Journal of Experimental Botany, Vol. 51, No. 353, pp. 2021-2029,
December 2000
© 2000 Oxford University Press
Original Papers |
Phenotypic responses of wild barley to experimentally imposed water stress
1 Scottish Crop Research Institute, Invergowrie, Dundee, DD2 5DA, Scotland, UK
2 China Agricultural University, Beijing, PR China
3 US Department of Agriculture, University of Wisconsin, Madison, USA
4 Biomathematics and Statistics Scotland (BioSS), Scottish Crop Research Institute, Invergowrie, Dundee, DD2 5DA, Scotland, UK
5 Institute of Evolution, University of Haifa, Mt. Carmel, Haifa 31905, Israel
Received 29 June 2000; Accepted 6 July 2000
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Abstract |
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Responses to water stress within a population of wild barley from Tabigha, Israel, were examined. The population's distribution spans two soil types: Terra Rossa (TR) and Basalt (B). Seeds were collected from plants along a 100 m transect; 24 genotypes were sampled from TR and 28 from B. Due to different soil water-holding capacities, plants growing on TR naturally experience more intense drought than plants growing on B. In a glasshouse experiment, water was withheld from plants for two periods (10 d and 14 d) after flag leaf emergence. A total of 15 agronomic, morphological, developmental, and fertility related traits were examined by analysis of variance (ANOVA). Ten of these traits were significantly affected by the treatment. A high degree of phenotypic variation was found in the population with significant genotypextreatment and soil typextreatment interactions. Principal component analysis (PCA) was performed using combined control and stress treatment data sets. The first three principal components (pc) explained 88.8% of the variation existing in the population with pc1 (47.9%) comprising yield-related and morphological traits, pc2 (22.9%) developmental characteristics and pc3 (18.0%) fertility-related traits. The relative performance of individual genotypes was determined and water stress tolerant genotypes identified. TR genotypes were significantly less affected by the imposed water stress than B genotypes. Moreover, TR genotypes showed accelerated development under water deficit conditions. Data indicate that specific genotypes demonstrating differential responses may be useful for comparative physiological studies, and that TR genotypes exhibiting yield stability may have value for breeding barley better adapted to drought.
Key words: Hordeum spontaneum, drought, adaptation, GxE interaction, principal component analysis.
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Introduction |
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Barley is a crop of major economic importance and also a model species for genetics and physiology (Koornneef et al., 1997
). Wild barley, Hordeum spontaneum C. Koch, is the progenitor of the crop species H. vulgare L. (Harlan, 1968, 1995) and is widely distributed in the Fertile Crescent where domestication took place some 10 000 years ago (Zohary and Hopf, 1988). Habitats of wild barley in the Fertile Crescent differ widely in water availability, temperature, soil type, altitude, and vegetation. Morphological and physiological variation observed in these habitats has arisen by natural selection (Nevo et al., 1981, 1983, 1986). The genetic diversity of wild barley has been studied both within and between populations collected from around the Fertile Crescent (reviewed by Nevo, 1992; Forster, 1999). The wild barley population from Tabigha, a micro-site north of the Sea of Galilee, Israel, has been analysed in several studies (Nevo et al., 1981, 1983; Owuor et al., 1999). The Tabigha site is of particular ecological interest as the barley population at this site spans two diverse soil types, Terra Rossa (TR) and Basalt derived soil (B). The transition between the two soil types is abrupt, such that plants growing on TR and B can be separated by a few metres. The B type soil possesses a greater water-holding capacity compared to TR. This combined with an almost complete lack of rain in early summer and the relatively low annual rainfall (436 mm) frequently results in drought which is most severe in TR (Nevo et al., 1994). Annual plants on the TR area typically flower and ripen 3–4 weeks after the last rains in late spring compared to 8–10 weeks on the B area (Nevo et al., 1988). Since the wild barley plants growing at the Tabigha site experience the same temperatures, including vernalization temperatures, photoperiod and rainfall, it may be expected that a large portion of the variation exhibited is related to adaptation to edaphic conditions. The controlled glasshouse experiment described here was designed to mimic the in situ early summer drought in order (1) to measure phenotypic variation within the population, (2) to compare the performance in well-watered and water-withheld conditions, (3) to relate stress responses to soil type, and (4) to identify individuals with contrasting responses to water stress. |
Materials and methods |
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Plant material and site information
Wild barley genotypes were collected (Nevo et al., 1981
), where present, every metre along a 100 m transect at the Tabigha site (longitude: 35° 53', latitude: 32° 90'). The transect is equally divided into two soil types derived from Terra Rossa (TR) and Basalt (B) rocks. Twenty-four genotypes from TR (first 50 m) and 28 genotypes from B (second 50 m) were studied. The 52 genotypes were numbered according to their metre position along the transect. The original collections have been maintained at the Institute of Evolution, Haifa, Israel, and subsequently at the Scottish Crop Research Institute (SCRI), Dundee, UK. The red Terra Rossa soil is derived from Middle Eocene hard limestone and the brown Basalt soil is derived from Pleistocene basalt flows (Nevo et al., 1981). The mean annual rainfall at the Tabigha site is 436 mm with essentially no precipitation from May to September, but large variation within and between years can occur (Nevo et al., 1988). The mean annual temperature is 24.1 °C with monthly means ranging from 15 °C in January to 32 °C in August (Nevo et al., 1988).
