Introduction
Cowpea (Vigna unguiculata L.) is a protein-rich grain that complements
staple cereal and starchy tuber crops. Cowpea is commonly used as a companion
crop in many intercrop systems in sub-Saharan Africa (SSA), because of its
ability to provide fixed atmospheric nitrogen to cereal crops in rotation
(Asiwe 2009).
Many smallholder farmers in Limpopo Province practise intercropping of
maize (Zea mays L.) with legumes to
reduce the risk of crop failure, and enhance their production. Cereal-legume
intercropping is commonly practised in South Africa, including the Limpopo
Province, because of its yield advantage, greater stability, and lower risk to
crop failure compared to monoculture (Kermah et al. 2017). Several research works have been reported recently on
cereal-legume intercropping systems in South Africa and elsewhere. These
include maize and pigeonpea (Kiwia et al.
2019); maize and dry bean (Phaseolus vulgaris L.) intercropping (Kutu and Asiwe 2010; Nthabiseng et al. 2015); and wheat (Triticum
aestivum L.)-canola (Bracica juncea L.) intercropping (Khan et al. 2012; Tripathi et al. 2016). The traditional practice of farmers in Limpopo Province is the mixed
intercropping, whereby crops are broadcasted at planting without definite row
arrangement (Mucheru-Muna et al.
2010). Mixed intercropping hinders farm input application, results in
non-optimal plant population (Mahapatra 2011), as well as intra and inter
species competition (Muhammad et al.
2008; Chitra and Shrestha 2014), which lead to low crop yield and poor return
on investment. This practice is not sustainable and economically viable.
Therefore, farmers in Limpopo Province are in dire need of an innovative
intercropping system that is more sustainable and profit-oriented. Strip
intercropping is a promising intercropping system where crops are planted with
definite row arrangement, and has the potential of reducing inter-species
competition, optimising plant population, and increasing crop yield and cash
return (Singh and Ajeigbe 2007; Iderawumi and Friday 2013). The hypothesis of the study was to investigate whether the
performance of the novel strip intercropping system would be better than or
same as the traditional mixed intercropping currently being practised by
farmers. Therefore, the objective of the study was to assess the performance
and economic feasibility of five improved cowpea varieties under a cowpea-maize
strip intercropping system compared to mixed intercropping system in Limpopo
Province, South Africa.
Materials and Methods
Description of the study area
The study was conducted at the
University of Limpopo’s (23°53’ 9.6” S, 29°43’ 4.8” E and 24°01’ 59” S, 29°47’
56” E, respectively) Experimental Farm (UL-Farm’s) during 2015–2016 and 2016–2017.
The site is characterised by erratic low rainfall, which ranges between 450 and
650 mm per annum, and falls predominantly during summer (Table 1).
Experimental materials
This consisted of
five cowpea varieties (Glenda (check), IT87K-499-35, IT82E-16, IT86D-1010, and
TVu-13464, a maize cultivar, and PAN 6479, obtained from PANNAR Seed Ltd.,
South Africa). The cowpea varieties were obtained from the gene bank of the
University of Limpopo, South Africa.
Treatments
The experiment was
laid out following randomized complete block design under split plot arrangement
with three replications. The main plot factor was cropping system (intercrop
and monocrop; the mono and mixed cropping systems were included as standard
control practices) and the subplot factor was the varieties (‘Glenda’ (check),
‘IT87K-499-35’, ‘IT82E-16’, ‘IT86D-1010’, and ‘TVu-13464). The maize cultivar was planted at a spacing
of 0.9 m × 0.3 m with 4 m row length, giving a plant population of 52 and 40
plants per intercrop plot for maize and cowpea, respectively; and each plot
area was 5.6 m × 4.0 m. The intercrop plots consisted of four rows of cowpea,
sandwiched between two rows of maize. The monocrop plots consisted of six rows
of cowpea and maize planted at an inter-row spacing of 0.75 m × 0.2 m and 0.9 m
× 0.3 m, respectively. The net plot for each intercrop was 4.8 × 4.0 m, while
that for monocrop (maize) was 4.8 m × 4.0 m, and 3.0 m × 4.0 m for the cowpea monocrop.
