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Effect of crop location and genotype on phenolic compounds, mineral contents, and antioxidant activity in yellow maize landraces

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Abstract

The Mesoamerican region is center of origin, domestication, and diversification of maize. In this ecogeographic context, the objective was to evaluate the variation in the phenolic compounds, antioxidant activity and concentration of minerals in the grain of a population collection of yellow maize landraces from southeastern Mexico. During 2016, samples of landraces of yellow maize were collected and integrated into 32 populations and experimental varieties, which were planted in two locations in Oaxaca, Mexico, under a random block design. At harvest, a sample of grain was taken, which was grounded to evaluate the polyphenolic compound contents and antioxidant activity by UV-visible spectrophotometry, and macro-and microelement contents were determined using inductively coupled plasma-optical emission spectrometry. The effect of crop location was significantly greater than the effects of populations and location-population interaction on polyphenol contents and concentration of Ca, P, Mg, K, Na, S, Cu, Fe, Mn and Zn. In the Amatengo locality, a higher macroelement contents were recorded, and in the second locality, the concentration of microelements, polyphenols, and flavonoids contents were higher. The populations showed high variability, with significant interactions with crop location in bioactive compounds, antioxidant activity and Ca, Cu, Na, Mn and S contents.
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Effect of crop location and genotype on phenolic
compounds, mineral contents, and antioxidant activity in
yellow maize landraces
Cecilia Vázquez-Rodríguez1, Raquel Martínez-Martínez2, Araceli Minerva Vera-Guzmán2, José Luis
Chávez-Servia2* and Homar Rene Gill-Langarica1
1Laboratorio de Biotecnología Vegetal, Centro de Biotecnología Genómica-Instituto Politécnico
Nacional. Blvd. Del Maestro s/n esq. Elías Piña, Col. Narciso Mendoza. CP 88710, Reynosa,
Tamaulipas, México. 2CIIDIR-Oaxaca, Instituto Politécnico Nacional, Hornos 1003, Col. Noche
Buena, 71230, Santa Cruz Xoxocotlán, Oaxaca, México.
*Corresponding author: jchavezs@ipn.mx.
Abstract
The Mesoamerican region is center of origin, domestication, and diversification of maize. In this
ecogeographic context, the objective was to evaluate the variation in the phenolic compounds,
antioxidant activity and concentration of minerals in the grain of a population collection of yellow maize
landraces from southeastern Mexico. During 2016, samples of landraces of yellow maize were collected
and integrated into 32 populations and experimental varieties, which were planted in two locations in
Oaxaca, Mexico, under a random block design. At harvest, a sample of grain was taken, which was
grounded to evaluate the polyphenolic compound contents and antioxidant activity by UV–visible
spectrophotometry, and macro- and microelement contents were determined using inductively coupled
plasma–optical emission spectrometry. The effect of crop location was significantly greater than the
effects of populations and location-population interaction on polyphenol contents and concentration of
Ca, P, Mg, K, Na, S, Cu, Fe, Mn and Zn. In the Amatengo locality, a higher macroelement contents were
recorded, and in the second locality, the concentration of microelements, polyphenols, and flavonoids
contents were higher. The populations showed high variability, with significant interactions with crop
location in bioactive compounds, antioxidant activity and Ca, Cu, Na, Mn and S contents.
Keywords: Bioactive compounds, spectrophotometry, optical emission spectrometry (OES),
interactions genotype-environment, communitarian food systems.
1. Introduction
Maize (Zea mays L.) is one of the most important crops in the world, and its grain provides
carbohydrates, protein, lipids, vitamins, fiber, minerals, and a high diversity of bioactive
compounds with high antioxidant activity. Pigmented grains are considered functional foods.
However, genetic factors inherent to grain and environmental and genetic-environmental
interactions affect the variation in quantity and quality of its nutritional-nutraceutical
constituents (Palacios-Rojas et al., 2020). Pigmented grain maize provides secondary
metabolites of high nutraceutical value, such as carotenoids, anthocyanins and phenolic
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compound complexes (Domínguez-Hernández et al., 2022). Experimentally, the extracts of
products or subproducts of pigmented grains have shown antimutagenic and anticarcinogenic
activity (Loarca-Piña et al., 2019: Herrera-Soto et al., 2020) and have shown potential to
counteract the increase in chronic diseases related to diet (e.g., diabetes, cancer, and
degenerative diseases).
The greatest genetic diversity of the species is concentrated in the centers of the origin and
diversification of maize, and this specie continues to evolve under domestication, commonly
classified phenotypically in native populations, landraces, or races. These landraces and races
are highly heterogeneous and phenotypically share common morpho-agronomic biochemical
characteristics and are adapted to certain geographic regions (Vielle-Calzada and Padilla, 2009;
Newton et al., 2010). The biochemical composition of the grain is the product of selection by
farmers in their cultivation plots and storage places (Hoogendoom et al., 2018) to satisfy their
family nutritional needs and of adaptation to agroecological crop conditions and is a research
hotspot for the landraces of blue, red, yellow, purple and variegated grains as sources of
secondary metabolites, minerals, protein and starch and their interaction with abiotic factors
and crop conditions (Domínguez-Hernández et al., 2022).
