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Optimisation of mild-acidic protein extraction from defatted sunflower (Helianthus annuus L.) meal
Food Hydrocolloids 23 (2009) 1966–1973
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Optimisation of mild-acidic protein extraction from defatted sunflower (Helianthus annuus L.) meal Claudia Pickardt a, b, Sybille Neidhart a, *, Carola Griesbach b, Mark Dube a, Udo Knauf b, Dietmar R. Kammerer a, Reinhold Carle a a b
Institute of Food Science and Biotechnology, Chair of Plant Foodstuff Technology, Hohenheim University, Garbenstrasse 25, 70599 Stuttgart, Germany Fraunhofer Institute for Process Engineering and Packaging (IVV), Giggenhauser Strasse 35, 85354 Freising, Germany
a r t i c l e i n f o
a b s t r a c t
Article history: Received 28 August 2008 Accepted 2 February 2009
For protein isolation from defatted sunflower meal, mild-acidic extraction was investigated to minimise concomitant oxidation and polymerisation of phenolic compounds and their irreversible binding to proteins. Because of the impaired solubility of sunflower proteins at low pH, the potential of sodium chloride (NaCl) to improve protein extractability was firstly screened for pH 2–11. Increasing NaCl concentrations of the aqueous solvent (cNaCl) up to 2.8 mol/L enhanced the relative protein yield to almost 80% at ambient temperature and pH 5.6–7.4. As to improved protein recovery at minimal interactions with phenolic acids, the concerted effects of pH (3.2–7.4), cNaCl (1–3 mol/L), temperature (T, 15–45 C), and meal-to-solvent ratio (MSR, 0.03 and 0.05 g/mL) on the protein concentration of the extract (cPE) and the relative protein yield (RPY) were examined, using response surface methodology (RSM). Aside from the prevailing influence of pH value and salt concentration, elevated temperature slightly enhanced protein extraction, whereas MSR mainly influenced cPE, but hardly RPY. Calculated models proved suitable for the evaluation of extraction processes and the prediction of optimum conditions in terms of high protein yields at the lowest pH possible. Extraction at pH w6.0 was shown to be an appropriate compromise yielding 76–83% of the meal protein, depending on the constraints given. With elevated NaCl concentrations compensating for unfavourable pH conditions, mild-acidic extraction was found to be suitable for the recovery of high-quality sunflower protein in terms of light-coloured protein isolates. Ó 2009 Elsevier Ltd. All rights reserved.
Keywords: D-optimal design Polyphenol oxidation Protein extraction Sunflower Yield
1. Introduction Apart from soybeans, oil palm fruits and rapeseed, sunflower seeds (Helianthus annuus L.) are among the world’s most important oilseeds with a global production of 27.0 million tonnes in year 2007 (FAO, 2009). Sunflower seeds contain w20% of protein, whereas protein contents of the oil press cakes and extraction residues range from 30 to 50% (Dorrell & Vick, 1997). The technofunctional properties of sunflower proteins are comparable with those of soy and other leguminous proteins (Gonza´lez-Pe´rez et al., 2005). Although lysine deficiency is a major drawback from the nutritional point of view, proteins from sunflower press cake are considered a valuable alternative as food ingredients, since they are
* Corresponding author. Hohenheim University (150d), Institute of Food Science and Biotechnology, Chair of Plant Foodstuff Technology, Garbenstrasse 25, 70599 Stuttgart, Germany. Tel.: þ49 (0)711 459 22317; fax: þ49 (0)711 459 24110. E-mail address: [email protected] (S. Neidhart). 0268-005X/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodhyd.2009.02.001
low in antinutritional compounds and devoid of toxic substances (Gassmann, 1983; Gonza´lez-Pe´rez & Vereijken, 2007). The comparatively high content of phenolic compounds in Helianthus (w1–4% in defatted flour from dehulled seeds), mainly chlorogenic and caffeic acids (Sripad, Prakash, & Narasinga Rao, 1982; Saeed & Cheryan, 1988), has been the main restriction of sunflower protein application in food commodities so far. Conventional processes of protein extraction yield dark-coloured products with decreased nutritional and functional quality. This is mainly attributed to covalent binding of phenolic acids to reactive groups of the proteins, such as those of cysteine and lysine, during alkaline processing (Sosulski, 1979; Sahidi & Naczk, 2004). Therefore, utilisation of press residues from sunflower oil extraction is still mainly restricted to animal feed (Gonza´lez-Pe´rez et al., 2002). In terms of sustainable agricultural production, many attempts have been made to valorise the press residues by recovery of sunflower proteins devoid of co-extracted polyphenols, thus improving their nutritional and sensory performance. Common strategies, as reviewed by Gonza´lez-Pe´rez et al. (2002), comprise
C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
the extraction of sunflower meal with mixtures of organic solvents and water and subsequent protein recovery from the pre-extracted material. However, the use of organic solvents may not only cause protein denaturation but also high costs for solvent recovery and safety precautions. Pre-extraction with water has also been studied in great detail. Such processes either proved insufficient or timeconsuming (Taha & El-Nockrashy, 1981). In further approaches, oxygen was removed during alkaline protein extraction and antioxidants were added, respectively, to prevent polyphenol oxidation. Furthermore, the use of inert gases was combined with the removal of free polyphenols from alkaline extracts by membrane filtration (O’Connor, 1971). However, also this process has not been upscaled to practice so far, most probably due to tedious processing and high water consumption. Proteins from oilseeds are commonly extracted under alkaline conditions because of their solubility profile (Arntfield, 2004). Solubility of sunflower proteins in water exhibits a minimum around the isoelectric point (pH 4–5), where only approximately 10–20% of the protein is soluble (Pawar, Patil, Sakhale, & Agarkar, 2001). In contrast, protein extraction in the acidic region prevents irreversible binding of phenolic acids to proteins (Saeed & Cheryan, 1989). This facilitates the removal of free phenolic compounds from the extracts, which is a prerequisite to obtain colourless protein products. However, due to the poor solubility of sunflower proteins in the low-acid region, optimisation of protein extraction is required. Like proteins of other oilseeds, those of sunflower seeds mainly consist of globulins. Thus, the majority of the proteins is insoluble in water but can be extracted with 5% NaCl (Gheyasuddin, Cater, & Mattil, 1970). It is well known that the addition of salts enhances protein extractability, especially close to the isoelectric point. The pH region of minimum solubility (pH 4–6) is shifted towards lower pH values upon salt addition (Pawar et al., 2001). The effects of pH and various salt concentrations on protein extractability from sunflower meal have been studied by different authors as reviewed by Mieth, Lange, and Bru¨ckner (1984). Additionally, Gheyasuddin et al. (1970) investigated the effects of temperature and the meal-to-solvent ratio (MSR) on protein extractability. The effects of time and MSR were evaluated by Pawar et al. (2001). Although the effects of all those process parameters on the protein yield have been assessed separately, a systematic study of their concerted application is still lacking. Only scant attention has been paid to acidic protein extraction (Mieth & Roloff, 1985). Therefore, this study aimed at the identification of optimum conditions for mild-acidic protein extraction from sunflower seeds by combining the parameters pH, NaCl concentration, temperature, and MSR. By means of response surface methodology, the interaction of those parameters on protein yields were explored, after identifying the range of favourable NaCl concentrations in a previous pH-dependent screening.
2. Materials and methods 2.1. Materials Two batches 1 and 2 of dehulled confectionery sunflower seeds were purchased from local suppliers (Chiemgauer Naturkost, Unterreit-Gru¨nthal, and Gusto, Hohenpolding, Germany, respectively). Bovine serum albumin (BSA, Fraction V) and NaCl were obtained from VWR International (Darmstadt, Germany). All reagents and solvents were of analytical grade. NaCl solutions were prepared on a molar basis (Mr ¼ 58.44 g/mol). Deionised water was used throughout.
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2.2. Production of defatted sunflower meal (DSM) Dehulled seeds were flaked with a roller mill (Streckel & Schrader, Hamburg, Germany) at a gap width of 200 mm and defatted with n-hexane. For DSM 1, seed batch 1 (1 kg) was defatted for 24 h in a Soxhlet apparatus and desolventised over night in a cold air stream. DSM 2 was produced from 50 kg of seed batch 2, defatted in a pilot plant percolator (volume 1.5 m3, e&e Verfahrenstechnik, Warendorf, Germany) and flash-desolventised with hexane vapour at 400–500 mbar, prior to steam desolventation (maximum product temperature 60 C). The defatted flakes were ground in a pin mill (Alpine, Augsburg, Germany) until passing through a sieve of 0.5 mm mesh size. Protein contents (N 5.6) of DSM 1 and DSM 2 were 59.9 and 57.3%, respectively, total lipids amounted to 3.1 and 3.7%, and ash contents were 6.1 and 6.9% on a dry weight base (92.0% for both meals) according to standard methods (AOAC, 1990a, b; DGF, 2004). 2.3. Protein quantification The protein contents of DSM 1 and 2 were calculated from the nitrogen content (N 5.6) that was determined by the Dumas combustion method (AOAC, 1990a), using a Protein/Nitrogen Analyzer FP 528 (Leco, St. Joseph, MI, USA). This method was also applied to the protein extracts of experimental series 1, in addition to the Biuret method (AACC, 1983). By the latter, protein concentrations of all extracts obtained in series 1 and 2 were determined photometrically at 550 nm (spectrometer Lambda 25 UV/Vis, PerkinElmer Life and Analytical Sciences, Rodgau, Germany) in triplicate after calibration with BSA. Absolute deviation was always 0.02 absorbance units. Even though NaCl concentrations did not affect protein quantification, as previously verified, absorbance of each sample was corrected using a blank solution of the same NaCl concentration. If necessary, samples were diluted with appropriate NaCl solutions. 2.4. Setup for the screening of extraction parameters (series 1) In a first series, the effects of pH and NaCl concentration (cNaCl) on protein extractability (as relative protein yield, RPY, Eq. (1)) at ambient temperature (w25 C) were evaluated. Aqueous extraction of DSM 1 (60 min) was performed at pH 2.0, 3.8, 5.6, 7.4, 9.2, and 11.0. Each pH level was assessed in the presence of NaCl at concentrations of 0, 0.4, 0.8, 1.2, 1.6, 2.0, 2.4, 2.8, and 3.2 mol/L of solvent at constant MSR (0.05 g/mL), performing each run in duplicate. Protein contents of all samples were determined according to the Dumas combustion method. Extraction at NaCl levels of 0–2.0 mol/L was additionally monitored by protein quantification with the Biuret assay. 2.5. Setup for the optimisation of extraction parameters (series 2) For a second series, a modified D-optimal design for four factors (A–D) according to Petersen (1991) was chosen to evaluate the effects of the meal-to-solvent ratio (A ¼ MSR at two levels xMSR), temperature (B ¼ T at three levels xT), pH value (C ¼ pH at four levels xpH), and NaCl concentration (D ¼ cNaCl at four levels xCNaCl) on the protein concentration of the extracts (response R1 ¼ cPE) and the relative protein yield (response R2 ¼ RPY, Eq. (1)). The basic plan according to Petersen (1991) comprised 30 runs. In order to meet the requirements of the analytical software used for evaluation, complementary points were added, yielding a total of 38 runs. The factorial settings xi of all runs are listed in Table 1. Following the results of the previous screening (series 1), NaCl concentrations of 0, 1, 2, and 3 mol/L were selected. Considering minimal
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C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
Table 1 Mild-acidic protein extraction (pH 3.2–7.4; experimental series 2): protein concentration (cPE) and relative protein recovery (RPY) at various extraction conditions defined through the meal-solvent ratio (MSR), temperature (T), pH value and salt concentration (cNaCl). Run
Factors
No.
