Anthropression as a Factor Affecting the Content of Heavy Metals in the Flowers of Sambucus nigra L.—A Medicinal Plant Affecting Human Health

Abstract

The harvesting of herbs from urban and peri-urban areas requires systematic monitoring of soils and plants, especially of trace element concentrations. The aim of the study was to assess the phytoaccumulation of selected trace elements (Zn, Cu, Fe, and Mn) in elderberry flowers from the Kuyavian-Pomeranian province (Poland). The enzymatic activity of soils was also assessed in the context of the impact of metals on the biological properties of soils at risk of contamination with trace elements. Soil and plant samples were taken from seven locations with different anthropopressures. Flowers from sites with a high frequency of road traffic were characterized by a greater number of elements (location 1, 3–7) than from areas away from busy roads (location 2). The correlation analysis showed that Cu and Zn contents were highly correlated in the flowers of elderberry as compared to the corresponding soils seven locations with different anthropopressures Regarding the Zn content, only flowers from habitats 1, 2, 7 met the conditions specified in the WHO standard for herbs used in herbal medicine (<50 mg·kg⁻¹). Based on the conducted research, it was found that the level of soil enzymatic activity in the tested soils varied within wide limits but clearly depended on their location. The highest enzyme activity in the soil was found in soil from town center 1 (location 3), where high DHA dehydrogenase DHA (114.5 mg TPF·g⁻¹·24 h⁻¹), fluorescein diacetate hydrolysis FDA (51.26 μg F·g⁻¹·h⁻¹), and β-glucosidases GLUC activity (4.833 μg pNP·g⁻¹·h⁻¹) were determined, as well as in soil from residential area 2 (location 3), where high DHA (165.9 mg TPF·g⁻¹·24 h⁻¹) and FDA (48.23 μg F·g⁻¹·h⁻¹) activity were determined. Analyzing the soil properties, it can be concluded that the content of Cu_t and Zn_t in the soil and their forms available for plants, as well as DHA activity, correlates most closely with the content of organic matter.

1. Introduction

The impact of human activity on the environment often results in an increase of trace element contamination in soil and plants. In many urban areas, there are gardens and allotments where vegetables and herbs are grown. This concerns the sustainable use of soils and small-scale food production in suburban areas. Sambucus nigra L. is a widespread species of the Adoxaceae family [1]. This plant can be found throughout Europe but also in Western Asia, Northern Africa, and the USA [2]. The shrubs of elderberry grow to a height of 4–6 m and produce white flowers gathered in umbel-shaped panicles at the tops of the shoots and dark violet drupes that grow in clusters [3]. Due to the shape and color of leaves and flowers, this species is eagerly planted in gardens and parks [4]. In addition to its decorative value, due to the presence of bioactive substances in its tissues, it is used to increase the body’s immunity. Extracts from the tissues of this species are a rich source of specific bioactive substances belonging mainly to the group of flavonoids derived from quercetin (isoquercitrin, hyperoside, and rutoside), kaempferol (astragaline, nicotiflorin), and isorhamnetin 3-G-glucoside and 3-0-rutinoside [5,6]. All parts of this plant can be medicinal raw materials, but the parts most often used are the flowers and fruits, which are obtained from the natural state [6]. While immature berries as well as green leaves and stems contain toxic cyanogenic glycoside and sambunigrin and thus should be avoided in human consumption, the flowers and fully ripe berries have widespread culinary use [7]. In addition, the fruits of the elderberry are rich in other compounds and are valuable for human health; such compounds include vitamins A, B, and C; organic acids; polyphenolic acids; triterpenes; and minerals such as K, Ca, Fe, Mg, P, Na, Zn, Cu, Mn, Se, Cr, Ni, and Cd [5,6,8,9]. Due to their composition, flower extracts can be used as an antipyretic, diaphoretic, vasoconstrictor, and diuretic. Extracts from the tissues of this species also have a cleansing and detoxifying effect on the body and have antibacterial, antiviral, and antifungal properties. Therefore, this species is used in the treatment of colds, flu, angina, asthma, measles, and scarlet fever. It is recommended to consume juices and syrups from flowers and fruits in cases of bronchitis, pneumonia, cough, phlegm in the upper respiratory tract, and sore throat [5,6], and there are many medicines and dietary supplements containing S. nigra extract on the pharmaceutical market.

The development of industry, and the technical and technological progress in the world, has led to the pollution of the natural environment with trace metals. These include elements necessary for living organisms, elements that play an unknown physiological role, and toxic elements. Microelements that are necessary for plant growth and development are iron (Fe), nickel (Ni), cobalt (Co), manganese (Mn), zinc (Zn), copper (Cu) and molybdenum (Mo). Other metals, such as mercury (Hg), thallium (Tl), arsenic (As), lead (Pb), and cadmium (Cd). They do not have any physiological function in the plant; they are therefore called the so-called ballast elements, and at higher concentrations they may be toxic [10]. Plants have the ability to absorb some heavy metals that are needed for plant biochemistry and physiology, but their higher concentrations may be toxic to plants and the consumer. Long term exposure to heavy metals can cause stress in plants, lipid peroxidation, enzyme inactivation, DNA damage, respiratory inhibition, gas exchange, the limitation of photosynthesis, and the disturbance of water balance. This may cause visible changes in plant morphology, wilting aging, an overall reduction in biomass production, a limited number of seeds, and even plant death [11].

