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首页> 外文期刊>Journal of food engineering >Weight loss of frozen bread dough under isothermal and fluctuating temperature storage conditions
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Weight loss of frozen bread dough under isothermal and fluctuating temperature storage conditions

机译:等温和温度波动条件下冷冻面包面团的失重

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Evaporative weight loss from food leads to both loss of saleable weight and quality deterioration so it need to be minimized. The effect of isothermal and fluctuating conditions on frozen dough weight loss was measured and compared with kinetic, physical and artificial neural network (ANN) models. Frozen dough samples were regularly weighed during storage for up to 112 days in loose-fitting plastic bags. The storage temperatures were in the range of -8 to -25 °C with fluctuations of ±0.1 °C (isothermal), ±1, ±3 or +5 °C about the mean. For each combination of temperature and fluctuation amplitude, the rate of dough weight loss was constant. The rate of weight loss at constant temperature was nearly proportional to water vapour pressure consistent with standard theories for evaporative weight loss from packaged foods but was also accurately fitted by Arrhenius kinetics. Weight loss increased with amplitude of temperature fluctuations. The increase could not be fully explained by either the physic model based on water vapour pressure differences or the kinetic model alone. An ANN model with six neurons in the input layer, six neurons in hidden layers and one neuron in the output layer, achieved a good fit between experimental and predicted data for all trials. However, the ANN model may not be accurate for product, packaging and storage systems different to that studied.
机译:食物中蒸发掉的重量损失会导致可售重量损失和质量下降,因此需要将其降至最低。测量了等温和波动条件对冷冻面团重量损失的影响,并将其与动力学,物理和人工神经网络(ANN)模型进行了比较。在松散的塑料袋中存放多达112天的冷冻面团样品时要定期称重。储存温度在-8至-25°C的范围内,平均温度波动范围为±0.1°C(等温),±1,±3或+5°C。对于温度和波动幅度的每种组合,面团的失重速率是恒定的。恒温下的重量损失率几乎与水蒸气压力成正比,这与包装食品中蒸发性重量损失的标准理论相一致,但也可以通过Arrhenius动力学精确拟合。重量损失随温度波动幅度的增加而增加。无论是基于水蒸气压差的物理模型还是仅基于动力学模型,都无法完全解释这种增加。在输入层中有六个神经元,隐藏层中有六个神经元,输出层中有一个神经元的ANN模型在所有试验的实验数据和预测数据之间都达到了良好的拟合度。但是,对于不同于所研究的产品,包装和存储系统,ANN模型可能并不准确。

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