4046
J. Agric. Food Chem. 1999, 47, 4046−4052
Study of the Phenolic Profile of Cider Apple Cultivars at Maturity by Multivariate Techniques Juan J. Mangas,* Roberto Rodrı´guez, Bele´n Sua´rez, Anna Picinelli, and Enrique Dapena Centro de Investigacio´n Aplicada y Tecnologı´a Agroalimentaria, Apartado 13, E-33300 Villaviciosa, Asturias, Spain
Phenolic compounds in 46 Spanish cider apple varieties were determined by RP-HPLC with direct injection. Several pattern recognition procedures, including principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares (PLS-1), were applied to the data in an attempt to classify the samples into bitter and nonbitter categories. Reliable decision rules were obtained by both LDA and PLS-1. LDA achieved 91.3 and 85.7% correct classification respectively, for internal and external evaluation of the model. Keywords: Cider apple; polyphenols; direct injection HPLC; chemometric INTRODUCTION
Various types of phenolic compounds are found in cider apple cultivars, namely, hydroxycinnamic acid derivatives, monomeric and oligomeric flavan-3-ols, dihydrochalcones, and flavonols (Picinelli et al., 1997; Guyot et al., 1998; Escarpa and Gonza´lez, 1998). They play an important role in browning processes and in the formation of hazes and sediments, they contribute to the flavor of processed apple products, and from the point of view of health, some of them, such as hydroxycinnamates, are an important source of antioxidants and free radical scavengers (Okuda, 1993; Chen and Ho, 1997; Donovan et al., 1998). Many studies have dealt with the phenolic composition of apples and its relation to browning susceptibility. Enzymatic browning occurs in fruits and vegetables as a result of enzymatic oxidation of phenolic compounds into quinones, which subsequently polymerize into brown products (Nicolas et al., 1994). Quinones are highly unstable and can undergo reactions with other phenolic compounds, giving rise to dimers with an o-diphenolic structure; they can later undergo oxidation enzymatically or by coupled oxidation with o-quinones (Macheix et al., 1990a). At the same time, other nonphenolic substances such as amino or thiol groups can react with quinones, giving rise to a new o-diphenolic structure that, once oxidized, can form intensely colored products. Polyphenol-protein interaction (based on hydrogen and/or hydrophobic bonding) is involved in haze formation in fruit juices and alcoholic beverages, the amount of haze formed being related to polyphenol and protein levels and to their ratio (Siebert et al., 1996a). At the same time, the percentage of proline in polypeptides has also been shown to be very important in haze production; in fact, polypeptides with a high content of proline produced more haze. The nature of polyphenols is also involved in the formation of haze. In this sense, flavan3-ols dimers of (+)-catechin and (-)-epicatechin were * Author to whom correspondence should be addressed (telephone 34-85890066; fax 34-85891854; e-mail juanjoma@ princast.es).
found to be implicated in the formation of haze in alcoholic beverages and apple juice (Siebert et al., 1996b). The taste of cider is dependent on the presence of flavan-3-ol derivatives. Bitterness and astringency are related to the degree of polymerization of procyanidins (Lea, 1990), the most astringent being the most polymerized procyanidins. At the same time, certain hydroxycinnamic acids are bitter (Macheix et al., 1990b) and monomers of flavan-3-ols such as (+)-catechin were rated bitter and astringent (Robichaud and Noble, 1990). Polyphenol analysis is generally accomplished by RPHPLC with UV-vis detection. Due to the complexity of the analysis, two methods for polyphenol fractionation have traditionally been used: liquid-liquid extraction (Salagoity-Auguste and Bertrand, 1984; Sua´rez et al., 1994) and solid-liquid extraction (Lee and Jaworski, 1987; Sua´rez et al., 1996). However, analysis of major polyphenols of low molecular mass can be carried out by direct injection following a simple treatment of the sample (Bete´s-Saura et al., 1996; Sua´rez et al., 1998). Likewise, the optimization of analytical information can be carried out by means of chemometric techniques when a large amount of data is available. For example, exploratory data analysis can be used to search for “natural” groupings of samples and to reduce dimensionality. Principal component analysis (PCA) allows reduction of the number of variables and visualization of the data structure. Linear discriminant analysis (LDA) computes a decision rule to predict the class to which a sample belongs. Partial least squares (PLS) regression allows prediction of the values of one or more dependent variables from a set of predictor variables (Massart et al., 1988; Martens and Naes, 1989; Meloun et al., 1992). When the dependent variable is the class identity, the procedure is called PLS discriminant analysis. Although classification of cider apple varieties into technological groups has been successfully done in the past using data for total polyphenols and total acidity (Beech and Carr, 1977), the information obtained by means of the analysis of global parameters can be