Anthropogenic human activity has led to the excessive accumulation of trace metals in the environment. These elements can accumulate in soil, water, living organisms, and bottom sediments [12,13,14]. Medicinal plants may also accumulate trace metals [14,15,16]. An increase in the concentration of these elements in the tissues of medicinal plants may inhibit the synthesis of biologically active substances and influence changes in the mineral composition of plants, thereby reducing the medicinal value of raw plant material. Very high concentrations of heavy metals may impair human health and even lead to body poisoning and death [16,17]. In the EU countries and in the world, the permissible content of heavy metals in herbal raw materials used in the pharmaceutical industry is regulated by the standards of the European Pharmacopoeia [18] and the requirements of the World Health Organization [19]. The content of trace elements, especially Fe, Mn, Zn, and Cu in plant remedies, is not regulated by law. According to the WHO, the permissible lead content in medicinal plants is Pb 10 mg kg⁻¹ d.w. In turn, the provisions of the Polish Pharmacopoeia are more restrictive. According to these standards, the concentration of Pb in herbs should be below 5.0 mg kg⁻¹ d.w. [20].

Enzymes in soils are essential for organic matter decomposition and nutrient cycling; they represent soil’s microbial metabolism and its reaction to environmental change. Soil dehydrogenases are often used as an indicator of overall microbial activity in the soil. They take part in soil oxidation and reduction reactions by transferring protons and electrons from substrates to soil organic matter acceptors [21]. Hu et al. [22] proposed that dehydrogenases (DH), which act by dehydrogenating the substrate, can be used as an indicator for assessing heavy metal contamination. Soil hydrolases participate in the degradation of various substrates, making nutrients available to microorganisms and plants. They catalyse nutrient-rich “labile” soil organic matter, which is directly related to meeting the demand for C, N, P, and S elements [23]. The hydrolytic activity of the soil is detected by the hydrolysis of the sodium salt of fluorescein diacetate, which is carried out by various hydrolases such as proteases, lipases, and esterases [24].

Poland is one of the main producers and exporters of herbal ingredients in Europe. An important element of the raw material supply chain is its origin. Its control comes down to monitoring the share of trace elements in the plant material. The aim of the study was to assess the phytoaccumulation of Zn, Cu, Fe, and Mn in elderberry flowers (S. nigra) and the soil of seven locations with different traffic intensity (different degrees of anthropopressure) in the Kuyavian-Pomeranian province (central Poland). The enzymatic activity of soils was also assessed in the context of the impact of metals on the biological properties of soils at risk of contamination with trace elements. Knowledge of soil potential contamination is key to helping communities identify problems with soils and to solving problems so that each plant is healthy.

2. Materials and Methods

2.1. Study Area

The content of Zn, Cu, Mn, and Fe was assessed in elderberry flowers (S. nigra) and soil collected from 7 locations in the city of Bydgoszcz (Poland) and its surroundings (330,000 inhabitants) at the turn of May and June 2021. The places where plant and soil samples were taken, their location, and the degree of traffic intensity in the examined place are presented in

Table 1. Places of collecting plant and soil samples.

Sampling Location	The Place Where the Material Is Collected	Location	Distance to Road	The Degree of TrafficIntensity *
1	a suburb	53°01′31.7″ N 17°53′10.6″ E	40 m	b
2	suburban location with forest (control)	53°08′12.1″ N 17°48′46.4″ E	330 m	a
3	Bydgoszcz city (town center 1)	53°08′04.4″ N 18°02′08.4″ E	5 m	c
4	Bydgoszcz city (residential area 1)	53°07′15.8″ N 18°01′59.4″ E	4 m	c
5	Bydgoszcz city (old town center)	53°07′15.6″ N 18°00′23.1″ E	6 m	c
6	Bydgoszcz city (residential area 2)	53°09′59.2″ N 18°09′48.1″ E	20 m	b
7	Bydgoszcz city (town center 2)	53°09′58.1″ N 18°02′40.1″ E	15 m	b

* a—places away from road traffic; b—places with medium traffic intensity; and c—places with heavy traffic.

. The control in the experiment was shrubs of S. nigra from suburban location with forest (sampling location 2, from 330 road distance), separated from traffic with trees and dense vegetation.

2.2. Plant Sampling and Analysis Methods

The plant material consisted of the elderberry flowers collected in the full flowering phase. Ten inflorescences were collected from each S. nigra bush. The plants were collected from seven locations at the turn of May and June 2021, dried on paper at room temperature to an air-dry state, and ground in an agate mortar. The homogenized material (300 mg) was microwave-digested in the Speedwave Two mineralizer (Berghof, Eningen, Germany) with the wet mineralization method (5 mL 65% HNO₃, 1 mL 30% H₂O₂). In mineralized plant samples, the total content of Zn, Cu, Mn, and Fe was determined by atomic absorption spectrometry (AAS) with the SOLAAR S4 spectrometer (ThermoElemental, Cambridge, UK). Analyses were performed in three replications.

2.3. Soil Sampling and Analysis Methods

The soil was sampled from the plant root zone (0–25 cm). Additionally, some soil was taken from a depth of 120–150 cm to determine the background metal content. Soil samples were taken at 20 cm from the elderberry trunk. The soil was sieved through a sieve with a mesh diameter of 2 mm, the granulometric composition was determined using the Mastersizer 2000 analyzer (Malvern Instrument, Malvern, UK), the total organic carbon content (TOC) was determined using the Vario Max CN analyzer from Elementar provided by Analysensysteme GmbH (Hanau, Germany), and the pH was determined using the potentiometric method on a pH meter after adding a 1 M KCl solution to the soil samples, at a soil/solution ratio of 1:2.5. The total metal contents were determined applying digestion with HF and HClO₄ acid solutions according to the Crock and Severson [25] method. The certified reference materials (TILL–3. the Canadian Certified Reference Materials) were used to verify the accuracy of the results. The recovery rates for the elements were as follows: 98%, 99%, 103%, 97%, and 99% for Zn, Cu, Pb, Mn, and Fe, respectively. Analyses were performed in three replications. The total metal content was determined by atomic absorption spectrometry (ASA) using the SOLAAR S4 spectrometer (ThermoElemental). Dehydrogenase activity (EC 1.1.) was researched by the reduction of 2, 3, 5-triphenyltetrazolium chloride via 24 h of incubation in 37 °C according to Thalmann [26]. The reaction product was triphenylformazan, extracted with acetone and assayed at 546 nm in UV-VIS spectrophotometer. The activity of FDA (fluorescein diacetate hydrolysis) (EC 3.) used like an indicator of global soil hydrolysis activity was detected by measuring as described by Adam and Duncan [24]. The researched soil was incubated for 1 h after this time enzymatic reaction was stopped by putting it in a mixture of methyl alcohol and chloroform (1:2). The fluorescein was measured at 490 nm. The soil β-glucosidase (EC 3.2.1.21) activity was determined according to Eivazi and Tabatabai [27] as a substrate was using p-nitrophenyl-β-D-glucopyranoside. The concentration of p-nitrophenol was determined at 400 nm. The activity of arylsulfatase (EC 3.1.6.1) was analyzed by Tabatabai and Bremner [28] using a substrate p-nitrophenyl-β-D-sulphate. The color product was analyzed by spectrophotometer measure by 420 nm.

