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Biological drug substance (DS) is often frozen to enhance storage stability, prolong shelf life, and increase flexibility during manufacturing. However, the freezing and thawing (F/T) of bulk DS at the manufacturing scale can impact product quality as a result of various critical conditions, including cryo-concentration during freezing, which are influenced, among other things, by product-independent process parameters (e.g., container type, fill level, F/T equipment, and protocols). In this article, we report the optimization of two major methodologies to study product-independent process parameters in DS bottles at the manufacturing scale, namely the recording of temperature profiles and liquid sampling after thawing to quantify the concentration gradients in the solution. We report experimentally justified measuring positions for temperature recordings, especially for the selection of the last point to freeze position, and highlight the implementation of camera-assisted inspection to determine the last point to thaw and the actual thawing time. In particular, we provide, for the first time, a detailed description of the technical implementation of these two measuring set-ups. Based on the reported case studies, we recommend choosing relevant measuring positions as a result of initial equipment characterization, resulting in a resource-conscious study set-up. [ABSTRACT FROM AUTHOR]

This study focuses on analyzing the texture properties and bioelectrical impedance characteristics of frozen chicken breasts during low‐temperature thawing, meanwhile, we also compared the differences in physiochemical properties. Frozen chicken breasts were thawed at 4 ± 2°C for 2, 4, 6, 8, and 10 h separately, then the physiochemical properties (color, pH, water‐holding capacity, water distribution), the texture properties (easy‐to‐cut level), and the bioelectrical impedance were determined and analyzed. The easy‐to‐cut level of the samples was evaluated by the sensory panel and two indexes, one is Warner‐Bratzler shear force measured by texture analysis machine, and the other is cutting speed value calculated by the consumer‐oriented cutting behavior analysis using frame‐by‐frame video recording analysis method. These two methods were used to characterize the easy‐to‐cut level of the frozen samples during thawing from the industrial processing and home cooking standpoint. Strong correlations were observed between the easy‐to‐cut level and the bioelectrical impedance of the frozen chicken breasts during thawing. The impedance magnitude at 100 kHz showed a high correlation coefficient (R2 =.9417) with Warner‐Bratzler shear force, and the impedance magnitude at 50 Hz showed a high correlation coefficient (R2 =.8658) with cutting speed. Our results indicated the acceptability of using bioelectrical impedance to evaluate the easy‐to‐cut thawing endpoint for both industry processing and home cooking. [ABSTRACT FROM AUTHOR]

Partial air-drying, instant controlled pressure drop, freezing, and thawing operations were combined to minimize the texture loss of frozen/thawed apple fruits. Fresh apple samples (700% db) and samples previously dehydrated until different water contents [200, 100, and 30% dry basis (db)] and DIC treated at constant conditions (0.2 MPa, 25 s) were completely frozen at − 30 °C and at two different freezing velocities and then thawed at 4 °C. The effects of sample water content and freezing velocity on freezing/thawing durations and apple texture were assessed. Lower sample water content implied higher freezing and thawing rates, and lower freezing and thawing times. Indeed, freezing times are 108 min and 30 min for samples with water contents of 700% and 100% db, respectively. Thawing time was also reduced from 588 to 42 min for conventionally frozen and DIC-dehydrofrozen samples (100% db). During thawing, the amount of water exudate was approximately 12% (g/100 g residual water) for conventionally frozen apples at the lower freezing velocity. Whereas, it is lowered to 1.6% for 100% db DIC-dehydrofrozen samples. Moreover, the impact of freezing velocity on water exudate was significant and very important only for conventionally frozen apples (with high water content) and remains insignificant for DIC-dehydrofrozen samples with different water content levels. Thawed apple firmness was as higher as the water content was lower, without any significant impact of freezing velocity. Dehydrofreezing assisted by instant controlled pressure drop exhibited significant effects on reducing thawing duration and enhancing frozen apple fruit texture. [ABSTRACT FROM AUTHOR]

