Fertility and Embryo Development of Broiler Hatching Eggs Evaluated with a Hyperspectral Imaging and Predictive Modeling System

A hyperspectral imaging system and a predictive modeling technique was evaluated for determining fertility and early embryo development of broiler chicken hatching eggs. Twenty-four broiler eggs were collected (12 fertile, 12 infertile) for each of 8 replicate trials (n = 192) and imaged on Days 0, 1, 2 and 3 of incubation for training and model validation. Three replications of 30 eggs each (fertile and infertile eggs randomly mixed) were collected and imaged as above for model verification (n = 90). Eggs were backlit and positioned below and vertical to the imaging system (lens, spectrograph and CCD camera). Spatial and spectral data from approximately 400-1000nm were collected for each egg on each day of incubation with refinement to 550-899nm. A Mahalanobis Distance (MD) supervised classifier was trained with spectral data from the first 5 replicate sets of eggs, then Principal Component Analysis (PCA) was performed. This model was applied to the next 3 sets for model validation and then to the three 30 egg sets for verification. Fertility was confirmed on Day 5 of incubation by candling and breakout. The MD/PCA model predictions for the 3 validation sets of eggs were: 71% accuracy for Day 0; 63% for Day 1, 65% for Day 2 and 83% for Day 3. For the 3 sets of verification eggs, the MD/PCA model accurately predicted 46/90 on Day 1 and 45/90 on Day 3. The data indicate that the particular MD/PCA model used is not appropriate for predicting fertility and early development.