Provitamin A Carotenoids in Grain Reduce Aflatoxin Contamination of Maize While Combating Vitamin A Deficiency

Abstract

Aflatoxin contamination of maize grain and products causes serious health problems for consumers worldwide, and especially in low- and middle-income countries where monitoring and safety standards are inconsistently implemented. Vitamin A deficiency (VAD) also compromises the health of millions of maize consumers in several regions of the world including large parts of sub-Saharan Africa. We investigated whether provitamin A (proVA) enriched maize can simultaneously contribute to alleviate both of these health concerns. We studied aflatoxin accumulation in grain of 120 maize hybrids formed by crossing 3 Aspergillus flavus resistant and three susceptible lines with 20 orange maize lines with low to high carotenoids concentrations. The hybrids were grown in replicated, artificially-inoculated field trials at five environments. Grain of hybrids with larger concentrations of beta-carotene (BC), beta-cryptoxanthin (BCX) and total proVA had significantly less aflatoxin contamination than hybrids with lower carotenoids concentrations. Aflatoxin contamination had negative genetic correlation with BCX (-0.28, p < 0.01), BC (-0.18, p < 0.05), and proVA (-0.23, p < 0.05). The relative ease of breeding for increased proVA carotenoid concentrations as compared to breeding for aflatoxin resistance in maize suggests using the former as a component of strategies to combat aflatoxin contamination problems for maize. Our findings indicate that proVA enriched maize can be particularly beneficial where the health burdens of exposure to aflatoxin and prevalence of VAD converge with high rates of maize consumption.

Full text

fpls-10-00030 January 25, 2019 Time: 17:49 # 1
ORIGINAL RESEARCH
published: 29 January 2019
doi: 10.3389/fpls.2019.00030
Edited by:
Rosa Ana Malvar,
Misión Biológica de Galicia (MBG),
Spain
Reviewed by:
Ana Butron,
Spanish National Research Council
(CSIC), Spain
Jose Ignacio Ruiz De Galarreta,
Neiker-Tecnalia, Spain
*Correspondence:
Kevin V. Pixley
k.pixley@cgiar.org
†Present address:
Willy B. Suwarno,
Department of Agronomy and
Horticulture, Faculty of Agriculture,
Bogor Agricultural University,
Bogor, Indonesia
Pattama Hannok,
Program of Agronomy, Maejo
University, Chiangmai, Thailand
Kevin V. Pixley,
International Maize and Wheat
Improvement Center,
Texcoco, Mexico
Specialty section:
This article was submitted to
Plant Breeding,
a section of the journal
Frontiers in Plant Science
Received: 04 November 2018
Accepted: 09 January 2019
Published: 29 January 2019
Citation:
Suwarno WB, Hannok P,
Palacios-Rojas N, Windham G,
Crossa J and Pixley KV (2019)
Provitamin A Carotenoids in Grain
Reduce Aflatoxin Contamination
of Maize While Combating Vitamin
A Deficiency. Front. Plant Sci. 10:30.
doi: 10.3389/fpls.2019.00030
Provitamin A Carotenoids in Grain
Reduce Aflatoxin Contamination of
Maize While Combating Vitamin A
Deficiency
Willy B. Suwarno1†, Pattama Hannok1,2†, Natalia Palacios-Rojas1, Gary Windham3,
José Crossa1and Kevin V. Pixley1,2*†
1International Maize and Wheat Improvement Center, Texcoco, Mexico, 2Department of Agronomy, University of
Wisconsin-Madison, Madison, WI, United States, 3Corn Host Plant Resistance Research Unit, United States Department
of Agriculture-Agricultural Research Service, Starkville, MS, United States
Aflatoxin contamination of maize grain and products causes serious health problems
for consumers worldwide, and especially in low- and middle-income countries where
monitoring and safety standards are inconsistently implemented. Vitamin A deficiency
(VAD) also compromises the health of millions of maize consumers in several regions
of the world including large parts of sub-Saharan Africa. We investigated whether
provitamin A (proVA) enriched maize can simultaneously contribute to alleviate both
of these health concerns. We studied aflatoxin accumulation in grain of 120 maize
hybrids formed by crossing 3 Aspergillus flavus resistant and three susceptible lines
with 20 orange maize lines with low to high carotenoids concentrations. The hybrids
were grown in replicated, artificially-inoculated field trials at five environments. Grain
of hybrids with larger concentrations of beta-carotene (BC), beta-cryptoxanthin (BCX)
and total proVA had significantly less aflatoxin contamination than hybrids with lower
carotenoids concentrations. Aflatoxin contamination had negative genetic correlation
with BCX (−0.28, p<0.01), BC (−0.18, p<0.05), and proVA (−0.23, p<0.05). The
relative ease of breeding for increased proVA carotenoid concentrations as compared to
breeding for aflatoxin resistance in maize suggests using the former as a component of
strategies to combat aflatoxin contamination problems for maize. Our findings indicate
that proVA enriched maize can be particularly beneficial where the health burdens
of exposure to aflatoxin and prevalence of VAD converge with high rates of maize
consumption.
Keywords: aflatoxin, beta-carotene, beta-cryptoxanthin, biofortification, maize breeding, mycotoxins, vitamin A
deficiency
Abbreviations: AFT, aflatoxin concentration in grain; BC, β-carotene; BCX, β-cryptoxanthin; LT, lutein; pER, A. flavus ear
rot symptom scores; pFL, A. flavus colonization of grain measured by bright greenish yellow fluorescence scores; ProVA, total
provitamin A carotenoids concentration; ZX, zeaxanthin.
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Suwarno et al. Carotenoids and Aflatoxin in Maize Grain
INTRODUCTION
Aflatoxin contamination of maize is a serious health threat and
burden for millions of maize consumers worldwide. Aflatoxin is
a secondary metabolite produced by the ubiquitous Aspergillus
flavus fungus, and is very toxic to humans and animals.
Consumption of aflatoxin contaminated food is particularly
serious for children because it leads to compromised immune
system and increased morbidity and mortality from malaria
and other diseases, reduced efficiency of use for various macro-
and micro-nutrients, and stunting or underweight development
(Williams et al., 2004;Wild, 2007). In adults, aflatoxin is mainly
associated with liver and other cancers, but chronic exposure
to aflatoxin has also been associated with increased occurrence
of micronutrient deficiencies and increased burden of diseases
(e.g., malaria and HIV/AIDS) from weakened immune system
have also been reported or postulated (Williams et al., 2004).
