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Processing optimization and functional properties of gelatin from shark (Isurus oxyrinchus) cartilage
Food Hydrocolloids 18 (2004) 573–579 www.elsevier.com/locate/foodhyd
Processing optimization and functional properties of gelatin from shark (Isurus oxyrinchus) cartilage S.M. Choa, K.S. Kwaka, D.C. Parkb, Y.S. Gua, C.I. Jia, D.H. Jangc, Y.B. Leea, S.B. Kima,* a
Department of Food Science and Technology, Institute of Seafood Science, Pukyong National University, Busan 608-737, South Korea b Korea Food Research Institute, Sungnam 463-746, South Korea c Division of Mathematical Sciences, Pukyong National University, Busan 608-737, South Korea Received 20 March 2003; accepted 3 October 2003
Abstract Gelatin processing from shark (Isurus oxyrinchus) cartilage was optimized by response surface methodology: the dependent variable was gelatin yield and independent variables were sodium hydroxide concentration and treatment time for the alkali treatment, and extraction temperature and time for the hot-water extraction. Predicted maximum yields of 79.9% for gelatin processing were obtained under the conditions of alkali treatment with 1.6N sodium hydroxide for 3.16 days and hot-water extraction at 65 8C for 3.4 h. Amino acid composition and functional properties of shark cartilage gelatin were examined in comparison to two porcine skin gelatins. Shark cartilage gelatin had lower concentration of hydroxyproline than the two porcine skin gelatins. Shark cartilage gelatin showed worse turbidity than the two porcine skin gelatins. Foam formation ability, foam stability, water-holding capacity and gel strength of shark cartilage gelatin were lower than the two porcine gelatins, but fat-binding capacity was higher in the shark cartilage gelatin. q 2003 Elsevier Ltd. All rights reserved. Keywords: Gelatin; Shark cartilage; Functional properties; Gel strength; Response surface methodology
1. Introduction Gelatin is a denatured protein derived from collagen by thermo-hydrolysis and has a rheological property of thermoreversible transformation between sol and gel. Gelatin is one of the most important biopolymers, with widespread applications in the food, pharmaceutical, cosmetic and photographic industries. Recently, its use is expanding to new applications such as functional foods. Gelatin is commercially made from skins and skeletons of bovine and porcine and mammalian gelatin has been intensively studied (Ward & Courts, 1977; Gilsenan & Ross-Murphy, 2000). However, mammalian gelatin is at risk for contamination with bovine spongiform encephalopathy, so fish skins, as by-products from fish processing, have been studied as a replacement for mammalian sources (Gudmundsson, 2002). Therefore, research on fish gelatin is very important for the development of methods for the efficient utilization of by-products from fish processing * Corresponding author. Tel.: þ 82-51-620-6418; fax: þ82-51-622-9248. E-mail address: [email protected] (S.B. Kim). 0268-005X/$ - see front matter q 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodhyd.2003.10.001
as replacements for mammalian sources (Montero & Go´mez-Guille´n, 2000). Gelatin quality is typically evaluated on the basis of several functional properties. Gel strength is the most important property of gelatin for industrial applications. Moreover, the quality of commercial gelatin is also determined by other properties, such as viscosity, melting point, gelling point, turbidity, solubility, etc. These properties are affected by many factors, such as amino acid composition, and the ratio of a-chain and content of bcomponent (Go´mez-Guille´n et al., 2002). Generally speaking, the functional properties of fish gelatin are inferior to mammalian gelatin. Furthermore, fish gelatin has a dark color and fishy odor. As a result, fish gelatin is seldom used commercially and not mass-produced. Little research has been devoted to the processing and functional properties of fish gelatin (Choi & Regenstein, 2000). The limited research on fish gelatin has evaluated gelatin derived from lumpfish (Osborne, Voight, & Hall, 1990), tilapia (Grossman & Bergman, 1992; Jamilah & Harvinder, 2002), conger and squid (Kim & Cho, 1996), cod (Gudmundsson & Hafsteinsson, 1997), shark (Yoshimura et al., 2000) and megrim
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(Montero & Go´mez-Guille´n, 2000). These studies were limited to only fish skins of a few marine species. The objectives of this study were to make gelatin from shark cartilage instead of fish skin, to determine the optimum conditions for gelatin processing using response surface methodology with a central composite design, and to compare the gelatin with two commercial porcine skin gelatins. Therefore, this study had two primary outcomes: first was an investigation of new materials for replacing traditional sources of gelatin, and the second was the optimization of gelatin production using response surface methodology.
2. Materials and methods Frozen shark (Isurus oxyrinchus) cartilage, which was analyzed as the proximate composition of 78.3% moisture, 19.2% protein, 1.4% lipid and 1.1% ash was provided by Songho Food Development Co., Ltd (Busan, Korea). Two commercially produced porcine skin gelatins were used; one food grade (GF, 280 Bloom) was obtained from Baek Kyeung Food Co, Ltd (Kimhae, Korea) and one analytical grade (GA, 300 Bloom) was purchased from Osaka Pharmaceutical and Chemical Industry (Osaka, Japan). All reagents used were analytical grade. 2.1. Gelatin processing Shark cartilage was washed to remove contaminants, chopped and frozen at 2 15 8C until used. Cleaned shark cartilage was soaked in 8 volumes of (v/w) of sodium hydroxide solution (1 –2N) at 8 8C in a 200 rpm shaking incubator (HB-201SF, Hanbaek Scientific Co., Korea) for 2 – 4 days, to remove the non-collagen protein and subcutaneous tissue after they were swollen (SKW Biosystems, 2001, 2002). The alkali treated shark cartilage was washed, neutralized with 2N HCl and rewashed. For hot-water extraction, 7 volumes of (v/w) of distilled water were added. Gelatin was extracted at the pre-determined temperatures (40 – 80 8C) and times (1 – 5 h) in a water bath (SB-651, EYELA, Japan). The extracted solutions (pH 8) was centrifuged (SUPRA 30K, Hanil Science Industrial Co., Korea) for 30 min at 900g at 30 8C. The upper phase was vacuum-filtered with a filter paper (5A 110 mm, Advantec, Japan), and the filtered solution vacuum-concentrated to 10 brix at 60 8C and dried at 1.4 m/s for 24 h in a hot-air dryer (WFO-601SA, EYELA, Japan). 2.2. Quantitative analysis of gelatin Gelatin content was estimated from hydroxyproline content by the method of Sato, Ohashi, Ohtsuki, and Kawabata (1991), using a conversion factor of 11.42. Hydroxyproline content was determined by the method
described in ISO (1978), with slight modifications. 100 mg of dried gelatin and 5 ml of 6N HCl were added to test tubes. Gelatin in test tubes was hydrolyzed in a dry bath (Dry bath incubator 11-718-2, Fisher Scientific Co., USA) for 12 h. Following hydrolysis, the sample solutions were neutralized with 6N NaOH, 2 ml of acetate/citrate buffer was added and the samples brought to a total volume of 25 ml with 0.3 M NaCl. Next, 300 ml of the sample solutions, 300 ml of isopropanol and 600 ml of oxidant solution were pipetted into test tubes. After 4 min, 4 ml Ehrlich’s reagent solution was added to each tube, the sample solutions were mixed, and the tubes were heated for 25 min in a 60 8C water bath. Absorbance of the solutions was measured with a spectrophotometer (UV-140-02, Shimadzu, Japan) at 660 nm. The hydroxyproline contents of the sample solutions were calculated from a calibration curve derived from standards using analytical grade hydroxyproline. 2.3. Analysis of amino acids A 5 mg aliquot from each dried gelatin sample was dissolved in 3 ml of 6N HCl, dried, and hydrolyzed in vacuum-sealed glass tubes at 110 8C for 24 h using a dry bath (Dry bath incubator 11-718-2, Fisher Scientific Co., USA). After hydrolysis, samples were vacuum-dried, dissolved in citric acid buffer (pH 2.2, Sigma Chemical Co.) and injected into an amino acid auto analyzer (Amino acid analyzer S-433H, Sycam, Germany). 