2.4. Statistical Analysis and Mathematical Calculations

All the analytical measurements were performed in three replications. Single-factor analysis of variance (ANOVA) was performed. The arithmetic mean values are shown in tables ± standard deviation. The activities of all the enzymes in soil and metal content in elderberry flowers and soil against the background were evaluated using the principal component analysis (PCA). The first two principal components (PC1 and PC2) were selected to determine which soil properties differentiate respective sampling sites. The work also used cluster analysis (CA). The cluster analysis allows for the separation of groups of objects based on the differentiation of variables. Ward’s method was used in the cluster analysis. The data were grouped using Euclidean distance [29]. All of the analyses were made using the “Statistica 12.0 for Windows Pl” package [30].

The coefficient of variation (CV) of the parameters was calculated as follows:

CV = (S/X) × 100%.

where CV is the coefficient of variation (%), S is the standard deviation, and X is the arithmetic mean. The values: 0–15%, 16–35%, and >36% indicate low moderate or high variability, respectively [31].

The human activity impact on soils was estimated with the enrichment factor (EF) based on the normalization of the metal measured against a reference metal. Fe was used as the reference element. The values of EF were calculated according to the formula:

EF = [C_n/C_nFe]/[B_n/B_nFe]

where the C_n is the total content of metal in soil sample; C_nFe is the total content of Fe in soil sample; B_n is the content of metal for the geochemical background; and B_nFe is the content of Fe for the geochemical background as the reference element [32]. For the calculations, it was assumed that the content of metals in parent material was at the depth of 120–150 cm. Based on value of EF, the categories were determined as <2, deficient to minimal enrichment; 2–5, moderate; 5–20, considerable; 20–40, very high; and >40, extremely high enrichment [33].

The values of the bioconcentration factor (relative content) of Zn, Cu, Mn, and Fe in the plant material were calculated following the formula of a ratio of the total content of the elements studied in flowers (CS_f) to their content in soil (CS_s):

BCF_{f flowers} in S. nigra = CS_f flowers/CS_s soil.

To evaluate the degree of accumulation of Zn, Cu, Mn, and Fe, a four-degree scale provided by Kabata-Pendias et al. [34] was used. The values of the bioconcentration factor (BCF) were interpreted as follows: 0.001–0.01, lack; 0.01–0.1, weak; 0.1–1.0, medium; and 1.0–10.0, intensive of accumulation.

3. Results and Discussion

The tested soils had grain sizes of clayey sands and sandy clay. Soil samples taken from locations 1, 4, and 5 showed sandy clay grain size. These soils contained from 64.9% to 71.6% of sand fraction (2.0–0.05 mm), from 26.5% to 31.8% of silt fraction (0.05–0.002 mm), and from 2.0% to 3.3% of clay fraction (<0.002 mm). In turn, soil samples from locations 2, 3, 6, and 7 showed clayey sand grain size and contained from 73.4% to 80.6% of sand fraction, from 16.7 to 25.3% of the silt fraction, and from 1.0 to 1.3% of the clay fraction (

Table 2. Selected properties of soil samples (0–25 cm).

Sampling Location *	pH 1 M KCl	TOC g kg−1	Grain Size Composition [%]			Textural Class USDA **
			Sand 2.0–0.05 mm	Silt 0.05–0.002 mm	Clay <0.002 mm
1	6.54 ± 0.04	11.0 ± 0.22	71.6	26.4	2.0	SL
2	4.03 ± 0.03	6.51 ± 0.30	80.6	18.3	1.1	LS
3	5.86 ± 0.05	22.4 ± 0.21	77.1	21.7	1.2	LS
4	6.77 ± 0.06	16.1 ± 0.20	64.9	31.8	3.3	SL
5	6.47 ± 0.02	11.3 ± 0.22	70.0	27.9	2.1	SL
6	6.70 ± 0.08	12.8 ± 0.23	73.4	25.3	1.3	LS
7	6.56 ± 0.05	12.6 ± 0.22	80.3	16.7	1.0	LS
mean	6.13	13.2	73.98	24.01	1.71
Sd	0.97	4.95	5.74	5.39	0.82
CV (%)	15.8	37.3	7.76	22.5	48.0

* sampling location explanations as in Table 1; TOC—total organic carbon in soil; SL—sandy loam; LS—loamy sand; Sd—standard deviation; CV—coefficient of variation; and ** USDA [35].

). Based on the soil analyses, it was found that these soils had a reaction ranging from acidic to alkaline. The organic carbon (TOC) content ranged from 6.51 to 22.4 g·kg⁻¹. The most varied were the TOC content and the clay fraction in the soil, as evidenced by the CV coefficients of 37.3 and 48%, respectively. The soil sample taken from location 2 had the lowest pH value and the lowest TOC content.

The soil in the surface layer showed varying total contents of individual metals (

Table 3. Total content of metals (Zn_t, Cu_t, Pb_t, Mn_t, and Fe_t) in topsoil (0–25 cm).

