Improved Hairline Crack Detector and Poor Shell-Quality Eggs

Lawrence, Kurt C.; Jones, D. R.; Yoon, Seongheum; Heitschmidt, Gerald W.; Anderson, K. E.

doi:10.13031/2013.41275

Cited by 1 publication

(1 citation statement)

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“…Studies to develop abnormal egg detection technology using a modified pressure technology [9][10][11][12] and hyperspectral imaging technology [13][14][15][16] have also been conducted in addition to the currently commercialized technology. All techniques for detecting defective eggs are non-destructive and require a defective egg identification algorithm.…”

Section: Introductionmentioning

confidence: 99%

Current advances in detection of abnormal egg: a review

So¹,

Joe²,

Hwang³

et al. 2022

J Anim Sci Technol

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Internal and external defects of eggs should be detected to prevent cross-contamination of intact eggs by abnormal eggs during storage. Emerging detection technologies for abnormal eggs were introduced as an alternative to human inspection. The advanced technologies could rapidly detect abnormal eggs. Abnormal egg detection technologies using acoustic response, machine vision, and spectroscopy have been commercialized in the poultry industry. Non-destructive egg quality assessment methods meanwhile could preserve the value of eggs and improve detection efficiency. In order to improve detection efficiency, it is essential to select a proper algorithm for classifying the types of abnormal eggs. This review deals with the performance of the detection technologies for various types of abnormal eggs in recently published resources. In addition, the discriminant methods and detection algorithms of abnormal eggs reported in the published literature were investigated. Although the majority of the studies were conducted on a laboratory scale, the developed detection technologies for internal and external defects in eggs were technically feasible to obtain the excellent detection accuracy. To apply the developed detection technologies to the poultry industry, it is necessary to achieve the detection rates required from the industry.

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