Foam-Mat Drying Process of Duck Egg White

2020 ◽  
Vol 25 ◽  
pp. 54-82
Author(s):  
E. Rodrigues Mangueira ◽  
J. de Assis Cavalcante ◽  
N. Alves Costa ◽  
A.G. Barbosa de Lima
Keyword(s):  
Computational Simulation ◽  
Storage Conditions ◽  
Egg White ◽  
Coefficient Of Determination ◽  
Process Time ◽  
Drying Time ◽  
Drying Temperature ◽  
Stirring Rate ◽  
Duck Egg ◽  
High Level

The foam-mat dryingprocessof egg white, developed in the food industry, promotes a porous product, brittle and easy to grind. The powderedegg white has a good rehydration properties, safer consumption and storage conditions than fresh product, keeping the high level of proteins and vitamins contained in the egg. In this way, the objective of this work is to study, through numerical computational simulation, the physical aspects of the duck egg white foam-matdrying process. For this, the foam was characterized by its density, percentage of expansion, air over run, stability and moisture. Temperature (50, 60 and 70°C), stirring rate (levels 6, 7 and 8) and stirring time (4, 5 and 6 minutes) are taken as input conditions and the product final moisture and drying time are the output variables. Drying was performed based on the complete factorial 23 + 3 central point experimental design in this procedure. It has been observed that the time and stirring rate significantly influence the product final moisture and that the drying temperature is predominant for the total process time. From the foam moisturedata, adjustments of empirical mathematical models were made; evidencing that theModifiedPage and the Page models provided the best results, with a standard deviation lower than 0.01 and the coefficient of determination above 0.99. For this analysis, the case where the drying temperature, time and the stirring rate were, respectively, 70 °C, 6 minutes and 8 level, presented the best results.

scholarly journals Production of protein powder from salted duck eggs white

2019 ◽  
Vol 02 ◽  
pp. 119-130
Author(s):  
Trinh A. Nguyen
Keyword(s):  
Design Method ◽  
Egg White ◽  
Regression Equation ◽  
Process Conditions ◽  
Drying Time ◽  
Process Yield ◽  
Surface Design ◽  
Duck Egg ◽  
Salted Duck Eggs

The objective of the research was to determine process conditions to produce protein powder from salted duck egg whites based on the two main steps including precipitation of the protein from egg white and drying the protein. Optimization for process parameters of protein's precipitation and drying were carried out by Response Surface Design method with the results obtained from the experiment. Basing on the determination of the limits of studied factors, defining the regression and choosing the optimal parameters for precipitation and drying processes. The result of optimal protein precipitation was the ratio of water/salted duck egg white: 3.5/1, the temperature of 80oC and precipitation time of 60 minutes with the process yield was 9.63% and the salt separation was 19.61%. The result of optimal drying process was the drying temperature at 75oC, material density: 0.35 g/cm2 (wind speed of 0.64 m/s and drying time of 4 h) with the product solubility of 11.05%, the water content of 8.19% and aw of 0,476. Verifying the defined regression equation and experiment showed the different level is less than 5%, the defined regression equation is valid and has the potential to apply in production.

scholarly journals Surface Analysis, Mechanical and Corrosion Behavior of Welded Steel in 1M HCl Corrosive Media with Epoxy/Alumina Coating

2021 ◽  
Vol 12 (3) ◽  
pp. 3559-3571
Keyword(s):  
Energy Consumption ◽  
Thermal Sensitivity ◽  
Coefficient Of Determination ◽  
Alumina Coating ◽  
Suitable Model ◽  
Corrosive Media ◽  
Drying Time ◽  
Drying Temperature ◽  
Color Characteristics ◽  
Drying Conditions

Asparagus roots were dried in four selected driers vacuum, fluidized bed, tray, and solar dryer at temperatures starting from 40 to 70 °C. The drying kinetics of asparagus roots was studied with the analysis of the influence of all stated drying conditions on the drying rate, dehydration ratio, rehydration characteristic, color characteristics, and energy consumption. With an increase in the temperature required for drying asparagus, there is an increasing trend of dehydration ratio (DR) and decreasing trend of drying time. The rehydration characteristics are found to be increases with a decrease in drying temperature from 70-60 °C but decrease with a further decrease in drying temperature from 60-40 °C. The energy consumption based on the drying conditions showed great thermal sensitivity and was found higher for low-temperature drying. The results of color characteristics (Chroma, hue angle, and ΔE) showed that the cream color of roots was relatively unaffected by drying. However, the brightness of roots was observed to be increased. Eleven thin-layered drying mathematical models were applied to experimental data of different drying conditions, and the model best describing its behavior was selected based on the coefficient of determination (R2), sum square error (SSE), and root mean square error (RMSE). All selected models give good fitting results (R2 > 0.96) and found the cubic model as the most suitable model for all treatments (R2 > 0.99).

