Evaluation of Process Conditions for Ultrasonic Spray Freeze Drying of Transglutaminase

U ovom je istraživanju komercijalni enzim transglutaminaza sušen pomoću ultrazvučnog raspršivanja i zamrzavanja, te je optimiran učinak procesnih parametara radi postizanja maksimalne aktivnosti transglutaminaze pri završetku procesa. U skladu s tim odabrani su parametri koji utječu na aktivnost enzima, kao što su: frekvencija mlaznica (48 i 120 kHz), protok (2, 5 i 8 mL/min) i temperatura ploče sekundarnog sušenja (25, 35 i 45 °C). Također, ispitan je utjecaj različitih pH-vrijednosti (pH=2,0 i 9,0) i visoke temperature (80 °C) na enzimsku aktivnost, fizikalna svojstva i morfologiju čestica transglutaminaze. Rezultati pokazuju da je aktivnost enzima bila očuvana usprkos utjecaju ultrazvučnog sušenja raspršivanjem i zamrzavanjem. Upotreba ultrazvuka povećala je aktivnost enzima. Optimiranjem metode prema principu poželjnosti određene su optimalne vrijednosti parametara: protok od 3,10 mL/min, temperatura ploče 45 °C i frekvencija mlaznica 120 kHz. Predviđeni omjer aktivnosti enzima nakon postupka sušenja i početne aktivnosti enzima u otopini bio je 1,17; a eksperimentalno utvrđeni omjer 1,14±0,02. Nadalje, enzim je nakon 8 sati sušenja imao mali udjel vlage (2,92-4,36 %). Ispitivanje morfološke strukture čestica enzima nakon ultrazvučnog sušenja raspršivanjem i zamrzavanjem pri optimalnim uvjetima otkrilo je da su čestice bile sferične s porama na površini. Također, prema Carrovom indeksu protok dobivenog praha bio je dobar pri većini uvjeta.In this study, a commercial transglutaminase enzyme was dried using an ultrasonic spray freeze drying method and the effects of the process conditions were optimized to maximize the final transglutaminase activity. Accordingly, process parameters affecting enzyme activity were selected, such as nozzle frequency (48 and 120 kHz), flow rate (2, 5 and 8 mL/min) and plate temperature for secondary drying (25, 35 and 45 °C). Moreover, the effects of different pH values (pH=2.0 and 9.0) and high temperature (80 °C) on enzyme activity, physical properties and particle morphology of transglutaminase were discussed. According to the results, transglutaminase preserved its activity despite ultrasonic spray freeze drying. Sonication enhanced the enzyme activity. Using the desirability function method, the optimum process conditions were determined to be flow rate 3.10 mL/min, plate temperature 45 °C and nozzle frequency 120 kHz. The predicted activity ratio was 1.17, and experimentally obtained ratio was 1.14±0.02. Furthermore, enzyme produced by ultrasonic spray freeze drying had low moisture values (2.92-4.36 %) at 8 h of drying. When the morphological structure of the transglutaminase particles produced by ultrasonic spray freeze drying under the optimum conditions was examined, spherical particles with pores on their surfaces were observed. In addition, flow properties of the transglutaminase powders were considered as fair under most conditions according to the Carr index

Evaluation of Process Conditions for Ultrasonic Spray-Freeze Drying of Transglutaminase

In this study, a commercial transglutaminase enzyme was dried using an ultrasonic spray freeze drying method and the effects of the process conditions were optimized to maximize the final transglutaminase activity. Accordingly, process parameters affecting enzyme activity were selected, such as nozzle frequency (48 and 120 kHz), flow rate (2, 5 and 8 mL/min) and plate temperature for secondary drying (25, 35 and 45 °C). Moreover, the effects of different pH values (pH=2.0 and 9.0) and high temperature (80 °C) on enzyme activity, physical properties and particle morphology of transglutaminase were discussed. According to the results, transglutaminase preserved its activity despite ultrasonic spray freeze drying. Sonication enhanced the enzyme activity. Using the desirability function method, the optimum process conditions were determined to be flow rate 3.10 mL/min, plate temperature 45 °C and nozzle frequency 120 kHz. The predicted activity ratio was 1.17, and experimentally obtained ratio was 1.14±0.02. Furthermore, enzyme produced by ultrasonic spray freeze drying had low moisture values (2.92-4.36 %) at 8 h of drying. When the morphological structure of the transglutaminase particles produced by ultrasonic spray freeze drying under the optimum conditions was examined, spherical particles with pores on their surfaces were observed. In addition, flow properties of the transglutaminase powders were considered as fair under most conditions according to the Carr index.</jats:p

