The potential of synthetic hexaploid wheats to improve zinc efficiency in modern bread wheat

Abstract

Synthetic hexaploid wheats (Triticum aestivumL) derived from crosses between durum wheat [Triticum turgidum ssp. durum (Desf.) Husn.] and diploid wheat (Aegilops tauschii Coss.) have been developed as a means of transferring desirable characteristics of Aegilops tauschii Coss. such as disease resistance and abiotic stress tolerance into modern bread wheat genotypes. In a growth room experiment using soil culture, we studied a group of 30synthetic hexaploid wheat accessions together with modern wheat genotypes in order to identify new sources of zinc efficiency for further improvement of zinc efficiency in modern wheat genotypes. There was considerable genetic variation in expression of zinc deficiency symptoms (slight to severe), zinc efficiency (70–100%), shoot Zn concentration (5.8–10.5 and 33–53mg/kg DW under deficient and sufficient Zn, respectively), shoot Zn content (3.8–10.6 and 34.0–64.6g/plant, under deficient and sufficient Zn, respectively) and Zn utilization (0.096–0.172 and 0.019-0.033g DW/g Zn under deficient and sufficient Zn, respectively) within synthetic accessions. The presence of synthetic accessions with greater zinc efficiency (100%) than zinc efficient modern wheat genotypes (85%) indicates that the synthetic hexaploids can be used to improve current levels of zinc efficiency in modern wheat genotypes. Synthetic hexaploids may also be a good source of high grain Zn concentration (28–66mg Zn/kg seed DW).

Full text

Plant and Soil 262: 23–32, 2004.
© 2004 Kluwer Academic Publishers. Printed in the Netherlands.
23
The potential of synthetic hexaploid wheats to improve zinc efficiency in
modern bread wheat
Y. G e n c
1,3
&G.K.McDonald
2
1
Molecular Plant Breeding CRC, Waite Campus, PMB 1, Glen Osmond SA 5064, Australia.
2
School of Agriculture
and Wine, University of Adelaide, Waite Campus, PMB 1, Glen Osmond SA 5064, Australia.
3
Corresponding
author
∗
Received 19 August 2003. Accepted in revised form 21 October 2003
Key words: bread wheat, synthetic hexaploid wheat, Triticum aestivu m, zinc deficiency, zinc efficiency
Abstract
Synthetic hexaploid wheats (Triticum aestivum L) derived from crosses between durum wheat [Triticum turgidum
ssp. durum (Desf.) Husn.] and diploid wheat (Aegilops tauschii Coss.) have been developed as a means of transfer-
ring desirable characteristics of Aegilops tauschii Coss. such as disease resistance and abiotic stress tolerance
into modern bread wheat genotypes. In a growth room experiment using soil culture, we studied a group of
30 synthetic hexaploid wheat accessions together with modern wheat genotypes in order to identify new sources
of zinc efficiency for further improvement of zinc efficiency in modern wheat genotypes. There was considerable
genetic variation in expression of zinc deficiency symptoms (slight to severe), zinc efficiency (70–100%), shoot Zn
concentration (5.8–10.5 and 33–53 mg/kg DW under deficient and sufficient Zn, respectively), shoot Zn content
(3.8–10.6 and 34.0–64.6 µg/plant, under deficient and sufficient Zn, respectively) and Zn utilization (0.096–0.172
and 0.019-0.033 g DW/µg Zn under deficient and sufficient Zn, respectively) within synthetic accessions. The
presence of synthetic accessions with greater zinc efficiency (100%) than zinc efficient modern wheat genotypes
(85%) indicates that the synthetic hexaploids can be used to improve current levels of zinc efficiency in modern
wheat genotypes. Synthetic hexaploids may also be a good source of high grain Zn concentration (28–66 mg Zn/kg
seed DW).
Introduction
Worldwide, zinc (Zn) deficiency is a chronic prob-
lem of cereal-grown soils, and has been the subject
of a large number of recent publications (Cakmak
et al., 1996, 1997, 1998; Graham et al., 1992; Takkar
and Walker, 1993). While addition of Zn-containing
fertilisers and soil-crop management (e.g., gypsum ap-
plication, amending soil with organic manures and
rotation) are general practices to correct deficiency
(Takkar and Walker, 1993), these practices are costly
and not always effective. For instance, in many cases,
adding fertiliser may not result in yields that are equiv-
alent to that produced by an efficient genotype with
∗
FAX No: +61 883037109.
E-mail: yusuf.genc@adelaide.edu.au
no additional fertiliser. Uptake of and response to Zn
fertiliser is affected greatly by environmental condi-
tions. For example, periods of dry weather will reduce
uptake of Zn, and in such cases crops may suffer from
micronutrient deficiency even after fertiliser has been
applied. A high level of micronutrient efficiency will
help crops cope with variable nutrient supplies and
provide a more stable alternative to a strategy based
only on fertiliser applications.
