3.3. LA ESCUELA Y LA EDUCACIÓN EN VALORES
3.3.4. La moral y los valores vistos por los niños y adolescentes
The pH medium significantly affects crystal structure and surface morphology such as the size and the entanglement of TiO2 nanostructures [22-24]. Due to the small particle size, the Van der Waals interaction is significant; this interaction increases exponentially as the particle size decreases. These facts favour the growth of clusters. Ibrahim and Sreekantan[25] reported that lower acidity promotes anatase structure while high acidity results in rutile phase formation.
This shows that the degree of crystallinity of anatase is pH dependent and lower acidity enhances the crystallinity, which also promotes the formation of big crystallite size. Mutuma et al. [26] reported the formation of pure TiO2 rutile phase calcined at 800°C and mixed phase (anatase and brookite) at 600 °C in a strongly acidic medium. While in the investigation
SPSBIC2019 71 | P a g e reported by Cassaignon et al. [27], a rutile crystalline phase was formed at the pH conditions less than 4.5 and only anatase structure formed at pH greater than 4.5.
However, the possibility of anatase structure in acidic medium is apparent. Therefore, investigation of TiO2 nanoparticles synthesized by a facile sol-gel method under acidic and basic medium is necessary for the clarification of the crystal forms, microstructure and optical properties of TiO2 nanoparticles.
4. Conclusion
TiO2-NPs have been extensively investigated during the last decade due to their wide view of applications. In summary, it is observed that the synthesis of this nanomaterial was mostly done using the sol-gel technique due to the high quality of TiO2 nanoparticles produced. The sol-gel technique has emerged as a promising processing route for the synthesis of nanosized particles because of the simplicity and high purity nanopowders resulting from the availability of high purity chemicals raw materials. Changes in composition, structure, and morphology of the TiO2
nanoparticle are strictly dependence with the pH and calcination temperature.
Acknowledgements
The authors appreciate the financial supports received from the Tertiary Education Trust Fund (TETFund) of Nigeria under a grant number TETFUND/FUTMINNA/2017/01 is highly appreciated.
References
[1] M. Troester, H. Brauch, and T. Hofmann (2016). Vulnerability of drinking water supplies to engineered nanoparticles Water Research 96: 255-279.
[2] H. Qian, Y. Hu, Y.Liu, M. Zhou, and C. Guo(2012). Electrostatic self-assembly of TiO2
nanoparticles onto carbon spheres with enhanced adsorption capability for Cr(VI).
Materials Letters68: 174-177.
[3] S.G. Ullatti, and P. Periyat(2017). Sol-Gel Synthesis of Titanium Dioxide. Sol-Gel Materials for Energy. Environment and Electronic Applications 1: 271-283.
[4] A. Sharma, R.K. Karn, and S.K. Pandiyan (2014). Synthesis of TiO2 Nanoparticles by Sol-gel Method and Their Characterization. Journal of Basic and Applied Engineering Research 1(9): 1-5.
[5] K. Zhang, K.C. Kemp, and V. Chandra(2012). Homogeneous anchoring of TiO2
nanoparticles on graphene sheets for waste water treatment. Materials Letters 81: 127-130.
[6] Y. Li, W. Zhang, X. Li, and Y. Yu(2014). TiO2 nanoparticles with high ability for selective adsorption and photodegradation of textile dyes under visible light by feasible preparation. Journal of Physics and Chemistry of Solids 75: 86-93.
[7] H. Lu, J. Wang, M. Stoller, T. Wang, Y. Bao, and H. Hao (2016). An Overview of Nanomaterials for Water and Wastewater Treatment. Advances in Materials Science and Engineering 1: 1-10.
SPSBIC2019 72 | P a g e [8] S.Z. Islam, S. Nagpure, D.Y. Kim, and S.E. Rankin(2017). Synthesis and Catalytic
Applications of Non-Metal Doped Mesoporous Titania. Inorganics 5(15): 1-43.
[9] A.B. Kashyout, M. Soliman and M. Fathy(2010). Effect of preparation parameters on the properties of TiO2 nanoparticles for dye sensitized solar cells. Renewable Energy 35:
2914-2920.
[10] T. Phonkhokkong, S. Thongtem, C.S. Thongtem, A.Phuruangrat,and W.
Promnopas(2016). Synthesis and Characterization of TiO2Nanopowders for Fabrication of Dye Sensitized Solar Cells. Digest Journal of Nanomaterials and Biostructures 11(1):
81-90.
[11] M.A. Khan, M.S. Akhtar, and O. Yang(2010). Synthesis, characterization and application of sol-gel derived mesoporous TiO2 nanoparticles for dye-sensitized solar cells. Solar Energy 84: 2195-2201.