Phenolic compounds are biosynthesized in all plants and are subject to different regulatory
mechanisms, both genetic and biotic and abiotic interactions where plants develop (Cheynier
et al., 2013). The main phenolic compounds in maize kernels are simple phenols and
polyphenols, phenolic acids, flavonoids, coumarins, stilbenes, carotenes, anthocyanins, lignans
and lignins, tocopherols and others, and their concentrations vary among populations,
landraces, races and varieties. Their composition is affected both by crop agroecology and
during postharvest processing (Salinas-Moreno et al., 2017; Gálvez-Ranilla, 2020). Yellow
grain maize, with a high content of phenolic compounds, including carotenoids and
anthocyanins, has been associated with greater antioxidant activity and nutritional-
nutraceutical potential in the prevention of diseases associated with food (Žilić et al., 2012;
Bae et al., 2021).
Feil et al. (2005) indicated that the mineral composition of corn grains is affected by ecological-
environmental factors such as pre-anthesis drought and the rate of assimilation of nitrogen
added through fertilization. In this regard, Seebauer et al. (2010) indicated that grain
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composition is a product of the source-demand relationships after anthesis and that during grain
maturation, the phenolic compound content, starch composition and antioxidant activity are
affected (Borrás et al., 2002; Xu et al., 2010; Martínez et al., 2019). In addition to
environmental effects, a complex of genes and genetic-environmental interactions also regulate
phenolic compound biosynthesis and mineral concentration (Chakraborti et al., 2011; Zhang et
al., 2020). The proposed objective of this study was to evaluate the variation in total polyphenol
and flavonoid content, antioxidant activity and mineral concentration in the grain of a
population collection of yellow maize landraces from southeastern Mexico.
2. Materials and Methods
2.1 Sampling of yellow maize landraces and crop locations
During the first months of 2016, maize with yellow grain was collected from farmers in
Oaxaca, Mexico (16° 30 '37' 'at 17° 59' 59 '' W latitude, 95° 58 '30' 'at 98°. 19´69´´ N longitude;
from 700 to 2087 masl), generating a collection of 30 population samples plus two
experimental varieties as controls: YTB (yellow grain) and BSBA-4032 (blue grain). The
collection was planted in San Agustín Amatengo and Santa María Coyotepec, Oaxaca, under
a random block design; both locations have a semidry to semiwarm climate, an average
temperature of 20 °C, average rainfall of 526.5 to 693.8 mm, a soil pH of 7.8. to 8.3 and
excellent organic matter availability. San Agustín is located at 1361 masl and Santa María at
1518 masl. Fertilization (120N-100P-60K) and management were constant for both evaluation
sites, and both sites had full exposure to rainy conditions (rainfall).
2.2 Sample preparation and evaluation of total polyphenols, flavonoids, and antioxidant
activity
Sample preparation. At harvest, a random sample of ten healthy ears per maize population was
taken at each experimental location. The ears sampled were manually threshed to generate a
sample of approximately 600 g. Later, a subsample of 100 g grain per population was ground
and crushed (Apex Construction®, LTD and Krups®, Mexico), and the final flour was sieved
through a 500-μm mesh and stored in amber vials at -20 °C until analysis. A sample of flour
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(3 g) was extracted with 80% methanol, and the total polyphenol and flavonoid contents and
antioxidant activity were determined.
Total polyphenols. The total polyphenol contents were determined using the method described
by Singleton and Rossi (1965); deionized water and Folin-Ciocalteu reagent were added to 400
μL of the diluted extract and left to rest for 5 minutes. Subsequently, 7% Na2CO3 was added,
and the sample was incubated for 1 h at room temperature (23 ± 3 °C). Absorbance readings
were conducted in triplicate in a spectrophotometer (Shimadzu UV-1800, Kyoto, Japan) using
distilled water as the blank. The total polyphenol content was estimated as milligrams of gallic
acid equivalents per 100 g in dry weight (mg GAE 100 g-1 dw) using a gallic acid calibration
curve with concentrations ranging from 0.02 to 0.125 mg mL-1.
Flavonoid content. The flavonoid content was determined using the method described by
Zhishen et al. (1999). First, 75 μL of NaNO2 was added to 400 μL of the methanolic extract
and left to rest for 5 minutes; then, AlCl3 ● 6H2O at 10% plus 1 M NaOH and deionized water
were added. The absorbance was read in triplicate at 510 nm. The flavonoid concentrations
were calculated as milligrams of catechin equivalents per gram of dry sample (mg CE g-1 dw)
using a (+)(-)catechin calibration curve with concentrations ranging from 0.0122 to 0.122 mg
mL-1.
