Integrated spectral and textural features of hyperspectral imaging for prediction and visualization of stearic acid content in lamb meat

Wang, Yan; Wang, Caixia; Dong, Fujia; Wang, Songlei

doi:10.1039/d1ay00757b

Cited by 19 publications

(10 citation statements)

References 42 publications

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“…The absorption band at 1400–1500 nm represents the first O-H stretching of COOH. The infrared spectrum in the 1600–1700 nm region was related to the amide I band of the protein, which was mainly attributed to the absorption of the C=O bond [ 17 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ].…”

Section: Resultsmentioning

confidence: 99%

“…The appearance of these autocorrelation peaks indicates that with the change in Ala content, the spectral absorption intensity of the band underwent a strong change, and the spectral signals of these characteristic variables were more sensitive to external interference. Among them, 1055 nm belonged to the second stretching of the N-H bond in amides, 1136 nm was the double-frequency absorption band of the C-H bond in CH 2 , 1323 nm was the third vibration of the C=O bond, 1478 nm was the first O-H stretching of COOH, and 1648 nm was the absorption stretching of the C=O bond in the amide I band of protein [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. Analyzing the cross peaks outside the main diagonal of the synchronous spectrum, only the obvious cross peaks were observed at (1136–1323), (1323–1478), and (1478–1136) nm.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, the selection of characteristic wavelength variables became a key step in spectral analysis, which was mainly used to simplify the model and eliminate data redundancy. The use of genetic algorithms, principal component algorithms, iterative algorithms, and weight algorithms to extract feature variables has been reported by a large number of researchers [ 27 , 28 , 29 ]. In this study, two weight algorithms (CARS and RC) were used to select characteristic wavelengths to develop simplified models for the full spectral (FS) area and sensitive local areas selected from 2D–COS analysis.…”

Section: Methodsmentioning

confidence: 99%

“…This makes it difficult to extract the NIR spectral information of the meat, and the spectral signal presents overlapping and complexity [ 27 ]. As a result, quantitative analysis by NIR has relied heavily on the application of chemometric analysis to relate the subtle spectral changes to the variations in concentrations of certain components in the analyte [ 28 ]. In previous studies, the derivative method, weight value method, principal component analysis, and feature variable extraction were the main spectral response analysis methods for studying the spectral characteristic variables of objects [ 29 , 30 ].…”

Section: Introductionmentioning

confidence: 99%

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A Combination of Near-Infrared Hyperspectral Imaging with Two-Dimensional Correlation Analysis for Monitoring the Content of Alanine in Beef

Dong

Bi²,

Hao³

et al. 2022

Biosensors

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Alanine (Ala), as the most important free amino acid, plays a significant role in food taste characteristics and human health regulation. The feasibility of using near–infrared hyperspectral imaging (NIR–HSI) combined with two–dimensional correlation spectroscopy (2D–COS) analysis to predict beef Ala content quickly and nondestructively is first proposed in this study. With Ala content as the external disturbance condition, the sequence of chemical bond changes caused by synchronous and asynchronous correlation spectrum changes in 2D–COS was analyzed, and local sensitive variables closely related to Ala content were obtained. On this basis, the simplified linear, nonlinear, and artificial neural network models developed by the weighted coefficient based on the feature wavelength extraction method were compared. The results show that with the change in Ala content in beef, the double-frequency absorption of the C-H bond of CH2 in the chemical bond sequence occurred prior to the third vibration of the C=O bond and the first stretching of O-H in COOH. Furthermore, the wavelength within the 1136–1478 nm spectrum range was obtained as the local study area of Ala content. The linear partial least squares regression (PLSR) model based on effective wavelengths was selected by competitive adaptive reweighted sampling (CARS) from 2D–COS analysis, and provided excellent results (R2C of 0.8141, R2P of 0.8458, and RPDp of 2.54). Finally, the visual distribution of Ala content in beef was produced by the optimal simplified combination model. The results show that 2D–COS combined with NIR–HSI could be used as an effective method to monitor Ala content in beef.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Combination of Near-Infrared Hyperspectral Imaging with Two-Dimensional Correlation Analysis for Monitoring the Content of Alanine in Beef

Dong

Bi²,

Hao³

et al. 2022

Biosensors

Self Cite

View full text Add to dashboard Cite

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“…This makes it more advantageous than the single spectroscopic and imaging techniques in food safety detection and control. Therefore, the hyperspectral imaging technology is widely used in the detection of different substances, such as the total acid, moisture, sugar content of Daqu (Huang, Hu, Tian, Chen, & Huang, 2021; Huang, Hu, Tian, Jiang, Luo, & Huang, 2021; Jiang et al, 2021), oil content of corn kernels (Zhang et al, 2022), stearic acid content, TBARS content of mutton and the fat content of peanut kernels (Fan et al, 2021; Sun et al, 2020; Wang, Wang, et al, 2021). This hyperspectral imaging technology obtained satisfactory results in the detection of substance content, which demonstrates its feasibility for the detection of the starch content of mixed sorghum.…”

