Heliyon xxx (xxxx) e11618
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Heliyon
journal homepage: www.elsevier.com/locate/heliyon
Research article
Characterization of macro and micro-minerals in cassava leaves from
genotypes planted in three different agroecological locations in Nigeria
Emmanuel Oladeji Alamu a, b, *, Alfred Dixon b, Tolu Emma Eyinla b, c, Busie Maziya-Dixon b
a International Institute of Tropical Agriculture, Southern Africa, Research and Administration Hub (SARAH) Campus, PO Box 310142, Chelstone, Lusaka, 10101, Zambia
b International Institute of Tropical Agriculture, PMB 5230, Ibadan, Oyo State, Nigeria
c Department of Human Nutrition and Dietetics, University of Ibadan, Ibadan, Oyo State, Nigeria
A R T I C L E  I N F O A B S T R A C T
Keywords: Diversity in the mineral composition of cassava leaves bred in sub-Saharan Africa has not been fully investigated.
Cassava leaves This study characterized macro and micro-minerals in 400 genotypes of Cassava leaves planted in three different
Minerals agroecological environments in Nigeria. Laboratory analysis of the leaves was done using an Inductively Coupled
Nigeria
Iron Optical Emission Spectrometer. Across all three locations sampled in this study, the iron content ranged from 43
Zinc to 660 mg/kg, zinc from 16 to 440 mg/kg, Manganese 16–61mg/kg, Copper 0.7–14 mg/kg, Aluminum 5.3–630
mg/kg. Among the macro elements, Calcium ranged from 3600 to 17600 mg/kg, Magnesium 1760–6500 mg/kg,
Sodium 0.4–720 mg/kg, Potassium 3100–27000 mg/kg. When the location effect was tested, there was a signifi-
cant difference among the genotypes for all elements. Cluster analysis resulted in five clusters containing 187,
147, 60, 2, and 4 genotypes, respectively. Cluster 2 contained eight varieties (01/0046, 94/0020, 93/0098, 88/
112-7(3X), I00/0017, 91/00417, I00/0017, 88/112-7(3X)) that possessed the highest mineral compositions in
Fe, Al, Ti, Na, K, S, Mn, and B, respectively. Genotypes 93/0681(4X), 92/0430, and 95/0460 in cluster 3 had the
highest concentrations of Mg, Na, and Zn, respectively. The correlation results showed a notable positive rela-
tionship among iron with zinc, copper, aluminum, and titanium (r = 0.33, 0.39, 0.48, and 0.56, respectively),
zinc with nickel, titanium, and sulphur (r = 0.52, 0.3,2 and 0.51, respectively) while calcium negatively corre-
lated with potassium (r = ‒ 0.31), phosphorus (r = ‒0.41). This study provides evidence that genotypic diversity
exists for mineral composition in cassava leaves and, therefore, can be exploited for genetic improvement by
breeders seeking solutions to reduce persistent mineral deficiencies in sub-Saharan Africa.
1. Introduction The roots (an important source of carbohydrate) and leaves (a great
source of proteins and micronutrients) constitute the bulk of the food
Cassava (Manihot esculenta Crantz), which originated from South utilization of the cassava plant (Montagnac et al., 2009), with the roots
America, is one of the primary sources of dietary energy in the sub- playing a more dominant role. In sub-Saharan African countries, the
Saharan African diet, ranking highest with rice, wheat, and maize leaves are consumed as a vegetable, either as a soup eaten with starchy
(Ceballos et al., 2004; FAO, 2022). Africa, especially Nigeria, is the dishes or as cooked green vegetables (Achidi et al., 2005; Latif and
world's highest cultivator of the crop. As of 2020, world cassava pro- Müller, 2015). Being rich in protein, it contributes to protein intake in
duction was about 303 million tons, with Africa contributing about developing countries (Ayele et al., 2021) and has an amino acid profile
60% and Nigeria contributing a third of Africa's production (FAO, similar to some animal-sourced protein foods (Babu and Chatterjee,
2022). Cassava is tolerant of diverse weather conditions and soil types 1999; Popoola et al., 2019). However, its shortcoming has been its com-
(Ceballos et al., 2004) and is grown year-round. After maturity, it can position of anti-nutritional compounds, including phytates, saponins,
be left for a year and harvested when needed, thereby playing a proven oxalates, and especially cyanogenic compounds, which is why they
role in improving food security (Montagnac et al., 2009). have not been extensively incorporated into the food system (Latif. and
The roots and leaves are the two main products that are the nutri- Müller, 2015; Ayele et al., 2021). They are also a known rich source of
tively beneficial parts of a mature cassava plant (Ceballos et al., 2004). minerals and vitamins, with some reports suggesting that they have
GGA, Genetic Gain Assessment; IVS, Inland Valley Hydromorphic site; ICP-OES, Inductively Coupled Optical Emission Spectrometry
* Corresponding author.
