Comparison of Sensory Qualities in Eggs from Three Breeds Based on Electronic Sensory Evaluations

Advances in Emerging Non-Destructive Technologies for Detecting Raw Egg Freshness: A Comprehensive Review

Eggs are a rich food source of proteins, fats, vitamins, minerals, and other nutrients. However, the egg industry faces some challenges such as microbial invasion due to environmental factors, leading to damage and reduced usability. Therefore, detecting the freshness of raw eggs using various technologies, including traditional and non-destructive methods, can overcome these challenges. As the traditional methods of assessing egg freshness are often subjective and time-consuming, modern non-destructive technologies, including near-infrared (NIR) spectroscopy, Raman spectroscopy, fluorescence spectroscopy, computer vision (color imaging), hyperspectral imaging, electronic noses, and nuclear magnetic resonance, have offered objective and rapid results to address these limitations. The current review summarizes and discusses the recent advances and developments in applying non-destructive technologies for detecting raw egg freshness. Some of these technologies such as NIR spectroscopy, computer vision, and hyperspectral imaging have achieved an accuracy of more than 96% in detecting egg freshness. Therefore, this review provides an overview of the current trends in the state-of-the-art non-destructive technologies recently utilized in detecting the freshness of raw eggs. This review can contribute significantly to the field of emerging technologies in this research track and pique the interests of both food scientists and industry professionals.

Overcoming the Limits of Cross-Sensitivity: Pattern Recognition Methods for Chemiresistive Gas Sensor Array

As information acquisition terminals for artificial olfaction, chemiresistive gas sensors are often troubled by their cross-sensitivity, and reducing their cross-response to ambient gases has always been a difficult and important point in the gas sensing area. Pattern recognition based on sensor array is the most conspicuous way to overcome the cross-sensitivity of gas sensors. It is crucial to choose an appropriate pattern recognition method for enhancing data analysis, reducing errors and improving system reliability, obtaining better classification or gas concentration prediction results. In this review, we analyze the sensing mechanism of cross-sensitivity for chemiresistive gas sensors. We further examine the types, working principles, characteristics, and applicable gas detection range of pattern recognition algorithms utilized in gas-sensing arrays. Additionally, we report, summarize, and evaluate the outstanding and novel advancements in pattern recognition methods for gas identification. At the same time, this work showcases the recent advancements in utilizing these methods for gas identification, particularly within three crucial domains: ensuring food safety, monitoring the environment, and aiding in medical diagnosis. In conclusion, this study anticipates future research prospects by considering the existing landscape and challenges. It is hoped that this work will make a positive contribution towards mitigating cross-sensitivity in gas-sensitive devices and offer valuable insights for algorithm selection in gas recognition applications.

Pattern-based colorimetric sensor array chip for discrimination of Baijiu aromas

Gas mixtures are comprised of numerous complex components, making the accurate identification a continuing challenge due to the significant limitations of existing detection methods. Herein, we developed a low-cost and sensitive pattern-based colorimetric sensor array chip for the identification of typical gas mixtures - Baijiu aroma. Specifically, three nanomaterials (AuNPs, MoS2 and ZIF-8) were prepared to adsorb gas molecules and enhance the reaction of trace gases with sensor arrays. The colorimetric sensor array chip took only 5 min to complete the recognition of Baijiu aromas and effectively avoided recognition errors caused by sommelier olfactory fatigue. Notably, the hierarchical cluster analysis (HCA) revealed no confusion or errors in the results of 80 tests across the five trials involving 16 commercial Baijius. Even fake Baijius with similar ingredients could be easily identified, demonstrating the excellent analytical capabilities of the system in Baijiu identification and its significant potential for quality control of Baijius.

Investigation into the Sensory Properties of Plant-Based Eggs, as Well as Acceptance, Emotional Response, and Use

Consumers have become interested in plant-based alternatives to animal-based products. One of the under-studied alternatives is plant-based eggs (PBEs). This research investigated PBEs relative to conventional eggs and tofu scramble-another plant-based alternative. Firstly, participants (n = 93) completed a word association task asking them about PBEs. Participants then evaluated the different food samples using hedonic scales, check-all-that-apply (CATA), and temporal check-all-that-apply (TCATA), as well as identified their emotional response and proposed use for PBEs. Participants were interested in plant-based alternatives, including PBEs, but they were concerned about the sensory properties. When they evaluated the different samples, the flavour and texture of the PBEs were disliked in comparison to the eggs. This result may be due to the beany, bitterness, and off-flavour attributes associated with the PBEs. Participants also associated the PBEs with negative emotions. The liking of tofu scramble was not significantly different from the eggs, and the eggs and tofu scramble were mainly associated with positive emotions. During the TCATA evaluation, the participants focused on the flavour attributes of PBEs, while their evaluation of the eggs was dominated by the textural attributes. Whether following a plant-based diet or not, consumers are interested in PBEs, but the sensory properties of PBEs need to be improved before they are willing to adopt them into their diet. This study is one of the first to evaluate the sensory properties of PBEs, as well as consumers' emotional response to them and their attitudes about PBEs.

