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Euphytica (2008) 163:381–390
DOI 10.1007/s10681-008-9681-x
123
Relationship between yield and mineral nutrient
concentrations in historical and modern spring
wheat cultivars
Kevin M. Murphy · Philip G. Reeves ·
Stephen S. Jones
Received: 5 September 2007 / Accepted: 14 March 2008 / Published online: 3 April 2008
© Springer Science+Business Media B.V. 2008
Abstract The diet of approximately three billion
people worldwide is nutrient deWcient and most of the
world’s poorest people are dependent on staple food
crops as their primary source of micronutrients. One
component of the solution to nutrient deWciencies is
collaboration among plant breeders, cereal chemists
and nutritionists to produce staple crop cultivars with
increased mineral nutrient concentration. Sixty-three
historical and modern wheat cultivars were evaluated
for grain yield and concentration of calcium, copper,
iron, magnesium, manganese, phosphorus, selenium,
and zinc. While grain yield has increased over time,
the concentrations of all minerals except calcium
have decreased. Thus a greater consumption of whole
wheat bread from modern cultivars is required to
achieve the same percentage of recommended dietary
allowance levels contributed by most of the older cul-
tivars. The decrease in mineral concentration over the
past 120 years occurs primarily in the soft white
wheat market class, whereas in the hard red market
class it has remained largely constant over time. This
suggests that plant breeders, through intentional
selection of low ash content in soft white wheat culti-
vars, have contributed to the decreased mineral nutri-
ent concentration in modern wheat cultivars. These
results contradict the theory that there exists a geneti-
cally based, biological trade-oV between yield and
mineral concentrations. Therefore, using the abundant
variation present in wheat cultivars, it should be pos-
sible to improve mineral concentrations in modern
cultivars without negatively aVecting yield.
Keywords Micronutrients · Plant breeding ·
Recommended dietary allowance · Wheat · Landraces ·
Yield
Introduction
Over 40% of the world’s population is currently
micronutrient deWcient (a condition referred to as
‘Hidden Hunger’), resulting in numerous health prob-
lems, inXated economic costs borne by society, and
learning disabilities for children (Branca and Ferrari
2002; Grantham-McGregor and Ani 1999; Ramakrish-
nan et al. 1999; Sanchez and Swaminathan 2005). The
dietary intake of iron (Fe) of more than two billion
people worldwide is inadequate (Stoltzfus 2001), mak-
ing Fe-deWciency the most common micronutrient
deWciency in the world (Graham et al. 2001). Almost
two-thirds of all childhood deaths are associated with
nutritional deWciencies (Caballero 2002). Although a
diversiWcation of diet to include micronutrient-rich
K. M. Murphy · S. S. Jones (&)
Department of Crop and Soil Sciences,
Washington State University, 387 Johnson Hall,
Pullman, WA 99164-6420, USA
e-mail: joness@wsu.edu
P. G. Reeves
USDA-ARS, Grand Forks Human Nutrition Research
Centre, 2420 Second Avenue, North Grand Forks,
ND 5820, USA
382 Euphytica (2008) 163:381–390
123
traditional foods is the preferred solution to these chal-
lenges (Frison et al. 2006), many of the world’s
poorest people do not have access to a wide variety of
nutritionally dense food crops (Graham et al. 2001).
The large increases in the percentage of people
suVering from micronutrient malnutrition over the
last four decades coincide with the global expansion
of high-yielding, input-responsive cereal cultivars
(Welch 2002; Welch and Graham 2002). While glo-
bal cereal grain yields have increased dramatically
since the Green Revolution (Abeledo et al. 2003;
Borlaug 1983; Slafer and Peltonen-Sainio 2001), glo-
bal food systems are not providing suYcient micronu-
trients, resulting in an increased prevalence of
micronutrient deWciencies (Welch 2002).
For much of the world’s population without access
to diverse food crops, staple cereal grains are the pri-
mary dietary sources of micronutrients (Graham et al.
2001). Cereal crops could provide a signiWcant increase
in the overall micronutrient availability in human popu-
lations whose diets are dominated by staple crop con-
sumption. For example, nutritional screening of staple
food crops has suggested that micronutrient content of
cereals could be twice the level found in commonly
grown cultivars (Welch and Graham 1999). Bouis
(2003) estimated that a doubling of Fe density in a sta-
ple crop would result in a 50% increase in total Fe
intake for a population relying heavily on a single food
(e.g., rice in Bangladesh). Most micronutrients account
for less than 0.1% of the dry weight of a food, which
indicates that signiWcant increases in micronutrient lev-
els are theoretically possible (DellaPenna 1999).
