Evaluating the Yield Response to Bio-Inoculants of Vigna unguiculata in the Kavango Region in Namibia

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Review Article Open Access
Luchen et al., J Plant Pathol Microbiol 2018, 9:10
DOI: 10.4172/2157-7471.1000456
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ISSN: 2157-7471
Research Article Open Access
Volume 9 • Issue 10 • 1000456
J Plant Pathol Microbiol, an open access journal
ISSN: 2157-7471
Keywords: Arenosols; Climate-change; Cultivars; Vigna unguiculata;
Cowpea, Bio-inoculants; Fertilizer; Bradyrhizobium; Yield
Introduction
ere is a general notion that the Kavango region could be the
“Breadbasket” of Namibia if the elds in the area could be productive
[1]. is belief is met with challenges due to the harsh climate and the
Kalahari sands (arenosols) that dominate most of the area. Terminalia
sericea species are dominant in this area and these trees have been known
to be an indication of poor sandy soils in an area [2]. e constraints
that aect agriculture in e Kavango are the same ones that aect most
of the Northern areas of Namibia [1], with poor nutrition status and
water retention of the soil, a variable climate and a far distance from
the market being the major ones. People’s main source of livelihood in
these area is small scale farming [3] despite the poor crop production
capacity of the porous soils, hence the need to intervene and study how
crops that are widely grown in these regions with harsh conditions can
be improved so as to contribute in increasing the fertility of the soils.
As the world’s population is on the verge of a dramatic increase that
will threaten food security, there is an important need of looking for
a long-term food security solution by selection of crops with that are
highly nutritious and are high-yielding [4]. erefore, plant breeders
and scientists at large are looking for a crop that can be enhanced or
is already adapted to the foreseeable biotic and abiotic environmental
changes [4]. With Southern Africa having the highest population of
undernourished people in the world [4], cowpea, which is one of the
major grain legumes in the region [5], is favourable to be explored to
prepare for this threatened food security. Legumes such as cowpea are
known to be raw materials that are important in the balancing of the
human diet due them being able to provide high proteins, vitamins,
minerals and an important source of carbohydrates according to
Kiim et al. [6]. ey have been known to have multiple physiological
eects such as the prevention of metabolic diseases like colon cancer
and diabetics and also in the reduction of blood and glucose levels
[7]. Vigna unguiculata has been reported to have a high amount of
organic matter and generally multiuse properties hence its use by
farmers as fodder to feed their animals [8]. Pennisetum glaucum (locally
known as mahangu), which is one of Namibia’s staple foods, is widely
cultivated in the Kavango region. ere have been reports of mahangu
yields in the area being lower than they were about 30 years ago [1]
due to decreasing soil fertility, therefore an urgent need to intervene is
required. Despite legumes having to be known to be of wide occurrence
during traditionally set cropping settings, they are also deliberately used
to manage the soil fertility by most small scale subsistence farmers [9].
Legumes do this by xing atmospheric nitrogen into ammonia by the
help of the nitrogenase enzyme and also by their incorporation into
cereal based cropping systems which result into them increasing the
soil fertility as was demonstrated by Zahran [10]. Nitrogen xation is
an important process for life forms on earth, biological processes such
as the use of legumes, x about 60% of the world’s nitrogen [10]. us,
this process is a major source of nitrogen into soils especially for arid
environments [11]. for example states that nitrogen xation by rhizobia
on soy bean production in Brazil results in an estimated save of about
US$ 10 billion annually instead of the use of chemical fertilizer, this is by
using Bradyrhizobium as a bio-inoculant. e outcome of this study will
be signicant in providing the subsistence farmers with bio-inoculants
that are able to eectively x biological nitrogen when in symbiosis with
cowpea under a climate of low rainfall. is will in turn increase prots
and crop productivity at large as less money will be spent on chemicals
in trying to enrich the poor soils in the regions and Namibia at large.