The effects of sucrose/NaCl combined pickling on the textural characteristics, moisture distribution, and protein aggregation behavior of egg yolk

Salted egg yolks have a tender, loose, gritty, and oily texture and are commonly employed as fillings in baked goods. This study investigated the formation mechanism of egg yolk gels using three different pickling methods: NaCl, sucrose, and mixed groups. The results revealed that of these pickling methods, egg yolks pickled with the mixture had the lowest moisture content (11.59% at 25°C and 10.21% at 45°C), almost no free water content, and the highest hardness (19.11 N at 25°C and 31.01 N at 45°C). Intermolecular force measurements indicated that pickling with the mixture mitigated the surface hardening effect of sucrose and facilitated protein cross-linking. Moreover, confocal laser scanning microscopy of the egg yolk gels pickled with the mixture displayed macromolecular aggregates and oil exudation, suggesting that this method partially disrupted the lipoprotein structure and notably promoted yolk protein aggregation and lipid release. Overall, egg yolks formed a dense gel via the mixed pickling method owing to the ionic concentration and dehydration effects. These findings show the impact of NaCl and sucrose in pickling egg yolks, providing a crucial foundation for developing innovative and desirable egg yolk products. PRACTICAL APPLICATION: This study introduces a novel pickling strategy that combines sucrose and NaCl for egg yolk processing. The egg yolk pickled using this method exhibited improved quality according to the evaluated textural characteristics, moisture distribution, and protein aggregation behavior. The findings may broaden the use of sucrose as a pickling agent for egg yolk processing and provide new ideas for developing and producing pickled eggs and other food products.

Eggshell biometrics for individual egg identification based on convolutional neural networks

Individual egg identification technology has potential applications in breeding, product tracking/tracing, and anti-counterfeit. This study developed a novel method for individual egg identification based on eggshell images. A convolutional neural network-based model, named Eggshell Biometric Identification (EBI) model, was proposed and evaluated. The main workflow included eggshell biometric feature extraction, egg information registration, and egg identification. The image dataset of individual eggshell was collected from the blunt-end region of 770 chicken eggs using an image acquisition platform. The ResNeXt network was then trained as a texture feature extraction module to obtain sufficient eggshell texture features. The EBI model was applied to a test set of 1,540 images. The testing results showed that when an appropriate Euclidean distance threshold for classification was set (17.18), the correct recognition rate and the equal error rate reached 99.96% and 0.02%. This new method provides an efficient and accurate solution for individual chicken egg identification, and can be extended to eggs of other poultry species for product tracking/tracing and anti-counterfeit.

A Comparison between the Egg Yolk Flavor of Indigenous 2 Breeds and Commercial Laying Hens Based on Sensory Evaluation, Artificial Sensors, and GC-MS

The focus of this study was to compare the yolk flavor of eggs from laying hens of Chinese indigenous and commercial, based on detection of volatile compounds, fatty acids, and texture characteristics determination, using sensory evaluation, artificial sensors (electronic nose (E-nose), electronic tongue (E-tongue)), and gas chromatography-mass spectrometry (GC-MS). A total of 405 laying hens (Hy-Line Brown (n = 135), Xueyu White (n = 135), and Xinyang Blue (n = 135)) were used for the study, and 540 eggs (180 per breed) were collected within 48 h of being laid and used for sensory evaluation and the instrument detection of yolk flavor. Our research findings demonstrated significant breed differences for sensory attributes of egg yolk, based on sensory evaluation and instrument detection. The milky flavor, moisture, and compactness scores (p < 0.05) of egg yolk from Xueyu White and Xinyang Blue were significantly higher than that of Hy-Line Brown. The aroma preference scores of Xinyang Blue (p < 0.05) were significantly higher, compared to Hy-Line Brown and Xueyu White. The sensor responses of WIW and W2W from E-nose and STS from E-tongue analysis were significantly higher foe egg yolks of Hy-Line Brown (p < 0.05), compared to that of Xueyu White and Xinyang Blue. Additionally, the sensor responses of umami from E-tongue analysis, was significantly higher for egg yolks of Xueyu White (p < 0.05), compared to that of Hy-Line Brown and Xinyang Blue. Besides, the contents of alcohol and fatty acids, such as palmitic acid, oleic acid, and arachidonic acid, in egg yolk were positively correlated with egg flavor. The texture analyzer showed that springiness, gumminess, and hardness of Hy-Line Brown and Xueyu White (p < 0.05) were significantly higher, compared to Xinyang Blue. The above findings demonstrate that the egg yolk from Chinese indigenous strain had better milky flavor, moisture, and compactness, as well as better texture. The egg yolk flavors were mainly due to presence of alcohol and fatty acids, such as palmitic acid, oleic acid, and arachidonic acid, which would provide research direction on improvement in egg yolk flavor by nutrition. The current findings validate the strong correlation between the results of egg yolk flavor and texture, based on sensory evaluation, artificial sensors, and GC-MS. All these indicators would be beneficial for increased preference for egg yolk flavor by consumers and utilization by food processing industry, as well as a basis for the discrimination of eggs from different breeds of laying hens.

