The optimization of a conventional extraction of bioactive compounds from Cornus mas by RSM and the determination of favourability factors by GIS technique

Rich in vitamins, polyphenols, carotenoids, carbohydrates, with a high antioxidant activity, cornelian cherry (Cornus mas) is one of the 65 species of Cornaceae family, fruits that are used in food industry, cosmetic industry or homeopathic medicine. The valuable bioactive compounds and the high economical potential of this tree makes suitable to be considered as a raw material to study the optimum extraction conditions in order to maximize the bioactive compounds’ concentration. In this study, the main purpose was to investigate both the favourable and restrictive conditions for Cornus mas using the GIS technique. The Remote Sensing and Geographic Information Systems (GIS) technique indicated the favourability factors for Cornus mas trees in Romania country. The response surface methodology was employed to study the effect of temperature, time and solvent concentration on the flavonoids’ (TFC) and polyphenols (TPC) concentrations and the antioxidant activity values. The maximum concentration of TPC (24.70 mg GAE/g raw material) and TFC (1.36 mg QE/g raw material) were obtained with 60% ethanol concentration at different temperature and time values. The cube model with centred faces for the Box-Behnken central composition revealed the highest value of the concentration of TAA (101.31 mg TE/g raw material) at 100% ethanol concentration, 50 °C extraction temperature and the maximum extraction time of 30 min. The most relevant variable was the solvent concentration and the obtained results suggested that the central-face cube model (86% for TPC, 97% for TFC and 95% antioxidant activity) approximated the experimental data.


Introduction
The current climate changes such as the migration of some species towards higher altitudes, the drying of some forest species due to longer periods of drought, the increase of the sensitivity of forest species after snow damage, windfalls, drought, or identified soil erosion both globally and regionally have a major impact on the Soxhlet extraction (Dhanani et al., 2015;Altemimi et al., 2017;Dumitrascu et al., 2019).
C. mas fruits are used fresh or processed in food products, such as: jams, jelly, juices, liquor, marmalade, pestil (dried marmalade produced in Turkey), pekmez (syrup obtained in Turkey by fruit must), stewed fruit, syrups, tea infusions, wines (Güleryüz et al., 1998;Capanoglu et al., 2011;Sochor et al., 2014;Nizioł-Łukaszewska et al., 2018). Some fresh fruits of C. mas genotypes from Turkey have indicated a vitamin C content ranging from 36 to 122 mg/100 mL (Ercişli, 2004). Amongst the many benefits associated to humans health, cornelian cherry fruits are successfully used for: anaemia, cancer, diabetes, diarrhoea, fever, hyperlipidemia, gastrointestinal disorders, malaria, obesity, reducing intraocular pressure, urinary tract infections, as well as to have antioxidant and neuroprotective activity (Asgary et al., 2013;Szumny et al., 2015;Dinda et al., 2016). The cornelian cherry forest fruits were used as the whole plant by humans over the years due to geographical distribution.
The main purpose of this study was to achieve a collection of thematic maps for the national favourability classes for C. mas. Further the conventional extraction was performed in order to evaluate the optimum extraction parameters in regards to three different variables (temperature, time, and hydro alcoholic solution concentration) so as to maximize the total flavonoids' content (TFC), the total polyphenols' content (TPC) and the total antioxidant activity (TAA). Our research is important due to the high occurrence of C. mas at a national level as raw a material and also a good perspective for it to be use as food ingredients.