Sampling Location *	Znt	Cut	Mnt	Fet
	mg·kg−1			g kg−1
1	32.1 ± 1.25	6.7 ± 0.25	127.1 ± 10.11	3.02 ± 0.11
2	23.2 ± 1.45	2.1 ± 0.08	67.1 ± 4.12	2.62 ± 0.09
3	89.4 ± 1.26	4.6 ± 0.21	166.3 ± 14.11	7.56 ± 0.13
4	142.0 ± 2.25	5.5 ± 0.25	265.4 ± 24.00	5.35 ± 0.06
5	104.2 ± 1.42	13.8 ± 1.25	162.5 ± 11.16	4.44 ± 0.10
6	116.8 ± 1.90	9.2 ± 0.08	150.0 ± 13.09	6.00 ± 0.05
7	91.1 ± 1.25	5.5 ± 0.15	128.8	5.09 ± 0.10
mean	85.5	6.77	152.4	4.86
Sd	43.40	3.76	59.9	1.71
CV (%)	50.7	55.7	39.3	35.0

* sampling location explanations as in Table 1; _t—total contents of metals; Sd—standard deviation; and CV—coefficient of variation.

). The tested soils did not show any contamination with heavy metals in their surface layer. The content of individual metals in soil samples can be ordered as follows: Cu_t < Zn_t < Mn_t < Fe_t. The total Fe_t content in the surface layer of soil ranged from 2.62 g∙kg⁻¹ (location 2) to 7.56 g∙kg⁻¹ (location 3), Cu_t—from 2.1 mg∙kg⁻¹ (location 2) to 13.8 mg∙kg⁻¹ (location 5), Mn_t—from 67.1 mg∙kg⁻¹ (location 2) to 265.4 mg∙kg⁻¹ (location 4), and Zn_t—from 23.2 (location 2) to 142.0 mg∙kg⁻¹ (location 4). The highest total content of trace elements was determined in soil samples collected close to roads with heavy traffic. Assessing the overall metal content, it can be concluded that they did not exceed the permissible contents provided for in applicable law [36].

The contents of Cu_a forms available for plants ranged from 0.8 to 3.20 mg kg⁻¹; Fe_a—from 185.1 to 730.7 mg kg⁻¹; Mn_a—from 16.4 to 43.0 mg kg⁻¹; and Zn_a—from 4.2 to 21.0 mg kg⁻¹ (

Table 4. Content of metals (Zn_a, Cu_a, Pb_a, Mn_a, and Fe_a) available for plants (0–25 cm).

Sampling Location *	Zna	Cua	Mna	Fea
	mg·kg−1
1	4.2 ± 0.08	1.8 ± 0.02	25.5 ± 1.44	482.0 ± 22.05
2	5.1 ± 0.09	0.8 ± 0.01	16.4 ± 1.22	185.1 ± 20.08
3	9.5 ± 3.08	1.7 ± 0.03	28.9 ± 1.50	730.7 ± 19.05
4	21.0 ± 2.20	1.3 ± 0.08	43.0 ± 1.41	355.0 ± 12.15
5	13.2 ± 0.16	3.2 ± 0.16	33.0 ± 0.90	370.1 ± 16.17
6	14.7 ± 0.13	1.9 ± 0.05	34.1 ± 1.60	412.9 ± 22.20
7	11.0 ± 0.10	1.1 ± 0.02	28.3 ± 1.05	298.8 ± 30.30
mean	11.24	1.67	29.88	404.9
Sd	5.79	0.77	8.21	171.0
CV (%)	51.5	46.1	27.5	42.2

* sampling location explanations as in Table 1; _a—content of forms available for plants (1 M HCl); Sd—standard deviation; and CV—coefficient of variation.

). As reported by Ociepa [37], the availability of heavy metals to plants is affected by many factors, especially the type of the parent material, the soil reaction and the content of the organic substance, clay minerals, and the interaction with other elements. The greatest variation among the tested metals available for plants was recorded for Zn_a content (51.5%) (Table 4).

The highest percentage of mobile metal forms in their total content was for Cu and ranged from 20.0% in the soil sample taken from location 7 to 37.0% in sample number 2 (Figure 1).

The EF values indicate a small accumulation (minimum enrichment > 1.5) of Cu and Mn in the surface layer of the tested soils of locations 1 and 5 compared to the content of the geochemical background (Figure 2). The enrichment factor (EF) is used to assess the presence and intensity of anthropogenic contaminant deposition on the surface horizon of soils [38,39,40].

The average metal content in the host rock was 42.4 mg·kg⁻¹ for Zn, 4.97 mg·kg⁻¹ for Cu, 183.8 mg·kg⁻¹ for Mn, and 5.51 g kg⁻¹ for Fe, constituting the geochemical background content of the region’s soils (

Table 5. Total content of metals (Zn_tg, Cu_tg, Pb_tg, Mn_tg, and Fe_tg) in parent material (120–150 cm).

Sampling Location *	Zntg	Cutg	Mntg	Fetg
	mg·kg−1			g kg−1
1	27.5 ± 3.08	5.2 ± 0.08	250.2 ± 11.12	4.24 ± 0.07
2	22.8 ± 2.18	2.0 ± 0.03	145.0 ± 9.18	3.25 ± 0.03
3	65.4 ± 4.07	4.4 ± 0.07	150.3 ± 10.12	6.89 ± 0.08
4	53.4 ± 5.08	3.3 ± 0.06	230.4 ± 21.08	5.25 ± 0.09
5	42.7 ± 4.02	7.2 ± 0.10	220.4 ± 23.12	3.98 ± 0.03
6	37.5 ± 3.12	7.7 ± 0.12	182.3 ± 11.00	8.45 ± 0.12
7	47.5 ± 3.08	5.0 ± 0.07	108.0 ± 13.14	6.54 ± 0.10
mean	42.4	4.97	183.8	5.51
Sd	14.75	2.02	52.1	1.86
CV (%)	34.8	40.6	28.3	33.7

* sampling location explanations as in Table 1; _tg—total content of metals in parent material; Sd—standard deviation; and CV—coefficient of variation.

