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Optimum Conditions for Microwave Assisted Extraction for Recovery of Phenolic Compounds and Antioxidant Capacity from Macadamia (Macadamia tetraphylla) Skin Waste Using Water Adriana Dailey † and Quan V. Vuong †, * Received: 2 November 2015; Accepted: 29 December 2015; Published: 31 December 2015 Academic Editor: Michael Henson School of Environmental and Life Sciences, University of Newcastle, Newcastle, NSW 2258, Australia; [email protected] * Correspondence: [email protected]; Tel.: +61-2-4348-4124; Fax: +61-2-4348-4145 † These authors contributed equally to this work.

Abstract: This study aimed to develop optimal microwave assisted extraction conditions for recovery of phenolic compounds and antioxidant properties from the macadamia skin, an abundant waste source from the macadamia industry. Water, a safe, accessible, and inexpensive solvent, was used as the extraction solvent and Response Surface Methodology (RSM) was applied to design and analyse the conditions for microwave-assisted extraction (MAE). The results showed that RSM models were reliable for the prediction of extraction of phenolic compounds and antioxidant properties. Within the tested ranges, MAE radiation time and power, as well as the sample-to-solvent ratio, affected the extraction efficiency of phenolic compounds, flavonoids, proanthocyanidins, and antioxidant properties of the macadamia skin; however, the impact of these variables was varied. The optimal MAE conditions for maximum recovery of TPC, flavonoids, proanthocyanidins and antioxidant properties from the macadamia skin were MAE time of 4.5 min, power of 30% (360 W) and sample-to-water ratio of 5 g/100 mL. Under these conditions, an extract could be prepared with TPC of 45 mg/g, flavonoids of 29 mg RUE/g of dried macadamia skin. Keywords: by-products; macadamia; skin; waste; bioactive; antioxidant

1. Introduction Waste generated throughout the cycle of food production is known as a major problem of the food industry as it not only has adverse effects on the environment and human health, but is also associated with high costs for treatment [1,2]. Many attempts have been made to retrieve, recycle, or utilise wasted by-products in order to reduce the negative effects and/or to add more value for the food industry [2]. The macadamia is known as a native plant of Australia with two more popular species, the Macadamia integrifolia (smooth shelled) and the Macadamia tetraphylla (rough shelled) (Figure 1) [3]. Approximately 8300 tons of macadamia kernel alone were produced in 2012 with a value of more than $120 million [4]. As the kernel itself only accounts for approximately 20% of the total weight of the plant, while the skin and husk total approximately 80% of the fruit weight, it can be estimated that about 18,000 tons of skin, and a similar amount of husk, are generated. However, only small portions of this waste have been utilized to produce activated carbon material [5], to make furniture panels [6], to use as a renewable fuel source for energy production and to prepare garden mulch [3]. It should also be noted that the global production of macadamia has been projected to increase about 10% annually, resulting

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in moreinwaste being generated from the macadamia industry [4]. Therefore, it is necessary to develop more waste being generated from the macadamia industry [4]. Therefore, it is necessary to develop methods to utilize the large quantities of of waste macadamia industry. methods to utilize the large quantities wastefrom from the the macadamia industry.

Figure 1. Macadamia tetraphylla nuts.

Figure 1. Macadamia tetraphylla nuts. Phenolic compounds are generally found in vegetables, fruits, and many food sources that commonly form a largeare portion of the human In the earlyfruits, 1960s, phenolic compounds were that Phenolic compounds generally founddiet in[7]. vegetables, and many food sources considered as a metabolic waste product stored in the plant vacuole [8]. Today they are known as commonly form a large portion of the human diet [7]. In the early 1960s, phenolic compounds one of the most concentrated and therapeutically useful bioactive substances [7]. Besides plant were considered as a metabolic waste product stored in the plant vacuole [8]. Today they are materials, phenolic compounds can be abundant in agro-industrial wastes and by-products [9]. known Phenolic as one of the most have concentrated and attention therapeutically useful bioactive [7]. compounds attracted great for their potential use in thesubstances food industry andBesides plant materials, phenolic compounds can be abundant in agro-industrial wastes and by-products [9]. therapeutic effects as a health promoter [10]. Therefore, it is worthy to recover the phenolic Phenolic compounds have attracted great attention for their potential use in the food industry and compounds and antioxidants from macadamia skin. extraction [10]. (MAE) has been widely applied the recovery of bioactive therapeutic Microwave-assisted effects as a health promoter Therefore, it is worthy to for recover the phenolic compounds compounds and it is considered one of the dominant trends in the “green chemistry” movement and antioxidants from macadamia skin. [11,12,13]. Application of MAE not only reduces the extraction time and amount of solvent required, Microwave-assisted extraction (MAE) has been widely applied for the recovery of bioactive but also increases the extraction yield with less degradation of bioactive compounds [12,14,15]. compounds and itthis is considered one ofMAE the dominant trendsofinphenolic the “green chemistry” Therefore, study employed for the recovery compounds andmovement antioxidant[11–13]. Application of MAE not only reduces the extraction time and amount of solvent required, but also capacity from macadamia skin. Water, which is a safe, accessible, and cheap solvent, was used as the increases the extraction with less Surface degradation of bioactive Therefore, extraction solvent, yield and Response Methodology (RSM)compounds was applied[12,14,15]. for designing experimental conditions and analyzing theof experimental data to reduceand the number of experiments this study employed MAE for the recovery phenolic compounds antioxidant capacity from and toskin. determine thewhich relationships between different on the response variables macadamia Water, is a safe, accessible, andvariables cheap solvent, was used as the[16]. extraction Therefore, the aim of this study was to apply RSM for development of the optimal microwave assisted solvent, and Response Surface Methodology (RSM) was applied for designing experimental conditions extraction conditions for recovery of phenolic compounds and antioxidant properties from the and analyzing the experimental data to reduce the number of experiments and to determine the macadamia skin using water for further isolation and utilization.

