# A Data Mining Approach to Improve Inorganic Characterization of Amanita ponderosa Mushrooms.

1. IntroductionMushrooms are known from ancient times for their medicinal properties and gastronomic properties. Therefore the consumption of edible wild-growing mushrooms has been very popular. The demand for the commercialization of edible wild mushrooms has proved to be a widely expanding business with increasing economic importance in many rural areas of some countries. In recent years, the consumption of edible mushrooms has been increasing and gaining prominence due to their gastronomic potential, also for their both organoleptic properties (texture and pleasant aroma) [1-4], their chemical composition, mineral content, and nutraceutical value [4-8]. Mushrooms are an important source of proteins, dietary fibres, and vitamins (B, C, D, E) containing low levels of sugar and fats. They can assimilate large amounts of water and minerals such as phosphorus, iron, potassium, cadmium, magnesium, copper, and zinc, due to the large area of mycelium overgrowing the surface layer of soil [9]. This mycelia network is ideally suited to penetrate and access soil pore spaces and an extensive surface area of fungal hyphae and physiology enable for many species on effective absorption and bio concentration of various metallic elements, metalloids, and nonmetals [10]. Bioconcentration factor (BCF), the ratio of the element content in fruiting body to the content in underlying substrate, can express the ability of fungi to accumulate elements from substrate, and this capacity of the mushroom is affected by fungal lifestyle, age of fruiting body, specific species and element, and environment such as pH, organic matter, and pollution [9]. Moreover, the symbiotic relationships that some mushrooms species, namely, A. ponderosa, can establish with some plants of their habitats allowing the accumulation of high concentrations of some metals. Therefore, mineral content and organic composition of edible mushrooms are dependent on the species and the characteristics of the ecosystems in which they are inserted [11, 12]. Some minerals are essential elements for the correct human body function, although others may present toxicity [5, 6, 9, 11, 13, 14]. There are many species of edible mushrooms growing wild, and some of them are slightly characterized about minerals content and the potential of heavy metals bioaccumulation such as lead, mercury, cadmium, and silver [5, 13, 15-17]. On the other hand, due to the great diversity of wild mushrooms, the similarity between some species and the lack of knowledge of others may lead to intoxication when harvesting wild species, leading in some cases to death [18].

The genus Amanita is one of the best known from Agaricales order and comprises edible and poisonous mushrooms distributed worldwide, occupying mainly a mycorrhizal habitat and playing a significant role in forest ecosystems [19, 20]. This genus includes important species of edible mushrooms, as is the case of Amanita ponderosa [18, 20-24]. The south of Portugal, due to its Mediterranean characteristics and diversity of flora, is one of the regions of Europe with a greater predominance of A. ponderosa wild edible mushrooms [23]. These robust basidiomata grow during spring in mounted areas with acid soils, in forests of holm oaks and cork trees like Quercus ilex and Quercus suber, and with shrubs like Cistus ladanifer, Cistus laurifolius, and Lavandula stoechas establishing a symbiotic relationship with them (Figure 1). Gastronomically, this species is very relevant, not only due to the traditional consumption in the rural populations, but also due to its commercial value in the gourmet markets having high exportation potential in Portugal, thus, the chemical and mineral characterization of numerous species of edible mushrooms for certification purposes and further commercialization process becoming of extreme importance.

In recent years, some artificial intelligence based tools, namely, Data Mining, Artificial Neural Networks (ANNs), and Decision Trees (DTs) have been applied for fungal environment systems [18, 25, 26]. Data mining tools were used in latest studies about A. ponderosa mushrooms in order to establish a bridge of inorganic contents, molecular fingerprints, and geographical sites. In one study a segmentation model based on the molecular analysis was developed, which allowed relating the clusters obtained to the geographical site of sampling. There were also developed explanatory models of the segmentation, using Decision Trees, to relate the molecular and inorganic data, following two different strategies: one based on DNA profile and another based on the mineral composition [22]. Another study based on ANNs exposed the selected model and can predict molecular profile based on inorganic composition with a good match between the observed and predicted values [18].

The aim of this study was to determine the inorganic composition of fruiting bodies of A. ponderosa mushrooms from different sampling sites in the southwest of the Iberian Peninsula, analysing the variations in mineral content. Additionally, the mineral composition of the corresponding soil substrates was analysed in order to correlate with the mineral composition of the fruiting bodies. In the present work, the k-means clustering method was used to study the mineral composition of A. ponderosa fruiting bodies. To explain the segmentation model, that is, in order to obtain rules to assign a case to a cluster DTs were used.

2. Materials and Methods

2.1. Sampling Collection. Fruiting bodies of the Amanita ponderosa mushrooms were collected in spring, between February and April, from 24 different sampling sites, in the southwest of the Iberian Peninsula, namely, 11 samples collected from Alto Alentejo region and 10 from Baixo Alentejo, Portugal, 2 samples collected from Andalusia and 1 from Extremadura, Spain (Table 1). These mushrooms were collected in acid soils, in forests of Quercus suber, Q. ilex ssp. ballota, Cistus ladanifer, and Cistus laurifolius (Figure 1).

Three individuals in the same growth stage were selected per each sampling site to avoid the effect of size. Fruiting bodies were identified by a specialist, based on morphological features according to taxonomic description of A. ponderosa [27]. During the collection process fruiting bodies were placed in wicker baskets and samples were transported in refrigerated containers and deposited in the Biotechnology Laboratory of Chemistry Department of University of Evora (Portugal). In parallel, soil samples were randomly collected from the surrounding soil of fruiting bodies of each site.

Fruiting bodies samples were weighed and carefully washed with double distilled water and representative samples of each sampling site were catalogued, stored in sterile bags, and preserved at -20[degrees]C for its inorganic study. The sheath was eliminated during the pretreatment of fruiting bodies samples, since it is not usually consumed.

Soil substrates were sampled (0-15 cm), after removing some visible organisms, small stones, sticks, and leaves. Samples were air-dried in room temperature for 1-2 weeks and, subsequently, sieved through a pore size of 2 mm and stored at -4[degrees]C.

2.2. Inorganic Characterization. Mineral composition was determined in A. ponderosa fruiting bodies and respective soil collected in 24 different sampling sites described, using different analytical techniques: Flame Atomic Absorption Spectrometry (FAAS), Flame Emission Photometry (FEP), and UV-Vis molecular absorption spectrometry.

2.2.1. Treatment of Samples. Mineral composition analysis of fruiting bodies was performed by the dry mineralization method [28]. Three samples of mushrooms from each sampling site (25 g, fresh weight) were dried in a furnace at 100[degrees]C to constant weight (48 h) from which the moisture content was calculated. Samples were homogenized, transferred to porcelain crucibles, and incinerated in a muffle furnace (Termolab) at 460[degrees] C for 14 h. In order to determine the organic matter and mineral content in mushrooms samples, ashes were weighted at constant weight. Afterwards, ashes were bleached after cooling by adding 2 M nitric acid, drying them on thermostatic hotplates, and maintaining them at 460[degrees]C for 1 h. Ashes recovery was performed with 15 mL of 0.1 M nitric acid and stored at 4[degrees]C until analyses.

Three soil samples (5 g dw) collected from each sampling site were cold treated with an extracting solution of 25% nitric acid (HN[O.sub.3]) (40 ml) and shaking with orbital agitation for 24 h at room temperature. The extracts obtained after filtering through Whatman No. 42 filter paper were stored into polyethylene bottles and stored at 4[degrees]C until analyses [11].

2.2.2. Analytical Determinations. Aluminium (Al), barium (Ba), calcium (Ca), cadmium (Cd), lead (Pb), copper (Cu), chromium (Cr), iron (Fe), magnesium (Mg), manganese (Mn), silver (Ag), and zinc (Zn) contents were quantified by flame atomic absorption spectrometry (Perkin-Elmer 3100 model) with atomization in an air-acetylene flame and single element hollow cathode lamps and background correction with deuterium lamp for manganese. For the determinations of calcium and magnesium, strontium chloride (Sr[Cl.sub.2]) was added to make up a final concentration of 0.1125% of the sample, in order to prevent anionic interferences which might modify the result [29].

Sodium (Na) and potassium (K) were quantified by flame emission photometry with a Jenway model PFP7 flame emission photometer [30, 31]. Phosphorus (P) was quantified by vanadomolybdophosphoric acid colorimetric method, using a spectrophotometer (Hitachi, U-3010 model) [32].

All sample determinations were performed in triplicate for each one of the three independent ash extracts of mushroom samples from 24 sampling sites (n = 9) and for three extracts of each soil substrate (n = 9). Concentration values were calculated through the standard curves for each element expressed in mg/kg dw. The bioconcentration factor (BCF) value, which is the quotient of the concentration in fruiting bodies divided by the concentration in the soil substrates, was determined for all minerals in each sampling site.

2.3. Data Mining

2.3.1. Cluster Analysis. In the present study a cluster analysis was carried out. The technique applied in order to build up clusters was the k-means clustering method [33] and the software used was WEKA [34]. In WEKA Simple k-means algorithm the normalization of the numerical attributes is carried out automatically when the Euclidean distance is computed. A more detailed description of the mentioned algorithm can be found in Witten [35].

2.3.2. Decision Trees. In the k-means clustering method clusters were formed without information about the groups and their characteristics. Therefore, it is necessary to understand how the clusters were formed. To attain such a purpose Decision Trees (DTs) were used. In this study the algorithm used to generate DTs was the WEKA J48 [34], corresponding to the 8th revision of the C4.5 algorithm. The detailed description of the J48 algorithm can be found in Witten et al. [35].

2.4. Statistical Analysis. Data were evaluated statistically using the SPSS[R] 21.0 software Windows Copyright[c], (Microsoft Corporation), by descriptive parameters and by one-way ANOVA in order to determine statistically significant differences at the 95% confidence level (p < 0.05). The homogeneity of the population variances was confirmed by the Levene test and the multiple comparisons of media were evaluated by Tukey's test.

3. Results

3.1. Fruiting Bodies and Soil Substrates' Mineral Composition. Mineral analysis of A. ponderosa mushrooms samples collected from 24 sampling sites of Alentejo (Portugal), Andalusia, and Extremadura (Spain) regions was evaluated.

Table 2 shows the contents in moisture, organic content, and minerals present in the samples of A. ponderosa collected in the different places. Moisture content ranged from 89.5[+ or -] 0.0 to 93.8[+ or -]0.5% (Table 2). The analyses of variance (one-way ANOVA) showed that A. ponderosa fruiting bodies samples collected in Almendres (1) and Serpa (20) presented significantly higher values compared to the other samples, while the sample from Mina S. Domingos (11) showed moisture content significantly lower than the remaining samples. Dry weight values, for several samples, ranged between 6.2 [+ or -] 0.5 and 10.5 [+ or -] 0.1%, consisting in organic content values between 5.8 [+ or -] 0.3 and 9.8 [+ or -] 0.1% and minerals between 0.5 [+ or -] 0.0 and 1.4 [+ or -] 0.1%. Fruiting bodies samples collected in Almendres (1) and Serpa (20) presented values of organic content significantly lower and the sample collected in the Mina S. Domingos (11) significantly higher than all analysed samples (p < 0.05). The mineral content of the fruiting bodies collected in Cabezas Rubias (6) was 1.4 [+ or -] 0.1%, a value significantly higher than the remaining samples. However, the samples from Serpa (20) and Villanueva del Fresno (24) showed the lowest values, significantly different from the another samples (p < 0.05).

Figure 2 shows the average contents of water, dry weight, organic content, and minerals present in the 24 samples of A. ponderosa analysed. The fruiting bodies presented water content, corresponding to 90.3 to 93.1% of their fresh weight. The organic matter content ranged between 6.2 and 9% and mineral content between 0.5 and 0.9%. Thus, 100 g of edible A. ponderosa mushrooms corresponds to a maximum of 9 g of macronutrients, such as lipids, carbohydrates, and proteins, and less than 1 g of mineral content. These values were similar to those observed in a study with mushrooms harvested in some regions of Andalusia (water content 87.8%, organic content 11.8%, carbohydrates 6.6%, proteins 3.2%, lipids 0.5%, fibre 1.5%, and mineral content 0.4%) [24] and these fruiting bodies have a caloric content of 42kcal/100 g of mushroom, similar to other edible mushroom species, characterized as low calorie foods [8, 28, 36].

Tables 3-6 show the mineral content of 24 sampling sites of A. ponderosa fruiting bodies as well as their corresponding soil samples. The studied A. ponderosa fruiting bodies showed higher mineral content in macroelements calcium (Ca), magnesium (Mg), sodium (Na), potassium (K), phosphorus (P), and microelements aluminium (Al), copper (Cu), and iron (Fe) (Tables 3 and 4). Potassium was present in higher concentrations and was higher in Cabezas Rubias (6) fruiting bodies, 69565 [+ or -] 362 mg/kg dw. The samples showed lower values of the trace elements silver (Ag), barium (Ba), cadmium (Cd), chromium (Cr), manganese (Mn), lead (Pb), and zinc (Zn) (Tables 5 and 6).

Minerals contents of A. ponderosa fruiting bodies and their corresponding soil samples presented significant differences for all the studied elements (p < 0.05). Cabezas Rubias (6) presented significantly higher aluminium and calcium contents (p < 0.05). The cadmium content was significantly higher (p < 0.05) in the fruiting bodies collected in N. [S.sup.ra] Machede (16) and Almendres (1). Samples from Evora (7), Cabezas Rubias (6), and Villanueva del Fresno (24) showed similar chromium contents (p > 0.05), which were significantly higher than the others A. ponderosa fruiting bodies (p < 0.05). Results obtained for soil mineral content showed some significant differences between sampling sites (p < 0.05). The sample collected in N. [S.sup.ra] Machede (16) presented significant different contents of silver, aluminium, and magnesium (p < 0.05). The Montejuntos sample (14) presented significantly differences of aluminium, iron, phosphorus, and magnesium contents (p < 0.05) and Villanueva del Fresno (24) presented significant differences for barium and manganese (p < 0.05). Significant differences in copper content were observed for [Her.sup.de] da Mitra sample (9). Mertola sample (10) presented significant differences in zinc and Baleizao sample (3) in potassium contents (p < 0.05). Serpa samples (20), presented significant differences in calcium, chromium, iron, magnesium, sodium, and zinc (p < 0.05). Almendres (1), Evora (7), [M.sup.te] Novo (13) and Valverde (22) samples did not present significant differences for the iron content (p > 0.05). Samples of Cabezas Rubias (6), Serpa (20), and Rosal de la Frontera (17) did not present significant differences in lead content (p > 0.05). Concerning phosphorus content, two groups with no significant differences (p > 0.05) were observed, one including Baleizao (3) and Rosal de la Frontera (17) and the other group including [S.sup.to] Aleixo Restauracao (18), S. Miguel de Machede (19), and Vila Nueva del Fresno (24) samples. Finally, samples from Baleizao (3) and Valverde (22) did not present significant differences in sodium and potassium content (p > 0.05).