GIS technique
Considering the objectives of a study, GIS technology implementation is based on a spatial analysis considering of digital databases managed through the spatial analysis functions of geoinformation programs (Roșca et al., 2017).
This type of analysis techniques is used successfully in various studies to determine the most favourable agricultural crops (Islam et al., 2018;Matei et al., 2020), tree species (Beck et al., 2020) having the advantage of providing practical landscaping solutions at different scales of analysis taking into account the landscape and soil conditions but also depending on the market requirements (Zu et al., 2014). Spatial analysis allows the adaptation of crops to global climate change that imposes requirements adapted to new climatic parameters using the Analytic Hierarchy Process (AHP) system (Acharya et al., 2021) the bivariate statistical analysis (BSA) or the analysis expert knowledge (Bhandari et al., 2013). But this aspect involves specialized technical 3 knowledge, an interdisciplinary working group and the creation of a detailed database to understand the complexity of the involved ecological factors involved.
In our case, the first stage for the C. mas favourability determination was the acquisition of a database in a digital format (acquisition directly based on the spatial analysis sub models for the soil type and elevation, geological classes and the acquisition based on the implementation of the interpolation functions for the climatic factors).
The application of the actual spatial analysis based on the qualitative class determination through expert knowledge implies the granting of specific classes of favourability as well as the restrictiveness for the species studied within the entire territory of Romania (Table 1). It also implies as the final step -absolutely compulsory for the GIS models -the model validation stage (by directly comparing it to the reality from the field) in order to determine the predictability degree of predictability of the created model and the possible calibration of its parameters (Roșca et al., 2019). The validation of the results was performed through the comparison of the results obtained by applying the model developed in this study to frequency points reported in the European Atlas of Forest Species in Europe in the year of 2016.

Sample processing
The cornelian cherry fruits were collected from spontaneous flora from different village's hills of the Galati County, Romania, in September 2017. After being washed with distilled water, the fruits were blotted on paper towels and the stone of the fruits were removed. Afterwards, the fruits were freeze-dried (Christ Alpha 1-4 LD plus, Germany) at -42 °C under a pressure of 0.10 mbar for 72 h. In order to obtain a compact powder, after lyophilization, the fruits were grinded under domestic conditions and stored at 4 °C for further experiments. In addition, 100 fruits and stones of cornelian cherry were measured and weighed in order to make a correlation between them and the characteristics of the fruit collection area used in this study.
Conventional extraction method and the phytochemical characterization of the extracts The Design Expert software was used to analyse the influence of three different variables regarding the conventional extraction (CE) method (temperature 30-50 °C, time 15-45 min and ethanol concentration 60-100%). In order to maximize the BACs content, the BOX-Behnken model with 15 experiments was used and for each experiment 1 g of lyophilized raw material and 10 ml solvent were used. The total flavonoids content (TFC) was determined using a modified colorimetric method described by Turturică et al. (2016). The total polyphenols content (TPC) was determined using Folin-Ciocâlteu method, expressed as mg Gallic Acid Equivalent (GAE)/g raw material while the total antioxidant activity (TAA), expressed as mg Trolox/g raw material described as described by Vasile et al. (2020) and Oancea et al. (2017).
All the experiments were done using a water bath (Grant, OLS 200). All the measurements were replicated three times and the responses experimental values were expressed as the means.

Response surface methodology
The Response Surface Methodology (RSM) was applied to obtain the optimum conditions for the maximum extraction values of the TPC, the TFC and the TAA. The Box-Behnken design (BBD) was used to determine the optimum conditions for the CE method.
The coded and decoded values of the used independent variables used and their levels are shown in Table 1 and Table 2. The designs consisted of 15 randomized runs with three replicates at the central point and were analysed using the Design-Expert 6.0 Trial software (Stat-Ease, Minneapolis, Minnesota, USA) in terms of statistical analysis of variance, regression coefficients and regression equation. The experimental data for the three responses were fitted into a second-order polynomial model based on Eq. (1) in terms of the code factors, as follows: (1) where Y represents the response variable, Xi and Xj are the independent variables affecting the responses, and β0, βi, βii and βij are the regression coefficients for the intercept, linear, quadratic and interaction terms (Zeković et al., 2014).
The optimum extraction conditions were determined considering the highest values for the total flavonoids, total polyphenols and the antioxidant activity values.

Statistical analysis
The Design-Expert 6.0 Trial (Stat-Ease, Minneapolis, Minnesota, USA) software was used for the Response Surface Methodology. The statistical analysis of the data was performed using ANOVA.