10.1021/jf9903197 CCC: $18.00 © 1999 American Chemical Society Published on Web 09/18/1999
Polyphenols in Cider Apples
J. Agric. Food Chem., Vol. 47, No. 10, 1999 4047
limited. Because a balanced phenolic profile is desirable both to control microbiological spoilage and to guarantee flavor quality of ciders, a study of the phenolic profile of apple varieties should be necessary. The purpose of the present work was to carry out a technological characterization of various Spanish cider apple varieties traditionally used in cider-making on the basis of their phenolic profiles. MATERIALS AND METHODS Samples. Spanish cider apple cultivars, grown during the 1994 (42 varieties) and 1995 (46 varieties) seasons in the experimental orchard of the CIATA (Villaviciosa, Asturias, Spain), were harvested at maturity and directly sampled (2.02.5 kg of fresh apples; ∼24 fruits). Apples from each variety were milled with a hammer mill and pressed by means of a small hydraulic press; the apple musts obtained were subsequently clarified by centrifugation (12000g; 5 min) and frozen at -20 °C until analysis. Ascorbic acid (10 g/L) was added to the apple juices prior to filtration through a 0.45 µm cellulose acetate membrane filter (Teknokroma, Barcelona, Spain) before chromatographic analysis. Total polyphenols were determined according to the Montreau method (1972) and expressed as grams of tannic acid per liter; total acidity was done determined by using the AOAC procedure (AOAC, 1984) and calculated as grams of sulfuric acid per liter. Reagents. Standards for polyphenols [chlorogenic acid, (-)epicatechin, p-coumaric acid, and phloridzin] were obtained from Sigma, Spain. Procyanidin B2 and phloretin 2-xyloglucoside were provided by Dr. Lea (Reading, U.K.) and used for identification purposes only. Methanol and acetic acid were of HPLC quality (Panreac, Barcelona, Spain) and degassed with helium prior to use. Chromatography. Experimental data were obtained using an HPLC system (Kontron Instruments S.A., Madrid, Spain) equipped with a 465 autosampler (Vi ) 25 µL), two 422 pumps, a 440 diode array detector, and a KromaSystem 2000 software data module. Analytical separation of phenolic compounds was carried out on a Spherisorb ODS-2 column (250 mm × 4 mm, 3 µm; Teknokroma, Barcelona, Spain) at 35 °C, using 2% acetic acid (solvent A) and methanol (solvent B) as mobile solutions. The elution conditions were as follows: starting from 0% solvent B, one linear step of increase of solvent B in solvent A until 45% B in 55 min; flow rate ) 0.7 mL/min. Identification of polyphenols was achieved by comparing their spectra and retention times and by spiking with the available compounds under the same conditions. Quantitation was done at 280 nm by the external standard method. For those analytes having no standard available, standards of the same family were used; thus, procyanidin B2 was quantitated as (-)-epicatechin, phloretin 2-xyloglucoside and the unknown dihydrochalcone were determined as phloridzin, and the unknown phenolic acid derivatives (compounds referred to as PHA) were determined as p-coumaric acid. A chromatogram of the phenolic compounds of low molecular mass is displayed in Figure 1. Data Processing. Data were processed by means of the PARVUS statistical package (Forina et al., 1988). We constructed a data matrix (46 × 9) in which the rows (46) represented cider apple varieties harvested in 1995, and the columns (9) corresponded to phenolic compounds [an unknown phenolic acid derivative, PHA1 (λmax ) 316.7 nm), procyanidin B2, chlorogenic acid, (-)-epicatechin, an unknown phenolic acid derivative, PHA2 (λmax ) 312 nm), phloretin 2-xyloglucoside, an unknown dihydrochalcone (λmax ) 283 nm), phloridzin (phloretin glucoside), and an unknown phenolic acid derivative, PHA3 (λmax ) 312 nm)]. In addition, samples were categorized as bitter (B) or nonbitter (N), according to their total pholyphenol contents. Samples included in the bitter category presented total phenol levels >1.5 g/L, whereas the nonbitter category were 1.9 g/L. Total acidity was mainly comprised between 4.00 and 5.50 g/L (55.7%, Figure 2b). These parameters are usually employed for the classification of apples into technological groups; however, this information can be limited, because nothing is said about differences in the quantitative phenolic profiles of apple varieties.