E-mail address: oalamu@cgiar.org (E.O. Alamu).
https://doi.org/10.1016/j.heliyon.2022.e11618
Received 31 May 2022; Received in revised form 10 October 2022; Accepted 10 November 2022
2405-8440/© 20XX
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E.O. Alamu et al. Heliyon xxx (xxxx) e11618
substantial potential to reduce deficiencies if consumption is taken to 2.2. Sample preparation
scale (Montagnac et al., 2009; Aregheore, 2012). Minerals are elements
critically needed by the body as regulators of biochemical processes. Mature, succulent leaves from four plants were plucked from their
They are broadly divided into trace and macro elements based on their stalks and washed with de-ionized water. They were then chopped be-
quantitative contribution to dietary and nutrient intake. Microelements fore mixing thoroughly. The chopped leaves were divided into quarters,
include Iron (Fe), Zinc (Zn), Manganese (Mn), Boron (B), Copper (Cu), and adjacent sections were mixed. The leaves were wrapped in muslin
Nickel (Ni), Aluminum (Al), and Titanium (Ti). Macro elements include cloth before being blanched using tepid de-ionized water (60 °C) for 4
Calcium (Ca), Magnesium (Mg), Sodium (Na), Potassium (K), Phospho- min. The leaves were then dried in a convection oven at 40 °C for 48 h
rus (P), and Sulphur (S). Various sources in the literature provide com- using stainless steel trays.
positional information on some genotypes and products of cassava
leaves prepared into food or animal feed (Chávez et al., 2000; Nassar 2.3. Determination of mineral profile
and Marques, 2006; Achidi et al., 2008; Nguyen et al., 2012; Popoola et
al., 2019) but evaluation of a large number of genotypes is not com- The trace and the macro element content were determined using In-
mon. A recent mineral compositional evaluation of large germplasms of ductively Coupled Optical Emission Spectrometry (ICP-OES) as pre-
cassava roots grown in sub-Saharan Africa has been reported (Alamu et sented by Wheal et al. (2011) and replicated in Alamu et al. (2020b),
al., 2020a, 2020b, 2021, 2022). Also, an extensive collection of leaves which involved an acid digestion phase before instrumentation. The di-
was evaluated for genotypic effects on amino acids, carotenoids, and gestion was done at 125 °C for 2 h using 2.0 mL of HNO3 and 0.5 mL of
cyanogenic properties in Latin America (Ospina et al., 2021). However, H2O2 in a 72-position DigiPrep digestion block chamber (SCP Scientific,
this report did not provide compositional data on macro and trace ele- Baie D'Urf e, Quebec, Canada) and made to the 25 ml level with de-
ments contained in genotypes of cassava leaves. Another notable ionized water. Each sample was then run in duplicate. The trace ele-
knowledge gap is the performance of genotypes across different envi- ments identified in the samples investigated were Iron (Fe), Zinc (Zn),
ronments since plants (in this case, cassava) are known to give signifi- Manganese (Mn), Boron (B), Copper (Cu), Nickel (Ni), Aluminum (Al),
cant differential genotypic responses under varying environmental con- and Titanium (Ti). The macro elements were Calcium (Ca), Magnesium
ditions (Ceballos et al., 2004; Maroya et al., 2012). Therefore, this (Mg), Sodium (Na), Potassium (K), Phosphorus (P), and Sulphur (S).
study characterized 14 micro- and macro-elements of cassava leaves
from 400 genotypes planted in three different agroecological locations 2.4. Statistical analysis
in Nigeria to provide information for plant breeding purposes and exist-
ing food compositional databases within sub-Saharan Africa and world- The data generated in this study were subjected to descriptive and
wide. inferential statistical analysis using the Statistical Analysis System Soft-
ware Cary, NC, USA (SAS, 2012). Means were separated using Fisher's
2. Materials and methods least significance difference test. Principal component analysis (PCA)
and hierarchical cluster analysis (HCA) were also utilized.
