Phytochemical Components and Bioactivity Assessment among Twelve Strawberry (Arbutus unedo L.) Genotypes Growing in Morocco Using Chemometrics

There are not many exhaustive works emphasizing the amount of genetic diversity among the strawberry tree (Arbutus unedo L.) genotypes in Morocco. This work aims to assess the biochemical composition of strawberry tree fruits, as well as to establish the variation of this composition among them. In this study, total phenols (TP), total flavonoids (TF), condensed tannins (CT) and hydrolyzable tannins (HT), total anthocyanins (TA), and free radical scavenging activity through ABTS were investigated in strawberry tree fruits. Furthermore, qualitative and quantitative analyses of individual phenolic compounds by high-performance liquid chromatography (HPLC) were carried out. Color parameters such as lightness (L*), Chroma (c*), and hue angle (h°) were also investigated. All studied variables showed highly significant differences among all samples with the exception of hydrolyzable tannins and chromatic coordinates. TP varied from 22.63 ± 1.74 to 39.06 ± 2.44 mg GAE/g DW, TF varied from 3.30 ± 0.60 to 8.62 ± 1.10 mg RE/g DW, and TA ranged between 0.12 ± 0.06 and 0.66 ± 0.15 mg cya-3-glu/100 g DW. In addition, CT and HT amounts were in the range of 10.41 ± 1.07–16.08 ± 1.50 mg TAE/g DW and 4.08 ± 2.43–6.34 ± 3.47 TAE/g DW, respectively. Moreover, the IC50 value (ABTS) ranged between 1.75 and 19.58 mg AAE/g DW. 17 phenolic compounds were detected in strawberry tree fruits. Gallocatechol and catechin were the most abundant phenolic compounds. Matrix of correlations revealed significant positive and negative correlations among variables particularly c*, a*, and b*. Principal component analysis (PCA) showed that the first three components formed than 68% of the total inertia. The following variables gallic acid, protocatechuic, gallocatechin, gallic acid derivative, chlorogenic acid, syringic acid, ellagic acid derivative II, L*, and h* were the most involved in the total variance explained. Hierarchical clustering classified samples into one main cluster, with a single branch. The results highlight a high biochemical diversity within studied strawberry genotypes, which is probably more genetically related.


Introduction
The strawberry tree (Arbutus unedo L.) is a wild fruit tree belonging to the Ericaceae family and the genus Arbutus. It is an evergreen fruit tree distributed in the Atlantic-Mediterranean region mainly in southern Europe, North Africa, Ireland, Palestine, and Macaronesia [1]. This plant can grow at different altitudes, from sea level to 1200 m, in various types of soils, but preferably acidic soils [2].
In the past, a few studies were conducted to demonstrate the genetic diversity among strawberry tree genotypes from Turkey, Spain, and a few other countries [16][17][18]. Morphological and biochemical markers have been widely used in fruit trees valorization and in the investigations into diversity of species and the relationship between genotypes, cultivars, and their wild parents. More recently, biochemical content, in particular, bioactive content of fruits has been widely searched in terms of their human health benefits. The growers are now searching to find genotypes that have higher bioactive content in order to use them to select new cultivars that possess high nutrient value for Human health [19].
In Morocco, strawberry tree fruits remain underexploited and their consumption lasts seasonal. To our knowledge, there are no scientific studies yet studying biochemical variability among strawberry tree genotypes under Moroccan ecological conditions. Moreover, phenolic compounds and fruit skin color measurements were rarely included in previous works on strawberry tree characterization. In the present work, twelve strawberry tree genotypes, belonging to several areas in Morocco, were characterized according to their biochemical markers and skin color coordinates.
The main objectives of this study were: (1) to assess the biochemical composition and colorimetric characteristics of strawberry tree fruits; (2) to determine the correlations between all parameters in order to provide information about the ones that are potentially important in assessing strawberry tree genotypes; and (3) to evaluate the biochemical diversity among the strawberry tree genotypes belonging to several areas in Morocco. The genetic variability determined in this study will facilitate strawberry tree breeding and identification of genetic determinants of trait variability.

Plant Material
Fruits of strawberry tree (Arbutus unedo L.) were harvested during the period between October and November of 2019 from several regions of Morocco where they grow naturally (Table 1). At each site, three random samples of fruits were harvested at their full maturity from 30 randomly selected trees. Random samples of fruits were established with approximately 500 g fruits each.
All selected berries had no diseases and visual blemishes. The samples were frozen at −20 • C, freeze-dried, and ground prior to the analyses.

