Journal of Civil Engineering and Urbanism  
Volume 10, Issue 6: 53-61; November 25, 2020  
ISSN-2252-0430  
Effect of Stabilization on Failure Susceptibility of Oshogbo-Iwo Road in  
South-Western Nigeria  
Oluyemi-Ayibiowu Bamitale Dorcas1, Omomomi Oladapo Jayejeje and Fadugba Olaolu George  
Civil Engineering Department, Federal University of Technology, Akure, Nigeria.  
Corresponding author’s Email: ogfadugba@futa.edu.ng;:  
ABSTRACT  
The research evaluated the failure susceptibility of biopolymers (Guar Gum, Xanthan Gum, Bentonite) and  
polyvinyl acetate (PVAc) stabilized soil samples from three failed locations along Oshogbo – Iwo Road’s using the  
TDRAMS mathematical model formulated by Aderinola et al., (2015). The stabilizers were added to the soils in  
concentrations of (0.25-2) % Biopolymers, (1-3) % Bentonite and 2% PVAc. The samples were classified according  
to AASHTO as A-5 (slty-sand) and ML group (inorganic silts, sfine sands with low plasticity) based on USCS  
classification system. Geotechnical tests carried out on both natural untreated and treated samples showed that the  
natural soil samples gave OMC values of between (11.7-14.97) %, MDD (1644-1453.6) Kg/m3, and soaked CBR  
(2-6) %. 1% Guar gum, 1 % Xanthan gum, 3% Bentonite and 2% Poly vinyl Acetate were deduced to be optimal  
mixes for improved strength. However, Guar gum was observed to be the best stabilizer. With the TDRAMS model,  
1% Guar gum reduced the failure susceptibility indices of the road by 11.02 % (i.e. from 127 to 113). However, for  
maximum benefits to be achieved from the stabilization, other factors like provision of good drainage facilities,  
adequate road sections etc. must be provided. This will help in improving the strength of the subgrade soils and  
overall durability of the road.  
Keywords: Stabilization, Guar Gum, Xanthan Gum, Polyvinyl acetate, Failure Susceptibility  
INTRODUCTION  
the road pavement is underlain by schist with pegmatite  
intrusion, whose minerals have weathered into expansive  
clay.  
In Nigeria today, it’s no surprise to drive along dilapidated  
road pavements. Many roads instead of providing safe  
passage to destinations, have long become death traps  
(Una, 2011). One of such roads is the Oshogbo-Iwo road  
located in Osun state, Southwestern Nigeria. It lies within  
latitudes 7º 37' 36.24"N and 7º 47' 22.08"N and longitudes  
4º 09'22.20"E and 4º 30' 23.58" E. The road connects  
Oshogbo to many other cities in Osun state like Ede,  
Ejigbo, Iwo, Ikire, Ogbagbaa etc. and links the state to  
Ibadan and many other parts of Oyo state. However, the  
incessant failure of the road pavement has negatively  
affected the socio-economic activities within the area and  
this needs urgent solution (Figure 1).  
investigate the cause but also provide a solution to the  
road’s incessant failure. Oyelami and Alimi (2015) also  
investigated the possible causes of the persistent failure  
along the road samples were taken along different failed  
sections of the road following a geological mapping of the  
area. The results of the geological mapping revealed that  
Figure 1. Typical Failed Sections of Oshogbo Iwo Road.  
Soil stabilization technique had been employed to  
improve the soil materials along the road. Alteration of the  
soil’s engineering properties through mechanical or  
chemical means is employed especially when it is more  
economical to overcome a deficiency in areadily available  
material than to bring in one that fully complies with the  
To cite this paper: Oluyemi-Ayibiowu BD, Omomomi, OJ, Fadugba OG (2020). Effect of Stabilization on Failure Susceptibility of Oshogbo-Iwo Road in South-Western Nigeria.  
53  
Oluyemi-Ayibiowu et al., 2020  
requirements of specification for the soil (Ola, 1975).  