A: MSR
38 9 7 28 10 34 3 32 37 20 12 1 8 15 27 36 5 29 26 4 30 16 17 18 24 23 14 21 13 25 2 35 6 22 11 31 19 33
Responses B: T
C: pH
(g/mL)
( C)
0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.03 0.03 0.05 0.03 0.05 0.05 0.05 0.03 0.03 0.05 0.03 0.03 0.03 0.05 0.05 0.05 0.03 0.03 0.03 0.05 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03
45 45 15 45 15 15 15 45 45 30 45 45 45 15 30 30 30 15 45 30 15 30 30 45 15 15 30 45 30 15 30 30 15 15 45 15 15 30
7.4 7.4 7.4 7.4 7.4 7.4 6.0 6.0 6.0 6.0 7.4 7.4 4.6 7.4 4.6 4.6 4.6 7.4 7.4 4.6 6.0 7.4 7.4 3.2 3.2 3.2 4.6 3.2 4.6 4.6 3.2 3.2 3.2 6.0 3.2 3.2 3.2 3.2
R2: RPYb
D: cNaCl
R1: cPEa
(mol/L)
(g/L)
n
(g/g)
2.98 1.00 2.98 1.00 2.98 1.99 1.00 2.98 1.00 1.00 2.98 2.98 1.00 1.00 1.99 1.00 0.01 2.98 0.01 0.01 2.98 0.01 0.01 1.99 1.99 1.99 0.01 1.99 0.01 0.01 1.99 2.98 2.98 0.01 2.98 0.01 0.01 2.98
27.5 A 25.7 B 25.6 B 25.4 B 24.9 C 23.3 D 23.3 D 22.8 E 22.7 E 22.4 E 15.8 F 15.2 G 14.7 H 13.6 I 13.2 IJ 12.8 JK 12.3 K 11.8 L 11.5 LM 11.4 LM 11.2 M 8.4 N 8.4 N 7.8 O 7.2 P 6.8 PQ 6.3 QR 6.0 RS 5.8 ST 5.4 T 4.5 U 3.9 V 3.9 V 3.9 V 3.9 V 3.8 V 3.8 V 3.5 V
6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 4 6 6 6 6 6 6 6 6 6 6 6 6
1.010 A 0.938 CD 0.975 AB 0.926 D 0.950 BCD 0.882 E 0.879 E 0.836 F 0.827 F 0.832 F 0.970 BC 0.937 CD 0.535 I 0.859 EF 0.490 J 0.475 J 0.471 JK 0.746 G 0.709 H 0.435 KL 0.707 H 0.534 I 0.531 I 0.290 N 0.231 PQ 0.221 PQ 0.402 LM 0.372 M 0.371 M 0.207 Q 0.278 NO 0.249 OP 0.243 OP 0.246 OP 0.237 PQ 0.243 OP 0.239 PQ 0.224 PQ
Means with the same letter within one column were not significantly different (p < 0.05). a Means of n analyses (subjected to Duncan test). b Means of 2 analyses (subjected to Tukey test).
concentration changes caused by pH adjustment, recalculated effective NaCl levels (cNaCl settings xCNaCl) were 0.01, 1.00, 1.99 and 2.98 mol/L, respectively. MSR was set to 0.03 and 0.05 g/mL (xMSR), ensuring complete dispersion of the meal in the solvent at reasonable protein levels. A broad pH range was included by pH levels of 3.2, 4.6, 6.0, and 7.4 (xpH). Process temperatures of practical relevance were considered by setting T to either 15, 30, or 45 C (xT), with a thermostatted water bath ensuring reliable temperature control for all settings. All settings were encoded (xA–xD), using 1 for the lowest level of a factor and þ1 for the respective maximum with equidistant intermediate stages [xA ¼ (xMSR 0.04)/0.01; xB ¼ (xT 30)/15; xC ¼ (xpH 5.3)/2.1; xD ¼ (xCNaCl 1.495)/1.485]. Based on a randomised order, each run was performed in duplicate. Protein contents were quantified using the Biuret assay.
2.6. Extraction of proteins Extraction of DSM samples was performed according to Morr et al. (1985) with slight modifications. Depending on MSR, 1.5–2.5 g of DSM was mixed with 40 mL of NaCl solution (0–3.2 mol/L) in
a 100 mL beaker. Under constant magnetic stirring (w200 rpm) at ambient temperature (series 1) or in a water bath (series 2), target pH values were adjusted with 1 and 0.1 M HCl or NaOH, respectively, during the first 15 min of extraction and re-adjusted after 30 and 45 min, if necessary, using a pH-metre WTW 353 with temperature sensor. After a total time of 60 min, the mixture was quantitatively transferred to a volumetric flask and the volume was made up to 50 mL with the respective salt solution. Temperatureinduced volume deviations at 45 C relative to the standard temperature (20 C) were considered in further calculations. Suspensions were centrifuged at 20,000 g for 15 min at 20 C and the supernatants were filtered through Whatman folded filters 595 ½ of 150 mm diameter (Schleicher & Schuell MicroScience, Dassel, Germany). The clarified extracts were stored at 5 C until analysis within 24 h maximum and re-tempered at 20 C before photometric analysis. Protein concentrations of the extracts (cPE in g/L) were analyzed by the Biuret assay. Relating the protein amount of the extract (mPE in g) to that of the sunflower meal used (mPM in g), protein extractability was calculated as relative protein yield (RPY in g/g) according to Eq. (1) from the total volume of the crude extract (vE in L), the protein concentration of the clarified extract (cPE in g/L), the meal weight (mM in g), and the protein content of the meal (cPM in g/g). Although cPE and RPY were intimately related to each other by Eq. (1), both variables were studied as responses R1 and R2, respectively, because the former is of importance in further extract processing and hence exerts an influence on the total protein yield of the production process as a whole.
Response R1 : Response R2 :
cPE RPY ¼ mPE =mPM ¼ vE ,cPE = mM ,cPM
(1)
2.7. Statistical analyses All values measured per response variable were subjected to analyses of variance (one-way ANOVA) and subsequent multiple pairwise comparisons of respective means, using the GLM procedure of the Statistical Analysis System (SAS version 9.1; SAS Institute, Cary, NC, USA) to explore significance of differences at p < 0.05. Means of RPY, resulting from n ¼ 2 extractions, were compared by dint of Tukey’s studentised range test. Duncan’s multiple range test was applied to the protein contents (cPE) of the extracts, including all cPE records of both extractions (Table 1). Impacts of the independent parameters xi (i ¼ A–D) of the Doptimal design (series 2) on the dependent variable yk (k ¼ R1–R2, Eq. (1)) were estimated by response surface fitting to a reduced quadratic model (Eq. (2); Petersen, 1991) with the approximated coefficients bi and the experimental variance e. For factor A (MSR), no quadratic term (bAAx2A) was included in Eq. (2), because calculation of quadratic effects requires more than two levels (Petersen, 1991).
yk ¼ b0 þ bA xA þ bB xB þ bC xC þ bD xD þ bAB xA xB þ bAC xA xC þ bAD xA xD þ bBC xB xC þ bBD xB xD
(2)
þ bCD xC xD þ bBB x2B þ bCC x2C þ bDD x2D þ e Using Design-Expert software version 6 (Stat-Ease, Minneapolis, MN, USA), regression analysis was repeatedly carried out for each response variable, successively rejecting insignificant terms by backward elimination (p < 0.05), until all terms finally included were either at significance levels 95% or maintained as linear term (main effect) crucial for model hierarchy. Significance of models and individual terms was indicated by corresponding F-values and transgression probabilities (p).
C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
To identify the overall optimal processing conditions, the models obtained for R1 and R2 in series 2 were subjected to the numerical optimisation routine of the Design-Expert software. The multiple response method of Derringer and Suich (Myers & Montgomery, 1995) was applied with 10 starting points. Based on its desirability function, the responses R1 and R2 were maximised for desired ranges of factor settings, after ranking them according to their relative importance among each other from 1 for the least to 5 for the most important optimisation goal. The full desirability range of 0–1 corresponded to the full range of each response variable as preset by the respective two extreme values observed. While combining the individual desirability values of all constraint factors and the respective response goals of R1 and R2, overall desirability was maximised, with a value of 1 representing full achievement of all individual goals. 3. Results and discussion 3.1. Potential of sodium chloride to enhance protein extractability at pH 2–11 In series 1, the suitable range of pH and cNaCl for acidic extraction of sunflower proteins was explored for subsequent process optimisation. At each pH level, protein recovery from DSM 1 in various NaCl solutions was determined by stepwise increase of cNaCl, until maximal protein extractability (Eq. (1)) was reached (Fig. 1). Aside from significant effects of cNaCl, the expected strong dependence of protein yields on the pH value became evident. Without NaCl, minimal recovery of w16.7% was observed at pH 3.8–5.6, consistent with other reports of a minimum between pH 4 and 6 (Gheyasuddin et al., 1970; Pawar et al., 2001). At pH 2 and 3.8, i.e. in a range below the isoelectric point of most of the sunflower proteins, overall protein extractability was poor (20–30%) and further decreased upon NaCl addition. Beyond this acidic range, recovery rates showed a steady upward trend with increasing pH value. Maximum yields (95%) were obtained under strong alkaline conditions (pH 11), nearly irrespective of cNaCl. In contrast, a pronounced effect of cNaCl on protein recovery was observed under slightly acidic to neutral conditions (pH 5.6–7.4). Low NaCl doses added are known to increase sunflower protein extractability due to the globular nature of the major sunflower protein fraction. Qualitatively consistent with previous studies on the extractability of sunflower (Gheyasuddin et al., 1970; Pawar et al., 2001) and
100
RPY (g/g)
80 60 40 20 0
0.0
0.8
1.6
2.4
3.2
C NaCl (mol/L) Fig. 1. Influence of NaCl concentrations (cNaCl in mol/L) on the relative protein yield (RPY in g/g) from defatted sunflower meal (DSM 1) at (6) pH 2.0, (B) pH 3.8, (-) pH 5.6, (:) pH 7.4, (,) pH 9.2, and (>) pH 11.0 [ambient temperature, MSR ¼ 0.05 g/mL (2.5 g/50 mL)]. Protein quantification as N 5.6 by the Dumas combustion method. Means of two extractions (n ¼ 2). Only absolute deviations >0.01 g/g from the mean are shown by error bars (maximum deviation: 0.057 g/g).
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linseed proteins (Dev, Quensel, & Hansen, 1986), the protein yield was enhanced with rising cNaCl within the range of pH 4–8 and decreased at pH <3 (Fig. 1). However, in our study, protein recovery at pH 5.6 and at pH 7.4 followed a constant upward trend with increasing cNaCl up to a maximum at 2.4–2.8 mol/L. Only upon further increase of cNaCl (2.8–3.2 mol/L), protein extractability slightly declined. At pH 9.2, maximal extractability also occurred at 2.4–2.8 mol/L, in addition to another maximum at 1.2 mol/L. The same trend was observed at pH 11 to a much weaker extent. Thus, the pH value was most crucial for protein recovery, because maximum yields at pH 11 were not attained with any combination of pH and cNaCl at lower pH values. However, interactions between cNaCl and pH considerably modulated protein recovery within the range of pH 5.6–7.4. Supportive NaCl concentrations were significantly higher than those found in earlier studies, where protein extractability was investigated up to a cNaCl level of 2 mol/L, with protein yields declining above 1.0 mol/L at pH >6 (Gheyasuddin et al., 1970). Another study similarly revealed maximum solubility (92–88%) at 1–1.5 mol/L. However, since extractions were only reported for 1.0, 2.0, and 3.0–6.0 mol/L, intermediate concentrations might result in better solubility (Bau, Mohtadi-Nia, Mejean, & Debry, 1983). At alkaline pH >8, linseed protein extraction was diminished by addition of NaCl (Dev et al., 1986). But within the mild-acidic to slightly alkaline range (pH 5–8), protein extractability rose again when cNaCl was ramped to 1.0 mol/L, without application of higher NaCl doses. The same trend was observed for sesame seed protein (Rivas, Dench, & Caygill, 1981). The different findings obtained in the present study might be attributed to different methods and materials (sunflower variety, pretreatment) and the limited cNaCl range explored in some of the previous studies.