In fact, mineral content of A. ponderosa fruiting bodies and their soil samples (Figure 3) varied very similarly for almost all the analysed elements, indicating the influence of the substrate characteristics on the composition of mushrooms samples collected at the different sites.

Mushrooms have a specialized mechanism to accumulate nutrients and minerals in their fruiting bodies. The age of the fruiting body or its size may contribute to mineral composition. Thus, A. ponderosa mushrooms analysed in this study were obtained at the same development stage, in order to eliminate possible size interferences in the comparison of their mineral content. Macroelements content, such as Ca, Mg, Na, K, and P, in fruiting bodies were similar to those reported in literature for A. ponderosa [28] and for other edible mushrooms species [5, 36-38]. The calcium and phosphorus contents for the different samples studied were 523 [+ or -] 143 and 294 [+ or -] 171 mg/kg dw. Potassium and sodium, minerals responsible for the hydroelectrolytic balance maintenance and important enzyme cofactors, have high RDIs (Recommended Daily Intakes), which are 4700 mg/day and 2000mg/day, respectively, for an adult [39]. Potassium and sodium levels of A. ponderosa mushrooms studied were 29648 [+ or -] 14908 and 1092 [+ or -] 620 mg/kgdw, respectively. Potassium content ranged from 18021 [+ or -] 1806 to 69565 [+ or -] 362 mg/Kg dw, presenting values similar to those described by Moreno-Rojas et al. [28], that report potassium levels ranging between 22410 [+ or -] 211 and 60890 [+ or -] 23950 mg/Kg dw. However, the low K levels observed for fruiting bodies from three sampling sites can be correlated with the large differences observed for potassium content in the surrounding substrates. Magnesium also plays an important role in large number of biological functions, particularly linked to energy metabolism, it is required for the proper function of certain enzymes as cofactor, and structural functions, the recommended magnesium intakes for adult (19-65 years), are 220-260 mg/day [40]. The mean magnesium content in the fruiting bodies was 738 [+ or -] 261 mg/kgdw, similar to that described in the literature [28].

A. ponderosa fruiting bodies presented values of trace minerals smaller than those found in other species of edible mushrooms [6, 11, 14, 38, 41]. Concentrations of trace elements in fruiting bodies are generally species-dependent [36]; however only one study of A. ponderosa mushrooms is reported [28]. The existence of higher metal concentrations in younger fruiting bodies can be explained by the transport of metals from the mycelium to the fruiting body during the beginning of fructification [36]. Trace elements like Fe, Cu, Zn, Cr, and Mn are essential metals since they play an important role in biological systems; however, these trace metals can also produce toxic effects when intake is excessively amount [38, 42, 43]. Copper is the third most abundant trace element found in the human body, and being an important element of several enzymes, it is also one of the agents involved in iron metabolism [42]. Iron is a component of haemoglobin and myoglobin, proteins responsible for transporting oxygen to tissues. It also participates in protein metabolism, energy production in cells and in various enzymatic reactions [44]. The copper content was 185 [+ or -] 125 mg/kg dw, and the highest value was found in A. ponderosa samples collected from Rosal de la Frontera (17) (584 [+ or -] 51 mg/kg dw). The iron content in A. ponderosa mushrooms was 92 [+ or -] 85 mg/kg dw. Copper levels were similar and iron levels are slightly lower than those described for Amanita spp. [5, 28]. The adult RDI is 2 mg/day for Cu and 18 mg/day for Fe [12, 39], so the concentrations of copper and iron present in these edible mushrooms are not considered to be a health risk. Manganese and zinc are important trace elements for the human organism, participating in macronutrients and nucleic acids metabolism and promoting several enzyme activity processes [14, 45, 46]. These elements can be accumulated by mushrooms and the recommended daily intakes were 2 mg/day and 15 mg/day, for manganese and zinc, respectively [12, 39]. In this study, mushrooms presented a mean value of 56 [+ or -] 27 mg/kg dw for manganese and 68 [+ or -] 25 mg/kg dw for zinc content, similar to values described in literature [5, 6, 11, 36, 47]. Chromium biological functions are not known precisely; it seems to participate in the metabolism of lipids and carbohydrates, as well as in the insulin action. The RDI for this metal is 120 [micro]g/day. The mean chromium content obtained was 1,19 [+ or -] 0,74 mg/kg dw, lower than those reported in the literature for other species of Amanita [5] and similar to some species of edible mushrooms described [11, 36]. Aluminium is one of the few abundant elements in nature but no significant biological function is known, although there are some evidences of toxicity when ingested in large quantities. Most acidic soils are saturated in aluminium instead of hydrogen ions, and this acidity is the result of aluminium compounds hydrolysis [48]. A. ponderosa fruiting bodies from the different sampling sites showed a high range of aluminium content with a medium value of 362 [+ or -] 204 mg/Kg dw. High aluminium levels were reported for some Amanita species, for example, A. rubescens that showed values around 262 mg/kg dw [15] and A. strobiliformis and A. verna presented aluminium levels of 72 and 343 mg/kg dw, respectively [5]. Other studies report different levels of aluminium in Amanita rubescens: 293, 75, and 512 mg/kg dw for the whole fruiting body, cap, and stipe, respectively [37]. The large range in aluminium content was also reported in a study of A. fulva that showed aluminium levels ranging from 40 to 500 mg/Kg dw in the stipe and 40 to 200 mg/Kg dw in cap [10]. Regarding cadmium and lead, these elements have the highest toxicological significance. Cadmium has probably been the most damaging metal found in mushrooms; some studies point out the existence of accumulating species, which, in polluted areas, accumulate this metal. The mean values of cadmium and lead were 1.00 [+ or -] 0.73 mg/kg dw and 2.41 [+ or -] 1.34 mg/kg dw, respectively, showing that the A. ponderosa had no toxicity due to the presence of these two elements [5,11]. The contents of heavy metals barium and silver in the studied mushrooms were 1.10 [+ or -] 0.59 mg/kg dw and 2.01 [+ or -] 1.56 mg/kg dw, respectively. These values are similar to those described in the literature for other species of edible mushrooms [11] and lower than those described for species of the genus Amanita [5, 13].

Bioconcentration factor (BCF) allows estimating the mushroom potential for the bioextraction of elements from the substratum (soil). Values of BCF of A. ponderosa fruiting bodies are summarized in Tables 7 and 8. The macroelements, K and Na, exhibited the highest values of BCF but Ca, Mg, and P also presented BCF > 1. Trace elements, Ag, Cd, Cu, and Zn, presented BCF > 1 with higher values for Cu. The remaining elements (Fe, Mn, Ba, Cr, and Pb) are bioexcluded showing lower values (BCF < 1). For copper, BCF values ranged from 9 to 248, showing bioaccumulation of this metal. The same heterogeneous behaviour is observed for Ag, Cd, and Zn with values ranging from 1-72, 1-38, to 2-25, respectively. Ag bioaccumulation was found in other Amanita species with much higher values of BCF [13]. The high levels of aluminium observed for some A. ponderosa fruiting bodies can be related to soil content and to their different ability to accumulate this mineral, with BCF > 1 for some stands. Some works with different species such as Leccinum scabrum, Amanita rubescens, and Xerocomus chrysenteron reported different aluminium accumulation [15]. Some species of Basidiomycetes can be useful for assessing the environmental pollution levels [38].

Metal concentrations were usually assumed to be species-dependent, but soil composition is also an important factor in mineral content [12, 36, 38, 49]. In order to clarify this association between inorganic composition of A. ponderosa mushrooms and soil, a data mining approach was developed.

3.2. Segmentation Models Based on Mushrooms and Soil Mineral Content: Interpretation and Assessment. The k-Means Clustering Method is a segmentation algorithm that uses unsupervised learning. The input variables used in the segmentation approach are macroelements content (Na, K, Ca, P, and Mg), trace elements content (Al, Fe, Cu, Zn, Cr, and Mn), and heavy metals (Ag, Ba, Cd, and Pb). The algorithm input parameter is the number of clusters, 3 in this study. Table 9 shows the clusters centre of gravity, in order to characterize the clusters formed.

The analysis of Table 9 shows that cluster 1 is characterized by high values of Ag, Ba, Cd, K, Mg, and P. Cluster 2 is characterized by high content of Cr, Fe, Mn, Na, Pb, and Zn and Cluster 3 showed lower mineral content. In order to evaluate the relationships between clusters and fruiting bodies sampling sites the graph presented Figure 4 was conceived.

The analysis of Figure 4 shows that cluster 1 is formed by the samples collected at Almendres (1), Baleizao (3), Cabeca Gorda (5), Evoramonte (8), Mina S. Domingos (11), Montejuntos (14), N. [S.sup.ra] Guadalupe (15), N. [S.sup.ra] Machede (16), Rosal de la Frontera (17), Serpa (20), and Villanueva del Fresno (24). Cluster 2 includes the samples collected at Beja (2), Evora (7), S. Miguel de Machede (19), and V. N. S. Bento (23). Finally, cluster 3 is composed by the samples collected at Azaruja (2), [Her.sup.de] da Mitra (9), Martola (10), [M.sup.te] da Borralha (12), [M.sup.te] Novo (13), [S.sup.to] Aleixo da Restauracao (18), [V.sup.e] de Rocins (21), and Valverde (22).

In order to generate an explanatory model of segmentation (i.e., seek to establish rules for assigning a new case to a cluster), Decisions Trees (DT) were used. Two different strategies were followed: one of them based on the mineral mushrooms content (strategy 1) and the other one based on the soil mineral composition (strategy 2).

To ensure statistical significance of the attained results, 25 (twenty-five) runs were applied in all tests, the accuracy estimates being achieved using the Holdout method [50]. In each simulation, the available data are randomly divided into two mutually exclusive partitions: the training set, with about 2/3 of the available data and used during the modelling phase, and the test set, with the remaining examples, being used after training, in order to compute the accuracy values.

The DT obtained using the strategy 1 is shown in Figure 5. The minerals that contribute to this explanatory model are Fe, Zn, and Ba and the rules to assign a case to a cluster are as follows:

(i) If Fe [less than or equal to] 118.76 mg/Kg and Zn > 51.454 mg/Kg and Ba > 0.523 mg/Kg Then [right arrow] Cluster 1 (ii) If Fe > 118.76 mg/Kg Then [right arrow] Cluster 2 (iii) If Fe [less than or equal to] 118.76 mg/Kg and Zn [less than or equal to] 51.454 mg/Kg Then [right arrow] Cluster 3 (iv) If Fe [less than or equal to] 118.76 mg/Kg and Zn > 51.454 mg/Kg and Ba [less than or equal to] 0.523 mg/Kg Then [right arrow] Cluster 3

A common tool for classification analysis is the coincidence matrix [51], a matrix of size L x L, where L denotes the number of possible classes. This matrix is created by matching the predicted and actual values. L was set to 3 (three) in the present case. Table 10 presents the coincidence matrix. The results reveal that the model accuracy is 100% both in the training set and in test set.

In order to relate the mineral mushrooms content to the soil mineral composition an explanatory model of the clusters formed was made, using the soil content of the same minerals (i.e., Fe, Zn, and Ba). Since the model accuracy is only 74% a new explanation model was built up. In this attempt all inorganic soil mineral content was available. The referred model is shown in Figure 6 and the respective coincidence matrix is presented in Table 11.

The model accuracy was 89.1% and 82.6%, respectively, for training and test sets. The soil minerals that contribute to this explanatory model are Cr, Ba, and Zn. The rules to assign the cases to each cluster are as follows:

(i) If Cr (soil) > 3.765 mg/Kg Then [right arrow] Cluster 1 (ii) If Cr (soil) [less than or equal to] 3.765 mg/Kg and Ba (soil) [less than or equal to] 3.012 mg/Kg and Zn (soil) [less than or equal to] 5.944 mg/Kg Then [right arrow] Cluster 1 (iii) If Cr (soil) [less than or equal to] 3.765 mg/Kg and Ba (soil) > 3.012 mg/Kg and Zn (soil) > 5.033 mg/Kg Then [right arrow] Cluster 2 (iv) If Cr (soil) [less than or equal to] 3.765 mg/Kg and Ba (soil) [less than or equal to] 3.012 mg/Kg and Zn (soil) > 5.944 mg/Kg Then [right arrow] Cluster 3 (v) If Cr (soil) [right arrow] 3.765 mg/Kg and Ba (soil) > 3.012 mg/Kg and Zn (soil) [less than or equal to] 5.033 mg/Kg Then [right arrow] Cluster 3

This study observed that the mineral content was influenced by the location area in which the mushroom samples were collected, possibly due to the soil composition and by environmental factors, such as medium temperature, vegetation, and rainfall. Indeed the inorganic composition of A. ponderosa allows group mushrooms according to the location area, based mainly in their Fe, Zn, and Ba content. On the other hand, it is possible to predict the same mushroom clustering taking into account the mineral soil content, based in Cr, Ba, and Zn soil composition although with a lower model accuracy.

Results of mineral composition do not reveal a direct correlation between inorganic composition of A. ponderosa mushrooms and their corresponding soil substrate; nevertheless, mushrooms are agents that play an important role in the continuous changes that occur in their habitats, and indeed they present a very effective mechanism for accumulating metals from the environment.

Moreno-Rojas et al. (2004), in the study of mineral content evaluation of A. ponderosa samples from Andalusia, also verified that variations occurred in the mineral composition according to the sample collection site, particularly in relation to Fe, K, and Na contents. Other authors also report that the main cause of variation of mineral composition between samples of different species of Amanita is the character and composition of the substrates (e.g., sand and wood) and may be influenced by the presence or absence of ability of the different species for a specific accumulation of some metals, namely, copper and zinc [5]. In a study carried out with a species of Boletaceae (Suillus grevillei), it is also mentioned that the variations in mineral composition of the different samples are related to the composition of the substrates and the geochemistry of the soils of each site [11].