relationships between different variables on the response variables [16]. Therefore, the aim of this 2. Materials Methods study was to applyand RSM for development of the optimal microwave assisted extraction conditions for recovery of phenolic compounds and antioxidant properties from the macadamia skin using water for 2.1. Materials further isolation and utilization.

Macadamia (Macadamia tetraphylla) nuts were collected from the Central Coast region, New South Australia (latitude of 33.4° S, longitude of 151.4° E) in July of 2014. The skin of the nuts 2. MaterialsWales, and Methods was separated from the harvested nuts and then frozen in liquid nitrogen immediately and freeze dried (FD3 freeze dryer, Thomas Australia Pty. Ltd., Seven Hills, NSW, Australia) in order to 2.1. Materials minimise oxidation or degradation of phenolic compounds. The dried skin was then ground into Macadamia (Macadamia nuts were(John collected the Central CoastNSW, region, New South small particle sizes usingtetraphylla) a commercial blender Morrisfrom Scientific, Chatswood, Australia) ˝ ˝ Wales, Australia (latitude 33.4mesh S, longitude of 151.4 E) Endecotts in July ofLtd., 2014. The skin the nuts was and then sieved usingof a steel sieve (1.4 mm EFL 2000; London, UK). of The dried ground skin kept in a sealed and then labelled container at 5 °Cnitrogen until further analysed. and freeze dried separated from thewas harvested nuts and frozen in liquid immediately

(FD3 freeze dryer, Thomas Australia Pty. Ltd., Seven Hills, NSW, Australia) in order to minimise oxidation or degradation of phenolic compounds. The dried skin was then ground into small particle sizes using a commercial blender (John Morris Scientific, Chatswood, NSW, Australia) and then sieved using a steel mesh sieve (1.4 mm EFL 2000; Endecotts Ltd., London, UK). The dried ground skin was kept in a sealed and labelled container at 5 ˝ C until further analysed.

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2.2. Chemicals All chemicals used in this study were analytical grade. Methanol and potassium persulfate were purchased from Merck (Damstadt, Germany). Folin-ciocalteau phenol regent, anhydrous sodium carbonate, sodium nitrile, ferric chloride, gallic acid, rutin, catechin, neocuproine, 2,4,6-Tris(2-pyridyl)-s-triazine, (˘)-6-hydroxy-2,5,7,8-tetramethylchromane-2-carboxylic acid (trolox) and 2,2-Diphenyl-1-picrylhydrazyl (DPPH) were purchased from Sigma-Aldrich Co. (Castle Hill, New South Wales (NSW), Australia). Sodium acetate trihydrate was purchased from Government Stores Department (Sydney, NSW, Australia). Aluminium chloride was obtained from Ajax Chem. (Sydney, NSW, Australia) and hydrochloric acid was obtained from Lab-scan Ltd. (South Australia, Australia).

2.3. Microwave-Assisted Extraction (MAE) Water was chosen as the extraction solvent as it is a safe and inexpensive solvent, and it is easily accessible when compared to other organic solvents [17]. The microwave extraction was conducted using a household microwave equipped with inverter technology (1200 W, Frequency 2450 MHz, Sharp Carousel, Abeno-ku, Osaka, Japan) at the pre-determined conditions that were designed by the Response Surface Methodology program for time (minutes), power (%, W), and sample-to-solvent ratio (g/100 mL). When the extraction was completed, the vessels were then immediately placed into an ice bath to cool to room temperature. The extracts were then filtered using filter paper (Lomb Scientific, Taren Point, NSW, Australia) and diluted for quantitative analysis. 2.4. Response Surface Methodology Response Surface Methodology (RSM) software was used to design experiments and analyse results, via JMP software (Version 11) with a Box-Behnken design with three central point replicates. The optimum range of the microwave variables was preliminarily identified and the range for microwave time was 2.5–5.5 min, power was 30%–70% (360–840 W) and sample-to-solvent ratio was 2–8 g/100 mL. The independent variables and their code variable levels are shown in Table 1. The JMP software was also used to develop the model equation, to graph 3D plots and 2D contour plots of the responses, as well as predicting the optimum conditions of the independent variables. Table 1. Box-Behnken design and the observed responses. Run