Materials and Methods
e study was conducted by obtaining cowpea cultivars from
Deutsche Gesellscha für Internationale Zusammenarbeit (GIZ),
these were namely (Figure 1) Nakare (Na), Lutembwe (Lu), I2, Bira
(Bi), Shindimba (Shi), and Silwana (Si) respectively. Cowpea strains
Evaluating the Yield Response to Bio-Inoculants of
Vigna unguiculata
in
the Kavango Region in Namibia
Charlie Chaluma Luchen1, Jean-Damascene Uzabikiriho1, Percy M Chimwamurombe2* and Barbara Reinhold-Hurek3
1Department of Biological Sciences, University of Namibia, Namibia
2School of Natural and Applied Health Sciences, Namibian Universities of Science and Technology, Namibia
3Faculty of Biology, Laboratory for General Microbiology, University of Bremen, Germany
Abstract
The Kavango region (Northern part of Namibia) were the study was carried out, is extensively involved in
agriculture and is also known to be dominated by the sandy aerosols soils. The bad soils in the region, which have
poor nutrients and water holding capacity, combined with a fast rate of climate change in the region has contributed
in the reduction in yield of most crops grown in the area. The main aim of the study was to determine cowpeas
response to bio-inoculants by assessing yield of the pulse. Six different cultivars of Vigna unguiculata (Cow pea)
were evaluated for their response to bio-inoculants. These cultivars were subjected to 3 different treatments. One
with chemical fertilizer, another with Bradyrhizobium strains (14-3) and (1-7) bio-inoculants and a third which was
a negative control with no treatment. After 90 days post seeding the cultivars were harvested and different yield
parameters assessed. The cowpeas that were subjected to the bio-inoculant treatments yielded a later grain yield in
kg per hectare as compared to the negative control and the fertilizer treatments. The outcome of this study therefore
provided the local subsistence farmers with a cheaper eco-friendly alternative to mineral fertilizers.
*Corresponding author: Percy M Chimwamurombe, School of Natural and Applied
Health Sciences, Namibian University of Science and Technology, Namibia, Tel: +264
61 2063358; E-mail: pchimwa@gmail.com
Received October 14, 2018; Accepted October 26, 2018; Published October 29, 2018
Citation: Luchen CC, Uzabikiriho JD, Chimwamurombe PM, Reinhold-Hurek B
(2018) Evaluating the Yield Response to Bio-Inoculants of Vigna unguiculata in the
Kavango Region in Namibia. J Plant Pathol Microbiol 9: 456. doi: 10.4172/2157-
7471.1000456
Copyright: © 2018 Luchen CC, et al. This is an open-access article distributed
under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original
author and source are credited.

Citation: Luchen CC, Uzabikiriho JD, Chimwamurombe PM, Reinhold-Hurek B (2018) Evaluating the Yield Response to Bio-Inoculants of Vigna
unguiculata in the Kavango Region in Namibia. J Plant Pathol Microbiol 9: 456. doi: 10.4172/2157-7471.1000456
Page 2 of 5
Volume 9 • Issue 10 • 1000456
J Plant Pathol Microbiol, an open access journal
ISSN: 2157-7471
that are resistant to the ‘witch weed’ Alectra vogelii, which according
to Mwaipopo [12] is a parasitic weed that is known to cause major
constraints on legumes and most especially cowpea, where obtained from
e International Crops Research Institute for the Semi-Arid Tropics
(ICRISAT) these were named I2. e cowpea was grown under rain
fed conditions so as to stimulate the natural environmental conditions
of the area. e eld was ploughed back and forth to homogenize the
plot on which the planting was done. It was divided into 3 sections,
with one section having a treatment of the 6 dierent cowpea cultivars
plus nitrogen fertilizer, the other section having the cowpea cultivars
plus bio inoculants and the third having only the cowpea cultivars
minus any other treatment. is design is illustrated in the diagram
below. e inoculant treatment was performed by getting a substantial
amount of bacterial inoculant strains called Bradyrhizobium (1-7) and
(14-3). e strains were grown fresh Modied Arabinose Gluconate
Medium, with peat as a carrier, then packed in Whirl-Pack® sample
bags. e bags were stored at room temperature with avoiding their
exposure to direct sunlight for long hours. Just before planting the bio
inoculant treatment, a small amount Polyvinylpyrrolidone (PVP-40)
was poured into 25 ml of distilled water. e PVP-40 was used because
it is sticky, hence it helped facilitate the sticking of the inoculant better
to the seeds. A Small can was used to mix the inoculant, one seed
cultivar and the PVP-40, all the six dierent cultivars were mixed this
way before planting. Urea was added on the soils were the nitrogen
fertilizer treatment was to be performed.