MATERIALS AND METHODS  
Quadri et al. (2018) improved the quality of the subgrade  
material with the use of portland cement and Renolith (a  
synthetic polymer) to stabilize the soil samples collected  
from four different locations along the road. Based on this  
work, the use of 5% cement and 4% Renolith by weight of  
soil sample was recommended to improve the subgrade  
soil to a sub-base material.  
The soil investigation was carried out under standard  
laboratory conditions on soil samples which were obtained  
along 3 different sections of Oshogbo -Iwo road, Osun  
state. Sample A was collected at a location with  
coordinates, longitude 7.7936711N and latitude  
4.4909929E; sample B from Longitude 7.794651N and  
Latitude 4.4877133E; and sample c from Longitude  
7.794651N and Latitude 4.48779677E (Figures 2 and 3).  
The soil samples were taken at a depth of 1.1m below the  
ground level using undisturbed and disturbed sampling  
kept in black sacks to prevent moisture loss. Testing was  
performed at the Geotechnical Laboratory, Civil  
Engineering Department of the Federal University of  
Technology, Akure, Ondo State, Nigeria.  
In recent times, the use of environmentally friendly  
additives like Biopolymers, Polyvinyl Acetate Bentonite  
and are currently being investigated as replacements for  
Biopolymers are polymers that are produced by living  
organisms. The most commonly used biopolymer in recent  
times includes polysaccharides, which are polymeric  
carbohydrate chains composed of monosaccharide units  
(Lorenzo et al., 2012). Polyvinyl Acetate (PVAc), on the  
other hand is a synthetic polymer. PVAc is a type of  
organic aqueous polymer soil stabilizer. Its main  
component is acetic-ethylene-ester. It comprises of many  
long-chain macromolecules and polarity carboxyl groups  
(OOCCH3). Bentonite, which comprises mainly of  
montmorillonite is often used as drilling mud for oil and  
gas wells and boreholes. It has the potential to adjust soil  
gradation and improve its geotechnical characteristics.  
Aderinola et al. (2015) considered the contribution of  
traffic[T], water-table[D], geotechnical indices such as  
Maximum Dry Density and California Bearing Ratio[M]  
and [R], road cross-section elements such as cambering[A]  
and asphalt thickness[S] to determine the road’s pavement  
failure indices. The research came up with a mathematical  
model called TDRAMS, which was used to determine the  
failure susceptibility of some soil samples from Oshogbo –  
Iwo road.  
Figure 2. Map of Osun State, Nigeria  
Figure 3. Sample locations (1-3).  
Two commercially available biopolymers were used in  
this study (i.e. Xanthan gum and Guar gum) due to their  
availability and reasonable prices compared to other  
biopolymers. Also Polyvinyl Acetate (PVAc) was also  
applied as another stabilizer in the study. Polyvinyl acetate  
is synthesized by the polymerization reaction of polyvinyl  
alcohol and vinyl acetate in the presence of per sulfate as a  
free radical initiator in the reaction kettle commonly used  
for polymerization (Bu et al., 2019). Commercially  
available PVAc was used in this study. Bentonite is a clay  
formed as a result of chemical weathering of volcanic ash.  
It consists predominantly of smectite minerals, usually  
montmorillonite [Si8Al4O20(OH)4.nH2O].  
This is a potent tool in assessing road pavement  
failure susceptibility at failed segments of any road. From  
the work, the soil samples were of high failure indices, and  
non-conformity in the construction of Oshogbo-Iwo road  
from the engineering specifications, both in material and  
in workmanship were deemed to be responsible for the  
road’s incessant failure. This work therefore further  
investigated the use of Biopolymers (Guar gum and  
Xanthan gum), Polyvinyl Acetate and bentonite to  
improve the engineering properties of the Osogbo-Iwo  
Road soil and assess the stabilized failure susceptibility  
indices using the TDRAMS model.  
54  
J. Civil Eng. Urban., 10 (6): 53-61, 2020  
Commercially available bentonite was used for the  
research.  
distribution for unstable soils with a large component of  
the soil being silty-fine to medium-fine sand and the (11-  
24.3) % clay acting as binder to bind the particles together.  
