agronomy
Article
High Soil Phosphorus Application Significantly Increased
Grain Yield, Phosphorus Content but Not Zinc Content of
Cowpea Grains
Saba B. Mohammed 1,2,* , Daniel K. Dzidzienyo 2, Adama Yahaya 3, Muhammad L. Umar 1,
Mohammad F. Ishiyaku 1, Pangirayi B. Tongoona 2 and Vernon Gracen 2,4
1 Institute for Agricultural Research, Ahmadu Bello University, Zaria 800001, Nigeria;
mahammadlawan@yahoo.com (M.L.U.); mffaguji@hotmail.com (M.F.I.)
2 West Africa Centre for Crop Improvement, University of Ghana, Accra 233, Ghana;
ddzidzienyo@wacci.ug.edu.gh (D.K.D.); ptongoona@wacci.ug.edu.gh (P.B.T.); vg45@cornell.edu (V.G.)
3 Department of Botany, Ahmadu Bello University, Zaria 800001, Nigeria; yadamcy@yahoo.com
4 Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 31328, USA
* Correspondence: bsmohammed@abu.edu.ng; Tel.: +234-806-929-9881
Abstract: To ameliorate the impact of soil phosphorus (P) deficiency on cowpea, the use of P-based
fertilizers is recommended. Plant zinc (Zn) is an essential nutrient required by plants in a wide range
of processes, such as growth hormone production and metabolism. However, a negative association
between plant Zn content and high P application has been reported in some crops. There are few
reports about soil P application and plant Zn content relationship on cowpea. Thus, this study



 investigated the response of cowpeas to three P rates in the screenhouse (0, 1.5, and 30 mg P/kg) and