scholarly journals Modelling the Thin-Layer Drying Kinetics of Untreated and Blanch-Osmotic Pre-treated Tomato Slices

2016 ◽  
Vol 4 (10) ◽  
pp. 850 ◽  
Author(s):  
Samuel Enahoro Agarry
Keyword(s):  
Linear Regression Analysis ◽  
Drying Kinetics ◽  
Coefficient Of Determination ◽  
Drying Rate ◽  
Drying Time ◽  
Drying Temperature ◽  
Hot Air ◽  
Thin Layer Drying ◽  
Pre Treatment ◽  
Air Dryer

The objective of this study was to investigate the effect of pre-treatment and drying temperature on the drying kinetics and nutritional quality of tomato (Lycopersicon esculantum L.) under hot air drying. Tomato samples were blanched at 80oC and osmotically dehydrated using 20% w/w sodium chloride solutions at 30oC for 20 min. The blanch-osmotic pre-treated and untreated tomato slices were dried at temperature of 40, 50, 60, 70 and 80oC, respectively in a hot air-dryer. The results showed that blanch-osmotic pre-treatment offered a higher drying rate and lower or faster drying time than untreated condition. The tomato drying regime was characteristically in the constant and falling rate period. The tomato drying rate curve showed characteristics of porous hygroscopic solids. The optimum drying temperature for tomato was found to be 60oC. Four semi-empirical drying models of Newton, Page, Henderson and Pabis, and Logarithmic were fitted to the drying data using non-linear regression analysis. The most appropriate model was selected using the coefficient of determination (R2) and root mean square error (RMSE). The Page model has shown a better fit to the drying kinetics data of tomato in comparison with other tested models. Transport of moisture during drying was described by Fick’s diffusion model application and the effective moisture diffusivity (Deff) thus estimated. The Deff at 60oC was 4.43 × 10-11m2/s and 6.33 × 10-11m2/s for blanch-osmotic pre-treated and untreated tomato slices, respectively.

scholarly journals Effect of Wood Vinegar Substitutes on Acetic Acid for Coagulating Natural Para Rubber Sheets during the Drying Process

2021 ◽  
Vol 11 (17) ◽  
pp. 7891
Author(s):  
Wachara Kalasee ◽  
Panya Dangwilailux
Keyword(s):  
Acetic Acid ◽  
Coconut Shell ◽  
Coefficient Of Determination ◽  
Drying Process ◽  
Yellowness Index ◽  
Drying Time ◽  
Drying Temperature ◽  
Wood Vinegar ◽  
Rubber Wood ◽  
Zero Degree

The coagulating properties of wood vinegar from para rubber wood, bamboo, and coconut shell used as a substitute for acetic acid in the production process of natural rubber (NR) sheets were investigated and considered. For the dirt and volatile content, the tensile strength at break, the percentage of elongation at break, and the 300% modulus, the results showed that the types of wood vinegar coagulants were not significantly different from acetic acid. However, the Mooney viscosity and plasticity retention index (PRI) properties were significantly different from those of acetic acid. The NR sheet temperature increased rapidly during the first hour after the drying process started due to heat transfer from the hot air. Afterward, the temperature of the NR sheet samples began to stabilize. When the drying process started, the drying temperature was increased, so the trend was reducing the drying time. For the yellowness index (YI) value, the increase in the YI value was related to the type of coagulating material, the increase in the airspeed, and the drying temperature. The dried sheet samples using para rubber wood vinegar as the coagulating material had a color value at the same level as acetic acid and the referent. However, the bamboo and coconut shell wood vinegars were at a lower level. In comparing the YI value data between the experimental results and prediction values, the second-degree model had a better fit in prediction than the zero-degree and first-degree models. This result was confirmed by the higher mean of the coefficient of determination. The dried sheet product coagulated by using wood vinegar had fungus growth prior to supplying it to the customer.