Background: Fresh frozen plasma (FFP) should be thawed before transfusing to the patient. Prolonged or uncontrolled thawing can denature plasma proteins. The potential risk of contamination by wet thawing had always been a point of concern. Aims: Here, we compared and evaluated the effect of thawing on clotting factor activities by two different methods (wet and dry) and other factors such as risk of bacterial contamination, throughput, turnaround time, and efficacy of thawing. Subjects and Methods: All FFPs were prepared from Group O donors and stored at −40°C. Twenty-one FFPs were thawed in Plasmatherm II at 45°C for 15 min and another 21 were thawed in thawing bath at 37°C for 20–30 min randomly. Analysis of prothrombin time, activated partial thromboplastin time, fibrinogen, and factor VIII was done in ACL TOP 300 (IL) at the time of preparation and immediately after thawing of FFPs. Volume, duration of thawing, ease of use, accessibility, and equipment maintenance were also compared. Results: There was a statistically significant difference in coagulation parameters after thawing in both methods compared to the time of preparation (P < 0.05), but all values were within normal limits. There was no significant difference in coagulation parameters between the two methods (P > 0.05). Mixed bacterial growth was observed from swabs taken from the water bath. Conclusion: Plasmatherm II can be a good alternative to water bath to rapidly thaw FFPs by preserving coagulation factors and eliminating the risk of bacterial contamination.

Determining thawing times of frozen foods is a challenging problem as the thermophysical properties of the product change during thawing. A number of calculation models and solutions have been developed. The proposed solutions range from relatively simple analytical equations based on a number of assumptions to a group of empirical approaches that sometimes require complex calculations. In this paper analytical, empirical and graphical models are presented and critically reviewed. The conditions of solution, limitations and possible applications of the models are discussed. The graphical and semi-graphical models are derived from numerical methods. Using the numerical methods is not always possible as running calculations takes time, whereas the specialized software and equipment are not always cheap. For these reasons, the application of analytical-empirical models is more useful for engineering. It is demonstrated that there is no simple, accurate and feasible analytical method for thawing time prediction. Consequently, simplified methods are needed for thawing time estimation of agricultural and food products. The review reveals the need for further improvement of the existing solutions or development of new ones that will enable accurate determination of thawing time within a wide range of practical conditions of heat transfer during processing.

The present study was designed to determine the best practical method of semen thawing which could be applied to frozen semen of bulls in straw produced by Artificial Insemination Center, Iraq. Frozen semen was thawed at 15°C for 30 sec, 40°C for 10 sec and 50°C for 5 sec. individual motility, live, and dead sperm cells was assessed using light microscope. Results revealed that number, motility, and live of sperm cells, were significantly higher at the 50°C for 5 sec than other thawing temperatures In conclusion, it is recommended to use a temperatures of 50°C for 5 sec and to dissolve the frozen semen because it gave the best quality semen after thawing and easy to utilize in field.

This study focuses on analyzing the texture properties and bioelectrical impedance characteristics of frozen chicken breasts during low-temperature thawing, meanwhile, we also compared the differences in physiochemical properties. Frozen chicken breasts were thawed at 4 ± 2°C for 2, 4, 6, 8, and 10 h separately, then the physiochemical properties (color, pH, water-holding capacity, water distribution), the texture properties (easy-to-cut level), and the bioelectrical impedance were determined and analyzed. The easy-to-cut level of the samples was evaluated by the sensory panel and two indexes, one is Warner-Bratzler shear force measured by texture analysis machine, and the other is cutting speed value calculated by the consumer-oriented cutting behavior analysis using frame-by-frame video recording analysis method. These two methods were used to characterize the easy-to-cut level of the frozen samples during thawing from the industrial processing and home cooking standpoint. Strong correlations were observed between the easy-to-cut level and the bioelectrical impedance of the frozen chicken breasts during thawing. The impedance magnitude at 100 kHz showed a high correlation coefficient (R 2  = .9417) with Warner-Bratzler shear force, and the impedance magnitude at 50 Hz showed a high correlation coefficient (R 2  = .8658) with cutting speed. Our results indicated the acceptability of using bioelectrical impedance to evaluate the easy-to-cut thawing endpoint for both industry processing and home cooking., (© 2023 Wiley Periodicals LLC.)