 field (0, 10, and 60 kg P2O5/ha) and their effects on plant P and Zn content, biomass, and grain yield.
Citation: Mohammed, S.B.; In the screenhouse, shoot and root dry weights, and shoot P and Zn content were measured. Shoot
Dzidzienyo, D.K.; Yahaya, A.; dry weight, grain yield, grain P, and Zn contents were determined from field plants. Higher rates of
Umar, M.L.; Ishiyaku, M.F.; Tongoona, P led to increased shoot biomass and grain yield of the field experiment but were not associated with
P.B.; Gracen, V. High Soil Phosphorus a significant change in shoot or grain Zn content. There was not a significant correlation between
Application Significantly Increased grain yield and Zn content in high soil P (p < 0.05). The effect of higher P application on reduced
Grain Yield, Phosphorus Content but plant Zn contents may be genotype-dependent and could be circumvented if genotypes with high Zn
Not Zinc Content of Cowpea Grains.
content under high soil P are identified.
Agronomy 2021, 11, 802.
https://doi.org/10.3390/
Keywords: cowpea; fertilizer; grain phosphorus; grain yield; grain zinc; phosphorus; shoot
agronomy11040802
phosphorus; shoot zinc; zinc content
Received: 9 February 2021
Accepted: 14 April 2021
Published: 19 April 2021
1. Introduction
Publisher’s Note: MDPI stays neutral Zinc (Zn) is among the seven most limiting micronutrients in human diets, as over
with regard to jurisdictional claims in two-thirds of the global diets are deficient in one or more of iron (Fe), zinc, copper, calcium,
published maps and institutional affil- magnesium, iodine, and selenium [1,2]. Zn is especially needed by pregnant women
iations. and children, especially because of its critical roles in pregnancy, enhanced protection
from infection, and maintenance of immune system functions. Its deficiency can lead
to complications in childbirth, low birth weight, poor growth of children, and reduced
tolerance to infectious diseases [3–5]. Zn is also an important factor in the prevention and
Copyright: © 2021 by the authors. treatment of common diseases such as common cold, malaria, diarrhea, and respiratory
Licensee MDPI, Basel, Switzerland. infections [4,5].
This article is an open access article Cowpea is a pulse crop providing food, nutrition, and cash for its value-chain actors
distributed under the terms and across sub-Saharan Africa (SSA) and beyond [6,7]. Every part of the crop, including leaves,
conditions of the Creative Commons green pods, and grains, are used by humans in making different dishes and its fodder is
Attribution (CC BY) license (https:// used for livestock feed [8,9]. Due to its rich protein content, the crop serves as an important
creativecommons.org/licenses/by/ supplement for the carbohydrate-rich cereals [9,10]. Cowpea is a strategically important
4.0/).
Agronomy 2021, 11, 802. https://doi.org/10.3390/agronomy11040802 https://www.mdpi.com/journal/agronomy
Agronomy 2021, 11, 802 2 of 18
crop capable of providing millions of people with nutritional security owing to its rich
nutritional value, especially high protein, Fe, and Zn. This contributes to its increasing
popularity [11]. Cowpeas are cultivated by smallholder farmers on soils with low available
plant phosphorus (P) with minimal to no P application [12–14].
Cereals are the most important source of calories globally but are deficient in Zn and
Fe due to the high content of phytic acids in grains that decrease the bioavailability of Zn.
Therefore, Zn deficiency is likely to be high in areas where cereals are the dominant food
source [4,15]. Legumes, being rich in important micronutrients like Fe and Zn, serve as
good complimentary food to micronutrient-deficient cereals [11,16]. P is stored in most
legumes including cowpea as phytic acid, which is known to limit the bioavailability
of Zn [16–18].
Increasing the bioavailability of micronutrients in human diets has become a global
priority, particularly for Fe and Zn in developing countries, where many people depend
on plant-based food products for nutrition [11,19,20]. Enhancing the bioavailability of
micronutrients in food could be achieved through improved agronomic practices such as
optimum application of fertilizers with micronutrients, and genetic improvement of elite
crop varieties [1,19]. Other ways to remedy micronutrients deficiency in food crops include
biofortification, diversity of diet, mineral supplementation, and food fortification [1,15,21,22].
In SSA, micronutrient deficiency is not only found in edible parts of plants, like grains,
but also in most soils of growing areas of major crops, including cowpeas. Micronutrient
deficiency of grains is further worsened because most farmers do not apply micronutrients
such as Zn to crop plants, even when the application of Zn to cowpea is known to increase
both grain yield and Zn content [20]. The low P of soils further leads to low productivity of
the crop [7,23,24].
Application of fertilizers supplying major nutrients like nitrogen-phosphorus-potassium
(NPK), with little or no consideration of micronutrient requirements, may lead to a reduced
amount of micronutrients in the edible tissues that serve as food for people [18], since
the micronutrient content of grains depends largely on the supply from soil nutrient pool
and micronutrients-containing fertilizers [1,18]. Two complementary approaches have
been recommended to achieve high cowpea yield on soils with low available P. First is the
use of improved agronomic approaches such as application of phosphate fertilizers, and
second is the development of elite varieties with high P use efficiency [25–27]. Varieties
with improved P efficiencies use different mechanisms, including increased solubilization
and mobilization of soil P, improved root architecture traits, and increased ability to acquire
P and accumulate it in edible tissues [27–30].
Loneragan and Webb [31] reported that there is confusing literature on plant P–Zn
interactions for crop plants and noted that the subject of plant P–Zn interactions remains
complex, involving many phenomena in both soils and plants, such as observations that
P applications can decrease, or not decrease, Zn content in plant grains and shoots. The
application of phosphate fertilizer is required for increased productivity of cowpea in areas
with low soil available P. However, its influence on micronutrient availability on the grains
and leaves has not been adequately investigated [16,32,33]. The application of P, especially
at a high rate, may be counterproductive, if P application negatively affects Zn availability,
as has been found in some cereals [15,18,22,34]. Thus, it is important to investigate the
influence of P fertilizer applications on cowpea’s growth (root and shoot biomass), grain
yield, and the potential relationship between P application in the growth medium and Zn
content in shoot and grain at varying levels of P concentrations of the growth environment.
2. Materials and Methods
2.1. Plant Materials
A total of thirty elite cowpea genotypes from four different breeding programs in West
Africa (Burkina Faso, Ghana, and Nigeria) and the USA were used. Twenty were parents
for recombinant inbred line populations previously studied for mapping of important
biotic and abiotic stresses [35–37]. The genotypes are presented in Supplementary Table S1.
Agronomy 2021, 11, 802 3 of 18
2.2. Description of the Experiments
Two experiments were conducted: one in the screenhouse and the other under the
field environment. In the screenhouse experiment, a river-sand was collected from the bank
of a local stream “Rafin Kudingi” at the Ahmadu Bello University Nigeria (11◦09′49.6′′ N
7◦37′13.8′′ E) and was acid-washed with 1% HCl. The acid-washed sand used had very
low P (3.70 mg/kg), N (0.11 g/kg), and K (0.08 cmol/kg) and organic carbon (0.24 g/kg
of soil contents), determined at the Department of Soil Science, Ahmadu Bello University
Nigeria, and this appropriately mimics major nutrient-deficient soil [38]. A Hoagland
nutrient solution with three different concentrations of P (0, 1.5, and 30 mg P/kg of soil)
as described in a previous study on cowpea [39] was used to water the plants during the
experiment. The screenhouse experiment used a randomized complete block design in five
replications. Cowpea seeds were sown and thinned to one plant per pot at 10 days after
sowing (DAS). The pots were watered with the dilute nutrient solution with graduated
beakers as follows: 300 mL per pot at planting, and subsequently 300 mL was applied at
3, 6, 9, 16, 23, 30, 37, 44, and 51 DAS for each of the P treatments (0, 1.5, and 30 mg P/kg
soil). Reverse osmosis (RO) was used to water the pots periodically to prevent wilting
and prevent the accumulation of salts in the soil. Spraying of insecticide (Karate 50 g/L
lambda-cyhalothrin, Syngenta Crop Protection AG, Basel, Switzerland) was used to protect
the plants against insect pests. Data on plant height (cm), shoot dry weight (g), root dry
weight (g), total plant dry weight (g) (shoot and root dry weights), shoot P, root P, and shoot
and root Zn content were collected from the screenhouse plants. Plant growth continued
until 55 days, at which time the screenhouse experiment was terminated.
A field experiment, comprising the same set of genotypes used in the screenhouse