It can be deduced that the silt controls the behavior of the  
soil. The typical range of specific gravity for silty sand is  
between 2.67 and 2.7 (Karkush, 2018). The sample was  
classified as ML group (inorganic silts, fine sands with low  
plasticity) according to the unified soil classification  
system (USCS) and as an A-5 material (silty sand) which  
is fair -poor in terms of general ratings as a subgrade  
material according to the AASHTO classification system.  
Table 1 shows the natural soil characteristics.  
Sample preparation  
To prepare treated soil specimens, the natural  
collapsible soil was disturbed by hand and air dried for  
one week. Wet mixing approach was employed in  
preparing stabilized samples, the stabilizers were first  
prepared with specific concentrations and then mixed with  
the air-dried soil. The percentage concentrations of  
Bentonite, Biopolymers and Polyvinyl Acetate (PVAc)  
used are (1-3) %, (0.25-2) % and 2% respectively. The  
solution concentration in each case was calculated as a  
ratio between the weight of the used additive and the  
overall percentage by weight of the solution. The  
powdered additives (Guar gum and Xanthan gum) were  
added to the water gently to avoid clumping and mixed  
until a homogeneous solution was obtained  
Table 1. Geotechnical properties of the untreated soil.  
Parameters  
Location  
1
Location  
2
Location  
3
Grain size distribution  
Gravel (%) (>4.75 mm)  
26.5  
29.8  
36  
31.7  
30.5  
Experimental programme  
Preliminary tests which included moisture content,  
Atterberg limit, Particle size distribution and specific  
gravity were conducted to determine the natural soil’s  
index properties according to the procedures in BS1377  
(1990). The soils were classified using the American  
Association of State Highway and Transportation Officials  
(AASHTO, 1986) and Unified Soil Classification System  
(USCS) (ASTM, 1992). West African Standard (WAS)  
Compaction Tests were carried out on both the natural and  
stabilized samples in accordance with the Nigeria General  
Specifications (1997). Unconfined Compressive Strength  
(UCS) was used to test the ability of the soil samples to  
withstand failure by compression. The natural and  
stabilized specimens were subjected to testing by crushing  
and the load that caused the failure of the specimen was  
divided by the cross sectional area of the specimen and the  
strength of the soil was determined following the  
procedure in BS1377 (1990). The samples were cured for  
7 days in order to see the effect of time on the strength of  
the treated materials. The California bearing ratio (CBR)  
test developed by the California State Highway  
Department was used for the evaluation of road sub grade  
strengths at the selected failed locations. The test was  
carried out on soaked and un-soaked samples according to  
the procedure in BS1377(1990).  
Sand (%) (4.75-0.075 mm)  
26.3  
Silt (%) (0.075-0.002 mm)  
Clay (%) (<0.002 mm)  
Natural moisture content (%)  
Specific Gravity (Gs)  
31.8  
11.9  
5
24.6  
13.1  
7.5  
13.5  
24.3  
5.6  
2.68  
2.7  
2.65  
Atterberg limits  
Liquid limit (%)  
Plastic limit (%)  
Shrinkage limit (%)  
Plasticity index (%)  
26.1  
16.0  
11.0  
10.1  
26.3  
16.5  
11.5  
9.8  
34.1  
20.3  
13.0  
13.8  
OMC (%)  
11.7  
14.57  
14.97  
MDD (kN/m3)  
1644  
10  
1489.61  
17  
1453.60  
10  
CBR Un-soaked (%)  
CBR Soaked (%)  
UCS (kN/m2)  
3
6
2
75.92  
A-5  
ML  
63.61  
A-5  
ML  
71.82  
A-6  
CL  
ASSHTO classifcation  
USCS Classification  
RESULTS AND DISCUSSIONS  
Natural soil characteristics  
The grain size curves of the samples from the three  
sections of the Oshogbo-Iwo road are shown in Graph 1.  