[12] R. Vijayalakshmi, and V. Rajendran(2012). Synthesis and characterization of nano-TiO2
via different methods. Archives of Applied Science Research 4(2): 1183-1190.
[13] M. Kavitha, C. Gopinathan, and P. Pandi(2014). Synthesis and Characterization of TiO2Nanopowders in Hydrothermal and Sol-Gel Method. International Journal of Advancements in Research and Technology 2(4): 102-108.
[14] A. Saleh, F.A. Rasin, and M.A. Ameen(2009). TiO2 nanoparticles prepared by sol-gel.
Journal of Materials Science and Engineering 3(12): 81-84.
[15] Y. Bessekhouad, D. Robert,and J.V. Weber (2003). Preparation of TiO2 nanoparticles by Sol-Gel route. International Journal of Photoenergy5: 153-158.
[16] L. Agartan, D. Kapusuz, J. Park, and A. Ozturk(2013). Effect of H2O/TEOT ratio on photocatalytic activity of sol-gel derived TiO2 powder, Nanomater. Energy2: 280-287.
[17] M. Islam,and S. Basu(2015). Effect of morphology and pH on (photo) electrochemical degradation of methyl orange using TiO2/Ti mesh photocathode under visible light.
Journal of Environmental and Chemical Engineering 3: 2323-2330.
[18] Y. Chen, X. Xu, J. Fang, G. Zhou, Z. Liu, X. Wu, J. Chu,and X. Zhu (2014). Synthesis of BiOI-TiO2 Composite Nanoparticles by Microemulsion Method and Study on Their Photocatalytic Activities. The Scientific World Journal 1: 1-8.
[19] K. Pavel, and K. Radovan(2015). The Effect of Calcination on the Structure of Inorganic TiO2 Nanofibers. Oct 14th-16th2015, Brno, Czech Republic, EU. NanoCon.
[20] N.S.A. Abdullah, S. So’aib, and J. Krishnan(2017). Effect of Calcination Temperature on ZnO/TiO2 Composite in Photocatalytic Treatment of Phenol under Visible Light.
Malaysian Journal of Analytical Sciences 21(1): 173-181.
[21] D. Aphairaj, D.Wirunmongko, P.Chaloey-arb, S. Pavasupree, and P. Limsuwan(2011).
Effect of calcination temperatures on structures of TiO2 powders prepared by hydrothermal method using Thai leucoxene mineral. 9thEco-Energy and Materials Science and Engineering Symposium, Chiang Rai, Thailand, 25-28 May 2011
[22] J. Xue, Q.Shen, F.Yang, W. Liang, and X. Liu (2014). Investigation on the influence of pH on structure and photoelectrochemical properties of CdSe electrolytically deposited into TiO2 nanotube arrays, Journal of Alloys and Compound607: 163-168.
[23] A.M. Selman, Z. Hassan, and M. Husham (2014). Structural and photoluminescence studies of rutile TiO2 nanorods prepared by chemical bath deposition method on Si substrates at different pH values. Measurement 56: 155-162.
[24] V.S. Mohite, M.A. Mahadik, S.S. Kumbhar, V.P. Kothavale, A.V. Moholkar, K.Y.
Rajpure, and C.H. Bhosale (2015). Photoelectrocatalytic degradation of benzoic acid usingsprayed TiO2 thin films. Ceramic International41: 2202-2208.
SPSBIC2019 73 | P a g e [25] S.A. Ibrahim, and S. Sreekantan (2010). Effect of pH on TiO2 nanoparticles via sol gel
method. International Conference on X-Rays & Related Techniques in Research &
Industry, June 9-10, 2010, Aseania Resort Langkawi, Malaysia,pp. 84-87.
[26] B.K. Mutuma, G.N. Shao, W.D. Kim, and H.T. Kim (2015). Sol-gel synthesis of mesoporous anatase-brookite and anatase-brookite-rutile TiO2 nanoparticles and their photocatalytic properties, Journal of Colloid Interface and Science442: 1-7.
[27] S. Cassaignon, M. Koelsch, and J.P. Jolivet (2007). From TiCl3 to TiO2 nanoparticles (anatase, brookite and rutile): thermohydrolysis and oxidation in aqueous medium.
Journal of Physical Chemistry and Solids 68: 695-700.
SPSBIC2019 74 | P a g e
Physicochemical Properties of Forest Surface Soils in Kogi State, Nigeria Azeez, A.A1*. Iyaka, Y.A2 . & Ndamitso, U.U3.