Section: Introductionmentioning

confidence: 99%

Rapid and accurate detection of starch content in mixed sorghum by hyperspectral imaging combined with data fusion technology

Jiang

Tian

et al. 2022

J Food Process Engineering

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Sorghum is a type of brewing material. The starch content of different kinds of mixed sorghum affect the quality and yield of liquor. Therefore, an accurate and efficient detection of its starch content is of great significance to obtain high‐quality and high‐yield of liquor. Based on the data of single visible light (Vis), near‐infrared (NIR), and Vis and NIR fusion, this study develops a genetic algorithm optimization BP neural network (GA‐BPNN) model and a particle swarm optimization support vector machine model. It is deduced that the model based on the data from the Vis and NIR fusion has the highest performance in predicting the starch content of mixed sorghum. For the prediction of amylose, the GA‐BPNN model developed after using the Pearson correlation coefficient to select the characteristic wavelength for fusion, has the highest performance (RMSEP = .0298 and = .9948). For the prediction of amylopectin, the GA‐BPNN model developed after fusion of spectral features extracted by principal component analysis, has the highest performance (RMSEP = .0213 and = .9985). In conclusion, the hyperspectral imaging combined with data fusion can rapidly and accurately detect the starch content of mixed sorghum.Practical ApplicationsAs the single raw material of Maotai‐flavor liquor and the main raw material of Luzhou‐flavor liquor, the amylopectin content of sorghum directly affects the quality of liquor. Its amylose content also affects the yield of liquor. Because the different varieties of sorghum have different amylose and amylopectin content, liquor manufacturers often use several mixed varieties of sorghum as a brewing material. In order to ensure the quality and yield of liquor, it is particularly crucial to detect the amylose and amylopectin content variables of blended sorghum. The traditional sorghum starch content determination methods, such as the chemical detection methods and near infrared spectroscopy, have the disadvantages of destructiveness, low efficiency, and low detection accuracy. In the process of liquor brewing, the traditional detection methods cannot guide the timely adjustment of brewing process parameters. The hyperspectral imaging technology is widely used in food material detection, due to its fast and nondestructive advantages. The data fusion technology can fuse data from different sources of the same object to be detected, in order to obtain more comprehensive data for the development of accurate prediction models. This study uses the hyperspectral imaging combined with data fusion in order to quickly and accurately predicts the starch content (amylose, amylopectin) of mixed sorghum, which has a guiding significance for the timely adjustment of process parameters in the brewing process of liquor. In addition, it provides an accurate method for the component detection of other grains.

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Slaughter performance of the main goose breeds raised commercially in China and nutritional value of the meats of the goose breeds: a systematic review

Yan

Zhen

et al. 2022

J Sci Food Agric

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A number of goose breeds are raised commercially in China. However, the data on the slaughter performance of the goose breeds and the nutritional value of their meats lack a thorough comparative analysis. In this systematic review, the slaughter performance of the goose breeds and nutritional value of their meats were comparatively analyzed to provide an overview of the characteristics of the goose breeds raised commercially in China. Fifteen goose breeds were selected from 27 research articles published up to January 2022 on the slaughter performance of the goose breeds raised commercially in China and their nutrient composition after literature searching, literature screening, variety selection, and data collation. The slaughter indexes of the goose breeds and the basic nutrient composition, amino acid composition, and fatty acid composition of the meats of the goose breeds were standardized using min–max normalization and compared. The results suggest that the slaughter indexes and nutritional indicators of the meats of Yangzhou white goose, Xupu goose, Landaise geese, and Sichuan white goose are more balanced than those of the meats of the other goose breeds. The results of this review can lay the foundation for optimizing the breeding methods of the commercially raised goose breeds and processing methods of the meats of the geese. © 2022 Society of Chemical Industry.

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Integrated spectral and textural features of hyperspectral imaging for prediction and visualization of stearic acid content in lamb meat

Abstract: Stearic acid content is an important factor affecting mutton odor. To obtain the distribution and content of stearic acid (C18:0) in lamb meat fast and nondestructively, a method integrating spectra...

Cited by 19 publications

References 42 publications

A Combination of Near-Infrared Hyperspectral Imaging with Two-Dimensional Correlation Analysis for Monitoring the Content of Alanine in Beef

A Combination of Near-Infrared Hyperspectral Imaging with Two-Dimensional Correlation Analysis for Monitoring the Content of Alanine in Beef

Rapid and accurate detection of starch content in mixed sorghum by hyperspectral imaging combined with data fusion technology

Slaughter performance of the main goose breeds raised commercially in China and nutritional value of the meats of the goose breeds: a systematic review

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