RESUMO
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 0.9-1.7â¯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.