Yield assessment
Harvest data collection: e yield of the dierent cowpea cultivars
under the three categories of namely: Nitrogen fertilizer, Bio inoculant
and No treatment was assessed by comparing the physiological
maturity of the dierent cultivars with the above-named treatments.
is assessment was done by selecting 10 cow pea plants from the
middle rows of a subplot avoiding the border plants. ese were used to
calculate the root dry matter, grain and plant dry matter and converted
into yield per kilo hectare. Each subplot was expected to have has an
estimated 120 plants. With some subplots recording only about half
the amount or less during harvesting. is was due to some plants
not being so adapted to the local soils and environment in the region
and some having been dried up by the time the harvesting took place.
Spades were used to dig up the 10 plants from the middle section of
each subplot during the owering phase. is was done carefully to try
to excavate as many roots as possible attached to that plant. e none
inoculated plots were harvested rst and for those subplots that had
a few plants growing on them due to some having been dried or not
germinated, for these, less than 10 middle plants were harvested such
as 7 Nakare plants being excavated. is was followed by the harvesting
of the bio inoculant treatment plots. Nakare and Shindimba cultivars
had a few cowpea plants growing on the designated subplots during
harvesting hence only 5 middle plants of the bio inoculant treatment
were dug up. e nitrogen fertilizer treatment plant was the last to be
harvested.
Shoot biomass: e harvested middle plants had their shoots
separated from their roots. ese 10 shoots were then weighed
immediately with a balance and the shoot dry mass recorded. ey
were then dried in an open space in sunlight for 4 days. Aer the
drying, dry weight measurements of these shoots was recorded. ese
obtained measurements were used to extrapolate the shoot dry matter
yield per subplot and were carried out on all the plots.
Figure 1: Cowpea cultivars that were used in the study with their indigenous names. Scale bar=1 cm in all the pictures (a) to (f).
Figure 2: Depicting the cowpea study eld at Mashare just before harvesting.
Figure 3: Showing one Lutembwe shoot immediately after harvesting.

Citation: Luchen CC, Uzabikiriho JD, Chimwamurombe PM, Reinhold-Hurek B (2018) Evaluating the Yield Response to Bio-Inoculants of Vigna
unguiculata in the Kavango Region in Namibia. J Plant Pathol Microbiol 9: 456. doi: 10.4172/2157-7471.1000456
Page 3 of 5
Volume 9 • Issue 10 • 1000456
J Plant Pathol Microbiol, an open access journal
ISSN: 2157-7471
Grain yield: For the grain yield data collection, 10 randomly
excavated plants had their pod numbers counted. is was used to give
an average number of pods per subplot based on the number of plants
that were on that subplot. is was carried out for all plots. From these
pods, 40 were selected randomly and the number of seeds in these 40
pods counted to get the average seeds per pod. Lastly 100 seeds were
selected, from the seeds obtained from the 40 pods, and weighed to get
the 100 seed weight per subplot. e seed weight per subplot was also
recorded and the above procedure was done for all the subplots.
Results
Harvesting
All the subplots minus the destruction plots were harvested for
yield assessment. e samples consisted of roots, shoots and pods.
ey had to be weighed in grams immediately aer harvesting to get
the root and shoot wet weights, with a beam balance and a hanging
balance respectively.
Cultivar Name Shoot wet
weight (g)
Shoot dry
wet (g)
Plant dry matter
yield (kg/ha)
Root wet
weight (g)
Root dry
weight (g)
Root dry matter
yield (kg/ha)
Grain yield
(g)
Grain yield (kg/
ha)
NAKARE Average Yield 383.33 225.21 1501.89 138.73 70.17 4678.22 2273.23 1262.9
SILWANA Average Yield 1125 225 15000 109.055 33.7525 2250.17 2401.86 1334.37
SHINDIMBA Average Yield 300 360 24000 339.24 80.31 5354.22 273.18 151.77
LUTEMBWE Average Yield 2500 1264.71 84313.9 105.3 27.65 1843.33 3560.66 1978.14
BIRA Average Yield 1800 990 66000 158.38 35.5 2366.33 4270.64 2372.58
Table 1: Average yield data per subplot from the negative control (non-inoculated plot).