There is a general consensus that the best long term
and cost effective solution to overcoming the prob-
lem is through genetic improvement of the ability of
plant to grow and yield in soils of low available Zn
(Zn efficiency). Genetic variation for this trait has
been well documented for a number of cereal spe-
cies (Cakmak et al., 1996, 1998; Genc et al., 2002;
Graham et al., 1992) and currently efficient genotypes

24
are routinely incorporated into breeding programs to
improve Zn efficiency. However, in wheat, an upper
limit to Zn efficiency appears to have been reached.
New sources of micronutrient efficiency would be de-
sirable to allow further improvements to be produced.
There appears to be promising sources of micronutri-
ent efficiency within Aegilops tauschii Coss. (Cakmak
et al., 1999a; 1999b) and development of new syn-
thetic hexaploids provides a new way of improving
micronutrient efficiency in hexaploid wheats.
Synthetic hexaploid wheat, Triticum aestivum L.
(2n=6x=42, AABBDD) is produced by crossing
durum wheat, Triticum turgidum ssp. durum (Desf.)
Husn. (2n=4x=28, AABB) with Aegilops tauschii
Coss. (2n=2x=14, DD). This relatively new ger-
mplasm has been reported to be a good source of
disease resistance as well as improving yield and qual-
ity (references in Ogbonnaya et al., 2001). However,
the potential of this germplasm for improving gen-
otypes with greater abiotic stress tolerance has not
been studied extensively except for a few studies on
salt tolerance, drought tolerance and herbicide resist-
ance. To date there has been only one study on the
potential of synthetic hexaploid wheats for improv-
ing Zn efficiency (Cakmak et al., 1999a). Even then
only a small number of synthetics were tested, and
they were not compared to modern hexaploid wheats.
Therefore, there is a need to examine Zn efficiency
in a larger number of synthetic hexaploid accessions
together with modern wheat genotypes of known Zn
efficiency in order to better evaluate the potential of
synthetic hexaploids for improving Zn efficiency of
modern bread wheat genotypes. The objective of this
study was to assess the potential of synthetic hexaploid
wheats for the improvement of Zn efficiency in bread
wheat.
Materials and methods
Plant material
The 30 synthetic hexaploid wheat (Triticum aes-
tivum L.) accessions used in this study were obtained
from Australian Winter Cereals Collection, Tam-
worth, QLD, Australia. For comparisons, modern
wheat genotypes of known Zn efficiency (Stylet, Tri-
dent, Zn-efficient; Cascades, moderately Zn-efficient;
Kukri, VM506 and RAC785-2, Zn-inefficient, Lewis
et al., 2001) were also included in this study. The
availability of a mapping population (The Interna-
tional Triticeae Mapping Initiative, ITMI) from a
cross between the synthetic accession 26818 [AL-
TAR84/AE.SQUARROSA (219) CIGM86.940] and
modern bread wheat genotype Opata (Nelson et al.,
1995) had led us to include Opata in the present study
as well to see if these two genotypes differed in Zn
efficiency. If so, this population could be studied to
understand not only genetic control of this trait, but
to develop molecular markers for breeding programs.
The seeds of all synthetic hexaploids and modern
wheat genotypes were multiplied in a medium named
University of California (UC) mix (Barker et al., 1998)
under glasshouse conditions prior to the experiment in
order to minimise variation in seed nutrient content in
particular Zn. The seeds from UC-mix grown plants
were analysed for nutrient composition prior to the
experiment.
Bio-assay
The soil used in this study was a sandy soil (DTPA-
extractable Zn=0.07 mg/kg soil), named Mt. Com-
pass sand, which was collected near Mt. Barker,
South Australia. The soil was washed three times
with doubled-deionised water and air-dried. One kg
samples of air-dried soil were placed into plastic
bags. Following addition and mixing of 0.5% cal-
cium carbonate throughout the soil, basal nutrients
were added to the surface of the soil and allowed to
dry. The contents in the plastic bags then were mixed
again and placed in cylindrical PVC pots with ap-
proximate dimensions of 6.5 × 30 cm (diameter ×
depth). The basal nutrients consisted of (in mg/kg
soil) NH
4
NO
3
(350); K
2
HPO
4
(90); K
2
SO
4
(120);
MgSO
4
, 90; MnSO
4
, (3.0); CuSO
4
(5); H
3
BO
3
(0.1);
CoSO
4
·7H
2
O(1);FeSO
4
·7H
2
O (1.4); MoO
3
(0.005);
NiSO
4
·6H
2
O (0.15). There were two Zn treatments,
deficient (0.025 mg Zn/kg soil) and adequate (1 mg
Zn/kg soil). Previous studies found that the differ-
ences in Zn efficiency and visual scores between the
Zn-efficient and Zn-inefficient genotypes were largest
at 0.025 mg Zn/kg soil, while at the adequate level
(≥ 0.25 mg Zn/kg soil), both Zn-efficient and Zn-
inefficient genotypes had similar responses.