Exposure to unsafe levels of aflatoxin in maize and maize
products is common for large populations in sub-Saharan Africa,
resulting in chronic morbidity and events of multiple deaths from
aflatoxicosis (Williams et al., 2004;Wild, 2007;Misihairabgwi
et al., 2017;Mahuku et al., 2019). Although we focus on human
health concerns of aflatoxin contamination in maize, aflatoxin in
grains other than maize, and in grains used in animal feeds are
also of huge economic and health concern.
Vitamin A deficiency (VAD) also affects millions of
maize consumers, particular children and pregnant women,
and especially in sub-Saharan Africa and Southeast Asia.
Biofortification, or breeding of provitamin A (proVA) enriched
maize varieties is ongoing at CIMMYT and other HarvestPlus
partner institutions (Pixley et al., 2013;Tanumihardjo et al.,
2017). Several proVA biofortified maize varieties have been
released in sub-Saharan Africa, where efficacy trials have
demonstrated their potential to benefit maize consuming, VAD
populations (Gannon et al., 2014). In contrast to the rapid success
of proVA breeding efforts, progress in breeding maize varieties
with resistance to A. flavus infection and aflatoxin contamination
has proven difficult and elusive (Henry et al., 2013;Warburton
and Williams, 2014). Bhatnagar-Mathur et al. (2015) reviewed
various methods to reduce aflatoxin contamination of grain,
including plant breeding, biological control in the field and
post-harvest handling of grain (see also Gressel and Polturak,
2018).
There is considerable evidence suggesting the potential of
breeding maize with enhanced concentrations of carotenoids
to have favorable health benefits for reducing the burden of
aflatoxin contamination of maize grain while also alleviating
VAD. Consumption of carotenoids, specifically beta-carotene
(BC) or beta-cryptoxanthin (BCX), has been associated with
reduced risk and decreased morbidity for diverse types of human
cancer, including lung, oral, pharynx, larynx, esophagus, colon,
prostate, and liver (Gradelet et al., 1998;Fiedor and Burda, 2014).
Krinsky (1991) cited 13 studies in mouse, 8 in hamster, and 5
in rat model for which BC inhibited tumor development and
or growth. The precise modes by which carotenoids exercise
anti-carcinogenic effects are not fully understood, but several
contributing mechanisms have been described. It is important to
note that the specific carotenoids, and not vitamin A (retinol),
have these beneficial effects (Krinsky, 1993;Alpsoy et al., 2009).
Preston and Williams (2005) explained that aflatoxin B1
(AFB1) is bio-converted to its more damaging form, AFBE, by the
action of cytochrome genes (e.g., CYP1A). AFBE then binds DNA
at a specific codon within the TP53 tumor-suppressing gene,
mutating it to inactivate its cancer-protective actions (Sporn et al.,
1966;Scaife, 1971;Preston and Williams, 2005). BC acts in several
ways to counter these carcinogenic effects of aflatoxin: (1) BC
up-regulates expression of TP53, thereby competing with AFBE’s
strategy to reduce production of TP53 transcript (Reddy et al.,
2006), (2) BC acts on CPY1A resulting in decreased production of
AFBE and increased metabolism of AFB1 to aflatoxin M1, a less
toxic metabolite (Krinsky, 1993;Gradelet et al., 1997, 1998), and
(3) BC reduces the production of AFB1 through its antioxidant
activities (Krinsky, 1989;Ponts et al., 2006;Fiedor and Burda,
2014;Montibus et al., 2015).
Montibus et al. (2015) reviewed the importance of
antioxidants in down-regulating secondary metabolism and
production of mycotoxins, including AFB1, by fungi. They
described how fungal invasion of plant cells commonly induces a
defensive “oxidative burst,” or release of reactive oxygen species
(ROS), intended to cause a hypersensitive, cell death reaction to
limit spread of the fungus. Some fungi, including A. flavus and
Fusarium spp. have evolved oxidation-demanding secondary
metabolism pathways that quench ROS while and by producing
mycotoxins (e.g., AFB1 by A. flavus, and deoxynivalenol (DON)
by Fusarium spp.). Carotenoids, especially BC and BCX, are
highly effective antioxidants that quench some of the ROS
produced in response to A. flavus invasion and thereby reduce
aflatoxin production. Many publications describe the antioxidant
role of flavonoids in down-regulating production of fumonisins
and DON (e.g., Boutigny et al., 2009;Atanasova-Penichon et al.,
2016;Giordano et al., 2017), and some allude to, or specifically
mention the analogous nature of carotenoids in combating
aflatoxin production.
Norton (1997) reported that carotenoid compounds (obtained
from commercial laboratories) that occur in yellow maize,
including BC, BCX, ZX, and LT, significantly reduced aflatoxin
production by A. flavus in vitro. Another in vitro study found
that commercially-obtained BC inhibited aflatoxin biosynthesis
by >70% for 38 Aspergillus genotypes isolated from Illinois
maize (Wicklow et al., 1998). More recently, Bhatnagar-
Mathur et al. (2015) discussed possibilities, albeit unrelated to
carotenoid concentrations in grain, to apply transgenic, RNAi
and gene editing approaches to combat aflatoxin production.
Subsequently, Thakare et al. (2017) demonstrated that transgenic,
host-induced gene silencing (HIGS) of the aflC gene, which
encodes an enzyme in the Aspergillus aflatoxin biosynthetic
pathway, inhibited aflatoxin biosynthesis by Aspergillus in maize
kernels. Although they did not evaluate Aspergillus and aflatoxin,
Díaz-Gómez et al. (2016) reported that transgenic maize lines
engineered to contain moderate concentrations of BC (5.9 µg
g−1) and BCX (3.7 µg g−1) had lower levels of fumonisin
accumulation (generally produced by Fusarium verticillioides and
F. proliferatum fungi) than their non-transgenic, white-grained
counterparts.
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There are no published reports about the relationship between
carotenoids content and aflatoxin accumulation in maize grain.
Therefore, our objective was to investigate the hypothesis that
proVA biofortified maize can have an additional health benefit by
reducing aflatoxin contamination of maize grain. Specifically, we
investigated the relationship between carotenoids concentrations
and aflatoxin accumulation in grain of A. flavus resistant or
susceptible hybrids with contrasting concentrations of BC, BCX,
ZX, and LT.
MATERIALS AND METHODS
Germplasm Materials
Twenty CIMMYT orange or yellow maize lines were chosen
based on their high (lines L1–L10) or low (L11–L20) total
provitamin A (proVA) concentrations (Supplementary
Table S1). The high proVA lines were promising lines within
CIMMYT’s proVA biofortification breeding program, while the
low proVA lines were also advanced lines, but would be discarded
due to their low proVA concentrations. Six white maize inbred
lines were chosen for use as testers based on prior information
about their resistance (lines R1–R3) or susceptibility (S1–S3)
to Aspergillus ear rot and aflatoxin accumulation (personal
communication, George Mahuku, former CIMMYT maize
pathologist) (Supplementary Table S2). We used white tester
lines because there were no orange or yellow resistant lines
available. The 20 lines were used as females for crosses with the
six testers as males, resulting in 120 F1hybrids.