Extraction Procedure
One gram of powder from each sample was mixed with 25 mL of ethanol (1:25, w/v) at 25 • C for 15 min using an IKA T-18 digital Ultra-Turrax homogenizer. The homogenate was then centrifuged for 10 min at 6000 rpm and the supernatant was removed from the residue. The latter was homogenized with ethanol and the supernatant removed as above. The supernatants were then combined and filtered.

Total Flavonoids (TF)
TF was measured using the colorimetric method with aluminum chloride [21]. First, 1 mL of the sample was diluted separately then mixed with 1 mL of a 2% aluminum chloride solution. The mixture was incubated at room temperature for 15 min. Rutin was used to develop the calibration curve. The absorbance was measured at 430 nm with a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Japan). The results were expressed as rutin equivalent per dry weight of strawberry tree fruit (mg RE/g DW).

Condensed Tannins (CT)
The CT were determined according to the colorimetric method of Folin Denis [22]. Briefly, 75 mL of distilled water, 1 mL of diluted extract, 5 mL of Folin Denis reagent, and 10 mL of saturated Foods 2020, 9,1345 4 of 20 solution (Na 2 CO 3 ) were introduced into 100 mL vial. The saturated solution (Na 2 CO 3 ) was prepared from 43.75 g of sodium carbonate dissolved in 100 mL of hot water (70 to 80 • C) and after cooling, the solution was filtered and adjusted to 125 mL. After mechanical stirring, the preparation was left to stand for 30 min and the optical density was measured at 760 nm with a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Tokyo, Japan). A tannic acid standard range was prepared under the same conditions. The results were expressed as tannic acid equivalent per dry weight of strawberry tree fruit (mg TAE/g DW).

Hydrolyzable Tannins (HT)
HT were determined according to the method described by Willis and Allen [23]. Briefly, 5 mL of KIO 3 solution (2.5%) were placed in test tubes, which were then placed in a water bath at 25 • C. 1 mL of diluted extract or standard was added and stirred for 10 s, then the tubes were returned to the water bath. After the optimum time (4 min) had elapsed, the absorbance was measured at 550 nm using a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Tokyo, Japan). A tannic acid standard range was prepared under the same conditions. The results were expressed as tannic acid equivalent per dry weight of strawberry tree fruit (mg TAE/g DW).

Total Anthocyanins (TA)
TA content was quantified according to the pH differential method using two buffer systems: Potassium chloride buffer pH 1.0 (25 mM) and sodium acetate buffer pH 4.5 (0.4 M) [24,25]. Briefly, 1 mL of the extract was mixed separately with 4 mL of each of the two buffers. The absorbance was measured at 510 and 700 nm with a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Tokyo, Japan) after 15 min of incubation at room temperature. The TA of samples (mg cyanidin-3-glucoside equivalent/100 g DW) was calculated by the following Equation (1): The CT were determined according to the colorimetric method of Folin Denis [ mL of distilled water, 1 mL of diluted extract, 5 mL of Folin Denis reagent, and 10 m solution (Na₂CO₃) were introduced into 100 mL vial. The saturated solution (Na₂CO₃) from 43.75 g of sodium carbonate dissolved in 100 mL of hot water (70 to 80 °C) and af solution was filtered and adjusted to 125 mL. After mechanical stirring, the preparat stand for 30 min and the optical density was measured at 760 nm with a spec (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Tokyo, Japan). standard range was prepared under the same conditions. The results were expressed equivalent per dry weight of strawberry tree fruit (mg TAE/g DW).

Hydrolyzable Tannins (HT)
HT were determined according to the method described by Willis and Allen [23] of KIO₃ solution (2.5%) were placed in test tubes, which were then placed in a water b mL of diluted extract or standard was added and stirred for 10 s, then the tubes were r water bath. After the optimum time (4 min) had elapsed, the absorbance was measu using a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-63 Tokyo, Japan). A tannic acid standard range was prepared under the same conditio were expressed as tannic acid equivalent per dry weight of strawberry tree fruit (mg T