Growth conditions
The seed was surface-sterilised and germinated on
moist filter paper in petri dishes for 24 h at room
temperature. Four pre-germinated seeds were trans-
planted into each pot and thinned to two plants after
emergence. Plants were grown in a growth cabinet
set at 20/15
◦
C day/night temperature, and 14/10 h

25
day/night day length regime. Pots were randomised
and watered daily to weight maintaining 12% field ca-
pacity moisture content. Plants were harvested 36 days
after sowing. Shoots were cut off at 1 cm above the soil
level. The samples were oven-dried at 65
◦
C for 48 h,
weighed and processed for nutrient analysis.
Measured traits
Several traits were measured during and at the end of
the experiment. Visual symptoms were recorded using
a scale of 1-9; 1=healthy green plants, 2=reduction
in shoot growth, 3=foliar symptoms (chlorotic areas)
appearing on first leaves, 4=chlorotic areas scattered
across the first leaves, 5=large chlorotic areas on
the first leaves, 6=leaves collapsing in the middle,
7=chlorotic areas developing on second leaves,
8=both first and second leaves turning pale yellow,
and 9=dead growing points.
Relative shoot dry matter (Zn efficiency) was cal-
culated as the ratio of shoot dry matter at deficient Zn
supply to that at sufficient Zn supply, as described by
Graham (1984).
Zn concentration in the shoot was measured by
Inductively Coupled Plasma (ICP) Spectrophotometer
(Zarcinas, 1984). The values were expressed on a
dry weight basis (mg Zn/kg DW). Shoot Zn content
(µg/plant) was calculated as shoot dry weight multi-
plied by shoot Zn concentration. Relative Zn content
was expressed as the ratio of Zn uptake under Zn defi-
ciency to that under Zn sufficiency. Zn utilisation was
estimated as shoot dry matter produced per unit of Zn
content in the shoot (g DM/µgZn).
Statistical analysis
The experiment was set up as split plot design (37 gen-
otypes × 2Znlevels× 3 replicates). Zn treatments
and genotypes were assigned to whole plots and sub-
plots, respectively. A linear mix model fitted by the
residual maximum likelihood (REML) method where
genotypes were fixed was considered since the pur-
pose of this study was to estimate genotypic effects.
Analysis of variance, pair-wise comparisons, data
transformation and cluster analysis were performed as
described elsewhere (Genc et al., 2002). Simple lin-
ear correlation analysis was carried out to estimate the
degree of linear association between the two variables
(e.g., seed Zn content versus visual scores) (Gomez
and Gomez, 1984).
Results
Visual symptoms
Typical deficiency symptoms of Zn, appearing first as
stunted shoot growth followed by varying degrees of
chlorosis and necrosis of leaves depending on severity
of Zn deficiency stress, became visible in synthetic ac-
cessions 29640, 29641, 29642, 29652, 29659, 29664,
29671, 29678, and 29680 at deficient soil Zn sup-
ply, Zn
0.025
at 28 days after transplanting (DAT).
At this stage, Zn-efficient genotypes (Stylet, Trident,
Cascades) showed only reductions in growth, while
Zn-inefficient genotypes (VM506, Kukri, RAC875-
2) developed chlorotic stripes on young leaves. By
harvest (36 DAT), deficiency symptoms became more
severe in sensitive genotypes, and there was consid-
erable variation in expression of deficiency symptoms
amongst the synthetic accessions (slight to severe) as
well as between Zn-efficient (slight) and Zn-inefficient
(severe) modern wheat genotypes (Figure 1).
Shoot dry matter and Zn efficiency
Zn fertilisation either increased or did not influence
shoot dry matter of synthetic hexaploid accessions.
Those that responded to Zn fertilisation included
26818, 29640, 29660, 29661 and 29671. All the mod-
ern wheat genotypes responded to Zn fertilisation,
irrespective of their efficiencies (Figure 2). Amongst
the synthetic accessions, there were also significant
genetic differences in shoot dry matter under both
Zn deficiency and sufficiency. Under Zn deficiency,
there was a 3-fold difference between the accessions
with highest (29677) and lowest dry matter (26818).
Similarly, the same accessions represented the highest
and lowest dry matter accumulators under Zn suffi-
ciency. Overall, synthetic accessions had higher dry
matter under Zn deficiency, while modern genotypes
had higher dry matter under Zn sufficiency.
Zn efficiency (relative shoot dry matter) differed
markedly amongst the synthetics and modern wheat
genotypes, ranging from 70 to 100%. Synthetic ac-
cessions 29637, 29642, 29659, 29676, and 29677
had significantly higher Zn efficiency than modern
Zn-efficient genotypes Stylet, Trident and Cascades
(Figure 3). Within the modern wheat, Zn-efficient
genotypes achieved greater Zn efficiency than Zn-
inefficient genotypes. Overall, there was a greater
range in Zn efficiency within the synthetic accessions
than within modern wheat genotypes.

26
Figure 1. Visual scores in synthetic hexaploids and modern wheat genotypes grown at Zn0.025 at 36 DAT (2 = slight symptoms, 7 = severe
symptoms). Genotypes were ordered in descending order of Zn efficiency.