The objectives of this study were to compare the
concentrations of eight minerals, including calcium
(Ca), copper (Cu), iron (Fe), magnesium (Mg), man-
ganese (Mn), phosphorus (P), selenium (Se), and zinc
(Zn) in historical and modern spring wheat cultivars,
and to explore the possibility of any biological trade-
oVs between mineral concentration and yield. Finally
we sought to estimate the dietary signiWcance of culti-
var diVerences in mineral concentration.
Materials and methods
Experimental design
A randomized complete block design nursery con-
taining 63 spring wheat cultivars (56 historical, 7
modern) was grown in Pullman, Washington, in 2004
and 2005. The historical cultivars were selected ran-
domly from a larger group of spring wheat cultivars
that were widely grown in the PaciWc Northwest
region of the USA from 1842 to 1965. The seven
modern cultivars were among the most widely grown
spring wheat cultivars in Washington State in 2003,
representing approximately 69% of the total spring
wheat area in the state (USDA 2005). Thirty-seven
cultivars were in the soft white market class, 20 were
in the hard red market class, four were in the hard
white market class and two cultivars were in the soft
red market class. There were three replicates of each
cultivar in 2004 and four replicates of each in 2005.
The soil and climatic conditions found in Pullman
are generally representative of the approximately
1.3 million hectare wheat-based farming region
known as the Palouse, located in the higher rainfall
zones (»500 mm/year) of Eastern Washington and
Northern Idaho. The nurseries were grown at the
same location in both years on a Palouse silt loam
soil. The nurseries were fertilized with PerfectBlend®
fertilizer at the rate of 6.05 kg/ha each of N, P, and K,
drilled with the seed at planting. No fungicidal or
insecticidal seed treatments were used. This manage-
ment practice was intended to reXect low-input wheat
production in the PaciWc Northwest. Plots consisted
of seven rows at 18 cm spacing, 2.5 m long and
1.25 m wide. Plots were harvested with a Hege plot
combine with stainless steel sieves and cleaned with a
Hege seed cleaner with stainless steel sieves. The
Weld replicates were bulked according to cultivar each
year and then sent to the Grand Forks Human Nutri-
tion Research Centre for mineral analysis.
Mineral analysis
The experimental design for the mineral analysis
was a randomized complete block with three repli-
cates per sample. Wheat samples were individually
ground to a powder (15 s) in a coVee grinder (Krups,
Model 208) with a stainless steel chamber and blade.
The chamber and blade were thoroughly cleaned
between samples to prevent cross contamination.
For the analysis of Ca, Cu, Fe, Mg, Mn, P, and Zn,
»0.4 g of each wheat sample was weighed and
placed in triplicate into separate Pyrex beakers.
Watchglasses were placed on the beakers and the
samples were ashed in a muZe furnace at 200°C for
Euphytica (2008) 163:381–390 383
123
2 h and at 490°C for 12 h. The ash was dissolved in
10 ml of concentrated nitric acid (11.03 mol/l) (J.T.
Baker Instra-Analyzed) and heated on a hotplate at
120°C for 2 h. Two milliliters of 30% hydrogen per-
oxide (J.T. Baker) were slowly added to each beaker
and the mixture reXuxed for 12 h. Samples were
allowed to dry, and ashed again in a muZe furnace
following the procedure outlined above. The result-
ing white ash was dissolved in 2 ml of 6 N HCl
(1.2 mol/l) (J.T. Baker Instra-Analyzed) with heat-
ing and subsequently diluted to 10 ml with deion-
ized water. Samples were analyzed simultaneously
for Ca, Cu, Fe, Mg, Mn, P, and Zn by Inductively
Coupled Argon Plasma (ICAP) techniques by using
a Perkin Elmer 3300 instrument. Four NIST
(National Institute of Standards and Technology,
Gaithersburg, MD, USA) durum wheat standards
and four acid blanks were run with each batch of
samples.
For the analysis of Se, approximately 2.0 g of
sample were placed into 100 ml Pyrex beakers
and mixed with 10 ml concentrated nitric acid
(11.03 mol/l), 5 ml of 40% magnesium nitrate solu-
tion, and 2 ml of concentrated HCl (4.8 mol/l). The
beakers were covered with watch glasses for 24 h.