Field Experiments
The 120 F1hybrids were evaluated in five environments: Agua
Fria, Puebla, Mexico (AF) (20◦320N, 97◦280W) and Tlaltizapan,
Morelos, Mexico (TL) (18◦41N, 99◦07W) during 2012 and
2013, and Mississippi State University, Starkville, Mississippi,
United States (MS) (33◦280N, 88◦460W) during 2012. The
experimental design was an alpha 0,1 lattice (Patterson et al.,
1978) with four replications (AF and TL) or three replications
(MS). Plots were 2 m long with 10 plants and between-row
spacing of 0.75 m. All plants were artificially inoculated with
A. flavus as described below. All primary ears from each plot
were hand-harvested, visually scored for Aspergillus ear rot
symptoms, as described below, and collected as a bulk. The
harvested maize ears were air-dried for a week to reduce
grain moisture to 13% prior to shelling for laboratory analyses
of F2 grains. Supplementary Table S3 presents the planting,
inoculation and harvest months, as well as average daily high
and low temperatures, rainfall and percent humidity for the
trials.
An additional un-replicated set of the F1hybrids was grown
as a nursery at each location (except MS) to enable carotenoids
quantification. These nurseries were non-inoculated and plants
were self-pollinated by hand. Carotenoid concentrations of
F2 grain from these nurseries were measured at CIMMYT’s
“Evangelina Villegas” Maize Quality Laboratory immediately
after harvest.
Field Inoculation With Aspergillus flavus
The A. flavus strains used for inoculum, final concentrations of
inoculum, number of inoculation points on the maize ears and
volume of conidial suspensions differed between the Mexican and
United States sites based on prior research experience at each site
and need to use strains endemic for each site, i.e., not to introduce
new strains or use strains that might not be adapted to conditions
at any site.
Aspergillus inoculation of the four trials in Mexico followed
CIMMYT’s standard protocols (Drepper and Renfro, 1990).
Four isolates of toxigenic A. flavus were grown in separate
jars containing sterilized maize grain for 2 weeks at 25◦C and
subsequently kept at 4◦C until use. Conidia were then collected by
adding sterilized tween 20-water into the jars, vigorously hand-
shaking and filtering the inoculum. Spores were counted using a
haemocytometer and diluted to achieve a final concentration of
106conidia ml−1. Maize ears were inoculated 14–18 days after
silking, with the mixed inoculum of 4 isolates of A. flavus. Using
a needle inoculation technique (Drepper and Renfro, 1990), the
primary ear on each maize plant was injected with the mixed
inoculum at two positions, i.e., on the side and on the tip of
the ear.
The inoculation procedure at MS was instructed by the
CHPRRU (Zummo and Scott, 1989). Briefly, A. flavus isolate
NRRL 3357 was increased in flasks containing 50 g of sterile
maize cob grits (size 2040, Grit-O-Cob, The Andersons Co.,
Maumee, OH, United States) and 100 ml of sterile distilled water,
and incubated at 28◦C for 21 days. Conidia were collected from
grits by adding sterilized tween 20-water and filtering through
layered sterile cheesecloth. The concentration of conidia was
counted with a haemocytometer and diluted to obtain 9 ×107
conidia ml−1. The primary ear of each plant was inoculated
7 days after silking using the side-needle technique with 3.4 ml of
the conidial suspension (Zummo and Scott, 1989;Williams et al.,
2013).
Visual Evaluations of Aspergillus Ear Rot
and Aflatoxin Contamination
The visible fungal colonization, or Aspergillus ear rot (ER)
symptom scores, were assessed for ears at harvest using a scale
of 1–5, where 1 is 0% and 5 is 100% of visible fungal infection
(adapted from Campbell and White, 1995).
The extent of A. flavus invasion in maize grain was assessed
using the bright greenish yellow fluorescence (BGYF) test
(Busboom and White, 2004;Matumba et al., 2013). After shelling
and drying (as described above), 100-kernel random samples
were taken for each plot. Kernel samples were arranged in one
layer on trays, and the extent of BGYF (FL) was visually assessed
in a dark room with 365 nm UV light using the same scale as
described above for ear rot score.
Data for ER and FL were obtained for the four Mexican
environments only. The ER and FL rating scores were converted
to percent ear rot (pER) and percent BGYF (pFL) by equating 0,
25, 50, 75, and 100% to scores of 1, 2, 3, 4, and 5, respectively.
The pER and pFL values were transformed using square root
to normalize the data distributions prior to statistical analyses
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FIGURE 1 | Quartile distribution box plots (upper) and histograms (lower) of hybrid means for aflatoxin concentration in grain [AFTt, log(AFT+1)], A. flavus ear rot
symptom scores [pERt, sqrt(pER)], and A. flavus colonization of grain measured by bright greenish yellow fluorescence scores [pFLt, sqrt(pFL)]. Across, across
environments; AF12, AF13, Agua Fria, 2012 and 2013; TL12, TL13, Tlaltizapan 2012 and 2013; MS12, Mississippi 2012.
(Figure 1). We subsequently refer to the transformed data as
pERt and pFLt.
Quantification of Aflatoxin Concentration
in Grain
Aflatoxin concentration in grain was quantified for 50 g sub-
samples of ground maize kernels from each plot using VICAM’s
AflaTest protocol (Watertown, MA, United States). Briefly, 5 g
NaCl were added to a glass blender jar containing the ground
grain and 100 ml of 80% methanol was added as a solvent to
extract aflatoxin from the grain. This solution was mixed at the
high speed of a common kitchen blender for 1 min. The filtrate
was then collected from each sample using fluted Whatman #4
filter paper. Ten ml of the filtered extract was added to a clean
flask with 40 ml of purified water and this diluted extract was
filtered again using a microfiber filter. Column chromatography
was performed by passing 2 ml of filtered diluted extract through
the AflaTest column. Contaminants were removed by washing
the column twice with 5 ml of purified water. One ml of HPLC
grade methanol was then added to the chromatography column
to elute the aflatoxin. Sub-samples with more than 500 parts
per billion (ppb) of aflatoxin were re-tested: (1) for samples
with 500–699 ppb, 1 ml of the first filtered extract was added
to 49 ml of 15% methanol and then 2 ml of this dilution was
passed through a new AflaTest column; (2) for samples with
700–999 ppb, only 1 ml of the dilution was used for the new
chromatography; and (3) for samples with >1000 ppb, a 40X
dilution was made by diluting 1 ml of the first filtrate in 99 ml
of 15% methanol and loading 1 ml of this 40X diluted filtrate
into the chromatography column. Aflatoxin concentration (AFT)
was expressed in nanograms per gram or ppb, and these data
were transformed using log10(AFT+1) to normalize the data
(Figure 1) prior to statistical analyses. We subsequently refer to
the transformed AFT data as AFTt.
