2011 International Conference on Food Engineering and Biotechnology IPCBEE vol.9 (2011) © (2011)IACSIT Press, Singapoore

Impact of Processing Conditions on the Milk Clotting Activity of Crude Protease Extracted from Chinese

+ Malik Muhammad Hashim 1, Muhammad Farooq Iqbal 2, Chen Xiaohong 1and Dong Mingsheng 1 1 College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, 2 Faculty of Veterinary and Animal Sciences, Arid Agricultural University, Rawalpindi, Pakistan

Abstract. The impact of three processing parameters namely homogenization time, pH of buffer, and amount of buffer, involved in the liquid extraction of proteinases from ginger rhizomes, was investigated on milk coagulating activity by response surface methodology. An empirical quadratic model was applied to experimental data pertaining to the average enzymatic activity and equation describing the optimal conditions was obtained. The maximum milk clotting activity (274 U/mL) was obtained by homogenizing the ginger rhizomes in 76 mL of extraction buffer with a pH of 7.0 for 2.4 min. No significant (p > 0.05) difference was observed between the experimental and predicted values. These results are useful in the optimization of extraction procedures, which are of significant relevance to the production of standardized plant coagulants suitable for the cheese industry. Keywords: Ginger protease, Plant coagulant, Response surface methodology

1. Introduction Proteolytic enzymes or proteases are very important industrial enzymes, accounting for nearly 60% of the total worldwide enzyme production [1]. Plant-derived proteases such as papain, bromelain, ficin, and calotropins have potential application in food and biotechnological industries due to their broad substrate specificity, high stability in extreme conditions, good solubility and activity over a wide range of pH and temperature. Most of the plant derived-proteases have been classified as cysteine proteases [2]. Rennin, a milk-coagulating enzyme used in cheese making, is obtained from the stomach of the unweaned calf [3]. The worldwide increase of cheese consumption combined with rennet scarcity and ethical concerns have developed a global interest for natural milk-curdling enzymes from plant sources. Ginger juice is extensively employed in the manufacture of Ginger milk curd (a traditional Chinese ), locally named as “Jiang zhi ning ru”. This sweet food was originated about 100 years ago in the Shawan town of , in the Province in southern China. The juice is squeezed from a piece of ginger, filtered and put into a bowl. Sugar is added to milk and allowed to heat until it simmers. After cooling for a while, milk is poured quickly into the bowl of ginger juice which solidifies to form curd. The coagulating activity of the ginger juice is due to enzymes which also possess proteolytic activity. There is not any information about the optimization of extraction conditions of milk coagulating cysteine protease from ginger rhizomes. In this study, a response surface methodology was employed for modelling the possible relationship between the extraction conditions, namely the homogenization time, pH of buffer and amount of extraction buffer on the milk coagulating property of extracted cysteine protease from ginger rhizomes. Research was conducted with the final goal of obtaining conditions that lead to maximum yields of

+ Corresponding author. Tel.: + 86 25 84396989; fax: +86 25 84399090. E-mail address: [email protected]. 327 extracted activity, which hopefully could be applied to the optimization of the extraction process, a requirement for industrial scale up and commercial exploitation of such alternative rennet. 2. Material and methods 2.1. Preparation of crude ginger protease extracts Unless stated otherwise, all of the extraction procedures were carried out at 0-4°C. Ginger rhizomes (Zingiber officinale cv. Laiwu Shandong, 15 g) were peeled, diced, washed with deionized water, and then homogenized for 1, 2 or 3 min (as appropriate) using an HR 2839 blender (Philips, China) with 50, 75 or 100 mL 20 mM phosphate buffer (as appropriate) having pH 6.0, 7.0 or 8.0. The homogenate was filtered through cotton cloth. The filtrate was centrifuged at 12,000g for 20 min (Allegra 64R Centrifuge, Beckman Coulter, USA) to obtain crude enzyme extract.