2.1. Background information on fresh cassava leaves
3. Results and discussion
Four hundred (400) genotypes of cassava leaves (Supplementary file
1) were collected in a genetic gain roots and leaves trial in readiness for 3.1. Mineral composition of GGA cassava leaves
on-farm trials before official release. They were collected from three lo-
cations—Ibadan (forest-savanna transition) and Mokwa (southern Table 1 represents the descriptive statistics of trace and macro min-
Guinea savanna), all maintained by the International Institute of Tropi- erals across all three sampled locations. Across all locations, the iron
cal Agriculture, Nigeria. Mature stem cuttings of the genotypes, includ- content ranged from 43 to 660 mg/kg (mean 105.1 ± 37.1 mg/kg),
ing checks, were planted on plots where ridges had been made. They zinc from 16 to 440 mg/kg (mean 54.3 ± 26 mg/kg), Manganese
were planted during the rainy season in mid-2005 in an Augmented 16–610 mg/kg (mean 187.2 ± 89.6 mg/kg), Boron 5.7–35 mg/kg
Completely Randomized Design with three checks (TME 1, 91/02324, (mean 19.5 ± 3.5 mg/kg), Copper 0.7–14 mg/kg (mean 8 ± 1.6 mg/
and 30572) repeated randomly in each sub-block using a spacing of 1 m kg), Nickel 0.8–43 mg/kg (mean 4.9 ± 3.7 mg/kg), Aluminum
× 0.5 m (5 plants per plot). Before planting, the plots had been 5.3–630 mg/kg (mean 42.4 ± 36.1 mg/kg), Titanium 0.1–56 mg/kg
ploughed and harrowed before being ridged. Ibadan growing locations (mean 3 ± 4.5 mg/kg). Among the macro elements were Calcium
had soil type-sandy loamy (classified as ferric luvisols), and Mokwa 3600–17600 mg/kg (mean 7656 ± 1774.4 mg/kg), Magnesium
growing locations had soil-type- dystric nitosols (Alamu et al., 2020b). 1760–6500 mg/kg (mean 3238.9 ± 522.9 mg/kg), Sodium 0.4–720
No fertilizers or herbicides were applied throughout the study. Manual mg/kg (mean 298.1 ± 158.3 mg/kg), Potassium 3100–27,000 mg/kg
weeding was done as necessary. The agroecological characteristics of (mean 13,467.1 ± 4432.4 mg/kg), Phosphorus 1790–6400 mg/kg
the growing locations are described as follows: (mean 3564.9 ± 793.1 mg/kg), Sulphur 1620–6100 mg/kg (mean
3336.2 ± 826.4 mg/kg). When the mineral composition is compared
i. IVS-Ibadan: is an Inland Valley Hydromorphic area situated in per location, varieties planted in Mokwa had the lowest micro and
the forest-savanna transition zone with an annual rainfall of 1312 macro-elements concentrations. The only exception was Nickel (1.1
mm and an average temperature range of 20.3–33.8 °C mg/kg) among microelements, which was the lowest in the Upland
ii. Upland-Ibadan: is a plain level area situated in the same planting location. In contrast, magnesium (1760 mg/kg) and sodium
agroecological zone as IVS-Ibadan. (0.4 mg/kg) were the exceptions for macro elements in IVS and Upland
iii. Mokwa: is a Southern Guinea savanna zone with an annual locations, respectively.
rainfall of 1149 mm and an average temperature range of
18.1–37.3 °C. The latitude and longitude for both locations are 3.2. Effect of genotypes and growing location on the mineral contents of
Ibadan 7° 38′N, 3° 89′E; Mokwa 9° 28′N, 5° 05′E. GGA cassava leaves
Supplementary file 1 and Table 2 present the mean values of trace
and macro elements of the sampled 400 leaves by genotype and the
analysis of variance based on genotypes and growing locations. There
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E.O. Alamu et al. Heliyon xxx (xxxx) e11618
Table 1
Descriptive statistics (mg/kg) for all mineral parameters across three locations.