2.4. Functional properties Gel strength was measured by rheometer (Compac-100, Sun Scientific Co. Ltd, Japan). A 6.67% (w/v) gelatin solution was gel-formed for 12 h at 5 8C, and the gel strength was measured by plunging into the middle of gel at the rate of 2 cm/min with a 50 mm diameter disc. The value of gel strength is represented as kPa. Turbidity of gelatins was determined by measuring absorbance of 0.1% gelatin solutions at 660 nm using a spectrophotometer (UV-140-02, Shimadzu, Japan). Turbidity was calculated from a calibration curve using a standard solution of Kaolin, and expressed in parts per million (ppm). Foam formation capacity and foam stability were measured by a partially modified method of Sathe, Deshpande, and Salunkhe (1982). A 1 g sample was placed in 50 ml distilled water and swollen. The sample solution was dissolved at 60 8C and the foam was prepared by homogenizing at 10,000 rpm for 5 min (Ace homogenize, AM-8, Japan). The homogenized solution was poured into a 250 ml mess flask. The foam formation ability was calculated as the volume ratio of foam liquid. The foam stability was calculated as the ratio of the initial volume of foam to the volume of foam after 30 min.
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Table 1 Experimental range and values of the independent process variables in the design for production of shark (I. oxyrinchus) cartilage gelatin
Table 2 Responses of dependent variables for production of shark (I. oxyrinchus) cartilage gelatin to independent variables
Process
Exp. No.
Independent variables
Symbol
Range and levels 21
Alkali treatment Hot-water extraction
0 1.5
þ1
Concentration of sodium hydroxide (N) Treatment time (days) Extraction temperature (8C)
X1
1
2
X2 X3
2 40
3 60
4 80
Extraction time (h)
X4
1
3
5
Water-holding and fat-binding capacities were measured by a partially modified method of Lin, Humbert, and Sosulki (1974). One gram of gelatin was placed in a centrifuge tube and weighed (tube with gelatin). For measuring water-holding capacity and fat-binding capacity, 50 ml distilled water or 10 ml corn oil were added, respectively, and held at room temperature for 1 h. The gelatin solutions were mixed with vortex mixer for 5 s every 15 min. The gelatin solutions were then centrifuged at 450g for 20 min. The upper phase was removed and the centrifuge tube was drained for 30 min on a filter paper after tilting to a 458 angle. Their capacities were calculated as the weight of the contents of the tube after draining divided by the weight of the dried gelatin, and expressed as the wt% of dried gelatin. 2.5. Response surface methodology The optimum conditions for processing gelatin from shark cartilage were determined by response surface methodology. Based on the results of preliminary studies, the two most important independent variables were (1) the concentration of sodium hydroxide and treatment time for alkali treatment and (2) the extraction temperature and time for hot-water extraction. The experimental design is shown in Table 1. The independent variables were coded to three levels of 2 1, 0, þ 1. The dependent variable was the amount the gelatin (%, dry basis) and was measured three times repeatedly. The optimum conditions for gelatin processing were obtained by using response surface methodology of the coded independent variables, using design of Table 2. All the experimental data were statistically analyzed by SAS software (Version 8.01, SAS Institute Inc., USA). 2.6. Statistical analysis The experimental data of gel strength turbidity, foam formation capacity, foam stability, water-holding and fatbinding capacities were measured three times repeatedly. Significant differences were performed using values that repeated three times. One-way variance analysis was
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
Variable levels
Responses, Y
X1
X2
X3
X4
21 21 21 21 21 21 21 21 21 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16
21 21 21 0 0 0 1 1 1 21 21 21 0 0 0 1 1 1 21 21 21 0 0 0 1 1 1 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 21 21 21 21 21 21 21 21 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 21 21 0 0 0 1 1 1 21 21 21 0 0 0 1 1 1 21 21 21 0 0 0 1 1 1
43.3 43.8 43.9 55.5 55.9 55.3 52.9 51.2 51.5 55.0 55.8 55.8 80.7 81.8 79.5 68.2 68.9 67.5 52.8 52.6 51.3 70.1 71.5 69.1 58.3 58.3 58.9 42.2 42.9 42.9 56.0 56.0 56.0 54.4 54.1 54.2 56.9 57.7 58.7 82.5 82.5 81.3 69.2 69.7 69.5 52.3 52.8 53.6 72.2 72.9 72.6 65.1 65.1 65.2
carried out and differences separated by the Tukey test (Tukey, 1953) using SAS software (Version 8.01, SAS Institute Inc., USA), differences were considered significant at p # 0:05:
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3. Results and discussion 3.1. Optimization of gelatin processing by response surface methodology
Table 4 Response surface model for production conditions of shark (I. oxyrinchus) cartilage gelatin Response
Quadratic polynomial model
R2
Significance
Recently, response surface methodology has been used to evaluate the effectiveness of food manufacturing processes. Response surface methodology is a collection of mathematical and statistical techniques widely used to determine the effects of multiple variables and to optimize different biotechnological process. Response surface methodology is a mathematical modeling technique that relates product treatment to outcomes and establishes regression equations that describe inter-relations between input parameters and ¨ zdemir & product properties (Rao, Kim, & Rhee, 2000; O Devres, 2000). Gelatin processing has two important steps: alkali treatment and hot-water extraction. The alkali treatment removes non-collagen protein after swelling the sample in the alkali solution, the hot-water extraction uses thermohydrolysis to solubilize and separate the gelatin. The alkali treatment using 8 times (v/w) the volume of sodium hydroxide solution as shark cartilage resulted in consistent yields of gelatin; therefore, the amount of hydroxide solution was fixed to 8 volumes. The concentrations of sodium hydroxide solution and treatment times were varied and were important independent variables. In the hot-water extraction, using 7 times (v/w) the distilled water as alkalitreated collagen resulted in consistent yields of gelatin, so the amount of distilled water was fixed to 7 volumes. The extraction temperature and time were varied and were also important independent variables. Independent variables were the concentration of sodium hydroxide solution, alkali treatment time, hot-water extraction temperature, and extraction time. As the result of procedure RSREG of SAS, linear term ðX1 ; X2 ; X3 ; X4 Þ and pure quadratic term ðX12 ; X22 ; X32 ; X42 Þ were significant (Table 3), but mixed quadratic term was not ðp ¼ 0:79Þ: Therefore, the response surface model was calculated by using the REG procedure (Table 4). This model equation was the best because the equation had the lowest AIC (Akaike Information Criteria, Akaike, 1973). When consider standard error of each parameter on the model equation, contributions of all factors, X1 (concentration of sodium hydroxide) and X2 (treatment time) on
Gelatin contents (%, dry basis)
Y ¼ 77:574 þ 4:989X1 þ4:533X2 þ 6:233X3 þ5:917X4 2 12:923X12 213:957X22 2 12:338X32 213:155X42
0.9571
0.001
Table 3 Analysis of variance for the regression model representing yield of gelatin ðYÞ
The amino acid compositions of GS (shark cartilage gelatin), GA (analytical grade gelatin) and GF (food additives grade gelatin) are shown in Table 5. The amino acid composition of GA and GF was similar, while that of shark cartilage gelatin was different from the porcine gelatins. Ledward (1986) reported that gelatin has a repeated structure of Gly-X-Y. When proline (Pro) and hydroxyproline (Hyp) were located in the X and Y positions, the gelatin structure was stable. While the imino acid content (Hyp þ Pro) of GA and GF of porcine gelatins
Sources
DF
SS
MS
F-value
P
Linear Quadratic Error Total
4 4 45 53
2188.066 4123.559 286.115 6597.740
547.017 1030.889 6.358
86.036 162.141
0.001 0.001
SS, sum of squares; DF, degrees of freedom; MS, mean square.
