Different Quartz Varieties Characterized by Proximal Sensing and Their Relation to Soil Attributes

Abstract

Quartz is one of the most common minerals in soils, mostly present in sand and silt fractions. Although quartz is basically formed of SiO₂, other elements can be easily detected and assessed nowadays using a portable X-ray fluorescence (pXRF) spectrometer. Our study aims to evaluate the chemical composition of different quartz varieties, identifying their main elements, and relating them to soil attributes. Six quartz varieties (hyaline, amethyst, milky, rose, smoky, and ferriferous) were analyzed via pXRF and 13 oxides/trace elements were identified and used for quartz discrimination (Al₂O₃, CaO, P₂O₅, SiO₂, Cl, Cr, Fe, K₂O, Mn, Rb, S, Ti, and V). Hyaline quartz was characterized by the highest SiO₂ and the lowest contents of other elements. Al₂O₃ was the second-highest compound present in all varieties of quartz, reaching 21,547 mg kg⁻¹ in the smoky variety. S, P₂O₅, Cl, SiO₂, and K₂O were the main components determined by Random Forest algorithm for discriminating quartz varieties. Some elements detected may serve as a reserve of nutrients to plants to be released in soils along weathering, depending on quartz particle size, soil texture, leaching, and associated attributes. pXRF enhanced the information on chemical characterization of quartz varieties, without the generation of chemical pollutants.

1. Introduction

The planet Earth is made up of three major layers: crust, mantle, and core. The crust and some portions of the mantle are composed of rocks formed by various minerals, which have in their constitution various chemical elements resulting from the physical–chemical conditions during their formation [1]. While minerals are natural, solid, and inorganic materials, with a crystalline structure and defined chemical composition, rocks are consolidated bodies of different minerals and/or organic, vitreous, or amorphous compounds. In this aspect, soils are formed through the weathering of rocks or accumulation of sediments on the surface of the planet, being mostly composed of minerals and a small portion of organic matter. Both minerals and organic matter may provide nutrients for the various forms of life on the planet after their release to soils [2,3].

Among the minerals composing soil and great portions of the Earth’s crust, quartz stands out as a mineral widely found and greatly resistant to weathering when its particle size is coarse. This mineral is considered the second most abundant in the Earth’s crust, occupying about 12% of its volume, behind feldspars, which are responsible for approximately 60% of the crust’s volume [2,3]. From the crystallization of magma/lava, quartz is the last mineral to form according to the Bowen series—a sequence of formation of minerals from cooling of magma [3,4]. For this reason, quartz has less variability of chemical elements in its constitution and a higher relative amount of SiO₂ compared to minerals formed at the beginning of the Bowen series, such as olivines, pyroxenes, and amphiboles [3,5]. Within this formation process, its resistance to weathering is due to the higher number of covalent bonds and lower degree of isomorphic substitution of interstitial elements compared to feldspars, which helps to explain its abundance on the Earth’s surface [5,6].

Quartz has a three-dimensional network of bonded tetrahedra rather than a linear or planar structure like other silicates. As consequence, it has no planes of weakness and is very resistant to both physical and chemical weathering [5,7]. In soils, quartz tends to concentrate in the sand and silt fractions, being one of the few minerals present in these fractions in highly weathered and leached soils, such as most Brazilian soils [8]. Due to its high resistance to weathering–leaching conditions and generalized occurrence in igneous, metamorphic, and sedimentary rocks, quartz is the most frequent mineral in the majority of soils of tropical regions [8,9].

In soils, it is concentrated in the sand and silt particle size fractions (even in Oxisols), and in lower contents in the coarse clay fraction (2–0.2 µm) [10]. The absence of quartz in the fine clay fraction (<0.2 µm) is attributed to its smaller resistance to dissolution when occurring in very fine particle sizes. Quartz tends to concentrate in the superficial (eluvial) horizons of some soils, due to its high resistance to greater weathering–leaching conditions in this part of these soil profiles [10].

Quartz has a vitreous luster and is one of the purest minerals, being basically composed of SiO₂. However, it may contain various other elements/compounds (Al, Ti, Fe, Na, K, Mg, Ca, OH) as interstitials or isomorphous substituents [11], besides coatings (in the forms of Fe and Mn oxide minerals, for example) on quartz grains. Such elements along with other factors, such as environmental conditions at the time of quartz formation, can cause variations in its characteristics, such as its color [1,12]. Quartz can be found in several colors, ranging from transparent (hyaline quartz) to darker colors such as purple (amethyst quartz), translucent gray, or brown (smoky quartz), as an easy indication of the presence of other elements than Si and O. These factors contribute to quartz use for various purposes: raw material for the manufacture of glass, piezo raw material for growing artificial quartz crystals, material for civil construction, and adornments, the latter mainly due to its color variability.