Figure 2. Effects of Zn fertilisation (mg/kg soil) on shoot dry matter (g/plant) in synthetic hexaploids and modern wheat genotypes at 36 DAT.
All the synthetic accessions and modern genotypes were ordered in descending order of Zn efficiency. The vertical bars represent standard
errors based on three replicates.
Concentration and content of Zn in shoots
Zn concentrations in the shoots were affected by Zn
fertilisation and genotype. At Zn
0.025
, the majority
of the synthetic accessions and modern wheat geno-
types had Zn concentrations below the critical level
(10–11 mg/kg in the shoot for modern wheat gen-
otypes Stylet, Cascades, and RAC875-2; Y Genc
and GK McDonald, unpublished) (Table 2). Despite
this, there was almost a 2-fold difference in Zn con-
centration amongst the synthetic accessions (5.8 to
10.5 mg/kg DW in 29649 and 29661, respectively).
Modern wheat genotypes showed a similar but slightly
smaller range (6.7–10.2 mg/kg DW). With adequate
Zn supply (Zn
1
), all the synthetic accessions and mod-
ern wheat genotypes achieved a 4–7-fold increase in
Zn concentration when compared with deficient Zn
supply. There was also a considerable variation in Zn
concentration amongst the synthetic accessions (33 to
53 mg/kg DW for 29678 and 29642, respectively) and
modern wheat genotypes (31 to 45 for RAC875-2 and
Trident, respectively).
Similar to our observation with shoot Zn con-
centration, shoot Zn content was affected by both
genotype and Zn fertilisation. At adequate Zn sup-
ply, there was a 6–8-fold increase in Zn content when
compared with deficient Zn supply. There was also
considerable variation in Zn content amongst the syn-
thetic accessions and modern wheat genotypes under
both Zn deficiency and sufficiency. Shoot Zn content
ranged from 3.8–10.6 µg/plant (26818 and 29658),
and 34.0–64.6 µg/plant (26818 and 29642) under
Zn deficiency and sufficiency, respectively (Table 2).
The range observed in modern wheat genotypes was
6.4–10.2 µg/plant (RAC875-2, Stylet) and 43.5–
59.7 µg/plant (RAC875-2, Trident) at deficient and
sufficient Zn, respectively.
Zn utilisation (shoot dry matter produced per unit
of Zn in the shoot) also varied with genotype and
Zn fertilisation. In contrast to Zn concentration and
content in the shoots, Zn fertilisation resulted in ap-

27
Table 1. Pedigree and seed Zn concentration and content of synthetic hexaploids and modern wheat genotypes
AUS# Pedigree Zn Zn
concentration content
(mg/kg DW) (µg/seed))
1 26818 ALTAR84/AE.SQUARROSA (219) CIGM86.940 66 3.5
2 26827 68112/WARD//AE.SQUARROSA (369) CIGM88.1313 35 1.9
3 26828 68112/WARD//AE.SQUARROSA (369) CIGM88.1313 49 2.5
4 26835 68.111/RGB-U//WARD RESEL/3/STIL/4/AE.SQUARROSA (783) CIGM89.538 50 2.6
5 26891 YAV_2/TEZ//AE.SQUARROSA (895) CIGM90.910 35 1.8
6 29503 CROC_1/AE.SQUARROSA (224) //OPATA 49 2.4
7 29636 CPI/GEDIZ/3/GOO//JO69/AE.SQUARROSA (208) 31 1.6
8 29637 ALTAR 84/AE.SQUARROSA (211) 54 2.7
9 29640 DVERD_AE.SQUARROSA (247) 31 1.6
10 29641 AOS/AE.SQUARROSA (269) 46 2.2
11 29642 ACO89/AE.SQUARROSA (309) 31 1.5
12 29649 GAN/AE.SQUARROSA (434) 59 3.2
13 29651 YAV79//DACKRABI/3/SNIPE/4/AE.SQUARROSA (447) 34 1.8
14 29652 DOY1/AE.SQUARROSA (488) 38 2.0
15 29656 68.111/RGB-U//WARD/3/FGO/4/RABI/5/AE.SQUARROSA (882) 43 2.1
16 29657 RABI//GS/CRA/3/AE.SQUARROSA (895) 28 1.5
17 29658 YAV_2/TEZ//AE.SQUARROSA (249) 47 2.5
18 29659 68.111/RGB-U//WARD/3/FGO/4/RABI/5/AE.SQUARROSA (809) 42 2.2
19 29660 68.111/RGB-U//WARD/3/FGO/4/RABI/5/AE.SQUARROSA (878) 30 1.5
20 29661 68.111/RGB-U//WARD/3/FGO/4/RABI/5/AE.SQUARROSA (878) 46 2.1
21 29662 68.111/RGB-U//WARD/3/FGO/4/RABI/5/AE.SQUARROSA (878) 33 1.7
22 29663 CETA/AE.SQUARROSA (895) 49 2.5
23 29664 CETA/AE.SQUARROSA (895) 34 1.6
24 29667 SCOOP_1/AE.SQUARROSA (634) 45 2.3
25 29671 GARZA/BOY//AE.SQUARROSA (165) 42 2.0
26 29675 YAV_2/TEZ//AE.SQUARROSA (170) 36 1.7
27 29676 CROC_1/AE.SQUARROSA (256) 37 1.8
28 29677 DOY1/AE.SQUARROSA (258) CIGM93.207 34 1.8
29 29678 DOY1/AE.SQUARROSA (264) CIGM93.211 33 1.7
30 29680 CPI/GEDIZ/3/GOO//JO69/CRA/4/AE.SQUARROSA (390) 45 2.5
31 Cascades Aroona
∗
3/Tadorna.Inia66 43 2.0
32 Kukri DT6870 41 1.8
33 Opata Bluejay/Jupateco F 73 46 2.3
34 RAC875-2 Rac655/Sr214
∗
Lance//4
∗
Bayonet 53 2.1
35 Stylet Molineux/Rac698//Rac698 (Trident) 33 1.5
36 Trident VPM1/5/Cook//4
∗
Spear 43 2.1
37 VM506 CIQ/Matong//VF508/3/VF19 35 1.6
Accessions appearing more than once represent independent hybrids of the same cross.
