An overview of recent advancements in hyperspectral imaging in the egg and hatchery industry

• Hyperspectral imaging (HSI) for table and hatching eggs analysis are reviewed. • Fundamentals of HSI and system customization for the egg industry are presented. • Multivariate techniques, software, and GUIs were discussed. • Challenges, potentiality, and future trends were critically analyzed. 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.

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Publication Details

Journal
Computers and Electronics in Agriculture
Published
2024-12-18
DOI
https://doi.org/10.1016/j.compag.2024.109847
Citations
26
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
6.13

Funders

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article

An overview of recent advancements in hyperspectral imaging in the egg and hatchery industry

J.L. Emmert, Alin Khaliduzzaman, Md Wadud Ahmed, Mohammed Kamruzzaman
26 citations
Computers and Electronics in Agriculture
Spectroscopy and Chemometric Analyses
6.13
article

An overview of recent advancements in hyperspectral imaging in the egg and hatchery industry

J.L. Emmert, Alin Khaliduzzaman, Md Wadud Ahmed, Mohammed Kamruzzaman
article en
26 citations

Abstract

• Hyperspectral imaging (HSI) for table and hatching eggs analysis are reviewed. • Fundamentals of HSI and system customization for the egg industry are presented. • Multivariate techniques, software, and GUIs were discussed. • Challenges, potentiality, and future trends were critically analyzed. 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.

Computers and Electronics in AgricultureVol. 230
University of Illinois Urbana-Champaign (US)
National Institute of Food and Agriculture
Openalex Percentile: Top 2%
Spectroscopy and Chemometric Analyses
6.13
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