Despite the wide presence of quartz in soils and rocks, the identification and quantification of its elements besides Si and O are traditionally done through laborious and time-consuming laboratory analysis, using destructive methods of the samples, which generate large amounts of chemical residues. Recently, portable X-ray fluorescence (pXRF) spectrometry has been increasingly adopted around the world to quantify the content of chemical elements in various matrices, such as rocks, minerals, soils, plants, among others, in a non-destructive and fast (~60 s) procedure, requiring minimal sample preparation [13]. This equipment has been used both for in situ and field analyses. Conversely to the growing number of works in the last five years using pXRF, there are very few studies focusing on the chemical composition of minerals [14,15,16]. In this sense, elements other than Si and O present in quartz can be rapidly identified, and consequences of their presence, such as long-term release of nutrients in soils, can be inferred.

Our study aims to (i) characterize the elemental composition of six different quartz varieties (hyaline, milky, smoky, amethyst, rose, and ferriferous) through pXRF; (ii) evaluate the influence of chemical elements on their colors; and (iii) identify quartz varieties and their elements with implications to soils of tropical regions.

2. Materials and Methods

2.1. Sampling and Laboratory Analyses

A total of 16 quartz samples belonging to the Minerals and Rocks collection of the Department of Soil Science at the Federal University of Lavras (UFLA) were studied. The samples corresponded to different quartz varieties—hyaline (HQ), milky (MQ), smoky or brown (SQ), purple (amethyst) (PQ), rose (RQ) and ferriferous or turbid milky quartz (FQ)—(Figure 1), being three samples each, except for the ferriferous quartz which had only one sample.

The 16 quartz samples were subjected to analysis by a portable X-ay fluorescence (pXRF) spectrometer, model S1 Titan LE (Bruker Analytical Instrumentation, Billerica, MA, USA), which features 4 W, 50 keV, and 5–100 μA X-ray tubes and a silicon detector (SSD) with a resolution of <145 eV. For a better evaluation of the chemical composition, each sample was analyzed in triplicate at three different faces of the mineral, during 60 s in General mode. The average of results of the three repetitions was used as the final result of each evaluated chemical element.

To verify the quality of the pXRF results, before scanning the quartz samples, the reference samples 2710a and 2711a certified by the National Institute of Standards and Technology (NIST) were analyzed, along with a sample certified by the pXRF manufacturer (check sample). The recovery values of the equipment for each studied element and oxide were determined, where the recovery value = content detected by pXRF/certified content in the sample. Recovery values (NIST 2710a/2711a/check sample) were as follows: Al₂O₃ 0.85/0.76/0.97; CaO 0.47/0.49/nd; Cl nd/nd/nd; Cr nd/1.15/nd; Fe 0.79/0.69/0.92; K₂O 0.66/0.52/0.88; Mn 0.75/0.65/0.87; P₂O₅ 2.5/3.1/nd; Rb 1.05/1.08/nd; S nd/nd/nd; SiO₂ 0.67/0.60/0.96; Ti 0.82/0.73/nd; and V 0.51/0.39/nd. Values referred to as “nd” indicate no detection by pXRF or no certified content. The closer the recovery value to 1, the higher the quality of the pXRF data for that element. The elements that were present in most of the quartz varieties were used in this study, since their presence or absence can help in the discrimination of these minerals. It was not possible to evaluate the interference of Li, Na, and H in the varieties of quartz, since elements with an atomic number lower than that of Mg are not detected by pXRF spectrometry [13,16].

2.2. Statistical Analysis

Descriptive statistical analyses of elements and oxides (Al₂O₃, CaO, Cl, Cr, Fe, K₂O, Mn, P₂O₅, Rb, Sr, SiO₂, Ti, and V) were performed by calculating minimum and maximum values, mean, standard deviation, and coefficient of variation for each element. The results of elemental contents in each quartz sample obtained by pXRF were subjected to analysis of variance and the Scott–Knott mean test at 5% significance using the SISVAR software (Department of Statistics, Federal University of Lavras, Lavras, Brazil) [17]. Pearson correlation was performed between the elemental contents using the corrplot package in R software (version 4.2.1, R Foundation for Statistical Computing, Vienna, Austria) [18]. Correlation values vary from −1 to +1, and the closer to the absolute value 1, the greater the correlation (direct or inverse) between the elemental contents.