GIS technique
To the best of our knowledge, in Romania only 38 areas were identified where the C. mas trees can grown, as described in Table 2 (Doniță et al., 2005). Table 2. Romania's areas of cornelian cherry trees (Doniță et al., 2005)  Favourability of the environmental factors for C. mas trees in Romania Taking into account the preferences of the C. mas species, a database was created with the multiannual precipitations values from the meteorological stations in Romania. Based on the GIS spatial analysis technique and by using the equations between the precipitations level and the elevation, the grid of the multiannual average precipitations was obtained. This was converted by considering the favourability as well as the restrictiveness of the studied species. Thus, the territories that benefit from values of an average multiannual precipitations lower than 650 mm/year were included in the classes of high favourability since the species has low requirements for water. The areas characterized by precipitation values between 650-900 mm/year were included in the medium favourability class. Thus, the main part of the Transylvanian Plateau, the area of the Sub-Carpathian hills, but also that of the low mountains offer medium conditions to this species from the pluviometry point of view.
In the areas where the volume of precipitations surpasses 900 mm/year, the restrictive conditions were fulfilled for C. mas, therefore the high-mountainous area of the Romanian Carpathians was included in the low favourability classes (Figure 1). 7 By using the same procedural stages, the multiannual average temperature grid was obtained which was the basis in generating the map of favourability map for C. mas in terms of the air temperature ( Figure 2). Thus, it could be observed that that the largest part of the Romanian territory offers medium favourable conditions for C. mas. Only the areas of the Danube floodplain, the Bărăgan Plain and the seaside are characterised by temperatures higher than 10.5 °C. As such, these are characterised by the best development conditions of the species, whereas the limitative areas were identified in the high-mountainous areas, characterised by temperature values that can reach 2 °C. Considering the influence of the elevation on the precipitations' volume, on the air temperature and, implicitly, on the pedological characteristics, and by using the information provided by the scientific literature on the ecological requirements of the analysed species, the Romanian territory was classified based on three favourability classes. The areas with an elevation lower than 100 m offer limitative conditions for the cultivation of C. mas, whereas the areas within the elevation 100-800 m offer good development conditions. Thus, the high areas characterised by a higher elevation than 800 m may become restrictive to the development and the achievement of an increased consistency of the species. The analysis of the forest habitats' types from Romania, where C. mas grows, allowed a classification based on favourability classes correlated to the soil types ( Figure 3, Table 1). It can be notice that a considerable part of the Romanian territory (143010 km 2 representing 59.85%) offers favourable conditions for the development of the species through the presence of specific soil types: Lithosols, Rendzinas, Terra-rossa, Chernozem, Preluvosoil, Phaeozem. The restrictive conditions are fulfilled on an approximately 25.16% of the national territory where types of soil such as Cambic Chernozem, Erodosoils, alluvial soils are present, whereas the other 14.9% of the territory offers medium conditions for the analysed species (Figure 4).  (Table 1). Therefore, a large part of the Romanian territory (58.9% of its surface) offers favourable conditions for C. mas. Only 4.2% imposes limits within the territories with salt deposits whereas the other territories offer medium development conditions for the studied species ( Figure 5). At a national level, the GIS analysis has highlighted the medium and the high favourability classes for C. mas which represented 75% of the studied territory, due to climatic, soil and geological conditions ( Figure 6). The largest areas that can support the development of the species and the obtainment of abundant fructification are located in several counties, such as: Bihor, Constanța and Bacău, whereas the most restrictive areas are located in the following counties: Suceava, Timiș, Harghita etc. (Table 3).
The validation of the model was made by using the reclassified result obtained from the implementation of a spatial analysis (favourability or restrictiveness for C. mas and a vector database of a polygon type. This was obtained from a direct acquisition representing geographical locations of the areas where the species exceeds 25% of the consistency of the habitats in which it develops, according to the Atlas of Species in Europe. Therefore, a validation rate of 83.5 % of the results was identified, which reflects the high level of sensitivity of the applied model (28 safe locations in the field where the C. mas species was identified, located in areas are included in the high favourability class, whereas 19 are present in the medium favourability class).

