Modeling
M. Almaei; S. M. Nassiri; M. A. Nematollahi; D. Zare; M. Khorram
Abstract
IntroductionDrying shrimp is one of the storage methods that, while increasing the shelf life, leads to the production of a versatile product with various uses, from consumption as snacks to use as one of the main components of foods. Drying is preferred over other preservation methods because it offers ...
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IntroductionDrying shrimp is one of the storage methods that, while increasing the shelf life, leads to the production of a versatile product with various uses, from consumption as snacks to use as one of the main components of foods. Drying is preferred over other preservation methods because it offers numerous advantages, including extended shelf life, enhanced microbial stability, convenient consumption, reduced transportation costs, increased value, and product diversity.To accurately model these processes and thus obtain information on factors such as shelf life and energy consumption, it is necessary to determine the product’s initial and final temperatures, its geometry and dimensions, and its thermo-physical characteristics. Simulation of different drying processes requires accurate estimation of the effective moisture diffusion coefficient, which is highly dependent on temperature and humidity. Its dependence can be shown by an equation with an Arrhenius structure as an empirical function of humidity and temperature, or by considering the activation energy.It is necessary to have sufficient knowledge about heat and mass transfer characteristics, such as diffusion or penetration coefficient and the heat transfer coefficient to estimate the final temperature and drying time. This study investigated the drying process of peeled farmed shrimp (Litopenaeus vannamei) using a convective hot air dryer. Various parameters such as shrinkage and the effective moisture diffusion coefficient were examined.Materials and MethodsA drying device was built to conduct experimental studies on drying shrimp samples. The experiments were conducted on sliced shrimp meat samples at temperatures of 40, 50, and 60 degrees Celsius, with a constant air velocity of 1.5 m/s. The experimental drying models were based on diffusion theory. In these models, it is assumed that the resistance to moisture diffusion occurs from the outer layer of the food. In most cases, Fick's second law was used to describe the phenomenon of moisture penetration.The study used the standard method of immersion in toluene to measure volume changes in the samples. During the drying process, the volume of the samples was measured at 45-minute intervals, and their volume changes were calculated. To measure the moisture content of the samples, each test started by recording the initial weight of the samples using a digital scale with an accuracy of ±0.001 g. During the drying process, the samples were weighed each time their volume was measured.Shrinkage during the drying process is commonly modeled by finding a relationship between shrinkage and moisture, using linear and non-linear models. In most cases, effective permeability is defined as a function of humidity and temperature. For this purpose, curve-fitting methods were employed to analyze the data collected from experimental tests. The appropriate function was extracted by incorporating the Arrhenius equation, which is applicable to most food items.Results and DiscussionBased on the results of statistical indices, the linear model was the best model for depicting the relationship between shrinkage changes versus moisture ratio changes among the various experimental models evaluated for shrinkage and drying kinetics. Similarly, the Weibull distribution demonstrated superior performance in expressing variations in moisture ratio over time. A moisture dependent experimental model was used to express the variations in the apparent density of shrimp, resulting in a computed range of 1017-1117 kg m-3. Furthermore, an Arrhenius equation was derived to express the effect of moisture content and temperature on the effective diffusion coefficient of shrimp. According to the results, the effective diffusion coefficient of shrimp exhibited variations ranging from 0.08 ×10-9 m2 s-1 to 7.39×10-9 m2 s-1. When deriving the effective diffusion coefficient, the impact of the number of terms in Fick's second law on the variation of the moisture ratio was studied. The findings revealed that increasing the number of terms beyond 100 did not significantly affect the model’s outputs.ConclusionThe linear model had the highest coefficient of determination (R2) among the evaluated shrinkage models, as well as the lowest root mean square error and sum of square error (SSE). This makes it the most optimal model for interpreting shrinkage at the tested temperature levels. The Weibull distribution experimental model proved to be the most suitable for expressing changes in the moisture ratio of shrimp meat slices over time within the evaluated temperature range. The Arrhenius model accurately predicts changes in the effective diffusion coefficient of shrimp slices with respect to temperature and moisture content within the tested temperature range.
Modeling
S. Rezaei; N. Behroozi-Khazaei; H. Darvishi
Abstract
IntroductionMicrowave drying compared to conventional hot air drying has many benefits to apply in food drying processes such as volumetric heating, high thermal efficiency, shorter drying time and improved product quality. In conventional microwave drying method, a fixed microwave power was used during ...