3.2. Attainable protein recovery at pH 3.2–7.4 under optimised process parameters Key role and limits of NaCl addition for partial compensation of pH conditions impairing protein extraction were well documented by Fig. 1, as discussed above. At the same time, a shift of the extract colour from faint yellow to dark green with rising pH values of the solutions was observed, revealing a greenish colour already at pH 7 and clear green at pH 8. This observation is in accordance with the report of Cater, Gheyasuddin, and Mattil (1972), whereby coextraction of chlorogenic acid resulted in green protein isolates upon further processing due to irreversible polyphenol binding. As stated by Mieth, Roloff, Kozlowska, and Rotkiewicz (1982), chlorogenic acid is readily oxidised at pH >8, but quite stable against oxidation at pH <8. Therefore, extraction below pH 8 is indispensable for the stabilisation of phenolic acids, avoiding their oxidation and covalent binding to proteins. According to our observations, pH <7, or even pH <6, is required to obtain lightcoloured sunflower protein. Consequently, the pH range of 3.2–7.4 was explored in more details for further optimisation of acidic protein extraction in terms of yield and purity (colour). The use of elevated cNaCl would not only enhance the protein yield, as shown above, but may also be conducive to a light-colour of the extracts (Mieth & Roloff, 1985). Apart from NaCl, further modulation of protein extraction at suboptimal pH levels was expected from temperature and MSR. Hence, all four decisive factors were included in the D-optimal design of series 2. Significant differences among results of individual runs of series 2 were indicated in Table 1. Among the 38 process variants, the protein concentrations cPE of the extracts ranged from 3.5 to 27.5 g/L, corresponding to an almost 8-fold increase. The relative deviation between cPE levels of duplicate runs was always <3%.
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C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
As revealed by comparative application of the Biuret and the Dumas method to extracts obtained at pH 2.0–7.4 and cNaCl 2 mol/L in series 1 (data not shown), both methods showed good correlation (R2 ¼ 0.92), although relative deviation for individual data pairs was up to 10–20%. Thus, protein recovery under identical extraction conditions in series 1 and 2 was not directly comparable when different DSM and protein quantification methods were used. With RPY rising 4.5-fold from 22.4–101.0% in series 2 (Table 1), the protein yield (Eq. (1)) at pH 3.2–7.4 was generally higher than in series 1 (Fig. 1). Slight overestimation of maximum RPY in series 2 might be attributed to different protein quantification methods applied to meal (Dumas combustion method) and extracts (Biuret method), including errors resulting from the conversion of N to protein and co-solutes interfering with the Biuret assay, such as co-extracted phenolics. The effects of the four extraction parameters and their interactions on cPE and RPY were described by the respective regression models in Tables 2 and 3, based on Eq. (2). The importance of each factor was evaluated using the equations calculated from the encoded factors, as discussed below. Since each of them ranged from 1 to þ1, the effects of all parameters were directly comparable, irrespective of individual units. 3.3. Extraction parameters influencing protein concentration and relative yield (RPY) at pH 3.2–7.4 All four parameters studied significantly influenced the protein concentrations of the extracts (cPE, Table 2) and the relative protein yield (RPY, Table 3) at pH 3.2–7.4 in the form of linear effects or in more complex ways. With coefficients of determination (R2) of 0.96 and 0.93, respectively, the overall correlation of cPE and RPY values predicted by the models with the measured values was high, despite some deviations of individual data sets (Figs. 2A/B). The prevailing influence of the pH value (factor C) became evident by the linear terms for C, where the coefficients reached by far the highest levels (bC ¼ 6.6 and 0.292, respectively) among all terms of the models, except for b0 (Tables 2A and 3A). Beside its linear effect as a single factor, interactions of the pH value with MSR and particularly cNaCl played significant roles, described by respective two-factor terms. In addition to this interaction, the key role of cNaCl in modulating pH-dependent protein extraction was expressed by the squared terms for D (bDD ¼ 2.687 for cPE and 0.127 for RPY), modifying the great direct impact of cNaCl described by significant linear terms.
Table 2 Protein concentration of the extracts (cPE) resulting from extractions at various sets of extraction parameters A–D, i.e. meal-solvent ratio A ¼ MSR (0.03–0.05 g/mL), temperature B ¼ T (15–45 C), pH value C (pH 3.2–7.4), and NaCl concentration of the solvent D ¼ cNaCl (0.01–2.98 mol/L): regression model for cPE (in g/L) (A.) computed with encoded factor settingsa and (B.) reconverted to effective factor levels. A. cPE
B. cPE
F-valueb
p
¼13.943 þ3.516 xA þ1.105 xB þ6.618 xC þ1.202 xD 2.687 x2D þ2.674 xA xC þ1.387 xC xD
¼7.549 323.193 xMSR þ0.0736 xT 2.606 xpH þ2.095 xcNaCl 1.218 xc2NaCl þ127.318 xMSR xpH þ0.445 xpH xcNaCl
93.60* 8.92* 287.12* 10.20* 10.27* 49.37* 7.49*
<0.0001 0.0056 <0.0001 0.0033 0.0032 <0.0001 0.0103
97.98*
<0.0001
Model: R2 ¼ 0.96 a
Factors xi encoded from 1 (low level) to þ1 (high level); xA ¼ (xMSR 0.04)/ 0.01; xB ¼ (xT 30)/15; xC ¼ (xpH 5.3)/2.1; xD ¼ (xcNaCl 1.495)/1.485. b F-values marked by an asterisk (*) and respective terms were significant (p < 0.05); p, transgression probability.
Table 3 Relative protein yield (RPY) resulting from extractions at various sets of extraction parameters A–D, i.e. meal-solvent ratio A ¼ MSR (0.03–0.05 g/mL), temperature B ¼ T (15–45 C), pH value C (pH 3.2–7.4), and NaCl concentration of the solvent D ¼ cNaCl (0.01–2.98 mol/L): regression model for RPY (in g/g) (A.) computed with encoded factor settingsa and (B.) reconverted to effective factor levels. A. RPY
B. RPY
F-valueb
p
¼0.634 þ0.019 xAc þ0.047 xB þ0.292 xC þ0.064 xD 0.127 x2D þ0.048 xA xC þ0.086 xC xD
¼0.239 10.265 xMSRc þ0.003 xT þ0.006 xpH þ0.069 xcNaCl 0.057 xc2NaCl þ2.298 xMSR xpH þ0.028 xpH xcNaCl
1.35 7.82* 271.60* 13.82* 11.09* 7.81* 13.93*
0.2548 0.0089 <0.0001 0.0008 0.0023 0.0090 0.0008
60.42*
<0.0001
Model: R2 ¼ 0.93 a
Factors xi encoded from 1 (low level) to þ1 (high level); xA ¼ (xMSR 0.04)/ 0.01; xB ¼ (xT 30)/15; xC ¼ (xpH5.3)/2.1; xD ¼ (xcNaCl 1.495)/1.485. b F-values marked by an asterisk (*) and respective terms were significant (p < 0.05); p, transgression probability. c Hierarchical term (insignificant) retained during backward elimination regression.
The main effects on RPY at pH 3.2–7.4 are illustrated by Figs. 3A/B, confirming the suitable pH and cNaCl ranges of series 1 for RPY maximisation under mild-acidic conditions. As cPE and RPY were intimately related to each other (Eq. (1)), the major effects on both responses were similar, apart from the impacts of MSR (Tables 2 and 3). For the design of efficient extraction processes, RPY is crucial. Unlike cPE, this relative variable is independent of dilution effects. Thus, results of different parameter settings and scales can easily be compared on this basis. However, the protein concentrations of the extracts (cPE) are of interest as regards further processing of the latter, e.g. protein precipitation, and were therefore specifically included in this study as a response variable (Table 2). Under the technical conditions applied, the DSM was well dispersed at both MSR levels used. Providing higher amounts of the protein source by raising MSR from 0.03 to 0.05 g/mL thus facilitated diffusion during the preset extraction time by an overall higher concentration gradient and enhanced cPE. In this way, MSR exerted a highly significant influence on the latter. However, in case of RPY, the importance of MSR was limited to the mentioned interaction with the pH value. Owing to this significant involvement, the linear MSR term was included because of model hierarchy, despite its missing significance (Table 3). The overall weak influence of MSR became evident when the response surfaces computed for each of both levels studied were compared (Figs. 3A,B). RPY faintly increased, when MSR rose from 0.03 to 0.05 g/ mL, consistent with a report on the extraction of cowpea proteins (Sefa-Dedeh & Stanley, 1979), ascribing the enhancing effect of MSR to less dilution of the intrinsic meal ash and hence higher ion concentrations in the extract solutions. Complexation and interaction of proteins with co-extracted polysaccharides as well as rising viscosity affecting separation of the proteins during centrifugation of the extracts may be further reasons (Oomah, Mazza, & Cui, 1994). Contrasting results were obtained for defatted linseed flour (Dev et al., 1986), whereas MSR insignificantly affected protein extractability from sunflower flour in a study of Gheyasuddin et al. (1970). A minor linear effect on cPE and RPY was attributed to temperature (Tables 2A and 3A). With increasing T up to the maximum of 45 C, protein concentrations and the resulting yields steadily increased, consistent with a study on the extraction of cowpea proteins (Sefa-Dedeh & Stanley, 1979). The low temperature influence is corroborated by Gheyasuddin et al. (1970), reporting an insignificant effect of temperature on protein extraction in the
C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
1971
experiments shown in Table 4, the weak temperature effect on the protein yield was irrelevant in practice (no. 1 vs. no. 3). Mutually compensating effects occurring at small differences of pH and cNaCl led to equal cPE and RPY (no. 1 vs. no. 2). Accuracy of the models was limited by the given preciseness of both the analytical methods and the parameter settings, beside unidentified minor effects. The Biuret determination might be affected by complexation of the copper reagent through coextracted phytic acid (Saeed & Cheryan, 1988) and by interfering carbohydrates. Nevertheless, the two models of Tables 2 and 3 were suitable to visualise the principal impact of the extraction parameters on protein recovery. Parameter screening (series 1) and process optimisation (series 2) were consistent in terms of observed extraction yields. In view of the relatively low impact of small parameter changes and the accuracy of prediction,
Fig. 2. Quality of the prediction of (A) the experimental protein concentrations of the extracts (cPE in g/L) by the model in Table 2 (R2 ¼ 0.96) and (B) the experimental protein yields (RPY in g/g) by the model in Table 3 (R2 ¼ 0.93) after protein extraction from defatted sunflower meal (DSM 2) at pH 3.2–7.4.
range of 26–60 C, although a slight maximum was observed at 45 C. 3.4. Validation of the models To verify the models presented in Tables 2 and 3, further protein extractions were performed by analogy to those of experimental series 2. However, parameter settings other than the previous design points were used (Table 4). To allow direct comparison of individual pairs, three intermediate levels were chosen for cNaCl and pH, while T was varied at two levels, i.e. room temperature and elevated temperature. For MSR, only the upper level was selected because of its higher practical relevance. The experimental results were compared to the predicted values. The protein yields topped predicted RPY levels by 14–30%, but ranged within the 95% prediction intervals or at least within those of 99% probability (extraction no. 3). Similarly, the cPE readings exceeded the predicted values, but were always close to the upper limits of the 95% prediction intervals. According to the individual pairs of
Fig. 3. Protein yields (RPY in g/g) achievable by extraction from defatted sunflower meal (DSM 2) at pH 3.2–7.4: response surface computed for RPY by Design-Expert according to Table 3 as a function of pH and NaCl concentration (cNaCl) at 30 C and a MSR of (A) 0.03 g/mL and (B) 0.05 g/mL. Base isolines indicate equal RPY levels.