Crop management
The land was conventionally
tilled with tractor-mounted implements (disc plough and harrow) to enhance
germination and seedling emergence. The
trial was planted on 11 January 2016 during the 2015–2016
cropping season; whereas during the 2016–2017, it was planted on 13 December
2016. Roundup (isopropyl amine salt of
glyphosate) and Dual (S-Metalachlor) were applied at the rates of 3 L ha-1
and 0.5 L ha-1, respectively, to control weeds before crop
emergence. Manual weeding was subsequently conducted to control emerged weeds.
Karate (Lambda-Cyhalothrin) and Aphox (Pirimicarb) were applied at the rate of
1 L ha-1 and 500 g ha-1 to control insect pests (blister
beetles, aphids, and pod-sucking bugs) on cowpea from seedling stage until pod
maturity. The trial was conducted under rain-fed conditions, and no fertilisers
or irrigation were applied. Soil samples were collected from the experimental
area, and the results of the analysis are shown in Table 2. The
organic carbon, matter and available P were too different during the two years
probably because the plots used during the two years were separate and
different.
Data collection
The following parameters were
measured in the same way during the two seasons to achieve the research study
objectives. The number
of days to 50% flowering was determined by counting the number of days from the
date of plant emergence to the date that 50% of the plant population in each
plot flowered. The number of days to 90%
maturity was calculated by counting the number of days from plant emergence
date to the date that 90% of
the plant population in each plot matured. Plant height was
determined by measuring the height of five plant samples with a meter rule.
Plant harvesting
Five plants from each plot were
sampled randomly at maturity and total number of pods of these plants was
counted and averaged to record number of pods/plants. The cowpea varieties were
harvested in May of each year. For grain yield, sun-dried samples were
harvested from four middle rows of each plot and threshed manually to obtain
grain yield per plot. Weight of grains per plot was determined by weighing the
grains on an electronic weighing balance, and the net yield was converted to kg
ha-1 using the following formula:
Grain yield = (grain weight [kg])/ (area harvested [m2])
×10000 m2
Maize grain was taken at maturity after
harvesting the cobs. The yields were determined by weighing the grain from each
net plot; and the weight was converted into
kg/ha using the following formula:
Grain yield = (grain weight [kg])/ (area harvested [m2])
×10000 m2
Assessment of intercrop productivity
For the assessment of the LER,
the relative yields of cowpea and maize with their sole treatments were
determined by using the following formulae (Mead and Willey 1980):
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Data analysis
Data collected during the two
seasons were subjected to an analysis of variance technique using the Genstat
18 Version software to check the overall significance of data. Means that
showed significant differences were separated using Duncan's new multiple range
test (MRT) at P ≤ 0.05 (Steel et al. 1997).
Economic analysis
A benefit-cost analysis was
conducted to estimate the economic achievements of the different crop mixtures
in the intercropping systems. The production costs of cowpea and maize included
the cost of field preparation, seed, sowing, crop protection measures,
harvesting, and processing. The total cost or revenue was estimated using the
prevailing average market prices in Rand for the grain yield of cowpea and
maize in South Africa. The amount in Rand was converted to USD$ by dividing
with the average exchange of 14.01 ZAR/$. The total profit was calculated by
subtracting the total cost from the total revenue, while the benefit-cost ratio
(BCR) was calculated by dividing the total revenue by the total cost.
Results
The results showed that interactions between
varieties and cropping system were significant (P ≤ 0.05) for most of the variables except plant height
(during 2017) (Table 3). During the 2015/2016 season, varieties planted in the
mixed intercropping plots flowered later than strip intercropping or
monocropping. However, during 2016/2017, varieties planted in the mixed
intercropping plots were the earliest to flower, followed by strip
intercropping and monocropping. Similar trend was observed for the maturity of
the varieties among the cropping systems. Maturity was later in the mixed
intercropping than strip intercropping or monocropping. During 2017, mixed
intercropping matured earlier than strip intercropping or monocropping. Results also show that plant height was observed to be shorter among
plants in the mixed intercropping followed by strip intercropping. Varieties in
the monocrop plots exhibited the tallest plants (Table 3). However, during
2017, no significant interaction was observed between varieties and cropping
systems. The number of pods obtained from strip intercropping plots during 2015–2016
was highest followed by monocropping, and the lowest was obtained from mixed
intercropping. However, during 2016–2017 season, mixed intercropping exhibited
the highest number of pods followed by strip intercropping and monocropping.