Total Anthocyanins (TA)
TA content was quantified according to the pH differential method using two b Potassium chloride buffer pH 1.0 (25 mM) and sodium acetate buffer pH 4.5 (0.4 M) [ 1 mL of the extract was mixed separately with 4 mL of each of the two buffers. The a measured at 510 and 700 nm with a spectrophotometer (UV/visible, Spectraphysic series V-630 instrument, Tokyo, Japan) after 15 min of incubation at room temperat samples (mg cyanidin-3-glucoside equivalent/100 g DW) was calculated by the follow

Determination of Antioxidant Capacity
The antioxidant activity was evaluated using ABTS [2,2′-azinobis-(3-ethylbenz sulfonic acid) assay and the results were presented as mean ± standard deviation. Th was described by Dorman and Hiltunen. [26]. The ABTS cation radical was prepared equal volume of potassium persulfate solution (2.45 mM) with stock solution of ABTS 16 h of incubation, the solution was diluted with ethanol to give 0.7 to 0.8 absorbance at 10 µL of this freshly prepared solution were added to 990 µL of extract and absorbance at 734 nm with a spectrophotometer (UV/visible, Spectraphysic Model JASCO instrument, Tokyo, Japan). Following this, 10 µL of this freshly prepared solution wer µL of extract and absorbance was measured at 734 nm after 6 min of incubation. Th expressed as mg ascorbic acid equivalent per dry weight of strawberry tree fruit (mg A The CT were determined according to the colorimetric method of Folin Denis [22]. Briefly, 75 mL of distilled water, 1 mL of diluted extract, 5 mL of Folin Denis reagent, and 10 mL of saturated solution (Na₂CO₃) were introduced into 100 mL vial. The saturated solution (Na₂CO₃) was prepared from 43.75 g of sodium carbonate dissolved in 100 mL of hot water (70 to 80 °C) and after cooling, the solution was filtered and adjusted to 125 mL. After mechanical stirring, the preparation was left to stand for 30 min and the optical density was measured at 760 nm with a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Tokyo, Japan). A tannic acid standard range was prepared under the same conditions. The results were expressed as tannic acid equivalent per dry weight of strawberry tree fruit (mg TAE/g DW).

Hydrolyzable Tannins (HT)
HT were determined according to the method described by Willis and Allen [23]. Briefly, 5 mL of KIO₃ solution (2.5%) were placed in test tubes, which were then placed in a water bath at 25 °C. 1 mL of diluted extract or standard was added and stirred for 10 s, then the tubes were returned to the water bath. After the optimum time (4 min) had elapsed, the absorbance was measured at 550 nm using a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Tokyo, Japan). A tannic acid standard range was prepared under the same conditions. The results were expressed as tannic acid equivalent per dry weight of strawberry tree fruit (mg TAE/g DW).

Total Anthocyanins (TA)
TA content was quantified according to the pH differential method using two buffer systems: Potassium chloride buffer pH 1.0 (25 mM) and sodium acetate buffer pH 4.5 (0.4 M) [24,25]. Briefly, 1 mL of the extract was mixed separately with 4 mL of each of the two buffers. The absorbance was measured at 510 and 700 nm with a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Tokyo, Japan) after 15 min of incubation at room temperature. The TA of samples (mg cyanidin-3-glucoside equivalent/100 g DW) was calculated by the following Equation

Determination of Antioxidant Capacity
The antioxidant activity was evaluated using ABTS [2,2′-azinobis-(3-ethylbenzothiazoline-6sulfonic acid) assay and the results were presented as mean ± standard deviation. The method used was described by Dorman and Hiltunen. [26]. The ABTS cation radical was prepared by mixing an equal volume of potassium persulfate solution (2.45 mM) with stock solution of ABTS (7 mM). After 16 h of incubation, the solution was diluted with ethanol to give 0.7 to 0.8 absorbance at 734 nm. Then, 10 µL of this freshly prepared solution were added to 990 µL of extract and absorbance was measured at 734 nm with a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Tokyo, Japan). Following this, 10 µL of this freshly prepared solution were added to 990 µL of extract and absorbance was measured at 734 nm after 6 min of incubation. The results were expressed as mg ascorbic acid equivalent per dry weight of strawberry tree fruit (mg AAE/g DW).

Extraction Method
Samples (1 g) were mixed with 10 mL of methanol: Water (80:20, v/v) and then the mixtures were sonicated during 30 min and macerated one h in refrigeration (4 °C). After this time, the samples were centrifuged for 10 min, 8000 g at 4 °C. The supernatants were collected, and the pellets were mixed : Molar absorptivity coefficient of cyanidin-3-glucoside (26,900 L/mol cm).

