Duck eggs are a good source of essential nutrients for the human body. However, transportation, processing, and handling can easily cause cracks in the eggshells. These cracks can lead to microbial contamination, reducing the shelf life and compromising food safety. In this study, a method for the nondestructive testing of cracks in duck eggshells was developed. First, the acoustic emission signals of intact and cracked eggshells were measured, and the most significant frequency features were selected to establish a calibration curve for cracked eggshells. Logistic regression using the frequency features was then adopted to predict intact and cracked eggshells. Then, we establish a set of optimal regression models and used independent samples for verification. The overall accuracy rates of the calibration and prediction models using five frequencies of bandwidth (1500, 5000, 6000, 8500, and 10,000 Hz) were 89.7% and 87.6%, respectively. Sound measurement enables a simple and quantitative method for duck egg crack detection and classification. This nondestructive and cost-effective method can be used for duck egg quality screening and can be integrated into duck egg processing machinery.
Keywords: calibration curve; cracked eggshell; duck eggs; nondestructive testing; sound detection.