2.2. Milk clotting activity The milk clotting activity was determined following the procedure of Arima et al. [4]. Briefly, assay milk

(2 ml, 10% skimmed milk in 0.01 M CaCl2, pH 6.5) was incubated for 10 min at 37 °C, and then enzyme extract (0.2 ml) was added. Milk clotting time was determined by manually rotating the flask occasionally and checking for visible clot formation. One milk-clotting unit is defined as the amount of enzyme required to clot 10 ml of substrate in 40 min at 37 °C.

2.3. Experimental design The impact of three independent variables, namely homogenization time (1–3 min, X1), pH of buffer (6– 8, X2) and amount of buffer (50–100 mL, X3) on milk clotting activity of extracted protease from ginger rhizomes was investigated using RSM. The independent variables and their levels were selected on the basis of literature and preliminary experiments. A Box–Behnken design with three variables at three levels was used to determine the response pattern and then establish a model [5, 6]. The experimental design, data analysis and quadratic model building were performed using “Design Expert” software (Version 8.0.4, Stat- Ease Inc., Minneapolis, MN, USA). n n n β ++= + 2 Y ∑∑jiijiio ∑XBXXBXB jjj i=<11ji j = where Y is response, B0 is a constant, Bi is the linear coefficient, Bij is the second-order interaction, and Bjj is the quadratic coefficients. The variable, Xi, is the un-coded independent variables. 3. Results and discussion 3.1. Optimization procedure In order to determine the optimum levels of the independent variables, multiple response optimizations were carried out [7]. According to Montgomery [8], the three dimensional (3D) response surface plots are highly recommended for the graphical demonstration of the interaction effect of the independent variables on the response variables. The effect of homogenization time, pH of buffer and amount of buffer on the milk clotting activity of ginger protease extracts from ginger rhizome and their interactions, are shown in Fig. 1. The factors significantly affected the response individually and interactively (p < 0.05). The effect of interaction between homogenization time and pH of buffer was more significant (p = 0.0031) than the interaction between homogenization time and amount of buffer (p = 0.0395) and pH of buffer and amount of buffer (p = 0.0045). Based on the linear effect homogenization time and pH of extraction buffer were more significant (p < 0.0001) than amount of buffer for milk clotting activity response (Table 1). An increase in homogenization time resulted in a higher milk clotting activity. Increasing the time of homogenization of the ginger rhizome is expected to improve extraction due to more extensive disruption of cell membrane (due to the more intimate contact promoted between the solid and the liquid phases) with concomitant easier and faster release of proteinases into the extraction medium [9]. The activity reached a maximum when the time of homogenization was at a certain level with no significant further improvement thereafter. Homogenization time above the optimum level had a negative effect on the activity of ginger

328 protease. A possible explanation for this phenomenon is the denaturation of proteins, and hence the enzyme inactivation due to intensive agitation. The pH of the extraction solution utilized has the most important linear effect on the final specific activity of the extracted enzyme. The total activity of ginger protease was enhanced at a pH of 7.0. It may be inferred that the large linear effect of pH on the final specific activity of the enzyme extracted arises primarily from the change in the intrinsic activity of the enzyme as a response to pH rather than from changes in the extraction yield brought about by pH [10]. Amount of buffer had a similar effect on the milk clotting activity of ginger protease as homogenization time and pH of the extraction medium. A volume of 76 ml of phosphate buffer was the best for extraction. There was a decrease in total activity when a lower volume of buffer was used for extraction, due possibly to an insufficient amount of buffer to penetrate the solid mass. In addition, increasing the buffer content above the optimum volume caused a rapid decrease in total activity of the extracted protease which ultimately resulted in undue dilution of solution [9].