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Background: Fresh frozen plasma (FFP) should be thawed before transfusing to the patient. Prolonged or uncontrolled thawing can denature plasma proteins. The potential risk of contamination by wet thawing had always been a point of concern. Aims: Here, we compared and evaluated the effect of thawing on clotting factor activities by two different methods (wet and dry) and other factors such as risk of bacterial contamination, throughput, turnaround time, and efficacy of thawing. Subjects and Methods: All FFPs were prepared from Group O donors and stored at −40°C. Twenty-one FFPs were thawed in Plasmatherm II at 45°C for 15 min and another 21 were thawed in thawing bath at 37°C for 20–30 min randomly. Analysis of prothrombin time, activated partial thromboplastin time, fibrinogen, and factor VIII was done in ACL TOP 300 (IL) at the time of preparation and immediately after thawing of FFPs. Volume, duration of thawing, ease of use, accessibility, and equipment maintenance were also compared. Results: There was a statistically significant difference in coagulation parameters after thawing in both methods compared to the time of preparation (P < 0.05), but all values were within normal limits. There was no significant difference in coagulation parameters between the two methods (P > 0.05). Mixed bacterial growth was observed from swabs taken from the water bath. Conclusion: Plasmatherm II can be a good alternative to water bath to rapidly thaw FFPs by preserving coagulation factors and eliminating the risk of bacterial contamination. [ABSTRACT FROM AUTHOR]

Electric energy plays an important role in reducing the thawing time and accelerating the entire thawing process. Corona wind speed was increased by increasing the applied voltage and current, which were 0.87 ± 0.19, 1.22 ± 0.19, 1.49 ± 0.13 m/s under 8, 10, 12 kV with 3, 5, 10 μA; 1.01 ± 0.12, 1.24 ± 0.17, 1.49 ± 0.10 m/s under − 8, − 10, − 12 kV with 5, 9, 14.5 μA. The models T1, T2, and T3 were designed to study the effects of current, corona wind and electric field on thawing, respectively. T1: a thin stainless-steel sheet covered the top of stainless-steel box with 10 g frozen distilled water; T2: a plastic sheet was placed under the stainless-steel box; T3: a plastic sheet covered the top of plastic box. Electric field alone cannot affect thawing time, which could be maximally reduced by 1/2 compared to that of air thawing. Industrial relevance We have studied HVEF thawing for several years because of its many advantages, such as the quick thawing of frozen meat with little energy consumption and good post-thawing quality. The mechanism of HVEF thawing and the reduction of the thawing time, which are important for the industrial application of new technology from principle to design, must be clarified. Meanwhile, this emerging technology will be beneficial for the food-thawing field. [ABSTRACT FROM AUTHOR]

Determining thawing times of frozen foods is a challenging problem as the thermophysical properties of the product change during thawing. A number of calculation models and solutions have been developed. The proposed solutions range from relatively simple analytical equations based on a number of assumptions to a group of empirical approaches that sometimes require complex calculations. In this paper analytical, empirical and graphical models are presented and critically reviewed. The conditions of solution, limitations and possible applications of the models are discussed. The graphical and semi-graphical models are derived from numerical methods. Using the numerical methods is not always possible as running calculations takes time, whereas the specialized soft ware and equipment are not always cheap. For these reasons, the application of analytical-empirical models is more useful for engineering. It is demonstrated that there is no simple, accurate and feasible analytical method for thawing time prediction. Consequently, simplified methods are needed for thawing time estimation of agricultural and food products. The review reveals the need for further improvement of the existing solutions or development of new ones that will enable accurate determination of thawing time within a wide range of practical conditions of heat transfer during processing. [ABSTRACT FROM AUTHOR]

Gıda maddelerinin muhafazası için uygulanan en etkin metotlardan birisi, dondurarak muhafaza etmektir. Dondurma, dondurulmuş ürünün depolanması ve çözülmesi işlemlerinin uygun bir şekilde yapılması durumunda, gıda maddesi orijinal haldeki özelliklerinin hemen hemen tamamını uzun bir süre koruyabilmektedir. Donma ve çözülme zamanlarının bilinmesi, hem dondurulmuş ürünün kalitesi hem de proses verimliliği ve ekonomisi açısından çok önemlidir. Donma ve çözülme zamanlarının hesaplama yöntemi ile belirlenmesi için kullanılacak olan bir metotta; basit çözüm, yüksek doğruluk oranı, az miktarda proses ve fiziksel özellik verilerine ihtiyaç duyması gibi nitelikler aranmaktadır. Ancak, bu özelliklerin tamamının aynı anda tek bir tahmin metodunda bulunması çok zordur. Bu nedenle, çok farklı donma ve çözülme zamanı tahmin metotları geliştirilmiş ve araştırmalar yapılmaktadır.