Fe Zn Mn B Cu Ni Al Ti Ca Mg Na K P S
IVS Minimum 65 42 44 12 5.6 1.4 12 1.5 3800 1760 220 4000 2200 2600
Maximum 340 124 610 29 13 21 220 56 17600 5900 700 17600 5500 6100
Mean 119.91 70.09 181.37 19.44 8.42 6.78 51.5 7.42 7429 3316 406.43 10649 3555 4211
SD 33.85 13.92 86.24 3.3 1.11 3.26 26.3 5.46 1747 519.44 87.34 2513 528.18 702.02
S.E 1.69 0.69 4.31 0.16 0.06 0.16 1.32 0.27 87.37 25.97 4.37 125.65 26.41 35.10
UPLAND Minimum 72 38 44 14 5.3 0.8 11 0.14 3800 2100 0.4 12400 2900 2400
Maximum 660 97 270 30 14 43 280 5.2 12500 4100 650 27000 6400 3900
Mean 118.15 57.53 128.43 20.35 8.93 3.61 38.72 0.85 7106 2977 139.34 18459 4245 3248
SD 38.72 8.57 46.97 2.8 1.14 2.7 23.9 0.53 1375 342.82 137.05 2272 603.64 213.09
S.E 1.94 0.42 2.35 0.14 0.06 0.14 1.19 0.03 68.78 17.14 6.85 113.61 30.18 10.65
MOKWA Minimum 43 16 16 5.7 0.7 1.1 5.3 0.12 3600 1860 144 3100 1790 1620
Maximum 280 440 540 35 10 37 630 4.4 15200 6500 720 21000 5500 3600
Mean 77.36 35.34 251.79 18.76 6.69 4.18 36.85 0.59 8430 3421 348.06 11304 2895 2547
SD 18.13 33.66 82.07 3.95 1.5 4.12 50.15 0.44 1880 569.6 96.54 3145 576.55 333.89
S.E 0.91 1.68 4.10 0.19 0.08 0.21 2.51 0.02 94.04 28.48 4.83 157.29 28.83 16.69
All locations Minimum 43 16 16 5.7 0.7 0.8 5.3 0.12 3600 1760 0.4 3100 1790 1620
Maximum 660 440 610 35 14 43 630 56 17600 6500 720 27000 6400 6100
Mean 105.1 54.3 187.2 19.5 8 4.9 42.4 3 7656 3238 298.1 13467 3564 3336
SD 37.1 26 89.6 3.5 1.6 3.7 36.1 4.5 1774 522.9 158.3 4432 793.1 826.4
S.E 1.07 0.75 2.59 0.10 0.05 0.11 1.04 0.13 51.22 15.10 4.57 127.95 22.90 23.86
SD- Standard deviation, S.E- Standard error.
Table 2
Mean values of trace and macro minerals by growing location.
Growing Fe Zn Mn B Cu Ni Ti Ca Mg Na K P S Al
locations
IVS 119.91 a 70.09 a 181.37 b 19.44 b 8.42 b 6.78 a 7.42 a 7429.75 3316.90 406.43 a 10649.25 3555.25 4211.75 51.50 a
b b c b a
Upland 118.14 a 57.51 b 128.31 c 20.35 a 8.93 a 3.61 c 0.85 b 7102.25 2976.25 139.00 c 18466.00 4245.25 3248.50 38.75 b
c c a a b
Mokwa 77.36 b 35.33 c 251.79 a 18.76 c 6.69 c 4.18 b 0.59 b 8430.00 3421.40 348.06 b 11304.75 2895.90 2547.88 36.85 b
a a b c c
Pr > F <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001 <0.0001
(Location)
were significant differences among mean values of genotypes except for ements with high concentrations) indicates that the regression models
the microelements Nickel, Aluminum, and Titanium, and one macro el- could not adequately predict the variability of the elements considered,
ement, Sodium. However, there was a significant difference among the as has been applied in a similar study (Alamu et al., 2020b). The ele-
genotypes based on growing locations for all elements. This location- ments with extremely high MSE are Calcium and Potassium. Statisti-
specific difference is similar to reported differences in cassava root eval- cally, this may be an unsuitable result, but it presents an advantage for
uation as reviewed by Montagnac et al. (2009) and highlighted explic- varietal selection since it shows that the compositional spread of the nu-
itly by Maroya et al. (2012) and Alamu et al. (2020a). Specifically, the trients is vast and thus allows germplasm selection and breeding.
