







































 
 

 

57 
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Agriculture and Food Sciences Research 
Vol. 6, No. 1, 57-65, 2019 

ISSN(E) 2411-6653/ ISSN(P) 2518-0193 
DOI: 10.20448/journal.512.2019.61.57.65 

© 2019 by the authors; licensee Asian Online Journal Publishing Group 

    
 

 
 
 
Prediction of Climate Change Effects on Plantain Yield in Ondo State, Nigeria 

 
Olotu Yahaya1 
Atanda E.O.2 
Rodiya A.A.3 
Okafor M.C.4 

 
 

( Corresponding Author) 
1,2,4Department of Agricultural Engineering & Bio-Environmental, Auchi Polytechnic, Auchi, Nigeria. 

 
3Department of Agricultural Engineering, Federal Polytechnic, Ado, Ado-Ekiti, Nigeria. 

 

 
Abstract 

This study investigated the effects of climate change on plantain (Musa spp) for three Agro-Ecological 
Zones (AEZs) in Ondo State. Climate projections of six selected general circulation models (GCMs) under 
climate scenarios-Representative Concentration Pathways (RCP 4.5) were applied for different periods; 
baseline (1975–2005); future periods 2035–2065 [2050s] and 2070–2100 [2080]). The results of 
regression analysis showed a positive relationship between precipitation and plantain yield, while 
maximum (Tmax) and minimum temperature (Tmin) indicated no significant relationship with plantain 

yield at P˂ 0.01 in all the AEZs. The output of trend analysis indicated an increase in Tmax of 
0.046oC/year for Ondo North Agro-Ecological Zone (ONAEZ), while Ondo South Agro-Ecological Zone 
(OSAEZ) has the lowest increment of 0.003oC/year. Tmin for Ondo Central Agro-Ecological Zone 
(OCAEZ) increased by 0.007oC/year and decreased with 0.004oC/year and 0.030oC/year for ONAEZ and 
OSAEZ. However, analysis of precipitation events in the study areas from 1975-2005 showed that 
OCAEZ received the highest increase of 7.47 mm/year and decreased by 13.48 mm/year and 2.84 
mm/year for ONAEZ and OSAEZ respectively. Largest plantain yield reduction compared to the 
control-period for CCCMA model was -30.3% and -38.1% for the 2050s and 2080s whereas ICHEC model 
predicted an average lowest reduction of -7.5% and -12.5% for the short time and long periods in 
ONAEZ. In OSAEZ, plantain yield decreases varied from -6.3% to -8.4% for CNRM model, -6.1% to -
6.7% (MPI) and -36.1% to -37.7% for CCCMA. In conclusion, overall climate change simulations in 
OCAEZ showed that projected climate may have relatively small negative effects on plantain yield 
compared to ONAEZ and OSAEZ respectively. 

 
Keywords: General circulation models, RCP 4.5, Climate change, Plantain, Precipitation, Maximum temperature, Minimum temperature, 
AEZ, Ondo state 

 
Citation | Olotu Yahaya; Atanda E.O.; Rodiya A.A.; Okafor M.C. 
(2019). Prediction of Climate Change Effects on Plantain Yield in 
Ondo State, Nigeria. Agriculture and Food Sciences Research, 6(1): 
57-65. 
History:  
Received: 29 January 2019 
Revised: 5 March 2019 
Accepted: 15 April 2019 
Published: 11 June 2019 
Licensed: This work is licensed under a Creative Commons 

Attribution 3.0 License  
Publisher:  Asian Online Journal Publishing Group 
 

Contribution/Acknowledgement: This study contributes to the existing 
literature by investigating the effects of climate change on plantain (Musa spp) 
for three Agro-Ecological Zones (AEZs) in Ondo State, Nigeria. 
Funding: This study received no specific financial support. 
Competing Interests: The authors declare that they have no conflict of 
interests. 
Transparency: The authors confirm that the manuscript is an honest, 
accurate, and transparent account of the study was reported; that no vital 
features of the study have been omitted; and that any discrepancies from the 
study as planned have been explained. 
Ethical: This study follows all ethical practices during writing.   