The grain size distribution can be taken as classical particle  
Graph 1. Grain size distribution for location (1-3).  
55  
Oluyemi-Ayibiowu et al., 2020  
This equation can also be written as:  
Effect of additives on the soil’s geotechnical  
characteristics  
The effects of the addiives on the compaction and  
strength properties of the soil are shown in tables 2 and 3.  
T. TDRAMS.I = 6Tr + 5Dr + 4Rr + 3Ar + 2Mr +Sr.................(2)  
Where, 6, 5, 4, 3, 2 and 1 are the assigned weights of  
traffic load [T], depth to water-table [D], soaked CBR [R],  
cambering [A], maximum dry density [M], and asphalt  
thickness [S] respectively as shown in Table 4, TDRAMS  
Rating System and Weights (Ola et al., 2009). This was  
used to evaluate the failure indices in order to further  
ascertain the effectiveness of the stabilizers.  
Determination of stabilized failure susceptibility  
indices  
The Total TDRAMS Index (Aderinola et al., 2015) is  
mathematically expressed as:  
T. TDRAMS.I= b0 + b1T + b2 D + b3R + b4A + b5M + b6S + er..............(1)  
Where: b0, b1, b2, b3, b4, b5, b6 are the independent  
variables for the regression models and er is the error  
coefficient.  
Table 2. Compaction characteristics of control and stabilized samples.  
Location 1  
Location 2  
Location 3  
% decrease in  
strength on  
wetting  
% decrease  
in strength  
on wetting  
% decrease  
in strength  
on wetting  
Sample  
Unsoaked  
CBR (%)  
Soaked  
CBR (%)  
Unsoaked  
CBR (%)  
Soaked  
CBR (%)  
Unsoaked  
CBR (%)  
Soaked  
CBR(%)  
Control  
10  
13  
3
4
70.00  
69.23  
17  
20  
6
7
64.70  
65.00  
10  
16  
2
3
80.00  
81.25  
Bentonite stabilized  
sample  
Guar gum stabilized  
sample  
Xanthan gum  
stabilized sample  
PVAc stabilized  
sample  
29  
22  
20  
17  
6
41.38  
72.73  
60.00  
31  
25  
23  
20  
18  
11  
35.50  
28.00  
52.20  
32  
30  
28  
26  
19  
15  
18.75  
36.67  
46.43  
8
Table 3. California bearing values of stabilized samples.  
S/N  
Sample  
Parameter (s)  
Location 1  
Location 2  
Location 3  
OMC (%)  
MDD (kg/m3)  
OMC (%)  
11.70  
1644.00  
12.03  
1441.00  
12.88  
1425.42  
24.61  
1206.96  
19.38  
1318.96  
12.7  
1506.00  
11.8  
1481.00  
9.60  
1499.22  
15.95  
1409.88  
12.02  
1502.61  
12.92  
1538.26  
15.20  
1566.23  
11.70  
14.57  
1489.60  
12.90  
1500.00  
12.70  
1400.00  
20.21  
1313.10  
20.21  
1313.10  
18.23  
1371.50  
13.20  
1476.38  
15.70  
1390.40  
20.6  
1348.65  
15.10  
1460.23  
12.50  
1567.23  
14.0  
1533.34  
14.57  
14.97  
1453.60  
15.56  
1358.34  
15.90  
1383.37  
16.90  
1421.34  
16.90  
1421.00  
19.41  
1405.00  
13.61  
1447.96  
13.5  
1430.34  
15.95  
1409.88  
12.50  
1535.11  
12.60  
1497.76  
11.50  
1483.54  
14.97  
1
Control  
2
0.5 % Gg +Soil  
1.0 % Gg + Soil  
1.5 % Gg + Soil  
2.0 % Gg + Soil  
0.5 % Xg + Soil  
1.0 % Xg + Soil  
1.5% Xg + Soil  
2.0 % Xg + Soil  
1.0 % Bent. + Soil  
2.0 % Bent. + Soil  