Barley seeds germinate shortly after the rains, which occur between October and November. The population is fully matured by the following April/May. The most important factor determining plant performance on TR and B is differential soil drying rates occuring in late spring (Nevo et al., 1988). Basalt soil has a higher clay content and is more fertile than TR. Apart from soil differences, wild barley plants growing on TR and B experience the same climatic conditions (e.g. temperature, photoperiod and rainfall). Therefore, variation found between TR and B genotypes is principally associated with adaptation to soil type.
Glasshouse experimentation and experimental design
Genotypes were sown in a heated glasshouse at SCRI until established (5-weeks-old). Glasshouse heating was then terminated to allow 10 weeks (13 November 1998–21 January 1999) of vernalization at ambient temperatures ranging from -3.1 °C to +14.9 °C. This was done to help reduce variation in plant development among the genotypes. Plants (one per pot) were grown in a free-draining mixture of 50% John Innes potting compost (JI No. 2; 7 parts loam, 3 parts peat, 2 parts sand; N:P:K=20:10:10) and 50% sand in 3.0 l pots, and fertilized once using granular (N:P:K=1:1:3, 15 weeks from sowing). Artificial lighting was supplied by sodium lamps for 16 h d-1 throughout the experiment to supplement and extend natural daylight. At harvest time, the irradiance near the top of the plants ranged from 300–450 µmol m2 s-1. Except for vernalization, the glasshouse was maintained at average day and night temperatures of 20 °C (16 h) and 10 °C (8 h), respectively.
The experiment had a nested design with three blocks. Within each block were two main plots, the well-watered control (C) and the water-stress treatment (S). There were therefore three replicates of each genotype per treatment. The individual genotypes were randomized within each main plot. The experiment included side and end border rows. Additional sown pots were used for soil moisture determinations.
Water-stress treatment
From the beginning of the experiment, pots in main plots were watered twice per week to soil saturation (normal watering). Plants from the well-watered control group were watered throughout the experiment. Pots containing well-watered (control) plants were placed on capillary matting, whereas pots of treatment plants were allowed to drain freely. When 50% of plants reached the flag-leaf stage (week 17, 1.5 weeks after the end of the vernalization period) water was withheld from plants of stress treatment main plots for 10 d. The start of the stress treatment with respect to plant development was designed to mimic in situ late spring and early summer water stress. Following the initial water stress period, the plants in the water-withheld treatment were given water to soil saturation such that they recovered rapidly from treatment-induced wilting. In order to induce a more severe stress, water was withheld for a second time from the stress treatment main plot for an additional 2 weeks (from mid-week 19). The second, longer water stress period caused more damage to the plants (e.g. wilting of all leaves, leaf yellowing and rolling). These effects could not be reversed when normal watering was resumed (mid-week 21). Plants were covered with perforated bags after seed set to prevent loss of seed when ears shattered at maturity. The experimental conditions enabled stressed plants to reach full maturity and yield viable seed.