experiment described above, was conducted in a low P field (4.2 mg P/kg—Bray-I method)
at the Institute for Agricultural Research farm (11◦10′31.7′′ N 7◦36′43.9′′ E), Nigeria.
The field used has been left uncultivated for several years and had low P (4.2 mg/kg),
N (0.13 g/kg), and K (0.68 cmol/kg) and organic carbon (0.79 g/kg of soil content), as de-
termined by the Department of Soil Science, Ahmadu Bello University, Nigeria. In the field,
P was applied using a single super phosphate fertilizer (SSP 18% P2O5, 11% Sulphur,
18% Ca, and 4% moisture (TAK-AGRO, Kaduna, Nigeria)) at the rate of 0, 10, and
60 kg P −1205 ha based on previous phosphate recommendations for cowpea [7,27]. The
field experiment was a factorial arrangement (with two factors, namely: 30 cowpea geno-
types and three P levels) in a randomized complete block design laid out in two replications.
Plots were one row of 2 m each with a 1 m unplanted walkway between plots, giving a
pot size of 1.5 m2 with an intra- and inter-row spacing of 0.20 and 0.75 m, respectively. All
the field plots received 30 kg/ha N (46% N, Urea) and K (30% K2O, Muriate of Potash) to
avoid any confounding effects of N and K deficiency on the plants. All the single fertilizers
were applied as dual banding by placing them below the soil surface five days after sowing.
Plants were protected against insect pests by spraying insecticide (Karate 50 g/L lambda-
cyhalothrin, Syngenta Crop Protection AG, Basel, Switzerland). Data collected from the
field experiment are plant height (cm), shoot dry weight (g), root dry weight (g), total plant
dry weight (g) (shoot and root dry weights), grain yield (kg/ha), P concentration, and Zn
content of the grains, shoot, and root samples. See Table 1 for the list and abbreviation of
the traits measured.
Agronomy 2021, 11, 802 4 of 18
Table 1. List of trait names with their abbreviation and definitions.
Traits Definition and Abbreviations
Grain yield, kg/ha Grain yield in kg per hectare from the low, medium, and highphosphorus treatments (yield.LP, yield.MP, and yield.HP)
Grain phosphorus Phosphorus concentration determined from grain samples
concentration, mg/kg from the low, medium, and high phosphorus treatments(grainP.LP, grainP.MP, and grainP.HP)
The zinc content of grain samples from the low, medium, and
Grain zinc content, ppm high phosphorus treatments (grainZn.LP, grainZn.MP, and
grainZn.HP)
The height of the plant measured in centimeters from the soil
Plant height, cm surface to the base of the top leaf on the main stem (average
per genotype) (pht.LP, pht.MP, and pht.HP)
Root dry weight, gram Weight of dry root, per plot of low, medium, and highphosphorus treatments (rdwt.LP, rdwt.MP, and rdwt.HP)
Root phosphorus concentration, Phosphorus concentration determined from root samples
mg/kg from the low, medium, and high phosphorus treatments(rootP.LP, rootP.MP, and rootP.HP)
The zinc content of root samples from the low, medium, and
Root zinc content, ppm high phosphorus treatments (rootZn.LP, rootZn.MP, and
rootZn.HP)
Shoot dry weight, gram Weight of dry shoot, per plot of low, medium, and highphosphorus treatments (sdwt.LP, sdwt.MP, and sdwt.HP)
Shoot phosphorus Phosphorus concentration determined from shoot samples
concentration, mg/kg from the low, medium, and high phosphorus treatments(shootP.LP, shootP.MP, and shootP.HP)
The zinc content of shoot samples from the low, medium, and
Shoot zinc content, ppm high phosphorus treatments (shootZn.LP, shootZn.MP, and
shootZn.HP)
Plant available phosphorus from the low, medium, and high
Soil phosphorus content, mg/kg phosphorus plots (soilP.LP, soilP.MP, and soil.P.HP),
determined using the Bray-I method
2.3. Determination of Phosphorus Concentration and Zinc Content from Plant Tissues
Samples of shoots and grains were taken from the screenhouse (only shoot samples)
and field experiments and analyzed for P concentration and Zn content. Grain samples
were ground using mortar and pestle, whereas an electric blender was used to mill shoot
samples. From each sample, 0.2 g was then weighed using an electric balance (Scouttm Pro
SPU202, Ohaus Corporation, Parsippany, NJ, USA) and digested with 30 mL mixed acids
(containing 26 mL nitric acid, 3.2 mL perchloric, and 0.8 mL sulfuric acids), then placed on
a digestion block set at 230–300 ◦C. The digest was then transferred into a 50 mL volumetric
flask and brought up to 50 mL with distilled water. Thereafter, 5 mL of the extract for
each sample was pipetted into a 25 mL volumetric flask and 5 mL of a color developing
agent made up of 50 g ammonium molybdate dissolved in 500 mL distilled water, 2.5 g
ammonium metavanadate dissolved in 500 mL distilled water, and 350 mL nitric acid in
1000 mL of distilled water, which were all mixed and made up to 2.5 L with distilled water.
To determine P concentration, absorbent readings were taken using a Spectrophotome-
ter (Helios Gamma UVG 875005, Spectronic Unicam, Caerphilly, UK) at a wavelength of
460 nm. The Zn content was determined using an atomic absorption spectrometer (AA280FS,
Agilent Technologies, Santa Clara, CA, USA). Zn standard solutions were made using
the 1000 µg/mL Zn Standard (1000 µg/mL SpectraScan, Teknolab AS, Verkstedveien,
Ski, Norway). The P concentration was determined in mg/kg, whereas the Zn was com-
puted in parts per million (ppm). The formula for Zn content and P concentration compu-
tations are presented in Supplementary Table S2.
Agronomy 2021, 11, 802 5 of 18
2.4. Statistical Analyses
2.4.1. Descriptive Analysis
Data from both the screenhouse and field experiments, including shoot parameters,
yield (shoot and grain), P concentrations, and Zn content, were analyzed using the linear
mixed effect model to generate the best linear unbiased estimator (BLUE) using the lme4
package in R. The BLUE outputs were used to visualize the phenotypic distribution of the
measured traits with box plots using the ggplot2 package in R (R Core Team). The relative
difference (%) in performance between the high P and low P (control) were computed
(Supplementary Table S2).
2.4.2. Relationships among Yield, Phosphorus, and Zinc Content
The relationship among yield (biomass and grain), plant P, and Zn content phenotypes
at the different soil P rate were investigated with the Pearson-product moment correlation
and correlation matrices were visualized with the corrplot package in R (R Core Team).
2.4.3. Interaction of the Genotype Main Effect Plus Genotype by Environment of
the Genotypes
The means of grain yield and grain Zn content were used to run a site regression anal-
ysis, also called genotype main effect plus genotype–environment interaction (GGE) [40].
The GGE is a linear-bilinear model that removes the effect of the environment (here, the
rates of soil P) and expresses the output as a function of the genotype effects and its
interaction with the environment. This model was used since the P rates are the main
source of variation concerning the contributions of the genotypes and the interaction of the
genotypes× P rates. The varying soil P rates were taken as environments for the analysis to
identify the mean performance and stability of the genotypes, determined by their location
and proximity to the origin of the biplot [40]. The GGE biplot outputs were used to indicate
discrimination of the environments (P rates), and the correlation coefficient between the
environments. The model used for the GGE analysis is as below:
N
Yij = µ+ ej + ∑ Tnγinδjn + εij
n=1
where Yij is the grain yield/Zn content of the i-th genotype (i = 1, . . . , 30) in the j-th
P rates (j = 1, . . . , 3), µ is the grand mean, ej is the P rates’ deviations from the grand mean,
Tn is the eigenvalue of the principal component (PC) analysis axis n, γin and δin are the
genotype and P rates’ PC scores for axis n, N is the number of PC retained in the model,
and εij is the error term.
3. Results
3.1. Variable Soil Phosphorus Effect on Shoot Dry Matter and Content of Phosphorus and Zinc
Phosphorus (P) fertilization was positively associated with increased growth and
performance of the plants for most of the measured traits under the screenhouse conditions
where plants were grown on acid-washed river-sand soil supplemented with Hoagland
nutrients solution with varying P levels. The plant height, shoot dry weight, root dry
weight, shoot to root ratio, and shoot P concentrations increased with increasing P supply,
but the addition of P to the growth media did not result in increased shoot Zn content of
the genotypes (Figure 1). The root Zn content of the MP and HP treatments were similar,
though were higher than those of the LP treatment. A similar response was observed for
the plants grown in the field with varying P supplied with the addition of SSP fertilizer,
where plant height, shoot dry weight, root dry weight, total plant dry weight, grain
yield, and P concentration of the grains increased as the P in the soil increased, except
shoot P, root P, seed weight (g/100 seeds), root, and grain Zn contents (Figures 2 and 3,
Supplementary Figure S1). There was a noticeable increase in shoot Zn content with the
varying soil P rates among the genotypes, which were not significantly different between
Agronomy 2021, 11, x  6 of 18 
 