The samples were then heated at »80°C for 24 h.
The covers were removed and the samples were
allowed to dry. They were then placed in a muZe
furnace and held at 490°C for 7 h. After the samples
cooled, 5 ml of deionized water and 5 ml of concen-
trated nitric (11.03 mol/l) were added and heated for
2h at »80°C on a hotplate. The covers were then
removed and the samples were allowed to air dry.
The samples were returned to the furnace and held at
490°C for 4 h. Four milliliters concentrated HCl
(4.8 mol/l) were added to the cooled samples and
they were heated until the ash was dissolved. The ash
was diluted to a Wnal volume of 10 ml and analyzed
by atomic absorption spectrometry using hydride
generation. Three NIST durum wheat standards and
three acid blanks were run with each batch of
samples.
Statistical analysis
Data were analyzed using analysis of variance soft-
ware PROC GLM (SAS Institute, Cary, NC).
Levene’s test was used to test for homogeneity of var-
iance across locations and normality was checked
using the Shapiro-Wilk test in PROC Univariate
(SAS Institute). Pearson’s correlation coeYcients
were calculated based on mean trait values and used
to estimate phenotypic relationships between traits of
interest. SigniWcance was assessed at the 5% proba-
bility level, unless otherwise stated.
Bioavailability, Recommended Dietary Allowance
(RDA) and Adequate Intake (AI) estimates
Bioavailability/absorption estimates were obtained
with wheat as the target crop, for each mineral, using
multiple sources (Table 1). RDA and AI levels were
adapted from Dietary Reference Intake (DRI) reports
from the National Academies Press (Table 2).
Reports included the DRI for Calcium, Phosphorous,
Magnesium, Vitamin D, and Fluoride (1997); DRI for
Vitamin C, Vitamin E, Selenium, and Carotenoids
(2000); and DRI for Vitamin A, Vitamin K, Arsenic,
Boron, Chromium, Copper, Iodine, Iron, Manganese,
Molybdenum, Nickel, Silicon, Vanadium, and Zinc
(2001).
Results
Mineral concentrations and yield
Highly signiWcant diVerences among the 63 wheat
cultivars were found for yield and for mineral concen-
trations of all eight nutrients (P< 0.0001). Modern
cultivars had higher yields than historical cultivars
(P< 0.0001). Mean yield for historical cultivars was
1.090 §79 kg/ha and that for modern cultivars was
1.915 §242 kg/ha. For seven of the eight nutrients,
Table 1 Percent bioavailability/absorption estimates obtained
using wheat as the target crop for each mineral
Mineral Bioavailability Source
Ca 78 Levrat-Verney et al. (1999)
Cu 23 Egli et al. (2004)
Fe 13 Hallberg and Hulthen (2000)
Mg 70 Levrat-Verney et al. (1999)
Mn 2.2 Johnson et al. (1991)
P 50 Weremko et al. (1997)
Se 81 Fox et al. (2005)
Zn 35 Levrat-Verney et al. (1999)
384 Euphytica (2008) 163:381–390
123
the historical cultivars had signiWcantly higher grain
mineral concentrations than the modern cultivars
(Table 3). Only Ca showed no signiWcant diVerence
between the historical and modern eras (P=0.07).
Highly signiWcant variation existed among wheat cul-
tivars for concentration of each mineral, indicating
the potential for genetic improvement (Fig. 1,
Table 4). A signiWcant genotype £year interaction
was found for each mineral. These interactions were
scalar in nature and did not represent signiWcant
changes in cultivar ranks between years. Addition-
ally, the values for the sums of squares for years were
very small compared to those for genotype, indicating
that most variation was due to genotype rather than
year.
Yield—mineral concentration trade-oV
For Ca, Cu, Mg, Mn, P and Se, yield was negatively
correlated with mineral concentration (Table 3). Fe
and Zn showed no signiWcant correlation with yield
(Table 3). A trade-oV between yield and Ca, Cu, Mg,
Mn, P, and Se concentrations is indicated; however,
this trade-oV could either be genetically based or the
result of inadvertent negative selection pressure on
mineral concentration by wheat breeders.
Thousand kernel weight (TKW) was positively
correlated with grain yield (r=0.60, P<0.001), and
concentrations of Cu, Mn, Se and Zn (Table 5). There
was no correlation between TKW and concentrations
of Ca or Fe, and a negative correlation existed
(P= 0.028) between TKW and the concentrations of
Mg and P. The mean TKW of the modern wheat culti-
vars was 34.6 g, whereas the historical cultivars had a
lower mean TKW of 30.0 g (P=0.004).