4. Conclusions

A. ponderosa mushrooms collected from different sites showed fruiting bodies with water content of 90-93%, dry mass ranging from 6.9 to 9.7%, contents of organic matter between 6.2 and 9.0%, and minerals between 0.5 and 0.9%. Mineral composition revealed high content in macroelements, such as potassium, phosphorus, and magnesium. Copper, chromium, iron, manganese, and zinc, essential microelements in biological systems, can also be found in fruiting bodies of A. ponderosa, within the limits of RDI. Bioconcentration was observed for some macro- and microelements, such as K, Na, Cu, Zn, Mg, P, Ag, Ca, and Cd. The presence of heavy metals, such as barium, cadmium, lead and silver, was quite low, within the limits of RDI, and did not constitute a risk to human health.

Our results pointed out that it is possible to generate an explanatory model of segmentation performed with data based on the inorganic composition of mushrooms and soil mineral content, showing that it may be possible to relate these two types of data. The inorganic analysis provides evidence that mushrooms mineral composition variation is according to the collecting location, indicating the influence of the substrate characteristics in the fruiting bodies. The relationship between mineral elements in mushrooms and soils from the different sampling sites can be an important contribution to the certification process and seem to be related to the substrate effects from interindividual or interstrain differences.

https://doi.org/10.1155/2018/5265291

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

The authors would like to acknowledge the HIT3CH Project-HERCULES Interface for Technology Transfer and Teaming in Cultural Heritage (ALT20-03-0246-FEDER-000004), MEDUSA Project-Microorganisms Monitoring and Mitigation-Developing and Unlocking Novel Sustainable Approaches (ALT20-03-0145-FEDER-000015), cofinanced by the European Regional Development Fund (ERDF), and ALENTEJO 2020 (Alentejo Regional Operational Programme).

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Catia Salvador, (1) M. Rosario Martins, (1,2) Henrique Vicente [ID], (2,3) and A. Teresa Caldeira [ID] (1,2)

(1) HERCULES Laboratory, Evora University, Largo Marques de Marialva 8, 7000-809 Evora, Portugal

(2) Departamento de Quimica, School of Sciences and Technology, Evora University, Rua Romao Ramalho 59, 7000-671 Evora, Portugal

(3) Centro ALGORITMI, Universidade do Minho, Braga, Portugal

Correspondence should be addressed to A. Teresa Caldeira; atc@uevora.pt

Received 30 April 2017; Revised 12 November 2017; Accepted 14 December 2017; Published 31 January 2018

Academic Editor: Gunther K. Bonn

Caption: Figure 1: Geographic representation of sampling location areas of the A. ponderosa fruiting bodies of forest area of the Alentejo, Andalusia, and Extremadura regions. In detail, we observe the sampling site of Evora region (Alentejo, Portugal), showing the surrounding vegetation of Quercus suber, Cistus ladanifer and a sample of the fruiting body collected at this local.

Caption: Figure 3: Concentration of mineral content of A. ponderosa fruiting bodies and soil substrates. The values are represented in logarithmic scale.

Caption: Figure 4: Relationships between clusters of mushrooms and different sampling sites.

Caption: Figure 5: The Decision Tree explanatory of segmentation model based in mineral content of mushrooms samples (strategy 1).

Caption: Figure 6: The Decision Tree explanatory of segmentation model based in mineral content of substrates.