alkali treatment and X3 (extraction temperature) and X4 (extraction time) on hot-water extraction, were resemblant almost. If any factors recede from optimal conditions close to code 0, yield of gelatin from shark cartilage has a tendency to decrease greatly because parameters of pure quadratic term are negative. Optimal conditions were determined by setting the partial derivatives of the model equation to zero. The stationary point is a maximum. Critical values of factors were concentration of sodium hydroxide; X1 ¼ 0:19; treatment time; X2 ¼ 0:16; extraction temperature; X3 ¼ 0:25; extraction time; X4 ¼ 0:22; respectively. Actual values of factors against critical values were concentration of sodium hydroxide; 1.6N, treatment time; 3.16 days, extraction temperature; 65 8C, extraction time; 3.44 h. Predicted value at stationary point was 79.9%. Chemical composition of shark cartilage gelatin was 7.98% moisture, 90.9% crude protein, 0.54% crude ash and 0.21% crude lipid and that of GA was 8.52% moisture, 90.2% crude protein, 0.51 crude ash and 0.29% crude lipid. Gelatin consists of most protein and water. So, ash, lipid and other impurity contents are important for quality of gelatin. Usually ash contents up to 2.0% can be accepted in food applications. Crude ash content of GS was 0.54% and analogous almost to 0.51% of GA. Furthermore, crude lipid content of GS was lower than that of GA. GS is satisfied for a gelatin standard of JIS (Japanese Industrial Standard) K6503-1996 (moisture 8 –14%, crude protein . 85%, crude ash , 2%, crude lipid and other components , 1%) and similar to moisture (8.52%), crude protein (90.2%), crude ash (0.51%) and lipid or other impurities , 1%. Therefore, GS has a potential for food applications. 3.2. Composition of amino acids of shark cartilage gelatin
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Table 5 Amino acid composition of shark (I. oxyrinchus) cartilage gelatin as compared with two porcine skin gelatins Amino acids
Hydroxyproline Aspartic acid Threonine Serine Glutamic acid Proline Glycine Alanine Valine Methionine Isoleucine Leucine Tyrosine Phenylalanine Lysine Histidine Arginine Imino acids (Hyp þ Pro)
Gelatin type GA
GF
GS
10.79 5.11 1.75 3.46 8.26 11.36 32.89 11.52 2.13 0.90 1.21 2.39 0.09 1.02 2.86 0.38 3.83 22.15
10.91 4.56 2.03 4.03 7.10 11.01 32.03 11.58 2.40 0.95 1.92 2.63 0.21 1.19 2.32 0.49 4.39 21.92
7.70 4.36 2.41 4.21 8.01 11.97 32.12 11.84 2.35 1.85 2.44 0.12 1.13 1.01 2.27 0.54 4.43 19.57
GA, Gelatin of analytical grade from porcine skin; GF, gelatin of food additives grade from porcine skin; GS, felatin from shark (I. oxyrinchus) cartilage.
was similar at 22.15 and 21.92%, respectively, the amount of hydroxyproline in GS, 7.70%, was much lower than those of GA (10.79%) and GF (10.91%). The amount of proline in GS, 11.97%, was a little higher than in GA (11.36%) and GF (11.01%). Therefore, the mammalian gelatins, GA and GF, had nearly equal amounts of proline and hydroxyproline. It is believed that the structural stability of gelatin is largely dependent on the amount of hydroxyproline, which was lower in the shark cartilage gelatin, although proline content was high. Lysine also stabilizes gelatin structure by forming cross-linking structures between chains. The percentage of lysine in GS was 2.27, which was equal to the 2.32 of GF and less than the 2.86 of GA. Glycine was the most abundant amino acid in all gelatin samples, and normally makes up about one-third of the total. GS, GA and GF had 32.12, 32.89 and 32.03% glycine, respectively, exhibiting close similarity. Fish gelatin tends to have different ratios of amino acids from mammalian gelatin. Because of the different ratio of amino acids, fish gelatin has different functional properties from mammalian gelatin, which is consistent with the results of Arnesen and Gildberg (2002). 3.3. Functional properties of shark cartilage gelatin Gel strength is one of the most important functional properties of gelatin and fish gelatin typically has less gel strength than mammalian gelatin (Gilsenan & Ross-Murphy, 2000). Gel strength is a function of complex interactions determined by amino acid composition and the ratio of a-chain and the amount of b-component. Gel
Fig. 1. Turbidity and gel strength of shark (I. oxyrinchus) cartilage gelatin as compared with two porcine skin gelatins. Different letters (a, b, c, a0 , b0 , c0 ) indicate significant differences at p # 0:05: GA, gelatin of analytical grade from porcine skin; GF, gelatin of food additives grade from porcine skin; GS, gelatin from shark cartilage.