In order to identify the elements that are more relevant in distinguishing the varieties of quartz in terms of their chemical composition, the importance of each element for their characterization was calculated by the Random Forest (RF) algorithm (where number of trees of the model (ntree) = 500, and nodesize and mtry where set to default), through caret package [19], using R software (version 4.2.1) (R Core Team, 2009). For that, all data obtained by pXRF spectrometry and the corresponding variety of quartz were modeled and validation was performed via leave-one-out cross validation. After the RF model was created, the identification of the most important elements and oxides for quartz discrimination was determined through the Mean Decrease Gini index. Gini is a measurement of the purity of nodes (points in the RF where samples are split into more similar groups). If a variable is important, it will help to split samples into purer (more similar) groups. If such a variable is permuted by a less important one, the purity of the split should decrease (more heterogeneous samples in the split). Hence, the more a variable decreases the purity of a node when removed, the more important it is, i.e., the higher the value of this index (a higher decrease in purity), the greater the importance of that element for the model.

Finally, the calculation of overall accuracy (number of corrected samples of predicted quartz variety/total number of samples) (Equation (1)) and Cohen’s Kappa coefficient (Equation (2)) was performed to evaluate the reliability and accuracy of the RF model:

$$\mathrm{O}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{a}\mathrm{l}\mathrm{l} \mathrm{A}\mathrm{c}\mathrm{c}\mathrm{u}\mathrm{r}\mathrm{a}\mathrm{c}\mathrm{y}=\frac{Pc}{N}$$

(1)

$$Cohe{n}^{\prime }s Kappa=\frac{Po-Pe}{1-Pe}$$

(2)

where, Pc is the sum of the confusion matrix’s main diagonal (predicted quartz variety), N is the total number of samples, Po is the observed agreement, and Pe is the probability of random agreement [20].

The overall accuracy, ranging from 0 to 1, was calculated by the sum of the correctly classified samples (the main diagonal) divided by the total number of samples in the entire confusion matrix (the closer to 1, the greater the accuracy) [21]. The Kappa coefficient, ranging from −1 to 1, considers the number of correctly classified samples, the total number of samples, and the misclassifications to deliver the results of the predictions (the closer to 1, the greater the prediction reliability) [20].

3. Results and Discussion

3.1. General Characterization of Varieties of Quartz via pXRF

Quartz is basically composed of SiO₂, which was consistently detected by pXRF in all the samples, although some noticeable irregularities were found. The descriptive statistics calculated for all the varieties of quartz are shown in

Table 1. Descriptive statistics for the 16 samples of 6 different varieties of quartz obtained with portable X-ray fluorescence (pXRF) spectrometry data.

Element/Oxide	Min	Max	Mean	SD 1	CV 2
Al2O3 (mg kg−1)	6887	46,679	12,468	9544	77
CaO (mg kg−1)	140	7830	1815	1982	109
Cl (mg kg−1)	573	3368	1408	788	56
Cr (mg kg−1)	<LOD *	448	160	152	95
Fe (mg kg−1)	124	1908	388	469	121
K2O (mg kg−1)	493	4581	1493	1053	70
Mn (mg kg−1)	<LOD *	50	3	12	400
P2O5 (mg kg−1)	1029	1883	1332	216	16
Rb (mg kg−1)	<LOD *	3	0.31	1	279
S (mg kg−1)	<LOD *	9139	1939	2561	132
SiO2 (mg kg−1)	692,237	1000,000	885,444	110,886	13
Ti (mg kg−1)	73	547	219	112	51
V (mg kg−1)	<LOD *	366	35	93	264

* Limits of detection of pXRF: Al—960 mg kg⁻¹; Ca—37 mg kg⁻¹; Cl—135 mg kg⁻¹; Cr—19 mg kg⁻¹; Fe—13 mg kg⁻¹; K—41 mg kg⁻¹; Mn—18 mg kg⁻¹; P—90 mg kg⁻¹; Rb—3 mg kg⁻¹; S—80 mg kg⁻¹; Si—500 mg kg⁻¹; Ti—20 mg kg⁻¹; V—8 mg kg⁻¹. ¹ standard deviation. ² coefficient of variation.