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IntroductionMicrowave drying compared to conventional hot air drying has many benefits to apply in food drying processes such as volumetric heating, high thermal efficiency, shorter drying time and improved product quality. In conventional microwave drying method, a fixed microwave power was used during the drying process. However, the water of the product evaporated and mass of product decreased over the time that resulted in microwave power density (MPD) increasing during the drying process. Increasing the power density, especially at the end of the process, sharply increased the product temperature. High temperature of products led to the deterioration of the product quality. Most research used variable microwave power program for preventing the risk of overheating and charring of product. The evaporation of the water causes the shrinkage of product. Therefore, many studies have used machine vision for measuring the shrinkage and this technology has been used in modeling and predicting the MC.Materials and MethodsThe fresh potato samples (Solanum tuberosum cv. Santana) with 83% (w.b.) of initial MC were sliced into the chips of 5mm thickness. The developed drying systems consisted of microwave oven, lighting unit and imaging unit, temperature sensor, microwave power adjusting unit and a data acquisition unit (DAQ). A LabVIEW (V17.6, 2017) program was developed to integrate all measurements and adjusting the microwave power during the drying process. In this study, two sets of experiment with different aims have done. The first set of experiments was used for calculating the shrinkage by developed image processing algorithm and MC by offline mass measurement and then data sets were used to investigate the artificial neural networks (ANNs). The second set was used for evaluating the reliability of investigating models. The experiments, in the first set, were done with 8, 4 and 2.67 W g-1. In the variable mode, the power varied in two/three steps with respect to the MC of samples during the drying process. Second set of experiments was done in two variable and constant power modes with 5 and 3 W g-1. An image processing algorithm was developed to measure the shrinkage of potato slice during the drying process. In this study the feed forward ANN with back propagation algorithm was used. Two structures of ANN were used for modeling of MC. In the first model time and power density and the second model shrinkage and power density were used as input. Also moisture ratio was used as an output parameter in two models.Results and DiscussionThe obtained results indicated that for the first model the ANN with 2-3-1 structure had better results than others structures. This structure had 0.0713, 0.0337 and 0.0640 of RMSE and 0.9764, 0.9973 and 0.9800 of R for train, validation and test, respectively. For the second model, the 2-2-2-1 structure of ANN with 0.0780, 0.0816 and 0.0908 of RMSE and 0.9598, 0.9799 and 0.9746 of R for train, validation and test, respectively had better results than other structures. The evaluation of these models with a second data set showed that the second model with shrinkage and power density as input with 0.067 of RMSE and 0.994 of R had better results than the first model with 0.173 of RMSE and 0.961 of R. These consequences expressed that the second model had higher reliability for prediction of MC based on shrinkage and power density during drying process.ConclusionIn this study, a microwave dryer was developed with a real-time image recording system and a microwave power level program during the drying process. Two ANN models were used for modeling of drying kinetics of the potato slices. Also image processing algorithm was investigated by measuring the shrinkage of potato slice during the drying process. The outcomes revealed that shrinkage as input in the ANN had great effect on MC prediction during the drying process.
H. Sadrnia; H. Monfared; M. Khojastehpour
Abstract
Drying is one of the oldest methods to preserve agricultural products and hence expanding the food market. By drying, the agricultural products can be stored and transferred to the market throughout the year. One of the most important and nutritious vegetables is turnip which can be used by drying in ...
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Drying is one of the oldest methods to preserve agricultural products and hence expanding the food market. By drying, the agricultural products can be stored and transferred to the market throughout the year. One of the most important and nutritious vegetables is turnip which can be used by drying in out of season. In this research, the hot air and vacuum drying methods of turnip were compared. The effect of independent factors including temperature and vacuum, on dependent factors such as the shrinkage, rehydration and rate of electric energy consumption on final products of turnip were investigated. A randomized completely design for hot air dryer and a factorial experiment based on completely randomized design for drying under vacuum condition were used. Results showed that the temperature and vacuum have affected the shrinkage, rehydration and electricity consumption. Shrinkage parameter is more depend on the final humidity of product and the energy consumption of the devices depends on time. The best quality of dried turnip was achieved from hot air drying device with final humidity of 14±1%, shrinkage of 39.98%, rehydration of 4.45 and consumed electricity of 32.36 kWh kg-1 of DM in 60˚C. For the vacuum drying device the best quality of produce achieved with shrinkage of 38.12%, rehydration of 4.87 and consumed electricity of 30.58 kWh kg-1 of DM in vacuum condition of 10 kPa in 60˚C. Comparison of results showed that the vacuum dryer is more appropriate than the hot air dryers for drying turnip with better quality and lower power consumption.
M. Rasouli; S. S. Seiiedlou Heris
Abstract
Garlic (Allium sativumL.) is one of the most important Allium spice. From an economic point of view, the dried garlic slices are valuable products. In this research, garlic slices as a thin layer were dried in a laboratory scale hot-air dryer, under air flow of 1.5 m/s, air temperatures of 50, 60 and ...
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Garlic (Allium sativumL.) is one of the most important Allium spice. From an economic point of view, the dried garlic slices are valuable products. In this research, garlic slices as a thin layer were dried in a laboratory scale hot-air dryer, under air flow of 1.5 m/s, air temperatures of 50, 60 and 70˚C and slice thicknesses of 2, 3 and 4 mm. The mean values of shrinkage of garlic slices obtained 69.8%. In addition, the effects of the drying variables on the shrinkage of dried garlic were evaluated. The ANOVA results indicated that the air temperature and slice thickness had no significant effect on final shrinkage of dried garlic slices. In order to derive and select the appropriate shrinkage model, four mathematical models were fitted to the experimental data. According to the statistical criteria (R2, SSE & RMSE) the best model was found to describe the shrinkage behavior of garlic slice.