Prediction of baking quality using machine learning based intelligent models

A domestic cookie baking process was modeled using nonlinear forward and inverse models to predict surface temperature, moisture content and browning index that describe the baking quality of the end product. The baking processes were carried out at different oven temperatures (160, 180, 200 °C) and the changes in surface temperature, moisture content and browning index were determined to construct the identification models namely nonlinear polynomial models (PLN) and nonlinear artificial-neural network (ANN) model. The parameters of the artificial models were optimized using least-squares estimation and Levenberg-Marquardt optimization, respectively. The predicted baking characteristics in both forward and inverse phases were in good agreement with the measured ones even for the browning index which was difficult to model because of the its nonminimum-phase dynamics. The application results indicated that the developed intelligient models were very accurate, having low root mean-squared errors, the ANN model approximated the desired values better than the PLN models for all the state variables. Thus, the designed ANN models are applicable for the automatized industrial and domestic oven designs of the future

Modelling of heat and mass transfer during cooking in steam-assisted hybrid oven

WOS: 000374357400007Semitendinosus muscle in a cylindrical shape was cooked in a domestic steam-assisted hybrid oven, and the simultaneous heat and mass transfer during the cooking process was modelled using commercial software COMSOL Multiphysics (version 3.5a). The temperature and moisture profiles of the product were predicted as functions of both position and time, and the predicted results were compared with the experimental ones. The surface convective heat transfer coefficient was determined experimentally using the lumped capacity method, and the surface convective mass transfer coefficient was calculated by simulation of the developed model at different temperatures. Also, the thermal conductivity of muscles was determined as a function of the temperature and moisture content by the line heat source method. The convective heat transfer coefficients were found to be in the range of 17.31-18.35 W/m(2)K, and the calculated surface convective mass transfer coefficients were in the range of 1.7 x 10(-7) -2.2 x 10(-7) m/s at 180, 210 and 240 degrees C cooking temperatures. The predicted results for the steam-assisted hybrid cooking process agreed well with the experimental temperature and moisture profiles, and the developed model is considered to be suitable for predicting cooking times in a steam-assisted hybrid oven. (C) 2016 Elsevier Ltd. All rights reserved.Scientific and Technical Research Council of TurkeyTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [TOVAG 109 O 087]This research was supported by the Scientific and Technical Research Council of Turkey (Project No. TOVAG 109 O 087). Also, equipment and material support of the companies of ARCELIK A.S. was acknowledged

Optimization of Extraction Conditions of Bioactive Compounds by Ultrasonic-Assisted Extraction from Artichoke Wastes

In this study, bioactive compounds were extracted by ultrasonic-assisted extraction and classical extraction processes using distilled water as solvent from artichoke leaves which are considered as agricultural wastes. Antioxidant capacity, total phenolic and total flavonoid content values of the obtained bioactive extracts were determined, and extraction yields and times were evaluated to compare the extraction processes. Also, the optimum extraction conditions of ultrasonic-assisted extraction (extraction time and ultrasonic power) which provide the highest extraction yield were determined using D-optimal design by ‘desirability’ function approach. According to the results, bioactive extracts having high antioxidant capacity were obtained at shorter times and higher extraction yields were achieved by ultrasonic-assisted extraction process than classical extraction. The highest extraction yield was estimated as 98.46% with an application of 20.05 minutes of extraction time and 65.02% of ultrasonic amplitude for the ultrasonic-assisted extraction process.</jats:p