3.0 % Bent. + Soil  
2.0 % PVAc + Soil  
MDD (kg/m3)  
OMC (%)  
3
MDD (kg/m3)  
OMC (%)  
4
MDD (kg/m3)  
OMC (%)  
5
MDD (kg/m3)  
OMC (%)  
6
MDD (kg/m3)  
OMC (%)  
7
MDD (kg/m3)  
OMC (%)  
8
MDD (kg/m3)  
OMC (%)  
9
MDD (kg/m3)  
OMC (%)  
10  
11  
12  
13  
MDD (kg/m3)  
OMC (%)  
MDD (kg/m3)  
OMC (%)  
MDD (kg/m3)  
OMC (%)  
MDD (kg/m3)  
1630.33  
1455.7  
1443.50  
56  
J. Civil Eng. Urban., 10 (6): 53-61, 2020  
average, Maximum dry density (MDD) is 2.1KN/m3 and  
Natural and stabilized soil failure indices  
According to Aderinola et al. (2015), Osogbo-Iwo  
road has 16 monitoring wells labeled MW1 through to  
MW16. From Tables 5-7, the CBR values are 20%,19%,  
11%, 22%, 23%, 18%, 45%, 54%,16%,49%, 9%, 34%,  
69%, 39%, 14% and 50% for MW1 to MW16  
respectively. The failure indices for the natural subgrade  
soils for MW1 to MW16 are 121, 127, 158, 150, 133, 141,  
118, 131, 133, 115, 158, 140, 132, 141, 145, 63  
respectively. According to Aderinola et al. (2015), the  
TDRAMS index for an ideal case scenario where the  
Depth to water table is farthest to the road pavement,  
soaked CBR is 50% and above, cambering is 3.75% on the  
asphalt thickness computed under the control monitoring  
well is 63. This is the numerical score that indicates the  
least failure susceptibility degree.  
The TDRAMS Index values for the stabilized samples  
which were computed using equation (1) are shown in  
Table 4. The stabilizers had varying levels of improvement  
on the failure indices of the soil with the highest levels of  
improvements (11.02%) decrease in the failure  
susceptibility indices) recorded by Guar gum at Location 2  
MW2 and the least level of improvement (-7.59 %)  
recorded at Location 3 MW3 as shown in Table 8.  
Table 4. TDRAMS Rating system and weights (Ola et al., 2009).  
Range  
Mean  
Rating  
Weight  
Parameter  
0-25  
25-50  
12.5  
37.5  
62.5  
87.5  
112.5  
137.5  
165.5  
187.5  
0.2  
1
2
50-75  
5
75-100  
125-150  
150-175  
175-200  
200+  
8
[T]  
Traffic Load (KN)  
10  
12  
14  
16  
10  
8
6
0-0.4  
0.4-0.8  
0.8-1.2  
1.2-1.8  
1.8-2.2  
2.2-2.6  
2.6-3.00+  
0-10  
0.6  
1.0  
6
[D]  
1.5  
4
5
4
Depth to water table (m)  
2.0  
3
2.4  
2
2.8  
1
5
9
10-20  
15  
7
20-30  
25  
5
[R]  
Sub-grade CBR Soaked (%)  
30-40  
35  
4
40-50  
45  
2
50+  
1
0-0.75  
0.375  
1.125  
1.875  
2.625  
8
0.75-1.5  
1.5-2.25  
2.25-3.00  
3.75+  
7
[A]  
Cambering (%)  
5
3
2
1
3
1
0-400  
200  
400  
10  
8
400-800  
800-1200  
1200-1600  
1600-2100  
2100+  
[M]  
MDD (Kg/m3)  
600  
5
1000  
1400  
4
2
1
0-0.01  
0.005  
0.015  
0.025  
0.035  
0.045  
7
0.01-0.02  
0.02-0.03  
0.03-0.04  
0.04-0.05  
6
[S]  
5
Asphalt Thickness (m)  
4
2
*weights of traffic load [T], depth to water-table [D], soaked CBR [R], cambering [A], maximum dry density [M], and asphalt thickness [S]  
57  
Oluyemi-Ayibiowu et al., 2020  
Table 5. Natural Soil Failure Indices (Aderinola et al., 2015).  
