SciELO - Scientific Electronic Library Online

vol.41Spatial variability of soil physical-hydric attributes under bovine trampling in agreste of Pernambuco State, BrazilTemporal evaluation of soil chemical attributes after slash-and-burn agriculture in the Western Brazilian Amazon author indexsubject indexarticles search
Home Pagealphabetic serial listing  

Services on Demand



  • text new page (beta)
  • English (pdf)
  • Article in xml format
  • How to cite this article
  • SciELO Analytics
  • Curriculum ScienTI
  • Automatic translation


Related links


Acta Scientiarum. Agronomy

Print version ISSN 1679-9275On-line version ISSN 1807-8621

Acta Sci., Agron. vol.41  Maringá  2019  Epub Dec 17, 2018 


Geochemical signatures and weathering rates in soils derived from different granites in contrasting climatic locations

Ygor Jacques Agra Bezerra da Silva1  *

Clístenes Williams Araújo do Nascimento1 

Caroline Miranda Biondi1 

Peter van Straaten2 

Valdomiro Severino de Souza Júnior1 

Tiago Osório Ferreira3 

1Departamento de Agronomia, Universidade Federal Rural de Pernambuco, Rua Dom Manuel de Medeiros, s/n, 52171-900, Dois Irmãos, Recife, Pernambuco, Brazil.

2University of Guelph, Guelph, Ontario, Canada.

3Departamento de Ciência do Solo, Escola Superior de Agricultura "Luiz de Queiroz”, Universidade de São Paulo, São Paulo, São Paulo, Brazil.


We studied the mineralogical properties and chemical composition of different granites using energy dispersive X-ray spectroscopy coupled with scanning electron microscopy to understand the relationship between granite signatures and soil characteristics, including weathering patterns and soil fertility status. The discriminant analysis (DA) was based on soil physical and chemical properties and was used to differentiate soils developed from I- and S-type granites across contrasting climatic conditions in northeast Brazil. The DA identified the highest values of organic carbon, clay and plant nutrients as key variables to recognize soil profiles derived from I-type granites. In contrast, the greater sand contents and Al saturation distinguished soils developed from S-type granites. These results were related to the mineralogical characteristics of each granite type, such as a high percentage of silica-bearing minerals in the S-type granites. The highest concentrations of K, Ca, Mg, and P in I-type granites were found in feldspars, amphiboles, and apatite. These elements account for the majority of nutrients derived in their soil profiles. However, it seems that the harsh conditions of the humid tropical environment equalized the effect of the rocks on weathering rates-the difference in chemical index of alteration is more extreme in the dry region.

Keywords: soil science; soil genesis; soil fertility; chemical index of alteration; northeastern Brazil


The mineralogical and chemical composition of granite is controlled by petrogenetic processes (Chappell & White, 2001). The subcategories of I-, S-, and A-type granites have been extensively applied in Earth science studies to geochemically classify granites and granitoids (Guani, Searle, Robb, & Chung, 2013; Guan et al., 2014; Wang et al., 2014; Foden, Sossi, & Wawryk, 2015; Litvinovsky, Jahn, & Eyal, 2015; Wang et al., 2015; Vilalva, Vlach, & Simonetti, 2016). I-type granites are derived from igneous protoliths, whereas S-type granites are mainly formed by a fusion of sedimentary rocks (Chappell & White, 2001). In turn, A-type granites (the term “A” denoting anorogenic and/or anhydrous) occur across rift zones and within stable continental blocks. The identification of A-type granites is based on both tectonic settings and chemical characteristics, while I and S types are strictly based on the difference in the rock sources (Chappell & White, 2001).

Soils developed from granitic rocks are widely distributed worldwide and cover large areas on all continents. Therefore, the knowledge of the properties of granites, which influence soil characteristics, can shed light on weathering patterns and soil properties. Although numerous studies have focused on understanding the mineralogy and chemical composition of granites, only a few have dealt with the effects of the contrasting origins and mineralogy on weathering and soil formation processes (Gontier et al., 2015; Mareschal, Turpault, & Ranger, 2015; Silva et al., 2016).

We studied I- and S-type granites in the Borborema Province in northeast Brazil. This province is in the Western portion of the extensive geologic Brasilian-Pan African orogenic system formed by the collision between the West Africa/São Luis and San Francisco-Congo Cratons (Van Schmus et al., 2008). Borborema Province covers approximately 380,000 km2 and is marked by a mosaic of tectonic blocks: a Paleoproterozoic basement and scattered Archean nuclei, Meso to Neoproterozoic supracrustal rocks, and large intrusions of granites (Van Schmus et al., 2008; Silva, Ferreira, Lima, Sial, & Silva, 2015). Neoproterozoic magmatism in this province produced voluminous S- and I-type granites. This geological setting represents part of the Gondwana continent found in vast tropical areas such as South America, sub-Saharan Africa, India, Asia (Southeast and East) and Australia.