mum for many traits when the applied P was highest for most of the parameters meas-
ured, except for shoot Zn content in the screenhouse, and shoot Zn, root Zn, and grain Zn 
contents in the field experiments. It therefore means that high soil P fertilization does not 
significantly result in reduced grain Zn content. The highest level of P fertilization did 
Agronomy 2021, 11, 802 slightly, but not significantly, reduce shoot Zn content from the field results (Figu6roef 138). 
The grain Zn content was relatively higher when P application was low and medium in 
the growth media compared with high P (Figure 3, see Supplementary Tables S2 and S3 
for means of parameters assessed for all genotypes evaluated in the screenhouse and the 
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a reduction of 17.1% in the Zn content of the HP over the LP (Table 2). 
 
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Agronomy 2021, 11, 802 7 of 18
Agronomy 2021, 11, x  7 of 18 
 
Agronomy 2021, 11, x  7 of 18 
 
 
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Figure 3. Phenotypic distribution of phosphorus (P) and zinc (Zn) contents of shoot, root, and grains from the field envi-  
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dh ird
quartile, where the X-axis is soil phosphorus concentrations, with 1_LP = no-P application, 2_MP = 10 kg P2O5 ha−1, andn t 
qua3rd_tiHflfePe, rw=e n6hc0e r kcegot mhPepOaXr -ihsaaox−ni1s.  tLiessetst to(eαirl s≤p  a0hb.o0os5vp)e.h  Meoarecuahns bsc oowxni tcphel onthtt reda estniaomontees  ,lsewitmtietihrla a1rri_etyL n Paomt= soningong- iPgfircaoapunpptlsiyc  aadsti ifpofeenrr,e2n_t.M P
−1
2 5  Tukey’=s h1o0nkegstPly2 Osi5gnhiafica,nat nd
3_H −1dPiff=er6e0nckeg cPom2Op5arhisaon .teLset t(tαe r≤s 0a.b05o)v. eMeeaacnhs bwoixthp tlhoet dsaemnoe tleetstiemr ailraer intoyt asmigonnifgicagnrotluyp dsifafesrpenert. Tukey’s honestly significant
 difference comparison test (α ≤ 0 .05). Means with the same letter are not significantly different.
  
The relative increase in plant height, shoot dry weight, shoot P concentration, and
shoot Zn content in high P (HP) over the low P (control) was 34.6%, 81.8%, 26.1%, and
−3.51% respectively, in the screenhouse (Table 2), where the Zn content in the shoot at the
HP (68.3 ppm) was slightly lower than the control (70.7 ppm), corresponding to −3.5%
relative reduction in Zn content of HP plants compared to the LP. The results for the field
evaluation followed a comparable pattern with the screenhouse in the relative difference
 
 
Agronomy 2021, 11, 802 8 of 18
in Zn content of HP relative to other P treatments. An increase in grain yield and grain
P followed a linear pattern with increasing P fertilizer to the soil, while Zn content was
higher in plants evaluated under low and medium soil P vis-à-vis the high P, which had a
reduction of 17.1% in the Zn content of the HP over the LP (Table 2).
Table 2. Relative difference (RD) in performance of high phosphorus treatment relative to low phosphorus on some traits
measured in the screenhouse and field conditions.
Screenhouse Field
Phosphorus Pht Sdwt ShootP ShootZn Sdwt ShootP ShootZn Yield GrainP GrainZn
Levels (cm) (g) (mg/kg) (ppm) (g) (mg/kg) (ppm) (kg/ha) (mg/kg) (ppm)
LP 14.5 0.4 942.4 70.7 20.6 1132.4 103.9 294.1 2106.8 34.3
MP 14.3 0.5 1054.1 73.4 38.9 1162.9 96.8 558.9 2286.4 31.5
HP 22.2 2.2 1275.9 68.3 94.5 1183.7 88.7 1406.6 2368.2 29.3
RD (%) 34.6 81.8 26.1 −3.5 78.2 4.3 −17.1 79.1 11.0 −17.1
LP = low phosphorus (no-P application), MP = medium phosphorus (1.5 mg P kg−1), and HP = high phosphorus (30 mg P kg−1) for
river-sand in the screenhouse, and MP = 10 kg P2O5 ha−1 and High P = 60 kg P O ha−12 5 for field evaluation, where Pht = plant height (cm)
at maturity, Sdwt = shoot dry weight (g), P = phosphorus concentration, Zn = zinc content, and RD = relative difference (%).
3.2. Phenotypic Association between Yield Components and Zinc Content in Cowpea
The relationships between several growth parameters and Zn content both in
the screenhouse and field trials were not significant (r = 0.1–0.2) (Figures 4 and 5,
Supplementary Tables S5 and S6). The shoot dry weight versus shoot Zn content at
HP treatment had a weak negative correlation (r = −0.1), while grain yield and grain
Zn content at HP (r = 0.1) showed a weak positively significant relationship from field
evaluation (Figure 5), indicating that high yield and Zn content can be combined in some
genotypes since there is no strong association between the two traits that would result
in a tradeoff between high yield vs. low Zn content, or vice versa. The correlation be-
tween these traits measured at the vegetative stage also showed similar weak associations
(Supplementary Figure S2). This suggests that selection of genotypes with high Zn content
is possible when cowpeas are grown on high soil P. This was confirmed from our analysis
which identified several genotypes with high Zn content and yield under high soil P treat-
ments (Table 3). Some genotypes (IT89KD-288, IAR-48, IT82E-18, IT97K-499-35, UCR779,
and DanMisra) had higher grain yield with high Zn content at HP soil environment over
other soil P rates (Table 3). Similarly, grain P and Zn (r = 0.1) were not significantly corre-
lated at all levels of soil P treatments, indicating that no strong association exists between
these traits.
Table 3. Mean performance of representative genotypes with higher shoot dry weight, grain yield, and grain Zn content at
high soil P fertilization under field environment.
Genotypes Sdwt Sdwt Sdwt Yield Yield Yield GrainZn GrainZn GrainZn.HP .MP .LP .HP .MP .LP .HP .MP .LP
IT89KD-288 98.6 33.0 19.0 1475.0 599.2 99.9 43.7 39.2 36.2
IAR-48 116.5 32.0 21.9 1547.1 421.9 388.7 41.1 22.6 26.3
IT82E-18 90.8 49.0 21.3 1171.1 643.9 519.2 40.7 37.2 31.7
IT97K-499-35 80.3 48.0 20.2 1261.1 925.1 289.3 39.5 34.6 30.3
UCR779 93.6 13.0 19.5 1197.1 232.0 22.2 31.4 19.0 21.1
DanMisra 127.6 27.0 22.1 2105.5 459.9 571.9 31.1 24.2 39.4
LP = no P application of P2O5, MP = 10 kg P O ha−12 5 , and HP = 60 kg P2O5 ha−1 for field evaluation.
Agronomy 2021, 11, 802 9 of 18
Agronomy 2021, 11, x  9 of 18 
 