1972
C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
Table 4 Protein concentration of the extracts (cPE in g/L) and relative protein yield (RPY in g/g) of extractions at MSR ¼ 0.05 g/mL performed for verification of the models in Tables 2 and 3. No.
pH
T ( C)
cNaCl (mol/L)
1
5.6
45
1.4
2
5.7
45
1.2
3
5.6
20
1.4
4
6.4
20
0.4
Response Parameter
Detected
Predicted
PI (95%)
PI (99%)
cPE RPY cPE RPY cPE RPY cPE RPY
23.3 0.86 24.0 0.89 22.9 0.87 19.3 0.74
19.79 0.74 19.94 0.74 17.95 0.67 18.71 0.65
15.87–23.71 0.57–0.92 16.02–23.85 0.57–0.92 14.05–21.85 0.49–0.84 14.73–22.69 0.47–0.83
14.51–25.07 0.50–0.98 14.66–25.21 0.50–0.98 12.70–23.20 0.43–0.90 13.35–24.07 0.41–0.89
PI, prediction interval at a probability level of 95 and 99%, respectively.
problem-oriented optimum operating ranges rather than an optimal working point may be deduced from the presented models. The studies were performed on the small laboratory scale, which allowed a multitude of experiments to explore a broad range of parameter settings. For practical reasons, single batch extraction with magnetic stirring was used. To achieve highly reproducible results despite small sample amounts, complete dispersion of the meal in the solvent was ensured by solvent excess, limiting MSR to comparatively low levels. Protein diffusion from the surface of the meal particles into the solvent was overall supported by the small particle sizes of the meal and the use of low MSR levels in combination with a long extraction time. By contrast, economic extraction on industrial scales would require higher MSR together with more vigorous stirring to accelerate extraction through maximum protein concentration gradients between meal and solvent and to improve efficiency of recovery through high protein concentrations of the extracts. Moreover, a counter-current process instead of the single batch extraction would enhance solvent efficiency in industrial practice. On the other hand, protein diffusion might be limited by minimised total extraction times and the use of flakes rather than meal. As indicated by the overall low impact of MSR on RPY (Fig. 3) despite great differences in protein concentrations of the extracts (Table 1), dispersion of the meal in the solvent and protein diffusion into the solvent were indeed not technically limiting factors in this study. Provided that both conditions are given, the RPY model (Table 3) is considered to be a valuable tool for the efficient optimisation of pH, cNaCl and T ranges in upscaling of sunflower protein extraction to industrial scales despite necessary technical adjustments.
3.5. Optimised mild-acidic protein extraction Whereas high pH values and optimum cNaCl of w2–2.8 mol/L were required for maximum protein extraction, a pH far below the alkaline range was the prerequisite for colourless protein extracts. To identify suitable operating ranges, the optimum conditions within the studied range were computed by numerical optimisation for maximum protein yield (RPY) at the lowest pH possible. Based on a medium priority of low pH, the calculated optimum was pH 6.0, where a maximum RPY of 84% would be achieved if cNaCl was set to 2.0 mol/L at maximum temperature (45 C) and MSR (0.05 g/mL) (Table 5A). Overall desirability for those parameter settings was only 61%, reflecting the compromise regarding the processing conditions. In addition to pH, the other factors may also be subjected to any constraints in practice. Although high cNaCl was shown to improve protein extractability, handling of the extracts, especially desalting, would be easier at lower salt concentrations. Extraction at low temperature would be favourable not only in terms of energy costs, but would also slow down oxidation of co-extracted phenolic acids, which are relatively stable at 20 C (Mieth et al., 1982). Furthermore, high protein concentrations may facilitate protein recovery by membrane filtration or precipitation. Considering these aspects, protein extraction at pH 6.1 at a salt concentration of 1.6 mol/L and 21 C is suggested (Table 5B). However, due to the described converse effects, i.e. unfeasible conformance to all requirements, maximum overall desirability was only 57% for those settings. Moreover, protein recovery would be reduced to 76% under these constraints.
Table 5 Proposed variants (no. 1–4) of extraction parameter settings for the production of light-coloured proteins from sunflower meal with predicted protein concentration of the extracts (cPE) and relative protein yields (RPY), as computed from the models in Tables 2 and 3 by numerical optimisation with Design-Expert according to the preset priority ranking of the response factors and parameter ranges. MSR (g/mL)
T ( C)
pH
A. Simple optimisation of extraction regarding maximum protein yield at low pH: Presettings 0.03–0.05 15–45 Minimise – – 2 Priority rankb Solution no 1 0.05 45 6.0 Solution no 2 0.05 45 6.0 Solution no 3 0.05 45 6.0 Solution no 4 0.05 45 5.9 B. Complex optimisation Presettings Priority rankb Solution no 1 Solution no 2 Solution no 3 Solution no 4 a b
cNaCl (mol/L)
cPE (g/L)
RPY (g/g)
Desirabilitya
0.01–2.98 – 2.0 2.0 2.0 2.0
3.5–27.5 – 21.9 22.0 22.1 21.6
Maximise 5 0.83 0.83 0.84 0.82
0–1 0.610 0.610 0.610 0.610
of extraction regarding maximum protein concentration of the extracts and maximum protein yield at low pH and under economic constraints: 0.03–0.05 Minimise Minimise Minimise Maximise Maximise 0–1 – 1 3 1 3 5 0.05 21 6.1 1.6 20.4 0.76 0.566 0.05 21 6.1 1.6 20.4 0.76 0.566 0.05 22 6.1 1.6 20.4 0.76 0.566 0.05 20 6.1 1.5 20.2 0.75 0.566
Overall desirability, with an ideal maximum level of 1 describing concurrent complete maximisation of each response factor. Ranks from 1 (lowest priority) to 5 (highest priority).
C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
Depending on the selected priorities, the extraction process may considerably differ from the examples proposed in Table 5. Through priority selection, further aspects, such as processing costs, in particular for subsequent desalting at high salt concentrations, may be included. 4. Conclusions Mild-acidic protein extraction (pH w6) at high salt concentrations (1.6–2.1 mol/L of solvent) was found to be suitable for the recovery of light-coloured proteins from sunflower seeds. The use of NaCl at such elevated concentrations suppressed protein-polyphenol interactions (Mieth & Roloff, 1985) and enhanced protein extractability to exploitable levels. The presence of NaCl compensated for pH conditions that were apparently suboptimal for protein extraction in terms of the yield, while green discoloration of the extracts was prevented. To obtain colourless protein isolates, removal of co-extracted phenolic acids is a prerequisite. As an alternative to the separation of phenolics by membrane filtration, the proposed procedure would also allow their removal by adsorption, which is facilitated by the low extract pH (Schieber, Hilt, Streker, Endreß, Rentschler, & Carle, 2003). Investigations to combine both processes are currently under way. Acknowledgement This research project was supported by the German Ministry of Economics and Technology (via AIF) and the FEI (Forschungskreis der Erna¨hrungsindustrie e.V., Bonn). Project AiF 14449 N. References AACC (1983). Method 46–15: Crude protein – 5-minute Biuret method for wheat and other grains. In Approved methods of the American Association of Cereal Chemists (8th edition). St. Paul, MN, USA: American Association of Cereal Chemists. AOAC (1990a). Method 968.06. Protein (crude) in animal feed. In Official methods of analysis of the Association of Official Analytical Chemists (15th edition). Washington, DC: Association of Official Analytical Chemists. AOAC (1990b). Method 923.03. Ash of flour. In Official methods of analysis of the Association of Official Analytical Chemists (15th edition). Washington, DC: Association of Official Analytical Chemists. Arntfield, S. D. (2004). Proteins from oil-producing plants. In R. Y. Yada (Ed.), Proteins in food processing (pp. 146–175). Boca Raton, Boston, New York, Washington, DC: CRC Press. Bau, H. M., Mohtadi-Nia, D. J., Mejean, L., & Debry, G. (1983). Preparation of colorless sunflower protein products: effect of processing on physicochemical and nutritional properties. Journal of the American Oil Chemists’ Society, 60, 1141–1148. Cater, C. M., Gheyasuddin, S., & Mattil, K. F. (1972). The effect of chlorogenic, quinic and caffeic acids on the solubility and color of protein isolates, especially from sunflower seed. Cereal Chemistry, 49, 508–514. Dev, D. K., Quensel, E., & Hansen, R. (1986). Nitrogen extractability and buffer capacity of defatted linseed (Linum usitatissimum L.) flour. Journal of the Science of Food and Agriculture, 37, 199–205. DGF (2004). Method of Caviezel, DGF K-I 2c (00). In Deutsche Gesellschaft fu¨r Fettwissenschaft e.V., Mu¨nster. DGF-Einheitsmethoden (2nd edition). Stuttgart: WVG. Dorrell, D. G., & Vick, B. A. (1997). Properties and processing of oilseed sunflower. In A. A. Schneiter (Ed.), Sunflower technology and production (pp. 709–744). Madison, Wisconsin: American Society of Agronomy.
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FAO (2009). FAOSTAT-Agriculture, last update 11 June 2008. FAO Statistics Division 2009, access date: 11 January 2009. http://faostat.fao.org/site/567/ DesktopDefault.aspx?PageID¼567#ancor. Gassmann, B. (1983). Preparation and application of vegetable proteins, especially proteins from sunflower seed, for human consumption. An approach. Die Nahrung, 27(4), 351–369. Gheyasuddin, S., Cater, C. M., & Mattil, K. F. (1970). Effect of several variables on the extractability of sunflower seed proteins. Journal of Food Science, 35, 453–456. Gonza´lez-Pe´rez, S., Merck, K. B., Vereijken, J. M., van Koningsveld, G. A., Gruppen, H., & Voragen, A. G. J. (2002). Isolation and characterization of undenatured chlorogenic acid free sunflower (Helianthus annuus) proteins. Journal of Agricultural and Food Chemistry, 50, 1713–1719. Gonza´lez-Pe´rez, S., van Koningsveld, G. A., Vereijken, J. M., Merck, K. B., Gruppen, H., & Voragen, A. G. J. (2005). Emulsion properties of sunflower (Helianthus annuus) proteins. Journal of Agricultural and Food Chemistry, 53, 2261–2267. Gonza´lez-Pe´rez, S., & Vereijken, J. M. (2007). Sunflower proteins: overview of their physicochemical, structural and functional properties. Journal of the Science of Food and Agriculture, 87, 2173–2191. Mieth, G., Lange, E., & Bru¨ckner, J. (1984). Sonnenblumensamen und deren Verarbeitungsprodukte. 1. Mitt. Aufkommen und wertbestimmende Bestandteile. Die Nahrung, 28, 533–577. ¨ ber die Qualita¨t und Ausbeute von Proteinpra¨parMieth, G., & Roloff, M. (1985). U aten aus Sonnenblumensamen beeinflussende Faktoren. 1. Mitt. Einflu¨sse von Samenbestandteilen und Prozessfu¨hrung auf die Farbe. Die Nahrung, 29, 441– 447. ¨ ber phenolische Mieth, G., Weiss, A., Kozlowska, H., & Rotkiewicz, D. A. (1982). U Inhaltsstoffe von Sonnenblumensamen. 1. Mitt. Modelluntersuchungen zum Absorptionsverhalten von Chlorogen- und Kaffeesa¨ure sowie deren Oxydationsprodukten. Die Nahrung, 26, 185–195. Morr, C. V., German, B., Kinsella, J. E., Regenstein, J. M., Van Buren, J. P., Kilara, A., Lewis, B. A., & Mangino, M. E. A. (1985). Collaborative study to develop a standardized food protein solubility procedure. Journal of Food Science, 50, 1715– 1718. Myers, R. H., & Montgomery, D. C. (1995). Response surface methodology: process and product in optimisation using designed experiments. New York: John Wiley and Sons. p. 244. O’Connor, D.E. (1971). Preparing light-colored protein isolate from sunflower meal by alkali extraction under an inert gas blanket followed by membrane ultrafiltration. US Patent 3622556. Oomah, B. D., Mazza, G., & Cui, W. (1994). Optimisation of protein extraction from flaxseed meal. Food Research International, 27, 355–361. Pawar, V. D., Patil, J. N., Sakhale, B. K., & Agarkar, B. S. (2001). Studies on nitrogen extractability of defatted sunflower meal. Journal of Food Science and Technology, 38, 217–219. Petersen, H. (1991). Plan no. 31.4.18: Modified D-Optimal design for 4 factors partly with 2 levels. In Grundlagen der Statistik und der statistischen Versuchsplanung. Landsberg/Lech, Germany: Ecomed. Rivas, N., Dench, J. E., & Caygill, J. C. (1981). Nitrogen extractability of sesame (Sesamum indicum L.) seed and the preparation of two protein isolates. Journal of the Science of Food and Agriculture, 32, 565–571. Saeed, M., & Cheryan, M. (1988). Sunflower protein concentrates and isolates low in polyphenols and phytate. Journal of Food Science, 53, 1127–1131, 1143. Saeed, M., & Cheryan, M. (1989). Chlorogenic acid interactions with sunflower proteins. Journal of Agricultural and Food Chemistry, 37, 1270–1274. Sahidi, F., & Naczk, M. (2004). Phenolics in food and neutraceuticals. Boca Raton, Ann Harbor, London, Tokyo: CRC Press. Schieber, A., Hilt, P., Streker, P., Endreß, H.-U., Rentschler, C., & Carle, R. (2003). A new process for the combined recovery of pectin and phenolic compounds from apple pomace. Innovative Food Science and Emerging Technologies, 4, 99– 107. Sefa-Dedeh, S., & Stanley, D. (1979). Cowpea Proteins. 1. Use of response surface methodology in predicting cowpea (Vigna unguiculata) protein extractability. Journal of Agricultural and Food Chemistry, 27, 1238–1243. Sosulski, F. W. (1979). Organoleptic and nutritional effects of phenolic compounds on oilseed protein products: a review. Journal of the American Oil Chemists’ Society, 56, 711–715. Sripad, G., Prakash, V., & Narasinga Rao, M. S. (1982). Extractability of polyphenols of sunflower seed in various solvents. Journal of Bioscience, 4, 145–152. Taha, F. S., & El-Nockrashy, A. S. (1981). Removal of chlorogenic acid from sunflower seed. Die Nahrung, 25, 473–478.