Determination of antioxidant activity by DPPH and FRAP. Antioxidant activity by was
analyzed using the DPPH (2,2-diephenyl-1-picrylhydrazyl) method described by Brand-
Williams et al. (1995). DPPH radical was added to 100 μL of the extract. The solution was
vortexed and allowed to rest for 30 minutes in darkness. Subsequently, readings were
performed at 517 nm using a spectrophotometer and 80% methanol as a reference. Antioxidant
activity was recorded using a Trolox calibration curve (6-hydroxy-2,5,7,8-
tetramethylchroman-2-carboxylic acid) with concentrations ranging from 0.13 to 0.79 μmol
mL-1 and expressed in μmol TE g-1 dw. Antioxidant activity was determined using the FRAP
method described by Benzie and Strain (1996). A total of 3 mL of FRAP reagent (sodium
acetate buffer pH 3.6, 10 mM TPTZ, and 10 mM FeCl3.6H2O) was added to 100 μL of the
extract. This solution was incubated for 30 minutes at 37 °C, and its absorbance was recorded
at 593 nm in a spectrophotometer. The quantification of antioxidant activity was performed
using a Trolox calibration curve with concentrations ranging from 100 to 1000 μmol L-1, and
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the results were expressed as μmol equivalent of Trolox per gram of dry weight (μmol TE g-1
dw).
2.3 Determination of mineral contents
Two grams of corn flour was dried in an oven at 105 °C (Barnstead/Thermolyne Oven series
9000, USA) (AACC 44-15). Then, ash was obtained using a muffle furnace at 570 °C
(Barnstead/Thermolyne. 1400, USA) (AACC 08-01.01), (AACC 1976). A total of 4 mL of
HCl (JT Baker®) was added to the ash, which was further dissolved with 50 mL of deionized
water. Finally, the solution was filtered and stored under refrigeration until analysis. The
quantification of micro- and macronutrients (Fe, Zn, Mn, P, Ca, Mg, K, Na and S) was
performed by inductively coupled plasmaoptical emission spectrometry (ICPOES Thermo
Scientific iCAP 6500 DUO, United Kingdom) using the methodology proposed by Martínez-
Martínez et al. (2019). The quantification was based on multielement standards (High Purity®
Standards, USA). All tests were performed in triplicate, and the results were expressed in mg
of the element 100 g-1 dry weight (mg 100 g-1 dw).
2.4 Statistical analysis
A database was compiled to evaluate the differences among populations, crop locations and
the location-population interaction (genotype-environment) using analysis of combined
variance and a linear model with a randomized complete block design for which blocks, or
repetitions were nested in locations. In addition, multiple comparisons of means were
performed by Tukey's test (p 0.05), and only significant comparisons of the location-
population interaction were visualized in scatter plots (SAS Institute, 2002).
3. Results and Discussion
In the analysis of variance, significant differences (p 0.05, 0.01) were identified between
evaluation locations (environments), between populations (genotypes) and in the location-
population interaction (genotype-environment) for all the variables evaluated, with the
exceptions of antioxidant activity, as evaluated by the FRAP method, between locations, Mg
content between populations and P, Mg, K, Fe and Zn concentrations for the locality-population
interaction. The variance or mean square of polyphenols was higher in localities than in
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populations and in the locality-population interaction, a pattern that was repeated for
antioxidant activity, as evaluated by DPPH, and mineral content, indicating that the effect of
the environment is significant for these compounds. For flavonoids, the variance was greatest
for the locality-population interaction, followed by the variance among populations and finally
between localities (Table 1).
Table 1. Significance of square means in the analysis of variance in the total polyphenol, flavonoid and
mineral contents and antioxidant activity in grains of yellow maize landraces.
Evaluated
compounds
Sources of variation
CV
(%)
Locations
(L)
Populations
(P)
L x P
Rep./L
Error
Total polyphenols
2084.90**
709.40**
373.70**
316.1**
26.50
6.6
Flavonoids
9.76**
15.04**
16.58**
1.36*
0.44
19.2
Antiox. act. by
DPPH
13.06**
3.51**
2.00**
0.21ns
0.11
8.8
Antiox. act. by
FRAP
<0.01ns
1.37**
0.95**
0.61**
0.10
8.2
Ca
54.92**
1.51**
1.35**
0.69ns
0.59
25.3
P
697969**
3789*
2874ns
4914*
2225.7
13.6
Mg
26027**
360ns
316ns
528ns
252.2
13.3
K
307623**
5111**
2225ns
1419ns
2181.9
12.9
Na
25.35**
0.12**
0.29**
0.10ns
0.068
7.2
S
9.45**
0.62**
0.51**
0.16ns
0.11
15.5
Cu
0.066**
0.01**
0.008**
<0.01ns
<0.01
23.8
Fe
1.737**
0.071**
0.044ns
0.081*
0.035
10.5
Mn
0.345**
0.016**
0.010*
0.013*
<0.01
14.6
Zn
18.12**
0.59*
0.44ns
0.73ns
0.38
18.8
nsNot significant (p > 0.05) * Significant at p ≤ 0.05, ** Significant at p ≤ 0.01; CV = coefficient of variation.
The landraces of yellow maize were strongly influenced in grain composition by crop location,
but the effect of the environment was different based on the type of compound. For total
polyphenols, flavonoids and microelements such as Cu, Mn and Fe, higher values were
recorded in San Agustín Amatengo, but in Santa María Coyotepec, greater antioxidant activity,
as determined by the DPPH method, and macronutrient contents, such as Ca, P, Mg. K and Na,
were observed. It means that crop locations have significant effects on grain composition, as
supported by Nankar et al. (2016), who studied amino acid, protein, anthocyanins, starch and
ash content. Menkir (2008) and Gu et al. (2015) also reported that mineral content is affected
not only by the location but also by the year of cultivation; that is, the composition of maize
grain changes or is influenced by the location and year of cultivation, two conditions that refer
to the effect of the environment on composition.