).

Ward’s method was used in the cluster analysis. The data was grouped using Euclidean distance [29]. In samples from locations 5 and 6, a similar content of metal forms available for plants and the concentration of metals in the dry matter of plants was found (Figure 3) compared to the remaining samples.

The tested elderberry flowers showed different trace element contents depending on the place where the samples were taken. Based on the results (

Table 6. Content of metals (Zn_f, Cu_f, Mn_f, and Fe_f) in dry weight of flowers S. nigra.

Sampling Location *	Znf	Cuf	Mnf	Fef
	mg·kg−1
1	37.5 ± 4.05	10.6 ± 2.10	29.6 ± 7.10	115.0 ± 17.10
2	27.1 ± 3.08	3.4 ± 1.12	20.0 ± 5.11	140.0 ± 20.13
3	51.3 ± 5.08	9.9 ± 2.13	23.2 ± 4.10	168.3 ± 21.10
4	53.8 ± 3.12	10.2 ± 2.00	28.3 ± 5.18	185.8 ± 18.20
5	57.1 ± 7.10	19.7 ± 3.10	22.1 ± 4.22	281.7 ± 24.40
6	53.3 ± 6.11	8.8 ± 1.06	29.6 ± 6.00	105.8 ± 17.60
7	39.2 ± 7.00	7.2 ± 1.15	27.5 ± 4.34	243.3 ± 30.41
mean	45.61	9.97	25.76	177.1
Sd	11.11	4.95	3.91	65.57
CV (%)	24.3	49.7	15.2	37.0

* sampling location explanations as in Table 1; _f—flowers; Sd—standard deviation; and CV—coefficient of variation.

), it can be concluded that the concentration of metals in elderberry flowers was in decreasing order: Fe > Zn > Mn > Cu.

Iron is a significant and essential metal for the biochemical and physiological processes of plants but in excess negatively affects plant growth and development, carbon metabolism, enzyme activity, respiration in plants, photosynthetic efficiency, and stress causes oxidative toxicity [41]. In the analyzed plants, the Fe_f content was determined in the range from 105.8 mg∙kg⁻¹ (location 6) to 281.7 mg∙kg⁻¹ (location 5). These data are similar to the results reported by Kołodziej et al. [42], who detected an iron content of 35.77 mg∙kg⁻¹ to 214.58 mg∙kg⁻¹ in the tested elderberry flowers. These values were lower than those compared to the results reported by other authors. Relatively higher concentrations were obtained by Tomaszewska-Sowa et al. [14] for sand Helichrysum inflorescences (248.6–271.8 mg·kg⁻¹), common yarrow (458–496.5 mg·kg⁻¹), and common nettle (335.1–704.2 mg·kg⁻¹).

Zinc is an essential metal for plants. It has an effect as a cofactor and a component of enzymes, and it is an important factor in the regulation of nitrogen metabolism and photosynthesis. However, excessively high concentrations of Zn are toxic to plants and humans, causing the disruption of several biochemical and physiological processes, causing disturbances in iron metabolism, and resulting in leaf defoliation. Plant species and genotypes vary significantly in their tolerance to high Zn concentrations [43]. The analyzed flower samples contained Zn_f ranging from 27.1 mg∙kg⁻¹ (location 2) to 57.1 mg∙kg⁻¹ (location 5). According to the World Health Organization [44], the average concentration of Zn in crops ranges from 10 to 100 mg∙kg⁻¹ dry matter. However, the Zn content in shoots in the range of 15–30 mg·kg⁻¹ is sufficient to meet the physiological needs of most plants [45]. This means that all tested plants except location 2 (the suburban location with forest) were characterized by Zn_f concentration in flowers exceeding the average physiological needs of these plants. Moreover, in elderberry plants obtained from natural locations 3, 4, 5, and 6, the concentration of this element was above the average physiological needs of these plants. The results show that the herbal raw material collected from locations 1, 2, and 7 met the conditions specified in the WHO standard for herbs that are used in herbal medicine. According to this standard, the Zn content cannot exceed 50 mg·kg⁻¹. These results can be compared to the observations presented by Kołodziej et al. [42], who tested samples from 16 locations at various distances from the road and obtained results from 23.92 to 39.29 mg∙kg⁻¹. These values indicate that elderberry flowers collected far from roads in rural areas were characterized by the smallest total content of Zn. The zinc in flower content in S. nigra plants (Zn_t) was significantly correlated (r = 0.755) with zinc available for plants Zn_a (Table 9).

Manganese in plants is necessary for the construction of photosynthetic proteins and enzymes and the proper functioning of chloroplasts and photosynthesis. However, its excessive concentration in plant tissues may damage the photosynthetic apparatus and disrupt various processes such as enzyme activity, absorption, translocation, and utilization of mineral elements, causing oxidative stress. The reaction of plants to excess Mn depends on the plant species and variety or genotype [46]. The Mn_f content in elderberry flowers ranged from 20 mg∙kg⁻¹ (location 2) to 29.6 mg∙kg⁻¹ (locations 1, 6). This coincides with the research on marshmallow (Allthae officinalis) and marigold (Calendula officinalis) flowers in which Chizzola et al. [47] discovered the Mn content at levels of 21.9 and 21.3 mg∙kg^−1, respectively. For comparison, the Mn_f content in other species ranged from 27.2 to 247.3 mg·kg⁻¹ [14], 124.3 to 338.6 mg·kg⁻¹ [16], and 75 to 1849 mg·kg⁻¹ [48]. According to Malzahn [49], the concentration of Mn_f in plants growing in areas far from the source of pollution ranges from 340 to 1339 mg·kg⁻¹.