structure of gelatin is more stable when the imino acid (Hyp þ Pro) content is higher, and the amount of aggregates of higher molecular weight is less (Go´mez-Guille´n et al., 2002). Gel strengths of GS, GA and GF are shown in Fig. 1. For comparison with shark cartilage gelatin, Bloom strengths of two porcine skin gelatins GA and GF are 300 Bloom and 280 Bloom, respectively. Gel strengths of GA and GF were 149.9 and 137.8 kPa showing a similar trend to their Bloom strengths. Gel strength of GS was 111.9 kPa, which was less than the porcine gelatins at 149.9 and 137.8 kPa for GF. The lower gel strength in GS is probably due to its lower amount of imino acids (Hyp þ Pro), which stabilize gelatin structures, which was not offset by high lysine which could form crosslinks that would stabilize the gelatin. As shown in Table 5, the amount of imino acids (Hyp þ Pro) of GS, GA and GF were 22.35, 24.82 and 24.95%, respectively, with shark cartilage gelatin having the least. Formation of higher molecular weight aggregates by hot-air drying is also thought to affect gel strength of shark cartilage gelatin. As shown in Table 5, the amount of proline was highest in GS, but the amounts of total imino acids and hydroxyproline were lowest. Hydroxyproline is believed to be the major determinant of stability due to its hydrogen bonding ability through its hydroxyl group, although proline is also important (Burjandze, 1979; Ledward, 1986). This study appears to confirm the role of hydroxyproline as the major determinant for gel strength. Turbidities of GS and two porcine skin gelatins of GA and GF are shown in Fig. 1. The turbidity of GS was 12.04 ppm, which was much higher than that of GA at 0.61 ppm and two times higher than GF at 6.33 ppm. When protein is treated for a long time at high temperatures, aggregation is activated and turbidity increased (Johnson
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and Zabik, 1981). As the aggregates of higher molecular weight increase turbidity also increases (Montero, Ferna´ndez, & Go´mez-Guille´n, 2002). The high turbidity of GS may be due to the formation of more aggregates of higher molecular weight during the 24 h of hot-air drying, decreasing the gelatin’s solubility by exposing many hydrophobic residues; turbidity may have also been increased because no purification steps were applied. GA was thought to have very low turbidity because GA is highly purified for an analytical grade. Nevertheless, GS was two times higher than that of GF, the food grade gelatin, although it may also have been more purified for industrial use. Greater purification may improve the turbidity of shark cartilage gelatin. Foam formation ability is another important property of gelatin for commonly used foods such as marshmallows. Foam formation abilities of GS, GA and GF are shown in Fig. 2. Foam formation ability of GS was 2.6 (the ratio of foam volume/liquid volume), a little lower than the 2.8 of GA and 2.9 of GF. Foam stability of GS was 1.5 (the ratio of the volume after 30 min/initial volume of foam) was a little less than the 1.4 of GA and GF, demonstrating the lower stability of GS. Therefore, GS has the lowest foam formation ability and the lowest foam stability of the three gelatins. It has been suggested that reduced foam formation and stability may be due to aggregation of proteins which interfere with interactions between the protein and water needed for foam formation (Kinsella, 1977).
Fig. 2. Foam formation ability and foam stability of shark (I. oxyrinchus) cartilage gelatin as compared with two porcine skin gelatins. Different letters (a, b, c, a0 , b0 , c0 ) indicate significant differences at p # 0:05: GA, gelatin of analytical grade from porcine skin; GF, gelatin of food additives grade from porcine skin; GS, gelatin from shark cartilage. The ratio of foam formation ability means foam/liquid (v/v) and that of foam stability means foam after 30 min/initial foam (v/v).
Fig. 3. Water-holding capacity and fat-binding capacity of shark (I. oxyrinchus) cartilage gelatin as compared with two porcine skin gelatins. Different letters (a, b, c, a0 , b0 , c0 ) indicate significant differences at p # 0:05: GA, gelatin of analytical grade from porcine skin; GF, gelatin of food additives grade from porcine skin; GS, gelatin from shark cartilage.
Water-holding and fat-binding capacities are functional properties that are closely related to texture by the interaction between components such as water, oil and other components. Water-holding capacity and fat-binding capacity of the three gelatins are shown in Fig. 3, showing that they have similar values. While GS had the highest fat-binding capacity, it had the lowest water-holding capacity. Fatbinding capacity depends on the degree of exposure of the hydrophobic residues inside gelatin. In the case of GS, hydrophobic residues are believed to have been exposed during the hot-air drying process. As shown in Table 5, the hydrophobic amino acid, tyrosine, made up 1.17% of GS which was much higher that that of porcine skin gelatins at 0.10 and 0.24% for GA and GF, respectively. The high amount of tyrosine is probably responsible for the high fatbinding capacity of GS. Water-holding capacity is believed to be affected by the amount of hydrophilic amino acids. The amounts of hydroxyproline in GS, GA and GF were 8.70, 12.09 and 12.42%, respectively, showing that GS had much less than the others. Also affecting water-holding capacity, GA and GF were commercially made to fine powders, whereas GS is thought to have larger particles, which may have affected the surface tension to water. Currently, many studies have investigated methods for improving the functional properties of fish gelatin with the hope of making the quality equivalent to mammalian gelatin (Ferna´ndez, Montero, & Go´mez-Guille´n, 2001; Montero, Go`mez-Guille`n, & Borderias, 1999). Because shark cartilage gelatin has different functional properties from mammalian gelatin, further research is needed to improve its functional properties; research is also need for
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the development of products well matched to the properties that are characteristic of shark gelatin.
Acknowledgements This work was supported by Pukyong National University Research Fund in 2000.