characteristics of the Mokwa agroecological zone may have contributed
to comparatively lower compositions found in this study. In general, the 3.3. Principal component analysis of mineral profiling of GGA cassava
results show a wide range of values in which the mean value of each nu- leaves
trient is higher than the values reported in the literature (Achidi et al.,
2008; Montagnac et al., 2009) and also in national and regional food The principal component analysis (PCA) results across the geno-
composition tables (NiFCT, 2017; WAFCT 2019). Worthy of mention is types, and growing locations are presented in Table 4. In this current
the abundance of key physiologically essential minerals like Iron, Zinc, study, PC 1 to 3 were extracted and contributed to 58.9% of the total
and Calcium in these genotypes, which implies that cassava leaves can variation, these three components had eigenvalues of 3.75, 2.9, and
be a key food source of these minerals. In comparison with existing lit- 1.59, respectively. The trend found in this study followed a similar sta-
erature on the mineral composition of cassava leaves as reviewed by tistical approach used by Luchese et al. (2017) and Alamu et al. (2021)
Montagnac et al. (2009) and Latif and Müller (2015), this study's results to explain the variation. Factor loadings ≥0.3 were selected as a cut-off
show that genotypic diversity exists for mineral composition in cassava point to identify important variations and common characteristics in
leaves and, therefore, can be exploited for genetic improvement by the data. P, K, and Cu were distinctly loaded on PC 1, Ti, Na, Al, Ni, and
breeders seeking options to reduce micronutrient deficiencies in sub- Mg were loaded on PC 2, and B, Ca, and Mn were loaded on the third
Saharan Africa. component. Sulphur, Iron, and Zinc loaded on both PC 1 and PC 2. The
Supplementary file 3 shows the goodness of fit statistics for the ele- different components reveal similarities in the various elements, which
mental compositions of genotypes from the three growing locations. reflect associations that can be valuable for decision-making during
The regression model used to analyze variance was predicted by breeding. Notable is PC 2, which loads eight elements, five of which dis-
38–81% of the composition data, which varied based on the dependent tinctly show an association among themselves.
variables. The mean square error (MSE) ranged widely from 1.2 to
1,981,516.1, where Copper had the lowest value and Calcium had the
highest, respectively. This very high range of MSE (especially for the el-
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E.O. Alamu et al. Heliyon xxx (xxxx) e11618
Table 3 showed a notable relationship among Iron with Zinc, copper, Alu-
Principal components analysis (PCA) of mineral elements across three loca- minum, and titanium (r = 0.33, 0.39, 0.48, and 0.56, respectively),
tions. Zinc with Nickel, titanium and sulphur (r = 0.52, 0.32, and 0.51, re-
PC1 PC2 PC3 spectively), Manganese with calcium, magnesium, sodium, potassium,
and phosphorus (r = 0.45, 0.42, 0.32,‒0.43, and ‒0.53, respectively).
Fe 0.55 0.49 – Boron with copper (r = 0.26), Nickel with titanium (r = 0.28). The
Zn 0.48 0.46 –
Mn – – 0.31 macro-elements showed relationships between Calcium with Magne-
B – – 0.70 sium (r = 0.49), potassium (r = ‒ 0.31), phosphorus (r = ‒0.41). Mag-
Cu 0.69 – – nesium and Sodium negatively correlated with Potassium and phos-
Ni – 0.49 – phorus (r = ‒0.40, r = ‒0.36 and r = ‒0.56, r = ‒0.34, respectively).
Al – 0.50 – The most notable relationship from this study is the correlation be-
Ti – 0.78 – tween potassium and phosphorus (r = 0.77). This strong correlation of
Ca – – 0.49
Mg – 0.40 P and K is different from the results presented by Alamu et al. (2020a)
–
Na – 0.63 – when cassava roots were evaluated across multiple harvest times and
K 0.68 – – sampling methods but is consonant with assertions presented by Alamu
P 0.85 – – et al. (2020b) in yellow-fleshed cassava roots. The correlation relation-
S 0.56 0.60 – ships presented in Table 4 mirror the PCA results in Table 3, where
Eigenvalue 3.75 2.90 1.59 some elements showed similar characteristics of belonging to the same
Cumulative % 26.81 47.54 58.93 components. Overall, positive relationships will be advantageous from
a breeding point of view. In contrast, negative relationships may pose a
3.4. Cluster analysis of GGA cassava leaf genotypes using the mineral challenge to the breeders seeking to improve the concentration of se-
composition lect minerals.