 
FigFuirgeu4r.e C4.o Crreolrarteiolantimonat rmicaetsrfiocerst rfaoirts trmaeitass umredasaucreodss avcarroysins gvasoryilinpgho ssopihl oprhuosslpevheolsruins ltehveels in the 
scrsecerneheonuhseou(nse= (3n0 =g e3n0o tgyepneos)t.yPpoessit)i.v Peoasnidtivneg aantidve naesgsoactiavteio ansssboectiwateieonngsi vbentwtreaeitns  agrieviennb tluraeits are in blue 
andanredd r, ereds,p reecstipvelcyt.ivTehleyc.o Tlohrei nctoelnosrit iynatnednstihteys aiznedo fththee sciizrecl eofa rtehpe rcoiproclreti oanrael ptorothpeocrotirorenlatli oton the correla-
coetfifiocni ecnotes.ffOicnietnhtesX. O-anxi sthoef Xth-eacxoisrr oelfo tghrea mco, rthrelolegreanmd ,c othloer lsehgoewnsdt hcoelcoorr rsehlaotwiosn tchoee fcfiocrierenltastion coeffi-
andcitehnetsco arnredsp tohned cinogrrceoslporosn. dLiPn=g lcoowloprhso. sLpPh o=r ulosw(n op-hPoasppphliocrautios n()n,oM-P =apmpeldiciautmiopnh),o sMphPo =ru ms edium phos-
(1.5pmhogrPusk g(1−.15) ,mangd PH kPg=−1h),i gahnpdh HosPph =o rhuisg(h3 0pmhogsPphkgo−ru1)s.  S(3ee0 Tmabgl eP1 kfogr−1l)i.s tSaened Taabbblree v1i aftoior nlsisotf and abbrevia-
thetitoranitss .of the traits. 
Likewise, in the screenhouse experiments, shoot Zn content and shoot dry weight
(shoot yield) on HP soil had higher negative association (r = −0.4) compared to the results
in the field, while the shoot P and Zn content at all soil P levels had a weak and insignificant
negative relationship (r = −0.1 − (0.1)) (Figure 4). Detailed correlation coefficients for these
traits in both screenhouse and field experiments are presented respectively in Supplemen-
tary Tables S5 and S6. The results indicate that there are suggestive negative relationships
between high soil P and yield (shoot and grain), but they are not strong enough to exclude
selection of outstanding genotypes with high yield and Zn content. See Supplementary
Figures S3 and S4 for scatter plots that further depict these weak relationships.
 
 
Agronomy 2021, 11, x  9 of 18 
 
 
Figure 4. Correlation matrices for traits measured across varying soil phosphorus levels in the 
screenhouse (n = 30 genotypes). Positive and negative associations between given traits are in blue 
and red, respectively. The color intensity and the size of the circle are proportional to the correla-
tion coefficients. On the X-axis of the correlogram, the legend color shows the correlation coeffi-
Agronomy 2021, 11, 802 cients and the corresponding colors. LP = low phosphorus (no-P application), M10Po f=1 m8 edium phos-
phorus (1.5 mg P kg−1), and HP = high phosphorus (30 mg P kg−1). See Table 1 for list and abbrevia-
tions of the traits. 
 
Figure 5. Correlation matrices for traits measured across varying soil phosphorus levels in the
field (n = 30 genotypes). Positive and negative associations between given traits are in blue and
red, respectively. The color intensity and the size of the circle are proportional to the correlation
 coefficients. On the X-axis of the correlogram, the legend color shows the correlation coefficients and
the corresponding colors. LP = no P2O5 application, MP = 10 kg P2O5P ha−1, and High P = 60 kg
P O ha−12 5 for P field evaluation. See Table 1 for list and abbreviations of the traits.
3.3. Interaction of Genotypes and Phosphorus Rates on Grain Yield and Zinc Content with
Biplot Analysis
The genotype main effect plus genotype by environment (GGE) biplot analysis, where
the different soil P rates were considered as distinct environments, revealed the presence of
divergence between the genotypes, grain yield, and Zn content at different soil P conditions.
Genotypes 8, 9, 13, 23, and 29 were the top-performing in the HP trials for grain yield,
and the angle between their vectors and the HP (environment) vector was less than 90◦
(acute angle), while genotypes like 2, 4, 6, 7, 19, and 25 had lower grain yield below
the mean and the angle of their vectors appeared to be greater than 90◦ (obtuse angle)
(Figure 6, see Supplementary Table S1 for names of the genotypes and their corresponding
entry numbers). The most stable genotypes across all the environments for the grain yield
were 13, 16, 24, and 30, which are nearer to the origin of the biplots of the PC1 vs. PC2,
while those genotypes that are farther away from the origin are more sensitive to the
varying levels of soil P (Figure 6).
Agronomy 2021, 11, 802 11 of 18
Agronomy 2021, 11, x  11 of 18 
 