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Johnson, T., & Zabik, M. (1981). Egg albumin proteins interactions in an angel food cake system. Journal of Food Science, 46, 1231. Kim, J. S., & Cho, S. Y. (1996). Screening for raw material of modified gelatin in marine animal skins caught in coastal offshore water in Korea. Agricultural and Chemical Biotechnology, 39, 134–139. Kinsella, J. E. (1977). Functional properties of protein: possible relationships between structure and function in foams. Journal Food Chemistry, 7, 273 –288. Ledward, D. A. (1986). Gelation of gelatin. In J. R. Mitchell, & D. A. Ledward (Eds.), Functional properties of food macromolecules (pp. 171– 201). London: Elsevier. Lin, M. H. Y., Humbert, E. S., & Sosulki, F. W. (1974). Certain functional properties of sunflower meal products. Journal of Food Science, 39, 368– 370. Montero, P., Ferna´ndez, M. D., & Go´mez-Guille´n, M. C. (2002). Characterization of gelatin gels induced by high pressure. Food Hydrocolloids, 16, 197–205. Montero, P., & Go´mez-Guille´n, M. C. (2000). Extracting conditions for megrim (Lepidorhombus boscii) skin collagen affect functional properties of the resulting gelatin. Journal of Food Science, 65, 434– 438. Montero, P., Go`mez-Guille`n, M. C., & Borderias, A. J. (1999). Functional characterization of muscle and skin collagenous material from hake (Merluccius merluccius L.). Food Chemistry, 65, 55–59. Osborne, K., Voight, M. N., & Hall, D. E. (1990). Utilization of lumpfish carcasses for production of gelatin. Advances in fisheries technology and biotechnology for increased profitability, Lancaster, PA: Technomic Publishing Co, pp. 143–153. ¨ zdemir, M., & Devres, O. (2000). Analysis of color development during O roasting of hazelnuts using response surface methodology. Journal of Food Engineering, 45, 17 –24. Rao, K. J., Kim, C. H., & Rhee, S. K. (2000). Statistical optimization of medium for the production of recombinant hirudin from Saccharomyces cerevisiae using response surface methodology. Process Biochemistry, 35, 639–647. Sathe, S. K., Deshpande, S. S., & Salunkhe, D. K. (1982). Functional properties of lupin seed (Supinus mutabilis) proteins and protein concentrates. Journal of Food Science, 7, 191–197. Sato, K., Ohashi, C., Ohtsuki, K., & Kawabata, M. (1991). Type V collagen in trout (Salmo gardineri) mescle and its solubility change during chilled storage of muscle. Journal of Agricultural and Food Chemistry, 39, 1222–1225. SKW Biosystems (2001, 2002). Process for the preparation of fish gelatin. Fr. EP. Patent 1,016,347 B1 and US Patent, 6,368,656 B1. Tukey, J. W (1953). The problem of multiple comparisons. Mimeographed monograph. Ward, A. G., & Courts, A. (1977). The science and technology of gelatins. New York: Academic Press, 599 pp. Yoshimura, K., Terashima, M., Hozan, D., Ebato, T., Nomura, Y., Ishii, Y., & Shirai, K. (2000). Physical properties of shark gelatin compared with pig gelatin. Journal of Agricultural and Food Chemistry, 48, 2023–2027.
Processing optimization and functional properties of gelatin from shark (Isurus oxyrinchus) cartilage S.M. Choa, K.S. Kwaka, D.C. Parkb, Y.S. Gua, C.I. Jia, D.H. Jangc, Y.B. Leea, S.B. Kima,* a
Department of Food Science and Technology, Institute of Seafood Science, Pukyong National University, Busan 608-737, South Korea b Korea Food Research Institute, Sungnam 463-746, South Korea c Division of Mathematical Sciences, Pukyong National University, Busan 608-737, South Korea Received 20 March 2003; accepted 3 October 2003
Abstract Gelatin processing from shark (Isurus oxyrinchus) cartilage was optimized by response surface methodology: the dependent variable was gelatin yield and independent variables were sodium hydroxide concentration and treatment time for the alkali treatment, and extraction temperature and time for the hot-water extraction. Predicted maximum yields of 79.9% for gelatin processing were obtained under the conditions of alkali treatment with 1.6N sodium hydroxide for 3.16 days and hot-water extraction at 65 8C for 3.4 h. Amino acid composition and functional properties of shark cartilage gelatin were examined in comparison to two porcine skin gelatins. Shark cartilage gelatin had lower concentration of hydroxyproline than the two porcine skin gelatins. Shark cartilage gelatin showed worse turbidity than the two porcine skin gelatins. Foam formation ability, foam stability, water-holding capacity and gel strength of shark cartilage gelatin were lower than the two porcine gelatins, but fat-binding capacity was higher in the shark cartilage gelatin. q 2003 Elsevier Ltd. All rights reserved. Keywords: Gelatin; Shark cartilage; Functional properties; Gel strength; Response surface methodology
1. Introduction Gelatin is a denatured protein derived from collagen by thermo-hydrolysis and has a rheological property of thermoreversible transformation between sol and gel. Gelatin is one of the most important biopolymers, with widespread applications in the food, pharmaceutical, cosmetic and photographic industries. Recently, its use is expanding to new applications such as functional foods. Gelatin is commercially made from skins and skeletons of bovine and porcine and mammalian gelatin has been intensively studied (Ward & Courts, 1977; Gilsenan & Ross-Murphy, 2000). However, mammalian gelatin is at risk for contamination with bovine spongiform encephalopathy, so fish skins, as by-products from fish processing, have been studied as a replacement for mammalian sources (Gudmundsson, 2002). Therefore, research on fish gelatin is very important for the development of methods for the efficient utilization of by-products from fish processing * Corresponding author. Tel.: þ 82-51-620-6418; fax: þ82-51-622-9248. E-mail address: [email protected] (S.B. Kim). 0268-005X/$ - see front matter q 2003 Elsevier Ltd. All rights reserved. doi:10.1016/j.foodhyd.2003.10.001
as replacements for mammalian sources (Montero & Go´mez-Guille´n, 2000). Gelatin quality is typically evaluated on the basis of several functional properties. Gel strength is the most important property of gelatin for industrial applications. Moreover, the quality of commercial gelatin is also determined by other properties, such as viscosity, melting point, gelling point, turbidity, solubility, etc. These properties are affected by many factors, such as amino acid composition, and the ratio of a-chain and content of bcomponent (Go´mez-Guille´n et al., 2002). Generally speaking, the functional properties of fish gelatin are inferior to mammalian gelatin. Furthermore, fish gelatin has a dark color and fishy odor. As a result, fish gelatin is seldom used commercially and not mass-produced. Little research has been devoted to the processing and functional properties of fish gelatin (Choi & Regenstein, 2000). The limited research on fish gelatin has evaluated gelatin derived from lumpfish (Osborne, Voight, & Hall, 1990), tilapia (Grossman & Bergman, 1992; Jamilah & Harvinder, 2002), conger and squid (Kim & Cho, 1996), cod (Gudmundsson & Hafsteinsson, 1997), shark (Yoshimura et al., 2000) and megrim
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(Montero & Go´mez-Guille´n, 2000). These studies were limited to only fish skins of a few marine species. The objectives of this study were to make gelatin from shark cartilage instead of fish skin, to determine the optimum conditions for gelatin processing using response surface methodology with a central composite design, and to compare the gelatin with two commercial porcine skin gelatins. Therefore, this study had two primary outcomes: first was an investigation of new materials for replacing traditional sources of gelatin, and the second was the optimization of gelatin production using response surface methodology.
