Optimizing Sensorial Quality of Iranian White Brine Cheese Using Response Surface Methodology MOHAMMAD ALIZADEH, MANOUCHEHR HAMEDI, and ASGHAR KHOSROSHAHI

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Optimizing Sensorial Quality of Iranian White Brine Cheese Using Response Surface Methodology MOHAMMAD ALIZADEH, MANOUCHEHR HAMEDI, and ASGHAR KHOSROSHAHI JFS S: Sensory and Nutritive Qualities of Food Optimizing Sensorial Quality of Iranian White Brine Cheese Using Response Surface Methodology MOHAMMAD ALIZADEH, MANOUCHEHR HAMEDI, AND ASGHAR KHOSROSHAHI ABSTRACT: Response surface methodology was used to evaluate the effects of processing variables, such as ripening time (20 to 60 d), ripening temperature (6 to 10 °C), level of rennet added (1 to 2 g/100 kg milk), and brine concentration (8% to 14%, w/v), on the sensorial quality of Iranian pickled cheese (feta type). Optimiza- tion of sensorial quality was performed by canonical analysis to derive the stationary point. Based on contour plots and canonical analysis, optimum conditions were ripening time 32 d, ripening temperature 8.3 °C, level of rennet added 1.6 g/100 kg of milk, and brine concentration 11%. Predicted sensory score was 20.76 from maxi- mum score of 25. Keywords: pickled cheese, sensorial quality, optimization, response surface methodology Introduction Materials and methods n Iran, pickled cheese is a major item in diet, and consumption Iper capita per annum is about 5.4 kg. At the industrial level, the Cheese making ripening time is about 45 to 90 d (Azarnia 1997). However, there are The brine cheese was manufactured for this study according to trends to reduce this time period for economical reasons. the method used in Iranian cheese-making plants. White brined Pickled cheese, like other types of ripened cheese, requires cheese was prepared from cows’ milk. The milk was standardized to maturation to develop the required sensory properties. In warm cli- a fat content of 2.5%, pasteurized at 72 °C for 15 s, and cooled to 32 mates, it is necessary to preserve cheeses in brine. The specific to 35 °C. CaCl2 was added at a level of 15 g/100 kg of milk followed characteristics of brine cheese develop in the salted water and by the addition of 1% starter culture (Hansen’s Laboratory, Roskil- chemical, physical, and sensorial properties of this type of cheese de, Denmark) 30 min before renneting. Cultures of Streptococcus sal- are controlled by processing and environmental conditions (Abd ivarius subsp. thermophilus and Lactobacillus delbrueckii subsp. El-Salam 1987; Caric 1987; Abou-Donia 1991; Scott 1986). bulgaricus were used as starter. Commercial powdered microbial Pickled cheese–manufacturing plants in Iran work with different rennet (Meito, Sangyo Co., Nagoya, Japan) with milk-clotting activ- levels of processing variables. For example, brine concentration ity of 1 g/100 kg of milk were added at 3 experimental levels (1, 1.5, varies from 8% to 16% w/v, ripening temperature varies from 6 to and 2 g/100 kg milk) to coagulate milk samples. Following coagula- 16 °C, and so on. It is evident that with these conditions, the pro- tion, the curds were cut and then stirred. The curds were pressed duced cheeses will not have uniform quality. The number of factors using weights for 1 h (20 kg weight/30 kg final curd). The curds were that determine sensorial quality of pickled cheeses is so large that then cut to a suitable shape and size and soaked in a sterile brine it is impossible to study all of them simultaneously. (22%, w/v) for 16 h. The curd pieces were then placed in tin cans; Response surface methodology (RSM) is an effective tool regu- brines with 3 different concentrations (8%, 11%, and 14%, w/v) were larly used for studying the separate and interactive effects of sys- added to cover the curds completely and fill cans. The filled cans tem factors on a desired response variable (Hunter 1959). RSM were sealed immediately after brining. The sealed cans were stored currently is the most popular technique in food science for empir- at 3 different ripening temperatures (6, 10, and 14 °C) for 3 different ical optimization studies because of its comprehensive theory, rea- ripening times (20, 40, and 60 d). sonably high efficiency, and simplicity (Arteaga and others 1994). First- or second-order polynomials are the most common model Experimental design functions used to describe RSM (Khuri and Cornell 1987). A 3-level, 4-factor experimental design with 3 replicates at the In this study, we have evaluated