Response Surface Methodology for the CE method of the BACs from cornelian cherry fruits
The experimental values were fitted to a second-order polynomial model (Eq.1) and the multiple regression coefficients were generated for all the responses using a statistical approach to determine the influence of the extraction parameters on the BACs from C. mas fruits.
The highest values for the BACs were obtained at 40 °C, 15 min and 60% hydro alcoholic solution, a Gallic Acid Equivalent GAE, 24.70±0.92 mg/g raw material, a Quercetin Equivalent QE, 1.36±0.00 mg/g raw material was obtained at 30 °C, 30 min and 60% hydro alcoholic solution, whereas the total antioxidant activity, of 101.31±3.90 mg Trolox /g raw material, was detected at 50 °C, 30 min and 100% etanol (EtOH).  The regression coefficients of the fitted second-order polynomial model for the BACs expressed as GAE, QE and Trolox Equivalents are presented in Table 5. The analysis of variances (ANOVA) of the fitted second-order polynomial model for the TPC, TFC and TAA responses is summarized in Table 6.
The high values of coefficients of multiple determination for all BACs (R 2 TPC = 0.86, R 2 TFC = 0.97 and R 2 TAA=0.95, respectively) through the model equations provided a good representation of the experimental values. For all three responses (the TPC, the TFC and the TAA), the mathematical models were statistically acceptable due to a significant regression for the model, p < 0.05 (Table 6). For this model, the lackof-fit values confirmed the adequacy of the experimental data fitting with insignificant p-values were (p > 0.05). The coefficient of determination (R 2 ) of the model was 0.86; b The coefficient of determination (R 2 ) of the model was 0.97; c The coefficient of determination (R 2 ) of the model was 0.95; s -significant; ns -not significant.
The GAE response was not significantly influenced by the combined action of the time-temperature parameters. A decrease in the TPC was observed at 40 °C and 30 minutes. The use of the temperature of 30 °C and an extraction time in the range between 15 and 45 min allowed a satisfactory concentration in the TPC ( Figure 7A). The influence of the combined action of the EtOH-extraction temperature parameters revealed a considerable increase of the TPC at the concentration of 60% EtOH throughout the temperature range between 30 to 50 °C ( Figure 7B). Using an optimum of EOH concentration of 60%, the optimum of extraction time for the temperature range between 30-50 °C, was maximum 15 minutes. Any increase in time over 15 minutes led to a decrease of the TPC ( Figure 7C).
The QE response was not significantly influenced by the combined action of the time-temperature parameters. A decrease of the TFC was observed at 40 °C and 30 minutes of extraction. The use of the temperature of 30 °C and an extraction time between 15-30 min will allow a satisfactory concentration in QE ( Figure 8A). The influence of the combined action of the EtOH -temperature parameters revealed a considerable the TFC increase at an EtOH concentration in the range 60-80% throughout the temperature range between 30-50 °C ( Figure 8B). Using an EtOH concentration between 60-70% in the temperature range between 30-50 °C, the optimum extraction time was 15 minutes. Any increase in time over 15 minutes leads to a decrease in the concentration of the TFC content ( Figure 8C).
The TAA response was influenced by the combined action of the time-temperature parameters. The use of a temperature found in the 40 °C to 50 °C range and a time interval of between 30-45 min., will allow a satisfactory TAA to be obtained. The use of a higher temperature revealed a better resistance of the phenolic compounds expressed as Trolox Equivalents ( Figure 9A). The influence of the combined action of the EtOHtemperature concentration parameters revealed a considerable increase of the TAA at a 95-100% co-solvent EtOH concentration throughout the temperature range between 30 °C to 50 °C ( Figure 9B). Using the optimum concentration of 100% EtOH, the optimum extraction time for the temperature range of 30-50 °C is 15-45 minutes. A maximum concentration was reached after 30 minutes of extraction ( Figure 9C).
The experimental values (observed values) and those predicted for the TPC are found in the immediate vicinity of the correlation line, which shows that the model predicted the experimental data very well, fact also proven by the coefficient of determination value R 2 =0.86 (quadratic model). This shows that 86% of the experimental data are approximated by the model. The remaining 14% represents the residual values of the model ( Figure 10A). The experimental values (observed values) and those predicted for the TFC are found in the immediate vicinity of the correlation line, which shows that the model predicts the experimental data very well, fact also proven by the coefficient of determination value R 2 =0.97 (quadratic model). This indicates that 97% of the experimental data were approximated by the model; the remaining 3% represents the residual values of the model ( Figure 10B). The experimental values (observed values) and those predicted for the TAA are found in the immediate vicinity of the correlation line, which confirms that the model predicts the experimental data very well, fact proven by the coefficient of determination value R 2 =0.95 (quadratic model). This proves that 95% of the experimental data were approximated by the model; the remaining 5% being the residual values of the model ( Figure 10C). Figure 10. Actual versus predicted values acquired through a second-order polynomial model to analyse the TPC (A), the TFC (B) and the TAA (C) The study of the extraction parameters effects values on the concentration of the TPC revealed that the EtOH concentration had a high degree of influence, being able to vary between 60-80% when the GAE concentration was between 10-20 mg/g raw material. The time and temperature parameters did not significantly influence the extraction process, the critical values being represented by the temperature of 40 °C and the extraction time of 30 min when a decrease of the TPC was observed ( Figure 11A). The study of the effects of the extraction parameters on the concentration of the TFC showed that the EtOH concentration was again very important, being able to vary between 60-80% when the QE concentration is between 1-1.4 mg /g raw material. Moreover, the time and temperature parameters did not significantly influence the extraction process ( Figure 11B). The study of the effects of the extraction parameters on the concentration of the TPC showed that EtOH concentration could vary between 80-100% when the concentration of phenolic compounds is between 40-100 mg/g raw material. The time and temperature parameters did not significantly influence the extraction process critical values that were represented by the temperature of 30 °C and the extraction time of 15 min when a decrease of the TPC was detected ( Figure 11C).
The central-face cube model for the Box-Behnken central composition revealed the highest concentration value of the TPC (28.43 mg GAE/g raw material) and TFC (1.41 mg QE/g raw material) at a 60% ethanol concentration, 30 °C extraction temperature and a maximum extraction time of 15 min ( Figure  12a and Figure 12b). The cube model with the centred faces for the Box-Behnken central composition revealed the highest value of the concentration of the TAA (102.49 mg TE/g raw material) at an 100% ethanol concentration, 50°C extraction temperature and maximum 45 min extraction time (Figure 12c). From the analysis of the experimental values compared to those offered by the model, it was observed that the time variables (for the TFC and the TAA) and temperature (for the TPC) are limiting factors.