Pengaruh Lama Pengasinan Terhadap Kadar Protein Putih Telur Itik

2014 ◽  
Vol 1 (1) ◽  
pp. 36 ◽  
Author(s):  
Siti Fatimah ◽  
Muji Rahayu ◽  
Siti Aminah
Keyword(s):  
Protein Level ◽  
Egg White ◽  
Special Treatment ◽  
Egg White Protein ◽  
Protein Levels ◽  
Duck Egg ◽  
Egg Period ◽  
Graph Presentation ◽  
And Control ◽  
The Impact

Background : Egg  is one of the animal protein source, which has delicious taste, easy to digest and highly nutritious. Besides its affordable price, its supply availability is unquestionable as well. However, due to its short storability, it requires special treatment, such as preserving, to store it for long period. One way to preserve the egg is by pickling egg, which generally requires seven to ten days of marinating. During the process of marinating, there will be a visual change of egg white and yolk. Their structures  will be more solid (the occurrence of thickening process) because salinization will lead to protein denaturalization. Consequently, it has an influence as well towards the content of egg white protein of duck egg. This study is aimed to explore the impact of various time of pickling egg towards egg white protein of duck egg. Method  : The study where takes place in a laboratories, is a true experimental study for the reason that the researcher must provide intervention, hence all of potentially confounding variables are manageable. Samples that had been used in this study are duck eggs which were bought from North Brebes. This study is expected to generate data from four various time of pickling egg and control (no treatment). Since there are four samples, accordingly the number of data resulted are twenty. The resulted data will be descriptively presented in table, graph, presentation, and narration. Result  : Protein level examination within duck white egg shows changes  in protein levels that occurs in every variation of pickling egg time, where the average results of the assay of duck egg white protein is 14.94% without treatment (control), in five days of pickling time is 13.68%, in seven days of pickling time is 13.29%, in nine days of pickling time is 12.87% and eleven days of pickling time is 12.78%. Conclusion  : There is a significant impact among the period of pickling time to the protein level degradation of duck white egg. Keywords : Duck egg, period of pickling time, level protein of duck white egg.

Decolorization of Reactive Black B from wastewater by electro-coagulation: optimization using multivariate RSM and ANN

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Kajal Gautam ◽  
Rishi K. Verma ◽  
Suantak Kamsonlian ◽  
Sushil Kumar
Keyword(s):  
Current Density ◽  
Operating Cost ◽  
Quadratic Model ◽  
Coefficient Of Determination ◽  
Process Time ◽  
Mathematical Tool ◽  
Electrode Gap ◽  
Artificial Neural Network Ann ◽  
Electro Coagulation ◽  
Optimized Conditions

AbstractThe present study is aimed to model and optimize the electrocoagulation (EC) process with five important parameters for the decolorization of Reactive Black B (RBB) from simulated wastewater. A multivariate approach, response surface methodology (RSM) together with central composite design (CCD) is used to optimize process parameters such as pH (5–9), electrode gap (0.5–2.5 cm), current density (2.08–10.41 mA/cm2), process time (10–30 min), and initial dye concentration (100–500 mg/l). The predicted percentage decolorization of dye is obtained as 97.21% at optimized conditions: pH (6.8), gapping (1.3 cm), current density (8.32 mA/cm2), time (23 min), and initial dye concentration (200 mg/L), which is very close to experimental percent decolorization (98.41%). The statistical analysis of variance (ANOVA) is performed to evaluate the quadratic model (RSM), and shows good fit of experimental data with coefficient of determination R2 >0.93. An Artificial Neural Network (ANN) is also used to predict the percentage decolorization and gives overall 94.96% which shows performance accuracy between the predicted and actual value of decolorization. The additional considerations of operating cost and current efficiency are also taken care to show the efficacy of EC process with mathematical tool. The sludge characteristics are determined by FE-SEM/EDX.

scholarly journals Unconventional effects of long-term storage of microwave-modified chicken egg white lysozyme preparations

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Grzegorz Leśnierowski ◽  
Tianyu Yang ◽  
Renata Cegielska-Radziejewska
Keyword(s):  
Microwave Radiation ◽  
Egg White ◽  
Process Time ◽  
High Quality ◽  
Chicken Egg ◽  
Egg White Lysozyme ◽  
Physicochemical Changes ◽  
Long Term Storage ◽  
Term Storage

