Microwave drying of germinated brown rice: Correlation of drying characteristics with the final quality

Shen, Liuyang; Gao, Ming; Zhu, Yong; Liu, Chenghai; Wang, Lei; Kamruzzaman, Md.; Chai, Linna; Zheng, Xianzhe

doi:10.1016/j.ifset.2021.102673

Cited by 50 publications

(37 citation statements)

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“…Olatunde et al [15] analyzed the effects of microwave drying on rice moisture removal, milled rice characteristics, and energy requirements, and concluded that the microwave energy should be 450-600 kJ/kg in order to maintain the quality of Processes 2021, 9, 1511 2 of 12 rice. Shen et al [16] investigated the effects of microwave drying on visual color and gamma-aminobutyric acid (GABA) of germinated brown rice (GBR) and found that a microwave intensity of 3-4 W/g is suitable. Yuan et al [17] researched the influence of different microwave conditions on water migration, quality, lipase activity and the internal structure of rice, and determined that the optimum microwave treatment conditions are a microwave intensity of 1.29 W/g and a drying temperature of 60 • C. In order to reduce the drying temperature and better maintain the nutritional components of grains, modified microwave drying methods, such as microwave vacuum drying, are often used in grain drying [5,18].…”

Section: Introductionmentioning

confidence: 99%

Microwave Drying Characteristics and Drying Quality Analysis of Corn in China

Liu

et al. 2021

Processes

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To identify the microwave drying characteristics of corn, microwave drying tests were conducted on corn. By taking the moisture content, drying rate, and drying temperature as indices, this research revealed the effects of different microwave powers and loads on the microwave drying characteristics of corn. Moreover, energy consumption and quality of dried corn were analysed under different drying conditions. The results demonstrate that microwave drying has significant energy-saving effects. The energy consumption by microwave drying is less than 0.3 times that used by electrothermal drying under the same load. Both microwave power and load exert significant influences on drying characteristics. Higher microwave power results in a greater average drying rate, wherein shorter periods of time are required to reach the maximum drying rate and higher temperatures of the corn. However, the load shows the opposite tendency. The smaller the load, the higher the temperature of the corn in the early stage of drying. However, as drying continues, the temperature curve changes significantly, and the temperature rises with the increase in load in the later stage of drying. In consideration of energy consumption and dried quality, the load of corn should be increased as appropriate, and the microwave intensity should be limited to no higher than 0.7 W/g in the experiment.

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Section: Introductionmentioning

confidence: 99%

Microwave Drying Characteristics and Drying Quality Analysis of Corn in China

Liu

et al. 2021

Processes

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“…Thus, the moisture ratio (MR) of sample during microwave puffing was calculated by using Equation (1):

MR goodbreak= \frac{M_{t} - M_{e}}{M_{0} - M_{e}}

where

M_{t}

is the moisture content of sample at drying time of t (g water/g dry matter);

M_{0}

is the initial moisture content of sample (g water/g dry matter);

M_{e}

is the equilibrium moisture content (g water/g dry matter), which may be considered as zero. Therefore, Equation (1) is simplified as Equation (2) (Shen, Gao, Zhu, Liu, & Zheng, 2021).

MR goodbreak= \frac{M_{t}}{M_{0}}

…”

Section: Methodsmentioning

confidence: 99%

Formation of texture quality of raspberry snack under microwave puffing

Feng

Zhao

et al. 2021

Journal of Texture Studies

Self Cite

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Raspberry snack, as a novel berry product, has rich favor and high crisp taste, where controllable texture quality is conducive to the palatability of the snack. Determinative factors of microwave puffing in microwave intensity and durationand key property of material in Young's modulus were introduced to investigate the formation of texture quality of berry snack under microwave puffing. The results indicate that the microwave intensity has negative correlation with Young's modulus of raspberry chips, which causes the more porosity inside under microwave puffing. Reasonable Young's modulus of raspberry chips enhances the interior porosity and exterior expansion volume of raspberry snack due to the water vapor wrapped other than escaped. The greater microwave intensity results in the higher volume expansion of raspberry chips, in which the great volume expansion from porous pores structure confers moderate hardness. In microwave puffing, the formation of hardness and crispness of raspberry snack depend on microwave puffing parameters, leading to high temperature and great dehydration rate in quick puffing duration, in addition to Young's modulus of raspberry chips, where high dehydration rate accelerates water removal inside raspberry chips to form a harder texture with decreasing springiness, whereas low dehydration rate leads to the gentle change of springiness. Raspberry snack with uniform internal pores and regular shape forming desirable texture may be achieved under the microwave intensity of 7.5 W/g and the puffing duration of 6 min. This study indicates that high-quality raspberry snack may be achieved via controlling heating rate in microwave puffing.

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“…Rice is one of the oldest and most important grains on earth. Due to the increase in population and the limitations of increasing the area under rice cultivation, the most important goal in the industry is the processing of this strategic plant and the production of the highest quality crop [1]. Rice is a very valuable food and plays an important role in human nutrition.…”

Section: Introductionmentioning

confidence: 99%

Application of Artificial Neural Networks, Support Vector, Adaptive Neuro-Fuzzy Inference Systems for the Moisture Ratio of Parboiled Hulls

Sharabiani

Kaveh²,

Taghinezhad

et al. 2022

Applied Sciences

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Drying as an effective method for preservation of crop products is affected by various conditions and to obtain optimum drying conditions it is needed to be evaluated using modeling techniques. In this study, an adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), and support vector regression (SVR) was used for modeling the infrared-hot air (IR-HA) drying kinetics of parboiled hull. The ANFIS, ANN, and SVR were fed with 3 inputs of drying time (0–80 min), drying temperature (40, 50, and 60 °C), and two levels of IR power (0.32 and 0.49 W/cm2) for the prediction of moisture ratio (MR). After applying different models, several performance prediction indices, i.e., correlation coefficient (R2), mean square error index (MSE), and mean absolute error (MAE) were examined to select the best prediction and evaluation model. The results disclosed that higher inlet air temperature and IR power reduced the drying time. MSE values for the ANN, ANFIS tests, and SVR training were 0.0059, 0.0036, and 0.0004, respectively. These results indicate the high-performance capacity of machine learning methods and artificial intelligence to predict the MR in the drying process. According to the results obtained from the comparison of the three models, the SVR method showed better performance than the ANN and ANFIS methods due to its higher R2 and lower MSE.

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Microwave drying of germinated brown rice: Correlation of drying characteristics with the final quality

Cited by 50 publications

References 50 publications

Microwave Drying Characteristics and Drying Quality Analysis of Corn in China

Microwave Drying Characteristics and Drying Quality Analysis of Corn in China

Formation of texture quality of raspberry snack under microwave puffing

Application of Artificial Neural Networks, Support Vector, Adaptive Neuro-Fuzzy Inference Systems for the Moisture Ratio of Parboiled Hulls

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