Cultivar Name Shoot wet
weight (g)
Shoot dry
wet (g)
Plant dry matter
yield (kg/ha)
Root wet
weight (g)
Root dry
weight (g)
Root dry matter
yield (kg/ha)
Grain yield
(g)
Grain yield
(kg/ha)
LUTEMBWE. Fertiliser Average Yield 2600 732.73 48848.58 118.905 32.53 2168.5 2264.78 1258.21
SHINDIMBA. Fertiliser Average Yield 517 517.5 34500 147.3 33.39 2226 463.97 257.76
NAKARE. Fertiliser Average Yield 966.67 172.07 11471.11 236.5 40.07 2671.33 1873.42 1040.79
SILWANA. Fertiliser Average Yield 2000 600 40000 110.28 29.13 1942.16 3703.37 2057.43
BIRA. Fertiliser Average Yield 2550 493 32866.67 104.38 39.7 2646.65 2460.98 1367.21
NIGERIAN Cultivar. Fertiliser Average Yield 350 105 7000 54.47 13.13 875.58 1652.95 918.31
Table 2: Showing the average yield data for the Subplots with fertilizer treatment.
Cultivar Name Shoot wet
weight (g)
Shoot dry
weight (g)
Plant dry matter
yield (kg/ha)
Root wet
weight (g)
Root dry
Weight (g)
Root dry Matter
yield (kg/ha)
Grain
yield (g)
Grain yield
(kg/ha)
LUTEMBWE+Bradyrhizobium stain 1-7
Average Yield 2100 966 64400 146.615 40.4025 2693.5 4901.745 2723.191667
LUTEMBWE+Bradyrhizobium strain 14-3
Average Yield 2350 1272.9175 84861.17 135.725 43.775 2918.33 4922.36 2734.64
NAKARE+Bradyrhizobium strain 14-3
Average Yield 850 578 38533.33 209.73 99.46 6630.67 8118 4510
NAKARE+Bradyrhizobium stain 1-7
Average Yield 300 427.5 28500 130.225 62.465 4164.33 4918.5 2732.5
SHINDIMBA+Bradyrhizobium stain 1-7
Average Yield 175 159.25 10616.67 188.8 53.32 3554.67 2921.4 1623
SILWANA+Bradyrhizobium stain 1-7
Average Yield 1900 1148.635 76575.67 129.95 49.965 3331 7185.49 3991.94
SILWANA+Bradyrhizobium strain 14-3
Average Yield 2300 1086.11 72407.33 168.425 41.985 2799 5844.51 3246.95
BIRA+Bradyrhizobium stain 1-7 Average
Yield 550 403.335 26889 129.82 31.75 2116.67 3324.88 1847.16
BIRA+Bradyrhizobium strain 14-3
Average Yield 1100 407 27133.33 142.76 35.905 2393.67 2664.01 1480.01
Table 3: Showing the yield data from the bio-inoculant treated plots.
Dependent variable: Plant_Dry_Matter_Yield
Source Type III sum of squares df Mean square F Sig. Partial Eta
squared
Corrected Model 39886390060.000a15 2659092671 4.194 0 0.572
Intercept 73585686100 1 7.3586E+10 116.055 0 0.712
Treatment 1076062735 2 538031367 0.849 0.434 0.035
Cultivar_Name 20984435470 5 4196887093 6.619 0 0.413
Treatment * Cultivar Name 13659285540 8 1707410693 2.693 0.016 0.314
Error 29800844500 47 634060521 -- -- --
Total 1.78973E+11 63 -- -- -- --
Corrected Total 69687234570 62 -- -- -- --
a.R Squared=0.572 (Adjusted R Squared=0.436)
Table 4: Tests of between-subjects’ effects (Plant_Dry_Matter_Yield).

