부산대학교 도서관

The traditional candling methods are very hard to discriminate the infertile chicken eggs from the fertile ones before hatching on the poultry farm. The purpose of this study was to detect infertile chicken eggs before hatching by use of the nondestructive technique of visible near infrared transmission spectroscopy. The Naïve-Bayes method was adopted to link spectral data and qualitative observation values of chicken eggs to build a model. Five preprocessing methods were applied to spectral data to improve the robustness of the models. The internal test method of leave one cross validation and an external test method were employed to test the predictive ability of the established models. Naïve-Bayes with a second derivative by the Savitzky-Golay preprocessing method was selected as the optimal prediction model by comparing with four evaluation parameters of other models. The overall accuracy of the model using the second derivative—Savitzky-Golay preprocessing method was 91.67%, while the sensitivity and the specificity were 95% and 100%, respectively. The prediction ability of the optimal model was assessed by use of unknown new egg samples. The average overall prediction accuracy of the prediction set containing 111 eggs was 89.12%, while the sensitivity and specificity were 88.14 and 90.38%, respectively. Results showed that the prediction model had good predictability and stability. Therefore, visible near infrared transmission spectroscopy would be an appropriate technology to detect infertile chicken eggs before hatching. The infertile chicken eggs from the fertile ones before hatching were discriminated Visible near infrared spectroscopy first detected infertile chicken eggs before hatching. Naive bayes classifier with five different pre-processing methods were compared. The unknown eggs were predicted by the optimal Naive bayes prediction model. [ABSTRACT FROM AUTHOR]