Table 1: Sampling sites description of A. ponderosa mushrooms and soil substrates. Sampling sites GPS coordinates Region/country (1) Almendres 38[degrees]33'57"N 8[degrees]02'40"O (2) Azaruja 38[degrees]42'10"N 7[degrees]45'58"O (3) Baleizao 38[degrees]01'34"N Alentejo, Portugal 7[degrees]42'38"O (4) Beja 38[degrees]02'44"N 7[degrees]50'56"O (5) Cabeca Gorda 37[degrees]55'19"N 7[degrees]48'47"O (6) Cabezas Rubias 37[degrees]43'50"N Andaluzia, Spain 7[degrees]05'11"O (7) Evora 38[degrees]35'01"N 7[degrees]51'46"O (8) Evoramonte 38[degrees]46'22"N 7[degrees]42'45"O (9) [Her.sup.de] da Mitra 38[degrees]31'35"N 8[degrees]00'51"O (10) Mertola 37[degrees]37'44"N 7[degrees]39'30"O (11) Mina S. Domingos 37[degrees]41'02"N Alentejo, Portugal 7[degrees]28'49"O (12) [M.sup.te] da Borralha 37[degrees]58'31"N 7[degrees]37'22"O (13) [M.sup.te] Novo 38[degrees]30'39"N 7[degrees]43'06"O (14) Montejuntos 38[degrees]32'24"N 7[degrees]19'49"O (15) N. [S.sup.ra] Guadalupe 38[degrees]33'47"N 8[degrees]01'23"O (16) N. [S.sup.ra] Machede 38[degrees]35'21"N 7[degrees]48'19"O (17) Rosal de la 37[degrees]57'21"N Andaluzia, Spain Frontera 7[degrees]13'12"O (18) [S.sup.to] Aleixo da 38[degrees]04'01"N Restauracao 7[degrees]09'46"O (19) S. Miguel de 38[degrees]37'34"N Machede 7[degrees]42'33"O (20) Serpa 37[degrees]55'59"N Alentejo, Portugal 7[degrees]35'05"O (21) [V.sup.e] Rocins 37[degrees]52'15"N 7[degrees]44'41"O (22) Valverde 38[degrees]32'24"N 8[degrees]01'18"O (23) V. N. S. Bento 37[degrees]56'27"N 7[degrees]23'51"O (24) Villanueva del 38[degrees]22'49" Extremadura, Spain Fresno N7[degrees]11'35"O Table 2: Moisture, organic content, and minerals contents of A. ponderosa fruiting bodies from different sampling sites. Fruiting bodies Sampling sites Moisture (%) (1) Almendres 93.6 [+ or -] 0.3 (a) (2) Azaruja 92.4 [+ or -] 0.5 (a,b,c,d) (3) Baleizao 90.7 [+ or -] 0.3 (b,c,d,e) (4) Beja 91.0 [+ or -] 0.0 (a,b,c,d,e) (5) Cabeca Gorda 91.6 [+ or -] 0.7 (a,b,c,d,e) (6) Cabezas Rubias 91.8 [+ or -] 0.4 (a,b,c,d,e) (7) Evora 90.2 [+ or -] 1.6 (c,d,e) (8) Evoramonte 90.4 [+ or -] 0.4 (b,c,d,e) (9) [Her.sup.de] da Mitra 90.5 [+ or -] 0.3 (b,c,d,e) (10) Mertola 93.2 [+ or -] 0.3 (a,b) (11) Mina S. Domingos 89.5 [+ or -] 0.0 (e) (12) [M.sup.te] da Borralha 91.5 [+ or -] 1.5 (a,b,c,d,e) (13) [M.sup.te] Novo 91.7 [+ or -] 1.2 (a,b,c,d,e) (14) Montejuntos 92.7 [+ or -] 0.4 (a,b,c,d) (15) N. [S.sup.ra] Guadalupe 91.4 [+ or -] 1.1 (a,b,c,d,e) (16) N. [S.sup.ra] Machede 91.4 [+ or -] 1.5 (a,b,c,d,e) (17) Rosal de la Frontera 90.4 [+ or -] 1.7 (b,c,d,e) (18) [S.sup.to] Aleixo da Restauracao 91.1 [+ or -] 1.1 (a,b,c,d,e) (19) S. Miguel de Machede 92.7 [+ or -] 0.4 (a,b,c,d) (20) Serpa 93.8 [+ or -] 0.5 (a) (21) [V.sup.e] Rocins 93.0 [+ or -] 0.7 (a,b,c) (22) Valverde 92.0 [+ or -] 1.6 (a,b,c,d,e) (23) V. N. S. Bento 90.0 [+ or -] 0.2 (d,e) (24) Villanueva del Fresno 93.1 [+ or -] 0.6 (a,b) Fruiting bodies Composition in fresh weight Sampling sites Organic content (%) (1) Almendres 5.8 [+ or -] 0.3 (a) (2) Azaruja 6.7 [+ or -] 0.5 (a,b,c) (3) Baleizao 8.6 [+ or -] 0.4 (b,c,d) (4) Beja 8.4 [+ or -] 0.1 (a,b,c,d) (5) Cabeca Gorda 7.8 [+ or -] 0.7 (a,b,c,d) (6) Cabezas Rubias 6.8 [+ or -] 0.1 (a,b,c) (7) Evora 9.2 [+ or -] 1.4 (c,d) (8) Evoramonte 8.8 [+ or -] 0.7 (b,c,d) (9) [Her.sup.de] da Mitra 8.9 [+ or -] 0.3 (c,d) (10) Mertola 6.0 [+ or -] 0.3 (a,b) (11) Mina S. Domingos 9.8 [+ or -] 0.1 (d) (12) [M.sup.te] da Borralha 7.8 [+ or -] 1.5 (a,b,c,d) (13) [M.sup.te] Novo 7.6 [+ or -] 1.1 (a,b,c,d) (14) Montejuntos 6.7 [+ or -] 0.4 (a,b,c) (15) N. [S.sup.ra] Guadalupe 7.9 [+ or -] 1.3 (a,b,c,d) (16) N. [S.sup.ra] Machede 8.0 [+ or -] 1.4 (a,b,c,d) (17) Rosal de la Frontera 8.8 [+ or -] 1.6 (b,c,d) (18) [S.sup.to] Aleixo da Restauracao 8.1 [+ or -] 1.1 (a,b,c,d) (19) S. Miguel de Machede 6.5 [+ or -] 0.3 (a,b,c) (20) Serpa 5.8 [+ or -] 0.5 (a) (21) [V.sup.e] Rocins 6.4 [+ or -] 0.7 (a,b,c) (22) Valverde 7.1 [+ or -] 1.6 (a,b,c,d) (23) V. N. S. Bento 9.1 [+ or -] 0.2 (c,d) (24) Villanueva del Fresno 6.4 [+ or -] 0.5 (a,b,c) Fruiting bodies Sampling sites Minerals (%) (1) Almendres 0.6 [+ or -] 0.1 (a,b,c) (2) Azaruja 0.9 [+ or -] 0.0 (b,c) (3) Baleizao 0.7 [+ or -] 0.1 (a,b,c) (4) Beja 0.6 [+ or -] 0.0 (a,b,c) (5) Cabeca Gorda 0.5 [+ or -] 0.0 (a,b) (6) Cabezas Rubias 1.4 [+ or -] 0.1 (d) (7) Evora 0.7 [+ or -] 0.2 (a,b,c) (8) Evoramonte 0.8 [+ or -] 0.3 (a,b,c) (9) [Her.sup.de] da Mitra 0.6 [+ or -] 0.1 (a,b,c) (10) Mertola 0.8 [+ or -] 0,1 (a,b,c) (11) Mina S. Domingos 0.8 [+ or -] 0.1 (a,b,c) (12) [M.sup.te] da Borralha 0.7 [+ or -] 0.1 (a,b,c) (13) [M.sup.te] Novo 0.7 [+ or -] 0.1 (a,b,c) (14) Montejuntos 0.5 [+ or -] 0.1 (a,b) (15) N. [S.sup.ra] Guadalupe 0.7 [+ or -] 0.2 (a,b,c) (16) N. [S.sup.ra] Machede 0.7 [+ or -] 0.2 (a,b,c) (17) Rosal de la Frontera 0.8 [+ or -] 0.1 (a,b,c) (18) [S.sup.to] Aleixo da Restauracao 0.8 [+ or -] 0.1 (a,b,c) (19) S. Miguel de Machede 0.7 [+ or -] 0.1 (a,b,c) (20) Serpa 0.5 [+ or -] 0.0 (a) (21) [V.sup.e] Rocins 0.6 [+ or -] 0.1 (a,b,c) (22) Valverde 0.9 [+ or -] 0.0 (c) (23) V. N. S. Bento 0.8 [+ or -] 0.0 (a,b,c) (24) Villanueva del Fresno 0.5 [+ or -] 0.1 (a) Values of each determination represents mean [+ or -] SD (n = 9). Different letters following the values indicate significant differences (p < 0.05). Table 3: Ca, Mg, Na, and K mineral content of A. ponderosa fruiting bodies and corresponding soil substrates from different sampling sites Minerals (mg/Kg dry weight) Sampling site Sample Ca (1) Almendres FB 757 [+ or -] 156 (a) SS 106 [+ or -] 11 (a,b) (2) Azaruja FB 139 [+ or -] 13 (b) SS 102 [+ or -] 12 (a,b) (3) Baleizao FB 606 [+ or -] 61 (a) SS 162 [+ or -] 11 (c,d) (4) Beja FB 615 [+ or -] 1 (a) SS 189 [+ or -] 14 (d,e) (5) Cabeca Gorda FB 554 [+ or -] 21 (a) SS 108 [+ or -] 6 (a,b) (6) Cabezas Rubias FB 352 [+ or -] 2 (c) SS 118 [+ or -] 16 (a,b,c) (7) Evora FB 605 [+ or -] 1 (a) SS 91 [+ or -] 23 (a) (8) Evoramonte FB 733 [+ or -] 15 (a) SS 102 [+ or -] 8 (a,b) (9) [Her.sup.de] da FB 579 [+ or -] 111 (a) Mitra SS 159 [+ or -] 8 (c,d) (10) Mertola FB 370 [+ or -] 57 (a,b) SS 112 [+ or -] 8 (a,b,c) (11) Mina FB 582 [+ or -] 1 (a) S. Domingos SS 143 [+ or -] 25 (b,c,d) (12) [M.sup.te] da FB 448 [+ or -] 33 (a,b) Borralha SS 70 [+ or -] 14 (a) (13) [M.sup.te] Novo FB 436 [+ or -] 72 (a,b) SS 148 [+ or -] 19 (b,c,d) (14) Montejuntos FB 412 [+ or -] 50 (a,b) SS 224 [+ or -] 16 (e,f) (15) N. [S.sup.ra] FB 408 [+ or -] 11 (a,b) Guadalupe SS 148 [+ or -] 8 (b,c,d) (16) N. [S.sup.ra] de FB 632 [+ or -] 111 (a) Machede SS 143 [+ or -] 3 (b,c,d) (17) Rosal de la FB 584 [+ or -] 25 (a) Frontera SS 83 [+ or -] 9 (a) (18) [S.sup.to] Aleixo FB 366 [+ or -] 1 (a) da Restauracao SS 79 [+ or -] 8 (a) (19) S. Miguel de FB 649 [+ or -] 74 (a) Machede SS 338 [+ or -] 35 (a,b,c) (20) Serpa FB 698 [+ or -] 148 (a,b) SS 119 [+ or -] 16 (g) (21) [V.sup.e] Rocins FB 448 [+ or -] 269 (a,b) SS 113 [+ or -] 8 (a,b,c) (22) Valverde FB 521 [+ or -] 146 (a,b) SS 93 [+ or -] 23 (a) (23) V. N. S. Bento FB 599 [+ or -] 1 (a) SS 233 [+ or -] 11 (e,f) (24) Villanueva del FB 459 [+ or -] 13 (a,b) Fresno SS 240 [+ or -] 26 (f) Total FB 523 [+ or -] 143 SS 143 [+ or -] 63 Minerals (mg/Kg dry weight) Sampling site Sample K (1) Almendres FB 26677 [+ or -] 915 (a,b,c,d,e) SS 363 [+ or -] 9 (a,b) (2) Azaruja FB 4589 [+ or -] 103 (a) SS 981 [+ or -] 37 (g) (3) Baleizao FB 25758 [+ or -] 4728 (a,b,c,d,e) SS 1099 [+ or -] 24 (h) (4) Beja FB 6090 [+ or -] 34 (a,b) SS 619 [+ or -] 19 (d,e) (5) Cabeca Gorda FB 38652 [+ or -] 1607 (c,d,e) SS 384 [+ or -] 16 (a,b,c) (6) Cabezas Rubias FB 69565 [+ or -] 362 (f) SS 443 [+ or -] 9 (c) (7) Evora FB 34630 [+ or -] 186 (c,d,e) SS 651 [+ or -] 9 (e) (8) Evoramonte FB 25148 [+ or -] 4556 (a,b,c,d,e) SS 576 [+ or -] 16 (d) (9) [Her.sup.de] da FB 31852 [+ or -] 5364 (a,b,c,d,e) Mitra SS 229 [+ or -] 9 (j,k) (10) Mertola FB 18021 [+ or -] 1806 (a,b,c) SS 731 [+ or -] 19 (f) (11) Mina FB 33607 [+ or -] 173 (b,c,d,e) S. Domingos SS 256 [+ or -] 16 (y) (12) [M.sup.te] da FB 26099 [+ or -] 1618 (a,b,c,d,e) Borralha SS 155 [+ or -] 91 (13) [M.sup.te] Novo FB 25763 [+ or -] 1608 (a,b,c,d,e) SS 603 [+ or -] 56 (d,e) (14) Montejuntos FB 41285 [+ or -] 982 (c,d,e) SS 256 [+ or -] 16 (i,j) (15) N. [S.sup.ra] FB 34814 [+ or -] 1763 (c,d,e) Guadalupe SS 656 [+ or -] 16 (e) (16) N. [S.sup.ra] de FB 24717 [+ or -] 1881 (a,b,c,d,e) Machede SS 912 [+ or -] 48 (g) (17) Rosal de la FB 51996 [+ or -] 2660 (e,f) Frontera SS 160 [+ or -] 16 (k,l) (18) [S.sup.to] Aleixo FB 18586 [+ or -] 106 (d,e,f) da Restauracao SS 773 [+ or -] 24 (f) (19) S. Miguel de FB 45011 [+ or -] 1152 (c,d,e,f) Machede SS 315 [+ or -] 9 (k,l) (20) Serpa FB 47715 [+ or -] 5220 (a,b,c) SS 171 [+ or -] 9 (a,l) (21) [V.sup.e] Rocins FB 21788 [+ or -] 1237 (a,b,c,d) SS 320 [+ or -] 16 (a,l) (22) Valverde FB 27256 [+ or -] 2180 (a,b,c,d,e) SS 405 [+ or -] 24 (b,c) (23) V. N. S. Bento FB 6228 [+ or -] 30 (a,b) SS 192 [+ or -] 16 (j,k,l) (24) Villanueva del FB 25713 [+ or -] 5847 (a,b,c,d,e) Fresno SS 368 [+ or -] 16 (a,b) Total FB 29648 [+ or -] 14908 SS 484 [+ or -] 273 Minerals (mg/Kg dry weight) Sampling site Sample Mg (1) Almendres FB 774 [+ or -] 130 (a,b,c) SS 286 [+ or -] 14 (a,b,c,d) (2) Azaruja FB 194 [+ or -] 10 (a) SS 324 [+ or -] 29 (a,b) (3) Baleizao FB 856 [+ or -] 107 (a,b,c,d) SS 312 [+ or -] 38 (a,b) (4) Beja FB 734 [+ or -] 1 (a,b,c) SS 277 [+ or -] 33 (a,b,c,d,e) (5) Cabeca