. As expected, SiO₂ presented the highest average amount considering all varieties of quartz (885,444 mg kg⁻¹), with a coefficient of variation (CV) of 13%. In addition, SiO₂ varied from 692,237 to 1000,000 mg kg⁻¹. Following SiO₂, Al₂O₃ had the second-highest average content, with only 12,468 mg kg⁻¹. This large discrepancy between the major and the second-highest-content element demonstrates the dominance of SiO₂ as the major compound of quartz. Also, Table 1 shows the other elements present in the crystalline structure of quartz varieties, in very small amounts.

Elements that showed the highest coefficient of variation among all varieties of quartz were Mn (400%), Rb (279%), and V (264%), respectively. Other elements that are potential nutrients to plants presented small amounts, on average, such as S (1939 mg kg⁻¹), CaO (1815 mg kg⁻¹), K₂O (1493 mg kg⁻¹), Cl (1408 mg kg⁻¹), P₂O₅ (1332 mg kg⁻¹), Fe (388 mg kg⁻¹), and Mn (3 mg kg⁻¹). Other elements presented variable average contents.

3.2. Elemental Characterization Per Varietiy of Quartz through pXRF Spectrometry

For a more detailed evaluation of the variability of elements and oxides,

Table 2. Mean values of elements and oxides of the different varieties of quartz, where the same letters in the same line express statistically equal values according to the Scott–Knott test at a 5% significance level.

Quartz Variety	Hyaline	Amethyst	Rose	Milky	Smoky	Ferriferous
Al2O3 (mg kg−1)	10,162 b	8127 b	10,624 b	10,758 b	21,547 a	17,474 a
CaO (mg kg−1)	1127 c	730 c	3043 b	1680 c	1027 c	7830 a
K2O (mg kg−1)	662 b	1051 b	1992 b	1664 b	1293 b	4581 a
P2O5 (mg kg−1)	1469 a	1209 b	1400 a	1096 b	1532 a	1320 a
SiO2 (mg kg−1)	995,382 a	876,832 b	823,506 b	835,828 b	890,423 b	960,181 a
Cl (mg kg−1)	891 c	881 c	1671 b	1879 b	1228 c	3368 a
Cr (mg kg−1)	250 a	152 a	51 a	109 a	172 a	356 a
Fe (mg kg−1)	148 c	222 c	286 c	272 c	522 b	1908 a
Mn (mg kg−1)	0 b	0 b	22 a	0 b	0 b	0 b
Rb (mg kg−1)	0 a	1 a	0 a	0 a	0 a	0 a
S (mg kg−1)	46 b	650 b	4978 a	3041 a	551 b	6032 a
Ti (mg kg−1)	158 a	192 a	239 a	349 a	179 a	226 a
V (mg kg−1)	0 a	13 a	12 a	124 a	39 a	0 a

shows the results of the Scott–Knott mean test at 5% probability between the contents of elements in different varieties of quartz. Moreover, and contrary to Table 1, it is possible here to notice the mean contents per variety of quartz. Except for Rb, Ti, V, and Cr, all elements presented some significant difference. Analyzing the contents of elements or oxides per quartz variety, it was possible to verify the variation of elemental contents. SiO₂ content ranged from 823,506 to 995,382 mg kg⁻¹, observed in RQ and HQ, respectively, with HQ being considered the purest quartz variety. The second variety of quartz richest in SiO₂ was FQ (960,181 mg kg⁻¹). The other varieties of quartz presented a lower content of SiO₂ and higher contents of other elements.

As expected, FQ presented the highest content of Fe, besides the highest contents of K₂O, CaO, Cl, Cr, and S, most of these latter ones being significantly higher than those of the other varieties of quartz. Although FQ had the highest contents of potential nutrients for plants, SQ had the highest contents of P₂O₅. For instance, Fe varied from 148 mg kg⁻¹ (HQ) to 1908 mg kg⁻¹ (FQ) (Table 2). The distribution of the content of the elements in each variety of quartz is better shown in Figure 2.

Smoky quartz (SQ) showed the highest contents of Al₂O₃ (21,547 mg kg⁻¹) and P₂O₅ (1532 mg kg⁻¹), and moderate contents of Fe (522 mg kg⁻¹); its color is related to Fe oxide minerals (general term for oxides, oxyhydroxides, and hydroxides). High levels of P₂O₅ were also found in HQ and RQ.