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Food Hydrocolloids journal homepage: www.elsevier.com/locate/foodhyd
Optimisation of mild-acidic protein extraction from defatted sunflower (Helianthus annuus L.) meal Claudia Pickardt a, b, Sybille Neidhart a, *, Carola Griesbach b, Mark Dube a, Udo Knauf b, Dietmar R. Kammerer a, Reinhold Carle a a b
Institute of Food Science and Biotechnology, Chair of Plant Foodstuff Technology, Hohenheim University, Garbenstrasse 25, 70599 Stuttgart, Germany Fraunhofer Institute for Process Engineering and Packaging (IVV), Giggenhauser Strasse 35, 85354 Freising, Germany
a r t i c l e i n f o
a b s t r a c t
Article history: Received 28 August 2008 Accepted 2 February 2009
For protein isolation from defatted sunflower meal, mild-acidic extraction was investigated to minimise concomitant oxidation and polymerisation of phenolic compounds and their irreversible binding to proteins. Because of the impaired solubility of sunflower proteins at low pH, the potential of sodium chloride (NaCl) to improve protein extractability was firstly screened for pH 2–11. Increasing NaCl concentrations of the aqueous solvent (cNaCl) up to 2.8 mol/L enhanced the relative protein yield to almost 80% at ambient temperature and pH 5.6–7.4. As to improved protein recovery at minimal interactions with phenolic acids, the concerted effects of pH (3.2–7.4), cNaCl (1–3 mol/L), temperature (T, 15–45 C), and meal-to-solvent ratio (MSR, 0.03 and 0.05 g/mL) on the protein concentration of the extract (cPE) and the relative protein yield (RPY) were examined, using response surface methodology (RSM). Aside from the prevailing influence of pH value and salt concentration, elevated temperature slightly enhanced protein extraction, whereas MSR mainly influenced cPE, but hardly RPY. Calculated models proved suitable for the evaluation of extraction processes and the prediction of optimum conditions in terms of high protein yields at the lowest pH possible. Extraction at pH w6.0 was shown to be an appropriate compromise yielding 76–83% of the meal protein, depending on the constraints given. With elevated NaCl concentrations compensating for unfavourable pH conditions, mild-acidic extraction was found to be suitable for the recovery of high-quality sunflower protein in terms of light-coloured protein isolates. Ó 2009 Elsevier Ltd. All rights reserved.
Keywords: D-optimal design Polyphenol oxidation Protein extraction Sunflower Yield
1. Introduction Apart from soybeans, oil palm fruits and rapeseed, sunflower seeds (Helianthus annuus L.) are among the world’s most important oilseeds with a global production of 27.0 million tonnes in year 2007 (FAO, 2009). Sunflower seeds contain w20% of protein, whereas protein contents of the oil press cakes and extraction residues range from 30 to 50% (Dorrell & Vick, 1997). The technofunctional properties of sunflower proteins are comparable with those of soy and other leguminous proteins (Gonza´lez-Pe´rez et al., 2005). Although lysine deficiency is a major drawback from the nutritional point of view, proteins from sunflower press cake are considered a valuable alternative as food ingredients, since they are
* Corresponding author. Hohenheim University (150d), Institute of Food Science and Biotechnology, Chair of Plant Foodstuff Technology, Garbenstrasse 25, 70599 Stuttgart, Germany. Tel.: þ49 (0)711 459 22317; fax: þ49 (0)711 459 24110. E-mail address: [email protected] (S. Neidhart). 0268-005X/$ – see front matter Ó 2009 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodhyd.2009.02.001
low in antinutritional compounds and devoid of toxic substances (Gassmann, 1983; Gonza´lez-Pe´rez & Vereijken, 2007). The comparatively high content of phenolic compounds in Helianthus (w1–4% in defatted flour from dehulled seeds), mainly chlorogenic and caffeic acids (Sripad, Prakash, & Narasinga Rao, 1982; Saeed & Cheryan, 1988), has been the main restriction of sunflower protein application in food commodities so far. Conventional processes of protein extraction yield dark-coloured products with decreased nutritional and functional quality. This is mainly attributed to covalent binding of phenolic acids to reactive groups of the proteins, such as those of cysteine and lysine, during alkaline processing (Sosulski, 1979; Sahidi & Naczk, 2004). Therefore, utilisation of press residues from sunflower oil extraction is still mainly restricted to animal feed (Gonza´lez-Pe´rez et al., 2002). In terms of sustainable agricultural production, many attempts have been made to valorise the press residues by recovery of sunflower proteins devoid of co-extracted polyphenols, thus improving their nutritional and sensory performance. Common strategies, as reviewed by Gonza´lez-Pe´rez et al. (2002), comprise
C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
the extraction of sunflower meal with mixtures of organic solvents and water and subsequent protein recovery from the pre-extracted material. However, the use of organic solvents may not only cause protein denaturation but also high costs for solvent recovery and safety precautions. Pre-extraction with water has also been studied in great detail. Such processes either proved insufficient or timeconsuming (Taha & El-Nockrashy, 1981). In further approaches, oxygen was removed during alkaline protein extraction and antioxidants were added, respectively, to prevent polyphenol oxidation. Furthermore, the use of inert gases was combined with the removal of free polyphenols from alkaline extracts by membrane filtration (O’Connor, 1971). However, also this process has not been upscaled to practice so far, most probably due to tedious processing and high water consumption. Proteins from oilseeds are commonly extracted under alkaline conditions because of their solubility profile (Arntfield, 2004). Solubility of sunflower proteins in water exhibits a minimum around the isoelectric point (pH 4–5), where only approximately 10–20% of the protein is soluble (Pawar, Patil, Sakhale, & Agarkar, 2001). In contrast, protein extraction in the acidic region prevents irreversible binding of phenolic acids to proteins (Saeed & Cheryan, 1989). This facilitates the removal of free phenolic compounds from the extracts, which is a prerequisite to obtain colourless protein products. However, due to the poor solubility of sunflower proteins in the low-acid region, optimisation of protein extraction is required. Like proteins of other oilseeds, those of sunflower seeds mainly consist of globulins. Thus, the majority of the proteins is insoluble in water but can be extracted with 5% NaCl (Gheyasuddin, Cater, & Mattil, 1970). It is well known that the addition of salts enhances protein extractability, especially close to the isoelectric point. The pH region of minimum solubility (pH 4–6) is shifted towards lower pH values upon salt addition (Pawar et al., 2001). The effects of pH and various salt concentrations on protein extractability from sunflower meal have been studied by different authors as reviewed by Mieth, Lange, and Bru¨ckner (1984). Additionally, Gheyasuddin et al. (1970) investigated the effects of temperature and the meal-to-solvent ratio (MSR) on protein extractability. The effects of time and MSR were evaluated by Pawar et al. (2001). Although the effects of all those process parameters on the protein yield have been assessed separately, a systematic study of their concerted application is still lacking. Only scant attention has been paid to acidic protein extraction (Mieth & Roloff, 1985). Therefore, this study aimed at the identification of optimum conditions for mild-acidic protein extraction from sunflower seeds by combining the parameters pH, NaCl concentration, temperature, and MSR. By means of response surface methodology, the interaction of those parameters on protein yields were explored, after identifying the range of favourable NaCl concentrations in a previous pH-dependent screening.
2. Materials and methods 2.1. Materials Two batches 1 and 2 of dehulled confectionery sunflower seeds were purchased from local suppliers (Chiemgauer Naturkost, Unterreit-Gru¨nthal, and Gusto, Hohenpolding, Germany, respectively). Bovine serum albumin (BSA, Fraction V) and NaCl were obtained from VWR International (Darmstadt, Germany). All reagents and solvents were of analytical grade. NaCl solutions were prepared on a molar basis (Mr ¼ 58.44 g/mol). Deionised water was used throughout.