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

Experimental Conditions

Experimental Results

X1

X2

X3

TPC

Flavonoids

2.5 4 4 5.5 2.5 2.5 4 4 4 5.5 5.5 2.5 4 4 5.5

50 30 70 50 30 70 50 50 50 30 70 50 30 70 50

2 2 2 2 5 5 5 5 5 5 5 8 8 8 8

63.71 111.43 69.43 68.35 35.76 48.20 32.88 40.46 32.40 44.10 18.23 30.21 33.25 43.06 33.36

13.07 21.10 19.88 23.31 6.22 16.28 26.22 35.09 36.62 26.41 3.65 13.17 16.74 15.14 17.02

ProanthoABTS cyanidins 16.34 37.63 10.38 17.09 11.18 9.42 22.18 17.59 17.03 18.35 7.98 17.43 22.32 34.97 23.52

172.56 544.67 343.02 289.65 147.32 308.87 352.19 319.28 298.35 390.75 46.60 123.23 254.67 217.87 190.58

DPPH

CUPRAC

FRAP

200.21 479.79 396.25 348.96 143.60 216.62 331.00 283.93 340.53 287.67 43.33 138.00 240.19 258.69 193.72

426.42 726.33 683.01 606.29 287.39 360.86 583.11 475.93 718.12 459.83 99.88 320.20 472.72 544.95 526.64

58.39 119.07 64.89 91.89 48.04 47.49 91.22 86.21 71.35 86.24 17.99 42.74 68.69 75.21 101.28

X1 (time, min), X2 (power, %, W) and X3 (sample-to-solvent ratio, g/100 mL). TPC (mg GAE/g of dried weight), Flavonoids (mg RUE/g of dried weight), Proanthocyanidins (mg CE/g of dried weight), ABTS (µM TE/g of dried weight), DPPH (µM TE/g of dried weight), CUPRAC (µM TE/g of dried weight) and FRAP (µM TE/g of dried weight).

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To express the amount of phenolic compounds and the level of antioxidant properties as a function of the independent variables, a second-order polynomial equation must be employed [17]: Y “ βo `

k ÿ

β i Xi `

i“1

kÿ ´1

k ÿ

i“1 iăj

j “2

β ij Xi X j `

k ÿ

β ii X2i

(1)

i“1

where various Xi values are independent variables affecting the responses Y; β0 , βi , βii and βij are the regression coefficients for intercept, linear, quadratic, and interaction terms, respectively; and k is the number of variables. The three independent variables were assigned as: X1 (time, min), X2 (power, %, W), and X3 (sample-to-solvent ratio, g/100 mL). Thus, the function containing these three independent variables is expressed as follows: Y “ β 0 ` β 1 X1 ` β 2 X2 ` β 3 X3 ` β 12 X1 X2 ` β 13 X1 X3 ` β 23 X2 X3 ` β 11 X12 ` β 22 X22 ` β 33 X32

(2)

2.5. Methods for the Determination of Chemical Properties 2.5.1. Total Phenolic Content (TPC) The total phenolic content (TPC) was determined as described by Vuong et al. [18]. 1 mL of diluted sample was added with 5 mL of 10% (v/v) Folin-Ciocalteu reagent, followed by the addition of 4 mL of 7.5% (w/v) Na2 CO3 , then combined well on a vortex mixer and incubated in the dark at room temperature for one hour before the absorbance was measured at 760 nm using a UV spectrophotometer (Varian Australia Pty. Ltd., Mulgrave, Victoria, Australia). A standard curve was created using gallic acid and the results were then specified in mg of gallic acid equivalents per g of sample (mg GAE/g). 2.5.2. Total Flavonoids The total flavonoid content was measured as described by Zhishen et al. [19]. 0.5 mL of diluted sample was added with 2 mL of H2 O and 0.15 mL of 5% (w/v) NaNO2 and left at room temperature for 6 min. Next 0.15 mL of 10% (w/v) AlCl3 was added and left at room temperature for a further 6 min. Lastly 2 mL 4% (w/v) NaOH and 0.7 mL of H2 O were added, and the final solution was mixed well and left at room temperature for a further 15 min before the absorbance was measured at 510 nm using a UV spectrophotometer. A standard curve was designed using rutin and the results were then specified in mg of rutin equivalents per gram of sample (mg RUE/g). 2.5.3. Proanthocyanidins The amount of proanthocyanidins was determined as described by Li et al. [20]. 0.5 mL of diluted sample was added to 3 mL of 4% (w/v) of vanillin and then 1.5 mL of concentrated HCl was added and left at room temperature for 15 min before measurement of the absorbance at 500 nm using a UV spectrophotometer. A standard curve was designed through the use of catechin and the results were expressed as mg of catechin equivalents per gram of sample (mg CE/g). 2.6. Methods for the Determination of Antioxidant Properties 2.6.1. ABTS Radical Scavenging Capacity ABTS radical scavenging capacity was determined according to the methods described by Thaipong et al. [21] and Kamonwannasit, et al. [22] with some modifications. A stock solution was prepared by adding 10 mL of 7.4 mM ABTS solution to 10 mL of 2.6 mM K2 S2 O8 and left at room temperature in the dark for 15 h, and then stored at ´20 ˝ C until required. The working solution was freshly prepared by mixing 1 mL of stock solution with 60 mL of methanol to obtain an absorbance