Citation: Luchen CC, Uzabikiriho JD, Chimwamurombe PM, Reinhold-Hurek B (2018) Evaluating the Yield Response to Bio-Inoculants of Vigna
unguiculata in the Kavango Region in Namibia. J Plant Pathol Microbiol 9: 456. doi: 10.4172/2157-7471.1000456
Page 4 of 5
Volume 9 • Issue 10 • 1000456
J Plant Pathol Microbiol, an open access journal
ISSN: 2157-7471
Shoot biomass yield
e dry matter yield of the shoots was compared amongst the
three treatments of fertilizer, bio-inoculant and a negative control
of no treatment to gure out (Figure 2) which was more eective by
measuring the yield. e tables (Tables 1-3) that follow are the results
of these comparisons in terms of the shoots, roots and the grain yield
of each cultivar planted.
Data analysis
A 2-Way Anova was carried out on the above datasets of namely:
Shoot Dry Matter Yield (kg/ha), Root Dry Matter Yield (kg/ha) and
Grain yield (kg/ha) aer the Anova assumptions were met. is
Analysis of variance tested the hypotheses below.
1. H0: ere is no signicance dierence in the Shoot, Root and
Grain yields across the 3 dierent treatments.
2. H0: ere is no signicant dierence in the Shoot, Root and
Grain yields across the dierent cultivars.
e p-value of treatment to Plant dry matter yield is 0.434, meaning
there is no statistical dierence between the treatments and shoot
biomass yield at the 0.05 level of signicance. On the other hand there
is a statistical dierence between Cultivar name and Plant Dry Matter
Yield and the interaction between Treatment and cultivar name at the
0.05 level of signicance with p values of 0.00 and 0.016 respectively.
e pairwise comparisons of the cultivars is shown in the Annex
(Table 4). erefore, there is insucient evidence to reject the rst null
hypothesis and enough evidence to reject the second null hypothesis.
Indicating a signicant dierence in Plant Dry Matter yield across the
six dierent cultivars.
Grain yield
For the grain yield statistical analysis, there is a statistical dierence
across the means of the dierent treatments and cultivar names at the
0.05 level of signicance with p-values of 0.00 and 0.009 respectively.
On the contrary there is no statistical dierence in means of the
interaction of Treatment and Cultivar name with grain yield with a
p-value of 0.059. erefore for Treatment and Cultivar name, the null
hypotheses that state:
1. H0: ere is no signicance dierence in the Grain yields across
the 3 dierent treatments.
2. H0: ere is no signicant dierence in the Grain yields across
the dierent cultivars.
Are rejected at the 0.05 level of signicance (Table 5).
Discussion and Conclusion
Yield in terms of shoot biomass
It is of utmost importance to assess the yield of the performed
treatments and how these yield components respond so as to reach
a conclusion as to which treatment would best suit a farmer’s needs.
From the yield assessment of the dierent cowpea cultivars in terms of
plant dry matter yield, there is no statistical dierence in the obtained
plant dry matter measurements across the three dierent treatments
with a p > 0.05, this is despite there being an observed dierence in
the obtained mean values of the treatments. is study’s ndings
in this regard correlates to a study done by Hungria et al. [13], who
reported that the use of mineral fertilizer did not have any signicant
eect on the shoot dry biomass when applied at recommended rates
but resulted in a signicant increment when applied at 1.5 times the
recommended amounts. ese obtained results indicate that the use
of nitrogen fertilizer to enhance shoot biomass of the bean is not
benecial. Andrade et al., [14] States that previous studies on soybean
that was treated with nitrogen fertilizer, did not indicate any benets as
compared to the application of bio-inoculants on the soybean grown in
Brazilian soils. With respect to the dierent cultivars’ relation to plant
biomass yield, it was observed that the obtained yield measurements
diered signicantly depending by the type of cultivar used with a
signicant p-value less than 0.05. When subjected to all the three
dierent treatments, the cultivar Lutembwe had the largest plant dry
yield per hectare as compared to the other cultivars (Figure 3). Hence
for farmers that would like to grow cowpea for forage use, this would
be the recommended cultivar. is is seconded by Silwana followed
by Bira, with the Nigerian cultivar not faring well in terms of shoot
yield as compared to the other cultivars. is poor performance of the
cultivar could be attributed to it not natively grown in the Southern
African soils hence the poor yield. With regards to the interaction
between cultivar name and the type of treatment and their eect
on shoot dry matter yield, at the 0.05 level of signicance, there is a
signicant interaction between the factors and the shoot dry matter
yield of 0.016. e cultivars Lutembwe and Nakare had a poor shoot
dry matter yield with the fertilizer treatments with Bira and Shindimba
reporting the lowest shoot dry matter yield with the bio-inoculant
treatment while Silwana and Nakare reported the highest yield with
bio-inoculant. e Nigerian cultivar was only subjected to the fertilizer
treatment. erefore with regards to the shoot biomass, with fertilizer
treatment maximum yield is achieved by Lutembwe, while with bio-
inoculant maximum yields are achieved by the cultivar Silwana. Such
information is handy when cowpea is cultivated for its shoot biomass
with an indication that the use of fertilizer when cultivating cowpea for
this purpose is non-protable.
