TY - JOUR
T1 - An overview of recent advancements in hyperspectral imaging in the egg and hatchery industry
AU - Ahmed, Md Wadud
AU - Khaliduzzaman, Alin
AU - Emmert, Jason Lee
AU - Kamruzzaman, Mohammed
N1 - Publisher Copyright:
© 2024 The Author(s)
PY - 2025/3
Y1 - 2025/3
N2 - Conventional egg quality analysis and compliance monitoring methods have inherent limitations, necessitating non-destructive techniques in the modern egg industry. Hyperspectral imaging (HSI) has emerged as a fast, accurate, and non-destructive tool for quality assessment, effectively determining egg's internal and external properties. Following the fundamentals of HSI and image analysis, this review consolidates and discusses recent applications of HSI technology for table and hatching egg analysis, addressing its limitations and potential challenges. Current research demonstrates HSI's efficacy in rapidly and accurately determining parameters such as freshness, shell integrity, defects, chemical composition, and detection of fake eggs. Despite its promising performance, the widespread industrial application of HSI would encounter multiple challenges due to the inherent properties of the samples (e.g., complex shape, light diffusivity, light and heat sensitivity) and current technological limitations. The existing research is insufficient for early predicting certain critical parameters such as fertility, egg sex, and embryonic mortality in high-throughput screening. However, current research underscores HSI's enormous potential, highlighting that advanced machine learning combined with HSI technology can revolutionize conventional egg and hatchery operations, enhancing automation, economic sustainability, and global animal welfare. This review can guide researchers and policymakers in understanding the contemporary challenges of HSI technology, developing innovative solutions, improving regulatory frameworks, and fostering advancements to maximize the benefits of this cutting-edge green technology.
AB - Conventional egg quality analysis and compliance monitoring methods have inherent limitations, necessitating non-destructive techniques in the modern egg industry. Hyperspectral imaging (HSI) has emerged as a fast, accurate, and non-destructive tool for quality assessment, effectively determining egg's internal and external properties. Following the fundamentals of HSI and image analysis, this review consolidates and discusses recent applications of HSI technology for table and hatching egg analysis, addressing its limitations and potential challenges. Current research demonstrates HSI's efficacy in rapidly and accurately determining parameters such as freshness, shell integrity, defects, chemical composition, and detection of fake eggs. Despite its promising performance, the widespread industrial application of HSI would encounter multiple challenges due to the inherent properties of the samples (e.g., complex shape, light diffusivity, light and heat sensitivity) and current technological limitations. The existing research is insufficient for early predicting certain critical parameters such as fertility, egg sex, and embryonic mortality in high-throughput screening. However, current research underscores HSI's enormous potential, highlighting that advanced machine learning combined with HSI technology can revolutionize conventional egg and hatchery operations, enhancing automation, economic sustainability, and global animal welfare. This review can guide researchers and policymakers in understanding the contemporary challenges of HSI technology, developing innovative solutions, improving regulatory frameworks, and fostering advancements to maximize the benefits of this cutting-edge green technology.
KW - Digital twin
KW - Egg industry
KW - Hatchery operations
KW - Hyperspectral imaging
KW - Non-destructive analysis
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U2 - 10.1016/j.compag.2024.109847
DO - 10.1016/j.compag.2024.109847
M3 - Review article
AN - SCOPUS:85212539230
SN - 0168-1699
VL - 230
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
M1 - 109847
ER -