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value of 1.1 ˘ 0.02 at 734 nm. 0.15 mL of sample was added with 2.85 mL of the working solution and mixed, then left in the dark at room temperature for 2 h before its absorbance was measured at 734 nm using a UV-VIS spectrophotometer (Cary 50 Bio, Varian Australia Pty. Ltd.). A standard curve was designed through the application of trolox and the results were expressed as µMoles trolox equivalents per gram of dried sample (µM TE/g). 2.6.2. DPPH Radical Scavenging Activity The DPPH radical scavenging activity was measured based on the method described by Thaipong et al. [21], with some modifications. A stock solution was prepared by dissolving 24 mg DPPH in 100 mL methanol and then stored at ´20 ˝ C until required. The fresh working solution was prepared by mixing 10 mL stock solution in 45 mL methanol to obtain an absorbance at 515 nm of 1.1 ˘ 0.02. 0.15 mL of sample was mixed with 2.85 mL of working solution and then left in the dark, at room temperature for 3 h before measuring the absorbance at 515 nm using the UV spectrophotometer. A standard curve was designed through the use of trolox and the results were expressed as µMoles of trolox equivalents per g of sample (µM TE/g), as seen with ABTS radical scavenging activity. 2.6.3. Cupric Reducing Antioxidant Capacity (CUPRAC) CUPRAC was determined as described by Apak et al. [23] with a minor adjustment. 1 mL of CuCl2 , 1 mL of neocuproine and 1 mL of NH4 Ac were added and then 1.1 mL of diluted sample was added. After combining well, the mixture was incubated at room temperature for 1.5 h before measuring the absorbance at 450 nm using the UV spectrophotometer. A standard curve was designed through the use of trolox and the results were expressed as µMoles of trolox equivalents per g of sample (µM TE/g). 2.6.4. Ferric Reducing Antioxidant Power (FRAP) FRAP was measured as described by Thaipong et al. [21] and Kamonwannasit et al. [22]. A working FRAP solution was prepared by mixing 300 mM Acetate buffer, 10 mM TPTZ in 40 mM HCl and 20 mM FeCl3 in the ratio of 10:1:1 and warmed at 37 ˝ C in a water bath (Ratek Instruments Pty. Ltd., Boronia, Victoria, Australia) before using. To 0.15 mL of sample, 2.85 mL of the working FRAP solution was added and incubated at room temperature in the dark for 30 min, after which its absorbance was read at 593 nm. A standard curve was designed through the use of trolox and the results were expressed as µMoles trolox equivalents per gram of dried sample (µM TE/g). 2.7. Statistical Analyses The statistical design program JMP (Version 11, SAS, Cary, NC, USA) was used to design the experiments and all the experiments were performed in triplicate. The program was used to create the model equation, to graph the 3D and 2D contour plots of the responses and to predict the optimum values for the independent variables. The Student’s t-test from SPSS software (Version 20, IBM, Armonk, NY, USA) was applied to compare the sample means. The differences between the sample means were chosen at the significance level of p < 0.05. 3. Results and Discussion 3.1. Statistical Analysis and Fitting of the Model In order to ensure that the RSM mathematical models are reliable in the prediction of MAE conditions for TPC, flavonoids, proanthocyanidins, and the antioxidant capacity from the skin of the macadamia, different statistical analyses of variation including “lack of fit”, R squared, Predicted Residual Sum of Square (PRESS), F ratio, and Prob > F were identified and examined and the results are shown in Table 2. The “lack of fit” is able to calculate whether the model has the expected impact, and the R squared value is able to assess the proportion of variation that occurs in the response that is

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able to be accounted for by the model, rather than by random error, therefore an R squared value that nears 1 indicates that the model is a strong predictor of the response [24]. Results (Table 2) showed that “lack of fit” for phenolic compounds, flavonoids, proanthocyanidins, and four antioxidant assays were significantly higher than 0.05, meaning that the models for phenolic compounds and antioxidant Processes 2016, 4, 1 6 of 15 properties were fitted and reliable for prediction of the actual values. Furthermore, R squared values for phenolic compounds and antioxidant were higher thanthat 0.82,the indicating thatphenolic at least 82% antioxidant assays were significantly properties higher than 0.05, meaning models for of thecompounds predicted values could be matched with the actual values. and antioxidant properties were fitted and reliable for prediction of the actual values. Furthermore, R squared values for phenolic compounds and antioxidant properties were higher than Table Analysis variance for the determination of model fitting. 0.82, indicating that at2.least 82% ofofthe predicted values could be matched with the actual values. ProanthoAntioxidant Table 2. Analysis of variance for the determination of model fitting. Capacity TPC