Regressions of mineral concentrations on year of
release were separated according to either hard red or
soft white market classes (Fig. 1). SigniWcant decreases
were shown among soft white cultivars for all minerals
except Ca and Mg. Among hard red cultivars, only Zn
decreased over time, whereas Mg increased over time
(Fig. 1). All other mineral nutrients remained stable
among HR cultivars over the past 120 years.
Ca concentration was positively correlated with
that of all the other minerals (r= 0.19–0.59, Table 5),
indicating that selection for increased grain concen-
tration of Ca may increase grain contents of other
minerals if the correlations are genetically based.
Eight cultivars (Lemhi, Lemhi 66, Mackey, Idaed 59,
Little Club, Big Club, New Zealand and Hybrid 143)
were ranked among the top 12 (top 20%) for concen-
tration of four or more minerals and four of these
Table 2 Recommended
Daily Allowance (RDA) or
Adequate Intake (AI) levels
of Ca, Cu, Fe, Mg, Mn,
P, Se, and Zn
Gender/Age Ca Cu Fe Mg Mn P Se Zn
AI RDA RDA RDA AI RDA RDA RDA
Children 4–8 500 0.34 7 80 1.2 460 20 3
Males 19–30 1,000 0.9 8 400 2.3 700 55 11
Females 19–30 1,000 0.9 18 320 1.8 700 55 8
Males 31–50 1,000 0.9 8 420 2.3 700 55 11
Females 50–70 1,200 0.9 8 320 1.8 700 55 8
Estimates are recorded as
mg/day for all minerals
except Se (g/day)
Table 3 Mineral concen-
tration in historical and
modern wheat cultivars
Mineral Mineral concentration Grain yield/Mineral
correlation
Historical (1842–1965) Modern (2003) % Change
Ca 421.6 §10.9 398.5 §16.1 ¡6¡0.41***
Cu 4.8 §0.1 4.1 §0.2 ¡16*** ¡0.17***
Fe 35.7 §1.0 32.3 §1.8 ¡11** 0.05
Mg 1402.6 §21.0 1307.6 §25.6 ¡7*** ¡0.35***
Mn 50.0 §1.2 46.8 §3.1 ¡7* ¡0.17**
P 3797.1 §55.7 3492.7 §119.3 ¡9*** ¡0.25***
Se 16.2 §1.7 10.8 §2.7 ¡50* ¡0.38***
Zn 33.9 §0.9 27.2 §1.9 ¡25*** ¡0.06
Mineral concentrations are
given in mg/kg dry
weight §standard error for
all minerals except Se,
which is given in g/kg. *,
**, *** P< 0.05, 0.01 and
0.001, respectively
Euphytica (2008) 163:381–390 385
123
cultivars (Lemhi, Lemhi 66, Mackey and Idaed 59)
were ranked among the top 12 for concentration of six
or more minerals (Table 4). Correlations were espe-
cially strong (r¸0.90) between the concentrations of
Cu and Mn, Cu and Zn, and Zn and Mn.
Discussion
Using historical and modern data, overall decreases in
mineral content of vegetables and horticultural crops
were reported over a 50-year period (Davis et al.
2004; White and Broadley 2005), and a trade-oV the-
ory was proposed for the interaction between yield
and mineral content (Davis et al. 2004). However,
diVerences in cultivars, environments, sampling and
laboratory analytical methods could be responsible
for the reported reduction in mineral content in any
one crop (Davis et al. 2004).
The dilution eVect, due to bran versus endosperm
ratio change, may play a role in the negative relation-
ship between yield and mineral content for cereal
crops. Previous studies showed negative associations
between grain yield and grain nitrogen concentration
(Cox et al. 1985; Heitholt et al. 1990; Pepe and
Heiner 1975), indicating that the dilution of nitrogen
compounds in high-yielding grains was a conse-
quence of the breeding process during this century
Fi
g.
