Biologically Active Substance Content inEdible Plants of Zakarpattia and TheirElemental Composition Model

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Tamara Meleshko, Roman Rukavchuk,

Larysa Buhyna, Oleksandra Pallah,

Sergii Sukharev, Volodymyr Drobnych &

Nadiya Boyko

Biological Trace Element Research

ISSN 0163-4984

Biol Trace Elem Res

DOI 10.1007/s12011-020-02345-y

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Biologically Active Substance Content in Edible Plants of Zakarpattia

and Their Elemental Composition Model

Tamara Meleshko1,2 & Roman Rukavchuk2 & Larysa Buhyna2 & Oleksandra Pallah1,2 & Sergii Sukharev3 &

Volodymyr Drobnych4 & Nadiya Boyko1,2

Received: 3 July 2020 /Accepted: 12 August 2020

# Springer Science+Business Media, LLC, part of Springer Nature 2020

Abstract

Consumption of edible plants satisfies a significant part of human body needs in macro- and micronutrients while biologically

active substances contain strong antioxidant properties and reduce the risk of a number of diseases. Balanced nutrition and design

of personalized diets and treatment rely on the data on the content of macro- and micronutrients and biologically active

substances. We determined polyphenol and anthocyanin content in 22 species of local edible plants using modified spectropho-

tometric method with Folin–Ciocalteu reagent as well as chemical elements’ content in a mixture of edible plants from 13 regions

using standard procedures. We performed correlational analysis of the obtained data and analysis of the main components in

OriginLab, developed regional models of chemical elements’ content for a mixture of edible plants, and conducted cluster

analysis using common tools in Python. The results of biologically active substances’study demonstrated that the highest content

of polyphenolic compounds and anthocyanins was found in grape meal of Vitis vinifera L. The study of chemical elements’

content demonstrated that edible plants from lowland areas are the best and revealed clear dependences of the elements on each

other and geographical conditions. The analysis of the principal components confirmed this finding. Based on the obtained data, a

number of regional models of chemical elements’ content in a mixture of edible plants were built, tested, and evaluated. Obtained

results are the basis for designing various diets, filling composite databases of the region’s food, and creating the newestbiologics—pharmabiotics.