TPC Lack of fit 0.167 2 0.95 R of fit Lack 0.167 2 0.87 Adjusted R2 R 0.95 PRESS 5129 Adjusted R2 0.87 F ratio of Model 11.13 PRESS 5129 Prob > F 0.01 F ratio of Model 11.13 Prob > F 0.01

Flavon-oids

Flavon-oids 0.892 0.93 0.892 0.81 0.93 439 0.81 7.60 439 0.02 7.60 0.02

cyanidins Proantho0.979 cyanidins 0.98 0.979 0.95 0.98 57 0.95 31.98 57 0.001 31.98 0.001

ABTS Antioxidant DPPH Capacity CUPRAC FRAP 0.136 0.989 0.525 0.239 ABTS DPPH CUPRAC FRAP 0.93 0.92 0.82 0.86 0.136 0.989 0.525 0.239 0.79 0.79 0.49 0.62 0.93 0.92 0.82 0.86 234,529 186,966 800,865 17,548 0.79 0.79 0.49 0.62 6.85 6.70 2.51 3.54 234,529 186,966 800,865 17,548 0.02 0.02 0.16 0.09 6.85 6.70 2.51 3.54 0.02 0.02 0.16 0.09

The PRESS value shows how well the predictive model fits each point in the design. The F Ratio PRESS how well predictive model fits each point the design. Theall F Ratio is the test The statistic forvalue a testshows of whether thethe model differs significantly from in a model where predicted is are the test statistic for a test Lastly, of whether model differs a model where all values the response mean. the the Prob > F is able significantly to measure from the probability of actually predicted are the Lastly, the Prob observed, > F is able in to measure the probability of obtaining an F values ratio that is asresponse high as mean. the one that is being the case where all parameters actually obtaining an F ratio that isSmaller as high Prob as the > one is being observed, in the case where all are zero, except for the intercept. F that values specify that the observed F ratio is parameters are zero, except for the intercept. Smaller Prob > F values specify that the observed F ratio highly unlikely [24]. The results (Table 2) showed that the PRESS, the F ratio and “Prob > F” for is highly unlikely [24]. The results (Table 2) showed that the PRESS, the F ratio and “Prob > F” for phenolic compounds, flavonoids, proanthocyanidins, and antioxidant properties all supported that the phenolic compounds, flavonoids, proanthocyanidins, and antioxidant properties all supported that mathematical models models for these are reliable for prediction of the values theseresponses. responses. the mathematical forresponses these responses are reliable for prediction of the valuesof of these The results (Figure 2) further showed the correlation between the predicted values and the The results (Figure 2) further showed the correlation between the predicted values and the actual actualvalues. values. from Figure the predicted for phenolic compounds, flavonoids As As seenseen from Figure 2, the2, predicted valuesvalues for phenolic compounds, flavonoids and and proathocyanidins werelinear lineartototheir theiractual actual values, indicating a close relationship further proathocyanidins were values, indicating a close relationship and and further supporting the mathematical modelswere werereliable reliable predictors predictors for responses. supporting that that the mathematical models forthese these responses.

Figure 2. The correlation between the predicted and the actual values for TPC, flavonoids,

Figure 2. The correlation between the predicted and the actual values for TPC, flavonoids, and proanthocyanidins. and proanthocyanidins.

The values (Y) for phenolic compounds, flavonoids and proanthocyanidins from the macadamia skin could be fitted to the below second-order polynomial Equations (3)–(5):

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𝑌𝑌𝑇𝑇𝑇𝑇𝑇𝑇 =(Y) 35.244467 − 1.7289𝑋𝑋 21.63091𝑋𝑋 The values for phenolic compounds, flavonoids proanthocyanidins from 1 − 5.700763𝑋𝑋 2 − and 3 − 9.576575𝑋𝑋 1 𝑋𝑋2 the macadamia 2 2 (3) − 0.373125𝑋𝑋 𝑋𝑋 + 12.95065𝑋𝑋 𝑋𝑋 − 7.029333𝑋𝑋 + 8.3548417𝑋𝑋 skin could be fitted to the below second-order polynomial Equations (3)–(5): 1 3 2 3 1 2 2 + 20.692542𝑋𝑋3 YTPC “ 35.244467 ´ 1.7289X1 ´ 5.700763X2 ´ 21.63091X3 ´ 9.576575X1 X2 ´ 𝑌𝑌𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 = 32.642667 + 2.7052375𝑋𝑋1 − 1.941475𝑋𝑋2 − 1.912388𝑋𝑋3 − 8.205𝑋𝑋1 𝑋𝑋2 (3) 0.373125X1 X3 ` 12.95065X2 X3 ´ 7.029333X1 2 ` 8.3548417X222 ` 20.692542X322 (4) − 1.597925𝑋𝑋1 𝑋𝑋3 − 0.0948𝑋𝑋2 𝑋𝑋3 − 10.53715𝑋𝑋1 − 8.966521𝑋𝑋2 − 5.463846𝑋𝑋3 2 YFlavonoids “ 32.642667 ` 2.7052375X1 ´ 1.941475X2 ´ 1.912388X3 ´ 8.205X1 X2 ´ (4) 2 2 2 𝑌𝑌𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜 = 18.933333 + 1.5706125𝑋𝑋 − 3.341063𝑋𝑋 + 2.10115𝑋𝑋 1.597925X 1 X3 ´ 0.0948X2 X3 ´ 10.53715X1 ´ 18.966521X2 ´25.463846X3 3 2 (5) − 2.1531𝑋𝑋1 𝑋𝑋2 + 1.335525𝑋𝑋1 𝑋𝑋3 + 9.976425𝑋𝑋2 𝑋𝑋3 − 7.465317𝑋𝑋1 2 2 YProanthocyanidins “ 18.933333 ` 1.5706125X ´ 3.341063X ` 2.10115X ´ 2.1531X X ` 2 3 2 1 1 + 0.2666333𝑋𝑋2 + 7.1262583𝑋𝑋3 (5) 1.335525X1 X3 ` 9.976425X2 X3 ´ 7.465317X1 2 ` 0.2666333X2 2 ` 7.1262583X3 2