AUS# number refers to accession number at Australian Winter Cereals Collection Centre, Tamworth.
The seed Zn concentration values were based on 20 seeds per genotype
proximately 4–7-fold decrease in Zn utilisation in all
the synthetic accessions and modern wheat genotypes
(29658 and 29649, the lowest and highest decrease,
respectively) (Table 2). There were significant genetic
differences in Zn utilisation under Zn deficiency and
sufficiency. Under Zn deficiency, Zn utilisation var-
ied from 0.096 g DW/µg Zn to 0.172 (29661 and
29652, respectively). When Zn supply was adequate,
a considerably smaller variation was observed; 0.019–
0.033 g DW/µg Zn for 26835 and 29863, respectively.

28
Table 2. Effects of Zn fertilisation (Zn
0.025
and Zn
1
) on shoot Zn concentration (µg/g), shoot Zn content (µg/
plant) and Zn utilisation (g dry matter/µg Zn) in synthetic hexaploids and modern wheat genotypes at 36 DAT
Shoot Zn concentration Shoot Zn content Zn utilisation
Zn
0.025
Zn
1
Zn
0.025
Zn
1
Zn
0.025
Zn
1
29677 6.0 (0.77) 41.7 (1.61) 8.6 (2.9) 58.5 (7.6) 0.169 (0.41) 0.025 (0.16)
29676 7.0 (0.84) 46.3 (1.66) 8.1 (2.8) 51.6 (7.2) 0.146 (0.38) 0.022 (0.15)
29637 8.6 (0.93) 42.3 (1.62) 9.4 (3.1) 46.3 (6.8) 0.119 (0.34) 0.024 (0.15)
29642 7.7 (0.88) 52.7 (1.72) 9.2 (3.0) 64.5 (8.0) 0.132 (0.36) 0.019 (0.14)
29659 7.6 (0.87) 49.7 (1.70) 8.0 (2.8) 52.9 (7.3) 0.138 (0.37) 0.020 (0.14)
29657 7.3 (0.86) 40.7 (1.61) 8.8 (3.0) 52.0 (7.2) 0.141 (0.37) 0.025 (0.16)
26828 9.6 (0.98) 48.7 (1.69) 9.0 (3.0) 47.8 (6.9) 0.105 (0.32) 0.021 (0.14)
29651 7.9 (0.90) 49.0 (1.69) 8.1 (2.8) 52.8 (7.3) 0.128 (0.36) 0.020 (0.14)
26827 7.6 (0.88) 49.0 (1.69) 7.6 (2.7) 52.6 (7.3) 0.132 (0.36) 0.021 (0.14)
29636 7.0 (0.84) 43.7 (1.64) 7.0 (2.6) 45.1 (6.7) 0.147 (0.38) 0.023 (0.15)
29656 7.2 (0.85) 43.7 (1.64) 7.0 (2.6) 46.2 (6.8) 0.144 (0.38) 0.023 (0.15)
29662 6.5 (0.80) 42.3 (1.62) 7.3 (2.7) 51.9 (7.2) 0.161 (0.40) 0.024 (0.16)
29641 8.6 (0.93) 48.3 (1.68) 9.9 (3.1) 61.1 (7.8) 0.118 (0.34) 0.020 (0.14)
29678 6.1 (0.78) 32.7 (1.51) 6.6 (2.6) 38.3 (6.2) 0.165 (0.41) 0.031 (0.18)
29658 7.9 (0.90) 33.3 (1.52) 10.6 (3.2) 49.1 (7.0) 0.127 (0.36) 0.030 (0.17)
29503 8.4 (0.92) 39.7 (1.60) 9.1 (3.0) 47.9 (6.9) 0.120 (0.35) 0.026 (0.16)
29680 6.5 (0.81) 39.0 (1.59) 8.3 (2.8) 55.0 (7.4) 0.155 (0.39) 0.026 (0.16)
26891 7.1 (0.85) 47.3 (1.68) 5.7 (2.3) 41.9 (6.5) 0.144 (0.38) 0.021 (0.14)
29649 5.8 (0.76) 43.3 (1.64) 6.7 (2.6) 57.4 (7.6) 0.172 (0.41) 0.024 (0.15)
29663 8.4 (0.92) 45.0 (1.65) 9.7 (3.1) 59.4 (7.7) 0.121 (0.35) 0.022 (0.15)
26835 7.8 (0.89) 52.7 (1.72) 6.4 (2.5) 51.0 (7.1) 0.130 (0.36) 0.019 (0.14)
29664 7.6 (0.88) 48.7 (1.69) 7.6 (2.8) 57.3 (7.6) 0.134 (0.37) 0.021 (0.14)
29652 5.9 (0.76) 37.3 (1.57) 6.4 (2.5) 47.5 (6.9) 0.174 (0.42) 0.027 (0.16)