Carotenoid Quantification
Carotenoid concentrations were quantified by Ultra Performance
Liquid Chromatography (UPLC) (Muzhingi et al., 2017). Briefly,
ethanol was added to 600 mg of finely ground grain samples,
followed by saponification and carotenoids extraction using
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Suwarno et al. Carotenoids and Aflatoxin in Maize Grain
hexane as a solvent. A 30C UPLC column was used for the
separation, and quantification of carotenoids used a multi-
wavelength detector set at 450 nm. Data collection and processing
were conducted using Waters Millennium, 2010 software
(Waters Chromatography, Milford, MA, United States). LT,
ZX, β-cryptoxanthin (BCX), and all-trans-β-carotene (BC) were
identified through their characteristic spectra and by comparing
their retention times with known standard solutions. Total
proVA content (µg g−1of dry matter) was calculated for each
sample as the sum of BC plus half of BCX.
Statistical Analyses
Analyses of variance (ANOVA) were performed for AFTt, pERt
and pFLt data for the 120 hybrids at individual and across
trial locations. Individual environment ANOVAs used a linear
mixed model with replications and incomplete blocks within
replications as random effects, and line, tester and line ×tester
(hybrid) considered as fixed effects. Similarly, for ANOVA
across environments, the effects of replicates within environment
and incomplete blocks within replicates and environment were
considered random effects, whereas lines, testers, and hybrids
as well as their interaction with environments were considered
fixed effects. These ANOVAs were performed using the MIXED
procedure of SAS (SAS 9, 2017).
The hybrids source of variation was sub-divided into variance
attributed to testers (T), lines (L) and interaction of L ×T. The
variance among testers was further sub-divided into variance
among hybrids of resistant (R) or susceptible (S) testers, and the
contrast between R and S. Similarly, the variance among lines (L)
was sub-divided into variance among hybrids of lines with high
(Hi) or low (Lo) carotenoids concentrations, and the contrast
between Hi and Lo. The contrast R vs. S estimated the significance
of differences in AFTt, pERt, and pFLt between hybrids of
resistant or susceptible testers, whereas the contrast of Hi vs.
Lo estimated the significance of differences in AFTt, pERt, and
pFLt between hybrids of lines with high or low concentrations of
carotenoids. The contrasts were performed for each trait (AFTt,
pERt, and pFLt) for each individual environment and combined
across environments using the MIXED procedure together with
the CONTRAST command of SAS (SAS 9, 2017).
The classification of the 20 experimental lines as Hi or Lo was
based on the average carotenoid concentrations of the F2grain
of their six hybrids (Table 1 and Supplementary Table S1). The
lines whose hybrids had greater carotenoid value than the average
were categorized as Hi, and the others were classified as Lo. This
classification was done independently for each carotenoid, BC,
BCX, ZX and LT. We used the classification based on carotenoids
concentrations in the F2 grain because A. flavus inoculations
and subsequent AFT, pER, and pFL measurements also used F2
grain.
Phenotypic and genotypic correlation coefficients among
variables were estimated using entry means (for aflatoxin traits)
and entry values (for carotenoid traits). Additive main effects
and multiplicative interactions (AMMI) (Gauch, 1988) analysis
was performed for four traits (BCX, BC, AFTt, pERt) where
the hybrid by environments interaction was decomposed into
principal components, and a biplot (hybrids and environments)
involving the first two principal components was drawn using
AGD-R software (Rodríguez et al., 2015).
Repeatability (H2) across environments was estimated as:
H2=
σ2
g
σ2
g+σ2
ge/l+σ2
g/rl
Where σ2
gis the genotypic variance, σ2
ge is the genotype by
environment interaction variance, σ2
gis error variance, ris the
number of replications and lis the number of environments. The
repeatability for individual environment analyses was:
H2=
σ2
g
σ2
g+σ2
e/r
RESULTS
The data transformations resulted in approximately normal
distributions for entry means for AFTt, pERt, and pFLt
(Figure 1). Subsequent analyses of variance resulted in moderate
to high repeatabilities at individual sites and across locations
for AFTt (0.45–0.71 and 0.61), pERt (0.32–0.56 and 0.42) and
pFLt (0.23–0.76 and 0.54) (Tables 2–4 and Supplementary
Tables S4–S6), indicating that the trials were of good quality.
Least squares means for AFTt, pERt and pFLt at individual and
across environments are presented in Supplementary Table S7.
The hybrids differed significantly (p<0.001) for AFTt, pERt,
and pFLt in all single- and across-location analyses. Environment
(E) effects were also highly significant (p<0.001) for all traits
(Supplementary Tables S4A, S5A, S6A), with the most notable
difference that mean AFTt was greater at AF12 than other sites
(Figure 1). The highly significant effect of hybrids confirms that
the 120 hybrids differed for their resistance or susceptibility to
A. flavus. Further, the significant (p<0.001) variance for all traits
due to testers, lines, and lines ×testers effects (Supplementary
Tables S4A, S5A, S6A), indicates the significance of additive or
general combining ability (GCA), and non-additive or specific
combining ability (SCA) effects on A. flavus resistance of the
hybrids. The highly significant (p<0.001) contrasts of resistant
versus susceptible testers (R vs. S) for AFTt, pERt, and pFLt
in the across-environment analyses (Tables 2–4) confirm that
the hybrids of resistant testers were indeed significantly more
resistant to A. flavus than the hybrids of susceptible testers.
Significant (p<0.001) interactions of environments with hybrid,
tester, line, and line ×tester effects indicate that GCA and SCA
effects varied between environments.
Analyses of variance for carotenoids concentrations identified
significant (p<0.0001 or p<0.001) environmental effects
and significant (p<0.0001) differences among hybrids for all
traits (proVA, BC, BCX, ZX, and LT) (ANOVA not shown).
More interestingly, the contrasts of hybrids with high versus
low carotenoid grain concentration (Hi vs. Lo) for total proVA
(p<0.05), BC, BCX, ZX, and LT (p<0.001) were significant
for across-environment analyses for AFTt (Table 2), indicating
that carotenoid concentrations affected aflatoxin accumulation in
grain. Similarly, the Hi vs. Lo contrasts for proVA, BC, and LT
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TABLE 1 | Numbers of hybrids and mean carotenoid concentrations (µg g−1dry weight) for F2 grain of hybrids grouped as high (Hi) and low (Lo) for carotenoids
concentrations.
