The runs were monitored at 280 nm (flavan-3-ols and dihydrochalcones), 320 nm (hydroxycinnamic PF-02341066 ic50 acids) and 350 nm (flavonols). Quantification was performed using calibration curves of standards (at least seven concentrations were used to build the curves) (Table 2). Data were presented as mean and standard deviation (SD) or pooled standard deviation (PSD). All variables had their variance

analysed using the F test (two groups) orby Hartley’s test (p ⩾ 0.05). Differences among groups were assessed by means of Student-t test for independent samples (two groups) or one-way ANOVA followed by Fisher LSD test. Pearson products (r) were used to evaluate the strength of correlation among the parameters evaluated. A p-value below 0.05 was considered significant. All statistical analyses were performed using Statistica 7.0 (StatSoft Inc., USA). The

mean values of the total phenols, flavonoids, DPPH and FRAP of the extraction performed on apples with methanol are Afatinib concentration shown in Table 3. The total phenols of the methanol extraction ranged statistically (p < 0.001) from 457.93 (assay number 8) to 599.09 mg/100 g (central point). The highest values for total phenols were observed at the central point of the experimental design with 85.0% methanol for 15 min at 25 °C (central point). The multiple regression analysis of total phenol values showed that the model was significant (p <   0.001), did not present lack of fit (p   = 0.16) and it could explain 80.91% of all variance in data ( Radj2 = 0.80). The quadratic regression coefficient of concentration (X3) was negative and significant. The predicted model can be described by the (Eq. 2) in terms of coded values. equation(2) Y=578.93-80.83X32 The results suggested that time and temperature had negligible effects on the yield of total phenols. The extraction of flavonoids ranged significantly

(p   < 0.001) from Interleukin-3 receptor 106.81 (assay number 5) to 167.95 mg/100 g (central point). 85.0% methanol for 15 min at 25 °C were the best combination for flavonoids extraction. The model of flavonoids extraction was significant (p   < 0.001), did not present lack of fit (p   = 0.28) and it could explain 88.38% of variance in data (( Radj2 = 0.82). Time (X1) significantly increased the flavonoid extraction, and quadratic regression coefficient of time (X1), concentration(X3) and interactions of time (X1) and temperature (X2); time (X1) and concentration (X3) had a significantly negative effect Eq. (3): equation(3) Y=160.63+9.68X1-11.68X12-14.28X32-11.19X1X22-16.35X1X3. Diluted methanol (85%) was more effective in the extraction of apple phenolic compounds; it revealed that a mixture of solvents and water are more efficient than the mono-solvent system in phenolic extraction (Spigno et al., 2007). Some phenolic compounds occur naturally as glycosides (Shahidi & Naczk, 2004) and the presence of sugars makes the phenolic compounds more water soluble.