1
Regress
i
ons o
f
wheat seed mineral nutrient
content on the date of vari-
ety release for soft white
(SW) spring wheat (open tri-
angle, light solid line) and
hard red (HR) spring wheat
(closed diamond, dark solid
line). Regression lines are
best-Wt simple linear regres-
sion model
SW = y = -0.06x + 158
HR = y = -0.03x + 83
20
25
30
35
40
45
1880 1900 1920 1940 1960 1980 2000 2020
Date of Variety Release
Seed Zn
SW = y = -0.08x + 165
HR = y = -0.004x + 22
5
10
15
20
25
30
35
Seed Se
SW = y = -3.9x + 11240
HR = y = -0.53x + 4692
3000
3250
3500
3750
4000
4250
4500
Seed P
SW = y = -0.02x + 82
HR = y = 0.02x + 5
35
40
45
50
55
60
65
Seed Mg
SW = y = -0.89x + 3158
HR = y = 0.85x - 336
1100
1150
1200
1250
1300
1350
1400
1450
1500
1550
1600
1880 1900 1920 1940 1960 1980 2000 2020
Date of Variety Release
Seed Mg
SW = y = -0.04x + 105
HR = y = 0.02x + 1
25.0
30.0
35.0
40.0
45.0
50.0
55.0
Seed Fe
SW = y = -0.008x + 20
HR = y = 0.004x - 3
3
3.5
4
4.5
5
5.5
6
Seed Cu
SW = y = -0.37x + 1139
HR = y = -0.14x + 652
250
300
350
400
450
500
550
600
Seed Ca
386 Euphytica (2008) 163:381–390
123
Table 4 Variety name, market class (MC), year of release or introduction to the PaciWc Northwest (year), grain yield (kg/ha), Ca, Cu,
Fe, Mg, Mn, P, Se and Zn concentrations, for each spring wheat cultivar used in the study
Variety MC Year Grain yield Ca Cu Fe Mg Mn P Se Zn
Wawawai SW 1994 2,212 339 4.2 30.6 1,328 47 3,584 2 29
Spinkota HR 1944 2,033 288 3.4 40.5 1,277 45 3,437 21 29
Canus HR 1934 1,934 471 4.3 36.5 1,358 51 3,804 15 34
Zak SW 2000 1,928 395 3.9 36.1 1,257 52 3,356 16 27
Wakanz SW 1987 1,802 428 4.1 31.6 1,286 46 3,445 2 26
Alpowa SW 1994 1,779 372 3.8 31 1,300 39 3,391 11 24
Westbred express HR 1991 1,732 414 4.9 33.8 1,336 51 3,545 13 27
White Marquis HW 1923 1,678 441 4.3 30.9 1,314 49 4,052 19 33
Cadet HR 1946 1,648 341 5.1 34.1 1,531 55 4,026 15 37
Ruby HR 1917 1,637 338 3.8 33.5 1,161 39 3,243 14 29
Scarlet HR 1999 1,619 387 4 34 1,295 46 3,527 12 28
Canadian Red HW 1919 1,615 371 4.2 36.4 1,280 50 3,421 13 33
Beaver SW 1965 1,555 361 3.7 29.6 1,349 47 3,549 20 30
Hope HR 1927 1,516 349 4.3 32.7 1,351 51 3,588 11 34
Hyper SW 1929 1,491 474 5.5 35.7 1,428 53 3,897 12 32
Idaed SW 1938 1,489 345 4.4 34.7 1,238 52 3,516 11 30
Sonora SW 1842 1,473 442 4.6 36.9 1,394 49 3,884 15 31
Reliance HR 1926 1,472 387 3.6 31.4 1,177 39 3,315 14 26
Idaed 59 SW 1962 1,452 479 5.5 52.2 1,723 57 4,738 15 36
Galgalos SW 1903 1,449 339 4.2 36.7 1,351 47 3,681 19 33
Allen SW 1900 1,448 374 4.9 42 1,582 52 4,323 20 37
Thatcher HR 1934 1,440 396 4.4 27.1 1,301 47 3,789 12 28
Ladoga HR 1888 1,401 385 4.4 38.4 1,368 49 3,935 15 35
Red Bobs HR 1918 1,387 298 3.5 31.4 1,145 43 3,206 13 30
Flomar HW 1933 1,360 414 3.9 34.6 1,355 49 3,613 14 32
Rink SW 1909 1,357 398 5.2 33 1,371 43 3,688 17 26
Currawa SW 1916 1,332 313 3.8 32.3 1,168 40 3,092 17 23
Comet HR 1940 1,288 413 4.3 36.1 1,366 54 3,738 13 35
Penawawa SW 1985 1,282 454 3.8 29.1 1,348 46 3,601 4 28
Indian SW 1917 1,266 370 5.2 42.8 1,536 56 4,236 15 34
Hard Federation HW 1915 1,214 358 4.9 35.8 1,462 56 3,725 12 36
Reward HR 1917 1,207 371 4.7 35.8 1,271 52 3,895 13 36
Supreme HR 1922 1,200 346 3.8 33.8 1,275 49 3,593 9 34
Marquis HR 1911 1,199 380 3.9 28.7 1,271 44 3,748 10 33
Komar HR 1930 1,106 471 4.4 30.3 1,386 48 3,806 14 35
Henry HR 1944 1,106 366 4.7 31.9 1,353 44 3,840 12 36
Sea Island HR 1890 1,096 490 4.2 29.7 1,237 47 3,532 16 28
Oregon Zimmerman SW 1921 1,071 365 5.5 32.5 1,446 47 3,995 12 39
Federation 67 SW 1967 1,057 440 4.6 33.2 1,394 51 3,351 16 32