Figure 3 further illustrated the correlation between the predicted values andand the the actual values for Figure 3 further illustrated the correlation between the predicted values actual values the four types of of antioxidant assays including DPPH, predicted for the four types antioxidant assays including DPPH,ABTS, ABTS,FRAP, FRAP,and andCUPRAC. CUPRAC. The The predicted values were found found to to be be linear linear with with the the actual actual values, values, with with the the R R squared squared value value for for DPPH, DPPH, ABTS, ABTS, values were FRAP, CUPRAC, of of 0.93, 0.93, 0.92, 0.92, 0.86, 0.86, and and 0.82, 0.82, respectively. respectively. These These results results further further supported supported that that FRAP, and and CUPRAC, the mathematical models also appropriate appropriate for the antioxidant antioxidant values values in in the the the mathematical models were were also for the the prediction prediction of of the current current study. study.

Figure 3. Correlation Correlation between between the the predicted predicted and and the the actual actual values values for Figure 3. for ABTS ABTS total total antioxidant antioxidant capacity, capacity, DPPH radical scavenging reducing antioxidant antioxidant power ferric DPPH free free radical scavenging capacity, capacity, cupric cupric reducing power (CUPRAC), (CUPRAC), and and ferric reducing antioxidant power power (FRAP). (FRAP). reducing antioxidant

The models could be fitted to the following second-order polynomial Equations (6)–(9): The models could be fitted to the following second-order polynomial Equations (6)–(9): 𝑌𝑌𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴 = 323.27111 + 20.698194𝑋𝑋1 − 52.63111𝑋𝑋2 − 70.44375𝑋𝑋3 − 126.4244𝑋𝑋1 𝑋𝑋2 2 YABTS “ 323.27111 ` 20.698194X 52.63111X22𝑋𝑋´ 70.44375X3 1´2 126.4244X − 12.4375𝑋𝑋 41.211111𝑋𝑋 + 23.082361𝑋𝑋 1´ 1 X2 ´ 1 𝑋𝑋3 + 3 − 122.969𝑋𝑋 2 2 2 2 2 12.4375X1 X3 ` 41.211111X − 6.297917𝑋𝑋 2 X3 3 ´ 122.969X1 ` 23.082361X2 ´ 6.297917X3 𝑌𝑌𝐷𝐷𝐷𝐷𝐷𝐷𝐷𝐷 = 318.48887 + 21.90625𝑋𝑋1 − 29.54325𝑋𝑋2 − 74.32553𝑋𝑋3 − 79.3389𝑋𝑋1 𝑋𝑋2 YDPPH “ 318.48887 ` 21.90625X1 ´ 29.54325X2 ´ 74.32553X3 ´2 79.3389X1 X2 ´2 − 23.25695𝑋𝑋 𝑋𝑋 + 25.51215𝑋𝑋2 𝑋𝑋3 − 14.596𝑋𝑋 1 − 11.08731𝑋𝑋 2 2 2 23.25695X1 X3 ` 25.51215X2 X31 ´2314.596X1 2 ´ 11.08731X 2 ` 36.329342X3 + 36.329342𝑋𝑋3 YCUPRAC “ 222.0527 ` 10.75407X+ 55.64071X2−´67.3052𝑋𝑋 67.3052X3−´59.8078𝑋𝑋 59.8078X1 ` 1` 𝑌𝑌𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶 = 222.0527 + 10.75407𝑋𝑋 55.64071𝑋𝑋 1 12 2 2 23 2 2 8.335271X1 X3 `+124.7403X 2 X𝑋𝑋 3 `+10.0905X 2 ` 104.4285X 3 1 `𝑋𝑋9.952907X 8.335271𝑋𝑋 124.7403𝑋𝑋 + 10.0905𝑋𝑋 + 9.952907𝑋𝑋 1 3 + 104.4285𝑋𝑋3 2

2 3

1

2

(6) (6)

(7) (7) (8) (8)