Keywords Polyphenols . Anthocyanins . Trace elements . Regional models . PCA

Introduction The normal functioning of the human body depends on a number of factors, including the state of environment and  balanced diet, which involves the intake of various biologi- cally active substances (BAS) and chemical elements. The  necessary chemical elements include macro- and micronutrients. Regarding the latter, essential (vital) ones play the most important role; they include iron (Fe), copper (Cu), zinc (Zn), manganese (Mn), molybdenum (Mo), cobalt (Co), and iodine (I). An important role is also played by selenium (Se) and fluoride (F), which are probably essential elements and bromine (Br), which is physically promotive trace element [1]. Such elements as arsenic (As), lead (Pb), and mercury (Hg) are considered potentially toxic [2]. While drinking water, a person satisfies the daily need for I, Cu, Zn, Mn, Co, and Mo by 1–10%, and mostly satisfies the need for F. The main source of other macro- and micronutrients is food. Foods of plant origin constitute a significant part of  human diet, which is of great importance for preventing var- ious diseases [3–5]. Local food plays a special role as it is  the basis for respective local diets [6]. This fact has caused  significant interest towards it in terms of chemical composi- tion, because without the knowledge of the latter, it is  * Roman Rukavchuk roman.rukavchuk@uzhnu.edu.ua 1 Department of Clinical Laboratory Diagnostics and Pharmacology, Faculty of Dentistry, Uzhhorod National University, Universytetska st. 16a, Uzhhorod 88000, Ukraine 2 Research Development and Educational Centre of Molecular Microbiology and Mucosal Immunology, Uzhhorod National University, Narodna sq. 1, Uzhhorod 88000, Ukraine 3 Department of Ecology and Environmental Protection, Faculty of Chemistry, Uzhhorod National University, Pidgirna st. 46, Uzhhorod 88000, Ukraine 4 Department of Land Management and Cadaster, Uzhhorod National University, Universytetska st. 14, Uzhhorod 88000, Ukraine Biological Trace Element Research https://doi.org/10.1007/s12011-020-02345-y  Author's personal copy  impossible to create balanced and adequate personalized di- ets [7, 8]. A recent trend also assumes the use of BAS of  plant origin, which mainly involve vitamins and antioxidants (polyphenols, anthocyanins, etc.) [9], to design modern drugs, that is, prebiotics and synbiotics [10, 11]. The reason is that polyphenols and anthocyanins of plant origin affect various important processes in the human body, including such fundamental ones as gene expression, production of enzymes and hormones, receptor activation, and immune and antioxidant processes [12]. The use of data on chemical composition and BAS for the development of personalized nutrition and treatment is a non-trivial task and can be implemented only with the use of modern information technologies, including information  systems, namely geographic information systems. The rea- son is that, as it is known, the content of micro- and  macroelements in food depends on the geochemistry of the area where it was obtained [13], and for BAS, it is well  known that their content depends on geographical and cli- matic conditions [14, 15]. It is also obvious that the content  of chemical elements, as well as BAS, depends on the season [16], directly relates to the quality of plants, and is often a critical factor in plants’ selection and practical  use. Such a situation creates a need for the search of “geo- graphical” patterns. However, they are still insufficiently  studied, even for small regions and elemental compositions though the latter is an ideal object for solving this problem due to their simplicity and better state of knowledge. One of the reasons for the lack of study is that it is necessary to consider a number of different indicators, including soil and water. However, with the development of data science  and improvement of data analysis methods, it became pos- sible to reveal these patterns, reduce the number of param- eters, and build various models that could measure the  content of macro- and micronutrients in plants with high reliability. Today, various methods are successfully used for this purpose, including principal component analysis (PCA) [17, 18]. However, these models do not cover Zakarpattia region and usually focus on individual plants, which are generally not typical for the region in terms of both consumption and cultivation. Our group has recently studied the elemental composition of water in 13 Zakarpattia districts [19], which revealed the presence of chemical composition correlations. The current article continues the latter studies, but regards the content of BAS in plants and identification of the most essential patterns of edible plants’ elemental structure. The purpose of this work is to determine the patterns of elemental composition of edible plant characteristic of Zakarpattia region, determine the gross content of BAS, and develop a model that would allow, based on several parameters, obtaining data on the content of macro- and micronutrients in edible plants.  Materials and Methods Biologically Active Substance Determination  The gross content of polyphenols and anthocyanins from sev- en districts of Zakarpattia region, namely Uzhhorod,  Mukachevo, Perechyn, Irshava, Berehiv, Volovets, and Mizhhirya districts, was determined for 22 species of local edible plants (Table 1).  The gross polyphenol content and the number of anthocy- anins were measured spectrophotometrically using Folin–  Ciocalteu reagent [20], and in modification [21], the number of each sample’s measures was 5 (n = 5); 96% ethanol was used as extractant. Determination of the gross content of biologically active substances relied on measuring the value of optical density at 765 nm and comparison with a standard scale of gallic acid and cyanidin-3-rutinoside. Interpretation of the results was performed taking into consideration sugar content in each test sample [22]. Macro- and Microelement Determination Studies of macro- and microelement composition of edible plants were conducted for all landscape areas of Zakarpattia region. Mountain (three districts: Rakhiv, Mizhhirya, Volovets), foothill (six districts: Svalyava, Tyachiv, Velykobereznyansky, Perechynsky, Irshavsky, Khust), and lowland areas (four districts: Uzhhorod, Mukachevo, Berehiv, Vynohradiv) were covered (Table 2).  Samples of edible plants’ mixture (potatoes; white cab- bage; beets; onions = 3:1:1:0.5) were prepared for each district  using different households, by averaging 10 samples after  grinding. The samples were homogenized. The ratio of mix- ture components was selected based on consumption require- ments while considering the reference diet of Zakarpattia  dwellers. Dry sample preparation was used to determine metals and wet mineralization was performed to determine nonmetals.  All reagents used in the experiment had respective analyt- ical purity; double distilled water was used as the main sol- vent. Standard procedures were used to identify  micronutrients in foods [23]. Standard solutions for calibra- tion curves’ construction (identification of As, Ca, Co, Cu, Fe,  Pb, Mg, Mn, Mo, Se, and Zn) were obtained via diluting a commercial standard stock solution (SPEX QC-21, USA).  The total content of microelements in food products was mea- sured. Identification of Cu, Zn, Fe, Pb, Mn, Mo, and Co (elec- trothermal technique: graphite cuvettes, chemical modifier Pd  (NO3)2, Hg (method of “cold” steam), As (hydrogen genera- tion method)) was conducted using atomic absorption spec- troscopy. In experimental conditions, the following wave- lengths were applied, nm: Cu - 324.8, Zn - 213.9, Fe -