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Table 2. Average total polyphenol, flavonoid and mineral contents and antioxidant activity of
yellow maize landraces cultivated in two locations of Oaxaca, Mexico.
Compound evaluated
Crop locations in Oaxaca, Mexico
San Agustín
Amatengo
Santa Maria Coyotepec
Total polyphenols (mg GAE 100 g-1)
79.1 ± 7.80 a1
75.6 ± 8.85 b
Flavonoids (mg EC g-1)
0.036 ± 0.01 a
0.033 ± 0.01 b
Antioxidant act. by DPPH (μmol TE g-1)
3.6 ± 0.60 b
3.9 ± 0.54 a
Antioxidant act. by FRAP (μmol TE g-1)
3.9 ± 0.39 a
3.9 ± 0.50 a
Mineral content (mg 100 g-1)
Ca
7.5 ± 4.6 b
13.0 ± 4.1 a
P
295.2 ± 51.5 b
400.2 ± 49.7 a
Mg
108.8 ± 17.6 b
129.0 ± 15.8 a
K
327.8 ± 47.3 b
397.3 ± 53.3 a
Na
1.04 ± 1.5 b
5.77 ± 3.1 a
S
3.79 ± 2.6 a
2.01 ± 1.9 b
Cu
0.24 ± 0.1 a
0.20 ± 0.1 b
Mn
0.56 ± 0.1 a
0.48 ± 0.1 b
Fe
1.54 ± 0.9 a
0.93 ± 0.8 b
Zn
2.99 ± 0.5 b
3.52 ± 0.8 a
1In the rows, means with the same letter are not significantly different (Tukey's test, p ≤ 0.05).
The variation in total polyphenol content among populations collected from yellow corn ranged
from 68.2 to 88.9 mg GAE 100 g-1 (Table 3), values that are within the range reported by Mora-
Rochin et al. (2010) and Loarca-Piña et al. (2019) for white, yellow, red and blue corn from
Mexico and within the values reported by Syedd-León et al. (2020) for white, yellow and red
grain from Costa Rica; although the upper range in the reference reports is greater than 140 mg
GAE 100 g-1, in all cases, the values were lower than the values reported by Bae et al. (2021)
and suggest differences in laboratory methodology, i.e., not only in the evaluated genotypes.
The references also suggest that there are no differential patterns in total polyphenols between
populations with similar or different grain color because there are populations with high and
low total polyphenol content between and within each color group. Loarca-Piña et al. (2019)
estimated a variation in flavonoid content of <0.001 to 0.12 mg EC g-1 in blue and red grain
from Querétaro, Mexico, and in this study, the estimated variation ranged from 0.016 to 0.053
mg EC g-1 (Table 3). However, both estimates differ from the higher values recorded by Bae
et al. (2021), i.e., 0.074 to 0.591 mg EC g-1 in yellow maize from Asia, and in a collection of
pigmented maize (0.248 to 0.337 mg EC g-1) evaluated by Žilić et al. (2012). That is, in this
work, the variation observed between landraces of Oaxaca, Mexico, was lower than that
estimated by other authors despite possible differences in specific laboratory methods. In this
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sense, Zhang et al. (2020) indicated that phenolic compound content decreases as grain
maturity advances or as grains lose moisture.
Table 3. Variation in total polyphenol, flavonoid, and mineral content and antioxidant activity
in the kernel of yellow maize landraces.
Pop.