ProVA BC BCX ZX LT
nMean nMean nMean NMean nMean
Hi 9 3.59 7 2.04 9 1.39 9 2.82 8 0.73
Lo 11 1.33 13 0.59 11 0.80 11 1.59 12 0.43
Hi/Lo 2.71 3.46 1.74 1.77 1.69
pvalue <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
Overall mean 2.35 1.10 1.07 2.14 0.55
ProVA, total provitamin A carotenoids concentration; BC, β-carotene; BCX, β-cryptoxanthin; ZX, zeaxanthin; LT, lutein. N is the number of lines in each group. See
Supplementary Table S1 for data for each hybrid.
TABLE 2 | Probabilities of significance (p) for F-tests for contrasts of hybrids of aflatoxin resistant (R) vs. susceptible (S) testers, and for hybrids with high (Hi) vs. low (Lo)
carotenoids concentrations for aflatoxin concentration in grain [AFTt, log(AFT+1)] for analyses of variance at individual and across five trial environments.
Source of variation Carotenoids Across (p) AF12 (p) AF13 (p) MS12 (p) TL12 (p) TL13 (p)
R vs. S All <0.0001 <.0001 0.0011 <0.0001 <0.0001 <0.0001
Hi vs. Lo ProVA 0.0235 0.2793 0.0002 0.4333 0.0299 0.6399
BC <0.0001 0.1620 <0.0001 0.4218 0.0175 0.0503
BCX 0.0008 0.7214 0.3698 0.0011 0.2961 0.1155
ZX <0.0001 0.8773 0.3364 0.0391 0.1530 <0.0001
LT <0.0001 0.2564 <0.0001 0.0202 0.0974 <0.0001
H20.61 0.66 0.68 0.71 0.45 0.71
CV (%) 28.15 8.65 26.85 34.39 53.60 45.02
AF12, AF13, Agua Fria, 2012 and 2013; TL12, TL13, Tlaltizapan 2012 and 2013; MS12, Mississippi 2012. ProVA, total provitamin A; BC, β-carotene; BCX,
β-cryptoxanthin; ZX, zeaxanthin; LT, lutein concentration in grain. H2, repeatability; CV, coefficient of variation.
TABLE 3 | Probabilities of significance (p) for F-tests for contrasts of hybrids of aflatoxin resistant (R) vs. susceptible (S) testers, and for hybrids with high (Hi) vs. low (Lo)
carotenoids concentrations for A. flavus ear rot symptom scores [pERt, sqrt(pER)] for analyses of variance at individual and across five trial environments.
Source of variation Carotenoids Across (p) AF12 (p) AF13 (p) TL12 (p) TL13 (p)
R vs. S All <0.0001 0.0001 0.2766 0.0442 0.0008
Hi vs. Lo ProVA <0.0001 0.0707 0.0101 0.5812 0.0017
BC <0.0001 0.1085 <0.0001 0.6628 0.0477
BCX 0.0825 0.0004 0.5990 0.7132 0.9981
ZX 0.4579 0.4143 0.0770 0.6834 0.9740
LT <0.0001 0.2999 <0.0001 0.1264 0.1012
H20.42 0.51 0.56 0.32 0.40
CV (%) 21.79 22.75 18.90 24.58 20.39
AF12, AF13, Agua Fria, 2012 and 2013; TL12, TL13, Tlaltizapan 2012 and 2013; MS12, Mississippi 2012. ProVA, total provitamin A; BC, β-carotene; BCX,
β-cryptoxanthin; ZX, zeaxanthin; LT, lutein concentration in grain. H2, repeatability; CV, coefficient of variation.
TABLE 4 | Probabilities of significance (p) for F-tests for contrasts of hybrids of aflatoxin resistant (R) vs. susceptible (S) testers, and for hybrids with high (Hi) vs. low (Lo)
carotenoids concentrations for A. flavus colonization of grain measured by bright greenish yellow fluorescence scores [pFLt, sqrt(pFL)] for analyses of variance at
individual and across five trial environments.
Source of variation Carotenoids Across (p) AF12 (p) AF13 (p) TL12 (p) TL13 (p)
R vs. S All <0.0001 <0.0001 0.2285 0.2572 <0.0001
Hi vs. Lo ProVA 0.2078 0.7548 0.9539 0.9113 0.0762
BC 0.0142 <0.0001 0.5900 0.4349 0.4506
BCX 0.1737 0.2260 0.7437 0.4114 0.8838
ZX 0.0155 0.8212 0.1718 0.0587 0.0537
LT 0.0054 0.6818 0.0054 0.0624 0.1601
H20.54 0.76 0.44 0.23 0.49
CV (%) 24.89 23.41 17.18 32.09 25.22
AF12, AF13, Agua Fria, 2012 and 2013; TL12, TL13, Tlaltizapan 2012 and 2013; MS12, Mississippi 2012. ProVA, total provitamin A; BC, β-carotene; BCX,
β-cryptoxanthin; ZX, zeaxanthin; LT, lutein concentration in grain. H2, repeatability; CV, coefficient of variation.
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TABLE 5 | Contrasts of aflatoxin concentration (AFTt), ear rot (pERt), and
fluorescence scores (pFLt) between hybrids with high (Hi) vs. low (Lo) grain
concentrations of five carotenoids, analyzed for all 120 hybrids and independently
for sub-sets of 60 hybrids of Aspergillus flavus resistant (R) or 60 hybrids of
susceptible (S) tester lines.
Trait Carotenoid All hybrids R testers S testers
Hi Lo Hi Lo Hi Lo
AFTt ProVA 1.99∗2.05 1.80 1.85 2.18∗2.26
BC 1.94∗∗∗ 2.07 1.74∗∗∗ 1.87 2.13∗∗∗ 2.27
BCX 1.98∗∗∗ 2.06 1.79 1.86 2.16∗∗∗ 2.27
ZX 2.08 1.97∗∗∗ 1.89 1.78∗∗ 2.28 2.17∗∗
LT 2.12 1.96∗∗∗ 1.89 1.78∗∗ 2.35 2.13∗∗∗
pERt ProVA 5.42∗∗∗ 5.65 5.28∗∗ 5.51 5.57∗∗ 5.79
BC 5.39∗∗∗ 5.63 5.26∗∗ 5.48 5.52∗∗ 5.79
BCX 5.49 5.59 5.40 5.41 5.60∗5.77
ZX 5.57 5.53 5.45 5.36 5.68 5.70
LT 5.71 5.44∗∗∗ 5.56 5.30∗∗ 5.85 5.59∗∗
pFLt ProVA 4.25 4.19 4.12 3.99∗4.38 4.40
BC 4.14∗4.26 4.02 4.06 4.25∗∗ 4.47
BCX 4.18 4.25 4.04 4.06 4.32 4.45
ZX 4.28 4.17∗4.10 4.01 4.47 4.33∗
LT 4.30 4.16∗∗ 4.11 4.01 4.49 4.32∗
∗,∗∗,∗∗∗ indicate the mean which is significantly (p <0.05, <0.01, or <0.001,
respectively) superior for the resistance trait (AFTt, pERt, or pFLt) in the respective
pair-wise contrast, e.g., Hi vs. Lo proVA concentration among all hybrids, among
hybrids of A. flavus resistant testers, or among hybrids of A. flavus susceptible
testers. Pairs of means without indication of significance were not significantly
different (p <0.05).