2. Materials and methods Frozen shark (Isurus oxyrinchus) cartilage, which was analyzed as the proximate composition of 78.3% moisture, 19.2% protein, 1.4% lipid and 1.1% ash was provided by Songho Food Development Co., Ltd (Busan, Korea). Two commercially produced porcine skin gelatins were used; one food grade (GF, 280 Bloom) was obtained from Baek Kyeung Food Co, Ltd (Kimhae, Korea) and one analytical grade (GA, 300 Bloom) was purchased from Osaka Pharmaceutical and Chemical Industry (Osaka, Japan). All reagents used were analytical grade. 2.1. Gelatin processing Shark cartilage was washed to remove contaminants, chopped and frozen at 2 15 8C until used. Cleaned shark cartilage was soaked in 8 volumes of (v/w) of sodium hydroxide solution (1 –2N) at 8 8C in a 200 rpm shaking incubator (HB-201SF, Hanbaek Scientific Co., Korea) for 2 – 4 days, to remove the non-collagen protein and subcutaneous tissue after they were swollen (SKW Biosystems, 2001, 2002). The alkali treated shark cartilage was washed, neutralized with 2N HCl and rewashed. For hot-water extraction, 7 volumes of (v/w) of distilled water were added. Gelatin was extracted at the pre-determined temperatures (40 – 80 8C) and times (1 – 5 h) in a water bath (SB-651, EYELA, Japan). The extracted solutions (pH 8) was centrifuged (SUPRA 30K, Hanil Science Industrial Co., Korea) for 30 min at 900g at 30 8C. The upper phase was vacuum-filtered with a filter paper (5A 110 mm, Advantec, Japan), and the filtered solution vacuum-concentrated to 10 brix at 60 8C and dried at 1.4 m/s for 24 h in a hot-air dryer (WFO-601SA, EYELA, Japan). 2.2. Quantitative analysis of gelatin Gelatin content was estimated from hydroxyproline content by the method of Sato, Ohashi, Ohtsuki, and Kawabata (1991), using a conversion factor of 11.42. Hydroxyproline content was determined by the method
described in ISO (1978), with slight modifications. 100 mg of dried gelatin and 5 ml of 6N HCl were added to test tubes. Gelatin in test tubes was hydrolyzed in a dry bath (Dry bath incubator 11-718-2, Fisher Scientific Co., USA) for 12 h. Following hydrolysis, the sample solutions were neutralized with 6N NaOH, 2 ml of acetate/citrate buffer was added and the samples brought to a total volume of 25 ml with 0.3 M NaCl. Next, 300 ml of the sample solutions, 300 ml of isopropanol and 600 ml of oxidant solution were pipetted into test tubes. After 4 min, 4 ml Ehrlich’s reagent solution was added to each tube, the sample solutions were mixed, and the tubes were heated for 25 min in a 60 8C water bath. Absorbance of the solutions was measured with a spectrophotometer (UV-140-02, Shimadzu, Japan) at 660 nm. The hydroxyproline contents of the sample solutions were calculated from a calibration curve derived from standards using analytical grade hydroxyproline. 2.3. Analysis of amino acids A 5 mg aliquot from each dried gelatin sample was dissolved in 3 ml of 6N HCl, dried, and hydrolyzed in vacuum-sealed glass tubes at 110 8C for 24 h using a dry bath (Dry bath incubator 11-718-2, Fisher Scientific Co., USA). After hydrolysis, samples were vacuum-dried, dissolved in citric acid buffer (pH 2.2, Sigma Chemical Co.) and injected into an amino acid auto analyzer (Amino acid analyzer S-433H, Sycam, Germany). 2.4. Functional properties Gel strength was measured by rheometer (Compac-100, Sun Scientific Co. Ltd, Japan). A 6.67% (w/v) gelatin solution was gel-formed for 12 h at 5 8C, and the gel strength was measured by plunging into the middle of gel at the rate of 2 cm/min with a 50 mm diameter disc. The value of gel strength is represented as kPa. Turbidity of gelatins was determined by measuring absorbance of 0.1% gelatin solutions at 660 nm using a spectrophotometer (UV-140-02, Shimadzu, Japan). Turbidity was calculated from a calibration curve using a standard solution of Kaolin, and expressed in parts per million (ppm). Foam formation capacity and foam stability were measured by a partially modified method of Sathe, Deshpande, and Salunkhe (1982). A 1 g sample was placed in 50 ml distilled water and swollen. The sample solution was dissolved at 60 8C and the foam was prepared by homogenizing at 10,000 rpm for 5 min (Ace homogenize, AM-8, Japan). The homogenized solution was poured into a 250 ml mess flask. The foam formation ability was calculated as the volume ratio of foam liquid. The foam stability was calculated as the ratio of the initial volume of foam to the volume of foam after 30 min.
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Table 1 Experimental range and values of the independent process variables in the design for production of shark (I. oxyrinchus) cartilage gelatin
Table 2 Responses of dependent variables for production of shark (I. oxyrinchus) cartilage gelatin to independent variables
Process
Exp. No.
Independent variables
Symbol
Range and levels 21
Alkali treatment Hot-water extraction
0 1.5
þ1
Concentration of sodium hydroxide (N) Treatment time (days) Extraction temperature (8C)
X1
1
2
X2 X3
2 40
3 60
4 80
Extraction time (h)
X4
1
3
5
Water-holding and fat-binding capacities were measured by a partially modified method of Lin, Humbert, and Sosulki (1974). One gram of gelatin was placed in a centrifuge tube and weighed (tube with gelatin). For measuring water-holding capacity and fat-binding capacity, 50 ml distilled water or 10 ml corn oil were added, respectively, and held at room temperature for 1 h. The gelatin solutions were mixed with vortex mixer for 5 s every 15 min. The gelatin solutions were then centrifuged at 450g for 20 min. The upper phase was removed and the centrifuge tube was drained for 30 min on a filter paper after tilting to a 458 angle. Their capacities were calculated as the weight of the contents of the tube after draining divided by the weight of the dried gelatin, and expressed as the wt% of dried gelatin. 2.5. Response surface methodology The optimum conditions for processing gelatin from shark cartilage were determined by response surface methodology. Based on the results of preliminary studies, the two most important independent variables were (1) the concentration of sodium hydroxide and treatment time for alkali treatment and (2) the extraction temperature and time for hot-water extraction. The experimental design is shown in Table 1. The independent variables were coded to three levels of 2 1, 0, þ 1. The dependent variable was the amount the gelatin (%, dry basis) and was measured three times repeatedly. The optimum conditions for gelatin processing were obtained by using response surface methodology of the coded independent variables, using design of Table 2. All the experimental data were statistically analyzed by SAS software (Version 8.01, SAS Institute Inc., USA). 2.6. Statistical analysis The experimental data of gel strength turbidity, foam formation capacity, foam stability, water-holding and fatbinding capacities were measured three times repeatedly. Significant differences were performed using values that repeated three times. One-way variance analysis was