3&2Department of Chemistry, Federal University of Technology, Minna,
1Department of Chemistry, Kogi State College of Education, Ankpa.
* Corresponding author Abstract
Soil is an essential component for growth of plants and survival of organisms. In this work, the soil samples are forty forest surface soils of Kogi state randomly collected at the depths of 0–
20cm and subjected to physicochemical examination using standard routine laboratory tests to assess the quality of soil. In addition, mean, range and Pearson’s moment correlation were employed to analyze the data. The results showed that sand, silt and clay contents ranged from 51.80 % - 94.00 %, 3.50 % - 31.00 % and 2.00 % - 22.60 % respectively. Texturally, the soils were predominantly sandy loam and loamy sand with sand dominating the particle fractions of the soil. Soils were moderately acidic with mean pH values 5.46 ranging from 4.47-6.84.
Electrical conductivity mean value of the saturation extract was 0.237 dSm-1 which ranged from 0.036 dSm-1 to 0.574 dSm-1 indicating non-saline nature of the soils and suitable for plants growth and soil microbial processes. The soils were non- calcareous in nature and having calcium carbonate content ranges from 0.08 % - 2.00 %. The available mean of soil organic matter was 8.85 % (ranged from 3.19 % - 13.35 %) indicating high soil organic matter. These results showed that organic matter is better protected and had potentials for storing organic carbon of appreciable concentration. Similarly, the mean of cation exchange capacity showed 15.01 cmolckg-1 (ranged 12.20 cmolc.kg-1-18.60 cmolckg-1) indicating moderate. Finally, pH showed strong positive correlation with soil organic matter, cation exchange capacity and calcium carbonate content while soil electrical capacity showed negative correlation with pH, soil organic matter and calcium carbonate content. From this study, it was ascertained that these forest soils possess potential to hold nutrients and make it readily available for plant to absorb which in turn possess the capacity to support ecosystems.
Keywords: forest, physio-chemical properties, soil nutrient, surface soil Introduction
Soil is a vital part of the Earth. It serves as a natural medium for plants growth (Osuocha et al., 2016). Soils are the naturally occurring physical materials covering of the earth’s surface and a mixture of organic matter, minerals, gases, liquids and organisms that together support life. The earth’s body of soil is the pedosphere (skin of the earth), which has four functions namely: a medium for plant growth; a means of water storage, supply and purification; a modifier of earth’s atmosphere and a habitat for organisms. All of which, in turns, modify the
SPSBIC2019 75 | P a g e soil. Soil, as an integral element of the natural environment, is a non-renewable resource (Massas et al., 2013). According to Keesstra et al. (2016), soils play an important role in global food security, water security, biofuel security and human health. To Decock et al. (2015), soil is a key component of the earth system as it controls the geochemical, biological, erosional and hydrological cycles and offers services, goods and resources for human kind.
Soil is a significant determinant of the economic status of nations. Soil ecosystem services fulfils human needs (Robinson et al., 2012), assigning economic value to things that contribute to human well-being. Based on this, soil quality has received great attention in recent years (Sinha et al., 2014). Specifically, Khormali et al (2009) refers to soil quality as a concept that includes soil physical, chemical and biological factors and it is used as a framework for the evaluation of soil. The quality of soils does not depend on its ability to supply adequate nutrients alone but the nutrients must be in the right proportion as needed by plants (Ayeni and Adeleye, 2011). In addition, high quality soils not only produce better food and fibre, but also help to establish natural ecosystems and enhance air and water quality (Griffiths et al., 2010).
The quality of growth and reproduction of forest cannot be understood without the knowledge of its soil nutrient. The soil and vegetation have a complex interrelation, because they develop together over a long period of time, the selective absorption of nutrient elements by different tree species and their capacity to return them to the soil brings about changes in soil properties (Sharma et al., 2010). Soil helps secure and renew the forest. Forests also help secure and renew the soil. The forest covers and protects the soil from extreme heat and cold while slowing the natural forces of erosion like water, wind, and gravity. The nutrients strength of a forest soil to maintain and support the plant growth generally depends on its physical, chemical and biological properties. Researchers have reported that the nature of parent material has been found to influence development and characteristics of soils (Umeri et al., 2016). Soil sustains the forest and provides raw materials for its life: fallen leaves, woody debris, and dead animals recycle through the soil.
The estimation of soil available nutrient contents in a complex heterogeneous system is of a great pedological as well as ecological importance (Olojugba and Fatubarin, 2015).