The water deficit of the soil medium after each of the two periods of water stress was determined according to Teulat et al. (Teulat et al., 1997a). The fresh weight (FW) of the soil medium of three pots of the water-stress treatment main plots was taken at the end of the first and second water-stress treatments. The dry weight (DW) of each soil sample was obtained after oven-drying for 4 d at 100 °C. The samples were then soaked with water and the moisture content (MW) of the soil medium at field capacity was measured 1 d after complete saturation. The moisture content (M) relative to field capacity was calculated using the formula M=(FW-DW)/(MW-DW)x100, and amounted to 35.4% and 16.2% at the end of the first and second water-stress treatments, respectively.
Data collection
Fifteen characters related to plant development, morphology, fertility and yield were recorded for each plant (Table 1). Awning time (AT, days from sowing to emergence of awns from flag leaf auricles, minus vernalization period, i.e. -70 d) and flowering time (FT, days from sowing to extrusion of anthers on leading spikes, -70 d) were recorded. At harvest time (week 28), plant height (PH) was measured from soil level to the collar of leading spikes and the total number of tillers (NT, fertile and infertile) were counted. Plants were cut at soil level and culms left for 4 weeks in the glasshouse to dry thoroughly. The harvested material (including disarticulated rachis segments) was weighed to determine total amount of above-ground dry matter (TDM). Rachis segments, possessing three florets (one fertile central and two infertile lateral), were de-awned and the number and weight of both fertile and sterile rachis segments obtained (NFRS, WFRS, NSRS, WSRS). From this set of nine primary traits, a secondary set of (six) characters was derived by simple mathematics: total number of rachis segments (TNRS), percentage of fertile rachis segments (PFRS), total rachis segment weight (TRSW), harvest index (HI=WFRS/TDM), 1000 fertile rachis segment weight (TFRSW) and 1000 sterile rachis segment weight (TSRSW).
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Data analysis
Analyses of variance (ANOVA) were performed on each trait to investigate the effects of the stress treatment on genotypes sampled from different soil types, and first order interactions. Genotypes were treated as a fixed effect because they were grown in a replicated experiment (three genotypes per treatment) designed to examine the effects of water stress imposed on the genotypes chosen for this study. Data sets were transformed before ANOVA if distribution of residuals was not random. While square root transformations were performed on NFRS data, loge transformations were used for WSRS data. As different genotypes had been sampled from the two soil types, the effect of soil type and its interaction with treatments were analysed by using an orthogonal contrast to partition the genotype and genotypextreatment sums of squares.
Principal component analyses (PCA) were performed using the primary traits to partition plant performance and morphology. The mean trait values obtained from the whole experiment, i.e. data from control (C) and stress treatment (S) main plots, were used for PCA, hereafter referred to as C&S data set. A second data set relating to stress performance was created by calculating 100x(C-S)/C for individual traits. Principal components were then derived from this (C-S)/C data set to identify stress-tolerant genotypes, i.e. genotypes that were least affected by the water-stress treatment.
Since PCA plots demonstrated differences in variability between C and S, and between TR and B, the ‘Bartlett's Test for homogeneity of variances’ was performed using the GENSTAT procedure ‘vhomogeneity’. The ‘Mann–Whitney U Test’ was used to determine significant differences between C and S, and between TR and B.
PCA was also conducted using two sets of three easily measured traits (TDM, PH and WFRS, and TDM, PH and NT) to examine whether identification of stress-tolerant genotypes was possible when analysing a reduced number of traits.
Associations among the 15 plant characteristics were examined by regression analyses using the control (C), stress (S) and (C-S)/C data sets.
The stress intensity coefficient (D) was calculated according to Fischer and Maurer (Fischer and Maurer, 1978), where
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Analyses of variance and principal component analyses were performed using GENSTAT for Windows computer software (Version 4.0; Rothamsted, 1996).
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Results |
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Analysis of variance (ANOVA)
The expression of ten out of 15 traits was significantly affected by the stress treatment (P<0.05, Table 1
). This included six out of seven yield-related traits (TNRS, TRSW, NFRS, WFRS, HI, TFRSW; with TDM being of borderline significance, P=0.052), both morphological traits (PH, NT), and two of the four fertility-related traits (NSRS, WSRS). No significant treatment effects were detected for individual developmental traits (AT and FT), which provides evidence for uniformity in plant development within the experimental plot. Genotype effects were significant for a large number of traits, 11 out of 15 (P<0.05) indicating a high level of genetic variability (Table 1). Genotypextreatment interactions were also detected for eight traits, indicating variable performance of genotypes in different growing conditions. No genotypextreatment interactions were found for awning and flowering time. This was not surprising as the experiment was primarily designed to examine yield stability.