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𝑌𝑌𝐹𝐹𝐹𝐹𝐹𝐹𝐹𝐹 = 230.6576 + 49.23343𝑋𝑋1 + 13.09773𝑋𝑋2 − 36.3954𝑋𝑋3 + 22.71136𝑋𝑋1 𝑋𝑋2 − 4.04451𝑋𝑋1 𝑋𝑋3 + 48.2822𝑋𝑋2 𝑋𝑋3 + 57.01089𝑋𝑋1 2 + 31.90199𝑋𝑋2 2 + 6.542708𝑋𝑋3 2

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YFRAP “ 230.6576 ` 49.23343X1 ` 13.09773X2 ´ 36.3954X3 ` 22.71136X1 X2 ´ (9) 2 Compounds, Flavonoids, 2 2 3.2. Effect4.04451X of Extraction Independent Variables on Phenolic and Proanthocyanidins 1 X3 ` 48.2822X2 X3 ` 57.01089X1 ` 31.90199X2 ` 6.542708X3 The impact of MAE radiation time, power and sample-to-solvent ratio on the extraction of 3.2. Effect of Extraction Independent Variables on Phenolic Flavonoids, and Proanthocyanidins phenolic compounds (TPC) is shown in Figure 4 andCompounds, Table 3. The impact of MAE radiation time, power and sample-to-solvent ratio on the extraction of Table 3. Analysis of variance for the experimental results on TPC, flavonoids, and proanthocyanidins. phenolic compounds (TPC) is shown in Figure 4 and Table 3. TPC

Flavonoids

Proanthocyanidins

Parameter Table 3. AnalysisDF of variance for the experimental results on TPC, flavonoids, and proanthocyanidins.

Estimate Prob > |t| Estimate Prob > |t| Estimate Prob > |t| β0 1 35.24 0.0008 * 32.64 |t| Estimate Prob > |t| β2 1 Estimate −5.70 Prob0.1141 −1.94 Prob0.2322 −3.34 0.0038 * β0 β 3 1 1 35.24 0.0008 * * 32.64 |t| results Estimateon antioxidant Prob > |t| Estimate

1 323.27 0.0002 * 1 20.70 0.3471 ABTS 1 −52.63 0.0461 * Estimate Prob >0.0167 |t| * 1 −70.44 1 −126.42 0.0065 * 323.27 0.0002 * 1 −12.44 0.6778 20.70 0.3471 1 41.21 0.204 ´52.63 0.0461 * 1 −122.97 0.0086 * * 1´70.4423.08 0.01670.4675 ´126.42 * 1 −6.30 0.00650.8387

318.49 0.0001 * 21.91 DPPH 0.2828 −29.54 0.1656 Estimate > |t|* −74.33 Prob0.0095 −79.34 0.0274 * 318.49 0.0001 * −23.26 0.4079 21.91 0.2828 25.51 0.3673 ´29.54 0.1656 −134.60 0.004 * ´74.33 * −11.09 0.0095 0.6963 ´79.34 0.0274 * 36.33 0.2333

592.38 0.0004 * 37.22 0.4303 CUPRAC −32.20 0.4916 Estimate Prob > |t| −72.19 0.1572 −108.36 0.1378 592.38 0.0004 * 6.64 0.9181 37.22 0.4303 28.89 0.6578 ´32.20 0.4916 −213.63 0.0205 * ´72.19 0.1572 −76.77 0.2834 ´108.36 0.1378 91.13 0.2131

82.93 0.0003* 12.59 FRAP 0.0765 −14.56 0.0498 * Estimate Prob>|t| −5.79 0.3531 −16.93 0.088 82.93 0.0003* 6.26 0.4695 12.59 0.0765 15.18 0.1163 ´14.56 0.0498 * −20.69 0.0555 ´5.79 0.3531 −12.30 0.1997 ´16.93 0.088 11.34 0.2316

1 ´12.44 0.6778 ´23.26 0.4079 6.64 0.9181 6.26 0.4695 * Significantly different at p < 0.05; β0 : Intercept; β1 , β2 , and β3 : Linear regression coefficients for time, 1 41.21 0.204 25.51 0.3673 28.89 0.6578 15.18 0.1163 power sample-to-solvent β12 , β13 , and 0.004 β23 : Regression coefficients for *interaction between0.0555 1 and´122.97 0.0086 *ratio; ´134.60 * ´213.63 0.0205 ´20.69 time 1x power, time x sample-to-solvent ratio and0.6963 power x sample-to-solvent ratio; β11 ,´12.30 β22 , and β330.1997 : 23.08 0.4675 ´11.09 ´76.77 0.2834 1 ´6.30 0.8387 0.2333 91.13 and 0.2131 11.34 ratio x0.2316 Quadratic regression coefficients for36.33 time x time, power X power, sample-to-solvent

sample-to-solvent * Significantly differentratio. at p < 0.05; β0 : Intercept; β1 , β2 , and β3 : Linear regression coefficients for time, power and sample-to-solvent ratio; β12 , β13 , and β23 : Regression coefficients for interaction between time x power, impact of MAE ratio radiation time,xpower, and sample-to-solvent the ABTS antioxidant timeThe x sample-to-solvent and power sample-to-solvent ratio; β11 , β22 ,ratio and βon 33 : Quadratic regression coefficients for time x time, power and sample-to-solvent x sample-to-solvent capacity of the macadamia skinXispower, represented in Table 4 andratio Figure 7. The results ratio. showed that the