Trees affect the forest ecosystem by manipulating its constituents prominent to changing future forest vegetation (Frouz et al., 2013c). Tree cover in turn, influences the growth and development of physical and chemical properties of soil. These properties sustain and support the plant growth in forest soil. Soil physical and chemical properties play a central role in transport and reaction of water, solutes and gases in soils, their knowledge is very important in
SPSBIC2019 76 | P a g e understanding soil behaviour to applied stresses, transport phenomena in soils, hence for soil conservation and planning of appropriate agricultural practices (Olorunfemi et al.,2018).
A good knowledge of the variations of soil physical and chemical properties their interactions as it relates to micronutrient status is essential for good land evaluation which is a pre-requisite for sound land use planning (Lawal et al., 2013). Assessing soil physicochemical properties are used to understand the potential status of nutrients in forest soils. This knowledge can ascertain whether the forest soils are useful to meet plants requirement for rapid growth.
For this reason, the present study attempts to evaluate the physiochemical properties of forest surface soils in Kogi state of Nigeria.
Materials and Methods Description of the Study Area
This research was conducted in the forest vegetative sites of Kogi state, Nigeria. The capital of Kogi state (Lokoja) is located on the confluence of Rivers Niger and Benue at Lokoja on Latitude 6° 44’ North and Longitude 7° 44’ East. Going by the present composition of the state, Kogi State is quintessentially Nigeria, with three dominant ethnic groups namely; Igala, Ebira and Okun (Yoruba) and several minorities (Omotola, 2008). Kogi state has a total land area of 28,313.53 square kilometres and on the basis of the 1991 Nigerian national population census, the total population of Kogi state was 2,141,756 (Ali et al., 2012).
Kogi state just as many other states in Nigeria is blessed with natural resources. It has expensive fertile land for agriculture all over the state, coal at Okobo, Ankpa, huge deposits of iron ore at Ajaokuta and limestone at Obajana. The climate of the Kogi state is a tropical climate with two distinct seasons [rainy season (March – October) and dry season (November – March)]. The rainfall regime shows double maxima which is separated by a comparatively low rainfall period (dry period) in August called August Break. The mean annual rainfall ranges from 1,560mm at Kabba in West to 1,808mm at Anyigba in the East. Average monthly temperature varies from 17oC to 36.2oC. The temperature shows some variation throughout the years. The state is known for cultivation of arable crops such as yam, cassava, maize, groundnut, cowpea etc (Omotola, 2008).
Sample Collection and Preparation
A total of 40 composite soil samples were collected at forty forest locations within villages of East, Central and West of Kogi State and used for this study. These forests are uncultivated and comprise of shrubs, woodlands and deciduous trees without the protection of the state forest reserve agency. From each forest location, five soil samples were randomly collected in different points and pooled together to form a composite sample for that location.
They were collected from surface at the depths of 0–20 cm by scooping surface soils of the sampling areas using a stainless steel hand trowel. After collection, each composite was then labelled, transferred to a separate clean plastic container and transported to the laboratory.
SPSBIC2019 77 | P a g e Prior to analysis, the composite soil samples were air- dried at room temperature for two weeks in the laboratory, ground (using a ceramic mortar and pestle), sieved (using a 2-mm sieve) and stored in well labelled sample plastics for laboratory analysis. The prepared soil samples were analyzed by means of internationally-accepted classical methods.
Determination of Physico-chemical Properties
Soil particle sizes were determined using the hydrometer method described by Gee and Or (2002) and classification was carried out using the USDA classification system (Soil Survey Staff, 2009). The pH and Electrical conductivity of the soil samples were measured in distilled water at ratio 1:1 as demonstrated by Osayande et al. (2015). Calcium carbonate content was estimated following the procedure described by Rowell (1994). The organic carbon was determined using the Walkley - Black wet oxidation procedure and the soil organic matter content was determined by multiplied organic carbon with 1.724 (Nelson and Sommers, 1982).
The cation exchange capacity (CEC) at pH 7.0 was determined following the procedure described by Chapman (1965).
Quality Control
All reagents and chemicals were of high analytical grade and high purity distilled water was used for all dilutions. All glassware and plastic containers used were soaked in 10% v/v HNO3 solution overnight (Onianwa, 2001) and rinsed thoroughly with distilled water before used to avoid contaminants.
Statistical Analysis
Data obtained was statistically analyzed using mean and range. Pearson’s correlation analysis was also used to establish significant relationship between the selected physiochemical properties of soils.
