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Development of a Novel Acoustic Spectroscopy Method for Detection of Eggshell Cracks.

István KertészViktória Zsom-MuhaRebeka AndrásFerenc HorváthCsaba NémethJózsef Felföldi
Published in: Molecules (Basel, Switzerland) (2021)
Non-destructive testing (NDT) for eggshell faults is highly important for the egg industry, as cracked eggs account for around 3% of total production. The most commonly used method at present, candling, is labor intensive, while computer vision systems are expensive and complicated. In this paper, we present a simple, yet efficient, novel method for eggshell crack detection by acoustic spectroscopy. Altogether, 693 sound recordings were evaluated by different classification methods. The results show a cross-validated 2.1% total classification error, with only 0.87% false positive rate, which is the crucial metric for fresh eggs. Adapting the developed method to an industrial setting may lead to a reliable, fast and cost-effective detection method.
Keyphrases
  • deep learning
  • machine learning
  • loop mediated isothermal amplification
  • high resolution
  • single molecule
  • real time pcr
  • mass spectrometry