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54
Variable levels
Responses, Y
X1
X2
X3
X4
21 21 21 21 21 21 21 21 21 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.16
21 21 21 0 0 0 1 1 1 21 21 21 0 0 0 1 1 1 21 21 21 0 0 0 1 1 1 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 21 21 21 21 21 21 21 21 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 21 21 21 0 0 0 1 1 1 21 21 21 0 0 0 1 1 1 21 21 21 0 0 0 1 1 1
43.3 43.8 43.9 55.5 55.9 55.3 52.9 51.2 51.5 55.0 55.8 55.8 80.7 81.8 79.5 68.2 68.9 67.5 52.8 52.6 51.3 70.1 71.5 69.1 58.3 58.3 58.9 42.2 42.9 42.9 56.0 56.0 56.0 54.4 54.1 54.2 56.9 57.7 58.7 82.5 82.5 81.3 69.2 69.7 69.5 52.3 52.8 53.6 72.2 72.9 72.6 65.1 65.1 65.2
carried out and differences separated by the Tukey test (Tukey, 1953) using SAS software (Version 8.01, SAS Institute Inc., USA), differences were considered significant at p # 0:05:
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3. Results and discussion 3.1. Optimization of gelatin processing by response surface methodology
Table 4 Response surface model for production conditions of shark (I. oxyrinchus) cartilage gelatin Response
Quadratic polynomial model
R2
Significance
Recently, response surface methodology has been used to evaluate the effectiveness of food manufacturing processes. Response surface methodology is a collection of mathematical and statistical techniques widely used to determine the effects of multiple variables and to optimize different biotechnological process. Response surface methodology is a mathematical modeling technique that relates product treatment to outcomes and establishes regression equations that describe inter-relations between input parameters and ¨ zdemir & product properties (Rao, Kim, & Rhee, 2000; O Devres, 2000). Gelatin processing has two important steps: alkali treatment and hot-water extraction. The alkali treatment removes non-collagen protein after swelling the sample in the alkali solution, the hot-water extraction uses thermohydrolysis to solubilize and separate the gelatin. The alkali treatment using 8 times (v/w) the volume of sodium hydroxide solution as shark cartilage resulted in consistent yields of gelatin; therefore, the amount of hydroxide solution was fixed to 8 volumes. The concentrations of sodium hydroxide solution and treatment times were varied and were important independent variables. In the hot-water extraction, using 7 times (v/w) the distilled water as alkalitreated collagen resulted in consistent yields of gelatin, so the amount of distilled water was fixed to 7 volumes. The extraction temperature and time were varied and were also important independent variables. Independent variables were the concentration of sodium hydroxide solution, alkali treatment time, hot-water extraction temperature, and extraction time. As the result of procedure RSREG of SAS, linear term ðX1 ; X2 ; X3 ; X4 Þ and pure quadratic term ðX12 ; X22 ; X32 ; X42 Þ were significant (Table 3), but mixed quadratic term was not ðp ¼ 0:79Þ: Therefore, the response surface model was calculated by using the REG procedure (Table 4). This model equation was the best because the equation had the lowest AIC (Akaike Information Criteria, Akaike, 1973). When consider standard error of each parameter on the model equation, contributions of all factors, X1 (concentration of sodium hydroxide) and X2 (treatment time) on
Gelatin contents (%, dry basis)
Y ¼ 77:574 þ 4:989X1 þ4:533X2 þ 6:233X3 þ5:917X4 2 12:923X12 213:957X22 2 12:338X32 213:155X42
0.9571
0.001
Table 3 Analysis of variance for the regression model representing yield of gelatin ðYÞ
The amino acid compositions of GS (shark cartilage gelatin), GA (analytical grade gelatin) and GF (food additives grade gelatin) are shown in Table 5. The amino acid composition of GA and GF was similar, while that of shark cartilage gelatin was different from the porcine gelatins. Ledward (1986) reported that gelatin has a repeated structure of Gly-X-Y. When proline (Pro) and hydroxyproline (Hyp) were located in the X and Y positions, the gelatin structure was stable. While the imino acid content (Hyp þ Pro) of GA and GF of porcine gelatins
Sources
DF
SS
MS
F-value
P
Linear Quadratic Error Total
4 4 45 53
2188.066 4123.559 286.115 6597.740
547.017 1030.889 6.358
86.036 162.141
0.001 0.001
SS, sum of squares; DF, degrees of freedom; MS, mean square.
alkali treatment and X3 (extraction temperature) and X4 (extraction time) on hot-water extraction, were resemblant almost. If any factors recede from optimal conditions close to code 0, yield of gelatin from shark cartilage has a tendency to decrease greatly because parameters of pure quadratic term are negative. Optimal conditions were determined by setting the partial derivatives of the model equation to zero. The stationary point is a maximum. Critical values of factors were concentration of sodium hydroxide; X1 ¼ 0:19; treatment time; X2 ¼ 0:16; extraction temperature; X3 ¼ 0:25; extraction time; X4 ¼ 0:22; respectively. Actual values of factors against critical values were concentration of sodium hydroxide; 1.6N, treatment time; 3.16 days, extraction temperature; 65 8C, extraction time; 3.44 h. Predicted value at stationary point was 79.9%. Chemical composition of shark cartilage gelatin was 7.98% moisture, 90.9% crude protein, 0.54% crude ash and 0.21% crude lipid and that of GA was 8.52% moisture, 90.2% crude protein, 0.51 crude ash and 0.29% crude lipid. Gelatin consists of most protein and water. So, ash, lipid and other impurity contents are important for quality of gelatin. Usually ash contents up to 2.0% can be accepted in food applications. Crude ash content of GS was 0.54% and analogous almost to 0.51% of GA. Furthermore, crude lipid content of GS was lower than that of GA. GS is satisfied for a gelatin standard of JIS (Japanese Industrial Standard) K6503-1996 (moisture 8 –14%, crude protein . 85%, crude ash , 2%, crude lipid and other components , 1%) and similar to moisture (8.52%), crude protein (90.2%), crude ash (0.51%) and lipid or other impurities , 1%. Therefore, GS has a potential for food applications. 3.2. Composition of amino acids of shark cartilage gelatin
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Table 5 Amino acid composition of shark (I. oxyrinchus) cartilage gelatin as compared with two porcine skin gelatins Amino acids
Hydroxyproline Aspartic acid Threonine Serine Glutamic acid Proline Glycine Alanine Valine Methionine Isoleucine Leucine Tyrosine Phenylalanine Lysine Histidine Arginine Imino acids (Hyp þ Pro)
Gelatin type GA
GF
GS
10.79 5.11 1.75 3.46 8.26 11.36 32.89 11.52 2.13 0.90 1.21 2.39 0.09 1.02 2.86 0.38 3.83 22.15
10.91 4.56 2.03 4.03 7.10 11.01 32.03 11.58 2.40 0.95 1.92 2.63 0.21 1.19 2.32 0.49 4.39 21.92
7.70 4.36 2.41 4.21 8.01 11.97 32.12 11.84 2.35 1.85 2.44 0.12 1.13 1.01 2.27 0.54 4.43 19.57
GA, Gelatin of analytical grade from porcine skin; GF, gelatin of food additives grade from porcine skin; GS, felatin from shark (I. oxyrinchus) cartilage.