With respect to grain yield, the interaction results showed that during both
seasons (Table 3) grain yield was consistently highest in the monocrop plots,
followed by strip intercropping, while mixed intercropping achieved the lowest
yield. Maize grain yield was significantly lower in mixed intercropping
compared to strip intercropping or monocropping during both seasons (Table 3).
There were no significant (P ≤
0.05) interactions observed between the varieties in the crop mixtures and
cropping systems for LER during 2016–2017 while the effect was significant
during 2015–2016 (Table 4). Higher LER were obtained from strip intercropping
which was consistently higher than that obtained from mixed intercropping and
monocropping (Table 4).
Table 1: Mean monthly rainfall, and minimum and maximum
temperatures during both seasons
|
Months |
Minimum temperature (ºC) |
Maximum temperature (ºC) |
Total rainfall (mm) |
|||
|
2016 |
2017 |
2016 |
2017 |
2016 |
2017 |
|
|
Dec
|
- |
16.9 |
- |
27.2 |
- |
120.9 |
|
Jan
|
17.0 |
12.1 |
28.6 |
25.3 |
87.4 |
101.7 |
|
Feb |
17.6 |
12.2 |
29.1 |
24.6 |
57.9 |
40.3 |
|
Mar |
15.7 |
06.0 |
28.1 |
24.0 |
126.7 |
23.1 |
|
Apr |
11.6 |
9.67 |
26.2 |
23.5 |
5.3 |
30.4 |
|
May |
13.5 |
3.4 |
25.8 |
21.4 |
1.0 |
11.4 |
|
Jun |
7.4 |
5.43 |
19.1 |
19.7 |
3.2 |
1.04 |
Source: Agricultural Research Council - ISCW and the
University of Limpopo Weather Station
Table 2: Pre-sowing physio-chemical analysis of soil in both seasons
|
Soil attributes |
2015-2016 |
2016-2017 |
|
Clay |
3 |
2 |
|
Silt |
13 |
14 |
|
Sand |
84 |
84 |
|
Textural class |
Sandy loam |
Sandy loam |
|
Chemical composition |
||
|
pH |
7.4 |
8.2 |
|
Organic carbon
(%) |
1.84 |
0.58 |
|
Organic matter
(%) |
3.17 |
1.00 |
|
Available P
(mg/kg) |
2.05 |
1.19 |
|
Ammonium N
(mg/kg) |
0.95 |
0.79 |
|
Nitrate N
(mg/kg) |
0.19 |
0.16 |
*P= Phosphorus; N= Nitrogen
Economic analysis showed that revenue obtained was a function of the
varieties’ yield, and the variation was significant (P ≤ 0.05) among varieties and cropping systems (Table 5). The
highest profits were obtained from crop mixtures of ‘IT86D-1010’ with maize
followed by the ‘IT82E-16’ mixture and ‘IT87K-499-35’ with maize as strip
intercropping while the lowest revenue was obtained from Glenda during both
seasons. Likewise, strip intercropping of cowpea varieties ‘IT86D-1010’ and
‘IT82E-16 with maize provided the highest profit and benefit-cost ratio
followed by monocropping, and the lowest profit and benefit-cost ratio were achieved
from mixed intercropping (Table 5).
