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Microwave spectroscopy based on the waveguide technique for the nondestructive freshness evaluation of egg

机译:基于波导技术的微波光谱法对鸡蛋的无损新鲜度评估

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A rectangular waveguide equipped with a network analyzer was used to assess the quality indices of shell egg. The scattering parameters of the eggs were acquired in the range of 0.9-1.7 GHz and they were then used to calculate microwave spectra of the samples. PLS and ANN regression methods were implemented to predict the egg quality indices and SIMCA and ANN classification methods were applied to classify the eggs based on their storage time. The best predictive models, however, obtained from ANN analysis where the yolk coefficient, air cell height, thick albumen height, Haugh unit, and albumen pH could be predicted with the residual predictive deviation (RPD) values of 3.500, 3.000, 2.411, 2.033, and 1.829, respectively. To classify the eggs according to their storage time, both SIMCA and ANN analyses resulted in the total accuracy of 100% when return loss spectra were used as the input.
机译:使用配有网络分析仪的矩形波导来评估带壳蛋的质量指标。在0.9-1.7 GHz范围内获取卵的散射参数,然后将其用于计算样品的微波光谱。运用PLS和ANN回归方法来预测鸡蛋的质量指标,并应用SIMCA和ANN分类方法根据存储时间对鸡蛋进行分类。然而,最好的预测模型是通过ANN分析获得的,其中蛋黄系数,气孔高度,厚蛋白高度,霍夫单位和蛋白pH值可以通过残留预测偏差(RPD)值3.500、3.000、2.411、2.033进行预测,和1.829。为了根据鸡蛋的存储时间对鸡蛋进行分类,当使用回波损耗谱作为输入时,SIMCA和ANN分析得出的总准确度为100%。

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