1967
2.2. Production of defatted sunflower meal (DSM) Dehulled seeds were flaked with a roller mill (Streckel & Schrader, Hamburg, Germany) at a gap width of 200 mm and defatted with n-hexane. For DSM 1, seed batch 1 (1 kg) was defatted for 24 h in a Soxhlet apparatus and desolventised over night in a cold air stream. DSM 2 was produced from 50 kg of seed batch 2, defatted in a pilot plant percolator (volume 1.5 m3, e&e Verfahrenstechnik, Warendorf, Germany) and flash-desolventised with hexane vapour at 400–500 mbar, prior to steam desolventation (maximum product temperature 60 C). The defatted flakes were ground in a pin mill (Alpine, Augsburg, Germany) until passing through a sieve of 0.5 mm mesh size. Protein contents (N 5.6) of DSM 1 and DSM 2 were 59.9 and 57.3%, respectively, total lipids amounted to 3.1 and 3.7%, and ash contents were 6.1 and 6.9% on a dry weight base (92.0% for both meals) according to standard methods (AOAC, 1990a, b; DGF, 2004). 2.3. Protein quantification The protein contents of DSM 1 and 2 were calculated from the nitrogen content (N 5.6) that was determined by the Dumas combustion method (AOAC, 1990a), using a Protein/Nitrogen Analyzer FP 528 (Leco, St. Joseph, MI, USA). This method was also applied to the protein extracts of experimental series 1, in addition to the Biuret method (AACC, 1983). By the latter, protein concentrations of all extracts obtained in series 1 and 2 were determined photometrically at 550 nm (spectrometer Lambda 25 UV/Vis, PerkinElmer Life and Analytical Sciences, Rodgau, Germany) in triplicate after calibration with BSA. Absolute deviation was always 0.02 absorbance units. Even though NaCl concentrations did not affect protein quantification, as previously verified, absorbance of each sample was corrected using a blank solution of the same NaCl concentration. If necessary, samples were diluted with appropriate NaCl solutions. 2.4. Setup for the screening of extraction parameters (series 1) In a first series, the effects of pH and NaCl concentration (cNaCl) on protein extractability (as relative protein yield, RPY, Eq. (1)) at ambient temperature (w25 C) were evaluated. Aqueous extraction of DSM 1 (60 min) was performed at pH 2.0, 3.8, 5.6, 7.4, 9.2, and 11.0. Each pH level was assessed in the presence of NaCl at concentrations of 0, 0.4, 0.8, 1.2, 1.6, 2.0, 2.4, 2.8, and 3.2 mol/L of solvent at constant MSR (0.05 g/mL), performing each run in duplicate. Protein contents of all samples were determined according to the Dumas combustion method. Extraction at NaCl levels of 0–2.0 mol/L was additionally monitored by protein quantification with the Biuret assay. 2.5. Setup for the optimisation of extraction parameters (series 2) For a second series, a modified D-optimal design for four factors (A–D) according to Petersen (1991) was chosen to evaluate the effects of the meal-to-solvent ratio (A ¼ MSR at two levels xMSR), temperature (B ¼ T at three levels xT), pH value (C ¼ pH at four levels xpH), and NaCl concentration (D ¼ cNaCl at four levels xCNaCl) on the protein concentration of the extracts (response R1 ¼ cPE) and the relative protein yield (response R2 ¼ RPY, Eq. (1)). The basic plan according to Petersen (1991) comprised 30 runs. In order to meet the requirements of the analytical software used for evaluation, complementary points were added, yielding a total of 38 runs. The factorial settings xi of all runs are listed in Table 1. Following the results of the previous screening (series 1), NaCl concentrations of 0, 1, 2, and 3 mol/L were selected. Considering minimal
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C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
Table 1 Mild-acidic protein extraction (pH 3.2–7.4; experimental series 2): protein concentration (cPE) and relative protein recovery (RPY) at various extraction conditions defined through the meal-solvent ratio (MSR), temperature (T), pH value and salt concentration (cNaCl). Run
Factors
No.
A: MSR
38 9 7 28 10 34 3 32 37 20 12 1 8 15 27 36 5 29 26 4 30 16 17 18 24 23 14 21 13 25 2 35 6 22 11 31 19 33
Responses B: T
C: pH
(g/mL)
( C)
0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.03 0.03 0.05 0.03 0.05 0.05 0.05 0.03 0.03 0.05 0.03 0.03 0.03 0.05 0.05 0.05 0.03 0.03 0.03 0.05 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03
45 45 15 45 15 15 15 45 45 30 45 45 45 15 30 30 30 15 45 30 15 30 30 45 15 15 30 45 30 15 30 30 15 15 45 15 15 30
7.4 7.4 7.4 7.4 7.4 7.4 6.0 6.0 6.0 6.0 7.4 7.4 4.6 7.4 4.6 4.6 4.6 7.4 7.4 4.6 6.0 7.4 7.4 3.2 3.2 3.2 4.6 3.2 4.6 4.6 3.2 3.2 3.2 6.0 3.2 3.2 3.2 3.2
R2: RPYb
D: cNaCl
R1: cPEa
(mol/L)
(g/L)
n
(g/g)
2.98 1.00 2.98 1.00 2.98 1.99 1.00 2.98 1.00 1.00 2.98 2.98 1.00 1.00 1.99 1.00 0.01 2.98 0.01 0.01 2.98 0.01 0.01 1.99 1.99 1.99 0.01 1.99 0.01 0.01 1.99 2.98 2.98 0.01 2.98 0.01 0.01 2.98
27.5 A 25.7 B 25.6 B 25.4 B 24.9 C 23.3 D 23.3 D 22.8 E 22.7 E 22.4 E 15.8 F 15.2 G 14.7 H 13.6 I 13.2 IJ 12.8 JK 12.3 K 11.8 L 11.5 LM 11.4 LM 11.2 M 8.4 N 8.4 N 7.8 O 7.2 P 6.8 PQ 6.3 QR 6.0 RS 5.8 ST 5.4 T 4.5 U 3.9 V 3.9 V 3.9 V 3.9 V 3.8 V 3.8 V 3.5 V
6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 4 4 6 6 6 6 6 6 6 6 6 6 6 6
1.010 A 0.938 CD 0.975 AB 0.926 D 0.950 BCD 0.882 E 0.879 E 0.836 F 0.827 F 0.832 F 0.970 BC 0.937 CD 0.535 I 0.859 EF 0.490 J 0.475 J 0.471 JK 0.746 G 0.709 H 0.435 KL 0.707 H 0.534 I 0.531 I 0.290 N 0.231 PQ 0.221 PQ 0.402 LM 0.372 M 0.371 M 0.207 Q 0.278 NO 0.249 OP 0.243 OP 0.246 OP 0.237 PQ 0.243 OP 0.239 PQ 0.224 PQ
Means with the same letter within one column were not significantly different (p < 0.05). a Means of n analyses (subjected to Duncan test). b Means of 2 analyses (subjected to Tukey test).
concentration changes caused by pH adjustment, recalculated effective NaCl levels (cNaCl settings xCNaCl) were 0.01, 1.00, 1.99 and 2.98 mol/L, respectively. MSR was set to 0.03 and 0.05 g/mL (xMSR), ensuring complete dispersion of the meal in the solvent at reasonable protein levels. A broad pH range was included by pH levels of 3.2, 4.6, 6.0, and 7.4 (xpH). Process temperatures of practical relevance were considered by setting T to either 15, 30, or 45 C (xT), with a thermostatted water bath ensuring reliable temperature control for all settings. All settings were encoded (xA–xD), using 1 for the lowest level of a factor and þ1 for the respective maximum with equidistant intermediate stages [xA ¼ (xMSR 0.04)/0.01; xB ¼ (xT 30)/15; xC ¼ (xpH 5.3)/2.1; xD ¼ (xCNaCl 1.495)/1.485]. Based on a randomised order, each run was performed in duplicate. Protein contents were quantified using the Biuret assay.
2.6. Extraction of proteins Extraction of DSM samples was performed according to Morr et al. (1985) with slight modifications. Depending on MSR, 1.5–2.5 g of DSM was mixed with 40 mL of NaCl solution (0–3.2 mol/L) in
a 100 mL beaker. Under constant magnetic stirring (w200 rpm) at ambient temperature (series 1) or in a water bath (series 2), target pH values were adjusted with 1 and 0.1 M HCl or NaOH, respectively, during the first 15 min of extraction and re-adjusted after 30 and 45 min, if necessary, using a pH-metre WTW 353 with temperature sensor. After a total time of 60 min, the mixture was quantitatively transferred to a volumetric flask and the volume was made up to 50 mL with the respective salt solution. Temperatureinduced volume deviations at 45 C relative to the standard temperature (20 C) were considered in further calculations. Suspensions were centrifuged at 20,000 g for 15 min at 20 C and the supernatants were filtered through Whatman folded filters 595 ½ of 150 mm diameter (Schleicher & Schuell MicroScience, Dassel, Germany). The clarified extracts were stored at 5 C until analysis within 24 h maximum and re-tempered at 20 C before photometric analysis. Protein concentrations of the extracts (cPE in g/L) were analyzed by the Biuret assay. Relating the protein amount of the extract (mPE in g) to that of the sunflower meal used (mPM in g), protein extractability was calculated as relative protein yield (RPY in g/g) according to Eq. (1) from the total volume of the crude extract (vE in L), the protein concentration of the clarified extract (cPE in g/L), the meal weight (mM in g), and the protein content of the meal (cPM in g/g). Although cPE and RPY were intimately related to each other by Eq. (1), both variables were studied as responses R1 and R2, respectively, because the former is of importance in further extract processing and hence exerts an influence on the total protein yield of the production process as a whole.
Response R1 : Response R2 :
cPE RPY ¼ mPE =mPM ¼ vE ,cPE = mM ,cPM
(1)
2.7. Statistical analyses All values measured per response variable were subjected to analyses of variance (one-way ANOVA) and subsequent multiple pairwise comparisons of respective means, using the GLM procedure of the Statistical Analysis System (SAS version 9.1; SAS Institute, Cary, NC, USA) to explore significance of differences at p < 0.05. Means of RPY, resulting from n ¼ 2 extractions, were compared by dint of Tukey’s studentised range test. Duncan’s multiple range test was applied to the protein contents (cPE) of the extracts, including all cPE records of both extractions (Table 1). Impacts of the independent parameters xi (i ¼ A–D) of the Doptimal design (series 2) on the dependent variable yk (k ¼ R1–R2, Eq. (1)) were estimated by response surface fitting to a reduced quadratic model (Eq. (2); Petersen, 1991) with the approximated coefficients bi and the experimental variance e. For factor A (MSR), no quadratic term (bAAx2A) was included in Eq. (2), because calculation of quadratic effects requires more than two levels (Petersen, 1991).
yk ¼ b0 þ bA xA þ bB xB þ bC xC þ bD xD þ bAB xA xB þ bAC xA xC þ bAD xA xD þ bBC xB xC þ bBD xB xD
(2)
þ bCD xC xD þ bBB x2B þ bCC x2C þ bDD x2D þ e Using Design-Expert software version 6 (Stat-Ease, Minneapolis, MN, USA), regression analysis was repeatedly carried out for each response variable, successively rejecting insignificant terms by backward elimination (p < 0.05), until all terms finally included were either at significance levels 95% or maintained as linear term (main effect) crucial for model hierarchy. Significance of models and individual terms was indicated by corresponding F-values and transgression probabilities (p).
C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
To identify the overall optimal processing conditions, the models obtained for R1 and R2 in series 2 were subjected to the numerical optimisation routine of the Design-Expert software. The multiple response method of Derringer and Suich (Myers & Montgomery, 1995) was applied with 10 starting points. Based on its desirability function, the responses R1 and R2 were maximised for desired ranges of factor settings, after ranking them according to their relative importance among each other from 1 for the least to 5 for the most important optimisation goal. The full desirability range of 0–1 corresponded to the full range of each response variable as preset by the respective two extreme values observed. While combining the individual desirability values of all constraint factors and the respective response goals of R1 and R2, overall desirability was maximised, with a value of 1 representing full achievement of all individual goals. 3. Results and discussion 3.1. Potential of sodium chloride to enhance protein extractability at pH 2–11 In series 1, the suitable range of pH and cNaCl for acidic extraction of sunflower proteins was explored for subsequent process optimisation. At each pH level, protein recovery from DSM 1 in various NaCl solutions was determined by stepwise increase of cNaCl, until maximal protein extractability (Eq. (1)) was reached (Fig. 1). Aside from significant effects of cNaCl, the expected strong dependence of protein yields on the pH value became evident. Without NaCl, minimal recovery of w16.7% was observed at pH 3.8–5.6, consistent with other reports of a minimum between pH 4 and 6 (Gheyasuddin et al., 1970; Pawar et al., 2001). At pH 2 and 3.8, i.e. in a range below the isoelectric point of most of the sunflower proteins, overall protein extractability was poor (20–30%) and further decreased upon NaCl addition. Beyond this acidic range, recovery rates showed a steady upward trend with increasing pH value. Maximum yields (95%) were obtained under strong alkaline conditions (pH 11), nearly irrespective of cNaCl. In contrast, a pronounced effect of cNaCl on protein recovery was observed under slightly acidic to neutral conditions (pH 5.6–7.4). Low NaCl doses added are known to increase sunflower protein extractability due to the globular nature of the major sunflower protein fraction. Qualitatively consistent with previous studies on the extractability of sunflower (Gheyasuddin et al., 1970; Pawar et al., 2001) and
100
RPY (g/g)
80 60 40 20 0
0.0
0.8
1.6
2.4
3.2
C NaCl (mol/L) Fig. 1. Influence of NaCl concentrations (cNaCl in mol/L) on the relative protein yield (RPY in g/g) from defatted sunflower meal (DSM 1) at (6) pH 2.0, (B) pH 3.8, (-) pH 5.6, (:) pH 7.4, (,) pH 9.2, and (>) pH 11.0 [ambient temperature, MSR ¼ 0.05 g/mL (2.5 g/50 mL)]. Protein quantification as N 5.6 by the Dumas combustion method. Means of two extractions (n ¼ 2). Only absolute deviations >0.01 g/g from the mean are shown by error bars (maximum deviation: 0.057 g/g).