Copper has an important function in CO₂ assimilation and ATP production in plant cell. It is the main component of proteins important in the photosynthesis process. Excessive Cu concentration in plants inhibits plant growth, causes leaf chlorosis, is cytotoxic, and causes oxidative stress by producing reactive oxygen species [50]. The Cu_f content was determined in the range from 3.4 mg∙kg⁻¹ (location 2) to 19.7 mg∙kg⁻¹ (location 5). Similar observations were made by Kołodziej et al. [42], who determined the copper content in elderberry flowers to range from 5.28 to 16.10 mg∙kg⁻¹, and Chizzola et al. [47], who determined the copper content from 6.8 to 16.9 mg∙kg⁻¹ in various plant species. Copper is a metal classified as a microelement in plants, but its excess may be toxic to plants [51]. According to Kabata-Pendias and Pendias [10], the copper content in plants is usually below 4–5 mg·kg^−1, and its average content in above-ground parts of plants ranges from 5 to 20 mg·kg⁻¹. The results obtained indicate that only flowers collected from location 5 had the content of this element above the average content. Therefore, this herbal raw material can be recommended as a source of this element in the diet. The greatest variability in plant material collected from seven locations was found in relation to copper content (CV = 49.7%) (Table 6). The relationship shows that the Cu_f content was dependent on total Cu (Cu_t) in soil (r = 0.889) and forms the Cu available for plant (Cu_a) content in soil (r = 0.947) content (Table 9).

The bioaccumulation index (BCF) values were used to assess the accumulative capacity of flowers collected from various locations. This coefficient determines the plants’ ability to accumulate elements, considering their initial content in the substrate. The higher the values of this indicator, the higher the concentration of the element that is found in the plant biomass in relation to its content in the soil [52]. The values and degree of the bioaccumulation index (BCF_f) of Zn, Cu, Mn, and Fe in elderberry flowers are presented in

Table 7. Values of bioaccumulation index (BCF_f) metals (Zn, Cu, Mn, and Fe) for flowers S. nigra.

Sampling Location *	Bioaccumulation Index (BCFf)
	Zn	Cu	Mn	Fe
1	1.17	1.58	0.23	0.04
Accumulation	intensive	intensive	medium	weak
2	1.17	1.62	0.30	0.05
Accumulation	intensive	intensive	medium	weak
3	0.57	2.15	0.14	0.02
Accumulation	medium	intensive	medium	weak
4	0.38	1.85	0.11	0.03
Accumulation	medium	intensive	medium	weak
5	0.55	1.43	0.14	0.06
Accumulation	medium	intensive	medium	weak
6	0.46	0.96	0.20	0.02
Accumulation	medium	medium	medium	weak
7	0.43	1.31	0.21	0.05
Accumulation	medium	intensive	medium	weak

* sampling location explanations as in Table 1; BCF_f (bioaccumulation index)—a ratio of the total content of the elements (Zn, Cu, Mn, and Fe) studied in flowers (CS_f) to their content in soil (CSs).

. The values of the bioaccumulation coefficient indicate that elderberry flowers accumulated Cu and Zn to the greatest extent. The tested plant material was characterized by a BCF_f value for Cu ranging from 0.96 (location 6) to 2.15 (location 3). In turn, Zn fluctuated in coefficient values from 0.38 (location 4) to 1.17 (locations 1, 2). Based on the data obtained, the degree of Cu and Zn accumulation in plant samples at all sites was determined to be intense or medium. In turn, the Mn accumulation rate was medium, and Fe was low in all of the variants. The BCF_f values for Mn ranged from 0.11 (location 4) to 0.30 (location 2), and for Fe from 0.02 (locations 3, 6) to 0.06 (location 5) (Table 7).

Based on the results obtained, it can be concluded that this parameter (BCFf) in elderberry flowers differed for the tested elements and was arranged according to the following series: Cu > Zn > Mn > Fe. The total content of metals slightly differentiated the bioaccumulation index of the tested trace elements. Attention is drawn to the lower rates of zinc bioaccumulation in objects with a higher content of this element in the soil, which indicates a lower ability to accumulate Zn in flowers in relation to soil resources (Table 3 and Table 6). Although the element is abundant in soil and can accumulate in flowers to relatively high levels, BCF below 1 can be achieved, as has been demonstrated for Fe and Mn. Depending on the environmental conditions, the values of BCF varied highly depending on trials element and were >1 for Zn and Cu, while they were <1 for Fe and Mn. The observations obtained confirm the research of other authors [53,54,55].

The activity of investigated enzymes was dependent on the sampling location (

Table 8. The enzyme activity in topsoil (0–25 cm).

Sampling Location *	DHA mgTPF·g−1·24 h−1	FDA μg F·g−1·h−1	GLUC μg pNP·g−1·h−1	ARYL μg pNP·g−1·h−1
1	20.70 ± 0,24	34,89 ± 0.09	1.517 ± 0.04	0.151 ± 0.06
2	0.234 ± 0.00	40.32 ± 0.67	0.638 ± 0.02	0.054 ± 0.01
3	114.5 ± 1.52	51.26 ± 0.58	4.833 ± 0.02	0.069 ± 0.03
4	14.65 ± 0.29	24.18 ± 0.48	1.532 ± 0.05	0.140 ± 0.00
5	2.38 ± 0.05	28.76 ± 0.45	1.579 ± 0.03	0.081 ± 0.01
6	165.9 ± 5.73	48.23 ± 0.46	3.461 ± 0.08	0.028 ± 0.00
7	31.40 ± 0.41	41.31 ± 1.41	3.748 ± 0.22	0.082 ± 0.01
mean	49.96	38.42	2.473	0.06
Sd	64.27	9.846	1.535	0.044
CV (%)	1.29	0.26	0.62	0.51

* sampling location explanations as in Table 1. Abbreviations: DHA—dehydrogenase activity; FDA—fluorescein diacetate hydrolysis activity; GLUC—β-glucosydase activity; and ARYL—arylsulphatase activity.