Determination of Antioxidant Capacity
The antioxidant activity was evaluated using ABTS [2,2 -azinobis-(3-ethylbenzothiazoline-6sulfonic acid) assay and the results were presented as mean ± standard deviation. The method used was described by Dorman and Hiltunen. [26]. The ABTS cation radical was prepared by mixing an equal volume of potassium persulfate solution (2.45 mM) with stock solution of ABTS (7 mM). After 16 h of incubation, the solution was diluted with ethanol to give 0.7 to 0.8 absorbance at 734 nm. Then, 10 µL of this freshly prepared solution were added to 990 µL of extract and absorbance was measured at 734 nm with a spectrophotometer (UV/visible, Spectraphysic Model JASCO series V-630 instrument, Tokyo, Japan). Following this, 10 µL of this freshly prepared solution were added to 990 µL of extract and absorbance was measured at 734 nm after 6 min of incubation. The results were expressed as mg ascorbic acid equivalent per dry weight of strawberry tree fruit (mg AAE/g DW).

Extraction Method
Samples (1 g) were mixed with 10 mL of methanol: Water (80:20, v/v) and then the mixtures were sonicated during 30 min and macerated one h in refrigeration (4 • C). After this time, the samples were centrifuged for 10 min, 8000 g at 4 • C. The supernatants were collected, and the pellets were mixed with 10 mL of acetone:water (70:30, v/v) and the same steps were repeated (sonication, maceration, and centrifugation). Then, the supernatants were combined and evaporated to dryness using a rotary Foods 2020, 9, 1345 5 of 20 evaporator R-205 (Büchi, Flawil, Switzerland) under reduced pressure, at 40 • C. Then, 5 mL of methanol were added to the residue, and the mixture was well shaken in a stirrer for 2 min. Due to the high sugar content present in the samples, which could interfere with the HPLC column, the samples were loaded onto a C18 Sep-Pak cartridge, previously conditioned with 5 mL of methanol, 5 mL of pure water, and then with 5 mL of 0.01 mol/L HCl. The cartridge was washed with 5 mL of pure water and then eluted with acidified methanol (0.1 g/L HCl). The collected fractions were stored at −20 • C until further use.

Determination of Polyphenolic Compounds
Polyphenolic profiles of all samples were determined by high performance liquid chromatography (HPLC) [27]. A volume of 20 µL of the samples were injected into a Hewlett-Packard HPLC series 1200 instrument (Woldbronn, Germany) equipped with a diode array detector (DAD) and a C18 column (Mediterranea sea 18, 25 × 0.4 cm, 5 micrometers particle size) from Teknokroma, (Barcelona, Spain). Polyphenolic compounds were analyzed in standard and sample solutions using a gradient elution at 1 mL/min. The mobile phases were composed by formic acid in water (1:99, v/v) as solvent A and acetonitrile as solvent B. The chromatograms were recorded at 280, 320, 360, and 520 nm ( Table 2). Polyphenolic compounds identification was carried out by comparing UV absorption spectra and retention times of each compound with those of pure standards injected in the same conditions ( Figure 1). The compounds were quantified through calibration curves of standard compounds injected in the same conditions. Phenolic acid standards were dissolved in methanol at different concentrations between 10 and 200 µg/mL; flavonoids standards were dissolved in methanol at different concentrations between 1 and 250 µg/mL. Quantification of anthocyanins was carried out based on linear curves of authentic standards. A cyanidin 3-glucoside calibration (concentration between 1 and 250 µg/mL) was used for cyanidin derivatives. each compound with those of pure standards injected in the same conditions ( Figure 1). The compounds were quantified through calibration curves of standard compounds injected in the same conditions. Phenolic acid standards were dissolved in methanol at different concentrations between 10 and 200 µg/mL; flavonoids standards were dissolved in methanol at different concentrations between 1 and 250 µg/mL. Quantification of anthocyanins was carried out based on linear curves of authentic standards. A cyanidin 3-glucoside calibration (concentration between 1 and 250 µg/mL) was used for cyanidin derivatives.
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Skin Coordinates Color
Color determinations were made on fresh strawberry tree genotypes, at 25 ± 1 • C, using a NH310 colorimeter (3 nh, Model YS3010, Shenzhen 3NH Technology, Co., Ltd., Shenzhen, China). This spectrophotometer uses a Xenon lamp, illuminant D65, 10 • observer, SCI mode, 11 mm aperture of the instrument for illumination and 8 mm for measurement. Color data were provided as International Commission on Illumination (CIE) L*a*b* coordinates, which define the color in a three-dimensional space. L* indicates lightness, taking values within the range of 0−100, and a* and b* were the chromatic coordinates, green−red and blue−yellow coordinates, respectively. Parameter a* takes positives values for reddish colors and negative values for the greenish colors, whereas b* takes positive values for yellowish colors and negative values for bluish colors. Color analyses were run in 25 replicates for each block, which means 10 strawberry fruit per treatment. Each measure was examined with three replications.