was similar at 22.15 and 21.92%, respectively, the amount of hydroxyproline in GS, 7.70%, was much lower than those of GA (10.79%) and GF (10.91%). The amount of proline in GS, 11.97%, was a little higher than in GA (11.36%) and GF (11.01%). Therefore, the mammalian gelatins, GA and GF, had nearly equal amounts of proline and hydroxyproline. It is believed that the structural stability of gelatin is largely dependent on the amount of hydroxyproline, which was lower in the shark cartilage gelatin, although proline content was high. Lysine also stabilizes gelatin structure by forming cross-linking structures between chains. The percentage of lysine in GS was 2.27, which was equal to the 2.32 of GF and less than the 2.86 of GA. Glycine was the most abundant amino acid in all gelatin samples, and normally makes up about one-third of the total. GS, GA and GF had 32.12, 32.89 and 32.03% glycine, respectively, exhibiting close similarity. Fish gelatin tends to have different ratios of amino acids from mammalian gelatin. Because of the different ratio of amino acids, fish gelatin has different functional properties from mammalian gelatin, which is consistent with the results of Arnesen and Gildberg (2002). 3.3. Functional properties of shark cartilage gelatin Gel strength is one of the most important functional properties of gelatin and fish gelatin typically has less gel strength than mammalian gelatin (Gilsenan & Ross-Murphy, 2000). Gel strength is a function of complex interactions determined by amino acid composition and the ratio of a-chain and the amount of b-component. Gel
Fig. 1. Turbidity and gel strength of shark (I. oxyrinchus) cartilage gelatin as compared with two porcine skin gelatins. Different letters (a, b, c, a0 , b0 , c0 ) indicate significant differences at p # 0:05: GA, gelatin of analytical grade from porcine skin; GF, gelatin of food additives grade from porcine skin; GS, gelatin from shark cartilage.
structure of gelatin is more stable when the imino acid (Hyp þ Pro) content is higher, and the amount of aggregates of higher molecular weight is less (Go´mez-Guille´n et al., 2002). Gel strengths of GS, GA and GF are shown in Fig. 1. For comparison with shark cartilage gelatin, Bloom strengths of two porcine skin gelatins GA and GF are 300 Bloom and 280 Bloom, respectively. Gel strengths of GA and GF were 149.9 and 137.8 kPa showing a similar trend to their Bloom strengths. Gel strength of GS was 111.9 kPa, which was less than the porcine gelatins at 149.9 and 137.8 kPa for GF. The lower gel strength in GS is probably due to its lower amount of imino acids (Hyp þ Pro), which stabilize gelatin structures, which was not offset by high lysine which could form crosslinks that would stabilize the gelatin. As shown in Table 5, the amount of imino acids (Hyp þ Pro) of GS, GA and GF were 22.35, 24.82 and 24.95%, respectively, with shark cartilage gelatin having the least. Formation of higher molecular weight aggregates by hot-air drying is also thought to affect gel strength of shark cartilage gelatin. As shown in Table 5, the amount of proline was highest in GS, but the amounts of total imino acids and hydroxyproline were lowest. Hydroxyproline is believed to be the major determinant of stability due to its hydrogen bonding ability through its hydroxyl group, although proline is also important (Burjandze, 1979; Ledward, 1986). This study appears to confirm the role of hydroxyproline as the major determinant for gel strength. Turbidities of GS and two porcine skin gelatins of GA and GF are shown in Fig. 1. The turbidity of GS was 12.04 ppm, which was much higher than that of GA at 0.61 ppm and two times higher than GF at 6.33 ppm. When protein is treated for a long time at high temperatures, aggregation is activated and turbidity increased (Johnson
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and Zabik, 1981). As the aggregates of higher molecular weight increase turbidity also increases (Montero, Ferna´ndez, & Go´mez-Guille´n, 2002). The high turbidity of GS may be due to the formation of more aggregates of higher molecular weight during the 24 h of hot-air drying, decreasing the gelatin’s solubility by exposing many hydrophobic residues; turbidity may have also been increased because no purification steps were applied. GA was thought to have very low turbidity because GA is highly purified for an analytical grade. Nevertheless, GS was two times higher than that of GF, the food grade gelatin, although it may also have been more purified for industrial use. Greater purification may improve the turbidity of shark cartilage gelatin. Foam formation ability is another important property of gelatin for commonly used foods such as marshmallows. Foam formation abilities of GS, GA and GF are shown in Fig. 2. Foam formation ability of GS was 2.6 (the ratio of foam volume/liquid volume), a little lower than the 2.8 of GA and 2.9 of GF. Foam stability of GS was 1.5 (the ratio of the volume after 30 min/initial volume of foam) was a little less than the 1.4 of GA and GF, demonstrating the lower stability of GS. Therefore, GS has the lowest foam formation ability and the lowest foam stability of the three gelatins. It has been suggested that reduced foam formation and stability may be due to aggregation of proteins which interfere with interactions between the protein and water needed for foam formation (Kinsella, 1977).
Fig. 2. Foam formation ability and foam stability of shark (I. oxyrinchus) cartilage gelatin as compared with two porcine skin gelatins. Different letters (a, b, c, a0 , b0 , c0 ) indicate significant differences at p # 0:05: GA, gelatin of analytical grade from porcine skin; GF, gelatin of food additives grade from porcine skin; GS, gelatin from shark cartilage. The ratio of foam formation ability means foam/liquid (v/v) and that of foam stability means foam after 30 min/initial foam (v/v).
Fig. 3. Water-holding capacity and fat-binding capacity of shark (I. oxyrinchus) cartilage gelatin as compared with two porcine skin gelatins. Different letters (a, b, c, a0 , b0 , c0 ) indicate significant differences at p # 0:05: GA, gelatin of analytical grade from porcine skin; GF, gelatin of food additives grade from porcine skin; GS, gelatin from shark cartilage.
Water-holding and fat-binding capacities are functional properties that are closely related to texture by the interaction between components such as water, oil and other components. Water-holding capacity and fat-binding capacity of the three gelatins are shown in Fig. 3, showing that they have similar values. While GS had the highest fat-binding capacity, it had the lowest water-holding capacity. Fatbinding capacity depends on the degree of exposure of the hydrophobic residues inside gelatin. In the case of GS, hydrophobic residues are believed to have been exposed during the hot-air drying process. As shown in Table 5, the hydrophobic amino acid, tyrosine, made up 1.17% of GS which was much higher that that of porcine skin gelatins at 0.10 and 0.24% for GA and GF, respectively. The high amount of tyrosine is probably responsible for the high fatbinding capacity of GS. Water-holding capacity is believed to be affected by the amount of hydrophilic amino acids. The amounts of hydroxyproline in GS, GA and GF were 8.70, 12.09 and 12.42%, respectively, showing that GS had much less than the others. Also affecting water-holding capacity, GA and GF were commercially made to fine powders, whereas GS is thought to have larger particles, which may have affected the surface tension to water. Currently, many studies have investigated methods for improving the functional properties of fish gelatin with the hope of making the quality equivalent to mammalian gelatin (Ferna´ndez, Montero, & Go´mez-Guille´n, 2001; Montero, Go`mez-Guille`n, & Borderias, 1999). Because shark cartilage gelatin has different functional properties from mammalian gelatin, further research is needed to improve its functional properties; research is also need for
S.M. Cho et al. / Food Hydrocolloids 18 (2004) 573–579
the development of products well matched to the properties that are characteristic of shark gelatin.
Acknowledgements This work was supported by Pukyong National University Research Fund in 2000.
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