Conclusions
In our GIS technique research, the validation of the model involved identifying its success rate based on a direct comparison between the predicted and the determined results. The validation of the model through the proposed method displayed a validation rate of 83.5% was obtained which highlights the correctness of the primary databases preparation, the methodology proposed as the basis of the spatial analysis and provides the means for the implementation within the analysed territory, the main purpose being decision-making when planting species adapted to the current climatic and environmental conditions. The Response Surface Methodology was employed to study the extraction parameters effect: temperature (30-50 °C), time (15-45 min.) and EtOH concentration (60-80%) on the BACs from the cornelian cherry fruits extract. As such, the flavonoids and polyphenols concentrations and the antioxidant activity values were determined. The highest values for the TPC and the TFC were obtained at 60% EtOH concentration and different values for the temperature and time. The most relevant variable was the EtOH concentration, the obtained results suggesting that the experimental data were well approximated by the central-face cube model (86% for the TPC, 97% for the TFC and 95% the TAA).
On the territory of Romania, the beneficiaries of our study can be the territorial administrative units or NGOs regarding reforestation deficient areas in C. mas. In addition, the growth of the area of this plant may attract the interest of the food industry in diversifying different ingredients made from this variety. The results of the study create also the premises of further research for obtaining a functional food based on C. mas fruits' extract.