248.3, Mn - 279.5, Mo - 313.3, Co - 240.7, Pb - 283.3, Hg - 253.7, and As - 193.7. Such instruments as AAS vario® 6 (Analytik Jena AG, Germany), hydrogen generator (Varian VGA-76, USA), and ultrapure Pd (NO3) 2 (Suprapur®, Merck, Germany) were used. Flame atomic emission spectroscopy was used to identify Ca and Mg (wavelength, nm: Ca - 434, Mg - 385; FPA-2-01,  LLC Labtime LTD, Russia). Potentiometry was used to deter- mine F- and Br- (SevenCompact S220, Mettler Toledo, USA),  inversion voltammetry to determine iodine (Ecotest-VA-io- dine, Russia), spectrofluorimetry to determine Se (abs = 378  nm, em = 520 nm, Hitachi F-7000, Hitachi Ltd., Japan), and spectrophotometry to determine P (Shimadzu UV-1800, Shimadzu Co., Japan). Cluster Analysis and BAS Data Comparison Data on the state of environment were obtained from the  National Atlas of Ukraine [24]. Data binding and manipula- tion, as well as GIS design, were performed in GIS  environment - ArcGIS Desktop 10.6. For most tasks, we used standard tools of this environment and database management system (DBMS) MS Access. Comparison of data available on BAS was conducted using the known literature search databases PubChem (https:// pubchem.ncbi.nlm.nih.gov) and Google Scholar (https:// scholar.google.com.ua/), as well as specialized databases dedicated to the content of BAS, such as ePlantLIBRA (http://eplantlibra.eurofir.org/Default.asp), Phenol-Explorer (http://phenol-explorer.eu/), and USDA Special Interest Database on Flavonoid (https://data.nal.usda.gov/dataset/ usda-special-interest-databases-flavonoids). Statistical Analysis Statistical analysis of the experimental results was performed using the OriginLab 2017 software, version 94E (OriginLab Corporation, USA, 2017). Pearson and Spearman correlation  coefficients were used to discover correlations. For data pro- cessing tasks, Python programming language and the known

Data Science libraries, such as PyPlotLib, MatPlotLib,  Pandas, and Scikit-Learn, were also used. p < 0.05 was con- sidered significant.  Results The highest content of polyphenolic compounds was found in grape meal of Vitis vinifera L., in particular in the grape meal of Cabernet Sauvignon (8.245 ± 0.256 mg/g) and Isabella (2.663 ± 0.081 mg/g) grown on the territory of Uzhhorod District, and the lowest content was found in Armoracia  rusticana Gaertn., Mey. et Scherb. (Fig. 1). Regarding sum- mer grasses, the highest content of polyphenols was found in  Apium graveolens L. leaves and roots (1.733 ± 0.052 mg/g) while Anethum graveolens L. and Petroselinum crispum  (Mill.) leaves contained almost the same number of polyphe- nols: 0.636 ± 0.019 mg/g and 0.758 ± 0.023 mg/g respective- ly. For anthocyanins, namely cyanidin 3-glycoside, the  highest content was found in Cabernet Sauvignon meal (6.057 ± 0.174 mg/g) and the lowest one in Rubus idaeus L. (0.072 ± 0.002 mg/g). The studied edible plants are rich in Fe, Cu, Mn, Mo, P, As, and F and contain Co, Se, I, Br, and Ca in small quantities. For instance, a mixture of edible plants (potatoes; white cabbage; beets; onions) contains iron in the amount of 3.92–7.81 mg × kg−1 , copper in the amount of 0.62–1.32 mg × kg−1  , manga- nese in the amount of 1.19–3.32 mg × kg−1  , molybdenum in  the amount of 0.05–0.109 mg × kg−1  , phosphorus in the  amount of 334–438 mg × kg−1  , and fluorine in the amount  of 0.092–0.228 mg × kg−1  . At the same time, it contains much smaller amounts of cobalt (0.018–0.053 mg × kg−1 ), selenium  (0.0031–0.0111 mg × kg−1  ), iodine (0.006–0.051 mg × kg−1 ),  bromine (0.102–0.246 mg × kg−1  ), and calcium (118–241 mg  × kg−1 ) (Fig. 2). The highest amounts of Fe, Zn, and Co and the lowest amount of Mn were found in the mixture from Berehiv District. Meanwhile, the lowest amount of all other metals is characteristic of edible plants of Rakhiv District. The largest amount of Cu was contained in the mixture from Vynohradiv District (1.32 ± 0.10 mg × kg−1  ), and of Mo from  Uzhhorod District (0.117 ± 0.008 mg × kg−1 ).  The total amount of polyphenols in Vaccinium myrtillus L. selected from Perechyn and Mizhhirya districts differs significantly. In fruits from Perechyn District, the gross content of polyphenolic compounds accounted for only 2.79 ± 0.084 mg/g, while in fruits grown in Mizhhirya District, polyphenols’ content was three times higher and amounted to 4.216 ± 0.126 mg/g. The difference in the gross content of polyphenolic compounds is also present in Rubus idaeus L. selected from Mukachevo and Volovets districts. Polyphenol content was measured in farm fruits (0.182 ± 0.005 mg/g) and wild fruits (0.273 ± 0.008 mg/g). Thus, the content of polyphenols in wild fruits is higher.  Existing differences also indicate that there are certain geo- graphical dependencies. Such dependencies are also ob- served with regard to the data on the elemental composi- tion of a mixture of edible plants. Edible plants from low- land areas are the richest in metals while plants from  mountainous areas are the poorest except Mn demonstrat- ing the reverse situation. The same is observed with regard