ID
Poly.1
Flav.2
Antiox. Activ.3
Macroelements (mg 100 g-1)
Microelements (mg 100 g-1)
DPPH
FRAP
Ca
P
Mg
K
Na
S
Cu
Fe
Mn
Zn
Y05
76.3
0.020
3.73
3.93
9.6
325.3
110.7
332.2
3.93
1.78
0.24
0.97
0.46
2.89
Y06
69.9
0.032
3.80
3.83
12.2
369.8
127.6
354.3
3.69
1.09
0.24
1.28
0.54
3.28
Y07
71.2
0.016
3.68
3.66
12.7
324.0
108.0
320.1
5.30
1.68
0.20
0.86
0.46
2.77
Y08
69.5
0.027
3.98
3.91
13.4
370.1
126.2
354.7
2.82
1.65
0.23
1.33
0.57
3.35
Y10
71.6
0.036
3.59
3.70
10.0
365.0
124.7
369.6
2.88
2.09
0.22
1.40
0.58
3.29
Y21
74.4
0.043
3.31
3.68
13.7
373.8
130.9
364.3
4.15
3.02
0.23
1.94
0.60
3.39
Y22
72.8
0.025
3.84
3.84
9.1
354.7
117.5
352.7
3.31
1.55
0.25
1.72
0.59
3.17
Y23
78.8
0.033
3.81
3.95
10.4
332.2
111.8
369.5
4.02
4.29
0.23
2.12
0.49
3.60
Y24
78.1
0.044
4.20
4.16
7.2
327.5
112.4
341.8
2.63
1.85
0.19
1.91
0.49
3.31
Y26
82.0
0.034
4.51
4.10
8.2
354.6
119.6
372.1
2.87
1.77
0.24
1.20
0.53
3.34
Y27
77.0
0.031
4.20
3.67
9.5
291.7
100.0
335.7
2.75
4.49
0.24
0.83
0.48
2.76
Y29
74.4
0.029
3.91
3.78
10.8
344.8
119.0
353.6
3.25
2.35
0.23
1.05
0.57
3.68
Y30
77.7
0.033
3.97
3.73
13.0
340.2
116.7
373.3
4.30
4.19
0.22
0.98
0.51
3.28
Y35
84.0
0.032
3.57
4.04
12.1
352.4
117.9
410.9
4.46
4.28
0.23
1.08
0.50
3.06
Y37
81.1
0.039
3.65
4.00
10.3
320.3
110.6
343.6
3.63
2.10
0.20
0.99
0.46
3.08
Y40
78.9
0.031
3.17
3.69
10.0
358.4
120.6
397.3
6.21
5.67
0.32
1.66
0.55
3.83
Y41
81.5
0.036
3.23
3.97
5.6
337.0
120.2
386.7
3.15
5.46
0.26
1.71
0.52
3.37
Y42
73.9
0.041
3.27
3.75
14.5
362.2
124.1
373.8
3.78
1.88
0.19
1.20
0.55
3.40
Y45
75.8
0.035
3.17
3.52
11.4
360.7
123.7
379.7
3.02
1.05
0.20
0.70
0.53
3.29
Y49
74.2
0.046
3.33
3.81
8.9
363.6
122.9
365.2
3.52
1.46
0.23
1.20
0.51
3.11
Y50
72.3
0.045
3.35
3.64
12.7
323.5
113.3
336.0
4.20
2.15
0.23
0.95
0.52
3.07
Y51
70.0
0.028
3.44
3.82
8.0
336.6
114.5
334.2
2.30
1.71
0.22
1.14
0.52
3.06
Y52
68.2
0.032
3.51
3.68
10.7
362.2
121.6
361.6
3.04
2.25
0.21
1.14
0.55
3.33
Y53
81.4
0.045
3.90
4.21
7.8
338.1
117.0
375.9
3.74
5.48
0.23
0.76
0.45
3.09
Y55
73.5
0.041
3.39
4.01
9.1
338.2
120.7
327.2
4.20
2.40
0.21
1.00
0.49
2.79
Y58
84.4
0.053
4.03
4.31
10.4
387.2
127.6
425.6
4.01
3.92
0.31
1.81
0.59
3.45
Y59
85.8
0.032
4.10
4.20
11.1
363.1
126.3
391.3
2.92
3.89
0.32
0.82
0.57
3.57
Y60
79.5
0.029
4.02
4.16
8.8
356.8
119.2
366.6
1.84
2.58
0.10
0.76
0.57
2.90
Y62
86.7
0.032
4.44
4.20
9.4
391.5
129.7
401.5
1.42
2.35
0.16
0.96
0.52
3.32
Y70
80.0
0.035
3.78
3.92
9.0
340.7
116.5
343.1
2.05
4.04
0.19
1.26
0.54
3.54
YTB
82.2
0.033
3.92
4.35
7.8
314.0
117.2
332.8
2.43
4.49
0.22
1.45
0.43
3.15
BSB
88.9
0.043
4.58
4.51
10.1
341.7
117.9
359.5
2.72
4.17
0.16
1.37
0.48
3.68
DMS1
5.68
0.007
0.36
0.36
7.5
91.26
ns
90.35
3.87
3.07
0.10
0.36
0.15
1.19
1 Total polyphenols (mg GAE 100 g-1); 2 Flavonoids (mg EC g-1); 3 μmol ET g-1, difference minimal significant
(Tukey's test p ≤ 0.05); ns = not significantly different.
Regarding antioxidant activity, as determined by the DPPH and FRAP methods, similar
interpopulation variation was observed, from 3.17 to 4.58 μmol ET g-1 and from 3.52 to 4.51
μmol ET g-1, respectively (Table 3), activity levels that were significantly different from those
recorded by Bae et al. (2021) using the DPPH method (104.1 to 31.3.4 μmol ET g-1) and by
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Zhang et al. (2020) using the FRAP method (12.5 to 15.0 μmol ET g-1). However, the
differences in the laboratory methods and antioxidant activity values are indicators of the
reducing capacity of free radicals in the sample under study due to the amount of bioactive
compounds with these reducing functions. In addition, Zhang et al. (2020) noted that this
reducing capacity does not necessarily decrease as the grain matures.