 

 

Contents 
1. Introduction ...................................................................................................................................................................................... 58 
2. Study Area ......................................................................................................................................................................................... 58 
3. Results and Discussion ................................................................................................................................................................... 60 
4. Conclusion ......................................................................................................................................................................................... 64 
References .............................................................................................................................................................................................. 65 
 

 

 

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1. Introduction 
Climate change due to increased ‘greenhouse gases’ atmospheric concentrations is expected to have an 

important impact on the different economy (e.g. agriculture, forestry, energy consumptions, tourism, etc.) [1].  
Changes in the climate system and land cover have important consequences on regional and global water resources 
management and conservation [2]. In particular, for agriculture, such a change in climate may have significant 
impacts on crop growth and yield, since these are largely determined by the weather conditions during the 
growing season [1]. According to Robinson [3] plantain is the fourth most important starchy staple after cereals, 
cassava and yam and based on the food value, the second most expensive starchy staple in the urban market after 
yam. Extreme climate events, such as high-temperature stress, drought, and flooding, could result in a severe 
reduction in plantain production.  

In Nigeria, banana and plantain farming sector are small in relative to its contribution to the national gross 
domestic product, and yet remains significant with respect to food production, rural employment and livelihoods 
particularly in the South-Western region of the country. Plantain production in these regions is during the wet 
season and the dry mostly under rainfed cultivation. The optimal temperature for growing plantain is 28°C, from 
28oC to 20°C, growth will gradually slow down and will become negligible around 16-18°C [4]. Plantain needs a 
lot of water. It should get around 200 mm per month or effective rainfall between 1650-1700 mm throughout its 
life cycle [4]. However, considering the increasing pressure that climate change may likely place on plantain 
cultivation; it is not yet clear how future precipitation and air temperature patterns will change and how such 
changes will affect plantain water requirements, irrigation water demands, and yields. However, current studies on 
this subject matter are still very few in Nigeria, but more climate change studies had been conducted on cereal and 
tuber crops.    

Global circulation models (GCMs) are the appropriate tools currently employed in providing climate 
projections of both present-day and distant future climate variables [5]. GCMs outputs cannot be applied directly 
because their current resolution is too large to be used on local scales. Based on this, the outputs of global climate 
models often subjected to downscaling processes in order to be compatible with the local scales. There are two 
types of downscaling approaches; dynamic and statistical downscaling methods. Dynamic techniques, often viewed 
as a miniature global climate model they have not gained popularity because they tend to use complex processes 
and approaches in order to capture local-scale variations [6]. Statistical methods are mostly used in climate studies 
because they are cheap to apply and provide site-specific climate information [7]. However, this climate change 
study is based on the latest greenhouse gas emission scenarios called Representative Concentration Pathways (RCPs), 
consisting of RCP 2.6, 4.5, 6.0 and 8.5; measured in watt per metre square ((Wm-2) [8]. Furthermore, most of the 
previous climate change studies in Nigeria were investigated based on the earlier version of climate change 
scenarios (A1, A2, B1, and B2) from Fourth Report on Special Report on Emission Scenario in the 
Intergovernmental Panel on Climate Change (IPCC). Therefore, this current study will be one of the few climate 
change kinds of research using the newly released RCP emission scenarios in Nigeria. 

In this study, the effects of climate change on plantain yield using an ensemble set of six GCMs under RCP 4.5 
for the future periods 2035-2065(the 2050s) and 2070-2100 (2080s) relative to baseline period 1975-2005 is 
investigated for the agro-ecological zones (AEZs) in Ondo State. 

 

2.  Study Area 
2.1. Location of study area 

Ondo state is one of the states in the South-western region of Nigeria. It has a total population of 3,440,024  of 
which 65% resides in fertile areas. It has a density of 236 persons per square meter and land square area of 
15,500Km2 [9]. The state has eighteen local government areas which are divided into three geographic zones and 
population concentration as follows: Ondo-North with a population of 1,064,900; Ondo-South has a population of 
1,054,675 and population of 1,320, 449 Ondo Central [9]. Generally, agriculture is the mainstay of the economy, 
and the chief products are cotton and tobacco from the north, cacao from the central part, and rubber and timber 
(teak and hardwoods) from the south and east; palm oil, kernels, banana, and plantain are cultivated throughout the 
state.  Other crops include rice, yams, corn (maize), coffee, cassava (manioc), vegetables, and fruits. The study area 
is bounded by the states of Kwara and Kogi on the north, Edo on the east, Delta on the southeast, and Osun and 
Ogun on the west and by the Bight of Benin of the Atlantic Ocean on the south. Ondo state includes mangrove-
swamp forest near the Bight of Benin, tropical rain forest in the centre part, and wooded savannah on the gentle 
slopes of the Yoruba Hills in the north. Fig.1 shows the map of Ondo State indicating the three agro-ecological 
areas under study. 