Results and Discussion
Table 1: Particle Size Distribution of the Experimental Forest Surface Soils
Sampling Site Sand (%) Silt (%) Clay (%) Texture Silt/Clay Silt and Clay (%)
SPSBIC2019 78 | P a g e 1
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
60.50 62.50 86.00 55.50 62.10 90.00 82.00 54.90 63.20 67.50 56.90 77.00 80.10 85.40 71.50 92.00 58.90 52.10 75.00 59.30 56.90 94.00 59.60 73.90 66.80 76.00 93.00
25.00 20.50 8.50 25.90 21.00 6.00 10.00 28.50 18.90 17.30 26.40 12.90 10.90 8.90 15.80 4.70 30.00 31.00 14.50 26.40 26.00 3.50 22.00 18.00 18.30 13.00 5.00
14.50 17.00 5.50 18.60 16.90 4.00 8.00 16.60 17.90 15.20 16.70 10.10 9.00 5.70 12.70 3.30 11.10 16.90 10.50 14.30 17.10 2.50 18.40 8.10 14.90 11.00 2.00
Sandy loam Sandy loam Sandy Sandy loam Sandy loam Sandy Loamy sand Sandy loam Sandy loam Sandy loam Sandy loam Loamy sand Loamy sand Sandy Loamy sand Sandy Sandy loam Sandy loam Loamy sand Sandy loam Sandy loam Sandy Sandy loam Loamy sand Sandy loam Loamy sand Sandy
1.72 1.21 1.55 1.39 1.24 1.50 1.25 1.72 1.06 1.14 1.58 1.28 1.21 1.56 1.24 1.42 2.73 1.83 1.38 1.85 1.52 1.40 1.20 2.20 1.23 1.18 2.50
39.50 37.00 14.00 44.50 37.90 10.00 18.00 45.10 36.80 32.50 43.10 23.00 19.90 14.60 28.50 8.00 41.10 7.90 25.00 40.70 43.10 6.00 40.40 26.10 33.20 24.00 7.00
SPSBIC2019 79 | P a g e 28
29 30 31 32 33 34 35 36 37 38 39 40
Overall mean Overall range
66.50 69.50 71.20 90.10 76.20 51.80 81.00 72.10 89.40 79.10 68.10 82.90 57.40 71.70 51.80- 94.00
21.30 18.80 14.90 6.00 13,80 25.60 11.00 18.50 6.40 12.50 18.90 10.00 24.00 16.77 3.50-31.00
12.20 11.60 13.90 3.90 10.00 22.60 8.00 9.40 4.20 8.40 13.00 7.10 18.60 11.53 2.00-22.60
Sandy loam Sandy loam Loamy sand Sandy Loamy sand Sandy loam Loamy sand Loamy sand Sandy Loamy sand Sandy loam Loamy sand Sandy loam Loamy sand
1.75 1.62 1.07 1.54 1.38 1.13 1.38 1.97 1.52 1.49 1.45 1.41 1.29 1.50 1.06-2.73
33.50 30.40 28.80 9.90 23.80 48.20 19.00 27.90 10.60 20.90 31.90 17.10 42.60 28.35
6.00-48.20
Soil particle distribution of Kogi State forest surface soils in Table 1 showed that, the overall mean of sand fraction was 71.70% (ranged 51.80%-94.00%), silt had 16.77% (ranged 3.50%-31.00%) and clay had 11.53 % (ranged 2.00%-22.60%). Thus sand fraction was the highest, followed by silt and then clay. This was in agreement with the findings of Adugna and Abegaz (2016) that found sand content of soils of forestland to be the highest. The results revealed that the textures of Kogi state forest soils are mainly sandy loam and loamy sand textured at the surface. This was in conformity with what Uquetan et al. (2017) reported.
The silt/clay ratio ranged from 1.06 - 2.73 with mean 1.50 was above 0.15 indicating that the soils are relatively young with high degree of weathering potential. This is in harmony with report from Sharu et al. (2013) and Jimoh et al. (2016) on the soils. More so, the finding showed that mean of 28.35 % silt plus clay content ranged 6.00% - 48.20%. This is because about 48%
of the soil samples contained more than 30% (clay + silt) contents. This has shown that silt plus clay content is a relatively important determinant of soil organic matter level in soils. The capacity of soils to maintain organic carbon is influenced by its clay plus silt content (Bationo et al., 2007).