29671 7.9 (0.90) 48.0 (1.68) 7.6 (2.7) 55.1 (7.4) 0.128 (0.36) 0.021 (0.15)
29675 8.4 (0.92) 41.7 (1.62) 9.6 (3.1) 57.5 (7.6) 0.120 (0.35) 0.024 (0.16)
29640 6.8 (0.83) 40.3 (1.60) 6.5 (2.5) 49.0 (7.0) 0.146 (0.38) 0.025 (0.16)
29667 8.3 (0.92) 47.7 (1.67) 7.0 (2.6) 51.9 (7.2) 0.121 (0.35) 0.022 (0.15)
26818 7.0 (0.84) 48.7 (1.69) 3.8 (1.9) 34.0 (5.8) 0.144 (0.38) 0.021 (0.14)
29660 6.8 (0.83) 44.7 (1.65) 6.6 (2.6) 55.9 (7.5) 0.147 (0.38) 0.023 (0.15)
29661 10.5 (1.02) 50.7 (1.70) 9.2 (3.0) 57.8 (7.6) 0.096 (0.31) 0.020 (0.14)
Opata 10.2 (1.01) 49.0 (1.69) 12.2 (3.5) 61.7 (7.9) 0.098 (0.31) 0.021 (0.14)
Stylet 9.0 (0.95) 44.0 (1.64) 10.2 (3.2) 58.3 (7.6) 0.111 (0.33) 0.023 (0.15)
Trident 8.4 (0.93) 45.3 (1.65) 9.3 (3.0) 59.7 (7.7) 0.119 (0.34) 0.022 (0.15)
Cascades 7.0 (0.84) 32.3 (1.51) 8.2 (2.9) 46.7 (6.8) 0.143 (0.38) 0.031 (0.18)
VM506 8.5 (0.93) 39.3 (1.59) 8.5 (2.9) 56.2 (7.5) 0.118 (0.34) 0.026 (0.16)
RAC875-2 6.7 (0.82) 30.3 (1.48) 6.4 (2.5) 43.5 (6.6) 0.150 (0.39) 0.033 (0.18)
Kukri 7.9 (0.89) 34.3 (1.53) 7.2 (2.7) 51.8 (7.2) 0.129 (0.36) 0.029 (0.17)
Tukey’s HSD
b
0.05
Genotype x Zn fertilisation
Within Zn level (0.07) (0.4) (0.03)
Between genotypes (0.08) (0.4) (0.03)
a
Numbers in parentheses refer to averages obtained from the analysis of variance of transformed data (logarithmic-
transformation for Zn concentration, and square root-transformation for shoot Zn content and Zn utilisation)
b
The HSD
0.05
values are applicable to transformed data
The synthetic hexaploids and modern wheat genotypes were ordered in descending order of Zn efficiency

29
Figure 3. Zn efficiency rankings of synthetic hexaploids and modern wheat genotypes. Zn efficiency is calculated as the ratio of shoot dry
matter at Zn
0.025
to that at Zn
1
and expressed as percent. The vertical bar represents Tukey’s HSD
0.05
value for genotype effect.
Table 3. Groupings of genotypes based on hierarchical cluster analysis and the mean Zn effi-
ciency (%), deficiency score (0–9), and shoot dry matter at deficient and adequate Zn supply
(g/plant) for the group
Group Zn Deficiency Shoot dry matter Genotype
efficiency score Zn
0.025
Zn
1
189± 3.53.7 ± 0.43 1.17 ± 0.059 1.32 ± 0.058 29503, 29641, 29642, 29649,
29652, 29657, 29658, 29569,
29662, 29663, 29675, 29677,
29680, Opata, Cascades,
Stylet, Trident
288± 6.02.7 ± 0.43 0.98 ± 0.050 1.12 ± 0.045 26827, 26828, 29636, 29637,
29640, 29651, 29656, 29660,
29661, 29667, 29676
377± 6.25.4 ± 0.43 0.97 ± 0.047 1.27 ± 0.111 26835, 29664, 29671, 29678,
Kukri, RAC875-2, VM506
472± 4.53.8 ± 0.27 0.82 ± 0.095 1.05 ± 0.072 26818, 26891
Values are presented as mean ± s.e.m.; Zn
0.025
,Zn
1
; Zn applied at 0.025 and 1 mg/kg soil
Zn efficiency is calculated as the ratio of shoot dry matter at Zn
0.025
to that at Zn
1
and
expressed as percent.