Multivariate statistical techniques have been widely applied to study environmental issues (Matiatos, Alexopoulos, & Ath, 2014; Zhang, Qian, Chen, & Qiao, 2014; Thivya et al., 2015; Matiatos, 2016; Taiti et al., 2016). These techniques provide information that is not available via univariate statistics. Principal component analysis (PCA) (Boteva, Radeva, Traykov, & Kenarova, 2016; Rojas, Prause, Sanzano, Arce, & Sánchez, 2016; Taboada, Rodríguez-Lado, Ferro-Vázquez, Stoops, & Cortizas, 2016), cluster analysis (CA) (Chung et al., 2015; Bitencourt et al., 2016; Nekoeinia, Mohajer, Salehi & Moradlou, 2016), and discriminant analysis (DA) (Fernandez et al., 2016; Haack et al., 2016; Silva et al., 2017) have been successfully used in studies from different fields of soil science. DA is mostly used to predict group discrimination based on observed predictors (Valaee, Ayoubi, Khormali, Lu, & Karimzadeh, 2016); for instance, it may be used for differentiating the weathering of soils developed from different rock types. We hypothesize that discriminant analysis may be a useful tool for revealing the contrasting granite types under diverse tropical climates.

Here, we studied the mineralogical properties and chemical composition of soils on different granite types using energy dispersive X-ray spectroscopy (EDS) coupled with scanning electron microscopy (SEM) and a discriminant analysis approach to understand the relationship between soil geochemical signatures and the underlying granitic parent materials. We hypothesized that different granite types can be indicators of soil fertility from an agrogeological perspective and may also indicate which soil properties can be used as proxies for the presence of granites with contrasting compositions.

Material and methods

Study region

The study was carried out in the Borborema Province, Pernambuco state, northeast Brazil. This area comprises a mosaic of tectonic blocks, including a Paleoproterozoic basement and scattered Archean nuclei as well as Meso to Neoproterozoic supracrustal rocks with large intrusions of granites (Van Schmus et al., 2008). Neoproterozoic magmatism in the Borborema Province has produced voluminous S- and I-type granites. The petrographic and geochemical details of the I- and S-type granites found here have been described previously (Silva et al., 2016; Silva et al., 2017).

The study area covered three climatic settings within the Borborema Province: dry, sub-humid and humid zones (Figure 1). The dry zone has a semiarid climate (Bhs) with an annual precipitation of 500 mm and a mean annual temperature of 28ºC. The sub-humid zone (Aw) has a transitional climate between the humid coastal area and the semiarid zone, presenting a longer dry season and lower precipitation (600-900 mm) compared to the humid zone. Finally, the humid zone has a typical tropical climate (Am) with a mean precipitation of 1,800 mm. In accordance with these contrasting climatic conditions, the vegetation demonstrates a clear zonation. A dry deciduous forest known as Caatinga covers the dry zone; semideciduous and primary evergreen forests (Atlantic rainforest) predominate in the sub-humid and humid zones, respectively (Nascimento, Oliveira, Ribeiro, & Melo, 2006).

Soil and Rock sampling

Samples of six soil profiles and their underlying rocks were taken from the three climatic zones. The sampling sites were chosen based on geological maps and confirmed on site (Figure 1). The sampling was carried out in relatively undisturbed environments to guarantee minimal anthropic influence and similar topographic conditions (gently sloping sites were prioritized). None of the diagnostic criteria for lithic discontinuity were in evidence in the soil profiles studied here (IUSS Working Group WRB, 2014), and hence, the soils developed directly from the underlying rocks.

Soil samples from all horizons were air-dried and sieved (< 2 mm) prior to analysis. Soil profiles derived from I-type granites were classified as eutric Regosols (dry and sub-humid zone) and hypereutric chromic lixisols (humid zone), whereas those developed from S-type granites were classified as eutric regosols (dry zone), dystric regosols (sub-humid zone) and dystric xanthic ferralsols (humid zone) according to the World Reference Base for Soil Resources (IUSS Working Group WRB, 2014). Fresh granite samples were collected from outcrops near the site of soil collection.

Figure 1 Location of the studied soil profiles over I-type and S-type granites in three contrasting climatic zones of Pernambuco State, Borborema Province, Northeast Brazil. Color in maps stands for precipitation rates. 

Granite analyses

The I- and S-type granites and their modal mineralogical compositions were determined in the fresh rock samples taken in situ. A petrographic microscope was used for mineral identification, which was performed in polished thin sections prepared according to Murphy (1986).

