The Future of Poultry: How Technologies are Solving the "Male Day-Old Chick" Dilemma

Introduction to the In-Ovo Sexing Project

Introduction: Ethical In-Ovo Sexing

In the modern poultry industry, the traditional practice of culling day-old male chicks has become a major ethical and environmental burden. European countries, such as Germany, have already begun prohibiting this practice, pushing the industry toward in-ovo sexing—determining the sex before hatching.

As highlighted in NHK and Nikkei articles, identifying the sex at the egg stage not only improves animal welfare by preventing pain perception (which starts after 7-12) but also optimizes production by reducing the time of stay in the incubator.

The Core Technology: Non-destructive Optical Analysis

The whole flow of the Non-destructive optical analysis follows: Generated by NotebookLM

There are many kinds of optical techniques for In-ovo sexing systems.

  • Spectroscopy
  • Hyperspectral Imaging (HSI)
  • Blood Vessel Morphology
  • Eggshell Shape/Color
  • AI Image Recognition
  • NMR Imaging
  • MRI Analysis

The system utilizes advanced computer vision and deep learning to analyze the internal state of the egg without causing any damage.

  • Early Detection: The analysis is performed on the 3rd day of incubation, significantly reducing resource waste.
  • High Precision: The AI model achieves a discrimination accuracy of up to 97%
  • Zero Damage: Using safe, non-invasive light irradiation, the system evaluates the internal biological characteristics without puncturing the shell, ensuring that the developmental process of the embryo remains completely uncompromised.

Project Approach: Adaptive Signal Processing

To handle the highly variable optical properties of eggshells and the subtle biological differences between male and female embryos at just 3 days of incubation, the system leverages adaptive signal processing. This involves filtering out optical noise caused by variations in eggshell thickness and pigmentation, isolating the most critical features indicative of the embryo’s sex. These refined signals are then fed into robust deep learning classifiers, ensuring consistent accuracy regardless of individual egg differences.

Academic Context: The Future of In-Ovo Sexing

A recent review by M. Corion et al. (2023) identifies Visible-Near-Infrared (VIS-NIR) and machine vision as promising non-destructive techniques for early sex determination. Our project aligns closely with these academic trends, demonstrating that integrating sophisticated AI with optimized optical sensing can overcome traditional bottlenecks in commercial hatchery settings, such as processing speed, equipment cost, and discrimination accuracy. By pushing the boundaries of non-destructive testing, this technology paves the way for a more sustainable and ethically responsible poultry industry.

  • AI Identifies Chicken Embryo Gender with 97% Accuracy to Cut Costs: Hitachi Affiliate and Partners Developed New Technology Link pdf
  • Joint Development of Technology by HSC, NARO, and Kyushu Institute of Technology (Kyutech) for Nondestructive Pre-hatching Sex Determination for Eggs on the 3 Day of Incubation Link
  • 雌雄判定システム及び雌雄判定方法 (Sex Identification service provision system and sex identification service provision method)
    Japan Patent Application No. 2025-154965

Disclaimer

This post is based on publicly available information reported by NHK and Nikkei, and academic trends cited from M. Corion et al. (2023). Specific proprietary model architectures and internal datasets are omitted to comply with the Non-Disclosure Agreement (NDA).

References