the effects of 4 factors, ripen- center point was used (Box and Behnken 1960). The 4 factors (pro- ing temperature, ripening time, the level of rennet added, and cessing variables), levels, and experimental design in coded and brine concentration, on sensorial quality of pickled cheese and uncoded terms are given in Table 1. determine optimum conditions. Sensory evaluation Sensory evaluations of cheese samples were obtained for flavor, MS 20040700 Submitted 10/22/04, Revised 12/30/04, Accepted 2/15/05. Au- body and texture, and odor and appearance by Iran’s standard thors Alizadeh and Khosroshahi are with Food Science and Technology Dept., Faculty of Agriculture, Univ. of Urmia, Urmia, Iran. Author Hamedi 2344-1 (ISIRI 2002) for white pickled cheese. In this sensory system, is with Food Science and Technology Dept., Faculty of Agriculture, Univ. of the product is graded on a 25-point scale as follows: 10 points max- Tehran, Karaj, Iran. Direct inquiries to author Alizadeh imum for flavor (1 = intensive foreign flavors like acid, bitter, soapy, (E-mail: [email protected]). and so on to 10 = special flavor of the Iranian ripened white brine © 2005 Institute of Food Technologists Vol. 70, Nr. 4, 2005—JOURNAL OF FOOD SCIENCE S299 Further reproduction without permission is prohibited Published on Web 4/28/2005 S: Sensory & Nutritive Qualities of Food Optimizing sensorial quality of cheese . Table 1—Box-Behnken design used to evaluate the effects of process variables on sensory score of cheese Rennet added Brine concentration Temperature (°C) (X1) Time (d) (X2) (g/100 kg milk) (X3) (% w/v) (X4) Uncoded Coded Uncoded Coded Uncoded Coded Uncoded Coded Run value value value value value value value value 1 6 –1 20 –1 1.5 0 11 0 2 6 –1 40 0 1 –1 11 0 3 6 –1 40 0 1.5 0 8 –1 4 6 –1 40 0 1.5 0 14 1 5 6 –1 40 0 2 1 11 0 6 6 –1 60 1 1.5 0 11 0 7 10 0 20 –1 1 –1 11 0 8 10 0 20 –1 1.5 0 8 –1 9 10 0 20 –1 1.5 0 14 1 10 10 0 20 –1 2 1 11 0 11 10 0 40 0 1 –1 8 –1 12 10 0 40 0 1 –1 14 1 13 10 0 40 0 1.5 0 11 0 14 10 0 40 0 1.5 0 11 0 15 10 0 40 0 1.5 0 11 0 16 10 0 40 0 2 1 8 –1 17 10 0 40 0 2 1 14 1 18 10 0 60 1 1 –1 11 0 19 10 0 60 1 1.5 0 8 –1 20 10 0 60 1 1.5 0 14 1 21 10 0 60 1 2 1 11 0 22 14 1 20 –1 1.5 0 11 0 23 14 1 40 0 1 –1 11 0 24 14 1 40 0 1.5 0 8 –1 25 14 1 40 0 1.5 0 14 1 26 14 1 40 0 2 1 11 0 27 14 1 60 1 1.5 0 11 0 cheese with no foreign flavor); 5 points maximum for body and tex- ture (1 = very soft or hard or sticky to 5 = continuous body, not very soft or hard); 5 points maximum for odor (1 = intensive foreign fla- vors like pungent, malty, or rancid to 5 = special flavor of the Iranian ␤ ␤ ␤ ␤ ripened white brine cheese with no perceptible foreign odors); and where Y is response (sensory score), 0, i, ii, and ij are constant 5 points maximum for appearance (1 = moldy, very porous with large coefficients, and xi is the uncoded independent variable. Pareto pores, and yellow color to 5 = uniform and nonporous with white chart and contour plots were created using Statistica version 6.0 color). Samples of white, brined cheese were cut into pieces about (Statsoft, Tulsa, Okla., U.S.A.). 3 ×times/ 3 × 2 cm in size and placed on white plates coded with three-digit random numbers. The cut samples were tempered by Results and Discussion holding at ambient temperature (20 ± 2 °C) and then presented to fter statistical analysis of data, the second-order polynomial the panelists in a random order for testing. Water was provided for Aequation is given below: mouth washing between samples. The cheeses were evaluated organoleptically after 20, 40, and 60 d of ripening by 5 experienced panelists according to a scoring card (Bodyfelt and others 1988). Panelists were familiar with feta cheese and were trained by exposure to the different commercial where Y is sensory score and x , x x , and x are ripening tempera- white brine cheese samples and a practice session was held 1 d 1 2, 3 4 ture, ripening time, rennet added, and brine concentration, respec- before the regular evaluation sessions. Each of the panelists eval- tively. uated each experimental sample, and in each session, 3 samples With the lack of fit test, the analysis of variance (Table 2) showed were given to each of the panelists. that the model appeared to be adequate, with no significant lack of The total score was obtained by adding the scores for the 4 sen- fit (P = 0.271) and with a satisfactory R2 (0.915). S: Sensory & Nutritive Qualities of Food sory attributes.
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