After optical microscopy, rock thin sections were coated with a 20-nm gold layer (model Q150R - Quorum Technologies) for mineral identifications by a scanning electron microscope (SEM) (TESCAN, VEGA-3 LMU) at an accelerating voltage of 15 kV. Afterwards, SEM-based energy dispersive X-ray spectroscopy (EDS) (Oxford Instrument, model: 51-AD0007) was used to determine the elemental composition of the mineralogical assembly.

Soil analyses

Particle size distribution of the soil samples previously treated with 30% H2O2 was determined according to Gee and Or (2002) using Calgon for chemical dispersion. Values of pH were obtained in H2O (1:2.5 soil: solution ratio), potential acidity (H+ + Al3+) was determined via the calcium acetate method (0.5 mol L-1, pH 7.0), and total organic carbon (TOC) was measured according to Yeomans and Bremner (1988). To calculate the sum of the bases (SB), cation exchange capacity (CEC) and aluminum saturation, Ca, Mg, K and Na were determined. Potassium and Na+ were extracted with Mehlich-1, while Ca2+, Mg2+, and Al3+ were extracted with 1 mol L-1 KCl. All elements were measured with optical emission spectroscopy (ICP-OES/Optima 7000, Perkin Elmer) using a dual observation mode (axial and radial) and a solid-state detector.

Weathering rate

The chemical index of alteration (CIA) was calculated according to Nesbitt and Young (1982):

CIA = [Al2O3 / (Al2O3 + Na2O+ CaO + k2O)] x 100.

For this calculation, the molecular proportions of the major elements (expressed as oxides) were determined by X-ray fluorescence spectrometry (XRF) (S8 TIGER ECO - WDXRF). Loss on ignition was determined at 1,000ºC. The analysis quality was verified using an international geochemical standard from the National Institute of Standards and Technology (SRM 2709 San Joaquin soil, NIST, 2002). The recovery rates (%) were Al (106), Ca (105), Fe (100), K (98), Mg (96), and Na (72).

Statistical analysis

The data were assessed by discriminant analysis (DA). By simultaneously analyzing several variables, the DA assesses the differences among the groups by defining the independent variables that are most important to distinguish selected data sets. The groups were defined based on parent rocks (I- and S-type granites) and climate conditions (humid, sub-humid and dry zones). Exploratory data treatments based on DA identified the main factors determining the variability among soils with regard to parent material and climatic environment. All statistical analyses were performed with XLSTAT statistical software (version 2014.5.03).

Results and discussion

Granite types vs. soil characteristic

The mineralogical composition of I-type granites is summarized as follows: K-feldspar (60%) > quartz (9%) = plagioclase (9%) > biotite (8%) > amphibole (5%) > opaque minerals (4%) > allanite (2%) = apatite (2%) > titanite (1%). S-type granites, in turn, showed the following composition: K-feldspar (35%) > quartz (28%) > plagioclase (18%) > biotite (11%) > muscovite (5%) > opaque minerals (2%) > allanite (1%). These mineralogical compositions are in accordance with the chemical properties of I- and S-type granites reported by Chappell & White (2001). As a result of these differences, soils developed from I- and S-type granites had sharply contrasting characteristics (Tables 1 and 2).

Table 1 Selected chemical and physical characteristics of soil profiles derived from S-type granites in different climatic zones of Northeast Brazil. 

Horizon/depth (cm) TOCa pH CECb BSc Sat. Al3+d Clay Silt Sand CIAe
(g kg-1) (H2O) (cmolc kg-1) ------- (%) ------- ------- (g kg-1) ------- (%)
Humid zone (348 m) - (Dystric Xanthic Ferralsols)
A (0-9) 39.68 4.6 7.1 39 20.7 200 244 556 91
A (9-20) 14.83 4.3 5.8 28 44.0 200 263 547 94
AB (20-37) 9.01 4.2 4.6 26 56.5 200 361 439 95
BA (37-50) 7.00 4.1 4.3 37 39.8 230 385 385 95
Bw1 (50-69) 4.23 4.2 3.0 38 51.1 230 364 406 96
Bw2 (69-89) 3.87 4.1 2.7 33 55.8 220 350 430 95
Bw3 (89-109) 3.64 4.1 2.5 33 55.5 200 362 438 95
Bw4 (109-147) 5.53 4.2 2.5 38 52.3 230 348 422 96
Bw5 (147-165) 4.05 4.1 2.6 38 51.8 250 365 385 96
Sub-humid zone (738 m) - (Dystric Regosols)
A (0-16) 4.44 4.3 4.1 58 1.4 50 90 860 79
AC (16-34) 2.82 4.1 2.8 28 35.0 30 126 844 83
CA (34-56) 3.31 3.8 2.8 21 62.3 60 139 801 83
C1 (56-93) 3.58 3.7 3.0 25 59.4 70 139 791 85
C2 (93-111) 2.60 3.9 3.2 25 58.4 80 137 783 84
C3 (111-136) 1.29 3.8 2.8 28 59.7 70 166 764 84
C4 (136-152) 1.44 4.0 2.3 25 66.6 60 161 779 82
C5 (152-195) 1.16 4.2 2.3 53 41.4 70 183 747 82
Cr (195-205) - - - - - - - - 72
Dry zone (389 m) - (Eutric Regosols)
Ap (0-5) 4.57 6.0 2.8 88 0.0 40 51 909 58
CA (5-17) 3.18 5.3 2.2 75 8.2 50 80 870 61
C1 (17-26) 1.98 5.2 2.2 70 16.0 50 97 853 62
C2 (26-40) 2.62 4.8 2.4 74 14.6 50 113 837 62
C3 (40-48) 1.77 5.2 2.4 81 7.0 40 120 840 61
Cr (48-59) - - - - - - - - 62