Discussion
Table 3: Interactive effect of intercropping systems and cowpea varieties on days
to 50% flowering, 90% maturity and yield component of cowpea, and maize yield
|
Varieties |
201–2016 |
2016–2017 |
||||
|
Mono
cropping |
Strip
intercropping |
Mixed
intercropping |
Mono
cropping |
Strip
intercropping |
Mixed
intercropping |
|
|
Number of days taken to complete 50% flowering
(days) |
||||||
|
Glenda |
53.00c |
53.00c |
53.00c |
60.67a |
60.00a |
51.67ab |
|
IT82E-16 |
50.33cd |
51.33cd |
53.00c |
51.33ab |
51.67ab |
51.67ab |
|
IT86D
-1010 |
53.33c |
52.67c |
53.00c |
52.33ab |
52.00ab |
51.50ab |
|
IT87K-499-35 |
58.67a |
56.67ab |
53.00c |
50.67ab |
50.57ab |
51.67ab |
|
TVu
13464 |
47.67d |
51.00cd |
53.00c |
48.67bc |
48.67bc |
51.48ab |
|
Number of days taken to complete 90% maturity
(days) |
||||||
|
Glenda |
88.67bc |
91.67ab |
94.00a |
103.67a |
103.67a |
85.67d |
|
IT82E-16 |
85.33c |
82.67cd |
94.00a |
98.00bc |
98.00bc |
85.67d |
|
IT86D
-1010 |
86.00c |
85.00c |
94.00a |
88.00cd |
88.00cd |
84.50d |
|
IT87K-499-35 |
95.00a |
91.00ab |
94.00a |
101.33ab |
101.00ab |
85.67d |
|
TVu
13464 |
82.00cd |
82.00cd |
94.00a |
94.00c |
96.33c |
86.81d |
|
Plant height (cm) |
||||||
|
Glenda |
54.27c |
57.73ab |
40.53de |
59.60NS |
51.80 |
39.00 |
|
IT82E-16 |
54.4c |
51.2cd |
40.53de |
35.87 |
34.47 |
39.00 |
|
IT86D
-1010 |
61.73a |
47.33d |
40.53de |
33.40 |
38.07 |
36.20 |
|
IT87K-499-35 |
52.2cd |
60.13a |
40.53de |
41.07 |
41.27 |
39.00 |
|
TVu 13464 |
39.8de |
39.93de |
40.53de |
29.60 |
29.53 |
39.95 |
|
Number of pods per plant |
||||||
|
Glenda |
14.63bc |
15.31bc |
14.00c |
9.33c |
9.73c |
16.13a |
|
IT82E-16 |
16.57ab |
18.77a |
14.00c |
10.87bc |
12.13ab |
16.13a |
|
IT86D
-1010 |
16.47ab |
17.55a |
14.00c |
9.40c |
9.53c |
17.20a |
|
IT87K-499-35 |
14.80bc |
16.25ab |
14.00c |
10.47bc |
12.07ab |
16.13a |
|
TVu
13464 |
16.07ab |
11.20 |
14.00c |
8.27cd |
7.67cd |
15.83a |
|
Grain yield (kg ha-1) |
||||||
|
Glenda |
1205bc |
635de |
157e |
715c |
573d |
390e |
|
IT82E-16 |
1995a |
1140c |
157e |
1265a |
1025ab |
390e |
|
IT86D
-1010 |
1525ab |
1052c |
157e |
1075ab |
1124a |
335e |
|
IT87K-499-35 |
920cd |
815d |
157e |
1280a |
887bc |
390e |
|
TVu
13464 |
905cd |
850d |
157e |
760c |
680cd |
409e |
|
Maize grain yield (kg ha-1) |
||||||
|
PAN
6479 |
3112a |
2996a |
1320b |
3237a |
3564a |
2237b |
Means,
with in columns and rows for each trait, with same letters are statistically
similar with each other according to DNMR test at P ≤ 0.05
NS=
Non-significant
Table 4: Interactive effect of intercropping systems and cowpea varieties on land equivalent
ratio
|
Crop mixtures |
2015–2016 |
2016–2017 |
||
|
Strip intercropping |
Mixed intercropping |
Strip intercropping |
Mixed intercropping |
|
|
Glenda + PAN 6479 |
1.25c |
0.56d |
2.29NS |
1.32 |
|
TVu 13464 + PAN 6479 |
1.48b |
0.61d |
1.81 |
1.13 |
|
IT82E-16 + PAN 6479 |
1.58a |
0.50d |
1.98 |
1.00 |
|
IT86D -1010 + PAN 6479 |
1.65a |
0.54d |
1.97 |
1.07 |
|
IT87K-499-35 + PAN 6479 |
1.59a |
0.60d |
2.15 |
1.04 |
Means,
with in columns and rows for each trait, with same letters are statistically
similar with each other according to DNMR test at P ≤ 0.05
NS=
Non-significant
Table 5: Interactive effect of intercropping systems
and cowpea varieties on net income and BCR
|
Crop mixture |
Maize RY yield (kg ha-1) |
Maize revenue (US$ ha-1) |
Cowpea RY (kg ha-1) |
Cowpea revenue (US$ ha-1) |
Total revenue (US$ ha-1) |
Total cost (US$ ha-1) |
Total profit (USD$ ha-1) |
BCR |
|
Glenda + Pan 6479 |
2638.5 |
1412.5 |
604.0 |
1724.5 |
3137.0 |
1302.9 |
1834.0 |
2.41 |
|
IT82E-16 + Pan 6479 |
2872.0 |
1537.5 |
1082.5 |
3090.7 |
4628.1 |
1653.0 |
2975.2 |
2.80 |
|
IT86D -1010 + Pan 6479 |
2797.0 |
1497.3 |
1088.0 |