to non-metals’ content. Their highest amounts (P, Se, I, and Br) were observed for the mixture of Vynohradiv District and Berehiv District (for F) while the lowest amount was observed for Rakhiv District, except for As  demonstrating the reverse situation. Regarding macronutri- ents Ca and Mg, the trend of lower amounts in mountain- ous areas and higher in lowlands is typical for them too.  For example, the highest content of Ca and Mg is charac- teristic of edible plants of Berehiv District and the lowest  of Rakhiv (Ca) and Mizhhirya (Mg) districts. The data obtained on the chemical element content in the  mixture of edible plants were analyzed using correlation anal- ysis demonstrating that experimental data are characterized by  strong correlations of most of the measured indicators and the absence of statistically insignificant correlations (p < 0.05) (Fig. 3). Such a situation assumes the presence of a certain set of indicators that are “basic” and on the basis of which, it is possible to build a certain model. In this case, one of the most popular methods of further data analysis is PCA, which we also used. As we have 13 sampling sites, the maximum number of principal components in the analyses was 13. The PCA analysis demonstrates that experimental data are characterized by an extremely important role of the first principal components in explaining these data’s variance (Table 3). The fact that the first main component  PC1 explains more than 80% of the original data’s disper- sion assumes the presence of an important feature, namely  direction (axis) in the 16-dimensional space of measured parameters, which explains a significant part of dispersion of the original data. That is, those baseline indicators playing a crucial role in PC1 formation significantly affect each other. Obviously, apart from PC1, this applies to other major components, which explain a significant percentage of the total variance of the original data. The current state of data science allows for direct use of such patterns (without their prior “classical” study) to solve practical problems. In our case, such a task (and a  very relevant one, for example, in the context of devel- opment of personalized nutrition based on local plants)  may assume measurement of various chemical element contents—based on the concentration of one or more of them—in the new plant samples taken from anywhere in the region. Existence of these regional patterns provides a possibility to solve this problem while PCA method allows for creation of a simple model for fulfillment of this possibility. In mathematical terms, this model relies on obtaining and further use of the load matrix P, calculated within the PCA based on a set of chosen experimental data. This  matrix, when the data is regionally representative, is a re- gional model of relationship of baseline indicators (chem- ical element content) and main components (PC1, PC2,  etc.). Herewith, it regards all samples from this area, in- cluding new ones. For instance, X is a matrix of original  data subjected to the well-known autoscale procedure [25],

leaving only the ones having the highest values of pairwise

Pearson correlation coefficients, that is, Fe, Zn, Co, Pb, Mg, P,

and Se. Regional matrix P, obtained for these indicators (ac-

cording to experimental data on 13 above samples), with the

maximum possible number of principal components in this

case A = 7, is presented in Table 4.