1969
linseed proteins (Dev, Quensel, & Hansen, 1986), the protein yield was enhanced with rising cNaCl within the range of pH 4–8 and decreased at pH <3 (Fig. 1). However, in our study, protein recovery at pH 5.6 and at pH 7.4 followed a constant upward trend with increasing cNaCl up to a maximum at 2.4–2.8 mol/L. Only upon further increase of cNaCl (2.8–3.2 mol/L), protein extractability slightly declined. At pH 9.2, maximal extractability also occurred at 2.4–2.8 mol/L, in addition to another maximum at 1.2 mol/L. The same trend was observed at pH 11 to a much weaker extent. Thus, the pH value was most crucial for protein recovery, because maximum yields at pH 11 were not attained with any combination of pH and cNaCl at lower pH values. However, interactions between cNaCl and pH considerably modulated protein recovery within the range of pH 5.6–7.4. Supportive NaCl concentrations were significantly higher than those found in earlier studies, where protein extractability was investigated up to a cNaCl level of 2 mol/L, with protein yields declining above 1.0 mol/L at pH >6 (Gheyasuddin et al., 1970). Another study similarly revealed maximum solubility (92–88%) at 1–1.5 mol/L. However, since extractions were only reported for 1.0, 2.0, and 3.0–6.0 mol/L, intermediate concentrations might result in better solubility (Bau, Mohtadi-Nia, Mejean, & Debry, 1983). At alkaline pH >8, linseed protein extraction was diminished by addition of NaCl (Dev et al., 1986). But within the mild-acidic to slightly alkaline range (pH 5–8), protein extractability rose again when cNaCl was ramped to 1.0 mol/L, without application of higher NaCl doses. The same trend was observed for sesame seed protein (Rivas, Dench, & Caygill, 1981). The different findings obtained in the present study might be attributed to different methods and materials (sunflower variety, pretreatment) and the limited cNaCl range explored in some of the previous studies.
3.2. Attainable protein recovery at pH 3.2–7.4 under optimised process parameters Key role and limits of NaCl addition for partial compensation of pH conditions impairing protein extraction were well documented by Fig. 1, as discussed above. At the same time, a shift of the extract colour from faint yellow to dark green with rising pH values of the solutions was observed, revealing a greenish colour already at pH 7 and clear green at pH 8. This observation is in accordance with the report of Cater, Gheyasuddin, and Mattil (1972), whereby coextraction of chlorogenic acid resulted in green protein isolates upon further processing due to irreversible polyphenol binding. As stated by Mieth, Roloff, Kozlowska, and Rotkiewicz (1982), chlorogenic acid is readily oxidised at pH >8, but quite stable against oxidation at pH <8. Therefore, extraction below pH 8 is indispensable for the stabilisation of phenolic acids, avoiding their oxidation and covalent binding to proteins. According to our observations, pH <7, or even pH <6, is required to obtain lightcoloured sunflower protein. Consequently, the pH range of 3.2–7.4 was explored in more details for further optimisation of acidic protein extraction in terms of yield and purity (colour). The use of elevated cNaCl would not only enhance the protein yield, as shown above, but may also be conducive to a light-colour of the extracts (Mieth & Roloff, 1985). Apart from NaCl, further modulation of protein extraction at suboptimal pH levels was expected from temperature and MSR. Hence, all four decisive factors were included in the D-optimal design of series 2. Significant differences among results of individual runs of series 2 were indicated in Table 1. Among the 38 process variants, the protein concentrations cPE of the extracts ranged from 3.5 to 27.5 g/L, corresponding to an almost 8-fold increase. The relative deviation between cPE levels of duplicate runs was always <3%.
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C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
As revealed by comparative application of the Biuret and the Dumas method to extracts obtained at pH 2.0–7.4 and cNaCl 2 mol/L in series 1 (data not shown), both methods showed good correlation (R2 ¼ 0.92), although relative deviation for individual data pairs was up to 10–20%. Thus, protein recovery under identical extraction conditions in series 1 and 2 was not directly comparable when different DSM and protein quantification methods were used. With RPY rising 4.5-fold from 22.4–101.0% in series 2 (Table 1), the protein yield (Eq. (1)) at pH 3.2–7.4 was generally higher than in series 1 (Fig. 1). Slight overestimation of maximum RPY in series 2 might be attributed to different protein quantification methods applied to meal (Dumas combustion method) and extracts (Biuret method), including errors resulting from the conversion of N to protein and co-solutes interfering with the Biuret assay, such as co-extracted phenolics. The effects of the four extraction parameters and their interactions on cPE and RPY were described by the respective regression models in Tables 2 and 3, based on Eq. (2). The importance of each factor was evaluated using the equations calculated from the encoded factors, as discussed below. Since each of them ranged from 1 to þ1, the effects of all parameters were directly comparable, irrespective of individual units. 3.3. Extraction parameters influencing protein concentration and relative yield (RPY) at pH 3.2–7.4 All four parameters studied significantly influenced the protein concentrations of the extracts (cPE, Table 2) and the relative protein yield (RPY, Table 3) at pH 3.2–7.4 in the form of linear effects or in more complex ways. With coefficients of determination (R2) of 0.96 and 0.93, respectively, the overall correlation of cPE and RPY values predicted by the models with the measured values was high, despite some deviations of individual data sets (Figs. 2A/B). The prevailing influence of the pH value (factor C) became evident by the linear terms for C, where the coefficients reached by far the highest levels (bC ¼ 6.6 and 0.292, respectively) among all terms of the models, except for b0 (Tables 2A and 3A). Beside its linear effect as a single factor, interactions of the pH value with MSR and particularly cNaCl played significant roles, described by respective two-factor terms. In addition to this interaction, the key role of cNaCl in modulating pH-dependent protein extraction was expressed by the squared terms for D (bDD ¼ 2.687 for cPE and 0.127 for RPY), modifying the great direct impact of cNaCl described by significant linear terms.
Table 2 Protein concentration of the extracts (cPE) resulting from extractions at various sets of extraction parameters A–D, i.e. meal-solvent ratio A ¼ MSR (0.03–0.05 g/mL), temperature B ¼ T (15–45 C), pH value C (pH 3.2–7.4), and NaCl concentration of the solvent D ¼ cNaCl (0.01–2.98 mol/L): regression model for cPE (in g/L) (A.) computed with encoded factor settingsa and (B.) reconverted to effective factor levels. A. cPE
B. cPE
F-valueb
p
¼13.943 þ3.516 xA þ1.105 xB þ6.618 xC þ1.202 xD 2.687 x2D þ2.674 xA xC þ1.387 xC xD
¼7.549 323.193 xMSR þ0.0736 xT 2.606 xpH þ2.095 xcNaCl 1.218 xc2NaCl þ127.318 xMSR xpH þ0.445 xpH xcNaCl
93.60* 8.92* 287.12* 10.20* 10.27* 49.37* 7.49*
<0.0001 0.0056 <0.0001 0.0033 0.0032 <0.0001 0.0103
97.98*
<0.0001
Model: R2 ¼ 0.96 a
Factors xi encoded from 1 (low level) to þ1 (high level); xA ¼ (xMSR 0.04)/ 0.01; xB ¼ (xT 30)/15; xC ¼ (xpH 5.3)/2.1; xD ¼ (xcNaCl 1.495)/1.485. b F-values marked by an asterisk (*) and respective terms were significant (p < 0.05); p, transgression probability.
Table 3 Relative protein yield (RPY) resulting from extractions at various sets of extraction parameters A–D, i.e. meal-solvent ratio A ¼ MSR (0.03–0.05 g/mL), temperature B ¼ T (15–45 C), pH value C (pH 3.2–7.4), and NaCl concentration of the solvent D ¼ cNaCl (0.01–2.98 mol/L): regression model for RPY (in g/g) (A.) computed with encoded factor settingsa and (B.) reconverted to effective factor levels. A. RPY
B. RPY
F-valueb
p
¼0.634 þ0.019 xAc þ0.047 xB þ0.292 xC þ0.064 xD 0.127 x2D þ0.048 xA xC þ0.086 xC xD
¼0.239 10.265 xMSRc þ0.003 xT þ0.006 xpH þ0.069 xcNaCl 0.057 xc2NaCl þ2.298 xMSR xpH þ0.028 xpH xcNaCl
1.35 7.82* 271.60* 13.82* 11.09* 7.81* 13.93*
0.2548 0.0089 <0.0001 0.0008 0.0023 0.0090 0.0008
60.42*
<0.0001
Model: R2 ¼ 0.93 a
Factors xi encoded from 1 (low level) to þ1 (high level); xA ¼ (xMSR 0.04)/ 0.01; xB ¼ (xT 30)/15; xC ¼ (xpH5.3)/2.1; xD ¼ (xcNaCl 1.495)/1.485. b F-values marked by an asterisk (*) and respective terms were significant (p < 0.05); p, transgression probability. c Hierarchical term (insignificant) retained during backward elimination regression.
The main effects on RPY at pH 3.2–7.4 are illustrated by Figs. 3A/B, confirming the suitable pH and cNaCl ranges of series 1 for RPY maximisation under mild-acidic conditions. As cPE and RPY were intimately related to each other (Eq. (1)), the major effects on both responses were similar, apart from the impacts of MSR (Tables 2 and 3). For the design of efficient extraction processes, RPY is crucial. Unlike cPE, this relative variable is independent of dilution effects. Thus, results of different parameter settings and scales can easily be compared on this basis. However, the protein concentrations of the extracts (cPE) are of interest as regards further processing of the latter, e.g. protein precipitation, and were therefore specifically included in this study as a response variable (Table 2). Under the technical conditions applied, the DSM was well dispersed at both MSR levels used. Providing higher amounts of the protein source by raising MSR from 0.03 to 0.05 g/mL thus facilitated diffusion during the preset extraction time by an overall higher concentration gradient and enhanced cPE. In this way, MSR exerted a highly significant influence on the latter. However, in case of RPY, the importance of MSR was limited to the mentioned interaction with the pH value. Owing to this significant involvement, the linear MSR term was included because of model hierarchy, despite its missing significance (Table 3). The overall weak influence of MSR became evident when the response surfaces computed for each of both levels studied were compared (Figs. 3A,B). RPY faintly increased, when MSR rose from 0.03 to 0.05 g/ mL, consistent with a report on the extraction of cowpea proteins (Sefa-Dedeh & Stanley, 1979), ascribing the enhancing effect of MSR to less dilution of the intrinsic meal ash and hence higher ion concentrations in the extract solutions. Complexation and interaction of proteins with co-extracted polysaccharides as well as rising viscosity affecting separation of the proteins during centrifugation of the extracts may be further reasons (Oomah, Mazza, & Cui, 1994). Contrasting results were obtained for defatted linseed flour (Dev et al., 1986), whereas MSR insignificantly affected protein extractability from sunflower flour in a study of Gheyasuddin et al. (1970). A minor linear effect on cPE and RPY was attributed to temperature (Tables 2A and 3A). With increasing T up to the maximum of 45 C, protein concentrations and the resulting yields steadily increased, consistent with a study on the extraction of cowpea proteins (Sefa-Dedeh & Stanley, 1979). The low temperature influence is corroborated by Gheyasuddin et al. (1970), reporting an insignificant effect of temperature on protein extraction in the
C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
1971
experiments shown in Table 4, the weak temperature effect on the protein yield was irrelevant in practice (no. 1 vs. no. 3). Mutually compensating effects occurring at small differences of pH and cNaCl led to equal cPE and RPY (no. 1 vs. no. 2). Accuracy of the models was limited by the given preciseness of both the analytical methods and the parameter settings, beside unidentified minor effects. The Biuret determination might be affected by complexation of the copper reagent through coextracted phytic acid (Saeed & Cheryan, 1988) and by interfering carbohydrates. Nevertheless, the two models of Tables 2 and 3 were suitable to visualise the principal impact of the extraction parameters on protein recovery. Parameter screening (series 1) and process optimisation (series 2) were consistent in terms of observed extraction yields. In view of the relatively low impact of small parameter changes and the accuracy of prediction,
Fig. 2. Quality of the prediction of (A) the experimental protein concentrations of the extracts (cPE in g/L) by the model in Table 2 (R2 ¼ 0.96) and (B) the experimental protein yields (RPY in g/g) by the model in Table 3 (R2 ¼ 0.93) after protein extraction from defatted sunflower meal (DSM 2) at pH 3.2–7.4.