 
FiguFrieg 6u.r eG6e.nGoetnyoptey pmeamina ienffefcfte cptlpulsu Gs Genenootytyppee bbyy EEnviironmentt ((GGGGEE))b bipiploltosth sohwowingintgh ethger aginrayinie lydieolfdt hoef gtheen ogteynpoetsyaptes at 
varyvinargy sinogil sPo ilePvelelsv.e Flsa.cFtaocrtso 1rs a1nadn 2d a2raer ethteh epprirninccipipaall ccoomponent axiiss.. LLoow--PP= =n nooP Pa paplpicliactaiotinoonf oPf2 OP25O, M5, eMdeiudm-P- P= =10 kg 
P2O51 h0ak−g1, PanOd Hhaig−h12 5 ,-Pan =d 6H0 ikggh- P2=O65 0hkag−1 Pfo2Or fiehlad− 15 evfoarlufiaetlidoenv. aluation.
Genotypes 8, 16, and 22 were the top-performing in the HP trials with high grain Zn
since the angle between their vectors and the HP vector is less than 90◦ (acute angle), while
genotypes 2, 4, 5, 14, 17, and 26 had lower grain Zn below the mean under the HP soil
since the angle of their vectors appeared to be greater than 90◦ (obtuse angle) (Figure 7).
The most stable genotypes across all the P environments for the grain Zn were 3, 21, 22,
and 23 because they are nearer to the origin of the biplots of the PC1 vs. PC2, while those
genotypes that are farther away from the origin are less stable for grain Zn content across
the P environments, these include genotypes 1, 4, 5, 6, 17, 25, and 29 (Figure 7). The vectors
of the P environments (levels) indicated positive correlations between grain yield and Zn
content because all the vectors of the P levels formed an acute angle. The level of P at HP
had the highest discriminating ability, while LP had the least, as shown by the length of
their vectors for grain yield, though for the grain Zn content, the LP and MP were more
discriminating over the HP (Figures 6 and 7).
 
Agronomy 2021, 11, x  Agronomy 2021, 11, 802 12 of 18 12 of 18
 
 
Figure 7.FGigeunorety 7p.e Gmeaninoteyfpfeec tmpaluins  Gefefneocty pleubsy GEennvoirtoynpme ebnyt (EGnGvEir)obnipmloetndt i(sGplGayEi)n gbitphleogt edniosptylpaeysinfogr tghrea igneZnno-content
at varyintgyspoeisl Pfolre vgerlasi.nF aZcnto crosn1taendt a2ta vreartyhienpgr isnociilp Pa llecovmelps.o Fnaecntoarxsi s1. aLnodw -2P a=ren tohPe apprpinlicciaptiaoln comf Pp2oOn5e, nMt edium-P =
10 kg P2Oax −15 ihsa. Lo,wan-Pd =H nigoh -PP a=p6p0likcgatPio2On 5ohf aP−2O1 f5o, rMfiedld-Pe v=a 1lu0a ktigo nP.2O5 ha−1, and High-P = 60 kg P2O5 ha−1 for 
field evaluation. 
4. Discussion
4. Discussion Increased performance of cowpea, as measured by indices of high dry matter yield
Increased p(sehrfooortm, raonotc,ea nodf ctotwalppela,n at sd rmyewaesiugrhetd), ibnyc rienadseicdecso onft ehnitgohf dphryo smphaottreurs y(Pie)lidn shoots in
(shoot, root, andt hteotsaclr epelnahnotu dsreys twudeyiguhsti)n, ginacsraenadse-ndu ctorinentetnsot louft ipohn.oHspighhorgurasi (nPy) iienld swhoaos tosb isne rved with
the screenhousea sntuindcyr euassiinngg sau spapnldy-onfuPtriinenthte sogrluowtiothn.m Hedigiah ignrtahien fiyeieldlde nwvairso onbmseenrvt.eTdh wis ictohr roborates
an increasing suspepvleyra ol fe aPr liine rthreep gorrtoswonthc omwepdeiaa’ sinre tshpeo nfiseeldto etnhve iardodnimtioennot.f TPhfeisr tciloizrerroubnodraetregsr eenhouse
several earlier raenpdorfitesl donco cnodwitipoenas’[s2 r7e–s3p0,o4n1,s4e2 ]t.oT thheeg aradidniZtinonco onft ep P
n tfoefrtcioliwzepre augnedneort ygpreeseenv-aluated in
this study showed no significant differences ( > 0.05) across the various P levels applied to
house and field tchoensdoiitli.oTnhsi s[2w7a–s3f0u,r4t1h,e4r2d].e Tmhoen sgtrraatiend Zbny ccoornrteelantti oonf acnoawlypseisa, wgehneoretygpraeisn eZvnacl-ontent had
uated in this stuadnyo snh-osiwgneidfi cnaon tsnigengaiftiicvaenats dsoicffieatrieonnc(ers= (p− >0 .02.,0p5=) a0c.3r)owssi tthhteh veahriigohursa Pte loefvPelasp plication
applied to the sociol.m Tphairse wdatso ftuhrethmeer ddieumoannsdtramteindi mbya lcsoorirlePlatriaotnes a. nTahlyesnise,g wathiveerea gnrdainno Zn-ns ignificant
content had a nornel-astiigonsifhiicpanbet tnweegeantihvieg hassooilcPiaatinodnZ (nr =co −n0t.e2n,t pi n=d 0ic.3a)te ws tihtha tththee rheigishn roattrea odfe oPf f between
application combpaalarendci ntog gthreea tmereydiieuldma nadndZ nmcionnimtenatl .sAocilh iPe vriantgesg.r eTahter nyeiegladtiwviet hanhidg hnPona-pplication
significant relataionndsdheipsi rbedetgwraeiennZ hnicgohn tseonitl aPre annodt  mZunt ucaollnytexnctl uinsidviec.aAtessi mthilaatr rthepeorert iosn ntwo o cowpea
tradeoff betweevna rbiaetliaenscwinitgh gdrifefaerteenr tyiailerleds paonnds eZtno  Pcofenrtteilnizta. tAiocnhsiheovwinegd gthraetahteigr hyPiefledr twilizitahti on, in the
high P applicatiaobns eanncedo df Zesniraepdp lgicraatiinon Z, wn acsoanssteoncita taerdew niotht Zmnudteufiaclileyn ceyxcsylumspivtoem. As, esvimeniltahro ugh there
report on two cwowaspneoa rveadruiecttiioens iwnitthhe dZinffceorenncetinatlr arteisopnoinnsteh etosh Po oftesrt[4il3iz].aOtitohne rsahuotwhoerds hthaavte reported
high P fertilizatithat higher rates of P supplied to cowpea led toaonnd, siene dth,eb uatbZsennccoen ocef nZtrna taiopnplwicaastiroend,u wceads a
asslionceiaarteindc rweaitshe iZn grain yield, P in leavesin leaves [44] and grna idnesf[i4c5ie].nIcnyc reasing P
symptoms, even though there was no reduction in the Zn concentration in the shoots [43]. 
Other authors have reported that higher rates of P supplied to cowpea led to a linear in-
crease in grain yield, P in leaves and seed, but Zn concentration was reduced in leaves 
[44] and grains [45]. Increasing P supply did not reduce Zn concentration of plant tissue 
in Brassica oleracea [46], where more shoot Zn concentration was seen in one genotype [47]. 
 