were significant for pERt (p<0.001) (Table 3), and the Hi vs. Lo
contrasts for BC, ZX (p<0.05) and LT (p<0.01) were significant
for pFLt (Table 4).
Analysis of the 60 hybrids of susceptible testers indicated that
hybrids with larger concentrations (Hi) of proVA, BC and BCX
always had significantly less ear rot and aflatoxin than hybrids
with smaller (Lo) concentrations of these carotenoids (Table 5).
This relationship was generally also significant for hybrids of
A. flavus resistant tester lines. By contrast, hybrids with larger
concentrations of ZX and LT were generally more susceptible to
A. flavus infection than those with smaller concentrations of these
carotenoids.
Some of the contrasts of R vs. S testers and Hi vs. Lo lines
from single environment analysis were not significant, indicating
the greater power of the combined analyses. The interaction
effects of E ×(R vs. S testers) were significant for AFTt and
pFLt (p<0.001), indicating that the magnitude of differences
among the means of hybrids of R and S testers varied between
environments (Table 6). Significant interactions occurred for
E×(Hi vs. Lo proVA, BC, ZX, and LT lines) for AFTt, E ×(Hi
vs. Lo BC and LT lines) for pERt, and E ×(Hi vs. Lo BC lines) for
pFLt.
Estimates of genotypic correlation coefficients indicate that
AFTt and pERt were negatively associated with concentrations
of BCX (p<0.01), BC (p<0.05), and proVA (p<0.05
TABLE 6 | Probabilities of significance (p) for F-tests for interaction contrasts of
environment (E) by hybrids of aflatoxin resistant (R) vs. susceptible (S) testers, and
for E by hybrids with high (Hi) vs. low (Lo) carotenoids concentrations for aflatoxin
concentration in grain [AFTt, log(AFT +1)], A. flavus ear rot symptom scores
[pERt, sqrt(pER)], and A. flavus colonization of grain measured by bright greenish
yellow fluorescence scores [pFLt, sqrt(pFL)] for analyses of variance across five
(AFTt) or four (pERt and pFLt) trial environments.
Source of variation Carotenoids (p) AFTt (p) pERt (p) pFLt (p)
E×(R vs. S) All <0.0001 0.3201 <0.0001
E×(Hi vs. Lo) ProVA 0.0016 0.1485 0.3845
BC 0.0352 0.0369 0.0006
BCX 0.0733 0.2110 0.7936
ZX 0.0157 0.4490 0.2649
LT <0.0001 0.0306 0.6668
ProVA, total provitamin A; BC, β-carotene; BCX, β-cryptoxanthin; ZX, zeaxanthin;
LT, lutein concentration in grain.
and p<0.01, respectively) in grain (Table 7). Phenotypic
correlation coefficients for carotenoids concentrations with
A. flavus infection traits were only significant (p<0.05) for
BCX with AFTt and pERt. The phenotypic and genotypic
correlation coefficients among carotenoid concentrations, and
among A. flavus infection parameters were generally as expected.
The phenotypic correlation between the two visually-scored
traits, pERt and pFLt, was moderate (rP= 0.56, p<0.001), but
the genotypic correlation coefficient between these traits was high
(rG= 0.93, p<0.001). Moreover, the correlation coefficients
between the visually-scored traits and the quantitative estimate
of aflatoxin concentration (AFTt) were all very strong (p<0.001)
and positive (rP= 0.56–0.69; rG= 0.89–1.00).
The AMMI biplot for main effects and interactions of
genotypes and traits visibly separated aflatoxin (AFTt and pERt)
from carotenoid concentrations (BCX and BC) along PCA1,
which explained 68% of the variation (Figure 2). PCA2, which
explained an additional 25% of the variation, indicated a factor
that associated AFTt and pERt positively with BC and negatively
with BCX.
DISCUSSION
Our finding of large variation for AFTt, pERt, and pFLt
among environments, and even among micro-environments
(replications), is consistent with previous reports of large
environmental influence on A. flavus infection during pre-
harvest, and on aflatoxin accumulation during both pre-
and post-harvest (Arunyanark et al., 2010;Mayfield et al.,
2011;Warburton et al., 2011). This highlights the importance
of using multiple replications and environments to achieve
repeatable results when studying A. flavus resistance-related
traits. The normal frequency distributions for the transformed
data (Figure 1), and the moderate to high repeatability estimates
from analyses of variance (Tables 2–4), indicate the reliability
of our results. Secondly, the clear separation of the hybrids’
grain as resistant or susceptible to A. flavus (R vs. S contrast,
Tables 2–4) justified the further analyses of associated effects of
grain carotenoids concentrations with A. flavus resistance.
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TABLE 7 | Pearson phenotypic correlation (above diagonal) and genotypic correlation (below diagonal) coefficients and among carotenoid and aflatoxin traits for F2 grain
of 120 hybrids grown at four environments.
LT ZX BCX BC ProVA pERt pFLt AFTt
LT 0.99∗∗∗ 0.68∗∗∗ 0.30∗∗ 0.40∗∗∗ −0.06 ns 0.07 ns −0.10 ns
ZX 0.99∗∗∗ 0.72∗∗∗ 0.35∗∗∗ 0.46∗∗∗ −0.10 ns 0.05 ns −0.11 ns
BCX 0.68∗∗∗ 0.73∗∗∗ 0.50∗∗∗ 0.65∗∗∗ −0.19∗0.01 ns −0.18∗
BC 0.29∗∗ 0.35∗∗∗ 0.50∗∗∗ 0.98∗∗∗ −0.12 ns 0.05 ns −0.13 ns
ProVA 0.39∗∗∗ 0.45∗∗∗ 0.64∗∗∗ 0.98∗∗∗ −0.15 ns 0.05 ns −0.16 ns
pERt −0.09 ns −0.14 ns −0.30∗∗∗ −0.23∗−0.26∗∗ 0.56∗∗∗ 0.56∗∗∗
pFLt 0.11 ns 0.09 ns 0.02 ns 0.08 ns 0.08 ns 0.93∗∗∗ 0.69∗∗∗
AFTt −0.16 ns −0.17 ns −0.28∗∗ −0.18∗−0.23∗0.89∗∗∗ 1.00∗∗∗
ProVA, total provitamin A; BC, β-carotene; BCX, β-cryptoxanthin; ZX, zeaxanthin; LT, lutein concentration in grain. ns, not significant, p <0.05; ∗,∗∗, and ∗∗∗ = significant
p<0.05, 0.01, and 0.001, respectively.