aTotal organic carbon; b Cation exchange capacity; c Base saturation; d Aluminum saturation; e Chemical index of alteration.

Table 2 Selected chemical and physical characteristics of three soil profiles derived from I-type granites in different climatic zones of Northeast Brazil. 

Horizon/depth (cm) TOCa pH CECb BSc Sat. Al3+d Clay Silt Sand CIAe
(g kg-1) (H2O) (cmoc kg-1) --------- (%) --------- ------- (g kg-1) ------- (%)
Humid zone (537 m) - (Hypereutric Chromic Lixisols)
Ap (0-8) 59.58 5.5 8.5 63 0.5 150 379 471 90
AB (8-18) 58.43 5.0 7.2 56 1.4 170 383 447 91
BA (18-30) 11.97 4.7 5.5 56 4.7 180 414 406 93
Bt1 (30-46) 6.37 4.8 4.6 59 3.5 250 440 310 94
Bt2 (46-64) 5.72 5.2 4.2 64 0.0 300 507 193 97
Bt3 (64-84) 4.19 5.0 4.2 62 1.9 310 506 184 98
Bt4 (84-135) 1.50 5.0 4.0 65 1.9 300 522 178 98
BC (135-175) 3.66 5.0 3.8 65 0.0 260 569 171 98
C (175-195+) 3.07 4.8 3.6 64 10.6 270 558 172 98
Sub-humid zone (695 m) - (Eutric Regosols)
A (0-11) 45.27 5.2 9.1 68 1.6 50 290 660 70
BA (11-17) 6.99 5.2 5.8 70 1.2 60 282 658 71
C1 (17-46) 3.95 5.1 4.5 67 3.2 50 280 670 70
C2 (46-70) 2.06 5.5 3.4 73 3.9 50 300 650 68
C3 (70-78) 1.65 5.7 2.5 70 5.5 50 240 710 64
Cr1 (78-148) - - - - - - - - 93
Cr2 (148-185) - - - - - - - - 87
Cr3 (185-200) - - - - - - - - 79
Dry zone (473 m) - (Eutric Regosols)
A (0-3) 39.64 7.1 10.6 100 0.0 50 195 755 56
CA (3-9) 11.29 6.9 10.8 100 0.0 80 304 616 70
C1 (9-17) 7.09 6.0 7.5 100 0.7 100 321 579 74
C2 (17-27) 4.97 5.5 8.2 100 0.9 110 308 582 76
C3 (27-39) 4.08 5.1 8.0 100 1.8 120 326 554 78
Cr1 (39-53) - - - - - - - - 83
Cr2 (53-63+) - - - - - - - - 75

aTotal organic carbon; b Cation exchange capacity; c Base saturation; d Aluminum saturation; e Chemical index of alteration.

The higher proportion of weathering resistant minerals in S-type granites (i.e., quartz and muscovite) explains the higher sand contents in soils derived from S-type granites (Table 1) compared with the soils from I-type granite (Table 2) regardless of the climatic zones. TOC concentrations in soils may be related to clay contents (Table 2) - probably in response to the ability of clay minerals to stabilize and protect organic matter against mineralization (Schmidt et al., 2011; Lehmann & Kleber, 2015). This finding likely explains the accumulation of OC being higher in soils originating from I-type granites.

The granite types also markedly influenced the CEC and base saturation - characteristics that are linked to soil fertility. Overall, we found that I-type granites were associated with more fertile soils. Therefore, the rock composition might be used to define soil zones according to their cropping potential in an agrogeological perspective.