Agronomy 2021, 11, 802 13 of 18
supply did not reduce Zn concentration of plant tissue in Brassica oleracea [46], where more
shoot Zn concentration was seen in one genotype [47]. Earlier observations of increasing P
levels in soil with no reduction in the Zn concentration of non-Zn-supplied plants have
been reported in beans and potatoes [48], russet Burbank potato [49], and subterranean
clover [50].
The association between plant P and Zn concentrations has been a topic of investi-
gation by several researchers. Although, most agree that high P applications could lead
to the development of Zn deficiency symptoms in certain crop plants, but not necessarily
cause reduced Zn or P content of plant tissues [31,47,48]. In crops or genotypes where the
development of Zn deficiency or reduction in Zn content because of high soil P application
has been reported, providing optimum Zn nutrition in the growth medium can be used
to remedy the condition. This phenomenon has been described in several publications as
P-induced Zn deficiency [31,48,51]. The inverse relationship between P and grain Zn con-
centrations when a high rate of P is applied without Zn fertilizers supplied to the growth
media has been reported in maize [52,53], wheat [54,55], common beans [56], and numerous
other crops [57]. Though, contrary observations have been reported by Loneragan and
Webb [31], who provide evidence of a linear relationship between the Zn and P concen-
trations in cereals and citrus leaves treated with superphosphate fertilizers. Increased Zn
concentration with high P application in plants receiving no external supply of Zn has been
documented [31]. However, some authors have opined that such observations may have
been due to contamination of the superphosphate used. Nevertheless, in crops where an
antagonist relationship exists between high P rates and grain Zn content, application of Zn
fertilizer/nutrients have been reported to help remedy the situation [18,31,58–60].
In contrast to these results, we observed that a high rate of P applications had no
significant effect on the Zn content of cowpea genotypes investigated and did not cause
the appearance of Zn deficiency symptoms in cowpea. There are few reports on cowpea
addressing the relationship between high P application and Zn content of grains or other
edible parts [32]. The few reports of the plant P–Zn relationship on the crop are sometimes
confusing. Oseni [61] reported decreased Zn content of cowpea plants when P was applied
at high levels in the soil. While a more recent study on the impact of contrasting P rates and
constant level of N fertilizers on iron and Zn contents of cowpea grains made a contrary
observation. Ayeni et al. [32] observed that application of P alone at high rates does not
significantly decrease the content of Zn and Fe on cowpea grains, but a combination of
high P (60 kg/ha) and N was associated with reduced Zn content of the grains. The authors
provided some explanation for this observation, suggesting that the lack of a decrease in
Zn content when only high P rate was applied may be due to applied P being fixed in
certain soil compounds. However, application of N, a known element that could enhance
the early establishment of cowpea [62] and uptake of P from soil [63], may be responsible
for decreased Zn content when N and P fertilizers were applied at a high level.
Several mechanisms have been proposed to explain plant P–Zn interaction in which a
decrease in Zn content is observed in certain crops or genotypes when P application is at
the highest level in the growth media. One of the mechanisms responsible for P-induced Zn
reduction in plant tissues includes the following: First, increasing P supply to the growth
medium stimulates the growth of crop plants sufficiently to dilute the concentration of
Zn in plant tissues to levels that could induce a decrease in Zn availability. Second, the
high P supply could suppress either absorption of Zn by roots or translocation of Zn from
roots to shoots [31,57,64,65]. The lower value of grain Zn content in some genotypes at
high soil P may be due to decreased diffusion of Zn in the soil colloids [57,65]. Another
explanation for the high P–Zn reduced bioavailability is that, when both P and Zn are
limited in soil, application of high P rates tends to promote plant growth and this could
cause dilution in tissue Zn, which may further lead to reduced availability of Zn in plant
tissues [31]. Such observations have led to the belief that an imbalance in the ratios of
P–Zn in the growth environment may be responsible for the reduced Zn content observed
in some crops/genotypes when P is applied at a high rate [43]. Some authors have also
Agronomy 2021, 11, 802 14 of 18
observed the highest grain Zn concentration on fields where mineral N, P fertilizers, and
organic nutrient sources were applied [20].
In the present study, we observed that the “so-called” P-induced Zn reduction phe-
nomenon may be genotype-dependent because the relationship between the increased yield
due to high P application and Zn content revealed an insignificant negative association.
Earlier investigations have supported this. Susceptibility to P-induced Zn deficiency was
attributed to genetic differences and soil conditions in cowpea [20,43] and navy beans [51],
where varieties had varying efficiency to absorb and use nutrient constituents of the soil.
Various approaches have been used to achieve greater grain yield and Zn content in
soils with higher P application. These include the application of Zn fertilizers either as a
foliar spray [18] or applied directly to the soil [20,53,58], improved agronomic practices such
as integrated soil fertility management and intercropping, in which cereals can increase Zn
bioavailability of the soil and benefit the companion legumes [20,66], adopting multiple
strategies such as dietary diversification [20], which could mean supplementing cowpea
meal with high micronutrient-rich crops like common beans, a legume also rich in Zn
content [17,19], and cultivation of varieties with inherently high Zn concentration at any
soil P rates. Other researchers [32] have recommended application of medium P rates such
as 40 kg P2O5/ha even without application of Zn fertilizer to obtain high yield and Zn
content in the grains [30,44,61]. Application of Zn-containing fertilizers has been observed
elsewhere to increase cowpea’s grain Zn content and yield under integrated soil fertility
management [20].
Ayeni et al. [32] observed that some cowpea genotypes had a high content of Zn at
all levels of P, a finding similar to our observation in this study where certain genotypes