FIGURE 2 | Additive main effects and multiplicative interactions (AMMI) biplot of hybrids and four traits: aflatoxin concentration in grain [AFTt, log(AFT+1)], A. flavus
ear rot symptom scores [pERt, sqrt(pER)], β-carotene (BC), β-cryptoxanthin (BCX) concentration in grain.
Although the trial environments were diverse and used
different A. flavus inocula, we treated them as fixed in ANOVA
analyses because there were only five of them. However, the five
environments included lowland tropical, mid-altitude tropical,
and temperate ecologies, and their respective fungal isolate
diversity. We speculated that the scope of inference for our
findings is broader than our five trial environments, and found
that ANOVA using environments as random effects produced
same results as the model treating environments as fixed, i.e., all
sources of variation were significant at the same broad probability
levels (NS, p<0.05, p<0.01, p<0.001, etc.) (Supplementary
Table S8). We conclude that our findings can be extended, with
caution until validated more widely, beyond the five experimental
environments.
Maize grain with higher concentrations of proVA, BC,
and BCX had less aflatoxin contamination (AFTt) than
grain with smaller carotenoid concentrations (Table 5). This
superior aflatoxin resistance of hybrids with high versus
low concentrations of proVA, BC, and BCX was statistically
significant among the 60 hybrids formed with A. flavus
susceptible tester lines. For the 60 hybrids formed with
A. flavus resistant parent tester lines, however, only hybrids
with contrasting BC concentrations differed significantly for
AFTt in grain. The fact that only BC provided a statistically
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Suwarno et al. Carotenoids and Aflatoxin in Maize Grain
significant additional aflatoxin resistance benefit to hybrids
formed with A. flavus resistant parents may have been because
the differences in high versus low carotenoids concentrations
were much larger for BC than for BCX and total proVA
(Table 1). These results indicate that increased concentrations
of BC, BCX, and proVA carotenoids can be a valuable first
line of defense against aflatoxin contamination of grain. This
further suggests that proVA biofortified maize, or any maize
with increased concentrations of these carotenoids can offer an
important health benefit for consumers affected by both VAD
and chronic exposure to aflatoxin contaminated maize products.
This is particularly important for sub-Saharan Africa, where a
large health burden of exposure to aflatoxin (see discussion above,
or e.g., Williams et al., 2004;Wild, 2007), prevalence of VAD
(Muthayya et al., 2013), and large dependence on maize as a staple
food converge.
The fact that hybrids with smaller concentrations of ZX and
LT were significantly more resistant to aflatoxin than hybrids
with larger concentrations of these carotenoids is likely due
to their competing roles with proVA, BC and BCX within the
carotenoid biosynthetic pathway. Provitamin A biofortification
breeding programs have selected for alleles of (1) the LcyE gene
(Harjes et al., 2008) that decrease flux toward the alpha-branch
of the carotenoid biosynthetic pathway, and hence decrease LT
concentration in grain, and (2) the CrtRB1 gene (Babu et al.,
2013) that reduce flux from BC toward BCX and ZX (Pixley et al.,
2013).
Maize grain with higher concentrations of BC had smaller
mean pERt and pFLt than grain with low BC concentration
(Tables 3,4). However, although generally favorable, the effects
of carotenoids concentrations on the means for the visually-
assessed indicators of aflatoxin contamination (pERt and pFLt),
were weaker and less consistent than for AFTt. This result is
consistent with lower repeatability for these visually-assessed
traits compared to AFTt.
The GCA effects of lines and testers, as well as their
interactions with environments were highly significant for AFTt,
pERt, and pFLt (p<0.001) (Supplementary Table S4A,
S5A, S6A). The line ×tester (SCA) effects were highly
significant for AFTt and pFLt (p<0.001), but not for pERt
(p= 0.056). This indicates the importance of both additive
and non-additive gene actions for the inheritance of aflatoxin
resistance in maize. These results are consistent with experience
that breeding for aflatoxin resistance is complex, requiring
selection for specific hybrid combinations that avail dominance
and epistatic gene actions. The fact that breeding directly for
aflatoxin resistance is very challenging adds importance to our
findings that increasing carotenoids concentrations had desirable
effect for reducing aflatoxin concentrations in grain. Breeding
for increased carotenoids concentrations in maize grain is
relatively straightforward (Pixley et al., 2013;Tanumihardjo et al.,
2017).
The significant genotypic correlation coefficients for proVA,
BC, and BCX with AFTt and pERt (Table 7) indicate that
these relationships are rooted in common genetic factors. The
magnitude of these genotypic correlations was small [rG= 0.18
(p<0.05) to 0.30 (p<0.01)], and the potential to achieve double
health benefits from proVA biofortified maize therefore requires
further validation.
The AMMI biplot helps visualize the strong negative genetic
correlations between aflatoxin traits (AFTt and pERt) and
carotenoids concentrations (BC and BCX) on the X-axis (68%
of variance), and a weaker factor negatively associating BCX and
positively associating BC concentration with aflatoxin traits (Y-
axis, 25% of variance) (Figure 2). Large cumulative percentage
for the two PC axes (93%) indicates that the biplot captured
most of the genotype-by-trait variation. The combined effects of
the two PCA axes suggest that while BC had strongest influence
(PCA1), BCX contributed an important additional mechanism
of action against aflatoxin production or accumulation (PCA2).
This finding adds a new dimension - aflatoxin resistance -
to support nutritional arguments presented by Dhliwayo et al.
(2014) and Taleon et al. (2017) for reconsidering current proVA
biofortification breeding strategies that strongly reduce BCX in
favor of accumulating more BC (Babu et al., 2013;Zunjare et al.,
2018). We propose to further investigate these relationships using
maize lines with wider ranges of BCX and BC concentrations
than used herein (Table 1).