We studied the properties of the three models of chemical

element content in edible plants based on this matrix and accord-

ing to the choice of A = 3 or A = 2 or A = 1 (that is, the task of

obtaining concentrations of all seven elements in a new plant

sample based on the measured content of three or two or one

of these elements). It was found that in all cases, the accuracy of

fulfilling the task strongly depends on the choice of those ele-

ments, and the content of which determines the concentrations of

other elements. A method of optimal selection was developed

and it assumes calculation (according to the elements of matrix P

and information from Table 4) of the rate of participation in the

first principal components’ formation (three or two or one for A =

3 or A = 2 or A = 1 respectively) for each of the baseline indica-

tors. It was found that for A = 3, the optimal choice is Pb, Co, and

Se; for A = 2 - Pb and P; and for A = 1 - Co.

Finally, for all three models of elemental composition de-

termination, their errors were measured, that is, the difference

(percentage difference) between the exact chemical element

content and the calculated one. For A = 3, A = 2, and A = 1, the

average absolute values of these errors were 3.1%, 4.5%, and

7.4% respectively.

We also performed cluster analysis of the obtained data

based on the results of PCA analysis and using the data on

the state of environment available in the National Atlas of

Ukraine including the following:

& Precipitation map;

& Map of humus content;

& Soil erosion;

& Humus stocks;

& Humus content in the soil;

& Iodine content in groundwater;

& Acidity of precipitation;

& Anthropoecological assessment of total pesticide load on

soils;

& Soil environment reactions (pH);

& Soil fertility;

& Average air temperature;

& Average soil temperature as of January and July;

& Total solar radiation;

& Sunshine duration;

& Soil quality.

Clusters were best formed for anthropoecological assess- ment of total pesticide load on soils and soil quality (Fig. 4).  For indicators “humus stocks” and “humus content in the soil,” clustering is impossible as we have only one selected sample with a different dimension, that is, belonging to a different data category (for instance, 12 samples have humus stock at the rate of 1–2% and the 13th one at the rate of 2–3%). In addition, it is impossible to identify clusters for such data as soil acidity and alkalinity; average air temperature; soil surface temperature, July; and soil surface temperature, January.  Discussion It is well-known that plants are used to treat and prevent many diseases for ages (Table 5). Nowadays, we know that BAS is  one of the reasons for such effects. Polyphenols, antocianins, and flavonoids are the most studied BAS. We determined content of polyphenols and antocianins but not flavonoids. Flavonoids are mainly quercetin flavonoids such as quercetin, morin, and rutin. Quercetin flavonoids account for about 0.4– 0.6% (depending on plant species) of the total number of  polyphenolic compounds. For their detail content determina- tion, other methods such as HPLC should be used [27].  Plant-derived BAS have strong antioxidant effects, and are secondary metabolites, and their content in plant products  reduces the risk of a number of diseases, including cardio- vascular disease, specific forms of cancer [46], and neurode- generative diseases [47]. In particular, a group of polyphe- nols known as flavonoids has been closely associated with  beneficial effects within many human-, animal-related, and in vitro studies [48]. Therefore, they are often considered a basis for the creation of new biologics and for the adjustment of human microbiota in general. Herewith, local plants are  the most important ones because they are most often con- sumed in a particular region. Therefore, to measure gross  polyphenols’ content and total anthocyanins’ amount, we selected the most typical edible plants for Zakarpattia region.