4048 J. Agric. Food Chem., Vol. 47, No. 10, 1999
Mangas et al.
Table 1. Phenolic Compound Concentrations in Apple Juice Cultivars (1995 Harvest)a polyphenols (mg/L) variety
ref
PHA1
B2
CA
E
PHA2
Ph XyG
Unk
Ph G
PHA3
Σ
TP
TA
Calabaza Campillo Duro´n Arroes Dolores Lagar Miyares Reineta Encarnada Repinaldo Hueso Loron˜esa Montoto Parda Carren˜o Parda Blanquera Loron˜e Meana Prieta Casado Fuentes Obdulina Pardona No Prieta Antigua Arbeya Arbeya Monte´s Lin Blanquina Clara Coloradona Collaos Cristalina De La Riega Duro´n Encarnado Durona Tresali Fresnosa Limo´n Monte´s Marin˜ana Panquerina Paraguas Pepa Perezosa Perico Raxao Regona Repinaldo Gozo´n Solarina Teo´rica Verdialona Xuanina
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
1.32 2.71 1.13 0.70 1.15 1.12 0.49 0.58 1.04 2.22 0.58 4.47 3.47 2.18 0.99 1.49 0.98 0.99 1.24 0.68 0.70 0.76 1.30 0.98 0.00 1.39 1.11 0.89 1.13 0.89 2.21 0.80 0.72 0.82 1.19 0.49 0.48 0.33 1.18 1.00 2.97 0.80 0.77 0.80 0.00 0.00
26.02 37.64 11.86 3.97 0.00 42.35 35.80 27.39 7.90 67.30 6.90 246.92 127.32 154.76 26.48 39.42 53.68 47.41 22.27 0.00 73.62 102.71 47.27 9.32 61.42 47.95 6.93 0.00 8.68 19.12 50.44 17.18 15.69 21.96 41.71 0.00 0.00 0.00 24.38 20.48 20.45 54.65 57.97 38.26 15.47 24.14
125.72 70.91 136.40 109.19 246.38 46.47 96.50 149.40 228.12 138.10 160.29 128.53 79.50 53.70 66.96 275.98 122.42 203.65 63.13 108.28 163.64 167.93 350.53 193.24 116.66 63.83 93.26 57.58 195.56 115.00 225.52 87.77 162.71 21.24 78.56 126.17 136.57 63.68 143.42 84.58 130.59 40.81 96.80 95.19 74.87 144.92
25.98 46.16 23.43 11.63 80.97 42.93 44.68 33.12 12.21 68.36 11.72 206.54 114.97 141.05 34.24 61.30 42.63 56.65 24.66 0.00 75.03 75.82 40.68 23.11 89.59 59.95 9.57 0.00 22.50 26.72 47.31 27.51 22.97 31.63 65.76 6.98 6.79 8.01 20.27 18.14 29.59 39.48 108.92 29.76 25.86 41.06
15.32 0.00 2.92 9.39 15.03 21.87 6.11 0.00 13.34 0.00 0.00 35.41 22.38 8.86 11.32 0.00 0.00 0.00 26.23 34.40 9.02 10.31 4.22 0.00 12.65 31.89 6.70 0.00 6.44 5.10 34.37 13.66 5.51 0.00 10.50 4.90 0.00 3.44 8.27 5.10 48.25 9.61 10.29 8.21 9.30 0.00
22.26 65.56 18.91 29.23 107.18 38.17 6.75 4.98 26.34 26.85 42.38 32.54 23.84 58.69 13.04 32.68 10.71 37.89 9.29 32.23 32.75 33.69 46.52 10.44 34.88 14.75 40.70 5.85 3.66 11.64 30.59 4.42 9.15 12.77 11.53 8.05 8.74 8.23 38.48 36.25 22.65 7.75 10.06 3.30 7.38 36.88