Onas SW 1918 1,043 392 5 33.7 1,372 55 3,625 5 32
Ceres HR 1926 1,033 453 5.1 28.8 1,430 60 3,989 20 33
Mackey SW 1906 1,029 483 5.8 45.6 1,468 50 4,125 30 39
Rival HR 1939 1,007 401 5.3 32.4 1,426 51 3,868 19 38
Euphytica (2008) 163:381–390 387
123
(Calderini et al. 1995). Genetic gains in grain yield of
US hard red winter wheat cultivars may be related to
reduced Fe, Zn, and Se concentrations (Garvin et al.
2006). Other studies, however, indicated that micro-
nutrient-rich cultivars can also be higher yielding than
less micronutrient-rich cultivars, especially when
grown on soils with low micronutrient availability
(Graham et al. 2001; Rengel 2001).
While yield and mineral concentration were usually
negatively associated, the correlations were weak and
exceptions existed for high yielding cultivars with
moderately high levels of certain minerals. Of the top
12 yielding cultivars, two were in the top 12 for P con-
centration, one was in the top 12 for each of Fe, Mg,
Mn, and Se, and none was in the top 12 for Ca, Cu or
Zn (Table 3). Of the lowest yielding 12 cultivars, how-
ever, six were among the top 12 in Ca, Cu, and P con-
centration, Wve were in the top 12 for Mg and Zn, three
for Fe and Se, and two for Mn. Though most of the
highest-ranking cultivars for mineral concentration
Table 4 continued
Mineral concentration results are in mg/kg, except for Se (g /kg). Cultivars in bold were designated as ‘modern’; other cultivars were
designated ‘historical’. SW, Soft White; SR, Soft Red; HR, Hard Red; HW, Hard White
Variety MC Year Grain yield Ca Cu Fe Mg Mn P Se Zn
Lemhi 66 SW 1966 980 531 6.4 43.6 1,572 55 3,800 23 41
Baart 46 SW 1948 971 375 4.8 37.5 1,489 47 3,943 22 32
White Federation SW 1916 944 454 4.2 33.9 1,408 53 3,431 10 33
Awned Onas SW 1950 860 458 4.3 31.1 1,415 50 3,383 25 31
Federation SW 1914 842 512 5 35 1,574 58 3,685 15 37
Bunyip SW 1914 826 422 4.9 40.7 1,524 62 3,895 19 35
Dicklow SW 1912 819 506 5.2 32.5 1,384 48 3,628 23 38
Gypsum SW 1912 762 429 5.2 39.2 1,386 48 3,864 22 37
Big Club SW 1870 759 494 4.3 37.9 1,518 52 4,306 25 37
New Zealand SW 1890 726 387 5.7 43.6 1,457 49 4,184 11 39
Lemhi SW 1939 618 560 7.2 40 1,627 55 4,039 14 43
Surprise SW 1870 578 478 5.6 33.1 1,302 45 3,490 19 32
PaciWc Bluestem SW 1882 569 440 5.2 36.3 1,488 52 3,958 16 39
Hybrid 143 SW 1907 542 519 4.7 35.8 1,547 58 4,107 18 32
BluechaV Club SW 1894 533 488 5.7 35.5 1,552 48 4,329 17 40
Little Club SW 1842 449 568 5.3 50.4 1,550 51 3,883 15 35
Hybrid 123 SR 1907 406 515 4.5 34.9 1,279 47 3,780 19 31
Red Fife SR 1842 352 398 4.5 35.5 1,435 50 4,041 11 34
Hybrid 63 SW 1907 338 467 5 31.9 1,456 42 3,684 20 33
Pilcraw SW 1917 331 433 5.4 34.9 1,436 47 3,709 20 34
LSD (P= 0.05) 127 29 0.5 4.5 86 3 217 2 2
Table 5 Correlations
between minerals in spring
wheat cultivars grown in
Pullman, WA in 2004 and
2005 using Pearson
correlation coeYcients
Mineral Ca Cu Fe Mg Mn P Se Zn
Cu 0.54*** –
Fe 0.26*** ¡0.07 –
Mg 0.59*** ¡0.03 0.53*** –
Mn 0.34*** 0.90*** ¡0.23*** ¡0.07 –
P 0.47*** ¡0.18*** 0.49*** 0.84*** ¡0.19*** –
Se 0.19*** 0.19*** ¡0.31*** 0.13 0.36*** 0.08 –
Zn 0.41*** 0.94*** ¡0.23*** ¡0.26*** 0.93*** ¡0.36*** 0.16** –
TKW ¡0.16 0.23* ¡0.04 ¡0.20* 0.28** ¡0.20* 0.29** 0.27**
TKW = 1,000 kernel
weight. * P<0.05;
** P< 0.01; *** P<0.001
388 Euphytica (2008) 163:381–390
123
were relatively low yielding, several high yielding cul-
tivars contained high concentrations of certain miner-
als, indicating the possibility that simultaneous genetic
gains could be made for both yield and mineral
concentration (Table 4). For example, high yielding