Cluster analysis
Genotypes were grouped into four groups by cluster
analysis when truncated at the 80% level of similarity
(Table 3). Based on the genotypes of known Zn effi-
ciency and for practical purposes, groups 1 and 2 can
be considered as Zn-efficient, while groups 3 and 4
as Zn-inefficient. Group 1 had better seedling growth
than group 2 at adequate Zn supply, while group 3
showed more severe symptoms than group 4.
Discussion
This study demonstrates that there is considerable
variation in expression of visual symptoms and Zn ef-
ficiency amongst synthetic hexaploid accessions and
modern wheat genotypes studied. These differences
are most likely to be inherent and not affected by
seed Zn content as seed Zn content was similar in
majority of genotypes. This argument is also sup-
ported by the lack of a correlation between seed Zn
content and either visual symptoms or Zn efficiency
(d.f. = 35, r = 0.177, r = 0.071, non-significant
at P = 0.05, respectively). Previously, it has been
reported that seed Zn content can have a significant
effect on expression of visual scores and Zn effi-
ciency especially under Zn deficient conditions in
wheat (Rengel and Graham, 1995a) and barley (Genc
et al., 1999, 2000). Therefore, in evaluation studies,
seed with similar Zn content should be used. The
greater variation in Zn efficiency within the synthetic
accessions than within modern wheat genotypes indic-

30
ates that synthetic hexapoids offer potential for further
improvement of Zn efficiency in modern wheat. Obvi-
ously, in selecting for Zn efficiency, genotypes with
high Zn efficiency will be considered together with
high yield under Zn deficient conditions. This is im-
portant since there is not always a strong correlation
between Zn efficiency and yield under Zn deficiency.
In the present study, there was a significant but not
very strong relationship between absolute dry mat-
ter under Zn deficiency and Zn efficiency (d.f. = 35,
r = 0.513, P<0.01), indicating that not all Zn-
efficient genotypes will also have high yield under
Zn deficiency. For instance, the synthetic accessions
29677 and 29637 had similar Zn efficiencies, while
29677 had approximately 30% higher shoot dry matter
than 29637 under both Zn deficiency and sufficiency.
Based on the current results, we recommend 29677
as a Zn-efficient donor for improving Zn efficiency of
modern wheat genotypes. In addition, the synthetic
accessions with highest and lowest Zn efficiency can
be used in development of segregating or permanent
populations to study genetic control of Zn efficiency.
Despite the lack of correlation between seed Zn
content and Zn efficiency, greater variation in seed
Zn concentration or seed Zn content in synthetic
hexaploids than in modern wheat genotypes indic-
ates that synthetic hexaploids may also be a good
source of high seed Zn concentration or content. High
seed Zn is also important for human nutrition (Gra-
ham et al., 1999; Graham and Welch, 1996). From
this study (Table 1 and Figure 3) and our recent
studies with other wheat genotypes, it appears that Zn-
efficient genotypes do not necessarily have high grain
Zn concentration, thus breeding for Zn efficiency and
high grain Zn concentration needs to be considered
separately (Y Genc and GK McDonald, Unpublished).
It was interesting to note that some synthetic ac-
cessions had low Zn efficiency (e.g., high reduction in
shoot dry matter), yet did not show severe symptoms
and vice versa. From these results presented here and
those published elsewhere (Genc et al., 2002: Kalayci
et al., 1999), it appears that Zn efficiency based on
shoot growth and severity of foliar symptoms do not
always correlate, indicating that these two phenomena
may be affected by Zn deficiency to a different degree,
and perhaps controlled by different genes (Lonergan,
2001). It is clear that under Zn deficiency, reduction
in shoot growth is a result of inhibited synthesis or
enhanced degradation of indole acetic acid (Cakmak
et al., 1989), while chlorosis or necrosis of leaves are
associated with oxidative damage caused by free oxy-
gen radicals (Cakmak, 2000; Marschner and Cakmak,
1989). Although it is speculative, it is possible that
the effects of Zn deficiency on these processes may
vary with genotypes. In the present study, a signi-
ficant but not a very strong correlation was observed
between visual symptoms and Zn efficiency (d.f = 35,
r = 0.532, P<0.01). This has implications for eval-
uation protocols reliant on foliar symptoms only. If
this is the case, it would be almost impossible to differ-
entiate between those showing severe symptoms and
reduction in shoot growth, and those showing no foliar
symptoms and severe reduction in growth. Obviously,
in evaluating for Zn efficiency, genotypes showing
no reduction in shoot growth and no foliar symptoms
would be preferred. Thus, it is recommended that the
evaluation be carried out at least at two levels, defi-
cient and sufficient, by which both visual symptoms
and reduction in shoot growth are considered jointly
in the assessment of genotypes for Zn efficiency. How-
ever, further research is required to elucidate this phe-
nomenon of severe reduction in shoot growth despite
the lack of severe visual symptoms.