Data on Monitoring wells  
Index value for monitoring wells  
Factors  
Rating  
Weight  
MW MW MW MW MW MW  
MW MW MW MW MW MW  
1
2
3
4
5
6
1
2
3
4
5
6
T (Traffic load at  
failed section (m)  
97  
97  
97  
97  
97  
97  
8
6
8
6
8
8
8
7
8
6
5
48  
48  
48  
48  
48  
48  
50  
D (Depth to water  
Table at Failed section (m)  
1.43  
1.34 -0.26 0.13 0.90 -0.01  
10 10  
10  
30  
30  
50  
50  
35  
R (Soaked CBR at  
Failed Section (%))  
20  
19  
11  
22  
23  
18  
7
3
7
5
7
8
5
8
5
8
7
3
4
3
28  
9
28  
15  
28  
24  
20  
24  
20  
24  
28  
9
A (Cambering of  
failed Section (%))  
2.4  
2.1  
0.0  
0.0  
0.0  
2.9  
M (MDD of Sub-grade at  
Failed Section (KN/m3)  
2
2.01  
2
1.85 1.75 1.94  
2
2
2
2
2
4
2
4
2
2
2
2
2
1
4
2
4
2
4
4
4
4
4
2
4
2
S (Asphalt Thickness at  
Failed Section (m))  
0.05  
0.05 0.04 0.04 0.05 0.05  
Total TDRAMS Index  
121 127 158 150 133 141  
4th 5th 15th 14th 8th 11th  
Degree of Susceptibility to failure  
Table 6. Natural Soil Failure Indices (Aderinola et al., 2015).  
Data on Monitoring wells  
Index value for monitoring wells  
Factors  
Rating  
Weight  
MW MW MW MW MW MW  
MW MW MW MW MW MW  
7
8
9
10  
11  
12  
7
8
9
10  
11  
12  
T (Traffic load at  
failed section (m)  
97  
111 111 111  
111  
111  
8
10 10 10 10 10  
6
48  
60  
60  
60  
60  
60  
D (Depth to water  
Table at Failed section (m)  
-0.16 -0.29 -1.35 1.02 0.05 -0.05 10 10  
6
7
10 10  
5
50  
50  
30  
35  
50  
50  
R (Soaked CBR at  
Failed Section (%))  
45  
54  
16  
49  
9
34  
2
1
2
3
7
3
2
2
9
2
4
3
4
3
28  
3
28  
9
28  
9
28  
6
20  
6
16  
9
A (Cambering of  
failed Section (%))  
2.4  
2.1  
0.0  
0.0  
0.0  
2.9  
M (MDD of Sub-grade at  
Failed Section (KN/m3)  
2
2.01  
2
1.85 1.75 1.94  
2
5
1
2
2
2
2
2
2
2
2
1
2
1
4
5
4
2
4
2
4
2
4
2
4
S (Asphalt Thickness at  
Failed Section (m))  
0.03 0.05 0.05 0.05 0.05 0.06  
1
Total TDRAMS Index  
Degree of Susceptibility to failure  
118 131 133 115 158  
140  
3rd 6th 8th 2nd 15th 10th  
58  
J. Civil Eng. Urban., 10 (6): 53-61, 2020  
Table 7. Natural Soil Failure Indices (Aderinola et al., 2015).  