1.12 3.21 0.81 1.23 6.52 2.11 0.00 0.00 1.20 1.65 2.48 1.15 0.84 2.42 0.54 1.89 0.63 2.05 0.49 1.46 1.76 1.77 2.23 0.00 1.09 0.80 2.50 0.00 0.00 0.63 1.74 0.00 0.46 0.65 0.44 0.37 0.00 0.00 1.87 1.81 1.08 0.00 0.00 0.00 0.39 2.11
6.82 11.53 9.85 10.09 8.71 11.38 4.36 2.50 7.89 6.13 12.31 32.39 26.62 9.55 7.14 12.06 5.39 10.58 5.28 2.91 8.07 7.04 9.34 13.85 7.22 7.31 6.69 2.83 3.65 5.80 17.16 2.49 9.83 6.58 8.42 4.70 3.26 3.49 8.04 6.32 24.13 4.44 6.52 5.96 3.51 6.46
0.61 0.48 0.76 0.63 0.67 0.64 0.79 0.35 0.48 0.50 0.59 0.61 0.49 0.51 0.77 0.66 0.58 0.78 0.39 0.52 0.69 0.68 0.51 0.52 0.60 0.47 0.54 0.00 0.36 0.66 1.20 0.88 0.48 0.62 0.80 0.55 0.57 0.00 0.52 0.52 0.66 0.81 0.67 0.43 0.77 0.69
225.17 238.20 206.07 176.06 466.61 207.04 195.48 218.32 298.52 311.11 237.25 688.56 399.43 431.72 161.48 425.48 237.02 360.00 152.98 180.48 365.28 400.71 502.60 251.46 324.11 228.34 168.00 67.15 241.98 185.56 410.54 154.71 227.52 96.27 218.91 152.21 156.41 87.18 246.43 174.43 280.37 158.35 292.00 181.91 137.55 256.26
1.43 1.15 1.19 0.79 2.40 1.58 1.10 1.30 1.56 1.65 1.10 2.25 1.99 2.06 1.04 2.08 1.10 1.75 1.18 0.86 1.58 1.52 2.36 1.00 2.42 1.70 1.14 0.75 1.23 1.07 1.54 1.23 1.30 0.96 1.17 1.10 1.27 0.77 1.22 0.87 1.70 0.92 1.36 0.92 0.92 1.08
5.76 3.80 3.80 3.80 4.66 3.43 3.19 4.04 3.80 4.04 3.92 5.39 3.92 4.78 4.78 6.98 5.51 2.57 6.49 0.74 4.17 5.15 5.15 3.80 1.59 1.35 4.04 2.94 4.29 5.27 5.64 4.66 5.76 3.31 3.43 2.21 1.72 3.92 3.68 4.78 7.72 2.08 3.55 6.00 2.57 4.78
1.16 0.87 4.47 0.00
38.37 45.27 246.92 0.00
126.96 66.31 350.53 21.24
44.27 39.42 206.54 0.00
10.44 11.43 48.25 0.00
24.58 19.79 107.18 3.30
1.16 1.19 6.52 0.00
8.62 6.07 32.39 2.49
0.59 0.20 1.20 0.00
256.15 121.78 688.56 67.15
1.36 0.45 2.42 0.75
4.11 1.46 7.72 0.74
mean SD maximum minimum
a Abbreviations: PHA1, phenolic acid derivative (λ ) 316.7 nm); CA, chlorogenic acid; E, (-)-epicatechin; PHA2, phenolic acid derivative (λ ) 312 nm); Ph XyG, phloretin xyloglucoside; Unk, unknown dihydrochalcone; Ph G, phloretin glucoside; PHA3, phenolic acid derivative (λ ) 312 nm); Σ, total polyphenols of low molecular mass; TP, total polyphenols (as grams of tannic acid per liter); TA, total acidity (as grams of sulfuric acid per liter); SD, standard deviation.