The synthetic accessions used in this study were
a random selection of a large collection held at In-
ternational Maize and Wheat Improvement Centre
(CIMMYT), Mexico. However, almost all the acces-
sions had Zn efficiency, either similar to or greater than
Zn-efficient modern genotypes and there were no ac-
cessions with lower Zn efficiency than Zn-inefficient
modern genotypes. This may be due to greater Zn
efficiency of either durum wheat or Aegilops tauschii
accessions used in the construction of these synthetic
hexaploid wheats. For example, synthetic accessions
26827 and 26828 had the same pedigree (Table 1),
and were similar in their Zn efficiencies (Figure 3)
and symptom expressions (Figure 1). When synthetic
accessions had one of their parents different, there
was a difference in either Zn efficiency or symptom
expression or both; 29677 and 29678 or 26818 and
29637 (Table 1, Figures 1 and 3). These results point
to genetic variation in either durum wheat or Aegilops
tauschii accessions. This conclusion is in accordance
with the results of Cakmak et al. (1999a) who sugges-
ted that not all Aegilops tauschii accessions may carry
Zn efficiency genes.
A significant but weak correlation (d.f. = 35, r =
0.382, P<0.05) between relative shoot Zn content
and relative shoot dry matter (Zn efficiency) indicates
that higher Zn content does not necessarily indicate
higher Zn efficiency. The proportion of total Zn con-
tent that is physiologically available but not the total

31
Zn content may be more important in terms of Zn
efficiency (Cakmak et al., 1997). Several other re-
searchers also reported that biochemical Zn utilisation
including the ability to maintain the activity of Zn re-
quiring enzymes under Zn deficiency may play a part
in Zn efficiency (Hacisalihoglu et al., 2003; Rengel,
1995). The correlation between Zn utilisation and Zn
efficiency at the plant level was significant, but not
strong (d.f. = 35, r = 0.375, P<0.05). This is
not surprising since Zn utilisation is a function of Zn
content which is based on Zn concentration estimated
by chemical analysis. Zn-efficient genotypes did not
always have a higher Zn utilisation than Zn-inefficient
genotypes (Table 2). For instance, despite similar Zn
utilisation, Opata showed greater Zn efficiency than
29661. These results suggest that Zn utilisation based
on chemical analysis may not always indicate Zn effi-
ciency, and there is a need to develop robust screening
methods to predict physiologically active Zn.
Fortuitously, of the parental genotypes of ITMI
mapping population tested in this study, Opata had
significantly higher Zn efficiency as well as shoot Zn
concentration and content under Zn deficiency com-
pared with synthetic accession 26818. These higher
values of Opata despite its lower seed Zn content
(Table 1) indicate that this population may be useful
for developing molecular markers associated with Zn
efficiency as well as improving our understanding of
inheritance of this trait. In addition, the variation in
grain Zn concentration and content in the parental gen-
otypes (Opata and synthetic accession 26818, Table 1)
and 30-selected lines from this population (G Lyons,
pers. commun.) points to the possibility of mapping
grain Zn concentration or content. Whether this pop-
ulation is suitable for mapping molecular markers
linked to Zn efficiency and/or grain Zn concentration
or content is yet to be demonstrated.
In conclusion, this relatively new germplasm, syn-
thetic hexaploids, offers potential for the improvement
of Zn efficiency in modern wheat genotypes. How-
ever, further evaluation is needed to see if high Zn
efficiency of synthetic accessions observed at the ve-
getative stage persists to maturity. If so, the higher
Zn efficiency of the synthetic hexaploids can be trans-
ferred into modern wheat genotypes of high yield and
quality or advance breeder’s lines by backcrossing.
Evaluation of more of these synthetics in the future, as
they become available, may identify accessions with
greater Zn efficiency than those in the present study.
However, the success rate of transfer of high efficiency
of synthetic hexaploids into modern wheat genotypes
relies on a good understanding of inheritance of this
trait (eg. number of genes and their heritability), which
remains to be elucidated.
Acknowledgements
The seeds of all the synthetic hexaploid accessions
used in this study were kindly provided by The Aus-
tralian Winter Cereals Collection at Tamworth, QLD,
Australia, courtesy of Dr Hugh Wallwork (South Aus-
tralian Research and Development Institute). We wish
to thank Mrs Teresa Fowles and Mr Lyndon Palmer for
technical assistance with ICP analysis. We also would
like to thank Ms Michelle Lorimer (The University of
Adelaide, Australia) for advice on statistical analysis.
This work was supported by Molecular Plant Breeding
CRC, Australia.
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