The presence of Mn and V was not observed in all samples. The highest Mn content was observed in RQ (22 mg kg⁻¹). With the exception of HQ and FQ, the lowest V content (12 mg kg⁻¹) occurred in RQ and the maximum one, in MQ (124 mg kg⁻¹).

Although the color of PQ is likely related to Fe content and other environmental factors [22], in this work, the Fe content was not expressive compared to the other varieties of quartz. For milky quartz (MQ), besides presenting the highest contents of Ti and V, no other clear distinction was observed between the contents of elements in relation to the other quartz varieties.

Strong correlations (r ≥ 0.80) were found for the following pairs of elements/oxides (Figure 3): CaO and K₂O (0.94), CaO and Cl (0.90), K₂O and Cl (0.90), CaO and S (0.85), and K₂O and S (0.80). Moderate correlations (0.60 ≤ r < 0.80) were obtained for six pairs of elements: Fe and Cl (0.77), Fe and K₂O (0.79), S and Cl (0.76), Fe and CaO (0.75), Mn and S (0.71), P₂O₅ and Al₂O₃ (0.61). The two oxides that presented the highest correlations (CaO and K₂O) presented their highest contents in RQ, and FQ (Table 1 and Table 2). The other elements that also presented strong correlations (Cl and S) had their highest contents found in FQ (Table 2).

3.3. Importance of pXRF Variables for Quartz Variety Discrimination

Aiming to identify the main elements and oxides for the discrimination of quartz varieties based on pXRF data, the RF algorithm delivered the importance of the elements and oxides for that purpose (Figure 4). The most important ones were S, P₂O₅, Cl, SiO₂, and K₂O. As they were responsible for decreasing most of the node purity in models, they were relevant to discriminate quartz varieties, and they probably are important influencers on the color of quartz varieties.

The least relevant elements were Mn and Rb, likely due to their lower variability and contents among the varieties of quartz (Figure 2). Furthermore, most data for the elements mentioned above were values below the limit of detection for many varieties of quartz, which would make it difficult to use these elements to help discriminating quartz varieties.

Based on the data obtained through the pXRF analyses and RF algorithm, the model for prediction of varieties of quartz reached an overall accuracy of 0.69 and a kappa index of 0.62. These results indicate a significant prediction capacity of the model for discriminating varieties of quartz based on pXRF-delivered elemental/oxides contents.

The prediction model only misclassified PQ as HQ; HQ as PQ; RQ as SQ; and PQ as RQ (Figure 5). Even with these misclassifications, the prediction model was considered adequate for the main purpose of its development. The goal was to test if data provided by pXRF were sufficient for characterizing the differences caused by elements other than Si and O present in quartz varieties, in order to identify the main elements and oxides contributing to the discrimination of varieties of quartz. If a model can be built and performs well, then the input data are likely capturing key differences in quartz varieties. Therefore, the main goal was not to create a model for predicting purposes,, since the visual identification of quartz varieties is much easier than to develop a model to predict each variety; the purpose was simply to verify if pXRF-delivered data could differentiate the quartz varieties with the aid of RF algorithm.

4. Discussions

4.1. Chemical Variability of Quartz Varieties Detected by pXRF and Relations to Color

Since quartz is considered one of the main minerals in soils and rocks and given its high content of SiO₂, the presence of other elements in quartz constitution may contribute to the delivery of such elements to soils along weathering. Such elements may be adequately detected by pXRF (Table 1 and Table 2 and Figure 2). The most chemically pure quartz is colorless and transparent with a glassy shine, but more commonly found quartz varieties may have other colors [23]. For each color, there is at least one component isomorphically substituting Si or in interstitial positions. Other varieties of more common quartz are mixtures of quartz and other minerals/elements, such as RQ (Ti), blue quartz (possibly ilmenite), red jasper (hematite), and MQ (clay minerals). The pXRF spectrometry detected 239 mg kg⁻¹ of Ti in the RQ (Table 2).