cultivars Spinkota, Zak and White Marquis had high
concentrations of Fe, Mn and Mg, respectively.
Eight cultivars were ranked among the top 12 for
concentrations of four or more minerals and four were
ranked among the top 12 for six or more minerals
(Table 4). This suggests that it is possible to select
cultivars with enhanced levels of multiple nutrients.
Correlations were especially strong (r¸0.90) for Cu
and Mn, Cu and Zn, and Zn and Mn, indicating that
selection for cultivars with high concentrations of Cu,
Zn, and Mn would be particularly eVective.
Fe and Zn are the two most important mineral nutri-
ents contributing to micronutrient deWciency (Welch
and Graham 1999). Fe and Zn were the only minerals
studied whose contents were not negatively correlated
with yield (Table 3), indicating that in the presence of
positive selection pressure, Fe and Zn would be the
minerals most likely to increase simultaneously with
yield. This corresponds with recent Wndings by Uauy
et al. (2006) that show both Fe and Zn content are
inXuenced by the high protein gene Gpc-B1.
Mineral concentration was regressed on the date of
variety release for both the soft white and hard red
spring wheat market class groups. Over a 120-year
time span, hard red cultivars had a neutral or slightly
positive trend for each mineral, except Zn, which
showed a slightly negative trend and Mg, which
showed a slightly positive trend (Fig. 1). The soft
white wheat group, however, had either a nutritional
decline or, in the cases of Ca and Mg, a neutral trend
for mineral concentration over time. This indicates
that plant breeders may be responsible for the decline
in nutritional concentration in soft white wheat culti-
vars, where selection often occurs for low ash con-
tent. High ash content has deleterious eVects on the
end-use quality of products made from soft white
wheat. Ash contains minerals and ash in Xour can
aVect color, giving a darker color to Wnished products.
Products that require white Xour need low ash content
whereas other products, such as whole wheat Xour,
have higher ash contents. For hard red wheats grown
in the PaciWc Northwest region, where ash content is
not strongly selected against, mineral content does not
show a negative trend.
Dietary signiWcance of mineral nutrient decline
How do these results translate into current levels of the
Recommended Dietary Allowance (RDA) and/or Ade-
quate Intake (AI)? To understand the dietary conse-
quences of the decrease in mineral concentration in
modern wheat cultivars, the numbers of slices of whole
wheat bread necessary to achieve either the RDA or AI
levels were estimated for Wve age/gender groups: (1)
children aged 4 to 8; (2) males aged 19 to 30; (3)
females aged 19 to 30; (4) males aged 31 to 50 and; (5)
females aged 50 to 70. These age/gender groups are
sample demographics representative, but not inclusive,
of the human population. A whole wheat loaf of bread
was estimated at 1,000 g, with 20 slices per loaf, there-
fore each slice was estimated to weigh 50 g. Although
bread is typically made with hard red wheat, all market
classes of wheat were included in this estimate, because
breeders will likely use genes for high mineral content
from any market class and introgress these genes into
locally adapted, high yielding hard red cultivars. In
addition, whole wheat bread is simply used as an exam-
ple that can be extended to other end-use products,
including steamed bread, cookies, sponge cakes, and
pasta, all of which are usually made from white wheat.
