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One unresolved challenge in the egg industry is how to efficiently and non-invasively detect unfertilized eggs prior to incubation. This detection ability would not only significantly improve hatching rates and reduce costs but also conserve incubator space and prevent poor-quality embryos from contributing to the spread of infections. This study demonstrates a procedure for distinguishing between fertilized and unfertilized eggs prior to incubation by studying the respiratory differences between fertilized and unfertilized eggs using the Non-invasive Micro-test Technique (NMT). A customized micro-testing examination platform, NMT Egg Testing System (NMT-ETS) was constructed for the real-time monitoring of the intensity and rate of oxygen exchange between the egg and its external environment. The results from this study revealed that at room temperature, there is a significant difference in gas exchange rates between fertilized and unfertilized eggs. The results indicate that the oxygen flux of fertilized eggs exceed 20 pmol/(cm2·s), whereas unfertilized eggs show a much lower oxygen flux. Based on the results, the NMT method can be used to effectively distinguish between fertilized and unfertilized chicken eggs. [ABSTRACT FROM AUTHOR]

In order to quickly distinguish infertile eggs from fertile eggs, the hyperspectral imaging technology consisting of imaging and spectral information was used for detecting the fertile information of eggs. Before hatching eggs were incubated, a hyperspectral imaging system (wavelength between 400 to 1 000 nm) was used to acquire the images one-by-one manually. The characteristic information of ratios of length to short axis, elongation, roundness and the ratios of the yolk area to the whole area was extracted based on the images. The normalization method was used as the spectral data preprocessing, and then 155 spectral characteristic variables were extracted from 520 nm waveband through the correlation coefficient method. Principal component analysis (PCA) method was adopted to reduce the dimensions of image-spectrum fusion information; the top six principal components were extracted. Support vector machine (SVM) method was used to establish classification of fertile and infertile eggs models, which are based on image, spectrum and image-spectrum fusion information respectively. The accuracy rates of the SVM models were 84.00%, 90.00% and 93.00% respectively. The experimental results show that the model based on image-spectrum fusion information technology is superior to the single information model. Hyperspectral transmission imaging technology is effective and feasible to detect the fertile hatching eggs before incubation. [ABSTRACT FROM AUTHOR]

The quality of salted eggs differs in curing process. They need to be tested and graded before factory packaging. The dynamic images of salted eggs were acquired on conveyor. Firstly, preprocessing of color images must be done: the target area of the binary image was determined by mathematical morphology and removal of the object of a small area. According to the binary image is a convex or concave figure, the target region light leaked or not was determined. The effects of leaked region were eliminated by searching for mutation points, fitting salted egg boundary by the Least Square algorithm, labeling the binary image and extracting single target area. Then, six characteristic parameters were extracted in color space, and quality testing model was established by minimum error probability. The experimental results indicated that the detection accuracy reached above 93% and classification efficiency was 5400/h. It is proved the model is feasible for salted egg grading. [ABSTRACT FROM AUTHOR]