Gıda maddelerinin muhafazası için uygulanan en etkin metotlardan birisi, dondurarak muhafaza etmektir. Dondurma, dondurulmuş ürünün depolanması ve çözülmesi işlemlerinin uygun bir şekilde yapılması durumunda, gıda maddesi orijinal haldeki özelliklerinin hemen hemen tamamını uzun bir süre koruyabilmektedir. Donma ve çözülme zamanlarının bilinmesi, hem dondurulmuş ürünün kalitesi hem de proses verimliliği ve ekonomisi açısından çok önemlidir. Donma ve çözülme zamanlarının hesaplama yöntemi ile belirlenmesi için kullanılacak olan bir metotta; basit çözüm, yüksek doğruluk oranı, az miktarda proses ve fiziksel özellik verilerine ihtiyaç duyması gibi nitelikler aranmaktadır. Ancak, bu özelliklerin tamamının aynı anda tek bir tahmin metodunda bulunması çok zordur. Bu nedenle, çok farklı donma ve çözülme zamanı tahmin metotları geliştirilmiş ve araştırmalar yapılmaktadır.

Gıda maddelerinin muhafazası için uygulanan en etkin metotlardan birisi, dondurarak muhafaza etmektir. Dondurma, dondurulmuş ürünün depolanması ve çözülmesi işlemlerinin uygun bir şekilde yapılması durumunda, gıda maddesi orijinal haldeki özelliklerinin hemen hemen tamamını uzun bir süre koruyabilmektedir. Donma ve çözülme zamanlarının bilinmesi, hem dondurulmuş ürünün kalitesi hem de proses verimliliği ve ekonomisi açısından çok önemlidir. Donma ve çözülme zamanlarının hesaplama yöntemi ile belirlenmesi için kullanılacak olan bir metotta; basit çözüm, yüksek doğruluk oranı, az miktarda proses ve fiziksel özellik verilerine ihtiyaç duyması gibi nitelikler aranmaktadır. Ancak, bu özelliklerin tamamının aynı anda tek bir tahmin metodunda bulunması çok zordur. Bu nedenle, çok farklı donma ve çözülme zamanı tahmin metotları geliştirilmiş ve araştırmalar yapılmaktadır.

Gıda maddelerinin muhafazası için uygulanan en etkin metotlardan birisi, dondurarak muhafaza etmektir. Dondurma, dondurulmuş ürünün depolanması ve çözülmesi işlemlerinin uygun bir şekilde yapılması durumunda, gıda maddesi orijinal haldeki özelliklerinin hemen hemen tamamını uzun bir süre koruyabilmektedir. Donma ve çözülme zamanlarının bilinmesi, hem dondurulmuş ürünün kalitesi hem de proses verimliliği ve ekonomisi açısından çok önemlidir. Donma ve çözülme zamanlarının hesaplama yöntemi ile belirlenmesi için kullanılacak olan bir metotta; basit çözüm, yüksek doğruluk oranı, az miktarda proses ve fiziksel özellik verilerine ihtiyaç duyması gibi nitelikler aranmaktadır. Ancak, bu özelliklerin tamamının aynı anda tek bir tahmin metodunda bulunması çok zordur. Bu nedenle, çok farklı donma ve çözülme zamanı tahmin metotları geliştirilmiş ve araştırmalar yapılmaktadır.