 

2.2. Baseline Climate and Plantain Yield  
Historical monthly climate data (maximum temperature, minimum temperature, precipitation,) for 1975-2005 

were taken from the CRU TS2.1 database through the Department of Agro-climatological, Ministry of Agriculture 
& Natural Resources, Ondo-State, Nigeria with a spatial resolution of 30 arc-minutes. Baseline plantains (1975–
2005) were collected from Ondo State Ministry of Agriculture and Natural Resources. Plantain yield was collected 
as the fiscal year basis, such as 1975–1976, 1976–1977, etc. Then, these fiscal year data were converted to yearly 
data, for example, 1975–1976 was considered as 1976. The plantain yield data are consistent with the statistical 
data from the Food and Agriculture Organization of Nigeria [11]. 

 

http://www.britannica.com/place/Nigeria
http://www.britannica.com/place/Kwara
http://www.britannica.com/place/Kogi
http://www.britannica.com/place/Edo-state-Nigeria
http://www.britannica.com/place/Delta-state-Nigeria
http://www.britannica.com/place/Osun
http://www.britannica.com/place/Ogun-state-Nigeria
http://www.britannica.com/topic/Yoruba


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Figure-1. shows the map of Ondo State indicating the three agro-ecological areas. 

   Source:  OSMHUD [10]. 

 
2.3. Statistical Downscaling Model 

Statistical downscaling model (SDSM) was applied to simulate 31-year historical dataset (1975-2005) from the 
study regions using different general circulation models (GCMs) and project future climate (2035-2065 and 2070-
2100) under representative pathway concentration (RCP 4.5). The climate models included Canadian Centre for 
Climate Modeling & Analysis (CCCMA), Max Planck Institute for Meteorology (MPI), Met Office Hadley Centre 
(MOHC), and Model for Interdisciplinary Research on Climate (MIROC), Irish Centre for High-End Computing 
(ICHEC) and National Centre for Meteorological Research (CNRM). In this study, these models were used to 
produce climate variables as one stochastic set of data for the baseline period and for future periods under a climate 
change scenario (RCP 4.5). The outputs of simulated climate variables were used to develop climate-plantain model 
useful to predict the climate change effects of future climate on plantain reduction yield in the three agro-ecological 
zones. Table 1 and Table 2 show the study regions and selected GCMs respectively. 

  
Table-1. Categorization of Agro-Ecological Zone in Ondo-State. 

S/N OSAEZ OCAEZ ONAEZ 

1 Odigbo Akure South Akoko N.W 
2 Okitipupa Akure North Akoko N.E 
3 Irele Ileoluji/Okeigbo Akoko S.W 
4 Ilaje Ifedore Akoko S.E 
5 Ese-Odo Ondo-East Owo 
6 Idanre Ondo-West Ose 

                                Source: ODSMA [9]. 
 

Table-2. GCMs selected for the research study. 

Models Emission scenarios Spatial resolution 

CCCMA RCP 4.5 48×96 cells, 3.750  ×3.750 
MPI RCP 4.5 96×192 cells, 1.90 ×1.90 

MOHC RCP 4.5 88×176 cells, 2.00 × 2.00 
MIROC RCP 4.5 67× 134 cells, 1.120 × 1.120 
CNRM RCP 4.5 64×128 cells, 2.80 ×2.80 
ICHEC RCP 4.5 60 × 120 cells, 2.90  × 2.90 

                                       Source: Soden and Held [5]. 

