Functional and sensory properties of hen eggs with modified fatty acid compositions

A residual dense comprehensively regulated convolutional neural network to identify spectral information for egg quality traceability

In the egg market, due to the different nutritional values of eggs laid by hens under different feeding conditions, it is common for low-quality eggs to be counterfeited as high-quality eggs. This paper proposes a residual dense comprehensively regulated convolutional neural network (RDCR-Net) to identify the quality of eggs laid by hens under different feeding conditions. Firstly, a hyperspectral system is used to obtain the spectral information of eggs. Secondly, due to the complex structure of the spectral information, a comprehensively regulated convolution (CRConv) is proposed to extract features hidden in the spectral information through feature transformation in multiple spaces. Thirdly, due to the limited availability of spectral information training samples, deep networks may suffer from feature degradation. The residual dense comprehensively regulated block (RDCR-Block) is proposed to tightly connect multiple CRConv layers with residual dense connections. Finally, the RDCR-Block is taken as the central unit, and the RDCR-Net is designed to identify egg spectral information. In the comparison of multi-model results, the RDCR-Net obtains the best classification performance with 96.29% accuracy, 97.53% precision, 97.14% recall, and 96.19% kappa coefficient. In summary, the RDCR-Net effectively extracts the deep features of spectral information, achieves high accuracy in identifying eggs laid by hens under different feeding conditions, and provides a new method for egg quality traceability.

Survey of egg quality in commercially available table eggs

Increased demand in consumer choice has resulted in a wide variety of egg selection available in the retail market. Specialty and designer chicken eggs represent a portion of the table egg market that is increasing in size. Egg quality is known to be of great importance in all eggs as it relates to food safety, consumer preferences, and product value. In this study, egg quality characteristics were analyzed using a one-way ANOVA to evaluate 2 commercially available conventional egg brands (A and B) and 4 commercially available designer egg brands (C–F). Three hundred nine eggs were evaluated for shell and content weight, dimensional measurements, and breakage force. Calculations were completed to determine %yolk and albumen, yolk index, and Haugh units (HU), followed by an accelerated lipid oxidation study. No significant variation exists in breakage force. Brands A–E meet AA grade standard at a score of 72 HU or above, while brand F, a pasture-raised brand, meets the A grade standard, falling between 60 and 71 HU. Brand F has the highest yolk fan color value (10.41 ± 0.193, P < 0.001) and the lowest yolk index (0.523 ± 0.013, P < 0.05). In addition, brand F has the lowest albumen height (P < 0.001). As albumen height is an indication of freshness, and as all eggs were of equivalent age, it is possible that brand F exhibits overall lower quality than other brands. The conventionally raised white eggs of A experienced the greatest increase in % free fatty acids, which would likely result in off-flavors from hydrolytic rancidity. The organic cage-free D eggs have a significantly greater peroxide value (17.3 ± 2.9, P < 0.001), relative to all other brands, and is over the 10 mEg/kg threshold, which would be considered an unsuitable product for consumption. Ultimately, the measures of egg quality used in this study are essential for evaluating the delivery of the specialty market to the consumer and may indicate that improved measures of quality are needed to truly differentiate between the different egg types and their quality.

Time course of nutritional and functional property changes in egg yolk from laying hens fed docosahexaenoic acid-rich microalgae

Marine microalgae (MA) has received wide attention as a promising source of omega-3 long-chain polyunsaturated fatty acids (n-3 LC-PUFA) enrichment in animal products to improve the health status and wellbeing of the consumers. This study evaluated dynamic changes in n-3 LC-PUFA, color, and functional properties as well as atherogenic and thrombogenic health lipid indices of egg yolk from hens fed graded levels (0, 0.5, and 1.0%) of docosahexaenoic acid (DHA)–rich MA (Aurantiochytrium sp.) during a 56-D feeding period. Egg freshness parameters and yolk lipid oxidative stability were also measured after 0, 14, and 28 D of refrigerated storage. The hen performance and egg quality (except for yolk color) were not affected (P > 0.05) by MA supplementation. Docosahexaenoic acid contents in yolk from hens fed 1.0% MA increased quadratically with feeding time with a plateau at about 30 D (P < 0.05). Afterward, the DHA content leveled off to a constant value (946.3 mg/100 g yolk) with the n-6/n-3 ratio at 3.5: 1. Dietary inclusion of 1.0% of MA also significantly decreased the atherogenic and thrombogenic indices of yolk lipid (P < 0.05). Because the microalgal carotenoids incorporated into egg yolk, the L∗ value of yolk from hens fed MA decreased whereas a∗ value increased (P < 0.05), corresponding to yolk Roche color scores. As expected, there were no significant changes in yolk functional properties (e.g., viscosity and emulsifying activity) related to DHA enrichment (P > 0.05). Microalgal carotenoids enrichment also helped attenuate fatty acid oxidation of the DHA-enriched yolk and increase their lipid oxidative stability. In conclusion, dietary supplementation with up to 1.0% of MA significantly increased DHA contents with more health-promoting n-6/n-3 ratio and atherogenic and thrombogenic indices, as well as more intense yolk color within consumers' acceptability, and the feeding strategy had a minimal impact on yolk physical and functional properties or oxidative stability during subsequent refrigerated storage.