Non-Invasive Gender Classification of Chicken Eggs Based on Image Analysis

Pavedan K; Kaveyaa shree S K; Tamil selvi M; Prathysha shri J

doi:10.71097/IJSAT.v16.i3.6839

Non-Invasive Gender Classification of Chicken Eggs Based on Image Analysis

Author(s)	Prof. Dr. Pavedan K, Ms. Kaveyaa shree S K, Ms. Tamil selvi M, Ms. Prathysha shri J
Country	India
Abstract	Hatched male chicks are usually killed because layer hens are only used by females. About 7 billion chicks are killed each year shortly after hatching. This situation is wrong and has a big economic cost. You can determine a chick's sex either before or after it hatches. While it's better to make this determination before hatching, the success rate is not very high. The Shape Index (SI) describes the shape of an egg by comparing its short diameter to its long diameter. Although SI varies by egg type, chick sex and SI are significantly related (r = 0.78). So, even though our classification accuracy was not as good as with ducks, we were still able to estimate chick gender based on SI. We measured seven additional parameters and included them in our analysis: mass, ovality, volume, eccentricity, short axis, and long axis. When we applied model predictions from previous studies to the probability of female chick hatching equation, we correctly classified 71% of the estimates. We estimated that around 80% of our predictions in this study were accurate. In this case, we could potentially save 5.65 billion chicks from being killed. In a similar way, many eggs were not wasted. In this study, we used the form index of the eggs to predict the gender of the chicks with a pre-trained TensorFlow model.
Keywords	Morphological Features, Non-Invasive Classification, Shape Index
Published In	Volume 16, Issue 3, July-September 2025
Published On	2025-07-10
DOI	https://doi.org/10.71097/IJSAT.v16.i3.6839
Short DOI	https://doi.org/g9sx6j

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Non-Invasive Gender Classification of Chicken Eggs Based on Image Analysis

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