At the time of this study, CIMMYT had no orange maize
lines with characterized resistances to Aspergillus ear rot and
aflatoxin accumulation for possible use as testers. Otherwise,
using orange maize lines as testers would have produced larger
levels of carotenoid concentrations in grains and might have
improved the investigation of their effects on Aspergillus ear
rot and aflatoxin accumulation. However, if orange testers had
been used, differences for carotenoid concentrations might have
been confounded with differences in resistance genes among the
testers, complicating the interpretation of results.
Several secondary traits associated with aflatoxin
accumulation have been proposed for use in indirect selection,
e.g., rating for insect damage, ear injury, husk cover (Betrán et al.,
2002), fungus biomass estimation by qPCR (Mideros et al., 2009),
and drought tolerance (Arunyanark et al., 2010). Campbell and
White (1995) suggested using visual selection for low Aspergillus
ear rot symptom scores (pERt in our study) to select lines with
greater aflatoxin resistance, thereby avoiding more expensive
aflatoxin assays. Visual ratings of Aspergillus ear rot symptoms
and of BGYF substance (pFLt in our study) are simpler and
much less expensive than aflatoxin quantification, which requires
expensive chemical reagents, specific equipment and technical
skills.
Although the genotypic correlation of Aspergillus ear rot
symptom score (pERt) with AFTt was highly significant (r= 0.89,
p<0.001) for the 120 hybrids studied herein, experience
and literature (e.g., Walker and White, 2001;Henry et al.,
2009) suggest that this trait is not a very reliable indicator of
aflatoxin concentration in grain. The strong positive genotypic
correlation for AFTt with pFLt (r= 1.00, p<0.001) (Table 7),
suggests that pFLt may be useful for rapid indirect assessment
of potential aflatoxin accumulation. Successful use of the BGYF
test requires technical skills for sampling (Campbell et al.,
1986) and visual scoring (Dickens and Whitaker, 1981;Henry
et al., 2009), but its simplicity, low cost and greater reliability
than visual ear rot symptom scores make it an appealing
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Suwarno et al. Carotenoids and Aflatoxin in Maize Grain
candidate for use as a secondary trait and predictor of aflatoxin
concentration.
In conclusion, this is the first published report documenting
significant reduction in aflatoxin contamination for maize
with conventionally-bred levels of carotenoids. This result was
found using maize hybrids with carotenoid concentrations that
are one-half, one-third, or only one-fourth as large as more
recent hybrids developed by CIMMYT’s proVA biofortification
breeding program (Pixley et al., 2013;Andersson et al., 2017;
Sowa et al., 2017). The relative ease of breeding for increased
carotenoid concentrations as compared to breeding for aflatoxin
resistance in maize make this finding especially significant as
part of a solution to aflatoxin contamination problems for maize.
Furthermore, because the antioxidant effects of carotenoids on
reducing aflatoxin production are non-enzymatic, it is likely
that these act also in grain during post-harvest, when A. flavus
infection and aflatoxin production are a serious concern and
when most breeding strategies, including transgenic HIGS
strategies are expected to be ineffective (Gressel and Polturak,
2018).
Future research should assess (1) whether stronger effects on
reducing A. flavus infection and aflatoxin contamination have
accrued by breeding maize with further-increased concentrations
of BC and BCX and (2) whether significant aflatoxin-reducing
effects also occur during post-harvest exposure of grain to
A. flavus. Also, and although aflatoxin is of greatest global
concern, it will be valuable to assess whether increased
concentrations of BC and BCX confer advantages for reducing
infection and production of mycotoxins by Fusarium spp.
The results herein demonstrate that BC, BCX, and proVA
concentrations already present in biofortified hybrids can provide
an advantage for reducing aflatoxin levels in maize. Thus,
maize with increased content of proVA carotenoids may offer
double health benefits by reducing aflatoxin concentrations while
contributing to reduce vitamin A deficiency in affected maize
consuming populations.
DATA AVAILABILITY STATEMENT
Datasets are available on request: The raw data supporting the
conclusions of this manuscript will be made available by the
authors, without undue reservation, to any qualified researcher.
AUTHOR CONTRIBUTIONS
WS, PH, and KP contributed equally as first authors. KP,
NP-R, and PH contributed conception and design of the study,
developed the hybrids, and oversaw the trials in Mexico. GW
implemented the trial at MS and enabled the VICAM aflatoxin
analyses for those samples. NP-R, PH, and WS organized the data.
PH conducted the VICAM aflatoxin analyses for all Mexican sites
and performed preliminary data analyses and interpretation as
part of her Ph.D. thesis under guidance of KP. NP-R oversaw
the carotenoids analyses. JC and WS performed the statistical
analyses. All authors contributed to manuscript revision, read
and approved the submitted version.
FUNDING
Financial support for this study was partially provided
by HarvestPlus (www.HarvestPlus.org), a global alliance of
agriculture and nutrition research institutions working to
increase the micronutrient density of staple food crops
through biofortification. The views expressed do not necessarily
reflect those of HarvestPlus. The CGIAR Research Program
MAIZE (CRP-MAIZE) also supported this research. CRP-
MAIZE receives support from the Governments of Australia,
Belgium, Canada, China, France, India, Japan, Korea, Mexico,
Netherlands, New Zealand, Norway, Sweden, Switzerland,
United Kingdom, United States, and the World Bank.
ACKNOWLEDGMENTS
This work builds on the Ph.D. dissertation of Dr. Pattama
Hannok at University of Wisconsin, Madison, WI, United States
(Hannok, 2015). We thank Dr. George Mahuku (formerly Maize
Pathologist, CIMMYT), who provided A. flavus resistant and
susceptible lines that we used as testers. We are grateful to Drs.
Paul Williams and Marilyn Warburton (CHPRRU, Mississippi)
for advice and support of activities at the MS site. This work
would not have been possible without the assistance of Ms.
LaDonna Owens, who assisted in AFT quantification for the
samples grown at CHPRRU, MS, and trained us to implement
the VICAM test at CIMMYT for samples grown in Mexico.
We thank Aide Molina and Alejandra Miranda at CIMMYT’s
“Evangelina Villegas” Maize Quality Laboratory, Carlos Muñoz
of CIMMYT’s maize pathology laboratory, Gregorio Alvarado of
CIMMYT’s Biometrics and Statistics Unit, and field technicians
at CIMMYT’s Agua Fria and Tlaltizapán research stations for
their remarkable support for this study. We thank the reviewers
for critical comments and suggestions that helped improve the
manuscript.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found online
at: https://www.frontiersin.org/articles/10.3389/fpls.2019.00030/
full#supplementary-material
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Conflict of Interest Statement: The authors declare that the research was
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be construed as a potential conflict of interest.
Copyright © 2019 Suwarno, Hannok, Palacios-Rojas, Windham, Crossa and Pixley.
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