Significant differences between the mean performance of the lines from TR and B were evident for nine characters, and were most pronounced for the developmental and morphological traits. The B genotypes were, on average, earlier, taller and produced more stems than the TR genotypes (Tables 1, 2). Soil typextreatment interactions were most pronounced for the yield traits, indicating highly variable performance of the lines within groups (TR and B) over treatments.
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Changes in trait means
Because of the major effect of soil type and its interaction with treatment for a number of characters, the means and ranges of each treatment/soil type combination have been estimated separately (Table 2). The ranges observed for many characteristics were, in general, relatively large. Basalt genotypes were shown to out-perform TR genotypes under well-watered conditions (C) as determined by PH, NT, TDM, TRSW, TNRS, and PFRS. However, B genotypes were affected more by the stress treatment than TR genotypes.
Apart from HI, all yield-related traits showed evidence of cross-over interactions (Baker, 1988): TR means were less than B means under the control treatment but greater under stress. The fact that TR genotypes had higher HI values under water-stress and non-stress conditions indicates that this character may be beneficial in reducing yield loss, thereby maximizing reproduction under stressed conditions.
Principal component analysis
Principal component analysis (PCA) was performed on data from the combined control and treatment data sets (C&S). The first three principal components explained 88.8% of the observed variation. The pc1 accounted for 47.9% of the variation and showed the largest loading values with yield-related and morphological characters. The pc2 accounted for 22.9% and pc3 18.0% of the observed variation, and shared the largest loading values with developmental and fertility related traits, respectively (Table 3).
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Variability in relation to yield-related traits forming pc1 was significantly greater in the control group than in the stress treatment group according to Bartlett's test (P=0.0001; Fig. 1
). PCA indicates that the genetic diversity present in the germplasm can be more widely expressed when plants are grown under favourable conditions.
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Genotype 66 showed very good performance under control conditions but was severely affected by water stress (Fig. 1
). In contrast, genotypes 18 and 19 showed relatively small effects of stress, and genotypes 20, 33 and 34 showed improved performance under water stress. This disparity is typical of the performance of several TR genotypes and also evident from the observed soil typextreatment interactions (Table 1). Interestingly, two genotypes, 93 and 100, had relatively high yields in both control and stress treatments.
PCA based on (C-S)/C data was used to define water stress-tolerant genotypes. The principal components shared the largest absolute loading values with yield (pc1), developmental (pc2), and morphological, developmental and fertility-related characters (pc3). However, pc1 accounted for only 34.6% of the variation, which is considerably less than the 47.9% variation accounted for by pc1 when using the C&S data set (Table 3). The relative dispersion of the genotypes demonstrates a high level of genetic diversity for water-stress tolerance in the germplasm examined (Fig. 2). Genotypes at the extremes of the PCA plot include 11, 20, 66, and 84. Genotype 66 showed the greatest yield reduction whereas genotypes 18, 19, 20, 33, and 34 were least affected by the water-stress treatment, with genotype 34 providing the highest TDM mean (data not shown). Two B genotypes, 93 and 100, were affected by water stress, but produced relatively high yields under both control and stress conditions (Fig. 1). The range of responses to the imposed water stress was significantly greater in the TR genotypes for yield-related traits (pc1; P=0.0047 according to Bartlett's test) than in B genotypes. The Mann–Whitney U test showed that the TR genotypes were significantly less susceptible to yield losses than the B genotypes (P=0.030 for pc1). Furthermore, the development of TR genotypes, particularly 40 and 11, was accelerated by the water-stress treatment (P=0.010 for pc2 according to Mann–Whitney U test).
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Neighbouring genotypes with similar (e.g. 33 and 34) or contrasting (e.g. 40 and 41) responses were found (Figs 1
, 2). Genotypes showing little developmental response to water-stress treatment (12, 28, 66, and 93) can be found close to the zero axis of pc2 (Fig. 2). PCA based on PH, TDM and NT, or PH, TDM and WFRS produced similar groupings of stress-tolerant genotypes (18, 19, 28, 33, 34 or 18, 19, 20, 28, 33, 34, 40, respectively) as PCA based on nine traits (plots not shown).
