Freshness Detection and Classification of Chicken Eggs using Spectroscopy

Abstract

The poultry industry plays a pivotal role in India's economy, with particular emphasis on egg production. India ranks as the world's third-largest producer of chicken eggs. Eggs are a delicate component of the human diet, and their quality can undergo substantial changes during storage. This has implications for egg quality and the classification of chicken eggs, both of which are critical factors affecting the poultry sector. Globally, numerous chicken breeds are being developed, necessitating the classification of eggs based on breed due to varying atmospheric conditions required for their storage. However, in India, there is a lack of technical methods for classifying eggs from different chicken breeds. The primary challenges faced by the poultry industry in India revolve around maintaining egg freshness and accurately classifying eggs by breed. While developed countries employ grading systems for eggs, this practice is less common in developing nations like India. To address these challenges, this study aims to propose a model that utilizes spectroscopy as a non-destructive method for assessing egg quality and freshness. The model seeks to establish a link between spectral data, collected using a handheld SCiO NIR spectrometer with wavelengths ranging from 740nm to 1070nm at a spectral resolution of 1 nm, and established destructive methods, particularly Haugh Units, to determine egg freshness based on storage duration.