 
2.4. Data Analysis 
2.4.1. Mann Kendall and Sen’s Slope Analysis 

Mann Kendall (M-K) test is a non-parametric statistical test widely used for the analysis of the trend in 
climatologic and other fields of science and engineering. One advantage of this test is that the data need not 
conform to any particular distribution [12]. Second, the test has low sensitivity to abrupt breaks due to 
inhomogeneous time series [13]. Using M-K test, the null hypothesis H0 assumes that there is no trend (the data is 
independent and randomly ordered), the observations of xi are randomly ordered in time, against the alternative 



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hypothesis, H1 which indicates increasing or decreasing trends. The estimation technique procedure for  M-K test 
applies the time series of n data points and Xi and Xj as two subsets of data where i = 1,2,3,…, n-1 and j = i+1, i+2, 
i+3, …, n as indicated in Equation 1. The data values are evaluated as an ordered time series. Each data value is 
compared with all subsequent data values. If a data value from a later time period is higher than a data value from 
an earlier time period, the statistic S is incremented by 1. On the other hand, if the data value from a later time 
period is lower than a data value sampled earlier, S is decremented by 1 as expressed in Equation 2. The net result 
of all such increments and decrements yields the final value of S [14]. 

              (1) 

 

 =         (2) 

Where Xj and Xi are the annual values in years j and i, j > i, respectively [15]. To derive an estimate of the 
slope S, the slopes of all data pairs are calculated as follows: 

        
2.5. Climate-Crop Yield Relationship  

The impact on climate change on plantain (Musa spp) yield was investigated and evaluated using developed 
newly empirical-statistical models of current and future time periods.  This model does not attempt to capture 
details of plant physiology or crop management; they do capture the net effect of the entire range of processes by 
which climate affects yields, including the effects of poorly modeled processes [16]. Correlation coefficient and 
multivariate regression analyses were performed to determine the climate-crop yield relationship using the 
Statistical Package for Social Sciences (SPSS). Pearson’s correlation coefficient was used to measure the strength of 
the association between crop yield and climatic variability [16]. This produced a linear association. The range of 
correlation coefficients is -1 to +1. The complete dependency between two variables is expressed by either -1 or +1, 
and 0 represents the complete independence of the variables as shown in Equation 3. A correlation coefficient is 
mathematically performed as follows: 

 

                                                       (3) 

The x represents the independent (climate) variable and y (plantain yield) represents the dependent variable. 
 
 Multivariate regression analysis of climate and crop yield was performed to estimate the percentage of the 
response of variations (plantain yield) from the predictor variables (minimum and maximum temperature and 
precipitation). Baseline plantain yield was estimated using a regression model in Equation 4, while Equations 5,6,7 
8 were used to estimate projected plantain yields for periods 2035-2065 and 2070-2100 under CCCMA and MOHC 
models respectively.  The multiple linear regressions with first differences in yield (∆Yield) as the response 
variable, and first differences of minimum temperature (∆tmin), maximum temperature (∆tmax) and precipitation 
(∆ppt) as predictor variables. 
  

                                                         (4) 

          (5) 

                (6) 

   

                      (7) 

       

                      (8) 

 

3. Results and Discussion 
3.1. Current Climate and Plantain Yield 
3.1.1. Temperature and Precipitation Trends 

Current minimum and maximum temperature from 1975 to 2005 for the three agro-ecological zones (ONAEZ, 
OSAEZ, and OCAEZ) in Ondo-State were analyzed using non-parametric Mann-Kendall and Sen’s slope estimates. 
The results of the trend analysis are showed in Table 3. The rate of increase in maximum temperature was highest 
in ONAEZ with 0.046oC/year while Ondo South Agro-Ecological Zone (OSAEZ) has the lowest increment of 
0.003oC/year. Similar results were obtained by Soden and Held [5].This region is characterized as swamp 
rainforest zone with high rainfall duration, intensity, and depth. The outputs of Sen’s slope estimates for minimum 
temperature (Tmin) followed a different pattern.  The Tmin for OCAEZ increased by 0.007oC/year where the 
remaining two regions (ONAEZ and OSAEZ) decreased by 0.004oC/year and 0.030oC/year as indicated in Table 3. 
The maximum temperature increased across the studied agro-ecological zones indicating warming throughout the 
period of consideration Figures 2-4. In addition, an increasing trend in maximum air temperature was found in 
Ondo State [17].  