Similar studies on BAS content were conducted for different regions of Ukraine and for different plants [49–51]. However, they did not cover such a large number of plants, especially in Zakarpattia region. In the world, similar studies  were performed for a significant number of plants. For ex- ample, obtained data on polyphenol and anthocyanin content  from three well-known databases in this area, namely ePlantLibra, Phenol Explorer, and USDA Special Interest Databases on flavonoids, involved 4262 unique entries in the table for 373 different BAS from 181 sources. After filtering the necessary data according to such criteria as plant part, data inaccuracies or absence, and data on polyphenol  and anthocyanin content, we obtained 2654 records. However, comparison of these results is a difficult task due to a large number of different measurement methods and,  therefore, there is a need to reduce results to a single dimen- sion [52]. Phenol-Explorer tries to solve this problem, but as  the content of BAS depends on a large number of different factors, data obtained in this system, namely the average values from different sources, has significant SD values. For example, for blackberry, the average content of (-)- Epicatechin (according to two sources) is 11.48 mg/100 g and its SD = ± 10.90. Similar situation is true for other data and indicates significant differences in the values of the  Table 5 Ethnopharmacology utilization of selected plants Plant specie Ethnopharmacology utilization  Rubus idaeus L. Anti-inflammatory and antipyretic agents in the treatment of flu-like infec- tions [28].  Rubus fruticosus L. Fruit juice has been used to treat asthma, colitis, and anemia. Jams, prepared without sugar, have been used to cure throat ailments in children and anti-diarrhea [29].  Ribes nigrum L. Fruits have been used as diuretic and diaphoretic, and they help to increase bodily resistance to infections and are a valuable remedy for treating colds and flu. Juice is used to stem diarrhea and calms indigestion [30, 31]. Ribes rubrum L. Leaves have been used due to their diuretic and diaphoretic effects, to ease the symptoms of rheumatic diseases and reduce the pain of dislocations. Fruits used as antiscorbutic, aperient, depurative, digestive, diuretic, laxative, refrigerant, and sialagogue [30, 32] Prunus avium (L.) L. Used as bechic, astringent, diuretic, and tonic [30, 33–35]. Prunus cerasus L. Fruits are used in the urinary system to cure number of diseases such as urinary tract infection, nephrolithiasis, cystolithiasis, and dysuria [36]. Vitis vinifera L. Fruits are used as cardiotonic and for the treatment of cardiovascular diseases. Dried grape products are also applied for memory problems, which are linked to the pathology of brain microvessels [37]. Vaccinium myrtillus L. Mostly knows for improving vision, antidiabetic effect [38]. Petroselinum crispum (Mill.) Parsley has been used as carminative, gastro tonic, diuretic, and antiseptic of urinary tract, anti-urolithiasis, anti-dote, and anti-inflammatory and for the treatment of amenorrhea, dysmenorrhea, gastrointestinal disorder, hypertension, cardiac disease, urinary disease, otitis, sniffle, diabetes, and also various dermal disease in traditional and folklore medicines [39]. Morus alba L. Ethnopharmacological surveys have listed out its uses in treating diabetes,  atherosclerosis, cancer, and throat irritation [40, 41].  Anethum graveolens L. Hydrochloric extracts of dill fruit were used as a traditional medicine for treating gastrointestinal disorders. Seeds used for the treatment of jaundice in liver, spleen, and rheumatism disorders and other inflammatory gout diseases [42].  Apium graveolens L. Various plant parts such as seeds, leaves, stem, roots, and essential oils are widely applied in traditional medicine to treat several ailments such as hypertension, diabetes, asthma, gastrointestinal infections, bronchitis, and hepatitis [43].  Ribes × nidigrolaria Used to prevent cardiovascular diseases, cataracts, against signs of aging,  increase immunity.  Prunus cerasifera Ehrh. Known for its antibacterial and antifungal effect [44]. Armoracia rusticana Gaertn., Mey. et Scherb.  It is traditionally used for treatment of sinus infections, bacterial infections of the respiratory tract, urinary bladder, and gastrointestinal systems, festering wounds and ease pain such as pain associated with sciatica and rheumatism [45]. Biologically Active Substance Content in Edible Plants of Zakarpattia and Their Elemental Composition Model Author's personal copy  content of certain BAS in the studies of different authors,  which makes it impossible to adequately use these data with- out taking into account additional factors, with factors related  to geographical conditions playing a special role. Their large  number and large variety make it almost impossible to ade- quately compare data without considering them. Therefore,  the problem remains unresolved. In addition, the solution of this problem is relevant not only for polyphenols, but also for other BAS [53]. Given that selected edible plants form the basis of Zakarpattia dwellers’ diet (about 68%) and are the main source  of Fe, Cu, P, and Mn, the study of their macro- and micronu- trient composition is extremely important. Micronutrient con- tent in the mixture for different landscape areas significantly  differs. Generally, a mixture from lowland areas is richer in  microelements (except As and Mn) than a mixture from foot- hills and mountainous areas. Thus, edible plants from lowland  areas of Zakarpattia region are more valuable sources of micronutrients for humans. However, these dependencies are  still unknown and non-trivial. And, obviously, they have de- pendencies similar to those characteristic of BAS.  