SPSBIC2019 80 | P a g e Table 2: pH, Electrical Conductivity (EC), Calcium Carbonate Content (CaCO3), Soil Organic Matter (SOM) and Cation Exchange Capacity (CEC) of the Experimental Forest Surface Soils
Sampling Site
pH EC (dSm-1) CaCO3(%) SOM (%) CEC (cmolckg-1)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
4.64 5.65 4.81 5.78 5.85 5.33 6.39 4.49 4.46 5.91 6.33 4.79 6.46 5.51 4.73 6.07 5.43 4.49 5.29 4.70 5.48 5.21 6.84
0.456 0.141 0.343 0.124 0.114 0.255 0.070 0.574 0.538 0.105 0.076 0.372 0.062 0.177 0.414 0.080 0.202 0.478 0.301 0.450 0.187 0.309 0.036
0.20 1.30 0.43 1.43 1.50 0.83 1.80 0.18 0.08 1.63 1.75 0.40 1.85 1.13 0.33 1.68 0.95 0.10 0.73 0.28 0.98 0.63 2.00
5.01 9.93 6.62 9.98 10.09 8.38 11.67 3.19 3.31 11.49 11.63 6.59 11.68 9.86 6.51 11.62 9.83 3.35 8.32 6.49 9.83 8.19 13.35
12.50 15.80 13.30 16.20 16.60 14.30 17.40 12.00 12.20 17.00 17.30 13.10 17.50 15.20 12.80 17.20 14.80 12.30 14.00 12.60 14.90 13.70 18.60
SPSBIC2019 81 | P a g e 24
25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
Overall Mean Overall Range
5.57 6.02 5.78 5.83 4.74 4.59 5.51 5.26 6.63 5.40 5.41 4.81 5.52 6.70 4.93 5.88 5.31 5.50 4.47-6.84
0.150 0.087 0.132 0.128 0.401 0.476 0.167 0.308 0.046 0.237 0.212 0.361 0.158 0.043 0.328 0.108 0.282 0.237 0.036-0.574
1.23 1.65 1.35 1.43 0.38 1.25 1.08 0.63 1.80 0.88 0.90 0.48 1.18 1.90 0.55 1.57 0.78 1.03 0.08-2.00
9.91 11.60 9.97 10.00 6.57 4.97 9.85 8.24 11.73 8.41 8.61 6.71 9.90 13.26 8.17 10.91 8.38 8.85 3.19-13.35
15.60 17.10 16.00 16.40 12.90 12.40 15.00 13.80 17.80 14.50 14.70 13.40 15.40 18.30 13.50 16.80 14.10 15.01 12.20-18.60
Soil pH
The results in Table 1 also, show that the overall mean pH of studied Kogi state forest surface soils ranged from 4.47 to 6.84 with a mean value of 5.50 indicating that the soils were moderately acidic to almost neutral. The mean value reported in this study is within the range for optimum plant growth and in almost the same range with pH of some selected soils of rain forest zones of Delta state, Nigeria which ranged from 4.72 to 6.52 at the surface soils reported by Umeri et al. (2017). Also, these pH values are within those obtained by Osakwe and Akpoveta (2012) and consistent with findings of Uquetan et al. (2017) who observed pH of 4.2- 6.0 in natural forest of Akamkpa, Cross River State, Nigeria. In addition, the mean pH of
SPSBIC2019 82 | P a g e 5.50 obtained is within the ideal pH range of 5.5-7.0 for optimum growth and nutrient availability to plants (Brady and Weil, 2010).
Electrical Conductivity (EC) of the soil
The overall mean EC of studied Kogi state forest surface sampled soils was 0.237 dSm-1 (ranged 0.036 dSm-1 to 0.574 dSm-1). Here, all the soil sampled (100%) were salt free (i.e. no saline). However, the EC values recorded from these forest surface soils were within the normal range of less than 1 dS/m which are considered non-saline and suitable for plants growth and soil microbial processes according to Deshmukh (2012) and Nachtergaele et al. (2009). Similar result was also reported by Jimoh et al. (2016) in Northern Guinea Savanna zone of Nigeria.
Calcium Carbonate Content of the soil
The overall mean CaCO3 content of the studied Kogi state forest surface soils showed 1.03%
(ranged 0.08% to 2.00%). On the basis of CaCO3 rating suggested by Nachtergaele et al.
(2009), the soils of the studied soils were non- calcareous in nature.
Soil Organic Matter (SOM) content
Additionally, the overall mean percentage of soil organic matter of studied Kogi state forest surface soils was 8.85% (ranged 3.19% to 13.35%). These values of organic matter contents are considered high for forest soils. The higher SOM content exhibited by the topsoil in this study is also consistent with that demonstrated by Ahukaemere et al (2012); Straaten et al, (2015) and Adugna and Abegaz (2016) in forestlands. The higher organic matter under these forest lands might be attributed to continuous accumulation of un-decayed and partially decomposed plant and animal residues mainly in the surface soils of forestland.