 
 
 
 
 
 



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Table-3. Statistical calibration for minimum and maximum temperature  for three Agro-Ecological Zones. 

Study regions Tmax Det.Corr Corr. Sig. Val Tmin 
Det. 
Corr Corr. Sig. Val 

AEZ Sen's slope (mm) R² r P-Value Sen's slope (mm) R² r P-Value 

ONAEZ 0.046 0.151 0.388 0.031* -0.004 0.020 -0.390 0.833b 
OSAEZ 0.003 0.020 0.045 0.812b -0.030 0.044 -0.210 0.256b 
OCAEZ 0.004 0.001 0.025 0.890b 0.007 0.006 0.079 0.674b 

   Source: Simulation output, 2018. 

 

 
Figure-2. Annual Minimum and maximum temperature trends at ONAEZ from 1975-2005. 

                          Source: Simulation output, 2018. 
 

 
Figure-3. Annual Minimum and maximum temperature trends at OCAEZ from 1975-2005. 

                        Source: Simulation output, 2018. 
 

 
Figure-4. Annual Minimum and maximum temperature trends at OSAEZ from 1975-2005. 

         Source: Simulation output, 2018. 
  

The analysis of precipitation events in the study areas from 1975-2005 showed that OCAEZ received the 
highest increase of 7.47 mm/year Table 4, Figure 5. However, total annual precipitation at ONAEZ and OSAEZ 
decreased by 13.48 mm/year and 2.84 mm/year. 

 
 



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Table-4. Statistical metrics for annual precipitation for the Agro-Ecological Zones. 

Study regions Sen's slope (mm) R² R P-Value Alpha-Value Sig. 

ONAEZ -13.475 0.138 -0.409 0.022* 0.050 Yes 
OSAEZ -2.837 0.067 0.314 0.086b 0.050 No 
OCAEZ 7.470 0.016 -0.126 0.500b 0.050 No 

              Source: Simulation output, 2018. 
 

 
Figure-5. Annual precipitation trends at ONAEZ-OSAEZ-OCAEZ from 1975-2005. 

          Source: Simulation output, 2018. 
 

3.2. Plantain (Musa spp) Yield Trend 
Plantain yield trend showed fluctuation over the period of consideration in all the studied agro-ecological 

zones. The yield increase of 0.039 ton/ha yearly is highly significant (P< 0.05) in OSAEZ Again, the yield reduced 
by -0.022 ton/ha in ONAEZ and -0.033 ton/ha in OCAEZ Table 5. These reductions were not significant (P > 
0.05) within the baseline period (1975-2005). Figure 6 depicts the plantain trend analysis. The trend of plantain 
yield in OSAEZ is similar to the production pattern in Nigeria for more than two decades with the country 
harvested 2.103 million tons from 389,000 ha [18]. However, the country experienced a great depression in 
plantain production between 1987–1988 and 1990 [18]. This reduction pattern is very similar to plantain yield 
trends in ONAEZ and OCAEZ respectively. 

 
Table-5. Statistical metrics for plantain yield trends for the Agro-Ecological Zones. 

Study regions Sen's slope (ton/ha) R² R P-Value Alpha-Value Sig. 

ONAEZ -0.022 0.044 -0.211 0.256 0.050 No 
OSAEZ 0.039 0.136 0.368 0.042* 0.050 Yes 
OCAEZ -0.033 0.108 -0.329 0.071 0.050 No 

                  Source: Simulation output, 2018. 

 

 
Figure-6. Plantain yield trends in three Agro-Ecological Zones from 1975-2005. 

              Source: Simulation output, 2018. 
 
3.3. Plantain Yield-Climate Simulation 

Relationship between the control-base plantain yield and climate variables in all the three agro-ecological 
zones were performed using correlation and regression models. The results of sensitivity analysis in Table 6 reveal 
that positive and strong correlation values (r = 0.80; 0.63 and 0.68) for ONAEZ, OSAEZ, and OCAEZ respectively. 