Statistical Analysis
Since we used different measure, data were standardized (µ = 0 and a σ = 1) so they can have a comparable scale [26]. Prior to the statistical analyses, data were tested for normality and homogeneity of variance using SPSS software v22. The means were evaluated according to descriptive statistics represented as Mean ± SE. Data analysis was performed using IBM SPSS v22. Analysis of variance (One-way ANOVA) was performed to test significant differences among the samples. The differences among means were estimated with Duncan new multiple range (DMRT) test. Correlation coefficients and their levels of significance were calculated using Pearson correlation. Principal component analysis was carried out using correlation matrix. In addition, a scatter plot was created according to the first three principal components (PC1-PC3). A distance matrix generated from biochemical data was used for cluster analysis based on Euclidian distance to better understand the patterns of variability among the samples.

Results and Discussion
All studied variables showed highly significant differences among all samples (p < 0.05), with the exception of hydrolyzable tannins and chromatic coordinates.

Total Phenols (TP)
TP ranged from 22.63 to 39.06 mg GAE/g DW, with an average of 30.20 mg/g DW ( Table 3). The highest value was recorded in "LAN" (39.06 mg/g DW) while the lowest value was observed in "OUA" (22.63 mg/g DW). The TP content of strawberry tree fruits reported in this study is higher than those found by other authors; Doukani and Tabak. [28] reported a range of 14.74 to 7.025 mg GAE/g in Algerian strawberry tree cultivars. In another study, Seker and Toplu. [29] reported a TP content ranging from 17.7 to 25.8 mg GAE/g). Also, Colak. [30] and Ruiz-Rodríguez et al. [13] recorded TP values ranging from 483 and 627 mg GAE/100 g and from 951 to 1973 mg/100 g in Turkish and Spanish genotypes, respectively, while Vidrih et al. [19] reported an average of 590 mg/100 g in Croatian fruits.

Condensed and Hydrolyzable Tannins (CT) and (HT)
CT and HT results data are presented in Table 3. A significant variation of CT was found at (p = 0.027) among genotypes. However, there was no statistical difference for HT among genotypes (p = 0.998). On the one hand, the CT content ranged from 10.41 to 16.08 mg TAE/g DW, with an overall mean of 13.03 mg TAE/g DW. The highest CT content was observed in "LAN" (16.08 mg TAE/g DW), while the lowest was observed in "BNO" (10.41 mg TAE/g DW). On the other hand, HT ranged from 4.08 to 6.34 mg TAE/g DW, with an overall average of 5.37 mg TAE/g DW. The highest value was found in "CHF" (6.34 mg AT/g DW) while the lowest was recorded in "TAH" (4.08 mg AT/g DW). These values were approximately similar with those revealed by Jurica et al. [31] who found (16.75-18.92 mg GAE/g) for total tannins.

Antioxidant Activity (AA)
The results obtained for antioxidant activity based on the radical scavenging capacity (ABTS) were reported in Table 3. Significant differences (p < 0.001) were observed among the genotypes studied. The value of ABTS assay ranged from 1.75 to 19.58 mg ascorbic acid equivalent/g DW, with an overall mean of 7.49 mg ascorbic acid equivalent/g DW. Gündogdu et al. [33] analyzed the antioxidant capacity (ABTS) of Turkish strawberry tree fruits. They found values ranged between 17.51 and 30.06 µmol TE/g. In other study, Colak. [30] analyzed the antioxidant capacity (ABTS) of Turkish strawberry tree fruits. They found values ranged between 18.07 and 33.41 µmol TE/g.