such as IT82E-18, UCR779, CB46, and IT97K-556-6 had increased grain Zn content with
increasing supply of P in the growth environment. This was confirmed by the GGE biplots
that displayed genotypes, such as 16 (IT89KD-288), 8 (Danila), and 22 (SAMPEA-9), with
high grain Zn content under high soil P fertilization, while genotypes such as 3 (58-77), 21
(SAMPEA-17), 22 (SAMPEA-9), and 23 (Sanzi) had stable grain Zn across all P levels. In
this study, we identified 3 very stable high-grain Zn-containing genotypes at high soil P
rate and 4 high-grain Zn genotypes across all the P levels based on site regression analysis
(SREG) biplot analysis [40]. Also, genotypes with high grain yield at all P levels were
identified. The use of GGE biplot analysis enabled us to visualize the genotypes and their
association with the different P rates (serving as environments) using biplots, which shows
genotypes that are high-performing for grain yield and grain Zn content at each P rate and
those that are most stable across all P levels [32,67]. The genotypes identified with high
grain Zn at a high P level should be tested in more locations to further substantiate this
finding and make possible recommendations for release to farmers as high Zn varieties.
5. Conclusions
There was wide variation for the P concentration and Zn content of cowpea geno-
types investigated. Increasing P fertilization leads to a significant increase in yield and
concentration of P in the shoots of the cowpea materials assessed. We conclude that since
no significant relationship between increased P fertilization and grain Zn content was
observed and high P fertilization is related to greater yield, there is no reason to not fertilize
with P at high levels. Increased grain yield under high P supply can be achieved without
sacrificing desired Zn content, especially if genotypes such as IT89KD-288, IAR-48, IT97K-
499-35, UCR779, CB46, IT97K-556-6, IT82E-18, and DanMisra, that do not show a negative
impact of decreased grain Zn content at high rates of P, are cultivated. The high-grain Zn
genotypes at high P fertilization can be used as parents in conventional or molecular plant
breeding pipelines for further improvement of grain Zn content in cowpea varieties that
are popularly grown in major producing areas.
Supplementary Materials: The following are available online at https://www.mdpi.com/article/
10.3390/agronomy11040802/s1, Figure S1: Phenotypic distribution of traits measured in the field
experiment at the vegetative stage under varying soil phosphorus levels. Box plot displays the
Agronomy 2021, 11, 802 15 of 18
median of each group bounded by the first and third quartile, with 1_LP = no-P application,
2_MP = 10 kg P2O ha−15 & 3_HP = 60 kg P O ha−12 5 . Figure S2: Correlation matrices for traits mea-
sured across varying soil phosphorus concentrations in the field experiment at the vegetative stage
(n = 30 genotypes). See Table 1 for list and abbreviations of the traits. Positive and negative as-
sociations between given traits are in blue and red, respectively. The color intensity and the size
of the circle are proportional to the correlation coefficients. On the X-axis of the correlogram, the
legend color shows the correlation coefficients and the corresponding colors. Figure S3: Scatterplot
showing weak correlations between pairs of traits from the field evaluation (a) Shoot dry weight (g)
and shoot Zn content (ppm) of high phosphorus treatment, R = −0.10; P = 0.58, (b) Soil available
phosphorus (mg/kg) and grain Zn content (ppm), R = −0.20, P = 0.29, (c) Grain yield (kg/ha) and
grain Zn content (ppm), R = 0.13, P = 0.47, (d) Grain phosphorus (mg/kg) and grain Zn content
(ppm), R = 0.02, P = 0.92. Each point represents an average of a genotype. Figure S4: Scatterplot
showing weak correlations between pairs of traits from the screenhouse evaluation (a) Shoot dry
weight (g) and shoot Zn content (ppm) of high phosphorus treatment, R = −0.43; P = 0.02, (b)
Shoot phosphorus (mg/kg) and shoot Zn content (ppm) of high phosphorus treatment, R = −0.20,
P = 0.29, (c) Root dry weight (g) and root Zn content (ppm) of high phosphorus treatment, R = −0. 30,
P = 0.11, (d) Root phosphorus (mg/kg) and root Zn content (ppm) of high phosphorus treatment,
R = 0.37, P = 0.04. Each point represents an average of a genotype. Table S1: List of cowpea genotypes
used and their origin/source, Table S2: Formulae used for computation of relative reduction (%),
phosphorus concentration, and zinc content of samples, Table S3: Means of genotypes for shoot
parameters measured in the screenhouse experiment under three soil phosphorus concentrations,
Table S4: Means of cowpea genotypes for shoot parameters measured in the field experiment under
three soil phosphorus concentrations, Table S5: Trait correlations between dry biomass yield, P and
Zn content of shoot and root of genotypes evaluated in the screenhouse under varying soil P rates,
Table S6: Trait correlations between grain yield, P and Zn content of shoot and grain of genotypes
evaluated in the field under varying soil P rates.
Author Contributions: Conceptualization, S.B.M., D.K.D., M.F.I., P.B.T., and V.G.; formal analysis,
investigation, writing—original draft preparation, S.B.M.; writing—review and editing, S.B.M.,
D.K.D., A.Y., M.L.U., M.F.I., P.B.T., and V.G.; supervision, D.K.D., M.F.I., P.B.T., and V.G.; funding
acquisition, S.B.M. All authors have read and agreed to the published version of the manuscript.
Funding: This research was partly funded by the Bill and Melinda Gates Foundation through the
Program for Emerging Agricultural Research Leaders (PEARL II) to the Ahmadu Bello University,
Nigeria, grant number “OPP1131397/INV-009560”, and The APC was funded by (OPP1131397/
INV-009560).
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: The data presented in this study are available within the article and as
Supplementary Material.
Acknowledgments: The present study was part of the PhD thesis of the first author. The first author
acknowledges the West Africa Agricultural Productivity Programme (WAAPP-Nigeria, a World Bank
Supported Intervention) for funding part of his PhD work. The authors are thankful to the team of
Technicians at the Cowpea Breeding Unit of the Institute for Agricultural Research Ahmadu Bello
University, Nigeria, for their assistance in conducting the experiments. The authors are grateful to
James D. Burridge and Mustafa Jibirn Ojonuba for their insightful comments.
Conflicts of Interest: The authors declare no conflict of interest.
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