Data on Monitoring wells  
Index value for monitoring wells  
Factors  
Rating  
Weight  
MW  
13  
MW  
14  
MW  
15  
MW  
C
MW  
13  
MW  
14  
MW  
15  
MWC  
T (Traffic load at  
failed section (m)  
111  
111  
111  
81  
10  
10  
10  
10  
8
8
1
6
5
60  
50  
60  
50  
60  
40  
48  
5
D (Depth to water  
Table at Failed section (m)  
0.00  
0.02  
0.71  
3.0  
10  
4
R (Soaked CBR at  
Failed Section (%))  
69  
39  
14  
50  
1
3
7
3
1
1
4
3
4
9
16  
9
28  
9
4
3
A (Cambering of  
failed Section (%))  
3.0  
2.8  
2.9  
3.8  
3
M (MDD of Sub-grade at  
Failed Section (KN/m3)  
1.8  
1.71  
0.05  
1.97  
0.04  
2.1  
2
5
2
2
2
4
1
1
2
1
4
5
4
2
4
4
2
1
S (Asphalt Thickness at  
Failed Section (m))  
0.03  
0.05  
Total TDRAMS Index  
Degree of Susceptibility to failure  
132  
7th  
141  
145  
63  
12th  
13th  
1st  
Table 8. Comparison between Natural and Stabilized failure susceptibility indices.  
Monitoring Well  
(MW)  
Natural soil Index  
(Control)  
Stabilized Index using  
Rating and weight Model  
Percentage Decrease  
(%)  
Items  
Location 1 MW1  
Location 2 MW2  
Location 3 MW3  
Location 1 MW1  
Location 2 MW2  
Location 3 MW3  
Location 1 MW1  
Location 2 MW1  
Location 3 MW3  
Location 1 MW1  
Location 2 MW2  
Location 3 MW3  
121  
127  
158  
121  
127  
158  
121  
127  
158  
121  
127  
158  
115  
113  
154  
123  
121  
162  
123  
129  
170  
115  
121  
162  
4.96  
11.02  
2.53  
-1.65  
4.72  
-2.53  
-1.65  
-1.57  
-7.59  
4.95  
Guar gum  
Xanthan gum  
Bentonite  
Polyvinyl Acetate  
4.72  
-2.53  
CONCLUSION  
Recommendations  
From this research carried out on the Osogbo-Iwo road  
soil, the following conclusions were drawn:  
Based on the present study, the following  
recommendation are made:  
A) 11% Guar gum, 1 % Xanthan gum, 2% Bentonite  
and 2% Polyvinyl Acetate were deduced to be optimal  
mixes. However, Guar gum was observed to be the best  
stabilizer.  
B) 11% Guar gum reduced the failure susceptibility  
indices of the road by 11.02 % (i.e. from 127 to 113) but  
did not meet the standard set by Aderinola et al. (2015) of  
a standard road due to the absence of other factors like  
good drainage facilities, adequate road sections etc.  
In order to achieve best stabilized results and for  
durability of the road in service, adequate road sections  
with proper drainage facilities should be provided.  
Regular maintenance of roads should be undertaken  
as and when due to prevent critical deterioration of roads.  
Proper awareness should be given to professionals  
on the availability and use of locally available  
environmentally friendly construction materials.  
59  
Oluyemi-Ayibiowu et al., 2020  
AW, Gallipoli D. (2017). Mechanical properties of  
Proper awareness should be given to professionals on  
the availability and use of locally available  
environmentally friendly construction materials.  
biopolymer-stabilised soil-based construction materials.  
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Roads and Bridges, Vol II. Google Scholar  
DECLARATIONS  
Author’s contribution  
All the authors contributed equally to this work.  
Ola, S. A. (1975). Stabilisation of Nigerian Lateritic Soils with  
Cement. 6th Regional Conference For Africa on Soil  
Mechanics and Foundation Engineering, 145152. Google  
Competing interests  
The authors declare that they has no competing  
interests.  
Ola, S. A., Adekoya, J. A., & Ojo, J. S. (2009). Report of the  
Geotechnical Investigative Studies of Osogbo-Iwo Road.  
Akure. In CERAD FUTA .  
Ola SA, Braimoh AS, Fadugba OG. (2019). Measurement and  
Estimation of Soil Water Characteristic Curve for Four  
Unsaturated Tropical Soils, Annals of Faculty Engineering  
Huneduara-international Journal of Engineering, Tome  
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