Profile of Polyphenolic Compounds
A total of 17 phenolic compounds were identified in strawberry tree fruits. The results obtained were summarized in Table 4. Significant variations in phenolic compounds were found at p < 0.001 among genotypes.
Gallocatechol was present in dominant amounts in all genotypes with the exception of "CHF" and "MDZ" where the dominant compound was catechin. The concentration of gallocatechol differed between genotypes. The highest level reported in "OUZ" (79.88 mg/100 g DW) and the lowest in "CHF" (16.15 mg/100 g DW). Catechin was found in higher amounts in all genotypes. "OUZ" had the highest concentration (65.53 mg/100 g DW) of catechin, and "BNO" had the lowest concentration (13.99 mg/100 g DW). Protocatechuic acid was present in significantly higher amounts in "OUZ" (6.98 mg/100 g DW) and significantly lower amounts in "MDZ" (1.84 mg/100 g DW). Gallic acid was present in significantly higher amounts in "OUZ" (58.07 mg/100 g DW), the lowest amount was recorded in "MDZ" (4.56 mg/100 g DW). Gallic acid derivatives were detected in all genotypes. The highest amount was present in "OUZ" (22.02 mg/100 g DW), and the lowest in "CHF" (4.98 mg/100 g DW).

Skin Color
Color measurements data are reported in Table 5, and there were no statistical differences between strawberry tree genotypes for all color indices L*, a*, b*, c*, and h • . Data showed that Lightening (L*) values ranged from 25.83 to 50.78. a* and b* values ranged from 28.93 to 58.91 and from 70.85 to 93.73, respectively. According to positive values of a* and b*, strawberry tree fruits included reddish orange to deep crimson red fruit colors. The Chroma (c*) was higher in genotypes with clear and bright fruit skin color, where it varied generally between 78.30 and 110.17. The hue angle (h • ) ranged between 54.70 • and 66.45 • . All strawberry tree genotypes were lighter (higher L* values) and tended to be more red (higher a* values) and yellower (higher b* values). Furthermore, the genotypes showed higher values of chroma (c*) and hue angle (h • ) corresponding to a lighter color. Therefore, skin color evaluation using these coordinates was of great importance in characterization and assessment of fruits quality and maturity. These results were, globally, in accordance with several studies. Islam and Pehlivan. [36] reported average L*, a*, and b* values of 40 genotypes as 47.26, 37.07, and 26.89, respectively. Also, Colak. [30] reported average L*, a*, and b* values of 15 genotypes as 44.30, 37.53, and 23.88, respectively. According to the literature, the color coordinates was, particularly correlated to the antioxidant compound, essentially phenols (anthocyanins, tannins, catechins, etc.) and carotenoids (lycopene, betacarotene, etc.) [37,38].

Principal Components Analysis (PCA)
PCA based on correlation coefficients was used to discriminate between variables in the datasets. The aim of this analysis was to determine the main factors to reduce the number of effective parameters to use in classification of the strawberry tree genotypes based on their biochemical parameters. In our study, only a principal component loading of more than |0.5| was considered as being significant for each factor.
Total variance of 93.19% was explained by seven components ( Table 7). The first three components consisted of 26 variables, which explained 68.77% of the total variability observed, which means that these characters had the highest variation between the genotypes and had the highest impact on discrimination of them. The first component accounted for 36.90% of the total variance, which is strongly Generally, these results were in accordance with those reported in previous strawberry tree biochemical studies [30,33]. They have reported that the biochemical attributes are important in order to evaluate the variation in traits of strawberry tree genotypes. These parameters can be used as a useful tool for selecting genotypes for breeding programs or to recommend new cultivars with superior traits.
Scatter plot was prepared according to the first three principal components: PC1, PC2, and PC3, (36.90, 18, and 13.87% of total variance, respectively) that discriminate between the genotypes according to their chromatic coordinates and biochemical characteristics (Figure 2). Starting from negative to positive values of PC1, the distribution of genotypes indicated a decrease in the peel lightness, total phenols, and condensed tannins. Whereas, starting from negative to positive values of PC2, the most of phenolic compound increased in their values. However, it showed a decrease in the skin coordinates color a*, b*, and c*. Starting from negative to positive values of PC3, the distribution of genotypes indicated an increase in the total anthocyanins, total flavonoids, hydrolyzable tannins, and ABTS.  Eigenvalues higher than |0.5| are marked in bold.