Development of various methods and techniques of data analysis and Big Data in recent years has stimulated the search for a solution of the problem of identifying patterns of BAS and macro- and microelement contents in edible  plants depending on geographical conditions. The well- known database ePlantLibra contains certain geographical  data on plants selected for analysis. However, since research  results are obtained from literature, these data are not exhaus- tive and are often insufficient for a complex and comprehen- sive analysis. Regarding the main source of macro- and  micronutrients for edible plants, namely composite foods, such data are completely absent. However, it is obvious that the content of macro-and microelements in plants depends  on pollution and the general state of environment. Such pat- terns could be revealed through data from systematic moni- toring of a large number of indicators. However, this requires  much research and the larger the area, the more data is need- ed to identify patterns and build a variety of models.  Therefore, most of the literature-based data either cover a small set of local indicators, or are presented in the form of ranking data, as it is in the case of the National Atlas of  Ukraine we used. In order to solve this problem, it is impor- tant to create various complex monitoring systems [54].  However, such systems still remain at the initial creation stage [55]. Meanwhile, data for their creation are usually not publicly available. Therefore, conducting a variety of complex types of data analysis and revealing patterns for small regions are simpler and urgent tasks. In particular, having conducted correlation analysis of the obtained data, we saw a unique result, because a significant number of indicators are statistically significant and strongly correlate with each other. This fact can be clearly  seen by comparing the results with previously published data on water [19]. This, as noted above, encouraged us to practically apply the identified patterns by creating respective regional PCA  models. Such models enable us to select a small set of indica- tors, and in our case, it is sufficient to use two indicators, that  is, Pb and P, which can help find the content of the other five  chemical elements. Herewith, as mentioned above, the aver- age absolute value of the error does not exceed 4.5%. Of  course, the choice of a greater number of indicators provides  a higher rate of accuracy, and like in case 3, the average ab- solute value of the error will not exceed 3.1%, though, as we  can see, the difference (1.4%) is not that significant. If such  accuracy rate is not required, it will be sufficient to just mea- sure the content of one Co. The use of this model can signif- icantly reduce costs and the number of different studies. Such  models can be created and built for other regions and for other  sets of indicators, such as water and soil. However, their con- struction is possible only when there are clear patterns not  only in terms of correlations but also within PCA analysis. This is clearly evident in our data, because as a result of  PCA analysis, the data look extremely interesting. The prin- cipal components show what percentage of dispersion they  describe (Table 3). The first 4 principal components describe more than 94% of dispersion, and if the number of indicators is reduced to 7, the first principal component describes more than 92% of original data dispersion. The data obtained on the clustering of edible plants using environmental parameters are rather primitive as in this case, ranking indicators are used and the data set is rather small.  However, already at this stage, we can see promising indica- tors in terms of further research and the data obtained confirm  the above-considered dependence of elemental composition on zonation.  Conclusion Local edible plants of Zakarpattia region were studied with regard to BAS (polyphenols and anthocyanins) content and were selected based on our previous research on their impact on typical representatives of the intestinal and oral human microbiomes. Together, these studies helped identify the most promising of them for their use as components of biologicals, namely Vitis vinifera L. (fruits and grape meal). We studied the elemental content of a mixture of edible  plants most typical for Zakarpattia dwellers’ diet, which dem- onstrated that lowland plants are more promising and are a  full-fledged food source. A non-trivial analysis of the obtained data was performed. It revealed the presence of close patterns depending on the  region of cultivation. These data formed the basis for region- al PCA-model construction, which opens a possibility of  Meleshko et al.  Author's personal copy  further research on macro- and micronutrient composition of plants in Zakarpattia region with the use of a much smaller amount of resources.  The results obtained in this study are the basis for the con- struction of various diets for population, filling the composite  bases of food in the region and creating innovative biological products—pharmabiotics and introduction of personalized medicine in Ukraine. Funding Information This work was supported by the Ministry of Education and Science of Ukraine, grant no. 0120U102244 personalized  approaches to the diagnosis, prevention, and treatment of vascular dis- eases with prognostic modeling of individual atherosclerosis  development.

Compliance with Ethical Standards Conflict of Interest The authors declare that they have no conflict of interest. 

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