Non-Destructive Evaluation of Physicochemical Properties for Egg Freshness: A Review

Tae-Gyun Rho and Byoung-Kwan Cho ()
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Tae-Gyun Rho: Department of Biosystem Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Republic of Korea
Byoung-Kwan Cho: Department of Biosystem Machinery Engineering, College of Agricultural and Life Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Republic of Korea

Agriculture, 2024, vol. 14, issue 11, 1-19

Abstract: Egg freshness is a critical factor that influences the egg’s nutritional value, safety, and overall quality; consequently, it is a priority for both producers and consumers. This review examines the factors that affect egg freshness, and it evaluates both traditional and modern methods for assessing egg freshness. Traditional techniques, such as the Haugh unit test and candling, have long been utilized; however, they have limitations, which are primarily due to their destructive nature. The review also highlights advanced non-destructive methods, including Vis-NIR spectroscopy, ultrasonic testing, machine vision, thermal imaging, hyperspectral imaging, Raman spectroscopy, and NMR/MRI technologies. These techniques offer rapid and accurate assessments while preserving the integrity of the eggs. Despite the current challenges related to calibration and implementation, integrating artificial intelligence (AI) and machine learning with these innovative technologies presents a promising avenue for the improvement of freshness evaluation. This development could revolutionize quality control processes in the egg industry, ensuring consistently high-quality eggs for consumers.

Keywords: egg; freshness; quality; physicochemical; spectroscopic techniques (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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