Development of Simplified Models for Non-Destructive Hyperspectral Imaging Monitoring of S-ovalbumin Content in Eggs during Storage

Yao, Kunshan; Sun, Jun; Cheng, Jiehong; Xu, Min; Chen, Chen; Zhou, Xin; Dai, Chunxia

doi:10.3390/foods11142024

Cited by 8 publications

(4 citation statements)

References 43 publications

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“…To obtain the typical spectrum of the sample, the background of the image should be removed from the hyperspectral image [ 24 ]. The threshold was determined by histogram, and then the mask was made by binarization.…”

Section: Methodsmentioning

confidence: 99%

Monitoring the Aging and Edible Safety of Pork in Postmortem Storage Based on HSI and Wavelet Transform

Xie,

Zhang,

et al. 2024

Foods

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The process of meat postmortem aging is a complex one, in which improved tenderness and aroma coincide with negative effects such as water loss and microbial growth. Determining the optimal postmortem storage time for meat is crucial but also challenging. A new visual monitoring technique based on hyperspectral imaging (HSI) has been proposed to monitor pork aging progress. M. longissimus thoracis from 15 pigs were stored at 4 °C for 12 days while quality indexes and HSI spectra were measured daily. Based on changes in physical and chemical indicators, 100 out of the 180 pieces of meat were selected and classified into rigor mortis, aged, and spoilt meat. Discrete wavelet transform (DWT) technology was used to improve the accuracy of classification. DWT separated approximate and detailed signals from the spectrum, resulting in a significant increase in classification speed and precision. The support vector machine (SVM) model with 70 band spectra achieved remarkable classification accuracy of 97.06%. The study findings revealed that the aging and microbial spoilage process started at the edges of the meat, with varying rates from one pig to another. Using HSI and visualization techniques, it was possible to evaluate and portray the postmortem aging progress and edible safety of pork during storage. This technology has the potential to aid the meat industry in making informed decisions on the optimal storage and cooking times that would preserve the quality of the meat and ensure its safety for consumption.

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Section: Methodsmentioning

confidence: 99%

Monitoring the Aging and Edible Safety of Pork in Postmortem Storage Based on HSI and Wavelet Transform

Xie,

Zhang,

et al. 2024

Foods

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“…The S ‐ovalbumin content of EW was measured by the method of Yao et al . (2022), with slightly modifications. The EW (1.5 g) was mixed with 25 mL phosphate buffer (0.01 m , pH 7) for 5 min using a magnetic stirrer.…”

Section: Methodsmentioning

confidence: 99%

Effect of refrigeration storage on functional properties and structure of egg white after defrosting treatments

Dai¹,

Xia²,

Huang

et al. 2022

Int J of Food Sci Tech

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The changes in refrigeration storage after defrosting treatments on functional properties and structure of egg white (EW) were investigated in this study. The foaming properties and surface hydrophobicity decreased significantly (P < 0.05), whereas the free thiol content of EW increased during prolonged refrigeration storage after defrosting treatments. The values of emulsifying activity index were slightly higher in EM subjected to refrigeration storage for 20-30 days after defrosting treatments (P < 0.05). The texture profiles showed that the cooked EW gel subjected to refrigeration storage for 20 days after defrosting treatments, reached the minimum hardness, springiness and gumminess values vs. that of Control and Group 1. Additionally, scanning electron microscope (SEM) reflected that more and larger protein aggregates as well as irregular structure in EM during prolonged refrigeration storage after defrosting treatments. The increase in free sulfhydryl group and decrease in surface hydrophobicity tended to cause protein oxidation, aggregation and degradation, leading to deterioration of functional properties in EW following refrigeration storage after defrosting treatments. The results of this study indicate that it is important to use the EW of Control and Group 1 without any detrimental effects on functional and morphology properties in food processing industry.

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“…Spectral pre-processing is an important step in establishing a spectral detection algorithm in order to reduce errors due to external factors and random noise, and baseline changes [27]. Additionally, influencing the spectrum are factors such as the scattering of the object's surface and the alteration of the optical path.…”

Section: Data Preprocessingmentioning

confidence: 99%

Application of Hyperspectral Imaging as a Nondestructive Technology for Identifying Tomato Maturity and Quantitatively Predicting Lycopene Content

Dai

Sun

Ren

et al. 2023

Foods

Self Cite

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Maturity is a crucial indicator in assessing the quality of tomatoes, and it is closely related to lycopene content. Using hyperspectral imaging, this study aimed to monitor tomato maturity and predict its lycopene content at different maturity stages. Standard normal variable (SNV) transformation was applied to preprocess the hyperspectral data. Then, using competitive adaptive reweighted sampling (CARS), the characteristic wavelengths were selected to simplify the calibration models. Based on the full and characteristic wavelengths, a support vector classifier (SVC) model was developed to determine tomato maturity qualitatively. The results demonstrated that the classification accuracy using the characteristic wavelength led to the obtention of better results with an accuracy of 95.83%. In addition, the support vector regression (SVR) and partial least squares regression (PLSR) models were utilized to predict lycopene content. With a coefficient of determination for prediction (R2P) of 0.9652 and a root mean square error for prediction (RMSEP) of 0.0166 mg/kg, the SVR model exhibited the best quantitative prediction capacity based on the characteristic wavelengths. Following this, a visual distribution map was created to evaluate the lycopene content in tomato fruit intuitively. The results demonstrated the viability of hyperspectral imaging for detecting tomato maturity and quantitatively predicting the lycopene content during storage.

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Development of Simplified Models for Non-Destructive Hyperspectral Imaging Monitoring of S-ovalbumin Content in Eggs during Storage

Cited by 8 publications

References 43 publications

Monitoring the Aging and Edible Safety of Pork in Postmortem Storage Based on HSI and Wavelet Transform

Monitoring the Aging and Edible Safety of Pork in Postmortem Storage Based on HSI and Wavelet Transform

Effect of refrigeration storage on functional properties and structure of egg white after defrosting treatments

Application of Hyperspectral Imaging as a Nondestructive Technology for Identifying Tomato Maturity and Quantitatively Predicting Lycopene Content

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