Gorda FB 848 [+ or -] 159 (a,b,c) SS 186 [+ or -] 8 (e,f,g) (6) Cabezas Rubias FB 1265 [+ or -] 1 (c,d) SS 277 [+ or -] 19 (a,b,c,d,e) (7) Evora FB 713 [+ or -] 1 (a,b,c) SS 171 [+ or -] 25 (f,g) (8) Evoramonte FB 760 [+ or -] 101 (a,b,c) SS 156 [+ or -] 11 (g) (9) [Her.sup.de] da FB 685 [+ or -] 89 (a,b,c) Mitra SS 298 [+ or -] 29 (a,b,c) (10) Mertola FB 658 [+ or -] 33 (a,b,c) SS 193 [+ or -] 18 (d,e,f,g) (11) Mina FB 737 [+ or -] 1 (a,b,c) S. Domingos SS 365 [+ or -] 43 (a) (12) [M.sup.te] da FB 696 [+ or -] 29 (a,b,c) Borralha SS 172 [+ or -] 23 (f,g) (13) [M.sup.te] Novo FB 562 [+ or -] 114 (a,b) SS 217 [+ or -] 34 (c,d,e,f,g) (14) Montejuntos FB 742 [+ or -] 53 (a,b,c) SS 910 [+ or -] 25 (j) (15) N. [S.sup.ra] FB 930 [+ or -] 158 (b,c,d) Guadalupe SS 255 [+ or -] 14 (b,c,d,e,f) (16) N. [S.sup.ra] de FB 843 [+ or -] 120 (a,b,c) Machede SS 804 [+ or -] 48 (i) (17) Rosal de la FB 1540 [+ or -] 77 (d) Frontera SS 365 [+ or -] 11 (a) (18) [S.sup.to] Aleixo FB 481 [+ or -] 1 (a,b,c) da Restauracao SS 477 [+ or -] 14 (h) (19) S. Miguel de FB 549 [+ or -] 140 (a,b) Machede SS 1466 [+ or -] 68 (a,b,c,d,e) (20) Serpa FB 736 [+ or -] 86 (a,b) SS 272 [+ or -] 15 (k) (21) [V.sup.e] Rocins FB 418 [+ or -] 203 (a,b) SS 284 [+ or -] 14 (a,b,c,d) (22) Valverde FB 586 [+ or -] 35 (a,b,c) SS 265 [+ or -] 41 (b,c,d,e,f) (23) V. N. S. Bento FB 657 [+ or -] 1 (a,b,c) SS 536 [+ or -] 37 (h) (24) Villanueva del FB 738 [+ or -] 49 (a,b,c) Fresno SS 267 [+ or -] 27 (b,c,d,e) Total FB 738 [+ or -] 261 SS 381 [+ or -] 296 Minerals (mg/Kg dry weight) Sampling site Sample Na (1) Almendres FB 1408 [+ or -] 146 (a) SS 70 [+ or -] 1 (a,b,c,d) (2) Azaruja FB 216 [+ or -] 135 (f) SS 75 [+ or -] 4 (a,b,h,i) (3) Baleizao FB 2249 [+ or -] 231 (g,h) SS 109 [+ or -] 4 (k) (4) Beja FB 1540 [+ or -] 17 (a,g) SS 69 [+ or -] 2 (a,b,c,d,e) (5) Cabeca Gorda FB 889 [+ or -] 38 (a,b,c,d,e,f) SS 69 [+ or -] 5 (a,b,c,d,e) (6) Cabezas Rubias FB 2645 [+ or -] 18 (h) SS 62 [+ or -] 2 (c,d,e,f) (7) Evora FB 1241 [+ or -] 16 (a,b) SS 52 [+ or -] 3 (f,g) (8) Evoramonte FB 614 [+ or -] 131 (b,c,d,e,f) SS 51 [+ or -] 2 (g) (9) [Her.sup.de] da FB 930 [+ or -] 58 (a,b,c,d,e,f) Mitra SS 51 [+ or -] 3 (g) (10) Mertola FB 484 [+ or -] 171 (c,d,e,f) SS 82 [+ or -] 2h' (i,j) (11) Mina FB 1097 [+ or -] 14 (a,b,c,d) S. Domingos SS 59 [+ or -] 5 (e,f,g) (12) [M.sup.te] da FB 368 [+ or -] 70 (e,f) Borralha SS 67 [+ or -] 5 (b,c,d,e) (13) [M.sup.te] Novo FB 379 [+ or -] 25 (e,f) SS 53 [+ or -] 4 (f,g) (14) Montejuntos FB 1146 [+ or -] 304 (a,b,c) SS 85 [+ or -] 2 (i,j) (15) N. [S.sup.ra] FB 551 [+ or -] 52 (b,c,d,e,f) Guadalupe SS 73 [+ or -] 1 (a,b,h) (16) N. [S.sup.ra] de FB 2185 [+ or -] 438 (g,h) Machede SS 80 [+ or -] 2 (a,h,i,j) (17) Rosal de la FB 964 [+ or -] 453 (a,b,c,d,e) Frontera SS 80 [+ or -] 1 (a,h,i,j) (18) [S.sup.to] Aleixo FB 1098 [+ or -] 103 (a,b,c,d) da Restauracao SS 70 [+ or -] 2 (a,b,c) (19) S. Miguel de FB 897 [+ or -] 11 (a,b,c,d,e,f) Machede SS 158 [+ or -] 5 (c,d,e,f,g) (20) Serpa FB 1078 [+ or -] 174 (a,b,c,d,e) SS 60 [+ or -] 5 (l) (21) [V.sup.e] Rocins FB 419 [+ or -] 212 (d,e,f) SS 86 [+ or -] 2 (j) (22) Valverde FB 895 [+ or -] 65 (a,b,c,d,e,f) SS 111 [+ or -] 3 (k) (23) V. N. S. Bento FB 1467 [+ or -] 15 (a) SS 60 [+ or -] 2 (d,e,f,g) (24) Villanueva del FB 1451 [+ or -] 147 (a) Fresno SS 78 [+ or -] 4 (a,h,i,j) Total FB 1092 [+ or -] 620 SS 75 [+ or -] 24 FB, fruiting bodies; SS, soil substrate. Mean values (n = 9) [+ or -] SD. Different letters for each element indicate significant differences with the confidence level of p < 0.05 (ANOVA, Tukey's test). Table 4: Al, Cu, Fe, and P mineral content of A. ponderosa fruiting bodies and corresponding soil substrates from different sampling sites. Minerals (mg/Kg dry weight) Sampling site Sample Al (1) Almendres FB 349 [+ or -] 124 (b,c,d,e,f) SS 277 [+ or -] 8 (a,b) (2) Azaruja FB 58 [+ or -] 8 (a) SS 243 [+ or -] 30 (a) (3) Baleizao FB 357 [+ or -] 29 (b,c,d,e,f) SS 397 [+ or -] 4 (c,d,e) (4) Beja FB 449 [+ or -] 13 (d,e,f,g) SS 254 [+ or -] 15 (a) (5) Cabeca Gorda FB 151 [+ or -] 25 (a,b) SS 196 [+ or -] 4 (k) (6) Cabezas Rubias FB 932 [+ or -] 77 (h) SS 375 [+ or -] 8 (c,d) (7) Evora FB 208 [+ or -] 11 (a,b,c,d) SS 368 [+ or -] 18 (c) (8) Evoramonte FB 423 [+ or -] 49 (c,d,e,f,g) SS 311 [+ or -] 6 (b) (9) [Her.sup.de] da Mitra FB 373 [+ or -] 26 (b,c,d,e,f) SS 157 [+ or -] 6 (1) (10) Mertola FB 333 [+ or -] 36 (b,c,d,e) SS 160 [+ or -] 81 (11) Mina S. Domingos FB 299 [+ or -] 14 (a,b,c,d,e) SS 417 [+ or -] 6 (e,f) (12) [M.sup.te] da Borralha FB 209 [+ or -] 42 (a,b,c,d) SS 159 [+ or -] 6 (1) (13) [M.sup.te] Novo FB 423 [+ or -] 59 (c,d,e,f,g) SS 300 [+ or -] 15 (b) (14) Montejuntos FB 545 [+ or -] 99 (e,f,g) SS 813 [+ or -] 11 (j) (15) N. [S.sup.ra] Guadalupe FB 209 [+ or -] 73 (a,b,c,d) SS 200 [+ or -] 6 (k) (16) N. [S.sup.ra] FB 313 [+ or -] 47 (a,b,c,d,e) de Machede SS 632 [+ or -] 19 (1) (17) Rosal de la Frontera FB 659 [+ or -] 36 (g) SS 381 [+ or -] 4 (c,d) (18) [S.sup.to] Aleixo da FB 65 [+ or -] 12 (d,e,f,g) Restauracao SS 449 [+ or -] 16 (f,g) (19) S. Miguel de Machede FB 610 [+ or -] 183 (f,g) SS 497 [+ or -] 6 (c,d) (20) Serpa FB 453 [+ or -] 66 (a) SS 378 [+ or -] 4 (h) (21) [V.sup.e] Rocins FB 181 [+ or -] 24 (a,b,c) SS 391 [+ or -] 9 (c,d,e) (22) Valverde FB 183 [+ or -] 54 (a,b,c) SS 453 [+ or -] 6 (g) (23) V. N. S. Bento FB 303 [+ or -] 7 (a,b,c,d,e) SS 409 [+ or -] 6 (d,e) (24) Villanueva del Fresno FB 602 [+ or -] 66 (f,g) SS 494 [+ or -] 4 (h) Total FB 362 [+ or -] 204 SS 363 [+ or -] 155 Minerals (mg/Kg dry weight) Sampling site Sample Cu (1) Almendres FB 80 [+ or -] 1 (a,b) SS 1 [+ or -] 0 (a) (2) Azaruja FB 30 [+ or -] 2 (a) SS 2 [+ or -] 0 (c) (3) Baleizao FB 356 [+ or -] 37 (a,b,c) SS 7 [+ or -] 0 (k) (4) Beja FB 373 [+ or -] 1 (b,c) SS 9 [+ or -] 1 (1) (5) Cabeca Gorda FB 161 [+ or -] 10 (a,b) SS 1 [+ or -] 0 (a) (6) Cabezas Rubias FB 140 [+ or -] 1 (a,b) SS 5 [+ or -] 0 (g) (7) Evora FB 198 [+ or -] 1 (a,b) SS 2 [+ or -] 0 (b,c) (8) Evoramonte FB 124 [+ or -] 20 (a,b) SS 2 [+ or -] 0 (c,d) (9) [Her.sup.de] da Mitra FB 193 [+ or -] 19 (a,b) SS 10 [+ or -] 0 (m) (10) Mertola FB 43 [+ or -] 15 (a,b) SS 5 [+ or -] 0 (f,g) (11) Mina S. Domingos FB 334 [+ or -] 1 (a,b,c) SS 3 [+ or -] 0 (d,e) (12) [M.sup.te] da Borralha FB 232 [+ or -] 63 (a,b) SS 2 [+ or -] 0 (c) (13) [M.sup.te] Novo FB 121 [+ or -] 16 (a,b) SS 3 [+ or -] 0 (c,d) (14) Montejuntos FB 170 [+ or -] 21 (a,b) SS 7 [+ or -] 0 (j,k) (15) N. [S.sup.ra] Guadalupe FB 264 [+ or -] 23 (a,b,c) SS 8 [+ or -] 0 (1) (16) N. [S.sup.ra] FB 148 [+ or -] 26 (a,b) de Machede SS 4 [+ or -] 0 (e,f) (17) Rosal de la Frontera FB 584 [+ or -] 51 (c) SS 9 [+ or -] 0 (1) (18) [S.sup.to] Aleixo da FB 129 [+ or -] 1 (a,b) Restauracao SS 6 [+ or -] 0 (g,h,i) (19) S. Miguel de Machede FB 207 [+ or -] 39 (a,b) SS 5 [+ or -] 0 (g,h) (20) Serpa FB 143 [+ or -] 14 (a,b) SS 5 [+ or -] 0 (f,g) (21) [V.sup.e] Rocins FB 84 [+ or -] 7 (a,b) SS 9 [+ or -] 0 (1) (22) Valverde FB 62 [+ or -] 3 (a,b) SS 1 [+ or -] 0 (a,b) (23) V. N. S. Bento FB 172 [+ or -] 1 (a,b) SS 6 [+ or -] 0 (h,i,j) (24) Villanueva del Fresno FB 100 [+ or -] 9 (a,b) SS 6 [+ or -] 0 (i,j) Total FB 185 [+ or -] 125 SS 5 [+ or -] 3 Minerals (mg/Kg dry weight) Sampling site Sample Fe (1) Almendres FB 66 [+ or -] 14 (a,b,c) SS 1547 [+ or -] 92 (a) (2) Azaruja FB 18 [+ or -] 4 (a) SS 2240 [+ or -] 160 (b) (3) Baleizao FB 27 [+ or -] 8 (a) SS 3093 [+ or -] 92 (d,e,f) (4) Beja FB 227 [+ or -] 1 (f,g) SS 4107 [+ or -] 92 (i,j) (5) Cabeca Gorda FB 51 [+ or -] 12 (a,b,c) SS 5067 [+ or -] 244 (k) (6) Cabezas Rubias FB 193 [+ or -] 1 (e,f) SS 3520 [+ or -] 160 (e,f,g,h) (7) Evora FB 292 [+ or -] 1 (g,h) SS 1653 [+ or -] 92 (a) (8) Evoramonte FB 62 [+ or -] 7 (a,b,c) SS 2400 [+ or -] 160 (b,c) (9) [Her.sup.de] da Mitra FB 35 [+ or -] 10 (a,b) SS 4747 [+ or -] 92 (k) (10) Mertola FB 22 [+ or -] 3 (a) SS 4853 [+ or -] 244 (k) (11) Mina S. Domingos FB 62 [+ or -] 1 (a,b,c) SS 3573 [+ or -] 92 (f,g,h) (12) [M.sup.te] da Borralha FB 41 [+ or -] 38 (a,b) SS 3840 [+ or -] 160 (h,i) (13) [M.sup.te] Novo FB 29.3 [+ or -] 1 (a) SS 1653 [+ or -] 244 (a) (14) Montejuntos FB 62 [+ or -] 10 (a,b,c) SS 8099 [+ or -] 251 (1) (15) N. [S.sup.ra] Guadalupe FB 110 [+ or -] 27 (b,c,d) SS 4960 [+ or -] 160 (k) (16) N. [S.sup.ra] FB 48 [+ or -] 13 (a,b,c) de Machede SS 3738 [+ or -] 258 (g,h,i) (17) Rosal de la Frontera FB 119 [+ or -] 97 (c,d,e) SS 3360 [+ or -] 160 (e,f,g,h) (18) [S.sup.to] Aleixo da FB 51 [+ or -] 1 (a,b,c) Restauracao SS 2827 [+ or -] 92 (c,d) (19) S. Miguel de Machede FB 311 [+ or -] 10 (h) SS 9040 [+ or -] 139 (d,e,f,g) (20) Serpa FB 43 [+ or -] 18 (a,b,c) SS 3253 [+ or -] 92 (m) (21) [V.sup.e] Rocins FB 36 [+ or -] 24 (a,b) SS 3040 [+ or -] 160 (d,e) (22) Valverde FB 57 [+ or -] 21 (a,b,c) SS 1440 [+ or -] 160 (a) (23) V. N. S. Bento FB 182 [+ or -] 1 (d,e,f) SS 4587 [+ or -] 244 (j,k) (24) Villanueva del Fresno FB 53 [+ or -] 17 (a,b,c) SS 2347 [+ or -] 92 (b,c) Total FB 92 [+ or -] 85 SS 3708 [+ or -] 1870 Minerals (mg/Kg dry weight) Sampling site Sample P (1) Almendres FB 319 [+ or -] 37 (a,b,c,d,e) SS 72 [+ or -] 2 (a,b) (2) Azaruja FB 44 [+ or -] 18 (h,i) SS 74 [+ or -] 4 (a,b) (3) Baleizao FB 525 [+ or -] 62 (j,k) SS 156 [+ or -] 4 (g) (4) Beja FB 212 [+ or -] 1 (d,e,f,g) SS 133 [+ or -] 8 (f) (5) Cabeca Gorda FB 447 [+ or -] 2 (a,j) SS 130 [+ or -] 3 (e,f) (6) Cabezas Rubias FB 73 [+ or -] 