PCA. PCA was carried out to reduce the number of variables and to define the structure of the data. Three significant components, which accounted for 74.9% of the variance, were computed and validated by means of a single-cross full-validation procedure that uses the search for a local minimum prediction residual error square sum (PRESS) as criterion. Phloridzin, (-)epicatechin, and the unknown dihydrochalcone were removed from the original data matrix because they contributed to the same information as PHA1, procyanidin B2, and phloretin 2-xyloglucoside, respectively. Then, a new PCA was carried out by taking into account only the six relevant variables. The same explained variance was obtained using the first three significant factors. A biplot constructed from the first two principal components is displayed in Figure 3. As can be seen in
this figure, we were able to establish two groups of variables: on the one hand, PHA1, B2, and PHA2 were correlated to the first factor, and, on the other, chlorogenic acid and phloretin 2-xyloglucoside were correlated to the second factor. Likewise, a structure of data can be assessed from this plot. For instance, the Parda Blanquera (12) variety was placed in the upper righthand corner of the factorial plane, because this variety showed a high content of procyanidin B2, PHA1, and PHA2; however, its chlorogenic acid content was relatively low. In contrast, the Cristalina (28) and Perezosa (38) varieties were placed in the upper left-hand corner of the factorial plane, which shows that these varieties have a low content of polyphenols of low molecular mass (Table 1). The Cristalina and Perezosa varieties, together with the Dolores and No Prieta Antigua varieties
Polyphenols in Cider Apples
J. Agric. Food Chem., Vol. 47, No. 10, 1999 4049
Table 2. Phenolic Compound Concentrations in Apple Juice Cultivars (1994 Harvest)a polyphenols (mg/L) variety
ref
PHA1
B2
CA
E
PHA2
Ph XyG
Unk
Ph G
PHA3
Σ
TP
TA
Calabaza Campillo Duro´n Arroes Dolores Lagar Miyares Reineta Encarnada Repinaldo Hueso Loron˜esa Montoto Parda Carren˜o Parda Blanquera Loron˜e Meana Prieta Casado Fuentes Obdulina Pardona Blanquina Clara Coloradona Collaos Cristalina De La Riega Duro´n Encarnado Durona Tresali Fresnosa Limo´n Monte´s Marin˜ana Panquerina Paraguas Pepa Perezosa Perico Raxao Regona Repinaldo Gozon Solarina Teo´rica Verdialona Xuanina
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
1.71 4.03 2.24 0.61 1.86 1.73 0.89 1.02 1.93 2.84 0.93 2.88 3.23 1.67 0.66 1.93 1.23 0.79 1.58 1.00 0.00 0.94 1.55 1.27 0.97 0.57 1.58 1.94 0.81 1.11 1.65 0.62 0.54 0.58 1.87 1.13 4.06 0.78 1.18 0.93 0.00 0.99
31.09 35.14 16.93 0.00 151.17 49.69 28.78 27.92 18.73 55.66 11.13 114.12 153.37 222.95 11.22 66.06 61.08 56.24 49.44 10.18 62.51 14.19 9.32 0.00 7.59 13.67 44.15 29.90 18.87 53.67 42.76 0.00 0.00 9.58 36.06 16.37 21.71 43.06 138.10 23.21 33.29 12.08
196.67 84.29 216.39 74.98 377.06 70.33 119.17 177.14 339.11 155.23 160.75 84.02 82.61 54.42 183.76 309.44 155.56 190.68 109.03 173.76 100.97 31.86 136.39 63.16 181.88 75.47 174.08 116.32 199.09 44.88 89.50 125.29 102.94 107.06 227.46 115.51 130.13 25.07 206.64 112.87 94.41 161.48
49.16 39.78 31.71 10.51 190.84 66.13 49.73 36.83 29.59 86.00 17.46 157.24 190.76 234.56 23.43 106.41 54.46 77.23 54.20 24.78 126.16 37.23 18.54 5.01 22.66 28.14 52.11 50.53 31.79 57.52 60.03 5.04 4.09 21.40 36.80 21.58 53.99 42.49 146.51 25.41 50.98 25.27