Dependent variable: Grain_Yield
Source Type III Sum of Squares df Mean Square F Sig. Partial Eta Squared
Corrected Model 61400644.780a15 4093376.319 4.758 0 0.603
Intercept 163213020.9 1 163213020.9 189.721 0 0.801
Treatment 22438450.78 2 11219225.39 13.041 0 0.357
Cultivar_Name 14938031.29 5 2987606.259 3.473 0.009 0.27
Treatment *Cultivar_Name 14217142.25 8 1777142.782 2.066 0.059 0.26
Error 40433110.91 47 860278.956 -- -- --
Total 308977495.6 63 -- -- -- --
Corrected Total 101833755.7 62 -- -- -- --
a.R Squared=.603 (Adjusted R Squared=.476)
Table 5: Tests of between-subjects’ effects (Grain_Yield).

Citation: Luchen CC, Uzabikiriho JD, Chimwamurombe PM, Reinhold-Hurek B (2018) Evaluating the Yield Response to Bio-Inoculants of Vigna
unguiculata in the Kavango Region in Namibia. J Plant Pathol Microbiol 9: 456. doi: 10.4172/2157-7471.1000456
Page 5 of 5
Volume 9 • Issue 10 • 1000456
J Plant Pathol Microbiol, an open access journal
ISSN: 2157-7471
Grain yield
Cowpea grain yield is considered one of the most important
parameters for farmers in terms of assessing how dierent treatments
aect yield [15]. is is due to the proteins having a high protein
content for consumption [14] in addition, the more the grain yield
the more prots the farmers expects from the legumes and also this
entails the farmer has a surplus to plant for the next season. ere
is a signicant dierence in the means of the dierent treatments
and cultivars with relation to the grain yields. Our study reviewed
a signicant mean dierence of 1604.14 based on the post hoc tests
between the fertilizer treatment and the bio-inoculant treatment, with
the bio-inoculant recording a higher grain yield. is is more than a
10% increase in grain yield which is a substantial as an indication that a
treatment is working according to Ronner et al. [16]. Our ndings are
close to the 30% increase in grain yield by bio-inoculant application
reported by Martins et al. [17]. If a farmer’s aim is to increase the grain
yield of their cowpea then it’s recommended to use bio-inoculant as
opposed to mineral fertilizer because not only is it eco-friendly but also
is a cheaper alternative, this is supported by our ndings. In addition
to this, the cultivars Silwana, Nakare and Lutembwe gave the largest grain
yield with the bio-inoculant treatment with yields of 3619.45, 3621.25
and 2728.92 kg/ha respectively. Shindimba had the lowest grain yield,
a less lower than the Nigerian cultivar. erefore outcome of this study
is signicant in providing the subsistence farmers with bio-inoculants
that are able to eectively x biological nitrogen when in symbiosis with
cowpea under a climate of low rainfall. is will in turn increase prots and
crop productivity at large as less money will be spent on chemicals in trying
to enrich the poor soils in the regions and Namibia at large.
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