3.2. Model fitting By use of analysis of variance (ANOVA), the established model was found to be significant (p < 0.0001) and could be used to predict milk clotting activity of ginger protease (Table 1).

a

b

c

Fig. 1: Fitted response surface and corresponding contour. (a): MCA vs. homogenization time and buffer pH at fixed amount of buffer 75mL; (b): MCA vs. homogenization time and buffer amount at fixed buffer pH 7; (c): MCA vs. buffer amount and buffer pH at fixed homogenization time 2 min. 329

The lack of fit of the model was p = 0.5413 which is not significant indicating that the model equations was adequate for predicting the response under any combination of values of the variables. Coefficient (R2) of determination is defined as the ratio of the explained variation to the total variation, and is a measurement of the degree of fitness [11]. A small value of R2 indicates a poor relevance of the dependent variables in the model. The model can fit well with the actual data when R2 approaches unity [12]. The high coefficient of determination value R2 = 0.9989 obtained indicated that the model as fitted can explain 99.8% of the variability thus confirming the adequacy of the model. Table 1 Analysis of variance (ANOVA) for response surface quadratic polynomial model Source Sum of squares d.f Mean squares F- value Prob (p) > F Model 15541.51 9 1726.83 688.77 <0.0001

X1 8064.50 1 8064.50 3216.61 <0.0001

X2 231.13 1 231.13 92.19 <0.0001

X3 55.13 1 55.13 21.99 0.0022 2 X1 4251.16 1 4251.16 1695.62 <0.0001 2 X2 828.21 1 828.21 330.34 <0.0001 2 X3 1368.00 1 1368.00 545.64 <0.0001

X1X2 49.0 1 49.0 19.54 0.0031

X1X3 16.00 1 16.00 6.38 0.0395

X2X3 42.25 1 42.25 16.85 0.0045 Residual 17.55 7 2.51 Lack of fit 6.75 3 2.25 0.83 0.5413 Pure error 10.80 4 2.70 Total 15559.06 16 2 2 2 R = 0.9989, R adj = 0.9974, R pred = 0.9920

3.3. Verification of the model Within the scope of the variables investigated in Box–Behnken design, additional experiments with different processing conditions were conducted to confirm the adequacy of the model equations. The conditions and the results of the confirmatory experiments are presented in Table 2. The correlation coefficient (R2) between the observed and predicted values of MCA was 0.90. The good correlation between the values observed in the experiments and the values predicted by the mathematical equations confirmed that the response model was adequate to reflect the expected optimization within the range of variables employed. Table 2 Observed and predicted values for validation of the experimental model Trial no Conditions Observed valuea Predicted value Homogenization Buffer pH Buffer amount time (min) (mL) 1 1.8 7.2 80 256 ± 2.5 258.26 2 2.0 6.8 77 263 ± 2.8 264.89 3 2.2 6.6 80 265 ± 1.6 266.14 4 2.6 6.4 70 265 ± 3.5 264.53 5 2.4 6.4 68 260 ± 2.9 264.30 aValues are indicated as mean + SD (n = 3)