HQ showed the highest content of SiO₂ and the lowest content of other elements. According to Correa [12], this produces its transparency/absence of color. Moreover, most of the color variation of quartz is related to the replacement of Si by Al³⁺ and Fe³⁺ ions. The SiO₄ tetrahedra are connected to each other by their vertices, forming a three-dimensional structure that originates empty spaces (interstitials) along the c axis (major direction of the unit cell), while smaller spaces are also formed perpendicular to the c axis of the unit cell [24,25]. The replacement of Si⁺⁴ by Al⁺³ (and by other elements in smaller portions, as Fe²⁺) generates a charge imbalance, requiring the incorporation of metallic ions, such as Li⁺, Na⁺, and K⁺, among others, which may occupy the empty spaces of the tetrahedral structure. The replacement of Si by Ti, V, Cr, Mn, and Fe, when possible, occurs in a limited space and is due to the small ionic rays and high valences of these elements; in addition, the incorporation of an ion is benefited by the presence of another [26].

Specifically, the color displayed by PQ and SQ is probably caused by Fe and Al in addition to fewer influences by Li and H [23]. According to Klein and Hurlburt [27], the color developed by SQ is a consequence of natural radiation in quartz together with elements, such as Al and Li. The pink color displayed by RQ occurs due to the presence of Ti³⁺, the change in charge between Fe²⁺ + Ti⁴⁺ + Fe³⁺ + Ti³⁺, Ti⁴⁺ + Ti³⁺, and trace amounts of Al and P [28]. Moreover, this replacement of Si⁴⁺ by P⁵⁺ occurs as P assumes the position of the main element in the mineral [29,30].

The color of PQ, in addition to other factors such as temperature, is determined by the presence and variation of Fe ions [12,23]. Regarding MQ, it is believed that its white color is due to tiny fluid inclusions in the mineral and not specifically due to the presence of metal elements [12].

Among the elements present in all the varieties of quartz, Ca showed high contents in FQ. Ca is found in quartz after reaction at high temperatures and its variation in terms of contents indicates quartz formation in different conditions. An example cited by Correa [12] is the formation of the mineral wollastonite (Ca₃Si₃O₉), which is formed from the interaction of quartz with calcite in some metamorphic reactions (e.g., skarn aureoles), in temperatures above 600 °C [31].

The purple color of PQ is also due to the presence of Fe (up to 350 mg kg⁻¹), although its color is not caused only by the presence of Fe, since Fe is present in other varieties of quartz and other elements can also be found in PQ [22,32,33]. The pXRF spectrometry detected 222 mg kg⁻¹ of Fe (Table 2), in agreement with the aforementioned limits of Fe³⁺.

The color of SQ is due to isomorphic substituent Al³⁺. The pXRF spectrometry detected 522 mg kg⁻¹ of Fe in the first and 21,547 mg kg⁻¹ of Al₂O₃ in this quartz variety (Table 2). It is important to emphasize that pXRF spectrometry can detect and quantify elements as isomorphic substituents in the quartz crystalline structure, in the interstitial positions, or as coatings on quartz grain surfaces [11,14], but without distinguishing their forms or specific locations.

4.2. Relations between Quartz Varieties and Soils

Quartz is the main mineral in the sand fraction for most Brazilian soils [8]. Although it is a mineral highly resistant to weathering, the presence of elements, especially nutrients, may contribute to the increase in these elements in soil solution, with possible absorption by plants [3,5]. This is especially important in soils with low natural content of nutrients, such as those developed from quartz-rich parent materials [2]. Thus, the characterization of quartz varieties in this study may contribute to show the main elements of different quartz varieties and the effects of quartz in soils of tropical conditions.

In tropical conditions, the presence of quartz greatly affects soil attributes in physical, chemical, and mineralogical terms. Lower specific surface area (generally greater particle size), lower hydration degree, and lower or null superficial electrical charge may occur as quartz concentration increases [2,3,34]. The H₄SiO₄ has a beneficial effect on the development of some crops, such as sugarcane and rice, although Si has not been considered an essential element to the growth of plants [5].

Due to the high resistance of quartz to weathering–leaching conditions and its common occurrence in igneous, metamorphic, and sedimentary rocks, quartz is the most frequent mineral in the majority of soils from tropical regions [9]. Moreover, given its high resistance to weathering, it is employed as a mineral index in studies of soil parent material uniformity, soil evolution, and its weathering–leaching degree [11,34,35]. In addition, quartz may be used in the discrimination of the parent materials of soils, for instance, rhyolite–dacite-derived soils contain more quartz than basalt-derived soils, thus distinguishing acidic from basic lava flows [36].