18.98 0.00 3.89 6.84 21.54 31.49 3.81 0.00 19.02 0.00 0.00 26.94 25.24 0.00 0.00 0.00 0.00 0.00 39.06 0.00 8.97 23.24 11.40 0.00 4.99 5.49 36.62 17.43 4.39 3.42 10.86 7.44 2.92 5.16 11.00 4.98 68.34 4.36 13.97 6.67 10.37 0.00
30.75 73.92 33.59 19.95 159.06 51.94 11.63 7.66 36.23 37.88 50.34 26.66 27.29 78.00 26.16 44.27 12.84 39.31 8.57 10.09 43.17 14.98 54.32 8.93 7.14 11.02 29.77 6.32 9.85 14.53 9.79 13.88 8.74 16.35 68.02 49.91 27.84 6.84 12.41 4.03 7.63 35.59
1.30 3.19 1.24 0.81 8.41 2.13 0.52 0.24 1.29 1.93 2.28 0.49 0.53 3.31 1.19 2.36 0.54 1.87 0.64 0.43 1.55 0.44 2.90 0.33 0.00 0.40 1.29 0.22 0.25 0.82 0.38 0.55 0.40 0.67 3.02 2.23 1.04 0.32 0.73 0.00 0.29 1.80
9.54 11.76 19.15 6.53 17.04 18.15 6.60 4.17 13.95 9.70 14.04 30.00 28.80 9.76 7.13 13.86 7.37 10.63 7.11 13.44 13.75 13.85 9.69 5.37 6.72 7.24 17.42 3.89 8.98 7.96 6.39 8.00 3.73 5.59 16.86 9.52 36.61 4.31 7.67 7.46 4.40 7.02
0.85 0.44 0.99 0.48 0.93 0.93 0.81 0.37 0.63 0.59 0.75 0.67 0.68 0.47 0.94 0.76 0.76 0.85 0.54 0.50 0.71 0.45 0.80 0.43 0.51 0.82 1.06 1.28 0.62 0.49 0.59 0.67 0.67 0.00 0.00 0.67 0.93 0.66 0.72 0.54 1.36 0.76
340.04 252.55 326.14 120.70 927.92 292.52 221.94 255.36 460.47 349.84 257.69 443.02 512.52 605.13 254.49 545.08 293.83 377.60 270.16 234.19 357.80 137.19 244.92 84.50 232.45 142.82 358.08 227.84 274.65 184.41 221.95 161.49 124.03 166.39 401.09 221.92 344.65 127.89 527.93 181.11 202.74 244.98
1.29 1.00
5.51 3.92
0.59 2.06 1.42 1.04 1.25 1.56 1.46 0.98 1.71 1.88 1.74 0.92 1.70
4.17 4.17 3.55 4.90 5.02 4.29 4.41 4.53 5.08 5.00 4.90 3.80 7.35
1.34 1.15 0.76 1.43 0.97 1.08 0.57 0.94 0.87 1.24 1.06 1.05 1.25 1.24 0.92 0.77 0.74 1.11 0.79 1.20 0.71 1.85 0.74 0.90 0.91
2.82 7.23 5.45 1.47 0.86 5.02 3.80 4.29 5.76 5.64 5.20 6.13 5.51 4.66 2.39 1.35 4.17 5.02 6.62 7.96 2.70 4.53 5.76 2.45 6.25
1.43 0.92 4.06 0.00
42.88 47.66 222.95 0.00
141.35 76.92 377.06 25.07
58.43 54.09 234.56 4.09
10.93 13.97 68.34 0.00
29.69 28.39 159.06 4.03
1.29 1.45 8.41 0.00
11.22 7.18 36.61 3.73
0.68 0.27 1.36 0.00
288.69 159.01 927.92 84.50
1.16 0.37 20.6 0.57
4.59 1.58 7.96 0.86
mean SD maximum minimum a
Abbreviations: see Table 1.
(4 and 20), presented the lowest Folin index (Table 1); however, the latter ones had higher levels for phenols as determined by HPLC, mainly CA. It was also possible to visualize other groupings of samples: varieties with a high content of chlorogenic acid (5, 16, 18, 23, and 31) scored negatively with respect to the second principal component; other varieties, however, such as Loron˜e, Meana, and Regona (13, 14, and 41), which showed a high content of PHA1 and a relatively low chlorogenic acid content, were placed in the upper right-hand quadrant of the factorial plane. At the same time, it was possible to draw a borderline in Figure 3 to differentiate the cider apple varieties with bitter and nonbitter properties. We categorized the samples from the structure visualized in the factorial plot as follows: the bitter class (B, 15 varieties), samples inside the borderline, and the nonbitter class (N, 31 varieties), samples outside the border; 87% of samples belonging to the bitter category presented contents for total phenol >1.5 g/L, and 90% of samples belonging to the nonbitter category presented total phenol contents