1 (g,h,i) SS 93 [+ or -] 4 (c) (7) Evora FB 201 [+ or -] 1 (d,e,f,g,h) SS 82 [+ or -] 5 (b,c) (8) Evoramonte FB 469 [+ or -] 83 (a,j) SS 94 [+ or -] 1 (c) (9) [Her.sup.de] da Mitra FB 277 [+ or -] 90 (b,c,d,e,f) SS 115 [+ or -] 3 (d,e) (10) Mertola FB 61 [+ or -] 21 (g,h,i) SS 119 [+ or -] 2 (d,e,f) (11) Mina S. Domingos FB 149 [+ or -] 1 (f,g,h,i) SS 74 [+ or -] 2 (a,b) (12) [M.sup.te] da Borralha FB 417 [+ or -] 65 (a,b,c,j) SS 75 [+ or -] 5 (a,b) (13) [M.sup.te] Novo FB 316 [+ or -] 76 (a,b,c,d,e,f) SS 84 [+ or -] 4 (b,c) (14) Montejuntos FB 442 [+ or -] 2 (a,b,j) SS 294 [+ or -] 11 (i) (15) N. [S.sup.ra] Guadalupe FB 344 [+ or -] 74 (a,b,c,d) SS 131 [+ or -] 5 (e,f) (16) N. [S.sup.ra] FB 542 [+ or -] 48 (j,k) de Machede SS 78 [+ or -] 1 (a,b,c) (17) Rosal de la Frontera FB 641 [+ or -] 98 (k) SS 154 [+ or -] 4 (g) (18) [S.sup.to] Aleixo da FB 34 [+ or -] 1 (a,j) Restauracao SS 185 [+ or -] 1 (h) (19) S. Miguel de Machede FB 270 [+ or -] 60 (c,d,ef) SS 111 [+ or -]2 (h) (20) Serpa FB 460 [+ or -] 16 (i) SS 179 [+ or -] 7 (d) (21) [V.sup.e] Rocins FB 165 [+ or -] 85 (e,f,g,h,i) SS 75 [+ or -] 5 (a,b) (22) Valverde FB 152 [+ or -] 34 (f,g,h,i) SS 65 [+ or -] 2 (a) (23) V. N. S. Bento FB 197 [+ or -] 1 (d,e,f,g,h,i) SS 116 [+ or -] 5 (d,e) (24) Villanueva del Fresno FB 310 [+ or -] 83 (a,b,c,d,e,f) SS 179 [+ or -] 12 (h) Total FB 294 [+ or -] 171 SS 120 [+ or -] 53 FB, fruiting bodies; SS, soil substrate. Mean values (n = 9) [+ or -] SD. Different letters for each element indicate significant differences with the confidence level of p < 0.05 (ANOVA, Tukey's test). Table 5: Ag, Ba, Cd, and Cr mineral content of A. ponderosa fruiting bodies and corresponding soil substrates from different sampling sites. Minerals (mg/kg dry weight) Sampling site Sample Ag (1) Almendres FB 2.6 [+ or -] 0.5 (a,b,c,d,e) SS 0.1 [+ or -] 0.0 (a) (2) Azaruja FB 6.6 [+ or -] 2.2 (f) SS 0.1 [+ or -] 0.0 (a, b,c,d) (3) Baleizao FB 5.1 [+ or -] 1.8 (a, b,c,d) SS 0.1 [+ or -] 0.0 (a, b,c,d) (4) Beja FB 1.1 [+ or -] 0.2 (a,b) SS 0.1 [+ or -] 0.0 (a, b,c,d,e,f) (5) Cabeca Gorda FB 2.1 [+ or -] 0.7 (a, b,c) SS 0.2 [+ or -] 0.0 (b,c,d,e,f) (6) Cabezas Rubias FB 1.5 [+ or -] 0.2 (a, b,c) SS 0.2 [+ or -] 0.0 (c,d,e,f,g) (7) Evora FB 0.5 [+ or -] 0.3 (a, b,c,d) SS 0.2 [+ or -] 0.0 (g,h,i) (8) Evoramonte FB 1.0 [+ or -] 0.1 (d,e,f) SS 0.1 [+ or -] 0.0 (a, b,c,d,e,f) (9) [Her.sup.de] da Mitra FB 0.7 [+ or -] 0.1 (a, b,c,d) SS 0.2 [+ or -] 0.0 (e,f,g,h) (10) Mertola FB 4.3 [+ or -] 0.8 (a,b) SS 0.1 [+ or -] 0.0 (a,b) (11) Mina S. Domingos FB 0.6 [+ or -] 0.1 (a, b,c) SS 0.3 [+ or -] 0.0 (i) (12) [M.sup.te] da FB 1.5 [+ or -] 0.1 (a, b,c) Borralha SS 0.2 [+ or -] 0.0 (d,e,f,g) (13) [M.sup.te] Novo FB 0.6 [+ or -] 0.1 (a) SS 0.1 [+ or -] 0.0 (a, b,c) (14) Montejuntos FB 1.5 [+ or -] 0.2 (a, b,c) SS 0.2 [+ or -] 0.1 (h,i) (15) N. [S.sup.ra] FB 2.5 [+ or -] 0.3 (e,f) Guadalupe SS 0.2 [+ or -] 0.0 (b,c,d,e,f,g) (16) N. [S.sup.ra] FB 0.4 [+ or -] 0.2 (a,b,c,d,e) Machede SS 0.4 [+ or -] 0.0 (j) (17) Rosal de la Frontera FB 1.6 [+ or -] 0.3 (c,d,e) SS 0.2 [+ or -] 0.0 (c,d,e,f,g) (18) [S.sup.to] Aleixo da FB 1.3 [+ or -] 0.3 (a, b,c) Restauracao SS 0.2 [+ or -] 0.0 (e,f,g,h) (19) S. Miguel de Machede FB 2.6 [+ or -] 0.3 (b,c,d,e) SS 0.2 [+ or -] 0.0 (e,f,g) (20) Serpa FB 1.7 [+ or -] 0.3 (a, b,c) SS 0.2 [+ or -] 0.0 (f,g,h) (21) [V.sup.e] Rocins FB 3.3 [+ or -] 2.2 (a) SS 0.1 [+ or -] 0.0 (a,b,c,d,e) (22) Valverde FB 1.8 [+ or -] 0.6 (a,b) SS 0.2 [+ or -] 0.0 (c,d,e,f,g) (23) V. N. S. Bento FB 0.4 [+ or -] 0.3 (a, b,c) SS 0.1 [+ or -] 0.0 (a, b,c,d,e,f) (24) Villanueva del FB 3.0 [+ or -] 0.3 (a) Fresno SS 0.1 [+ or -] 0.0 (a,b,c,d,e) Total FB 2.0 [+ or -] 1.6 SS 0.2 [+ or -] 0.1 Minerals (mg/kg dry weight) Sampling site Sample Ba (1) Almendres FB 2.9 [+ or -] 1.1 (a) SS 2.0 [+ or -] 0.3 (a,b) (2) Azaruja FB 0.9 [+ or -] 0.2 (d,e,f,g) SS 1.6 [+ or -] 0.2 (a) (3) Baleizao FB 0.6 [+ or -] 0.3 (d,e,f,g) SS 5.3 [+ or -] 0.9 (i) (4) Beja FB 0.8 [+ or -] 0.0 (b,c,d,e,f,g) SS 2.6 [+ or -] 0.7 (a, b,c,d) (5) Cabeca Gorda FB 0.3 [+ or -] 0.0 (d,e,f,g) SS 2.3 [+ or -] 0.1 (a, b,c,d) (6) Cabezas Rubias FB 2.0 [+ or -] 0.3 (d,e,f,g) SS 2.6 [+ or -] 0.4 (a, b,c,d) (7) Evora FB 0.8 [+ or -] 0.4 (f,g) SS 4.3 [+ or -] 1.1 (f,g,h,i) (8) Evoramonte FB 0.9 [+ or -] 0.1 (b,c,d,e) SS 2.8 [+ or -] 0.1 (a,b,c,d,e) (9) [Her.sup.de] da Mitra FB 1.2 [+ or -] 0.1 (g) SS 2.3 [+ or -] 0.1 (a, b,c) (10) Mertola FB 1.5 [+ or -] 0.2 (b,c,d,e,f) SS 3.0 [+ or -] 0.4 (b,c,d,e,f) (11) Mina S. Domingos FB 0.6 [+ or -] 0.0 (c,d,e,f,g) SS 1.9 [+ or -] 0.0 (a,b) (12) [M.sup.te] da FB 0.9 [+ or -] 0.1 (f,g) Borralha SS 2.3 [+ or -] 0.0 (a, b,c,d) (13) [M.sup.te] Novo FB 1.3 [+ or -] 0.2 (e,f,g) SS 3.4 [+ or -] 0.2 (c,d,e,f,g) (14) Montejuntos FB 1.1 [+ or -] 0.1 (b,c,d) SS 3.6 [+ or -] 0.3 (d,e,f,g,h) (15) N. [S.sup.ra] FB 0.7 [+ or -] 0.2 (d,e,f,g) Guadalupe SS 2.4 [+ or -] 0.1 (a, b,c,d) (16) N. [S.sup.ra] FB 0.6 [+ or -] 0.1 (b,c,d,e,f,g) Machede SS 4.0 [+ or -] 0.2 (e,f,g,h,i) (17) Rosal de la Frontera FB 1.5 [+ or -] 0.1 (b,c,d,e,f) SS 2.3 [+ or -] 0.1 (a, b,c,d) (18) [S.sup.to] Aleixo da FB 1.1 [+ or -] 0.1 (d,e,f,g) Restauracao SS 2.8 [+ or -] 0.2 (a,b,c,d,e) (19) S. Miguel de Machede FB 1.3 [+ or -] 0.3 (b,c,d,e,f,g) SS 3.4 [+ or -] 0.1 (c,d,e,f,g) (20) Serpa FB 0.4 [+ or -] 0.1 (a, b,c) SS 2.4 [+ or -] 0.3 (a, b,c,d) (21) [V.sup.e] Rocins FB 1.3 [+ or -] 0.5 (d,e,f,g) SS 4.8 [+ or -] 0.2 (h,i) (22) Valverde FB 0.5 [+ or -] 0.0 (d,e,f,g) SS 1.7 [+ or -] 0.3 (a,b) (23) V. N. S. Bento FB 2.1 [+ or -] 0.2 (c,d,e,f,g) SS 4.5 [+ or -] 0.4 (g,h,i) (24) Villanueva del FB 1.1 [+ or -] 0.2 (a,b) Fresno SS 11.3 [+ or -] 1.0 (j) Total FB 1.1 [+ or -] 0.6 SS 3.3 [+ or -] 2.0 Minerals (mg/kg dry weight) Sampling site Sample Cd (1) Almendres FB 2.2 [+ or -] 0.8 (a) SS 0.3 [+ or -] 0.0 (a,b) (2) Azaruja FB 0.3 [+ or -] 0.0 (b) SS 0.3 [+ or -] 0.1 (a) (3) Baleizao FB 1.1 [+ or -] 0.3 (b,c,d,e) SS 0.2 [+ or -] 0.0 (e) (4) Beja FB 0.4 [+ or -] 0.0 (b,c,d,e) SS 0.1 [+ or -] 0.0 (f) (5) Cabeca Gorda FB 0.7 [+ or -] 0.1 (c,d,e) SS 0.2 [+ or -] 0.0 (c,d,e) (6) Cabezas Rubias FB 0.8 [+ or -] 0.1 (c,d,e) SS 0.1 [+ or -] 0.0 (e,f) (7) Evora FB 0.4 [+ or -] 0.3 (b,c,d,e) SS 0.1 [+ or -] 0.0 (e,f) (8) Evoramonte FB 1.2 [+ or -] 0.2 (b,c,d,e) SS 0.1 [+ or -] 0.0 (e,f) (9) [Her.sup.de] da Mitra FB 1.0 [+ or -] 0.0 (b,c,d,e) SS 0.1 [+ or -] 0.0 (e,f) (10) Mertola FB 1.0 [+ or -] 0.3 (b,c,d) SS 0.1 [+ or -] 0.0 (e,f) (11) Mina S. Domingos FB 1.4 [+ or -] 0.2 (d,e) SS 0.1 [+ or -] 0.0 (e,f) (12) [M.sup.te] da FB 1.1 [+ or -] 0.2 (b,c) Borralha SS 0.1 [+ or -] 0.0 (e,f) (13) [M.sup.te] Novo FB 0.6 [+ or -] 0.1 (b,c,d,e) SS 0.2 [+ or -] 0.0 (b,c,d,e) (14) Montejuntos FB 1.3 [+ or -] 0.1 (b,c,d,e) SS 0.1 [+ or -] 0.0 (e,f) (15) N. [S.sup.ra] FB 0.9 [+ or -] 0.2 (b,c,d,e) Guadalupe SS 0.2 [+ or -] 0.0 (c,d,e) (16) N. [S.sup.ra] FB 0.7 [+ or -] 0.1 (f) Machede SS 0.1 [+ or -] 0.0 (e,f) (17) Rosal de la Frontera FB 1.0 [+ or -] 0.1 (b,c) SS 0.1 [+ or -] 0.0 (e,f) (18) [S.sup.to] Aleixo da FB 0.7 [+ or -] 0.1 (b,c) Restauracao SS 0.3 [+ or -] 0.0 (a, b,c,d) (19) S. Miguel de Machede FB 3.9 [+ or -] 0.5 (b,c,d,e) SS 0.1 [+ or -] 0.0 (e,f) (20) Serpa FB 0.4 [+ or -] 0.1 (b,c,d,e) SS 0.0 [+ or -] 0.0 (f) (21) [V.sup.e] Rocins FB 0.5 [+ or -] 0.2 (b,c) SS 0.2 [+ or -] 0.0 (d,e) (22) Valverde FB 1.0 [+ or -] 0.1 (e) SS 0.2 [+ or -] 0.0 (b,c,d,e) (23) V. N. S. Bento FB 0.7 [+ or -] 0.1 (b,c,d,e) SS 0.3 [+ or -] 0.1 (a, b,c) (24) Villanueva del FB 0.8 [+ or -] 0.3 (b,c,d,e) Fresno SS 0.3 [+ or -] 0.0 (a, b,c) Total FB 1.0 [+ or -] 0.7 SS 0.2 [+ or -] 0.1 Minerals (mg/kg dry weight) Sampling site Sample Cr (1) Almendres FB 1.3 [+ or -] 0.6 (a, b,c) SS 1.0 [+ or -] 0.2 (a) (2) Azaruja FB 0.6 [+ or -] 0.1 (c,d,e) SS 0.9 [+ or -] 0.1 (a) (3) Baleizao FB 1.0 [+ or -] 0.2 (d,e) SS 2.4 [+ or -] 0.1 (b,c,d) (4) Beja FB 0.8 [+ or -] 0.0 (a) SS 4.4 [+ or -] 0.2 (i,j) (5) Cabeca Gorda FB 0.8 [+ or -] 0.0 (b,c,d,e) SS 4.2 [+ or -] 0.0 (g,h,i,j) (6) Cabezas Rubias FB 0.9 [+ or -] 0.1 (f) SS 3.1 [+ or -] 0.5 (c,d,e,f,g,h) (7) Evora FB 0.9 [+ or -] 0.5 (f) SS 2.8 [+ or -] 0.5 (c,d,e,f) (8) Evoramonte FB 2.9 [+ or -] 0.1 (b,c,d,e) SS 2.6 [+ or -] 0.0 (c,d,e,f) (9) [Her.sup.de] da Mitra FB 1.8 [+ or -] 0.1 (b,c,d,e) SS 3.8 [+ or -] 0.1 (f,g,h,i,j) (10) Mertola FB 0.9 [+ or -] 0.3 (d,e) SS 3.0 [+ or -] 0.2 (c,d,e,f,g) (11) Mina S. Domingos FB 0.7 [+ or -] 0.1 (a,b,c,d,e) SS 5.1 [+ or -] 0.7 (j,k) (12) [M.sup.te] da FB 0.9 [+ or -] 0.1 (c,d,e) Borralha SS 3.7 [+ or -] 0.0 (d,e,f,g,h,i) (13) [M.sup.te] Novo FB 0.5 [+ or -] 0.1 (e) SS 2.6 [+ or -] 0.2 (c,d,e,f) (14) Montejuntos FB 1.0 [+ or -] 0.1 (a, b,c,d) SS 5.7 [+ or -] 0.2 (k) (15) N. [S.sup.ra] FB 0.5 [+ or -] 0.1 (a,b,c,d,e) Guadalupe SS 4.3 [+ or -] 0.1 (h,i,j) (16) N. [S.sup.ra] FB 0.4 [+ or -] 0.1 (b,c,d,e) Machede SS 3.8 [+ or -] 0.3 (e,f,g,h,i,j) (17) Rosal de la Frontera FB 1.2 [+ or -] 0.0 (a) SS 2.9 [+ or -] 0.2 (c,d,e,f) (18) [S.sup.to] Aleixo da FB 0.9 [+ or -] 0.0 (b,c,d,e) Restauracao SS 2.8 [+ or -] 0.9 (c,d,e,f) (19) S. Miguel de Machede FB 0.9 [+ or -] 0.1 (a,b) SS 2.3 [+ or -] 0.2 (b,c) (20) Serpa FB 0.6 [+ or -] 0.1 (b,c,d,e) SS 7.9 [+ or -] 0.4 (1) (21) [V.sup.e] Rocins FB 1.8 [+ or -] 0.6 (b,c,d,e) SS 2.5 [+ or -] 0.1 (b,c,d,e) (22) Valverde FB 2.9 [+ or -] 0.1 (b,c,d,e) SS 1.2 [+ or -] 0.1 (a,b) (23) V. N. S. Bento FB 2.8 [+ or -] 0.4 (b,c,d,e) SS 1.8 [+ or -] 1.3 (a, b,c) (24) Villanueva del FB 