3106.5 |
4603.7 |
1612.5 |
2991.2 |
2.86 |
|
IT87K-499-35 + Pan 6479 |
2686.0 |
1437.9 |
851.0 |
2429.7 |
3867.6 |
1497.8 |
2369.8 |
2.58 |
|
TVu 13464 + Pan 6479 |
2733.0 |
1463.1 |
765.0 |
2184.2 |
3647.2 |
1453.3 |
2193.9 |
2.51 |
|
Mixed cropping |
1778.5 |
952.1 |
269.9 |
770.6 |
1722.7 |
968.2 |
754.5 |
1.78 |
|
Monocropping |
3174.5 |
1699.4 |
1164.5 |
3324.8 |
5024.2 |
2324.3 |
2699.8 |
2.16 |
*BCR=
Benefit-cost ratio; 1 US$= 14.01 ZAR
Results of the study indicated that strip
intercropping performed significantly better than the mixed intercropping with
respect to grain yield, LER and net returns (Table 3–5) and have great
potential or attributes of improving the livelihood of farmers in Limpopo
Province. The performance of any crop variety in any environment or cropping
system is interplay of the variety’s genetic characteristics which are
expressed through the crop’s physiological and morphological attributes to take
advantage of the resources supplied by the environment or the cropping system.
In this study, we obtained significant interactions between the varieties and
the cropping systems for most variables measured (the number of days to 90%
physiological maturity, plant height, number of pods per plant, grain yield and
profit). This is an indication that the cropping systems influenced the
performance of the cowpea varieties. The earliness to flower and physiological
maturity are phenologically linked to enable the plant produce, and avoid
losses associated with pests, drought or frost damage. In this study, we found
that cowpea varieties flowered and matured differently among the cropping
systems. This will offer the farmers the opportunity to make selection among
the cowpea varieties, as well as giving them the empirical data to make an
informed decision regarding the adoption of strip intercropping. For instance,
farmers can select promising varieties that flower
and mature early in the strip intercropping to prevent drought and frost
damage. In this regard, ‘TVu 13464’ which attained earlier maturity in all the
cropping systems during 2015–2016 and 2016–2017 than the local variety Glenda
is an ideal variety for drought or pest evasion, as well as indicating that it
is well adapted to mature early under the strip intercropping systems (Idahosa et al. 2010; Agoyi et al. 2017). Varieties that exhibit late maturity are known to be
more vulnerable to drought and frost damage (Agbogidi and Egho 2012; Mafakheri et al. 2017).
The variations among the cowpea
varieties in the yield components especially, the plant height, and the number
of pods per plant as well as the grain yield point to the fact that the
cropping systems influenced the performance of inherent genetic characteristics
of the varieties, which were translated to their abilities to adapt to the
environments (Fery 1985; Ichi et al. 2013). The cropping systems
performed differently because the systems were able to discriminate the
abilities of the varieties to compete for growth resources such as light,
water, nutrients, space, and time. The results of this study corroborate the
findings of past reports (Nwosu et al.
2013; Agyeman et al. 2014; Zerihun et al. 2016). Cropping systems (strip intercropping and monocropping) that
supported higher plant height and pod numbers consistently produced higher
grain yield, except during 2016–2017, when the number of pods was higher under
mixed intercropping due to irregular plant density or no patterned plant
arrangement, which led to less optimal plant population (Gabatshele et al. 2012). Iderawumi and Friday (2013) and Matusso et al. (2014) reported that mono-cropped cowpea plots produced
significantly more pods per plant than those intercropped with maize.