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4. Acknowledgements This work was supported by 863 Program (2011AA100903), Ministry of Science and Technology, People's Republic of China. Malik Muhammad Hashim was financially supported by Higher Education Commission (HEC) of Pakistan. 5. References [1] K.B. Beg, V. Sahai, R. Gupta. Statistical media optimization and alkaline protease production from Bacillus mojavensis in a bioreactor. Process Biochem. 2003, 39: 203–209. [2] N.O. Caffini, LMI. Lopez, CL. Natalucci, NS. Priolo. Proteases of higher plants. General features, physiological roles and applications. Acta Farm. Bonaerense. 1988, 7: 195–213. [3] M.T.H. Cavalcanti, C.R. Martinez, V.C. Furtado, B.B. Neto, M.F. Teixera, J.L. Lima Filho, A.L.F. Porto. Milk- clotting protease production by Nocardiopsis sp. in an inexpensive medium. World J. Microbiol. Biotechnol. 2005, 21: 151–154. [4] K. Arima, J. Yu, S. Iwasaki. Milk-clotting enzyme from Mucor pusillus var. Lindt. Method Enzymol. 1970, 19: 446–459. [5] G.E.P. Box and D.W. Behnken. Some new three level designs for the study of quantitative variables. Technometrics. 1960, 2(4): 455–475. [6] L Wang, B. Pan, J. Sheng, J. Xu, Q. Hu. Antioxidant activity of Spirulina platensis extracts by supercritical carbon dioxide extraction. Food Chem. 2007, 105(1): 36–41. [7] H. Mirhosseini and C.P. Tan. Response surface methodology and multivariate analysis of equilibrium headspace concentration of orange beverage emulsion as function of emulsion composition and structure. Food Chem. 2009, 115: 324–333. [8] D.C. Montgomery. Design and Analysis of Experiments (5th ed) New York: Wiley, 2001. [9] M. Amid, C.P. Tan, H. Mirhosseini, N.A. Aziz, T.C. Ling. Optimisation of serine protease extraction from mango peel (Mangifera Indica Cv. Chokanan). Food Chem. 2011, 124: 666-671. [10] M.J. Sousa and F.X. Malcata. Effects of processing conditions on the caseinolytic activity of crude extracts of Cynara cardunculus L. Food Sci Technol Int. 1996, 2: 255-263. [11] A. Nath and P.K. Chattopadhyay. Optimization of oven toasting for improving crispness and other quality attributes of ready to eat potato-soy snack using response surface methodology. J. Food Eng. 2007, 80:1282–1292. [12] H.N. Sin, S. Yusof, N.S.A. Hamid, R.A. Rahman. Optimization of enzymatic clarification of sapodilla juice using response surface methodology. J. Food Eng. 2006, 73: 313–319.

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332 Author Index

A Dachyar Arbain 73,140 A. Prateepasen 234 Diana Ringgau 33 Abdul Latif Ibrahim 21 Ding Gong Tao 281 Abdul Razak Shaari 305 Dong Mingsheng 327 Abdul Wajid 60 Doraisamy Ponnusamy 229 Ahmad Anas Nagoor Gunny 73 Aisah Mohamed 38 E Ali Hoseinzadeh 69 Ebrahim Rahimi 162,171 Ali Rasaei 246,250 Effat Basiryan 48 Esfandiyar Sharifi 48 Alireza Jalalizand 77,92 Alireza sarkaki 48 F Amar Mohammadi Kaftarkari 189 Feng-Yi Shen 107 Aminah Abdullah 224 Ferda Mavituna 125 Amjed Al 317 Fereshteh Alian 171 Anirudh Kumar 176 Forogh Mortazaeinezahad 208 Apisda Ittitanakam 276 Foroogh Alian 171 Archana Singh Sikarwar 130 Fridelina Sjahrir 21 Ashwani Mittal 26 G Attila Sztrik 97 Gholamreza Ghalamkari 167 Avinash Marwal 240 Azadeh Karimy 92 H Azadeh Zahmatkesh 250 H. Dayanidhi Singh 198 Hafizah Mohd Johar 305 B Hamid Reza Rahmani 250 B. Nor Hidayah 296 Han-Yan Wang 310 Badredin Ebrahim 250 Haq Nawaz 255 Sayed-Tabatabaei Harsh Vardhan Batra 130 Barmak Jafari Haghighi 1 Hasan Mommtaz 162 Beáta Babka 97 Ho-Hsien Chen 107 Behrouz Alizadeh Behbahani 185 Ho-Hsien Chen 310 C Hong Sik Kong 219 Chao-Chin Chung 107,310 Hosein Navid 180 Chemah Tamby Chik 224 I Chen Xiaohong 327 Ijaz Rasool 317 Chen-Hsing Yu 107 Irfan A. Ghazi 176 Chularat Krongtaew 276 Ismail Yusoff 60 Claire Ciafré 261