AbstractThermal modification is an effective method that induces significant expansion of the antimicrobial properties and other valuable properties of chicken egg white lysozyme. In our latest research, a new innovative method of enzyme modification was developed, in which microwave radiation was used as an energy source to process liquid lysozyme concentrate (LLC). After modification, high-quality preparations were obtained. However, long-term storage in a concentrated form initiated various processes that caused darkening over time and could also lead to other significant changes to their structure and, consequently, to their functional properties. This necessitated multidirectional research to explain this phenomenon. This paper presents the results of research aimed at assessing the physicochemical changes in the properties of microwave-modified lysozyme in the form of a liquid concentrate after long-term storage under refrigeration conditions. The assessment also considered the conditions under the acidity of the modifying medium and the duration of the microwave modification. The analysis showed that the values of the basic parameters determining the quality and usefulness of the modified enzyme significantly improved during long-term storage of the preparations. The greatest changes were observed in the preparations modified for the longest time and in the most acidic environment (process time 260 s, pH 2.0), the number of oligomers under these conditions increased by 18% after 12 months of holding, and the surface hydrophobicity increased by as much as 31%. In addition, microbiological tests showed that the preparations of microwave-modified lysozyme had an effect on gram-positive bacteria as well as on gram-negative, and this effect was significantly enhanced after 12 months. The results confirm that LLC modification with microwave radiation is a highly efficient method to prepare high-quality and high utility potential lysozyme. Notably, an interesting and important phenomenon was the observation of the unconventional behaviour of the preparations during their long-term storage, which increased their utility potential significantly.

scholarly journals Evaluation of the Consistency of Simultaneously Acquired Sentinel-2 and Landsat 8 Imagery on Plastic Covered Greenhouses

2020 ◽  
Vol 12 (12) ◽  
pp. 2015 ◽  
Author(s):  
Manuel Ángel Aguilar ◽  
Rafael Jiménez-Lao ◽  
Abderrahim Nemmaoui ◽  
Fernando José Aguilar ◽  
Dilek Koc-San ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Remote Sensing Techniques ◽  
Image Pairs ◽  
Study Sites ◽  
High Level ◽  
Sentinel 2

Remote sensing techniques based on medium resolution satellite imagery are being widely applied for mapping plastic covered greenhouses (PCG). This article aims at testing the spectral consistency of surface reflectance values of Sentinel-2 MSI (S2 L2A) and Landsat 8 OLI (L8 L2 and the pansharpened and atmospherically corrected product from L1T product; L8 PANSH) data in PCG areas located in Spain, Morocco, Italy and Turkey. The six corresponding bands of S2 and L8, together with the normalized difference vegetation index (NDVI), were generated through an OBIA approach for each PCG study site. The coefficient of determination (r2) and the root mean square error (RMSE) were computed in sixteen cloud-free simultaneously acquired image pairs from the four study sites to evaluate the coherence between the two sensors. It was found that the S2 and L8 correlation (r2 > 0.840, RMSE < 9.917%) was quite good in most bands and NDVI. However, the correlation of the two sensors fluctuated between study sites, showing occasional sun glint effects on PCG roofs related to the sensor orbit and sun position. Moreover, higher surface reflectance discrepancies between L8 L2 and L8 PANSH data, mainly in the visible bands, were always observed in areas with high-level aerosol values derived from the aerosol quality band included in the L8 L2 product (SR aerosol). In this way, the consistency between L8 PANSH and S2 L2A was improved mainly in high-level aerosol areas according to the SR aerosol band.

Prediction Models for Truck Accidents at Freeway Ramps in Washington State Using Regression and Artificial Intelligence Techniques

1998 ◽  
Vol 1635 (1) ◽  
pp. 30-36 ◽  
Author(s):  
Wael H. Awad ◽  
Bruce N. Janson
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Linear Regression ◽  
Prediction Models ◽  
Washington State ◽  
Training Data ◽  
Coefficient Of Determination ◽  
Training Process ◽  
Truck Accidents ◽  
High Level

Three different modeling approaches were applied to explain truck accidents at interchanges in Washington State during a 27-month period. Three models were developed for each ramp type including linear regression, neural networks, and a hybrid system using fuzzy logic and neural networks. The study showed that linear regression was able to predict accident frequencies that fell within one standard deviation from the overall mean of the dependent variable. However, the coefficient of determination was very low in all cases. The other two artificial intelligence (AI) approaches showed a high level of performance in identifying different patterns of accidents in the training data and presented a better fit when compared to the regression model. However, the ability of these AI models to predict test data that were not included in the training process showed unsatisfactory results.

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