1.5 [+ or -] 0.4 (f) Fresno SS 4.9 [+ or -] 0.6 (i,j,k) Total FB 1.2 [+ or -] 0.7 SS 3.3 [+ or -] 1.6 FB, fruiting bodies; SS, soil substrate. Mean values (n = 9) [+ or -] SD. Different letters for each element indicate significant differences with the confidence level of p < 0.05 (ANOVA, Tukey's test). Table 6: Mn, Pb, and Zn mineral content of A. ponderosa fruiting bodies and corresponding soil substrates from different sampling sites. Minerals (mg/kg dry weight) Sample Mn (1) Almendres FB 28 [+ or -] 6 (a,b,c,d) SS 22 [+ or -] 1 (a) (2) Azaruja FB 6 [+ or -] 1 (a) SS 131 [+ or -] 9 (a,b) (3) Baleizao FB 91 [+ or -] 14 (g,h) SS 893 [+ or -] 17 (f,g) (4) Beja FB 84 [+ or -] 1 (f,g,h) SS 507 [+ or -] 45 (c) (5) Cabeca Gorda FB 66 [+ or -] 6 (c,d,e,f,g,h) SS 695 [+ or -] 62 (d,e) (6) Cabezas Rubias FB 81 [+ or -] 1 (e,f,g,h) SS 735 [+ or -] 30 (d,e,f) (7) Evora FB 59 [+ or -] 1 (b,c,d,e,f,g,h) SS 175 [+ or -] 3 (a,b) (8) Evoramonte FB 79 [+ or -] 11 (e,f,g,h) SS 212 [+ or -] 12 (b) (9) [Her.sup.de] da Mitra FB 47 [+ or -] 9 (a,b,c,d,e,f,g) SS 725 [+ or -] 17 (d,e) (10) Mertola FB 29 [+ or -] 6 (a,b,c,d) SS 725 [+ or -] 17 (d,e) (11) Mina S. Domingos FB 104 [+ or -] 1 (h) SS 290 [+ or -] 6 (b) (12) [M.sup.te] da Borralha FB 39 [+ or -] 16 (a,b,c,d,e,f) SS 199 [+ or -] 9 (b) (13) [M.sup.te] Novo FB 34 [+ or -] 4 (a,b,c,d) SS 139 [+ or -] 3 (a,b) (14) Montejuntos FB 49 [+ or -] 9 (a,b,c,d,e,f,g) SS 649 [+ or -] 27 (c,d,e) (15) N. [S.sup.ra] Guadalupe FB 38 [+ or -] 5 (a,b,c,d,e) SS 794 [+ or -] 232 (e,f) (16) N. [S.sup.ra] Machede FB 50 [+ or -] 13 (a,b,c,d,e,f,g) SS 123 [+ or -] 4 (a,b) (17) Rosal de la Frontera FB 90 [+ or -] 56 (g,h) SS 725 [+ or -] 17 (d,e) (18) [S.sup.to] Aleixo da FB 47 [+ or -] 15 (c,d,e,f,g,h) Restauracao SS 193 [+ or -] 7 (b) (19) S. Miguel de Machede FB 91 [+ or -] 1 (g,h) SS 576 [+ or -] 17 (g) (20) Serpa FB 69 [+ or -] 19 (a,b,c,d,e,f,g) SS 1002 [+ or -] 30 (c,d) (21) Ve Rocins FB 15 [+ or -] 10 (a,b) SS 893 [+ or -] 17 (f,g) (22) Valverde FB 26 [+ or -] 7 (a,b,c) SS 21 [+ or -] 1 (a) (23) V. N. S. Bento FB 72 [+ or -] 1 (d,e,f,g,h) SS 745 [+ or -] 45 (e,f) (24) Villanueva del Fresno FB 39 [+ or -] 6 (a,b,c,d,e,f) SS 1518 [+ or -] 45 (h) Total FB 56 [+ or -] 27 SS 529 [+ or -] 378 Minerals (mg/kg dry weight) Sample Pb (1) Almendres FB 0.7 [+ or -] 0.5 (a,b) SS 4.0 [+ or -] 0.4 (a) (2) Azaruja FB 0.4 [+ or -] 0.1 (a) SS 7.0 [+ or -] 1.0 (a,b,c,d,e) (3) Baleizao FB 1.7 [+ or -] 0.5 (c,d,e,f) SS 9.2 [+ or -] 1.1 (d,e,f) (4) Beja FB 2.8 [+ or -] 0.1 (a,b,c,d) SS 6.9 [+ or -] 0.6 (a,b,c,d,e) (5) Cabeca Gorda FB 1.9 [+ or -] 0.2 (c,d,e,f) SS 4.5 [+ or -] 0.2 (a,b) (6) Cabezas Rubias FB 5.1 [+ or -] 0.8 (h,i) SS 16.5 [+ or -] 0.6 (g) (7) Evora FB 1.9 [+ or -] 0.9 (i) SS 10.9 [+ or -] 0.2 (f) (8) Evoramonte FB 4.2 [+ or -] 0.2 (g,h,i) SS 7.4 [+ or -] 0.3 (a,b,c,d,e,f) (9) [Her.sup.de] da Mitra FB 1.4 [+ or -] 0.2 (b,c,d,e,f) SS 5.4 [+ or -] 0.3 (a,b,c) (10) Mertola FB 3.7 [+ or -] 0.9 (a,b,c,d,e) SS 8.0 [+ or -] 0.7 (b,c,d,e,f) (11) Mina S. Domingos FB 3.1 [+ or -] 0.7 (e,f,g,h) SS 10.3 [+ or -] 0.4 (e,f) (12) [M.sup.te] da Borralha FB 2.2 [+ or -] 0.3 (a,b,c) SS 5.4 [+ or -] 0.3 (a,b,c) (13) [M.sup.te] Novo FB 1.6 [+ or -] 0.3 (a) SS 8.2 [+ or -] 0.7 (c,d,e,f) (14) Montejuntos FB 3.0 [+ or -] 0.1 (e,f,g,h) SS 10.2 [+ or -] 1.5 (e,f) (15) N. [S.sup.ra] Guadalupe FB 2.1 [+ or -] 0.3 (a,b,c,d,e,f) SS 4.5 [+ or -] 0.2 (a,b) (16) N. [S.sup.ra] Machede FB 0.4 [+ or -] 0.1 (a,b,c) SS 8.4 [+ or -] 0.1 (c,d,e,f) (17) Rosal de la Frontera FB 3.0 [+ or -] 0.1 (c,d,e,f,g) SS 16.5 [+ or -] 0.6 (g) (18) [S.sup.to] Aleixo da FB 3.9 [+ or -] 0.3 (i) Restauracao SS 6.4 [+ or -] 0.9 (a,b,c,d) (19) S. Miguel de Machede FB 1.4 [+ or -] 0.1 (f,g,h) SS 5.8 [+ or -] 0.2 (a,b,c,d) (20) Serpa FB 1.0 [+ or -] 0.2 (d,e,f,g,h) SS 19.5 [+ or -] 3.7 (g) (21) Ve Rocins FB 2.3 [+ or -] 0.8 (b,c,d,e,f) SS 9.2 [+ or -] 1.1 (d,e,f) (22) Valverde FB 5.1 [+ or -] 0.2 (f,g,h) SS 4.4 [+ or -] 0.4 (a,b) (23) V. N. S. Bento FB 1.6 [+ or -] 0.1 (h,i) SS 8.4 [+ or -] 3.0 (c,d,e,f) (24) Villanueva del Fresno FB 3.1 [+ or -] 0.6 (a,b,c,d,e) SS 7.4 [+ or -] 0.5 (a,b,c,d,e,f) Total FB 2.4 [+ or -] 1.3 SS 8.5 [+ or -] 4.0 Minerals (mg/kg dry weight) Sample Zn (1) Almendres FB 59 [+ or -] 1 (a,b,c,d) SS 4 [+ or -] 0 (a,b) (2) Azaruja FB 16 [+ or -] 2 (a) SS 5 [+ or -] 1 (a,b,c) (3) Baleizao FB 97 [+ or -] 2 (c,d,e) SS 9 [+ or -] 0 (d) (4) Beja FB 104 [+ or -] 1 (d,e) SS 13 [+ or -] 0 (g) (5) Cabeca Gorda FB 81 [+ or -] 1 (b,c,d,e) SS 10 [+ or -] 0 (d) (6) Cabezas Rubias FB 132 [+ or -] 1 (e) SS 11 [+ or -] 1 (d,e) (7) Evora FB 75 [+ or -] 1 (b,c,d,e) SS 5 [+ or -] 1 (b,c) (8) Evoramonte FB 59 [+ or -] 7 (a,b,c,d) SS 6 [+ or -] 0 (c) (9) [Her.sup.de] da Mitra FB 61 [+ or -] 2 (a,b,c,d) SS 11 [+ or -] 0 (e,f) (10) Mertola FB 52 [+ or -] 8 (a,b,c,d) SS 15 [+ or -] 1 (h) (11) Mina S. Domingos FB 91 [+ or -] 1 (c,d,e) SS 4 [+ or -] 1 (a) (12) [M.sup.te] da Borralha FB 62 [+ or -] 4 (a,b,c,d) SS 10 [+ or -] 1 (d,e) (13) [M.sup.te] Novo FB 52 [+ or -] 4 (a,b,c,d) SS 5 [+ or -] 0 (a,b,c) (14) Montejuntos FB 60 [+ or -] 3 (a,b,c,d) SS 10 [+ or -] 0 (d,e) (15) N. [S.sup.ra] Guadalupe FB 63 [+ or -] 10 (a,b,c,d) SS 12 [+ or -] 0 (f,g) (16) N. [S.sup.ra] Machede FB 70 [+ or -] 2 (a,b,c,d) SS 9 [+ or -] 0 (d) (17) Rosal de la Frontera FB 95 [+ or -] 6 (c,d,e) SS 6 [+ or -] 0 (b,c) (18) [S.sup.to] Aleixo da FB 47 [+ or -] 1 (a,b,c,d) Restauracao SS 11 [+ or -] 0 (d,e) (19) S. Miguel de Machede FB 58 [+ or -] 8 (a,b,c,d) SS 9 [+ or -] 0 (d) (20) Serpa FB 61 [+ or -] 9 (a,b,c,d) SS 30 [+ or -] 1 (j) (21) Ve Rocins FB 31 [+ or -] 2 (a,b) SS 5 [+ or -] 1 (a,b,c) (22) Valverde FB 42 [+ or -] 2 (a,b,c) SS 5 [+ or -] 0 (a,b,c) (23) V. N. S. Bento FB 86 [+ or -] 1 (b,c,d,e) SS 27 [+ or -] 1 (I) (24) Villanueva del Fresno FB 68 [+ or -] 4 (a,b,c,d) SS 5 [+ or -] 1 (a,b,c) Total FB 68 [+ or -] 25 SS 10 [+ or -] 6 FB, fruiting bodies; SS, soil substrate. Mean values (n = 9) [+ or -] SD. Different letters for each element indicate significant differences with the confidence level of p < 0.05 (ANOVA, Tukey's test). Table 7: Bioconcentration factor (BCF) values for A. ponderosa fruiting bodies from different sampling sites. Sampling site Al Ca (1) Almendres 1.3 [+ or -] 0.4 7.1 [+ or -] 0.7 (2) Azaruja 0.2 [+ or -] 0.0 1.4 [+ or -] 0.0 (3) Baleizao 0.9 [+ or -] 0.1 3.7 [+ or -] 0.1 (4) Beja 1.8 [+ or -] 0.1 3.3 [+ or -] 0.2 (5) Cabeca Gorda 0.8 [+ or -] 0.1 5.1 [+ or -] 0.1 (6) Cabezas Rubias 2.5 [+ or -] 0.2 3.0 [+ or -] 0.4 (7) Evora 0.6 [+ or -] 0.0 7.0 [+ or -] 1.8 (8) Evoramonte 1.4 [+ or -] 0.1 7.2 [+ or -] 0.4 (9) [Her.sup.de] da Mitra 2.4 [+ or -] 0.1 3.6 [+ or -] 0.5 (10) Mertola 2.1 [+ or -] 0.1 3.3 [+ or -] 0.3 (11) Mina S. Domingos 0.7 [+ or -] 0.0 4.2 [+ or -] 0.7 (12) [M.sup.te] da Borralha 1.3 [+ or -] 0.2 6.5 [+ or -] 0.9 (13) [M.sup.te] Novo 1.4 [+ or -] 0.1 2.9 [+ or -] 0.1 (14) Montejuntos 0.7 [+ or -] 0.1 1.8 [+ or -] 0.1 (15) N. [S.sup.ra] Guadalupe 1.0 [+ or -] 0.3 2.8 [+ or -] 0.1 (16) N. [S.sup.ra] Machede 0.5 [+ or -] 0.1 4.4 [+ or -] 0.7 (17) Rosal de la Frontera 1.7 [+ or -] 0.1 7.1 [+ or -] 0.5 (18) [S.sup.to] Aleixo da Restauracao 0.1 [+ or -] 0.0 4.7 [+ or -] 0.5 (19) S. Miguel de Machede 1.2 [+ or -] 0.4 1.9 [+ or -] 0.0 (20) Serpa 1.2 [+ or -] 0.2 5.8 [+ or -] 0.5 (21) [V.sup.e] Rocins 0.5 [+ or -] 0.1 3.9 [+ or -] 2.1 (22) Valverde 0.4 [+ or -] 0.1 5.6 [+ or -] 0.2 (23) V. N. S. Bento 0.7 [+ or -] 0.0 2.6 [+ or -] 0.1 (24) Villanueva del Fresno 1.2 [+ or -] 0.1 1.9 [+ or -] 0.2 Sampling site Cu Fe (1) Almendres 123 [+ or -] 2 0.04 [+ or -] 0.01 (2) Azaruja 16 [+ or -] 1 0.01 [+ or -] 0.00 (3) Baleizao 48 [+ or -] 3 0.01 [+ or -] 0.00 (4) Beja 43 [+ or -] 2 0.06 [+ or -] 0.00 (5) Cabeca Gorda 248 [+ or -] 16 0.01 [+ or -] 0.00 (6) Cabezas Rubias 28 [+ or -] 1 0.05 [+ or -] 0.00 (7) Evora 122 [+ or -] 19 0.18 [+ or -] 0.01 (8) Evoramonte 52 [+ or -] 1 0.03 [+ or -] 0.00 (9) [Her.sup.de] da Mitra 20 [+ or -] 1 0.01 [+ or -] 0.00 (10) Mertola 9 [+ or -] 3 0.00 [+ or -] 0.00 (11) Mina S. Domingos 114 [+ or -] 10 0.02 [+ or -] 0.00 (12) [M.sup.te] da Borralha 119 [+ or -] 32 0.01 [+ or -] 0.01 (13) [M.sup.te] Novo 48 [+ or -] 2 0.02 [+ or -] 0.00 (14) Montejuntos 25 [+ or -] 1 0.01 [+ or -] 0.00 (15) N. [S.sup.ra] Guadalupe 31 [+ or -] 1 0.02 [+ or -] 0.00 (16) N. [S.sup.ra] Machede 39 [+ or -] 7 0.01 [+ or -] 0.00 (17) Rosal de la Frontera 68 [+ or -] 4 0.03 [+ or -] 0.03 (18) [S.sup.to] Aleixo da Restauracao 23 [+ or -] 1 0.02 [+ or -] 0.00 (19) S. Miguel de Machede 38 [+ or -] 4 0.03 [+ or -] 0.00 (20) Serpa 31 [+ or -] 1 0.01 [+ or -] 0.01 (21) [V.sup.e] Rocins 10 [+ or -] 1 0.01 [+ or -] 0.01 (22) Valverde 83 [+ or -] 24 0.04 [+ or -] 0.01 (23) V. N. S. Bento 28 [+ or -] 1 0.04 [+ or -] 0.00 (24) Villanueva del Fresno 16 [+ or -] 1 0.02 [+ or -] 0.01 Sampling site K Mg (1) Almendres 74 [+ or -] 1 2.7 [+ or -] 0.3 (2) Azaruja 5 [+ or -] 1 0.6 [+ or -] 0.0 (3) Baleizao 23 [+ or -] 4 2.7 [+ or -] 0.0 (4) Beja 10 [+ or -] 0 2.7 [+ or -] 0.3 (5) Cabeca Gorda 101 [+ or -] 0 4.5 [+ or -] 0.7 (6) Cabezas Rubias 157 [+ or -] 2 4.6 [+ or -] 0.3 (7) Evora 53 [+ or -] 0 4.2 [+ or -] 0.6 (8) Evoramonte 44 [+ or -] 7 4.9 [+ or -] 0.3 (9) [Her.sup.de] da Mitra 139 [+ or -] 18 2.3 [+ or -] 0.1 (10) Mertola 25 [+ or -] 2 3.4 [+ or -] 0.2 (11) Mina S. Domingos 132 [+ or -] 8 2.0 [+ or -] 0.2 (12) [M.sup.te] da Borralha 168 [+ or -] 1 4.1 [+ or -] 0.4 (13) [M.sup.te] Novo 