). Dehydrogenase was characterized by the greatest diversity of activity. Its activity was within a wide range of 0.234 mg TPF·g⁻¹·24 h⁻¹ (location 2) to 165.9 mg TPF·g⁻¹·24 h⁻¹ (location 6). FDA activity in the soil ranged from 24.18 (location 4) to 51.26 μg F·g⁻¹·h⁻¹ (location 3) (with an average value of 38.42 μg F·g⁻¹·h⁻¹), and in β-glucosides from 0.638 μg pNP·g⁻¹·h⁻¹ (location 2) to 4.833 μg pNP·g⁻¹·h⁻¹ (location 3) (with an average value of 2.473 μg pNP·g⁻¹·h⁻¹). Arylsulfatase takes plays an important role in S cycles because it can catalyze the hydrolysis of organic sulfate esters [28]. According to Fitzgerald [56], the main sources of arylsulfatase are fungi and bacteria, although plants and animals also produce this enzyme. The activity of this enzyme was from 0.028 μg pNP·g⁻¹·h⁻¹ (location 6) to 0.151 μg pNP·g⁻¹·h⁻¹ (location 1). The highest enzyme activity in the soil was found in soil from town center 1 (location 3), where the dehydrogenase activity (114.5 mg TPF·g⁻¹·24 h⁻¹), FDA (51.26 μg F·g⁻¹·h⁻¹), and β -glucosidases (4.833 μg pNP·g⁻¹·h⁻¹) were determined to be high. The activity of arylsulfatase was lower (0.069 μg pNP·g⁻¹·h⁻¹) in this location. It was found that the activity of enzymes in various research centers is influenced by microenvironmental conditions. The studies did not obtain a correlation between enzyme activity and the content of trace elements; similar results were obtained Bream et al. [57].

The reactions of enzymatic activity to heavy metals are very variable in the soil; they depend on differences in the enzymes’ structure and function, but also on the soil properties and on the properties of heavy metals and their concentration [58]. Environmental factors such as soil moisture, oxygen availability, pH, organic matter content, temperature, season, heavy metal pollution, and soil fertilization affect the soil enzymatic activity in the soil environment [59].

Enzymatic reactions are site-specific and depend not only on the level of pollution but also on the abiotic and biotic properties of the soil. Natural parameters (e.g., seasonal changes, geographic location, in situ distribution, physical–chemical properties, and the content of organic matter and clay) usually affect the enzyme activity level by influencing both the production of enzymes by plants and microorganisms and their persistence under natural conditions. According to Olagoke et al. [60], their adsorption is important for enzyme activity. The adsorption of extracellular enzymes to soil minerals protects them against degradation while modifying their activity. Based on the inverse relationships between the amount of adsorbed enzyme and the specific activity of the enzyme and its stability, it was shown that the limited availability of sorption sites is important for high specific activity and stability of enzymes. This is probably a consequence of the smaller and weaker number of bonds compared to the high availability of sorption sites, which results in a smaller effect on the active sites of the enzyme. This concept resulted in a correlation between the activity of dehydrogenases and the clay content (

Table 9. Correlation coefficient (r), and linear regression models for selected properties of soils and flowers S. nigra of Bydgoszcz agglomeration.

Variables Dependent (y)	Variables Independent (x)	Regression Equation	r
FDA *	clay	y = 55.787− 10.13x	−0.847
GLUC	Fet	y = −1.312 + 0.77744x	0.864
FDA	DHA	y = −140.5 + 4.9580x	0.759
pH	Mna	y = 4.5106 + 0.01064x	0.792
Fet	TOC	y = 0.55936 + 2.6055x	0.899
Fea	TOC	y = 3.3644 + 0.02440x	0.843
Zntg	TOC	y = 507.853 + 207.646x	0.927
Mnt	sand	y = 114.37 − 10.142x	−0.811
Mna	sand	y = 75.516 − 0.4476x	−0.799
Mntg	sand	y = 769.73 − 7.920x	−0.873
Mnt	clay	y = 17.700 +7.1084x	0.807
Mntg	clay	y = 98.346 + 49.848x	0.788
Mnt	silt	y = 51.61+8.4979x	0.765
Mntg	silt	y = −24.63 + 8.6796x	0.898
Mnt	Znt	y = −7.061+ 0.60741x	0.839
Mna	Znt	y = 14.802 + 0.17633x	0.933
Zna	Znt	y = 4.7889 + 7.1827x	0.959
Znf	Znt	y = −67.98 + 3.3656x	0.861
Mna	Mnt	y = 10.154 + 0.12943x	0.945
Cua	Cut	y = 0.37264 + 0.19391x	0.939
Cuf	Cut	y = 0.20306 + 0.14869x	0.889
Znf	Zna	y = −6.720 + 0.39380x	0.755
Cuf	Cua	y = 0.20306 + 0.14869x	0.947

* FDA—fluorescein diacetate hydrolysis activity; DHA—dehydrogenase activity; GLUC—β-glucosydase activity; ARYL—arylsulphatase activity; TOC—total organic carbon in soil; Zn_t—total Zn in soil; Cu_t—total Cu in soil; Mn_t—total Mn in soil; Fe_t—total Fe in soil; Zn_a—available Zn for plants; Mn_a—available Mn for plants; Cu_a—available Cu for plants; Fe_a—available Fe for plants; Zn_tg—total content Zn in parent material; Cu_tg—total content Cu in parent material; Mn_tg—total content Mn in parent material; Fe_tg—total content Fe in parent material; Zn_f—total Zn in flowers of S. nigra; Cu_f—total Cu in flowers of S. nigra; Mn_f—total Mn in flowers of S. nigra; and Fe_f—total Fe in flowers of S. nigra.