Shahid [14] reported the same results in Bangledesh. Conversely, an estimated relationship between precipitation 
and plantain yield is significant (P < 0.01) in all the study regions. These results indicate that an increase in annual 
precipitation could lead to an increase in plantain yield per hectare in all the agro-ecological zones (ONAEZ, 
OCAEZ, and OSAEZ).  Coefficient of determination  between plantain yields and minimum temperature for three 
agro-ecological is very weak with R2 = 0.005(ONAEZ), R2 = 0.042 (OSAEZ) and R2 = 0.053 (OCAEZ) with 
insignificant association at 95% confidence interval (P < 0.05).  While testing the effects of annual maximum 
temperatures, no significant relationship was observed in the yield of plantain in all the studied agro-ecological 



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zones. However, the coefficient of maximum temperature was very weak with R2= 0.07, R2 =0.04 and 0.01 for 
ONAEZ, OSAEZ and OCAEZ Table 6. Therefore, plantain yield decreases with increasing maximum and 

minimum temperatures. The findings are in agreement with the studies [2, 3]. 
 

Table-6. Statistical  for  Plantain yield-Temperature-Precipitation for the AEZs(1975-2005). 

Study 
regions 

Precipitation Tmax Tmin 
 

AEZ R² r Std.dev P-Value R² r Std.dev 
P-

Value R² r Std.dev 
P-

Value 

ONAEZ 0.65 0.80 299.6 0.00001* 0.005 0.07 1.00 0.699b 0.07 0.26 1.07 0.165b 

OSAEZ 0.40 0.63 216.4 0.00001* 0.042 0.21 1.27 0.268b 0.04 0.20 0.70 0.277b 

OCAEZ 0.46 0.68 252.8 0.00001* 0.053 0.23 1.19 0.149b 0.01 -0.11 1.23 0.510b 
    Source: Simulation output, 2018. 

 
3.4. Estimation of Climate Change Impacts on Plantain Yield 

Direct impacts of climate change on plantain yield for the three agro-ecological districts were estimated using a 
developed multiple linear regression model under control period (1975-2005) and the future periods (the 2050s and 
2080s). Average baseline plantain yields considered were 8.5 tons/ha, 8.6 tons/ha and 8.7 tons/ha for ONAEZ, 
OSAEZ and OCAEZ respectively. The results of multivariate regression analysis reveal the estimated potential 
impacts of climate change on plantain yield across the AEZs as shown in Tables 7-9. Simulation outputs indicate 
that all the GCMs predicted future reductions in plantain yield in all the three agro-ecological zones. CCCMA 
model has the highest decrease in plantain yields. Yield reductions of 2,567.0 kg/ha and 3,085.5 kg/ha were 
predicted for the time periods of the 2050s and 2080s in ONAEZ Table 8 whereas plantain yield decrease of 3,068.5 
kg/ha and 3,204.5 Kg were projected in OSAEZ Table 9 using CCCMA model. Smit and Skinner [6] showed 
similar observation with CCCMA simulations 

 However, for all the future time periods (the 2050s and 2080s) plantain yield reduction is marginally predicted 
in Ondo Central Agro-Ecological Zone Table 7. Largest plantain yield reduction percentage compared to the 
control-period across 1975-2005-2065 for CCCMA model was -30.3% and -38.1% for the 2050s and 2080s 
respectively in ONAEZ Table 8.  However, ICHEC model predicted an average lowest reduction of -7.5% and -
12.5% for a short time and long periods. 

 
Table-7. Projected climate change effects on plantain yield (%) relative to baseline period for OCAEZ. 

GCMs 

Plantain yield reduction (%) Plantain yield reduction (Kg/ha)  
Period (2080s) Period (2050s) Period (2080s) Period (2050s) 

Models 2035-2065 2070-2100 2035-2065 2070-2100 
CNRM 0.3 0.7 25.5 59.5  

MPI 0.6 0.8 51.9 65.5  
MIROC 0.7 1.0 62.9 82.5  
MOHC 0.7 1.0 57.0 80.8  
CCCMA 1.0 1.2 86.7 102.0  
ICHEC 0.1 0.2 2.6 17.0  

       Source: Simulation output, 2018. 
 

Table-8. Projected climate change effects on plantain yield (%) relative to baseline period for  ONAEZ. 

