trait had a substantially greater heritability than lint yield and the heritability estimate of each was always less than heritability of fiber quality traits. Further work measuring these physiological traits in segregating breeding populations is necessary to more clearly determine their usefulness in a cotton breeding program.


   ACKNOWLEDGMENTS
 
These studies were partially supported by funds from the Cotton Research and Development Corporation and the Cooperative Research Centre for Sustainable Cotton Production. Thanks are extended to Lindsay Heal and Chris Tyson for assistance with field experiments, Lennore Carpenter and Kellie Cooper for assistance with fiber testing, and Sue Wood of the Australian National University, Research School of Biological Science, for carbon isotope analysis in leaf dry matter.

Received for publication September 14, 2004.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 





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