Corn and common beans are the main crops grown in the region, and their lime and fertilizer requirements are lower in soils developed from I-type than from S-type granites. Therefore, granite types along with data such as soil testing and mean annual rainfall can identify land areas homogeneous enough to be served by the same fertilizer recommendation. Such an approach can be used in soils that have developed under similar granite types worldwide (Zhao, Zhou, Li, & Wu, 2008; Canosa, Izard, & Fuente, 2012; Chappell, Bryant, & Wyborn, 2012; Guan et al., 2014; Foden, Sossi, & Wawryk, 2015; Robinson, Foden, & Collins, 2015).

I-type granites had mean CIA values that were higher than S-type granites (Tables 1 and 2). This finding is probably due to the higher concentration of more easily weathered minerals, such as apatite and amphibole, in the I-type granites. The higher proportion of accessory minerals in the soils that developed from I-type granites also explains their higher natural soil fertility (Table 2). Microscopic images of apatite, magnetite, zircon, and biotite as well as their chemical compositions by SEM/EDS (Figure 2) demonstrated that these minerals are among the main sources of plant nutrients along with amphibole (a mineral found only in I-type granites).

Discriminant analysis

The DA used chemical and physical data from soils (TOC, clay, silt, sand, CEC, BS, Al saturation, pHH2O and CIA) as grouping variables. Soil samples derived from I-type granite - although well dispersed along the “y” axis (factor 2) - are mostly concentrated in the negative end of factor 1 compared to the soil samples from the S-type granite (Figure 3a). This pattern of data distribution is related to the higher values of TOC, clay, and an overall better fertility (higher BS, CEC, pH and lower Al saturation), which are also concentrated negatively along the “x” axis (factor 1) (Figure 3b).

Figure 2 Scanning electron microscope (SEM) image captured from I-type granites and their respective elemental composition by energy dispersive X-ray spectrum (EDS). (a) Chemical composition of apatite (Spectrum 20: Ca - 67%, P - 29%, Fe - 1%, Si - 1%, Al - 1% K - 1%), magnetite (Spectrum 21: Fe - 98%, Si, Al, Ca - 1%), and zircon (Spectrum 22: Zr - 78%, Si - 20%, Fe - 2%). (b) Chemical composition of magnetite: spectrum 28 (Fe - 98%, Si, Al - 1%) and spectrum 29 (Fe - 98%, Si, Al - 1%); and biotite (Spectrum 30 Si - 33%, Fe - 25%, Al - 16%, K - 13%, Mg 11%, Ti - 2%). 

Figure 3 Discriminant analysis based on the chemical and physical characterization and weathering index (CIA) in (a), soils that developed from I- and S-type granites in Pernambuco State and (b), Northeast Brazil. I - I-type granite; S - S-type granite; d - dry zone; h - humid zone; sh - sub-humid zone. 

The samples from soils that developed over S-type granites are mostly concentrated on the positive “x” axis (Figure 3a) in contrast to TOC and clay contents - a distribution pattern reflected by Al saturation and sand contents (Figure 3b). The grouping pattern indicates a contrast in weathering rates between soils developed from I- and S-types granites. These results can be mostly explained by the contrasting mineral composition of the parent rocks (Silva et al., 2017).

Soils formed from I-type granites showed a clear weathering gradient among the different climatic zones as evidenced by DA (Figure 3a). Data grouping showed the following increasing weathering degree: humid zone > sub-humid zone > dry zone. As indicated by factor 1 (Figure 3a), soil samples from humid zones were distributed positively along the “y” axis, whereas soil samples from sub-humid and dry zones (both granite types) were positioned negatively.

The distribution of the soil samples from the humid zone (Figure 3a) were clearly associated with the highest CIA values and the highest clay contents (Figure 3b). In contrast, soils from the sub-humid zone, and especially those from the dry zone, showed an opposite trend and remained distributed in the negative parts of both the “x” and “y” axes (factors 1 and 2, respectively) (Figure 3a). These samples were associated with higher CEC and BS values (Figure 3b), which indicates a more conservative environment.

The climate effects on weathering were less evident for soils that developed over S-type granites - especially for samples from the sub-humid and dry zones (Figure 3a). This inability to separate these two climatic zones by DA is a reflection of the higher amounts of highly resistant minerals in the S-type granites. This relationship governs the intensity of weathering more than the climate condition.


Soils originating from I-type granites presented higher chemical alteration than S-type derived soils. The mineralogical composition of the rocks likely explains why S-type granites carry a higher concentration of more stable minerals such as quartz and muscovite. The chemical composition of granites also influences soil fertility. Soils that developed from I-type granites showed a higher concentration of mineral nutrients than S-type-derived soils due to their overall lower concentrations of P, K, Ca, and Mg (feldspars, amphibole and apatite). I-type granites formed soils with higher clay contents and organic matter than soils originating from S-type granites. The integration of detailed mineralogical characterization of the granite types along with their chemical and physical analyses, using multivariate analysis can be an important approach in the understanding of the weathering process of granites across a climatic gradient.