Supplementary file 4 shows a cluster analysis of genotypes based on 4. Conclusion
their similarity to the elements considered in this study. Five indepen-
dent clusters were discovered and related in a dendrogram (Supplemen- This study presents data on the compositional information of micro-
tary file 4). Cluster 1 to 5 contained 187, 147, 60, 2, 4 genotypes respec- and macro-elemental composition of a large number of cassava leaves
tively. Notably, cluster 2 contained eight varieties (01/0046, 94/0020, and reports the various statistical interactions using genotype and
93/0098, 88/112-7(3X), I00/0017, 91/00417, I00/0017, 88/112-7 growing location factors. Generally, the results provide evidence of a
(3X)) that possessed highest mineral compositions in Fe, Al, Ti, Na, K, S, large diversity in the composition of elements in cassava leaves. The
Mn, and B, respectively. Genotypes 93/0681(4X), 92/0430, and 95/ most abundant elements were Fe & Ca, while Ti & Na were the least
0460 in cluster 3 had the highest concentrations of Mg, Na, and Zn, re- abundant micro- and macro-elements. A noticeable location effect was
spectively. While 30555(4X) had the highest values of Ca and belonged observed on the genotypes, showing that the agroecological
to cluster 4. Genotype K95/0671 was highest for Ni in cluster 1. Geno- zone—Mokwa—did not provide maximum genetic gain compared with
types 96/1630 and M98/0028, belonging to cluster 5, had the highest other zones. In terms of the specific varieties that could be considered
potassium and lowest calcium concentrations. Genotype 91/00262 as parental lines for breeding purposes, varieties 01/0046, 94/0020,
(3X), which belonged to cluster 1, had the lowest values in Fe and Al, 93/0098, 88/112-7(3X), I00/0017, 91/00417, I00/0017, 88/112-7
while genotype 98/0406, also in cluster 1, had the lowest values for (3X)) possessed highest mineral compositions in Fe, Al, Ti, Na, K, S, Mn,
macronutrients Mg and Na. and B, respectively and particularly grouped in the cluster analysis.
Overall, this study proves that an increase in the utilization of cassava
3.5. Correlation of mineral content of GGA cassava leaves leaves for food can reduce mineral deficiencies (especially in key ele-
ments of Fe, Ca, and Zn). The evaluation presented can thus provide
Table 4 shows Pearson's correlation coefficients of the elements breeders with information on varietal selection and trials and inform
contained in the genotypes across the growing locations. Generally, the nutritional choices for improved nutrient intake, as the case may apply.
relationships were statistically significant (p < 0.05) but had a weak
relationship in most cases between the elements. The microelements
Table 4
Pearson correlation coefficients (PCC)∗ of mineral composition of cassava leaves across three locations.
Variables Fe Zn Mn B Cu Ni Al Ti Ca Mg Na K P S
Fe 1
Zn 0.33 1
Mn –0.16 –0.36 1
B 0.14 –0.05 0.03 1
Cu 0.39 0.19 –0.27 0.26 1
Ni 0.17 0.52 –0.01 –0.16 0.04 1
Al 0.48 0.14 0.08 0.10 0.09 0.06 1
Ti 0.56 0.32 –0.03 0.01 0.17 0.28 0.04 1
Ca –0.08 –0.02 0.45 0.16 –0.21 –0.15 0.11 –0.07 1
Mg –0.06 0.02 0.42 0.00 –0.19 0.07 0.09 0.05 0.49 1
Na –0.02 0.02 0.32 –0.09 –0.11 0.30 0.14 0.34 0.17 0.31 1
K 0.19 0.06 –0.43 0.23 0.45 –0.08 –0.02 –0.27 –0.31 –0.40 –0.56 1
P 0.28 0.27 –0.53 0.21 0.60 0.10 0.00# 0.00 –0.41 –0.36 –0.34 0.77 1
S 0.44 0.51 –0.20 0.25 0.43 0.29 0.19 0.61 –0.14 –0.08 0.20 –0.02 0.33 1
∗ significant at p < 0.05.
# insignificant at p > 0.05.
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E.O. Alamu et al. Heliyon xxx (xxxx) e11618
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Author contribution statement [Alamu et al., 2021] E.O. Alamu, B. Maziya-Dixon, O. Lawal, G.A. Dixon, Assessment
of chemical properties of yellow-fleshed cassava (Manihot esculenta)
Alamu, Emmanuel Oladeji: Conceived and designed the experi- roots as affected by genotypes and growing environments, AGRIVITA
J. Agric. Sci. 43 (2) (2021) 409–421.
ments; Performed the experiments; Analyzed and interpreted the data; [Alamu et al., 2022] E.O. Alamu, B. Maziya-Dixon, A. Dixon, Datasets on the
Wrote the paper. variations of minerals in biofortified cassava (Manihot esculenta
Dixon, Alfred; Maziya-Dixon, Busie: Conceived and designed the ex- Crantz) as a function of storage root portion, maturity and
periments; Performed the experiments; Contributed reagents, materi- environment, F1000Research 11 (509) (2022) 509.
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CORRECTED PROOF