In terms of mineral macroelements, the variation between populations of yellow corn ranged
from 5.6 to 14.5 mg 100 g-1, from 291.7 to 391.5 mg 100 g-1, from 100 to 130.9 mg 100 g-1,
from 327.2 to 425.6 mg 100 g-1, from 1.42 to 6.21 mg 100 g-1 and from 1.05 to 5.67 mg 100 g-
1 for Ca, P, Mg. K, Na and S, respectively (Table 3). This variation is significantly higher than
the reference values reported by Gu et al. (2015) and by Feil et al. (2005), except for Ca for the
latter case; in all cases, the same PCI-OES methodology was used. However, the results are
consistent with the values reported by Menkir et al. (2008), who used the same methodology
in advanced lines of tropical maize. Together, these findings indicate that comparisons between
results for maize with different genotypes and results obtained using different laboratory
methods are challenging; however, such results contribute with successive approximations to
evaluate the genetic and phenotypic diversity of landraces, advanced lines, or cultivated
varieties of maize. which may be feasible to apply some genotypic selection methodology.
Regarding mineral microelements, Cu, Fe, Mn and Zn contents varied from 0.1 to 0.32 mg 100
g-1, from 0.7 to 2.12 mg 100 g-1, from 0.43 to 0.60 mg 100 g-1 and from 2.76 to 3.83 mg 100 g-
1, respectively (Table 3). Zn and Fe play essential roles against anemia in vulnerable
populations. The values recorded here for Zn were slightly higher than those recorded among
the varieties evaluated (2.34 to 2.65 mg 100 g-1) by Feil et al. (2005) and those estimated (1.64
to 2.46 mg 100 g-1) by Oikeh et al. (2003) but are consistent with the estimated values reported
by Demeke (2018) and Menkir (2008) and indicate a certain genetic potential in the evaluated
germplasm. However, when the Fe content was evaluated, the pattern was similar and, in some
cases, slightly lower that that reported in the studies referred to.
The interaction between populations and evaluation locations was not significant for all the
evaluated composition parameters. For example, the Zn, Fe, K, Mg and P interaction was not
significant, indicating independence between the effect of localities and germplasm or the
native varieties evaluated (Table 1). The polyphenol and flavonoid contents and antioxidant
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activity were affected by the location-population interaction, and at least four response patterns
were differentiated as a function of the average by locality (Figure 1), among which three are
of special interest to farmers and consumers. If interested in the response in both environments,
the quadrant of interest is the upper right quadrant in each scatter plot (Figure 1), but if the
interest is the response in one of the environments, the upper left or lower right quadrant would
be of greatest interest. For example, the most stable populations with regard to polyphenols
were Y62, Y59, Y58, Y37, Y35, Y41 and Y23 of yellow corn and BSBA of blue corn, those
with regard to flavonoids were Y58, Y53 and Y42, and those with regard to antioxidant
activity, as determined by the DPPH and FRAP methods, were Y60, Y59, Y26 and Y24. These
findings indicate that it is possible to select stable materials, based on the bioactive compound
content and antioxidant activity, among the evaluated populations of yellow corn.
Figure 1. Scatter plots for crop locations and populations with regard to total polyphenols,
flavonoids, and antioxidant activity in yellow maize landraces.
Y05
Y06 Y07
Y08
Y10
Y21
Y22
Y23
Y24 Y26
Y27
Y29
Y30
Y35
Y37
Y40
Y41
Y42
Y49
Y50
Y51
Y52
Y53
Y55
Y58 Y59
Y60
Y62
Y70
BSBA
YTB
65
70
75
80
85
90
95
65 70 75 80 85 90
Polyphenols -S. M. Coyotepec (mg GAE 100 g-1)
Total polyphenols - San Agustin Amatengo (mg GAE 100 g-1)
Average = 75.7
Average = 79.1
Y05
Y06
Y07 Y08 Y10
Y21
Y22
Y23
Y24
Y26
Y27
Y29
Y30
Y35
Y37
Y40
Y41 Y42
Y45
Y49
Y50
Y51
Y52
Y53
Y55
Y58
Y59
Y60
Y62
Y70
BSBA
YTB
0.003
0.013
0.023
0.033
0.043
0.053
0.063
0.02 0.03 0.04 0.05 0.06
Flavonoids - S.M. Coyotepec (mg CE 100 g-1)
Flavonoids - San Agustin Amatengo (mg CE 100 g-1)
Average = 0.04
Average = 0.03
Y05 Y06
Y07
Y08
Y10
Y21
Y22
Y23
Y24 Y26
Y27
Y29
Y30
Y35 Y37
Y40
Y41
Y42
Y45
Y49
Y50
Y51
Y52
Y53
Y55
Y58
Y59
Y60
Y62
Y70
BSBA
YTB
3.1
3.6
4.1
4.6
2.9 3.4 3.9 4.4 4.9
Ant. act. DPPH -S.M. Coyotepec (µmol TE g-1)
Antiox. act. DPPH - San A. Amatengo (μmol TE g-1)
Average = 3.6
Average = 3.9
Y05
Y06
Y07
Y08
Y10
Y21
Y22 Y23
Y24
Y26
Y27
Y29
Y30
Y35
Y37
Y40
Y41
Y42
Y45
Y49
Y50
Y51
Y52
Y53
Y55
Y58
Y59
Y60
Y62
Y70
BSBA
YTB
3.2
3.4
3.6
3.8
4.0
4.2
4.4
4.6
4.8
3.4 3.6 3.8 4.0 4.2 4.4 4.6
Ant. act. FRAP -S.M. Coyotepec (µmol TE g-1)
Antiox. act. FRAP - San A. Amatengo (µmol TE g-1)
Average = 3.9
Average = 3.9
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Menkir (2008), Chakraborti et al. (2011) and Gu et al. (2015) reported that maize genotypes
interact significantly with the environment or agroecological conditions and years of
cultivation with respect to the concentration of mineral microelements and macroelements in
grain, either inbred lines or genotypes with a heterogeneous genetic structure. In this study,
there was a significant interaction effect between Ca, Na, S, Cu and Mn content and the
environment for the populations studied (Table 1, Figure 2). For these mineral elements,
populations in the upper right quadrant of each scatter plot (Figure 2) contain consistently high
values for more than one mineral element; these populations include Y59, Y58, Y52, Y42,
Y40, Y30, Y23, Y22 and Y21. For example, for Ca, Cu, Na, Mn and S, the most established
populations had values greater than 7.5, 0.2, 1.0, 0.48 and 2.0 mg 100 g-1, respectively; these
values are similar to those estimated by Menkir (2008) and Gu et al. (2015). Together, Y58,
Y49, Y41, Y37, Y30 and Y29 stood out as the populations with the highest Ca, Cu, Na, Mn
and S contents.
