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

Md Wadud Ahmed, Alin Khaliduzzaman, Jason Lee Emmert, Mohammed Kamruzzaman

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number109847
JournalComputers and Electronics in Agriculture
Volume230
DOIs
StatePublished - Mar 2025

Keywords

  • Digital twin
  • Egg industry
  • Hatchery operations
  • Hyperspectral imaging
  • Non-destructive analysis

ASJC Scopus subject areas

  • Forestry
  • Agronomy and Crop Science
  • Computer Science Applications
  • Horticulture

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