When individual pc1 scores were plotted against corresponding metre position of the genotypes on the 100 m transect (Fig. 3) some neighbouring genotypes had very similar responses (e.g. groupings of 2, 4, 5, and 6; 18 and 19; 33 and 34; 37 and 38; 40 and 41; 55 and 56; 95 and 96; 99 and 100). Such patterns may indicate that these genotypes are genetically identical or similar. At the same time, large contrasts can be found between neighbours (such as 20 and 22; 30 and 33; 34 and 37; 76 and 77).
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Results of regression analyses
Moderately high positive associations were detected among traits when plants were grown under well-watered conditions. To avoid spurious significant results due to examining a large number of correlations, only correlations with significance <0.01 are given. For example, positive correlations were detected between PH and TDM (0.72, P<0.001), PH and NFRS (0.51, P<0.001), PH and WFRS (0.65, P<0.001), between NT and TDM (0.46, P<0.01), NT and NFRS (0.63, P<0.001) and NT and WFRS (0.47, P<0.01), and between TDM and NFRS (0.76, P<0.001) or TDM and WFRS (0.84, P<0.001). Under water-stress conditions, PH was negatively correlated with phenology, AT (-0.45, P<0.01) and FT (-0.56, P<0.001), indicating that taller plants flowered earlier. When the relative performances (C-S)/C were examined, weak associations were detected, e.g. between PH and TDM (0.42, P<0.01) and WFRS (0.36, P<0.01), and between NT and TDM (0.45, P<0.01).
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Discussion |
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Previous diversity studies on the Tabigha wild barley population were confined to characterizing phenotype and genotype, and associations with soil type (Nevo et al., 1981
, 1983, 1986) and did not attempt to define responses to experimentally imposed stress. The stress imposed in this experiment (D=0.4) can be regarded as being intermediate compared to the severe drought stress (D=0.6–0.7) observed under field conditions (S Ceccarelli, personal communication). Nevertheless, the treatment was effective in significantly altering phenotypic traits in the wild barley lines studied. Although data were obtained from plants grown in pots, these results can be related to in situ performance. Genotypes from TR, which are better adapted to naturally occurring drought stress, were more tolerant to experimentally imposed water stress than B genotypes. When individual pc1 scores from the (C-S)/C data set were sorted in a descending fashion (data not presented), eight out of the top 10 lines were TR genotypes, whereas eight B genotypes were found amongst the 10 least tolerant lines.
In this experiment the TR genotypes flowered later than B genotypes which seems to contradict in situ observations where TR plants flower earlier than B (Nevo et al., 1988). However, TR genotypes responded to imposed water stress by accelerating their development (pc2; Fig. 2) inferring an escape mechanism. In contrast, the development of B genotypes was unchanged by treatment. Plants growing on TR in situ are continually subjected to water stress, and accelerated development may begin at a much earlier stage than that observed in the present study.
Physiology of drought tolerance in barley
Wild barley germplasm has been tested for physiological traits associated with abiotic stress tolerance (Robinson et al., 2000). In addition to biomass changes under experimentally imposed stress, measurements included shoot and/or root stable isotope discrimination (
13C and 15N), %C and %N. The abundance of carbon and nitrogen isotopes has been used as a screening tool to assess barley genotypes for their responses to abiotic stress (Handley et al., 1997). The responses to salt stress of 30 wild barley lines from the Fertile Crescent, which included two genotypes from Tabigha, one from TR and one from B have been studied (Pakniyat et al., 1997). The most salt susceptible genotype of the 30 lines studied was the Tab-B genotype, with the Tab-TR genotype being intermediate in terms of shoot sodium content. The 13C data of these lines under salt stress also showed differences, with Tab-B having less negative 13C than Tab-TR. Differences in carbon isotope discrimination are known to reflect differences in water-use efficiency (Farquhar and Richards, 1987). Other physiological traits of interest with respect to drought tolerance mechanisms include accumulation of abscisic acid (ABA), content of soluble stem carbohydrates, stomatal conductance, osmotic adjustment, and leaf water content (Grossi et al., 1992; Gonzalez et al., 1999; Teulat et al., 1997a, b). Given the highly diversified responses to water stress, contrasting genotypes from TR and B may be selected for further studies to elucidate specific mechanisms associated with water-stress tolerance.