Borrás et al. (2002), Feil et al. (2005), Xu et al. (2010) and Zhang et al. (2020) reported that
the composition of maize grains depends on source-demand relationships during post-
flowering and during grain maturation, the agroecological conditions of cultivation (e.g.,
drought or soil fertility) and/or mineral fertilizers or management practices. That is, the genetic
conditions of a population or variety reflect certain gene expression profiles to generate basic
composition levels, but the effects of the cultivation environment and genetic-environmental
interactions are significant. In this study, the genetic-population effects or population variations
(genotypic variance, Table 1) were lower than the environmental effects of the location of
cultivation for most of the parameters evaluated, but the results indicate the possibility of
selecting outstanding populations or directly using these populations for feeding the families
of farmers who preserve this diversity.
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Figure 2. Scatter plots for crop locations and populations with regard to Ca, Na, S, Cu,
and Mn in yellow maize landraces.
Y05
Y06
Y07
Y08
Y10
Y21
Y22
Y23
Y24
Y26 Y27
Y29
Y30
Y35
Y37
Y40
Y41
Y42
Y45
Y49
Y50
Y51
Y52
Y53 Y55
Y58
Y59
Y60
Y62
Y70
BSBA
YTB
4
6
7
9
10
12
13
15
16
18
1.0 2.5 4.0 5.5 7.0 8.5 10.0 11.5 13.0 14.5 16.0
Ca - Santa Maria Coyotepec (mg 100 g-1)
Ca - San Agustin Amatengo (mg 100 g-1)
Average = 7.5
Average = 13.0
Y05
Y06
Y07 Y08
Y10
Y21 Y22
Y23
Y24
Y26
Y27
Y29
Y30 Y35
Y37
Y40
Y41
Y42
Y45
Y49
Y50
Y51
Y52 Y53
Y55
Y58
Y59
Y60
Y62
Y70
BSBA YTB
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.10 0.15 0.20 0.25 0.30 0.35
Cu - Santa Maria Coyotepec (mg 100 g-1)
Cu - San Agustin Amatengo (mg 100 g-1)
Average = 0.24
Average = 0.21
Y05
Y06
Y07
Y08
Y10 Y21
Y22 Y23
Y24
Y26
Y27 Y29
Y30
Y35
Y37
Y40
Y41
Y42
Y45 Y49
Y50
Y51
Y52
Y53 Y55
Y58
Y59
Y60
Y62 Y70
BSBA
YTB
1.5
2.5
3.5
4.5
5.5
6.5
7.5
8.5
9.5
10.5
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5
Na - Santa Maria Coyotepec (mg 100 g-1)
Na - San Agustin Amatengo (mg 100 g-1)
Average = 1.0
Average = 5.7
Y05
Y06
Y07
Y08
Y10
Y21
Y22
Y23
Y24
Y26
Y27 Y29
Y30
Y35
Y37
Y40
Y41
Y42
Y45
Y49 Y50
Y51
Y52
Y53 Y55
Y58
Y59
Y60
Y62 Y70
BSBA
YTB
0.35
0.40
0.45
0.50
0.55
0.60
0.40 0.45 0.50 0.55 0.60 0.65
Mn - Santa M. Coyotepec (mg 100 g-1)
Mn - San Agustin Amatengo (mg 100 g-1)
Average = 0.56
Average = 0.48
Y05
Y06
Y07
Y08
Y10 Y21
Y22 Y23
Y24
Y26
Y27
Y29
Y30
Y35
Y37
Y40
Y41
Y42
Y45 Y49
Y50
Y51
Y52
Y53
Y55
Y58
Y59
Y60
Y62
Y70
BSBA
YTB
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0
S - Santa Maria Coyotepec (mg 100 g-1)
S - San Agustin Amatengo (mg 100 g-1)
Average = 3.8
Average = 2.0
Y05
Y06
Y07
Y08
Y10
Y21
Y22
Y23 Y24 Y26
Y27
Y29
Y30
Y35
Y37
Y40
Y41
Y42
Y45
Y49
Y50
Y51
Y52
Y53
Y55
Y58
Y59 Y60 Y62
Y70
BSBA
YTB
7
9
11
13
15
17
19
21
23
25
27
29
31
4 6 8 10 12 14 16 18 20 22 24
Ca + Na + S + Cu + Mn - S. M. Coyotepec (mg 100 g-1)
Ca + Na + S + Cu + Mn - S. A. Amatengo (mg 100 g-1)
Average = 13.1
Average = 21.4
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4. Conclusions
In terms of grain composition, the evaluated population sample of yellow maize landraces in
two agroecological farming locations showed different response patterns. First, the
environmental effect (location) was significantly greater than the effects of population
(genotypic) and the location-population interaction on the total polyphenol, Ca, P, Mg, K, Na,
S, Cu, Fe, Mn and Zn content. For flavonoid content and antioxidant activity, as evaluated by
FRAP, the effect of location and location-population interaction caused greater variation in the
populations studied. In this work, the populations evaluated showed high variation in grain
composition, and the average or combined effect was that, at one location, the macroelement
content was higher and, at the other location, the microelement concentration was higher,
combined with a higher polyphenol and flavonoid content. The was a significant interaction
between cultivation location and bioactive compound content, antioxidant activity and Ca, Cu,
Na, Mn, and S content in yellow corn conserved in situ by the indigenous communities of
Oaxaca, Mexico.