Cation Exchange Capacity (CEC) of the Soil
The overall mean of CEC of the studied Kogi state forest surface soils was 15.01cmolc.kg-1 (ranged 12.20 cmolc.kg-1-18.60 cmolc.kg-1). Soil CEC has been classified as very low (<10cmolc.kg-1), low (10-15cmolc.kg-1), moderate (15-20cmolc.kg-1) and high (>20cmolc.kg
-1) (Abe et al., 2010). On the basis of this classification, 50% of the surveyed forest sites have CEC values >15 cmol kg-1and 50% have moderate CEC. CEC is an important property of soil because it is a useful indicator of soil fertility and nutrient availability for flora growth (Hazelton and Murphy 2007). Thus high SOM increases cation exchange capacity (CEC).
Table 3: Correlation between Studied Physico-chemical Properties of Soils
physico-chemical properties Correlation coefficient (r)
Soil pH and SOM 0.92
Soil EC and pH -0.59
SPSBIC2019 83 | P a g e
Soil CEC and SOM 0.95
Soil pH and CEC 0.95 Soil pH and CaCO3 0.98
Soil EC and SOM -0.98
Table 3 showed relationship existed among soil physicochemical properties which positively or negatively, interfered with nutrient availability (Onwudike, 2015).
Based on the Pearson correlation coefficient data analysis, the observed soil pH showed significant positive correlation with SOM and the correlation coefficient is 0.92 which indicated the higher the pH ( i.e. the lower the acidity level of the soil), the higher the SOM.
Also, soil EC showed negative correlation with pH (r= – 0.59). This means that at low soil pH value, there is high soluble salt content and therefore high electrical conductivity. The research findings consistent with the study of Nur Aini et al. (2014) who reported that soil EC had significant negative relationship with the soil pH.
In addition, soil CEC was correlated with SOM for all the soils which showed correlation coefficient of 0.95. This means that, there is a strong correlation between the CEC values, and the amount of organic matter present in the soil as Organic matter is a major source of negative electrostatic sites. The research findings conform to the works of Olorunfemi et al. (2018) and Fasinmirin and Olorunfemi (2012) who all reported that soil samples with higher values of CEC were found to have high levels of organic matter and pH levels. More so, there is a significant positive correlation between soil CEC and pH with correlation coefficient of 0.95.
This finding conform to the works of Olorunfemi et al. (2018) who all reported that soil samples with higher values of CEC were found to have high pH levels.
Further more, a positive correlation existed between soil pH and CaCO3 with correlation coefficient of 0.98. This relationship was strong and significant which indicated that pH increased with increased in the amount of CaCO3 present. Finally, organic matter was shown to correlate negatively with electrical conductivity (r = -0.98) suggesting that soils high in organic matter tend to favour the immobilization of soluble ions in soils. This indicated that soil EC decreased with an increased in SOM. This finding is supported by the works of Nelson et al. (2017) who all reported that SOM had significant strong negative relationship with the soil EC.
Conclusion and Recommendation
In conclusion, the forest soils in this studies area contain significant quantities of all the nutrients analysed. These forest soils proven to contain high soil organic matter, non-saline (i.e.
free from salt) and non- calcareous in nature. Also, the soils were predominantly sandy loam and loamy sand and possess suitable pH for normal forest ecosystems. These soils have moderate CEC values and this might be due to their high organic matter, presence of low amount of CaCO3 and very low soluble salt in the soil.
SPSBIC2019 84 | P a g e In addition, pH showed strong positive correlation with SOM, CEC and CaCO3. Also, soil EC showed negative correlation with pH and SOM. Correlation results showed that relationships existing among soil physicochemical properties interfered with nutrient availability. This conforms to the findings of Tsozue et al. (2016) who showed that plant nutrient availability depends on relationships among soil physicochemical properties.
It is therefore recommended that, the conservation of these forests in Kogi state is an urgent need for the proper management practices of the forests which will in turn increase the quality of soils and the forest. This will reduce indiscriminate destruction of forest cover and protection of the top soils.
References
Abe, S. S., Buri, M. M., Issaka, R. N., Kiepe, P. & Wakatsuki, T. (2010). Soil fertility potential for rice production. Journal of Agricultural Research quarterly, Vol. 44(4), 343–355.
Adugna, A. & Abegaz, A. (2016). Effects of land use changes on the dynamics of selected soil properties in northeast Wellega, Ethiopia. SOIL, Vol. 2, 63–70.
Ahukaemere, C.M., Ndukwu, B.N. & Agim, L.C. (2012). Soil quality and soil degradation as influenced by agricultural land use types in the humid environment. International Journal of Forest, Soil and Erosion, Vol. 2 (4), 175–179.