RDA’s are set to meet the needs of 97–98% of indi-
viduals in a group. AI is believed to cover the needs of
all individuals in a group, but lack of suYcient data pre-
vents the ability to specify with conWdence the percent-
age of individuals covered by this intake. RDA and AI
estimates are shown in Table 2. The estimates of dietary
signiWcance herein are based on the assumption that all
cultivars have the same level of bioavailability.
Although the increased yield of modern cultivars
could potentially increase the mineral content per acre
of grain production, the mineral concentration per
seed or loaf of bread is reduced. This reduction in per
loaf mineral concentration results in a necessary
increase in consumption of bread made from modern
wheat cultivars to reach the same level of mineral con-
tent in bread made from historical wheat cultivars
with high mineral nutrient content. In addition to his-
torical cultivars high in mineral concentration, many
historical cultivars have low levels of certain minerals.
The seven modern cultivars were compared with
seven historical cultivars chosen because they con-
tained high levels of each mineral. Figures 2 and 3
show that for all eight minerals more bread is required
to meet the RDA or AI in modern cultivars than in the
Euphytica (2008) 163:381–390 389
123
nutritionally dense historical cultivars for each age/
gender group. For example, females aged 19 to 30
would have to eat 10.6 slices of whole wheat bread
made with Xour from historical cultivars high in Zn to
reach the RDA, but would require 15.2 slices of bread
made with Xour from modern cultivars to achieve the
same RDA (Fig. 2). Males aged 31 to 50 would need
13 slices of bread made from historical cultivars high
in Cu and 19.1 slices of bread made from modern cul-
tivars to reach the RDA (Fig. 2).
It is unreasonable to expect acquisition of a signiW-
cant percentage of the RDA of certain minerals from
eating whole wheat bread (Fig. 3). For example, to
reach the RDA of Se would require consumption of
55 slices of bread made from cultivars high in Se and
123.5 slices of bread made from modern cultivars for
males and females aged 19 to 30 (Fig. 3). Addition-
ally, to reach the RDA of Ca would require consump-
tion of 39 slices of bread made from historical
cultivars high in Ca and 51 slices of bread made from
modern cultivars for children aged 4 to 8 (Fig. 3).
Greater potential dietary impact may be realized from
increased consumption of bread made with cultivars
containing high levels of Zn, Cu, Mg and P (Fig. 2).
For example, children aged 4 to 8 would need only
seven slices of bread made from cultivars high in Zn
and six slices of bread made from cultivars high in Cu
to achieve the RDA for these minerals (Fig. 2). These
estimates should be regarded with caution, because
they are dependent on bioavailability estimates
among cultivars, which were untested in this study.
Here we report signiWcant statistical and dietary
diVerences between modern and historical cultivars of
wheat and show the need to reverse this trend. Increases
in consumption of mineral nutrients can be accom-
plished partially through plant breeding, but requires
other approaches as well. Additional approaches
emphasize the necessity of improving dietary food
diversity, linking agricultural biodiversity to nutrition,
and the mobilization of indigenous and traditional food
systems in a multi-faceted approach to reducing world-
wide nutritional deWciencies (Frison et al. 2006).
Acknowledgements We thank Dr. Margaret Smith, Dr. Pres-
ton Andrews, Dr. Salvatore Ceccarelli, Dr. Byung-kee Baik,
Dr. Lu Ann Johnson, Dr. Gary Hareland, Dr. John Reganold,
Dr. Kim Campbell, Dr. Tim Murray, David Granatstein, Julie
Dawson and two anonymous reviewers for comments on the
manuscript. Unparalleled technical assistance was provided by
Steve Lyon, Meg Gollnick and Kerry Balow. This work was
funded by Washington State University’s Centre of Sustaining
Agriculture and Natural Resources, The Land Institute, the
Organic Farming Research Foundation, the United States
Department of Agriculture’s Integrated Organic Program (Grant
Number: 2006–02057) and Washington Wheat Growers. The
authors declare no competing Wnancial interests.
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Fig. 2 Estimated numbers of slices of bread required to meet
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0
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Top 7
Modern
Top 7
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Top 7
Modern
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Top 7
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