Acknowledgment
The authors are grateful for the financial support provide by Instituto Politécnico Nacional
(Projects nos. 20220980 and 20220820).
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In order to identify pigmented corn with nutraceutical potential, the secondary metabolite content, the antioxidant capacity and antimutagenic activity of red, and blue corn were analyzed. The ranges of total phenolic, flavonoid and anthocyanin contents of the corn samples were from 69.4 to 212.8 mg gallic ac. equiv./100 g DW, 0.07 to 12.19 mg (+) catechin eq./100 g DW and 3.89 to 34.17 mg cyanidin-3-O-glucoside eq./100 g DW, respectively. The phenolic extracts demonstrated the highest antioxidant capacity evaluated by the ABTS assay displaying values from 2.06 to 7.34 mmol Trolox/100 g DW. None of the extracts was toxic to the tested bacteria strains TA98 and TA100. For TA98 tester strain, percentage inhibition values against AFB1 mutagenicity from 61 to 93, and 38 to 75 for flavonoid and anthocyanin extracts were obtained. The total phenol and anthocyanin contents correlate with the observed antioxidant capacity. The most biological active corn samples were the blue color while the least actives were the red ones. The results show that the studied blue corn samples are good sources of antioxidant and antimutagenic compounds, which could use to develop products that contribute to human health.
Article
Maize (Zea mays L.) endosperms with high amylose proportion are harder and denser than endosperms with low amylose. Environmental conditions could affect amylose/starch ratio. The purpose of this work was to prove the effect of incident solar radiation, temperature, refertilization with nitrogen (N) and sulfur (S) and source/sink ratio during grain filling on maize amylose/starch ratio. The associations among changes in amylose/starch ratio and other grain components were also analyzed. We evaluated shading treatments in two periods during grain filling period. Fertilization treatments were evaluated by adding extra N and S per hectare in V15. Heating treatments were evaluated by increasing surface grain temperature during the grain filling period. Source/sink ratio was modified via defoliation and plant thinning. Variations in source/sink ratio or refertilization with N and S did not produce significant changes in starch composition. Increases in minimum temperature during early effective grain filling were related to decreases in starch percentage and to increases in amylose/starch ratio. Thus, future maize starch quality studies need to focus on thermal conditions during grain filling and on the metabolic steps involved. According to these results, management practices that imply a modification in temperature during the grain filling period affect starch composition.
Article
Maize is a food field crop with a highly developed formal seed sector. The study reported here, involving 4 case studies in Malawi, Zambia, the state of Chiapas in Mexico and the state of Bihar in India, indicates that smallholder farmers are increasingly purchasing seed from the formal maize seed system in these different parts of the world. Points of sale vary from seed agent and agro-dealer to the local rural market. Many farmers are growing hybrid varieties, although, in particular, under conditions where higher yields justify seed costs, and with the objective of maize grain sales rather than home consumption, for which traditional varieties continue to be grown. While the findings indicate well-functioning seed value chains in the areas of study, producer surveys and seed value chain analysis also pointed to significant weak links in the formal maize seed systems that need to be improved, such as certification and seed quality control at point of sale, and the availability of financial services to support investments by farmers in quality seed and in seed entrepreneurship. The seed subsidy programs in Malawi and Zambia are likely to have stimulated the use of hybrid seed, but it is questionable whether farmers will continue to purchase hybrid seed if subsidies cease to be available. Although the 4 areas of study are relatively well developed, still a genuine demand for improved open pollinated varieties (IOPVs), local varieties and/or on-farm seed saving was identified. Therefore it should be recognized that even for maize, in addition to the private formal seed value sector based on hybrid varieties, there remains a task for public maize breeding efforts and farmer based maize seed systems for the foreseeable future.