Cluster Analysis
Multivariate analysis based on bioactive compounds and antioxidant activity showed high polymorphism among the studied strawberry tree genotypes. Unweighted pair group method Generally, these results were in accordance with those reported in previous strawberry tree biochemical studies [30,33]. These studies indicated that high diversity in biochemical traits could be used as an efficient marker system to discriminate between strawberry tree genotypes, comparing our results to other fruits such as sweet cherry [44]. The authors have reported the importance of biochemical characterization as main factor in discriminating and assessing breeding materials of sweet cherry trees. Furthermore, the selection of highly discriminant variables is important to optimize resources for a feasible biochemical assessment. This is especially important in strawberry trees with hundreds of genotypes described worldwide in which many homonymies and synonymies may be detected.

Cluster Analysis
Multivariate analysis based on bioactive compounds and antioxidant activity showed high polymorphism among the studied strawberry tree genotypes. Unweighted pair group method (UPGMA) cluster analysis using Euclidean distance coefficient was performed to highlight the similarities among and differences between these genotypes. The genotypes were divided into one main cluster, with a single branch (Figure 3). The genotype "OUZ" was totally discriminated from the cluster. Furthermore, in the main cluster, the genotype "LAN" was the most interesting of the other genotypes and was classified as a singular item. The cluster included 11 genotypes subdivided into four main subgroups. The first subgroup contained "OUL" and "TAH". The second subgroup was comprised "CHF" and "MDZ". The third subgroup contained "KSB" and "BMR". The last subgroup was composed of "TAM", "OUA", "BNO", and "KHN". The findings of the present study showed the high variability within the strawberry tree genotypes based on biochemical parameters.
(UPGMA) cluster analysis using Euclidean distance coefficient was performed to highlight the similarities among and differences between these genotypes. The genotypes were divided into one main cluster, with a single branch (Figure 3). The genotype ''OUZ'' was totally discriminated from the cluster. Furthermore, in the main cluster, the genotype ''LAN'' was the most interesting of the other genotypes and was classified as a singular item. The cluster included 11 genotypes subdivided into four main subgroups. The first subgroup contained ''OUL'' and ''TAH''. The second subgroup was comprised ''CHF'' and ''MDZ''. The third subgroup contained ''KSB'' and ''BMR''. The last subgroup was composed of ''TAM'', ''OUA'', ''BNO'', and ''KHN''. The findings of the present study showed the high variability within the strawberry tree genotypes based on biochemical parameters.

Conclusions
This study proved a high variability among the genotypes studied. The results obtained showed that the strawberry tree fruits are an important source of bioactive compounds. Seventeen phenolic compounds were identified by HPLC, of which gallocatechol and catechin were the most abundant ones. According to the results obtained, the fruits of strawberry tree can be considered as a very rich source of health-promoting compounds, a fact that may encourage many people to consume them as an alternative source of bioactive compounds. The biochemical composition of the fruits of strawberry tree could also be useful to improve their future pharmacological and cosmetic usages. Furthermore, the findings confirmed the usefulness and the importance of biochemical parameters and their complementary information to study diversity within the wild inheritance of strawberry tree. Therefore, the results found in this study may be useful to promote the cultivation of species so as to maintain its longevity and diversity as well as to facilitate its use in breeding programs and industrial valorization. The high variability in biochemical composition observed among genotypes could be attributed to genetic factors. Therefore, it will be important to study and identify the genes

Conclusions
This study proved a high variability among the genotypes studied. The results obtained showed that the strawberry tree fruits are an important source of bioactive compounds. Seventeen phenolic compounds were identified by HPLC, of which gallocatechol and catechin were the most abundant ones. According to the results obtained, the fruits of strawberry tree can be considered as a very rich source of health-promoting compounds, a fact that may encourage many people to consume them as an alternative source of bioactive compounds. The biochemical composition of the fruits of strawberry tree could also be useful to improve their future pharmacological and cosmetic usages. Furthermore, the findings confirmed the usefulness and the importance of biochemical parameters and their complementary information to study diversity within the wild inheritance of strawberry tree. Therefore, the results found in this study may be useful to promote the cultivation of species so as to maintain its longevity and diversity as well as to facilitate its use in breeding programs and industrial valorization. The high variability in biochemical composition observed among genotypes could be attributed to genetic factors. Therefore, it will be important to study and identify the genes responsible for the biochemical properties in order to understand the pattern of variation in the biochemical composition of strawberry tree genotypes.