43 [+ or -] 1 2.6 [+ or -] 0.1 (14) Montejuntos 162 [+ or -] 6 0.8 [+ or -] 0.0 (15) N. [S.sup.ra] Guadalupe 53 [+ or -] 10 3.6 [+ or -] 0.4 (16) N. [S.sup.ra] Machede 27 [+ or -] 1 1.1 [+ or -] 0.1 (17) Rosal de la Frontera 326 [+ or -] 16 4.2 [+ or -] 0.1 (18) [S.sup.to] Aleixo da Restauracao 24 [+ or -] 1 1.0 [+ or -] 0.0 (19) S. Miguel de Machede 142 [+ or -] 33 0.4 [+ or -] 0.1 (20) Serpa 278 [+ or -] 16 2.7 [+ or -] 0.2 (21) [V.sup.e] Rocins 67 [+ or -] 34 1.5 [+ or -] 0.6 (22) Valverde 65 [+ or -] 50 2.2 [+ or -] 0.2 (23) V. N. S. Bento 33 [+ or -] 3 1.2 [+ or -] 0.1 (24) Villanueva del Fresno 70 [+ or -] 13 2.8 [+ or -] 0.1 Sampling site Na P (1) Almendres 20 [+ or -] 2 4.4 [+ or -] 0.4 (2) Azaruja 3 [+ or -] 2 0.6 [+ or -] 0.2 (3) Baleizao 21 [+ or -] 1 3.4 [+ or -] 0.3 (4) Beja 22 [+ or -] 0 1.6 [+ or -] 0.1 (5) Cabeca Gorda 13 [+ or -] 0 3.4 [+ or -] 0.1 (6) Cabezas Rubias 43 [+ or -] 1 0.8 [+ or -] 0.0 (7) Evora 24 [+ or -] 1 2.5 [+ or -] 0.1 (8) Evoramonte 12 [+ or -] 2 5.0 [+ or -] 0.8 (9) [Her.sup.de] da Mitra 18 [+ or -] 0 2.4 [+ or -] 0.7 (10) Mertola 6 [+ or -] 2 0.5 [+ or -] 0.2 (11) Mina S. Domingos 19 [+ or -] 1 2.0 [+ or -] 0.0 (12) [M.sup.te] da Borralha 5 [+ or -] 1 5.5 [+ or -] 0.5 (13) [M.sup.te] Novo 7 [+ or -] 0 3.7 [+ or -] 0.7 (14) Montejuntos 13 [+ or -] 3 1.5 [+ or -] 0.1 (15) N. [S.sup.ra] Guadalupe 8 [+ or -] 1 2.6 [+ or -] 0.5 (16) N. [S.sup.ra] Machede 27 [+ or -] 5 6.9 [+ or -] 0.5 (17) Rosal de la Frontera 12 [+ or -] 6 4.2 [+ or -] 0.5 (18) [S.sup.to] Aleixo da Restauracao 16 [+ or -] 1 0.2 [+ or -] 0.0 (19) S. Miguel de Machede 6 [+ or -] 0 2.4 [+ or -] 0.5 (20) Serpa 18 [+ or -] 1 2.6 [+ or -] 0.0 (21) [V.sup.e] Rocins 5 [+ or -] 2 2.2 [+ or -] 1.0 (22) Valverde 8 [+ or -] 0 2.3 [+ or -] 0.5 (23) V. N. S. Bento 24 [+ or -] 1 1.7 [+ or -] 0.1 (24) Villanueva del Fresno 19 [+ or -] 1 1.7 [+ or -] 0.4 Values of each determination represents mean [+ or -] SD (n = 3). Table 8: Bioconcentration factor (BCF) values for A. ponderosa fruiting bodies from different sampling sites. Sampling site Ag Ba (1) Almendres 38 [+ or -] 4 1.41 [+ or -] 0.33 (2) Azaruja 72 [+ or -] 8 0.57 [+ or -] 0.04 (3) Baleizao 55 [+ or -] 8 0.12 [+ or -] 0.04 (4) Beja 8 [+ or -] 1 0.33 [+ or -] 0.08 (5) Cabeca Gorda 14 [+ or -] 4 0.14 [+ or -] 0.01 (6) Cabezas Rubias 10 [+ or -] 1 0.77 [+ or -] 0.01 (7) Evora 2 [+ or -] 1 0.19 [+ or -] 0.05 (8) Evoramonte 7 [+ or -] 0 0.32 [+ or -] 0.02 (9) [Her.sup.de] da Mitra 4 [+ or -] 0 0.53 [+ or -] 0.02 (10) Mertola 61 [+ or -] 2 0.50 [+ or -] 0.01 (11) Mina S. Domingos 2 [+ or -] 0 0.30 [+ or -] 0.01 (12) [M.sup.te] da Borralha 9 [+ or -] 0 0.40 [+ or -] 0.04 (13) [M.sup.te] Novo 6 [+ or -] 0 0.39 [+ or -] 0.05 (14) Montejuntos 6 [+ or -] 1 0.29 [+ or -] 0.00 (15) N. [S.sup.ra] Guadalupe 16 [+ or -] 1 0.31 [+ or -] 0.08 (16) N. [S.sup.ra] Machede 1 [+ or -] 1 0.14 [+ or -] 0.02 (17) Rosal de la Frontera 11 [+ or -] 2 0.65 [+ or -] 0.01 (18) [S.sup.to] Aleixo da Restauracao 7 [+ or -] 0 0.39 [+ or -] 0.00 (19) S. Miguel de Machede 16 [+ or -] 1 0.38 [+ or -] 0.08 (20) Serpa 9 [+ or -] 0 0.18 [+ or -] 0.02 (21) [V.sup.e] Rocins 35 [+ or -] 21 0.27 [+ or -] 0.10 (22) Valverde 12 [+ or -] 2 0.31 [+ or -] 0.04 (23) V. N. S. Bento 4 [+ or -] 2 0.46 [+ or -] 0.01 (24) Villanueva del Fresno 32 [+ or -] 6 0.10 [+ or -] 0.01 Sampling site Cd Cr (1) Almendres 7 [+ or -] 2 1.30 [+ or -] 0.39 (2) Azaruja 1 [+ or -] 0 0.68 [+ or -] 0.03 (3) Baleizao 7 [+ or -] 0 0.42 [+ or -] 0.07 (4) Beja 15 [+ or -] 1 0.19 [+ or -] 0.00 (5) Cabeca Gorda 4 [+ or -] 0 0.18 [+ or -] 0.01 (6) Cabezas Rubias 8 [+ or -] 1 0.29 [+ or -] 0.00 (7) Evora 4 [+ or -] 2 0.30 [+ or -] 0.13 (8) Evoramonte 9 [+ or -] 1 1.14 [+ or -] 0.02 (9) [Her.sup.de] da Mitra 11 [+ or -] 2 0.47 [+ or -] 0.00 (10) Mertola 8 [+ or -] 1 0.32 [+ or -] 0.07 (11) Mina S. Domingos 13 [+ or -] 1 0.13 [+ or -] 0.00 (12) [M.sup.te] da Borralha 12 [+ or -] 1 0.24 [+ or -] 0.02 (13) [M.sup.te] Novo 3 [+ or -] 0 0.20 [+ or -] 0.02 (14) Montejuntos 10 [+ or -] 2 0.18 [+ or -] 0.01 (15) N. [S.sup.ra] Guadalupe 5 [+ or -] 1 0.12 [+ or -] 0.01 (16) N. [S.sup.ra] Machede 8 [+ or -] 1 0.10 [+ or -] 0.00 (17) Rosal de la Frontera 9 [+ or -] 1 0.42 [+ or -] 0.02 (18) [S.sup.to] Aleixo da Restauracao 3 [+ or -] 0 0.36 [+ or -] 0.10 (19) S. Miguel de Machede 38 [+ or -] 1 0.41 [+ or -] 0.03 (20) Serpa 14 [+ or -] 3 0.07 [+ or -] 0.01 (21) [V.sup.e] Rocins 3 [+ or -] 1 0.71 [+ or -] 0.24 (22) Valverde 5 [+ or -] 0 2.38 [+ or -] 0.03 (23) V. N. S. Bento 2 [+ or -] 0 2.46 [+ or -] 2.01 (24) Villanueva del Fresno 3 [+ or -] 1 0.30 [+ or -] 0.04 Sampling site Mn Pb (1) Almendres 1.27 [+ or -] 0.22 0.15 [+ or -] 0.10 (2) Azaruja 0.05 [+ or -] 0.00 0.06 [+ or -] 0.00 (3) Baleizao 0.10 [+ or -] 0.01 0.19 [+ or -] 0.03 (4) Beja 0.17 [+ or -] 0.01 0.41 [+ or -] 0.02 (5) Cabeca Gorda 0.09 [+ or -] 0.00 0.41 [+ or -] 0.03 (6) Cabezas Rubias 0.11 [+ or -] 0.00 0.31 [+ or -] 0.04 (7) Evora 0.34 [+ or -] 0.00 0.17 [+ or -] 0.08 (8) Evoramonte 0.37 [+ or -] 0.03 0.56 [+ or -] 0.00 (9) [Her.sup.de] da Mitra 0.06 [+ or -] 0.01 0.26 [+ or -] 0.03 (10) Mertola 0.04 [+ or -] 0.01 0.46 [+ or -] 0.07 (11) Mina S. Domingos 0.36 [+ or -] 0.00 0.30 [+ or -] 0.06 (12) [M.sup.te] da Borralha 0.19 [+ or -] 0.07 0.41 [+ or -] 0.03 (13) [M.sup.te] Novo 0.24 [+ or -] 0.02 0.20 [+ or -] 0.02 (14) Montejuntos 0.08 [+ or -] 0.01 0.30 [+ or -] 0.04 (15) N. [S.sup.ra] Guadalupe 0.05 [+ or -] 0.01 0.48 [+ or -] 0.06 (16) N. [S.sup.ra] Machede 0.40 [+ or -] 0.09 0.05 [+ or -] 0.02 (17) Rosal de la Frontera 0.12 [+ or -] 0.07 0.18 [+ or -] 0.00 (18) [S.sup.to] Aleixo da Restauracao 0.24 [+ or -] 0.07 0.62 [+ or -] 0.04 (19) S. Miguel de Machede 0.16 [+ or -] 0.00 0.23 [+ or -] 0.01 (20) Serpa 0.07 [+ or -] 0.02 0.05 [+ or -] 0.00 (21) [V.sup.e] Rocins 0.02 [+ or -] 0.01 0.25 [+ or -] 0.06 (22) Valverde 1.23 [+ or -] 0.28 1.16 [+ or -] 0.05 (23) V. N. S. Bento 0.10 [+ or -] 0.00 0.21 [+ or -] 0.07 (24) Villanueva del Fresno 0.03 [+ or -] 0.00 0.42 [+ or -] 0.06 Sampling site Zn (1) Almendres 13 [+ or -] 0 (2) Azaruja 3 [+ or -] 0 (3) Baleizao 10 [+ or -] 0 (4) Beja 8 [+ or -] 0 (5) Cabeca Gorda 8 [+ or -] 0 (6) Cabezas Rubias 13 [+ or -] 1 (7) Evora 15 [+ or -] 2 (8) Evoramonte 10 [+ or -] 1 (9) [Her.sup.de] da Mitra 5 [+ or -] 0 (10) Mertola 3 [+ or -] 0 (11) Mina S. Domingos 25 [+ or -] 3 (12) [M.sup.te] da Borralha 6 [+ or -] 0 (13) [M.sup.te] Novo 10 [+ or -] 0 (14) Montejuntos 6 [+ or -] 0 (15) N. [S.sup.ra] Guadalupe 5 [+ or -] 1 (16) N. [S.sup.ra] Machede 7 [+ or -] 0 (17) Rosal de la Frontera 16 [+ or -] 1 (18) [S.sup.to] Aleixo da Restauracao 4 [+ or -] 0 (19) S. Miguel de Machede 6 [+ or -] 1 (20) Serpa 2 [+ or -] 0 (21) [V.sup.e] Rocins 6 [+ or -] 0 (22) Valverde 9 [+ or -] 0 (23) V. N. S. Bento 3 [+ or -] 0 (24) Villanueva del Fresno 14 [+ or -] 1 Values of each determination represents mean [+ or -] SD (n = 3). Table 9: Clusters center of gravity. Variable Cluster 1 Ag 2.433 [+ or -] 1.593 Al 396.503 [+ or -] 210.361 Ba 1.442 [+ or -] 0.962 Ca 583.148 [+ or -] 246.929 Cd 1.316 [+ or -] 1.120 Cr 1.213 [+ or -] 0.933 Cu 224.094 [+ or -] 168.207 Fe 63.880 [+ or -] 41.865 K 34192.173 [+ or -] 13478.898 Mg 864.049 [+ or -] 419.246 Mn 64.046 [+ or -] 29.957 Na 1240.238 [+ or -] 624.901 P 422.333 [+ or -] 167.110 Pb 2.440 [+ or -] 1.468 Zn 72.936 [+ or -] 29.664 Variable Cluster 2 Ag 1.690 [+ or -] 1.248 Al 392.625 [+ or -] 226.842 Ba 0.996 [+ or -] 0.616 Ca 617.110 [+ or -] 151.838 Cd 0.854 [+ or -] 0.322 Cr 1.753 [+ or -] 1.122 Cu 238.065 [+ or -] 108.827 Fe 252.718 [+ or -] 74.423 K 23008.328 [+ or -] 23670.094 Mg 664.112 [+ or -] 268.732 Mn 76.347 [+ or -] 18.841 Na 1286.973 [+ or -] 354.879 P 219.741 [+ or -] 66.174 Pb 3.389 [+ or -] 1.805 Zn 80.972 [+ or -] 33.836 Variable Cluster 3 Ag 1.690 [+ or -] 2.309 Al 227.812 [+ or -] 187.093 Ba 0.719 [+ or -] 0.616 Ca 413.341 [+ or -] 260.514 Cd 0.630 [+ or -] 0.526 Cr 0.656 [+ or -] 0.486 Cu 112.320 [+ or -] 90.198 Fe 36.283 [+ or -] 27.911 K 21750.972 [+ or -] 12089.189 Mg 533.816 [+ or -] 354.098 Mn 30.254 [+ or -] 19.582 Na 598.937 [+ or -] 391.228 P 182.971 [+ or -] 173.598 Pb 1.640 [+ or -] 1.256 Zn 45.118 [+ or -] 29.973 Table 10: The coincidence matrix for Decision Tree model presented in Figure 5. Training set Variables Cluster 1 Cluster 2 Cluster 3 Cluster 1 24 0 0 Cluster 2 0 8 0 Cluster 3 0 0 14 Test set Variables Cluster 1 Cluster 2 Cluster 3 Cluster 1 9 0 0 Cluster 2 0 4 0 Cluster 3 0 0 10 Table 11: The coincidence matrix for Decision Tree model presented in Figure 6. Training Set Variables Cluster 1 Cluster 2 Cluster 3 Cluster 1 22 2 0 Cluster 2 1 7 0 Cluster 3 2 0 12 Test Set Variables Cluster 1 Cluster 2 Cluster 3 Cluster 1 8 1 0 Cluster 2 1 3 0 Cluster 3 2 0 8 Figure 2: Moisture, dry weight, and organic and minerals content of A. ponderosa fruiting bodies from 24 different sampling sites. Organic content 7.6 [+ or -] 1.4% Minerals 0.7 [+ or -] 0.2% dry weight 8.3 [+ or -] 1.4% Moisture 91.7 [+ or -] 1.4% Note: Table made from pie chart.

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Title Annotation: | Research Article |
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Author: | Salvador, Catia; Martins, M. Rosario; Vicente, Henrique; Caldeira, A. Teresa |

Publication: | International Journal of Analytical Chemistry |

Date: | Jan 1, 2018 |

Words: | 18492 |

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