J D J.I.Sultan 255 D.K. Choudhary 240

333 Jailani Salihon 281 Mohd. Jamil Maah 60 Jessica Wiludjaja 291 Mokhtar Ghobadi 246,272 József Prokisch 97 Mokhtar Mokhtari 48 Mozhgan Ghobadi Pour 16 K Muhammad Afzal 317 Ka Lung Chong 135 Muhammad Aqeel Ashraf 60 Kamiyar Abdi-niya 246 Muhammad Farooq Iqbal 327 Kamran Safavi 208,286 Muhammad Syarhabil 73,140,305 Kanlayanee Meesap 54 Ahmad Karamat Mahmood 60 Kun Woo Lee 219 N N. E. Islam 6 M N. G. Ahmad Anas 296 M. Salehifar 300 N. Rajmuhon Singh 198 M. Sharif 255 N. Robbarth Singh 198 M.Aasif Shahzad 255 N.A.Tauqir 255 M.H.R.O. Abdullah 43 Nadzarah A.Wahab 113 M.I.Rajoka 255 Nallusamy Sivakumar 102 M.Nisa 255 Nasir Landy 167 M.Sarwar 255 Nithya Ranganathan 12 Maegala Nallapan Maniyam 21 Noor hasyierah Mohd Salleh 140 Mahta Mirzaei 267 Nor Fashihah Mohd Noor 305 Majid Toghiani 82,167 Noriham Abdullah 224 Malik Muhammad Hashim 327 Norlida Buniyamin 33,38 Marcella 291 Matlob Ahmad 317 P P.E. Ch’ng 43 Mehdi Toghyani 77,82 Pasika 125 Mehdi Vadi 69 Chongcharoenthaweesuk Pawinee Chaiprasert 54 Mehrdad Modaresi 16,77,92,167 Péter Eszenyi 97 Minu Marry John 176 Pezhman Allahmoradi 272 Mir Zahoor Gul 176 Phumin Kirawanich 6 Mohamad Fahrurrazi Prasanthrajan Mohan 229 73 Tompang Prute Satusap 6 Mohamad Faiz Foong 113 Abdullah Q Mohamed Zulkali Mohamed Qurban Ali Panhwar 145 140 Daud Mohammad Ali Edriss 250 R Mohammad B. Habibi Najafi 323 R.K. Gaur 240 Mohammad javad Asgari 208,286 Radziah Othman 145 Mohammad-Eghbal Ghobadi 246 Ragunathan Ramachandran 12 Mohd Nasir Taib 38 Rajat Bindal 26 Mohd Razi Ismail 145 Rajesh Dabur 26

334 Ratanaporn Leesing 87 T.H. Lim 43 Reza Fellegari 180 Tiek Ying Lau 135 Rohit Kumar 119 Tilahun Seyoum Workneh 150 Ros Shilawani S. Abdul Tzou-Chi Huang 107,310 38 Kadir U S Uun Yanuhar 213 S. Anil Singh 198 S. Hafiza 296 V Saber Khederzadeh 189 V.K. Gupta 240 Safdar Hussain 317 Vijaya Raghavan 150 Sahrim Lias 38 Visith Chavasit 6 Sanjay R Dhakate 119 Sariah Meon 145 W W. Klomklieng 234 Sayed Ali Tabeidian 77,82,92 Waikhom Bimolata 176 Shahram Nanekarani 189 Wan Aida Wan Mustapha 224 Shahrbanu Taherabadi 272 Wan Fen Joveen-Neoh 135 Shakila Banu 102 Waranuch Tanubumrungsuk 276 Shayesteh Taherabadi 272 Y Shiva Amirkaveei 185 Y. Gariepy 150 Siamak Boudaghpour 193 Yuan Zhong 261 Sima Hajian 162 Somkiat seilsuth 219 Z Somkiet Techkarnjanaruk 54 Zaharah Abdul Rahman 145 Somyaparna Das 240 Zahra Ghalamkari 167 SRI ANDAYANI 203 Zainon Mohd Noor 113 Sriyana Abdullah 305 Zainuddin Mohamad 33 Subhash Chand 119 Zeynab Yarmahmodi 1 Sujata Sinha 119 Zhang Jiangdong 125 Supaporn Kookkhunthod 87 Zodie Mohamed Hanafiah 38 Susan Soka 291

Zunairah Hj Murat 33,38 T

335