). In our results, a correlation between dehydrogenases and FDA activity (Table 9, Figure 4) has been observed. This result suggested that the oxidoreduction reactions were connected with hydrolized organic matter (Figure 4). The relationship shows that the Mn_t content in soil was dependent on silt (r = 0.765) and Zn_t (r = 0.839) content. In nutrient available for plants, a relationship was observed between the content of Mn_a in the soil and Zn_t (r = 0.933) and Mn_t (r = 0.945). However, note that all analyses were performed on originating samples from seven selected locations from the city area of Bydgoszcz (Poland) and its surroundings; therefore, the generalizability of the results is also limited. In order to conduct a thorough analysis, the number of surveyed locations should be increased.

PCA analysis made it possible to determine general relationships between variables and to describe and classify parameters determined by other variables, which allowed for the determination of two main components (PC1 and PC2), which were responsible for over 67% of the variability observed in the soil (

Table 10. Values of the two extracted factor loadings (25 elements).

Parameters	Components Matrix
	PC1	PC2
DHA *	0.23915	−0.824650
FDA	−0.36749	−0.887678
GLUC	0.23677	−0.935761
ARYL	0.28964	0.614312
pH	0.83626	−0.060163
TOC	0.56495	−0.596703
sand	−0.81542	−0.507023
silt	0.79282	0.480383
clay	0.66632	0.641000
Znt	0.85912	−0.219253
Cut	0.61833	0.182219
Mnt	0.88887	0.083688
Fet	0.56613	−0.784938
Zna	0.79600	−0.009938
Cua	0.57873	0.159622
Mna	0.94888	0.016539
Fea	0.40328	−0.533773
Zn tg	0.60388	−0.531174
Cutg	0.52577	−0.217531
Mntg	0.53037	0.658673
Fetg	0.37308	−0.839651
Znf	0.93802	−0.184858
Cuf	0.69487	0.286634
Mnf	0.44820	−0.071375
Fef	0.29304	0.159350

* FDA—fluorescein diacetate hydrolysis activity; DHA—dehydrogenase activity; GLUC—β-glucosydase activity; ARYL—arylsulphatase activity; TOC—total organic carbon in soil; Zn_t—total Zn in soil; Cu_t—total Cu in soil; Mn_t—total Mn in soil; Fe_t—total Fe in soil, Zn_a—available Zn for plants; Mn_a—available Mn for plants; Cu_a—available Cu for plants; Fe_a—available Fe for plants; Zn_tg—total content Zn in parent material; Cu_tg—total content Cu in parent material; Mn_tg—total content Mn in parent material; Fe_tg—total content Fe in parent material; Zn_f—total Zn in flowers of S. nigra; Cu_f—total Cu in flowers of S. nigra; Mn_f—total Mn in flowers of S. nigra; and Fe_f—total Fe in flowers of S. nigra.; In bold is statistical significance.

).

Based on Figure 4, it can be concluded that the vectors of variables representing the physical properties of the soil are pH (0.836), sand (−0.815), and silt (0.793); content in the soil of Mn_t (0.889) and Zn_t (0.859); and content in the soil of Mn_a (0.949), Zn_a (0.796), and Zn_f (0.938), grouped according to the first principal component, which is responsible for the percentage of all of the variables. Factor 2 (PC2) showed a high negative correlation with the activity of the enzymes β-glucosidases (−0.936), DHA (−0.825), and FDA (−0.888) and a positive correlation with the content of Fe_t (−0.785) and Fe_tg (−0.840) (Table 10). By analyzing the soil properties, it can be concluded that the content of Cu_t and Zn_t in the soil and their forms available for plants, as well as DHA activity, correlates most closely with the content of organic matter. DHA plays a key role in the biological oxidation of soil organic matter by transferring hydrogen from organic substrates to inorganic acceptors. A comparison of locations 3 to 6 demonstrates that the soils contained similar contents of Fe_t and TOC and similar levels of dehydrogenase, glucosidase, and FDA (Figure 4).

4. Conclusions

Monitoring of elderberry flowers from the Kuyavian-Pomeranian province (Poland) showed that heavy metals such as Zn, Cu, Mn, and Fe are present in plant tissues. It is worth paying attention to the Zn content in flowers from some locations because they exceed the permissible value. Heavy metal contamination was not recorded in the investigated soils. The total metal content of the soil samples can be ordered as follows: Cu < Zn < Mn < Fe. The highest percentage of mobile metal forms in their total content was for copper. The enrichment factor values indicate a low accumulation (minimum enrichment > 1.5) of Cu and Mn in the surface layer of the investigated soils at locations 1 and 5 compared to the geochemical background content. However, the values of the bioaccumulation factor indicate that elderberry flowers have accumulated Cu and Zn the most.

Flowers from sites with a high frequency of road traffic were characterized by a greater number of elements (location 1, 3–7) than from areas away from busy roads (location 2). The correlation analysis showed that Cu and Zn contents were highly correlated in the flowers of elderberry as compared to the corresponding soils. Depending on the environmental conditions, the values of BCF varied highly depending on the trial element and were >1 for Zn and Cu, while they were <1 for Fe and Mn.

Taking into account that the average concentration of Zn in crop plants ranges from 10 to 100 mg∙kg⁻¹ dry matter (according to the WHO), it can be concluded that the Zn content only in flowers from habitats 1, 2, and 7 met the conditions specified in the standard for herbs used in herbal medicine (<50 mg·kg⁻¹).

The level of soil enzymatic activity in the tested soils varied within wide limits but clearly depended on their location. The highest enzyme activity in the soil was found in soil from town center 1 (location 3), where the DHA, FDA, and GLUC activity was determined to be high, and in the soil from residential area 2 (location 3), the DHA and FDA activity was determined to be high. The content of Cu_t and Zn_t in the soil and their forms available for plants, as well as the DHA activity, correlates most closely with the content of organic matter.