Abstract
We proposed here a non-destructive technology for pre-sorting eggs into subclasses characterized by a specifical acceptable shelf life and quality requirements. Egg characteristics were identified suiting a predictive model for controlling storage periods. Accordingly, the relationships of egg parameters were assessed, with weight loss (ΔW) during storage being the best indicator of changes in egg contents variables. Using changes in ΔW, we established three indicators with the maximum effect on fast egg drying and shrinkage. These included egg weight (W), egg volume-to-surface area ratio, and air cell diameter. The relationship formulae were derived to estimate the ΔW value accurately. This approach enables to judge regarding the potential of each particular egg subclass for its acceptable weight shrinkage and assign an optimal storage period for it. The proposed non-invasive analytical method can be implemented in industrial conditions for both table and hatching eggs with the available set of automated technological equipment.
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