We express gratitude to Dr. Carlos Alberto dos Santos, Dra. Ana Cláudia Aguiar Accioly, Dra. Vanja Coelho Alcantara from Resources Research Company (CPRM/Brazil), Geological Survey of Brazil, in Recife, Pernambuco State, Brazil, for supporting field works and petrographic analysis. Authors are also grateful to Coordination for the Improvement of Higher Education Personnel (CAPES) for funding through project PVE 104/2012.


Bitencourt, D. G. B., Barros, W. S., Timm, L. C., She, D., Penning, L. H., Parfitt, J. M. B., & Reichardt, K. (2016). Multivariate and geostatistical analyses to evaluate lowland soil levelling effects on physico-chemical properties. Soil & Tillage Research, 156, 63-73. DOI: 10.1016/j.still.2015.10.004 [ Links ]

Boteva, S., Radeva, G., Traykov, I., & Kenarova, A. (2016). Effects of long-term radionuclide and heavy metal contamination on the activity of microbial communities, inhabiting uranium mining impacted soils. Environmental Science and Pollution Research, 23(6), 5644-5653. DOI: 10.1007/s11356-015-5788-5 [ Links ]

Canosa, F., Izard, A. M., & Fuente, M. F. (2012). Evolved granitic systems as a source of rare-element deposits: The Ponte Segade case (Galicia, NW Spain). Lithos, 153, 165-176. DOI: 10.1016/j.lithos.2012.06.029 [ Links ]

Chappell, B. W., & White, A. J. R. (2001). Two contrasting granite types: 25 years later. Australian Journal of Earth Sciences, 48, 489-499. DOI: 10.1016/j.lithos.2012.06.029 [ Links ]

Chappell, B. W., Bryant, C. J., & Wyborn, D. (2012). Peraluminous I-type granites. Lithos , 153, 142-153. DOI: 10.1016/j.lithos.2012.07.008 [ Links ]

Chung, S. Y., Venkatramanan, S., Park, N., Rajesh, R., Ramkumar, T., & Kim, B. W. (2015). An Assessment of selected hydrochemical parameter trend of the Nakdong River water in South Korea, using time series analyses and PCA. Environmental Monitoring and Assessment, 187(4192), 1-13. DOI: 10.1007/s10661-014-4192-9 [ Links ]

Fernandez, A. L., Sheaffer, C. C., Wyse, D. L., Staley, C., Gould, T. J., & Sadowsky, M. J. (2016). Associations between soil bacterial community structure and nutrient cycling functions in long-term organic farm soils following cover crop and organic fertilizer amendment. Science of the Total Environment, 566-567, 949-959. DOI: 10.1016/j.scitotenv.2016.05.073 [ Links ]

Foden, J., Sossi, P. A., & Wawryk, C. M. (2015). Fe isotopes and the contransting petrogenesis of A-, I- and S-type granite. Lithos , 32(44), 212-215. DOI: 10.1016/j.lithos.2014.10.015 [ Links ]

Gontier, A., Rihs, S., Chabaux, F., Lemarchand, D., Pelt, E., & Turpault, M. P. (2015). Lack of bedrock grain size influence on the soil production rate. Geochimica et Cosmochimica Acta, 166, 146-164. DOI: 10.1016/j.gca.2015.06.010 [ Links ]

Guan, Y., Yuan, C., Sun, M., Wilde, S., Long, X., Huang, X., & Wang, Q. (2014). I-type granitoids in the eastern Yangtze Block: implications for the Early Paleozoic intracontinental orogeny in South China. Lithos , 206(207), 34-51. DOI: 10.1016/j.lithos.2014.07.016 [ Links ]

Guani, A. A., Searle, M., Robb, L., & Chung, S. L. (2013). Transitional I S type characteristic in the Main Range Granite. Peninsular Malaysia. Journal of Asian Earth Sciences, 76, 225-240. DOI: 10.1016/j.jseaes.2013.05.013 [ Links ]

Gee, G. W., & Or, D. (2002). Particle size analysis. In J. H. Dane, & C. T. Topp (Ed.), Methods of soil analysis: physical methods (p. 255-289). Madison, WI: SSSA. [ Links ]

Haack, S. K., Duris, J. W., Kolpin, D. W., Focazio, M. J., Meyer, M. T., Johnson, H. E., … Foreman, W. T. (2016). Contamination with bacterial zoonotic pathogen genes in U.S. streams influenced by varying types of animal agriculture. Science of the Total Environment, 563-564, 340-350. DOI: 10.1016/j.scitotenv.2016.04.087 [ Links ]