GCMs 

Plantain yield reduction (%) Plantain yield reduction (Kg/ha)  
Period (2080s) Period (2050s) Period (2080s) Period (2050s) 

Models 2035-2065 2070-2100 2035-2065 2070-2100 
CNRM 14.5 22.4 1232.5 1904.0 

MPI 19.4 24.2 1649.0 2057.0 
MIROC 3.6 33.9 306.0 2881.5 
MOHC 35.1 33.9 2983.5 2881.5 

CCCMA 30.2 36.3 2567.0 3085.5 
ICHEC 7.3 12.1 620.5 1028.5 

         Source: Simulation output, 2018. 
 

Table-9. Projected climate change effects on plantain yield (%) relative to baseline period for  OSAEZ. 

GCMs 

Plantain yield reduction (%) Plantain yield reduction (Kg/ha)  
Period (2080s) Period (2050s) Period (2080s) Period (2050s) 

Models 2035-2065 2070-2100 2035-2065 2070-2100 
CNRM 6.3 8.4 535.5 714.0  

MPI 6.1 6.7 518.5 569.5  
MIROC +1.8 17.1 153.0 1453.5  
MOHC 1.5 -1.9 127.5 161.5  

CCCMA 36.1 37.7 3068.5 3204.5  
ICHEC 1.8 2.4 153.0 204.0  

    Source: Simulation output, 2018. 
 

In OSAEZ region, a substantial reduction in plantain yield is estimated by 2050s and 2080s compared with 
baseline yield. Yield decrease varied from -6.3% to -8.4% for CNRM model, -6.1% to -6.7% (MPI), -1.5% to -1.9% 
(MOHC), -36.1% to -37.7% (CCCMA), -1.8% to -2.4% (ICHEC). However, an increase of plantain yield of 1.8% is 
estimated by the MIROC model in 2050s and reduction of -17.1% in 2080s as indicated in Figure 7b.  It could be 
deduced that plantain will largely decrease in OSAEZ and ONAEZ Figure 7a and 7b. A possible explanation for 
this could be related to the projected increase in minimum and maximum temperature in the regions. Higher 



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temperature influences increase in evapotranspiration (ETo) and increase plantain water requirement. In Ondo 
Central Agro-Ecological Zone (OCAEZ), predicted outputs from selected GCMs indicate decrease in plantain 
(Musa.spp) yield under two future scenarios Figure 7c. However, MIROC and MOHC simulations indicate equal 
reduction values of 0.6% and 0.8%; ICHEC predicted least decrease of 0.02% and 0.2% for the periods the 2050s and 
2080s respectively Figure 7c.   Overall simulations of impacts of climate change in OCAEZ showed that projected 
climate will have relatively small negative effects on plantain yield compared to the results predicted in ONAEZ 
and OSAEZ respectively. 
 

 
Figure-7a. Predicted plantain yield (%) for period (2035-2065) and (2070-2100) relative to 1975-2005 over ONAEZ. 

        Source: Simulation output, 2018. 

 
  

 
Figure-7b. Predicted plantain yield (%) for period (2035-2065) and (2070-2100) relative to 1975-2005 over OSAEZ. 

 Source: Simulation output, 2018. 

 
Figure-7c.Predicted plantain yield (%) for period (2035-2065) and (2070-2100) relative to 1975-2005 over OCAEZ. 

 Source: Simulation output, 2018. 
 

4. Conclusion 
The estimated relationship between baseline precipitation and plantain yield is significant (P < 0.01) in all the 

studied regions indicating an increase in seasonal precipitation could lead to increase in plantain yield per hectare 
in all the agro-ecological zones (ONAEZ, OCAEZ, and OSAEZ). Plantain yield was reduced under projected future 
climate (the 2050s and 2080s) and the decrease was different based on different GCMs outputs. CCCMA model has 
the highest decrease in plantain yields in all agro-ecological zones compared to other global climate models. This 
could be related to the projected increase in minimum and maximum temperature which influence 
evapotranspiration (ETo) and increases plantain water requirement. In OSAEZ region, a substantial reduction in 
plantain yield is estimated by 2050s and 2080s compared with baseline yield.  Overall simulations of impacts of 
climate change in OCAEZ showed that projected climate may likely have relatively small negative effects on 
plantain yield compared to the results predicted in ONAEZ and OSAEZ respectively. 



Agriculture and Food Sciences Research, 2019, 6(1): 57-65 

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