Comparative Characterization of Key Volatile Compounds in Slow- and Fast-Growing Duck Raw Meat Based on Widely Targeted Metabolomics

The volatile aroma compounds in raw duck meat strongly affect consumers' purchase decisions and they vary among breeds with different growth rates. In this study, slow-growing (SG) Liancheng White and fast-growing (FG) Cherry Valley ducks were selected, and their volatile compounds were characterized using electric nose and gas chromatography-mass spectrometry. Furthermore, a widely targeted metabolomics approach was used to investigate the metabolites associated with volatile compounds. The results showed that hexanal, nonanal, octanal, heptanal, and 2-pentylfuran were abundantly present in duck meat, regardless of the breed. The higher nonanal and octanal rates contributed to the fatty and fruity aroma in SG meat than FG meat, while FG meat had a mushroom note resulting from higher octenol. Furthermore, widely targeted metabolomics showed a lower carnitine content in SG meat, which might promote lipid deposition to produce more octanal and nonanal. Higher sugar and amino acid contents led to a meaty aroma, whereas more trimethylamine N-oxide may generate a fishy note in SG meat. Taken together, this study characterized the raw duck meat aroma and provided the basic mechanism of the formation of the key volatile compound.

Discrimination between raw and ginger juice processed Magnoliae officinalis cortex based on HPLC and Heracles NEO ultra-fast gas phase electronic nose

INTRODUCTION

Magnoliae officinalis cortex (MOC), a traditional Chinese medicine, has been used in treating gastrointestinal diseases since ancient time. According to the Chinese Pharmacopoeia, it includes two kinds of decoction pieces, raw and ginger juice processed Magnoliae officinalis cortex (RMOC and GMOC).

OBJECTIVE

The aim of this paper was to study the differences between non-volatile and volatile components in RMOC and GMOC.

METHODS

The non-volatile components were detected by HPLC fingerprinting coupled with content determination (syringin, magnoflorine, honokiol and magnolol). Meanwhile, their odor information was obtained using a Heracles NEO ultra-fast gas phase electronic nose to conduct radar fingerprint analysis, principal component analysis and discriminant factor analysis, and the volatile components were analyzed qualitatively by the Kovats retention index and the AroChemBase database.

RESULTS

The HPLC fingerprints were established and 20 common peaks were found in all chromatograms with similarity values of more than 0.900. The content determination results showed that the contents of syringin and magnoflorine decreased, while the contents of honokiol and magnolol increased in GMOC. By the gas phase electronic nose, the two decoction pieces could be distinguished obviously and 16 possible compounds were identified. Among them, the relative contents of (-)-α-pinene and β-pinene increased, while β-phellandrene and (+)-limonene levels decreased.

CONCLUSION

The results suggested that honokiol, magnolol, (-)-α-pinene and β-pinene might be the main substances which could enhance the harmonizing effect on the stomach. Moreover, this paper could lay a foundation for exploring the processing mechanism of MOC and provide a novel method for the research of other traditional Chinese medicine with strong aroma.

Studies on Flavor Compounds and Free Amino Acid Dynamic Characteristics of Fermented Pork Loin Ham with a Complex Starter

Staphylococcus simulans and Lactobacillus plantarum screened from Guizhou specialty food were used to prepare fermented pork loin ham. The sensory qualities and flavor profiles of fermented pork loin hams from 0 to 42 days were investigated in order to reveal the dynamics of fermented pork loin ham. The results show that total free amino acids (TFAA) content reached the highest value on the 35th day, and the umami amino acids, including aspartic acid (ASP), glutamic acid (GLU), glycine (GLY), and alanine (ALA), were the main amino acids in all periods. Notably, the RV coefficient (0.875) indicates that free amino acids (FAA) are highly correlated with the sensory score of the E-tongue. In terms of the volatile compounds identified, the esters content gradually increased between 7 and 42 days, and ethyl octanoate was the most abundant compound during all periods. These esters imparted a characteristic aroma component to the fermented pork loin ham. The most important finding was that the increase in the content of esters represented by octanoic acid-ethyl ester might be related to the increase in the content of FAA with the increase in fermentation time. Both the E-nose and E-tongue showed good discrimination ability for fermented tenderloin ham with different fermentation times, which was crucial in cases with large clusters. In addition, the multiple factor analysis (MFA) indicated that the E-nose aroma value might be the key factor in distinguishing fermented pork loin ham with different fermentation times.