IUSS Working Group WRB. (2014). World Reference Base for Soil Resources (World Soil Resources Report No. 106). Rome, IT: FAO. [ Links ]

Lehmann, J., & Kleber, M. (2015). The contentious nature of soil organic matter. Nature, 528(7580), 60-68. DOI: 10.1038/nature16069 [ Links ]

Litvinovsky, B. A., Jahn, B. M., & Eyal, M. (2015). Mantle-derived sources of syenites from the A-type igneous suites - New approach to the provenance of alkaline silicic magmas. Lithos, 232, 242-265. DOI: org/10.1016/j.lithos.2015.06.008 [ Links ]

Mareschal, L., Turpault, M. P., & Ranger, J. (2015). Effect of granite crystal grain size on soil properties and pedogenic processes along a lithosequence. Geoderma, 249(250), 12-20. DOI: 10.1016/j.geoderma.2015.02.009 [ Links ]

Matiatos, I., Alexopoulos, A., & Ath, G. (2014). Multivariate statistical analysis of the hydrogeochemical and isotopic composition of the groundwater resources in northeastern Peloponnesus (Greece). Science of the Total Environment, 476-477(C), 577-590. DOI: 10.1016/j.scitotenv.2014.01.042 [ Links ]

Matiatos, I. (2016). Nitrate source identification in groundwater of multiple land-use areas by combining isotopes and multivariate statistical analysis: A case study of Asopos basin (Central Greece). Science of the Total Environment, 541, 802-814. DOI: 10.1016/j.scitotenv.2015.09.134 [ Links ]

Murphy, C. P. (1986). Thin section preparation of soils and sediments. Berkhanmsterd: Academic Publis. [ Links ]

Nascimento, C. W. A., Oliveira, A. B., Ribeiro, M. R., & Melo, É. E. C. (2006). Distribution and availability of zinc and copper in benchmark soils of Brazil. Communications in Soil Science and Plant Analysis, 37(1-2), 109-125. DOI: 10.1080/00103620500403895 [ Links ]

National Institute of Standards and Technology [NIST]. (2002). Standard Reference Materials -SRM 2709, 2710 and 2711. Addendum Issue Date: 18 January, 2002. [ Links ]

Nekoeinia, M., Mohajer, R., Salehi, M. H., & Moradlou, O. (2016). Multivariate statistical approach to identify metal contamination sources in agricultural soils around Pb-Zn mining area, Isfahan province, Iran. Environmental Earth Sciences, 75, 760-770. DOI: 10.1007/s12665-016-5597-2 [ Links ]

Nesbitt, H. W., & Young, G. M. (1982). Early Proterozoic climates and plate motions inferred from major element chemistry of lutites. Nature, 299(5885), 715-717. DOI: 10.1038/299715a0 [ Links ]

Robinson, F. A., Foden, J. D., & Collins, A. S. (2015). Geochemical and isotopic constraints on island arc, synorogenic, post-orogenic and anorogenicgranitoids in the Arabian Shield, Saudi Arabia. Lithos, 220(223), 97-115. DOI: 10.1016/j.lithos.2015.01.021 [ Links ]

Rojas, J. M., Prause, J., Sanzano, G. A., Arce, O. E. A., & Sánchez, M. C. (2016). Soil quality indicators selection by mixed models and multivariate techniques in deforested areas for agricultural use in NW of Chaco, Argentina. Soil & Tillage Research, 155, 250-262. DOI: 10.1016/j.still.2015.08.010 [ Links ]

Schmidt, M. W., Torn, M. S., Abiven, S., Dittmar, T., Guggenberger, G., Janssens, I. A., … Trumbore, S. E. (2011). Persistence of soil organic matter as an ecosystem property. Nature, 478(7367), 49-56. DOI: 10.1038/nature10386 [ Links ]

Silva, T. R., Ferreira, V. P., Lima, M. M. C., Sial, A. N., & Silva, J. M. R. (2015). Synkinematic emplacement of the magmatic epidote bearing Major Isidoro tonalite-granite batholith: Relicts of an Ediacaran continental arc in the Pernambuco-Alagoas domain, Borborema Province, NE Brazil. Journal of South American Earth Sciences, 64, 1-13. DOI: 10.1016/j.jsames.2015.09.002 [ Links ]

Silva, Y. J. A. B., Nascimento, C. W. A., Biondi, C. M., Van Straaten, P., Souza Júnior, V. S., & Ferreira, T. O. (2016). Weathering rates and carbon storage along a climosequence of soils developed from contrasting granites in northeast Brazil. Geoderma, 284, 1-12. DOI: 10.1016/j.geoderma.2016.08.009 [ Links ]