Quartz tends to concentrate in fractions with coarse size fractions and in the superficial (eluvial) horizons of Ultisols, Alfisols, and Spodosols, due to its high resistance to extensive weathering–leaching conditions in this part of these soil profiles, and constitutes more than 90% of the mineral fraction of quartz-rich sandy soil classes (Quartzipsamments) [10]. In general, the higher the quartz concentration in soils or in parent materials, the more resistant to weathering they tend to be. Therefore, a lower content of smaller fractions (mainly clay) is formed by weathering of those soils and rocks, generating soils with greater sand content. A lower content of smaller fractions means less specific area. Thus, such soils tend to be less reactive (considering soils formed under similar environmental conditions) [9].

Further, quartz is present in soils mainly as a primary mineral, inherited from several parent materials. Authigenic (neoformed) quartz is abundant in siliceous sediments such as cherts, where it predominates in the granular form (microcrystalline). Authigenic quartz may also be formed by direct precipitation from the soil solution [37]. Drees et al. [38] stated that authigenic quartz forms are relatively common in soils and they play a substantial role as a cementing agent in various sediments and soil parent materials. It is the most common Si oxide mineral in soils of the tropical regions [8].

The very small amount of elements (besides Si) found in quartz, as indicated by the studied samples (Table 1 and Table 2), explains why soils derived from quartz-rich rocks and sediments are well-known for having low nutrient contents available to plants. Considering the nutrients detected by pXRF herein (Ca, K, P, S, Cl, Fe, and Mn) and associated to the different quartz varieties in soils, this potential reserve is dependent upon the quartz content and its particle size. If quartz particles are found in sizes ranging from fine sand to coarse clay fraction, there is a greater possibility of quartz dissolution and release of such nutrients to uptake by plant roots. It is important to highlight that authigenic quartz may be formed by direct precipitation from soil solution, but in this case in the clay-sized fraction [35] instead of the sand and silt fractions. This authigenic quartz in the clay size fraction is relatively common in soils and it is more reactive than the coarser fraction ones [38].

Still regarding such elements detected herein, Fe and Mn tend to decrease quartz stability in soils due to the possibility of seasonal redoximorphic conditions to promote their reduction to Fe²⁺ and Mn²⁺ forms, altering the electrical balance of quartz crystalline structure and facilitating its weathering. In the case of Ti, there is an opposite trend since it does not suffer reduction in soils and the Ti-O bonds are stronger (higher bond energy, in KJ mol⁻¹) than Si-O bonds [39], increasing quartz stability in soils of the tropics. Regarding Al, although it is not reduced in soils, similarly to Ti, its trivalent valence can alter the electrical balance of quartz crystalline structure when replacing tetravalent Si. Thus, it may also decrease the quartz stability in soils from the tropical regions.

It is worth mentioning that the quartz particle size is crucial for its behavior in soils, i.e., when the quartz size is equal or superior to the coarse sand fraction, its resistance to weathering–leaching degree is enormous; when it is smaller than that (fine sand or smaller), its solubility is increased and it is more reactive and unstable. Two examples of effects of the latter condition in Quartzipsamments in Brazil involve silica (this term refers to SiO₂ chemical composition, being employed as a generic designation for various forms of Si oxides) release in solution, even at a very slow rate, reducing the phosphates adsorption (very important aspect for soil fertility management), and inhibiting gibbsite formation [39]. These examples highlight that the kinetics (velocity of reactions) should be interpreted in association with the laws of thermodynamics in the behavior of quartz in soils of the tropical regions. The chemical elements of quartz may also interfere in this context, as previously stated.

5. Conclusions

It was possible to use pXRF spectrometry as a tool to determine the chemical variability of different varieties of quartz. Hyaline quartz presented the highest content of SiO₂, while the other varieties of quartz have greater presence of other elements. For the ferriferous quartz, the dominance of Fe is evident, as expected. Furthermore, the presence of Fe and Al in the composition of the different varieties of quartz was verified, confirming such elements present in quartz due to isomorphic substitution, in interstitial positions and/or as coatings during the diverse processes that form quartz varieties.

Via Random Forest algorithm, S, P₂O₅, Cl, SiO₂, and K₂O were the main compounds for the discrimination of the varieties of quartz based on pXRF data, with an overall accuracy of 0.69. Only rose quartz presented greater misclassifications than the other varieties of quartz.

A simple and fast analysis could offer insights about differences in quartz varieties. Although not as accurate as traditional wet chemistry and acid digestion assessments, pXRF could identify key signatures related to the elements that characterize each quartz variety. Future work is advised to further investigate how these different varieties relate to parent materials and soils formed from them.