Detection on the Fertility of Hatching Eggs Based on Heart Rate Threshold
The fertility detection and classification of hatching eggs is extremely significant in the production of Avian influenza vaccine. A novel method by setting rational heart rate threshold to solve the problem that it’s difficult to separate the dead eggs from the normal eggs during the incubation process is proposed in this paper, which is critical to ensure the quality of vaccine. The object of our research is the 9-day-later hatching eggs, which are divided into two types, namely fertile eggs and dead eggs. Firstly, we collect heartbeat signal of the 9-day-later hatching eggs by the method of PhotoPlethysmoGraphy(PPG). Secondly, in order to reduce noise interference, we design a butterworth high-pass filter to filter the collected signal and remove baseline drift. Finally, two classification algorithms based on heart rate threshold and frequency spectral amplitude threshold are designed to detect the fertility of hatching eggs from time domain and frequency domain respectively. The experimental results demonstrate that the method we proposed successfully achieved the goal of high detection accuracy of hatching eggs, which also indicate that our approach is feasible for classification of hatching eggs.
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