MAE radiation time did not have a significant impact, but the MAE power and the sample-to-solvent ratio did haveofa MAE significant impact on the ABTSand antioxidant capacity of the macadamia skin extract The impact radiation time, power, sample-to-solvent ratio on the ABTS antioxidant

capacity of the macadamia skin is represented in Table 4 and Figure 7. The results showed that the MAE radiation time did not have a significant impact, but the MAE power and the sample-to-solvent ratio did have a significant impact on the ABTS antioxidant capacity of the macadamia skin extract

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ProcessesThe 2016,higher 4, 1 of 15 lower (p < 0.05). the MAE power and sample-to-solvent ratio that were applied,11the (p < 0.05). The higher the MAE power and sample-to-solvent ratio that were applied, the lower the the antioxidant capacity obtained was. The results also showed that the interaction between time x antioxidant capacity The results also showedratio that that the interaction between timethe x (p < 0.05). The higherobtained the MAEwas. power and sample-to-solvent were applied, the lower sample-to-solvent ratio, and power x sample-to-solvent ratio did not have a significant impact, but the antioxidant capacity obtained was.x The results also showed that interaction between time sample-to-solvent ratio, and power sample-to-solvent ratio did notthe have a significant impact, butx interaction betweenbetween MAE time power had had a significant impact ononABTS capacity the interaction MAE time x power a significant impact ABTS antioxidantimpact, capacity of of the sample-to-solvent ratio, andxpower x sample-to-solvent ratio did not have a antioxidant significant but macadamia skin extract. themacadamia interaction between MAE time x power had a significant impact on ABTS antioxidant capacity of the skin extract.

the macadamia skin extract.

Figure 7. Impact of time (2.5–5.5 min), power (30%–70%, 360–840 W) and sample-to-solvent ratio

Figure 7. Impact of time (2.5–5.5 min), power (30%–70%, 360–840 W) and sample-to-solvent ratio Figure 7. Impact of time (2.5–5.5 min), power 360–840 W) and sample-to-solvent ratio (2–8 g/100 mL) on ABTS antioxidant capacity (µM(30%–70%, TE/g). (2–8 g/100 mL) on ABTS antioxidant capacity (µM TE/g). (2–8 g/100 mL) on ABTS antioxidant capacity (µM TE/g).

Figure 8. Impact of time (2.5–5.5 min), power (30%–70%, 360–840 W) and sample-to-solvent ratio (2–8 g/100 mL) on DPPH capacity (µM TE/g). Figure 8. Impact of timeantioxidant (2.5–5.5 min), power (30%–70%, 360–840 W) and sample-to-solvent ratio

Figure 8. Impact of time (2.5–5.5 min), power (30%–70%, 360–840 W) and sample-to-solvent ratio (2–8 g/100 mL) on DPPH antioxidant capacity (µM TE/g). (2–8 g/100 mL) on(Table DPPH4antioxidant (µM TE/g). The results and Figure capacity 8) illustrated the impact of MAE radiation time, power, and The results (Table 4 and Figurefree 8) illustrated the impact of MAE radiation time, power, and sample-to-solvent ratio on the DPPH radical scavenging capacity of the macadamia skin extract. sample-to-solvent on theFigure DPPH free radical scavenging capacityofof MAE the macadamia skin extract. The results (Tableratio 4 and 8) illustrated the impact radiation time, power,

and sample-to-solvent ratio on the DPPH free radical scavenging capacity of the macadamia skin extract. MAE radiation time and power were found not to significantly affect the DPPH, but the sample-to-solvent ratio did significantly affect the DPPH free radical scavenging capacity of the

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MAE radiation time and power were found not to significantly affect the DPPH, but the sample-tosolvent ratio didtime significantly affect the DPPH radical scavenging capacity of macadamia MAE radiation and wereAs found notinfree tothe significantly affectthe the DPPH, butthe the sample-tomacadamia skin extract (p power < 0.05). seen ABTS assay, interaction between time x skin extract < 0.05). As seen affect in the ABTS assay, the interaction between time x of sample-to-solvent solvent ratio(pdid significantly the DPPH free radical scavenging capacity the macadamia sample-to-solvent ratio, and power x sample-to-solvent ratio did not have a significant impact, but the ratio, and power x sample-to-solvent ratio assay, did not have a significant impact, the interaction skin extract (p < 0.05). As seen in the ABTS the interaction between time xbut sample-to-solvent interaction between MAE timehad x power had a significant impact on ABTScapacity antioxidant capacity of the between MAE time power a significant impact on ABTS antioxidant theinteraction macadamia ratio, and power x xsample-to-solvent ratio did not have a significant impact, butofthe macadamia skin extract (p < 0.05). skin extract (p