Silva, Y. J. A. B., Nascimento, C. W. A., Van Straaten, P., Biondi, C. M., Souza Júnior, V. S., & Silva, Y. J. A. B. (2017). Effect of I and S type granite parent material mineralogy and geochemistry on soil fertility: a multivariate statistical and gis-based approach. Catena, 149, 64-72. DOI: 10.1016/j.catena.2016.09.001 [ Links ]

Taboada, T., Rodríguez-Lado, L., Ferro-Vázquez, C., Stoops, G., & Cortizas, A. M. (2016). Chemical weathering in the volcanic soils of Isla Santa Cruz (Galápagos Islands, Ecuador). Geoderma, 261, 160-168. DOI: 10.1016/j.geoderma.2015.07.019 [ Links ]

Taiti, C., Giorni, E., Colzi, I., Pignattelli, S., Bazihizina, N., Buccianti, A., … Gonnelli, C. (2016). Under fungal attack on a metalliferous soil: ROS or not ROS? Insights from Silene paradoxa L. growing under copper stress. Environmental Pollution, 210, 282-292. DOI: 10.1016/j.envpol.2015.12.020 [ Links ]

Thivya, C., Chidambaram, R., Thilagavathi, R., Prasanna, M. V., Singaraja, C., Adithya, V. S., & Nepolian, M. (2015). A multivariate statistical approach to identify the spatio-temporal variation of geochemical process in a hard rock aquifer. Environmental Monitoring and Assessment, 187(9), 552-571. DOI: 10.1007/s10661-015-4738-5 [ Links ]

Valaee, M., Ayoubi, S., Khormali, F., Lu, S. G., & Karimzadeh, H. R. (2016). Using magnetic susceptibility to discriminate between soil moisture regimes in selected loess and loess-like soils in northern Iran. Journal of Applied Geophysics, 127, 23-30. DOI: 10.1016/j.jappgeo.2016.02.006 [ Links ]

Van Schmus, W. R., Oliveira, E. P., Silva, A. F. F., Toteu, S. F., Penaye, J., & Guimarães, I. P. (2008). Proterozoic links between the Borborema Province, NE Brazil, and the Central African Fold Belt. Geological Society of London, 294, 69-99. DOI: 10.1144/SP294.5 [ Links ]

Vilalva, F. C. J., Vlach, S. R. F., & Simonetti, A. (2016). Chemical and O-isotope compositions of amphiboles and clinopyroxenes from A-type granites of the Papanduva Pluton, South Brazil: Insights into late- to post-magmatic evolution of peralkaline systems. Chemical Geology, 420, 186-199. DOI: 10.1016/j.chemgeo.2015.11.019 [ Links ]

Wang, X. S., Hu, R. Z., Bi, X. W., Leng, C. B., Panl, C., Zhu, J. J., & Chen, Y. W. (2014). Petrogenesis of Late Cretaceous I-type granites in the southern YidunTerrane: New constraints on the Late Mesozoic tectonic evolution of the eastern Tibetan Plateau. Lithos, 208-209, 202-219. DOI: 10.1016/j.lithos.2014.08.016 [ Links ]

Wang, Z., Wang, J., Deng, Q., Du, Q., Zhou, X., Yang, F., & Liu, H. (2015). Paleoproterozoic I-type granites and their implications for the Yangtze block position in the Columbia supercontinent: Evidence from the Lengshui Complex. South China. Precambrian Research, 263(C), 157-173. DOI: 10.1016/j.precamres.2015.03.014 [ Links ]

Yeomans, J. C., & Bremner, J. M. (1988). A rapid and prec 9,ise method for routine determination of organic carbon in soil. Communications in Soil Science and Plant Analysis, 19(13), 1467-1476. DOI: 10.1080/00103628809368027 [ Links ]

Zhang, X., Qian, H., Chen, J., & Qiao, L. (2014). Assessment of groundwater chemistry and status in a heavily used semi-arid region with multivariate statistical analysis. Water, 6, 2212-2232. DOI: 10.3390/w6082212 [ Links ]

Zhao, X. F., Zhou, M. F., Li, J. W., & Wu, F. Y. (2008). Association of Neoproterozoic A- and I-type granites in South China: Implications for generation of A-type granites in asubduction-related environment. Chemical Geology, 257, 1-15. DOI: 10.1016/j.chemgeo.2008.07.018 [ Links ]

Received: September 27, 2017; Accepted: November 12, 2017

*Author for correspondence. E-mail:

Creative Commons License This is an open-access article distributed under the terms of the Creative Commons Attribution License