Population dynamics
The spatial distribution of wild barley genotypes is controlled by biological factors such as pollination and seed dispersal, and ecological factors such as edaphic variation. Barley is a predominantly inbreeding species, outcrossing rates range from 0–9.6% (Brown et al., 1978). Seed can drop to the ground upon ear shattering or be moved several kilometres attached to the coats of animals (e.g. grazing sheep and goats). These modes of dispersal may explain the occurrence of a few genotypes with atypical characteristics, such as the B genotypes 76 and 84 that display relatively low stress susceptibility, and TR genotypes 22 and 29 that demonstrate below-average stress tolerance. No clear-cut difference was observed at the transition region between TR and B involving genotypes 45, 48, 50, and 51 (Fig. 3). TR genotypes 2, 4, 5 and 6, which occur at the beginning of the transect, form another atypical group having lower than expected stress tolerance (Fig. 3). This may reflect the presence of micro-niches along the transect (bare rock, deep soil, inter-mixing, etc.), but detailed soil-profiling would be required to test this.
Wild barley and crop improvement
The wild barley population at Tabigha provides germplasm that has potential for crop improvement. Wild barley, Hordeum spontaneum, forms part of the primary gene pool of cultivated barley (Harlan, 1995), and is often cited as a source of novel variation for resistance to pests, diseases, abiotic stresses, and quality traits (Nevo, 1992; von Bothmer, 1996; Ellis et al., 1993, 2000). Useful genes have also been extracted from landrace barley, H. vulgare, germplasm for mildew resistance (Jørgensen, 1992) and drought tolerance (Ceccarelli and Grando, 1996). However, the genetic variation available in the H. spontaneum gene pool is much greater than that found in either the cultivated or landrace, H. vulgare, gene pool (Powell, 1997). There are indications that wild barley can also contribute useful genes for drought tolerance (Grando and Ceccarelli, 1991, 1995; Gunasekara et al., 1994; Hadjichristodoulou, 1995; Lu et al., 1999).
Systematic approaches to increase the level of abiotic stress tolerance require the evaluation of genetic variability in the barley gene pool, both within and among populations. Variation for carbon isotope discrimination, an indicator of stress tolerance, has been found among populations of wild barley (Forster et al., 1994). In this study, large variation for water-stress tolerance was found within a population. Single populations such as Tabigha that exhibit rich phenotypic and genotypic diversity may provide valuable resources for traits of agronomic importance. Strategies for exploiting wild barley in crop improvement have been discussed (Forster et al., 2000).
The high incidence of cross-over interactions found in this study demonstrates that performance under stress cannot be predicted from performance in non-stress conditions. Thus, there is a need to screen and select for stress-tolerant lines in stress environments (Ceccarelli and Grando, 1996; Ceccarelli et al., 1998). Data from the work presented here also indicate that phenotypic assessment of yield stability, an important breeding objective, can be effectively determined by PCA of selected morphological characteristics. The water- stress-tolerant genotypes identified in the Tabigha wild barley population may be combined with breeding lines exhibiting high yield potential. Genotypic analysis in combination with physiological studies is required to establish whether the water-stress-tolerant lines are similar, i.e. deploy the same mechanisms. If different mechanisms are identified there is potential for recombining these for further improvement.
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Acknowledgments |
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The authors are grateful to Glyn Bengough, Richard Keith and Jackie Lyon for valuable advice and skilful technical assistance. The authors also thank Salvatore Ceccarelli (ICARDA, Syria) for critically reviewing the manuscript. Victor Ivandic holds a Marie-Curie fellowship as part of the EC programme for ‘Training and Mobility of Researchers’. Professor Eviatar Nevo wishes to thank the Israeli Discount Bank Chair of Evolutionary Biology and the Ancel-Teicher Research Foundation for financial support. The research at SCRI is supported by Grant-in-Aid from the Scottish Executive for Rural Affairs Department (SERAD).
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Notes |
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6 To whom correspondence should be addressed. Fax: +44 1382 562426. A list of all principal component scores can be made available on request.
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