Optimization of Enzymatic Hydrolysis of Visceral Waste Proteins of Yellowfin Tuna (Thunnus albacares)

Abstract

Fish protein hydrolysate was produced from the viscera of yellowfin tuna (Thunnus albacares). Hydrolysis conditions (enzyme activity, temperature, and time) were optimized using response surface methodology. A factorial design was applied to minimize enzyme utilization and modeling of degree of hydrolysis (r 2 =0.94). Lack-of-fit test revealed a non-significant value for the model, indicating that the regression equation was adequate for predicting the degree of hydrolysis under any combination of the variables (P<0.05). The optimum conditions to reach the highest degree of hydrolysis were: 60.4°C, 90.25 min, and a protease (Alcalase 2.4 L) activity of 70.22 AU/kg protein.The spray-dried tuna visceral protein hydrolysates had relatively high protein (72.34%) and low lipid (1.43%) content. The chemical score of the hydrolysate indicated that it fulfils adult human nutritional requirements except for methionine. Lysine and methionine were the first and the second limiting amino acids in that order. Phenylalanine was the predominant amino acid in the hydrolysates with respect to common carp requirement. In addition, the protein efficiency ratio of tuna visceral hydrolysate was 2.85-5.35.

Response surface optimization of enzymatic hydrolysis of duck blood corpuscle using commercial proteases

“…This means that the hydrolysis conditions play a dominant role in the peptide bond cleavage in the protein substrate, which concurs with other observations (Adler-Nissen, 1986;Bhaskar et al, 2008;Ovissipour et al, 2012). The largest F-value (85.84) for time indicated that it was the most important linear variable influencing the values of TCA index, followed by initial pH, temperature and substrate concentration.…”

“…The predicted protein efficiency ratio (PER) was calculated from the amino acid composition based on equations developed by Alsmeyer et al (1974) and Lee et al (1978). These equations have also been applied by some researchers to predict protein hydrolysates (Grazziotin et al, 2006;Ovissipour et al, 2012). The predicted biological value (BV) was calculated using the regression equation developed by Morup and Olesen (1976).…”

Optimization of hydrolysis condition of blood meal by Bacillus subtilis with response surface methodology

“…The cleavage of the peptide bonds of the protein substrate has been found to be markedly influenced by the conditions under which the substrate is hydrolyzed with bacterial proteases (Wang and Xu, 2007;Zhu and Row, 2011;Ovissipour et al, 2012). In this study, after the proteases were produced from the B. subtilis, the cleavage of the peptide bonds of the blood cells was influenced by the degradation conditions.…”

Novel modeling methodology for the characterization of enzymatic hydrolysis of proteins

“…Empirical models have also been used in both polynomial equations using the response surface methodology (RSM) [22][23][24][25][26] and artificial neural networks (ANN) [27][28][29] applied to fish protein hydrolysis. Multivariable polynomial equations allowed for the simultaneous study of multiple factors affecting the hydrolysis process.…”