Fractionated thawing was studied as a method to recover solutes incorporated in the ice obtained in a cryoconcentrator. Thawing times and solute concentration in the ice were determined at several thawing temperatures. Ice sheets used for the thawing studies were obtained by cryoconcentrated solutions of sugars and simulated juice at initial concentrations of 5 to 20 °Brix. The ice sheets produced contained levels of solutes between 1.0 and 9.0 °Brix. Fractionated thawing was performed at temperatures of 20 to 30 °C while maintaining geometrical similarity for the test samples. By fractionated thawing more than 60% of the solutes retained in the ice was recovered in 34%, of the total thawing time. The procedure presented allows the determination of the solute concentration achieved in the various thawing fractions and predicts the thawing time required for a given form factor, melting temperature and the solute mass fraction in the ice. Industrial relevance The freeze concentration is a technology that allows eliminating water from liquid foods at temperatures below the water's freezing point, which allows obtaining products of better quality. Fractionated thawing was studied as a method to recover solutes incorporated in the ice, improving the global efficiency of a freeze concentration process by optimal recovery of the solutes retained in the ice. It also provides estimations of the energy used for thawing. This work continues the research in falling film freeze concentration technology which we have submitted and published in this journal. This work contributes to increase the global process efficiency. [ABSTRACT FROM AUTHOR]

Abstract: In this work a feedforward neural network, trained and validated using experimental values of freezing and thawing times of foods and test substances of different geometries, is developed. A total of 796 experimental times of both processes were collected from reported works. The database used covered a wide range of operative conditions as well as size, shape and type of material. The input layer had seven elements: shape factor, characteristic dimension, Biot number, thermal diffusivity, initial, ambient and final temperatures. The output layer had one element: the process time. The total number of hidden layers and the number of neurons in each hidden layer were chosen by trial and error. For each topology, a simple based genetic algorithm search technique was applied to obtain the initial training parameters of the neural network that improve its generalization capacity. Three particular networks were evaluated: one for freezing times, another one for thawing times, and a third one for both freezing and thawing times. The final topologies has one or two hidden layers with 4 nodes in each one. Our results show that the neural network had an average absolute relative error of less than 10%, suggesting that ANN provide a simple and accurate prediction method for freezing and thawing times, valid for wide ranges of food types, sizes, shapes and working conditions. [Copyright &y& Elsevier]

Thawing is one of the important processes of the food industry. Its speed and conditions can influence the quality and initial concentration of the microbial population in raw materials used for further processing. Experimental prediction of the optimum conditions of the thawing process is very time consuming and expensive. Therefore, a mathematical model of the process can help in the design of efficient thawing apparatus and process conditions. This paper compares experimental data of different thawing procedures with numerically calculated predictions using the software package food product modeller (FPM). The model calculations agree very well with experimental data on three different thawing process arrangements with reasonable accuracy. The verified mathematical model for convective thawing was selected for sensitivity analysis of the process parameters. The time of thawing was calculated as a function of different parameters for three different points in the thawed food piece. Graphs of the relative change of thawing time as a function of the relative change of the process parameters have been constructed. From these graphs one can read that the air temperature, surface heat transfer coefficient (SHTC), thickness of the layer, water content and enthalpy are the parameters with the greatest influence on thawing time. On the other hand the thermal conductivity or initial freezing point does not influence the thawing time as much. [Copyright &y& Elsevier]

The effects of different power (0, 100, 300, and 500 W) ultrasonic-assisted immersion thawing (UT) on the thawing time and muscle quality (thawing/cooking loss, shear force, colour, water distribution and microstructure) of common carp (Cyprinus carpio) were investigated. The results showed that the thawing time decreased gradually with the increase of ultrasonic power, and the thawing time of ultrasonic thawing at 500 W (UT-500) was the shortest among all the thawing methods (P < 0.05). However, the thawing and cooking losses of UT-500 samples were the largest among all thawed samples, while those of UT-300 samples were the smallest (P < 0.05). In addition, the result of fish colour indicated that UT-300 was beneficial for maintaining the colour of fish muscle after thawing. Low field nuclear magnetic resonance analysis showed that UT-300 effectively reduced the fluidity and loss of immobilised and free water. Microstructure analysis showed that the microstructure of UT-300 sample was more complete than that of other thawing treatment samples. Therefore, appropriate ultrasonic power (300 W) during thawing could accelerate the thawing process of frozen common carp, and maintain its muscle quality. • Thawing time decreased with the increase of ultrasonic-assisted thawing (UT) power. • Thawing and cooking losses of 300 W UT (UT-300) samples were the smallest. • UT-300 was beneficial for maintaining the colour of fish muscle after thawing. • UT-300 reduced the fluidity and loss of immobilised and free water of fish muscle. • The microstructure of UT-300 sample was more complete than that of other samples. [ABSTRACT FROM AUTHOR]