range of 26–60 C, although a slight maximum was observed at 45 C. 3.4. Validation of the models To verify the models presented in Tables 2 and 3, further protein extractions were performed by analogy to those of experimental series 2. However, parameter settings other than the previous design points were used (Table 4). To allow direct comparison of individual pairs, three intermediate levels were chosen for cNaCl and pH, while T was varied at two levels, i.e. room temperature and elevated temperature. For MSR, only the upper level was selected because of its higher practical relevance. The experimental results were compared to the predicted values. The protein yields topped predicted RPY levels by 14–30%, but ranged within the 95% prediction intervals or at least within those of 99% probability (extraction no. 3). Similarly, the cPE readings exceeded the predicted values, but were always close to the upper limits of the 95% prediction intervals. According to the individual pairs of
Fig. 3. Protein yields (RPY in g/g) achievable by extraction from defatted sunflower meal (DSM 2) at pH 3.2–7.4: response surface computed for RPY by Design-Expert according to Table 3 as a function of pH and NaCl concentration (cNaCl) at 30 C and a MSR of (A) 0.03 g/mL and (B) 0.05 g/mL. Base isolines indicate equal RPY levels.
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C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
Table 4 Protein concentration of the extracts (cPE in g/L) and relative protein yield (RPY in g/g) of extractions at MSR ¼ 0.05 g/mL performed for verification of the models in Tables 2 and 3. No.
pH
T ( C)
cNaCl (mol/L)
1
5.6
45
1.4
2
5.7
45
1.2
3
5.6
20
1.4
4
6.4
20
0.4
Response Parameter
Detected
Predicted
PI (95%)
PI (99%)
cPE RPY cPE RPY cPE RPY cPE RPY
23.3 0.86 24.0 0.89 22.9 0.87 19.3 0.74
19.79 0.74 19.94 0.74 17.95 0.67 18.71 0.65
15.87–23.71 0.57–0.92 16.02–23.85 0.57–0.92 14.05–21.85 0.49–0.84 14.73–22.69 0.47–0.83
14.51–25.07 0.50–0.98 14.66–25.21 0.50–0.98 12.70–23.20 0.43–0.90 13.35–24.07 0.41–0.89
PI, prediction interval at a probability level of 95 and 99%, respectively.
problem-oriented optimum operating ranges rather than an optimal working point may be deduced from the presented models. The studies were performed on the small laboratory scale, which allowed a multitude of experiments to explore a broad range of parameter settings. For practical reasons, single batch extraction with magnetic stirring was used. To achieve highly reproducible results despite small sample amounts, complete dispersion of the meal in the solvent was ensured by solvent excess, limiting MSR to comparatively low levels. Protein diffusion from the surface of the meal particles into the solvent was overall supported by the small particle sizes of the meal and the use of low MSR levels in combination with a long extraction time. By contrast, economic extraction on industrial scales would require higher MSR together with more vigorous stirring to accelerate extraction through maximum protein concentration gradients between meal and solvent and to improve efficiency of recovery through high protein concentrations of the extracts. Moreover, a counter-current process instead of the single batch extraction would enhance solvent efficiency in industrial practice. On the other hand, protein diffusion might be limited by minimised total extraction times and the use of flakes rather than meal. As indicated by the overall low impact of MSR on RPY (Fig. 3) despite great differences in protein concentrations of the extracts (Table 1), dispersion of the meal in the solvent and protein diffusion into the solvent were indeed not technically limiting factors in this study. Provided that both conditions are given, the RPY model (Table 3) is considered to be a valuable tool for the efficient optimisation of pH, cNaCl and T ranges in upscaling of sunflower protein extraction to industrial scales despite necessary technical adjustments.
3.5. Optimised mild-acidic protein extraction Whereas high pH values and optimum cNaCl of w2–2.8 mol/L were required for maximum protein extraction, a pH far below the alkaline range was the prerequisite for colourless protein extracts. To identify suitable operating ranges, the optimum conditions within the studied range were computed by numerical optimisation for maximum protein yield (RPY) at the lowest pH possible. Based on a medium priority of low pH, the calculated optimum was pH 6.0, where a maximum RPY of 84% would be achieved if cNaCl was set to 2.0 mol/L at maximum temperature (45 C) and MSR (0.05 g/mL) (Table 5A). Overall desirability for those parameter settings was only 61%, reflecting the compromise regarding the processing conditions. In addition to pH, the other factors may also be subjected to any constraints in practice. Although high cNaCl was shown to improve protein extractability, handling of the extracts, especially desalting, would be easier at lower salt concentrations. Extraction at low temperature would be favourable not only in terms of energy costs, but would also slow down oxidation of co-extracted phenolic acids, which are relatively stable at 20 C (Mieth et al., 1982). Furthermore, high protein concentrations may facilitate protein recovery by membrane filtration or precipitation. Considering these aspects, protein extraction at pH 6.1 at a salt concentration of 1.6 mol/L and 21 C is suggested (Table 5B). However, due to the described converse effects, i.e. unfeasible conformance to all requirements, maximum overall desirability was only 57% for those settings. Moreover, protein recovery would be reduced to 76% under these constraints.
Table 5 Proposed variants (no. 1–4) of extraction parameter settings for the production of light-coloured proteins from sunflower meal with predicted protein concentration of the extracts (cPE) and relative protein yields (RPY), as computed from the models in Tables 2 and 3 by numerical optimisation with Design-Expert according to the preset priority ranking of the response factors and parameter ranges. MSR (g/mL)
T ( C)
pH
A. Simple optimisation of extraction regarding maximum protein yield at low pH: Presettings 0.03–0.05 15–45 Minimise – – 2 Priority rankb Solution no 1 0.05 45 6.0 Solution no 2 0.05 45 6.0 Solution no 3 0.05 45 6.0 Solution no 4 0.05 45 5.9 B. Complex optimisation Presettings Priority rankb Solution no 1 Solution no 2 Solution no 3 Solution no 4 a b
cNaCl (mol/L)
cPE (g/L)
RPY (g/g)
Desirabilitya
0.01–2.98 – 2.0 2.0 2.0 2.0
3.5–27.5 – 21.9 22.0 22.1 21.6
Maximise 5 0.83 0.83 0.84 0.82
0–1 0.610 0.610 0.610 0.610
of extraction regarding maximum protein concentration of the extracts and maximum protein yield at low pH and under economic constraints: 0.03–0.05 Minimise Minimise Minimise Maximise Maximise 0–1 – 1 3 1 3 5 0.05 21 6.1 1.6 20.4 0.76 0.566 0.05 21 6.1 1.6 20.4 0.76 0.566 0.05 22 6.1 1.6 20.4 0.76 0.566 0.05 20 6.1 1.5 20.2 0.75 0.566
Overall desirability, with an ideal maximum level of 1 describing concurrent complete maximisation of each response factor. Ranks from 1 (lowest priority) to 5 (highest priority).
C. Pickardt et al. / Food Hydrocolloids 23 (2009) 1966–1973
Depending on the selected priorities, the extraction process may considerably differ from the examples proposed in Table 5. Through priority selection, further aspects, such as processing costs, in particular for subsequent desalting at high salt concentrations, may be included. 4. Conclusions Mild-acidic protein extraction (pH w6) at high salt concentrations (1.6–2.1 mol/L of solvent) was found to be suitable for the recovery of light-coloured proteins from sunflower seeds. The use of NaCl at such elevated concentrations suppressed protein-polyphenol interactions (Mieth & Roloff, 1985) and enhanced protein extractability to exploitable levels. The presence of NaCl compensated for pH conditions that were apparently suboptimal for protein extraction in terms of the yield, while green discoloration of the extracts was prevented. To obtain colourless protein isolates, removal of co-extracted phenolic acids is a prerequisite. As an alternative to the separation of phenolics by membrane filtration, the proposed procedure would also allow their removal by adsorption, which is facilitated by the low extract pH (Schieber, Hilt, Streker, Endreß, Rentschler, & Carle, 2003). Investigations to combine both processes are currently under way. Acknowledgement This research project was supported by the German Ministry of Economics and Technology (via AIF) and the FEI (Forschungskreis der Erna¨hrungsindustrie e.V., Bonn). Project AiF 14449 N. References AACC (1983). Method 46–15: Crude protein – 5-minute Biuret method for wheat and other grains. In Approved methods of the American Association of Cereal Chemists (8th edition). St. Paul, MN, USA: American Association of Cereal Chemists. AOAC (1990a). Method 968.06. Protein (crude) in animal feed. In Official methods of analysis of the Association of Official Analytical Chemists (15th edition). Washington, DC: Association of Official Analytical Chemists. AOAC (1990b). Method 923.03. Ash of flour. In Official methods of analysis of the Association of Official Analytical Chemists (15th edition). Washington, DC: Association of Official Analytical Chemists. Arntfield, S. D. (2004). Proteins from oil-producing plants. In R. Y. Yada (Ed.), Proteins in food processing (pp. 146–175). Boca Raton, Boston, New York, Washington, DC: CRC Press. Bau, H. M., Mohtadi-Nia, D. J., Mejean, L., & Debry, G. (1983). Preparation of colorless sunflower protein products: effect of processing on physicochemical and nutritional properties. Journal of the American Oil Chemists’ Society, 60, 1141–1148. Cater, C. M., Gheyasuddin, S., & Mattil, K. F. (1972). The effect of chlorogenic, quinic and caffeic acids on the solubility and color of protein isolates, especially from sunflower seed. Cereal Chemistry, 49, 508–514. Dev, D. K., Quensel, E., & Hansen, R. (1986). Nitrogen extractability and buffer capacity of defatted linseed (Linum usitatissimum L.) flour. Journal of the Science of Food and Agriculture, 37, 199–205. DGF (2004). Method of Caviezel, DGF K-I 2c (00). In Deutsche Gesellschaft fu¨r Fettwissenschaft e.V., Mu¨nster. DGF-Einheitsmethoden (2nd edition). Stuttgart: WVG. Dorrell, D. G., & Vick, B. A. (1997). Properties and processing of oilseed sunflower. In A. A. Schneiter (Ed.), Sunflower technology and production (pp. 709–744). Madison, Wisconsin: American Society of Agronomy.
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