Heavy metals' data in soils for agricultural activities

In this article, the heavy metals in soils for agricultural activities were analyzed statistically. Ten (10) soil samples were randomly taken across the agricultural zones in Odo-Oba, southwestern Nigeria. Ten (10) metals; namely: copper (Cu), lead (Pb), chromium (Cr), arsenic (As), zinc (Zn), cadmium (Cd), nickel (Ni), antimony (Sb), cobalt (Co) and vanadium (V) were determined and compared with the guideline values. When the values were compared with the international standard, none of the heavy metals in the study area exceeded the threshold limit. However, the maximum range of the samples showed that Cr and V exceeded the permissible limit which could be associated with ecological risk. The data can reveal the distributions of heavy metals in the agricultural topsoil of Odo-Oba, and can be used to estimate the risks associated with the consumption of crops grown on such soils.


a b s t r a c t
In this article, the heavy metals in soils for agricultural activities were analyzed statistically. Ten (10) soil samples were randomly taken across the agricultural zones in Odo-Oba, southwestern Nigeria. Ten (10) metals; namely: copper (Cu), lead (Pb), chromium (Cr), arsenic (As), zinc (Zn), cadmium (Cd), nickel (Ni), antimony (Sb), cobalt (Co) and vanadium (V) were determined and compared with the guideline values. When the values were compared with the international standard, none of the heavy metals in the study area exceeded the threshold limit. However, the maximum range of the samples showed that Cr and V exceeded the permissible limit which could be associated with ecological risk. The data can reveal the distributions of heavy metals in the agricultural topsoil of Odo-Oba, and can be used to estimate the risks associated with the consumption of crops grown on such soils.
& 2018 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Subject area
Earth Planetary Science More specific subject area Environmental Geophysics, Geochemistry, Soil Science Type of data

Raw and analyzed Experimental factors
Agricultural soils were randomly taken for heavy metal analysis

Experimental features
The ten metals as stated in the abstract were analyzed statistically and compared with the guideline values Data source location Odo-Oba, Southwestern Nigeria Data accessibility All the data are in this article

Value of the data
The data would give insight on the concentrations of heavy metals in the agricultural soils of the study area.
The data from this study could be used to study the relationships between the subsurface heavy metals and the rate of germination as well as productivity of the crops in the study area.
The study could be used to predict appropriate crops that could easily survive on the agricultural soils.
The data could be used for soil screening and to measure the food security strength in the environment.

Data
The data contains the geoexploration and geostatistical analysis of heavy metals in agricultural soils of Odo-Oba, southwestern Nigeria. Ten (10) samples were randomly collected for heavy metal analysis. Heavy metals are the metallic elements which exhibit relatively high density when compared with the density of water. The toxicity of heavy metals ranged from the route of exposure to the doses received [1]. In this article, ten (10) metals which are significant to the public health have been analyzed. The variables are: copper (Cu), lead (Pb), chromium (Cr), arsenic (As), zinc (Zn), cadmium (Cd), nickel (Ni), antimony (Sb), cobalt (Co) and vanadium (V). The results of the heavy metals from the study area are presented in Table 1. The data were compared with the international regulatory standard [2], which is presented in Table 2. The standards in Table 2 are grouped under threshold and permissible limits. These limits have been applied across the globe to measure the heavy metal contents in agricultural soils [3]. The threshold limit is used to checkmate the minimum toxicity in all soils environment. The permissible limit is applicable to the agricultural soils. If the values of the heavy metals exceed the permissible limit, such soil is regarded as contaminated soils for agricultural activities [1,2,4,5]. It is either associated with health risk (hr) or ecological risk (er). However, descriptive analyses were further used to explore the heavy metals' results, which are presented in Tables 3a and 3b.

Experimental design, materials and methods
Exploration of data sets in differs ways have been presented in [6][7][8][9][10][11]. Studies on the analysis of soils' usability for agricultural purposes could be found in [12][13][14][15][16]. Note: The risk associated with higher concentrations greater than the permissible limits are grouped into ecological risk (er) and health risk (hr).

Study area
The data were taken from the agricultural zones in Odo-Oba, southwestern Nigeria. The study area plays a key role in sustaining the food security of Ogbomoso and its environs. The major occupation of the residents in the study area is fishing and farming. Among the crops being cultivated in Odo-Oba are vegetables, tuber crops, leguminous crops and cereals crops [6]. The climatic conditions of the study area are the same as that of Ogbomoso, which have been discussed in [6,17].

Materials and methods
The samples were randomly collected from ten (10) locations, with the labeling ranging from Soil1 to Soil10. The labeled samples were dried under ambient temperature and sieved in order to remove the unwanted materials within the collected samples. The samples were packaged in plastic sock and moved to Canada for procedural analysis. The heavy metals' analysis was done in ACME Laboratories using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) technique. The standard procedures were followed during samples' collection [32,33] and analysis stages [34].

Statistical analysis
The range of each element was shown in Table 2. None of the mean value exceeded the threshold and the permissible limits. The maximum range of the samples showed that Cr and V exceeded the permissible limit which could be associated with ecological risk in the study area. Tables 3a and 3b show the comprehensive descriptive statistics of the data. Twenty-five (25) parameters were used to describe the distribution of the heavy metals in Odo-Oba. The results were presented as Tables 3a and 3b. The population number (N), mean, standard deviation (SD), standard error of mean (SEM),  Note: DF is the degree of freedom; at the 0.05, the data was not significantly drawn from a normally distributed population.  (Im), 1st quartile (Q1), median, 3rd quartile (Q3), maximum (Max), index of maximum (IM), Interquartile range (IR), and range were presented as the descriptive parameters in the two tables. Normality tests were further applied to the data sets in order to ensure if the values are modeled from the normal distribution based on the small sample size of the variables. The Lilliefors, Shapiro-Wilk and Kolmogorov-Smirnov normality tests were applied on the data sets. The results are shown in Table 4. In all the three tests, good fitting exist among the variables.
Correlation analyses among the variables were determined in order to visualize the kind of relationships that exist among the analyzed variables using Pearson (Table 5a), Spearman (Table 5b), and Kendall (Table 5c) correlations respectively. The distances between two correlated results were obtained by transforming the results from Tables 5a-5c using Eqs. (1)-(3). The results of these transformations were presented in Tables 6a and 6b. The scatter matrix plot of the correlated variables was shown in Fig. 2. It is a statistical tool that enables the estimation of the covariance matrix [8] (Table 6c).
where T is the transformation, P is the Pearson correlation, S is the Spearman correlation, and K is the Kendall correlation.

Acknowledgement
We sincerely appreciate the management of Covenant University, Nigeria for sponsoring the article processing fee of this work.

Transparency document. Supplementary material
Transparency document associated with this article can be found in the online version at doi:10. 1016/j.dib.2018.04.115.