Ali, S., Yusufu, B., Moses, S.E. & Abu, M. (2012). The Scramble for lugard house:
Ethnic identity politics and recurring tensions in Kogi State, Nigeria. Canadian Social Science, Vol. 8(1), 130–135.
Ayeni, L.S. & Adeleye, E.O. (2011). Soil nutrient status and nutrient interactions as influenced by agro wastes and mineral fertilizer in an incubation study in the Southwest Nigeria. International Journal of Soil Science, Vol. 6 (1), 60–68.
Bationo, A., Kihara, J., Vanlauwe, B.,Waswa, B. & Kimetu, J. (2007). Soil organic carbon dynamics, functions and management in West African agroecosystems.
Agricultural systems, Vol. 94, 13–25.
Brady, N.C. & Weil, R.R. (2010). Elements of the nature and properties of soils. 3rd edition. Pearson Education, Inc., Upper Saddle River, New Jersey. Pp. 74–89.
Chapman, H.D. (1965). Cation exchange capacity. In Methods of Soil Analysis (Number 9 in the Series Agronomy), Part 2, A. Black, ed., American Institute of Agronomy, Madi-son, Wisconsin, 891–901.
Decock, C., Lee, J., Necpalova, M., Pereira, E. I. P., Tendall, D. M. & Six, J. (2015).
Mitigating N2O emissions from soil: From patching leaks to transformative action.
Soil, Vol. 1, 687–694.
SPSBIC2019 85 | P a g e Deshmukh, K.K. (2012). Studies on chemical characteristics and classification of soils from
sangamner area, Ahmadnagar District, Maharastra. Rasayan Journal of .Chemistry, Vol.
5(1), 74–85.
Fasinmirin, J. T. & Olorunfemi, I. E. (2012). Comparison of hydraulic conductivity of soils of the forest vegetative zone of Nigeria. Applied Tropical Agriculture, Vol. 17(1), 64–77.
Frouz, J., Liveckova, M., Albrechtova, J., Chronakova, A., Cajthaml, T, Pizl, V., Hanil, L., Stary, J., Baldrian, P., Lhotakova, Z., Simackova, H. & Cepakova, J. (2013c). Is the effect of trees on soil properties mediated by soil fauna? A case study from post-mining sites. Forest Ecology and Management, Vol. 309, 87–95.
Gee, G. W. & Or, D. (2002). Particle size distribution. In: Dane, J. H and Topp, G. C.
(eds). Methods of soil Analysis. Part 4, Physical methods. Soil Science American Book Series No.5, ASA and SSSA, Madison, W.I. Pp. 255–293.
Griffiths, B.S., Ball, B.C. & Bohanec, M. (2010). Integrating soil quality changes to arable agricultural systems following organic matter addition, or adoption of a ley-arable rotation. Applied Soil Ecology, Vol. 46 (1), 43–53.
Hazelton, P. & Murphy, B. (2007). Interpreting Soil Test Result: What Do All the Numbers Mean? Australia: CSIRO Publishing. Pp. 64– 71.
Jimoh, A.I., Malgwi, W.B., Aliyu, J. & Shobayo, A.B. (2016). Characterization, classification and agricultural potentials of soils of gabari district, Zaria, Northern guinea savanna zone Nigeria. Biological and Environmental Sciences Journal for the Tropics, Vol. 13(2), 102–113.
Keesstra, S.D., Bouma, J., Wallinga, J., Tittonell, P., Smith, P., Cerda, A., Montanarella, L., Quinton, J.N., Pachepsky, Y., Putten, W.H.V., Bardgett, R.D., Moolenaar, S., Mol, G., Jansen, B.& Fresco, L.O. (2016).The significance of soils and soil science towards realization of the United Nations Sustainable Development Goals. Soil, Vol. 2, 111–128.
Khormali, F., Ajami, M., Ayoubi, S., Sirinivasarao, C.H. & Wani, S.P. (2009). Role of deforestation and hillslope position on soil quality attributes of loss-derived soils in Golestan province, Iran. Journal of Agriculture, Ecosystem and Environmental, Vol. 134, 178–189.
Lawal, B.A., Ojanuga, A.G., Isada, P.A. & Mohammed, T.A. (2013). Characterization, classification and agric potentials of soils on a Toposequence in Southern Guinea Savanna of Nigeria. World Academy of Science Engineering and Technology.
International Journal of Biology, Veterinary, Agricultural and Food Engineering, Vol.
7 (5), 146–150.
Massas, I., Kalivas, D., Ehaliotis, C. & Gasparatos, D. (2013). Total and available heavy metal concentrations in soils of the Thriassio plain (Greece) and assessment