Consistently, higher grain yields obtained from cowpea varieties under
monocropping during the two seasons is a clear indication that the varieties
were bred and selected under a mono-cultural system. This may suggest that
varieties to be utilised in an intercropping system must be developed and
screened for selection under intercropping systems. This also justifies our
decision to include several varieties so that farmers have the options to
select the most promising and adapted varieties for cultivation.
In this study, strip
intercropping produced three-fold more grain yield compared to the mixed
intercropping. Nonetheless, maize grain yield was also higher in the case of
strip intercropping compared with mixed intercropping due to efficient resource
utilization and optimal plant population (Table 3). However, contrary to the
observation of Matusso et al. (2014),
Mango et al. (2018) reported that intercropping can generate higher crop
yields and profits than monocropping.
The
variations exhibited among the cowpea varieties during both
seasons for most of the variables measured were due to their genetic
characteristics and their interactions with weather variables (rainfall and
temperature). A long period of rainfall during the reproductive phase is known
to alter or extend the maturity of legumes, because it prolongs the flowering
and podding period, which in turn leads to asynchronous maturity due to
overlapping flowering. Therefore, more pods and grain yield were produced
during the 2015–2016 cropping season, because rainfall and temperature
distributions during the reproductive phase of the crop were better than they
had been during the 2016–2017 season (Table 1). Zerihun et al. (2016)
and Agoyi et
al. (2017) also observed that adequate soil moisture during the
reproductive stage is known to enhance grain filling, which can result in an
increased grain yield.
Results of this study showed that the LER
for strip intercropping system were
greater than 1.00, which indicated that the
system was more efficient in land and resource utilisation compared to mixed
intercropping. According to Hamd et
al. (2014), “when the LER < 1.00, there is an obvious disadvantage
caused by intercropping, and the available resources were used more efficiently
by the sole crop than intercropping”. Mariotti et al. (2006) and Kitonyo et
al. (2013) also report that “when the LER is equal to 1, there is neither
an advantage nor a disadvantage of intercropping compared to a sole crop, but
when the LER > 1.00, it indicates that intercropping system has an advantage
in terms of improved use of available resources for plant growth and
development”. In this study, the higher LER values (two-fold) with a range
between 1.25 and 2.29 during both seasons were obtained for strip intercropping
thus indicating that available land resources were utilized more efficiently
compared to mixed intercropping with LER values ranging from 0.50 to 1.32 for
both seasons. In addition, this is an indication that the higher the yield and
more adapted the varieties, the more advantageous the benefit-cost ratio, and
the profit farmers would earn in cultivating such varieties. According to Zhang et al. (2015), intercropping cereals
with grain legumes has superior yield and economic benefits compared to sole
cropping. The prospect of any cropping system for adoption depends on its
comparative advantage in terms of yields and cash return over the sole crops
(Seran and Brintha 2010; Imran et al.
2011; Asiwe and Madimabe 2020). The findings from this study corroborate these
reports. Higher profit and benefit-cost
ratio were achieved from strip intercropping compared to the profit and
benefit-cost ratio achieved from mixed intercropping.
Conclusion
Results
revealed that grain yield, land equivalent ratio, net profits, and benefit:cost
ratio obtained from strip intercropping were higher compared to mixed
intercropping. Among the five varieties, ‘IT82E-16’, ‘IT86D-1010’, and ‘IT87K-499-35’ out-performed
Glenda in terms of grain yield, land equivalent ration and net returns in strip
intercropping system grown under rain-fed conditions. Therefore, these
varieties are recommended for cultivation under strip intercropping system and
rain-fed conditions of Limpopo Province, South Africa.
Acknowledgements
The first author acknowledges the financial grant
received from the Water Research Commission, South Africa (Project number
K5/2494) and the support from the University of Limpopo.
Author Contributions
Both authors contributed meticulously in the execution of the
study during planting of the trial, data collection and collation, data
analysis and the preparation of the First Manuscript Draft. The First author
handled the corrections and correspondence from the reviewers.
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