Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review

Fan, Ke-Jun; Su, Wen-Hao

doi:10.3390/bios12020076

Cited by 25 publications

(13 citation statements)

References 103 publications

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“…However, hyperspectral imaging direct use is limited by the extensive time needed to process large volumes of data. For this reason, the selection of characteristic wavelengths is made that allows the development of a multispectral imaging system [55,56]. For its part, near-infrared permits obtaining the spectrum of an object in the wavelength range of 750 to 2500 nm.…”

Section: Imaging Technologymentioning

confidence: 99%

Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry

Echegaray

Hassoun²,

Jagtap

et al. 2022

Applied Sciences

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Meat 4.0 refers to the application the fourth industrial revolution (Industry 4.0) technologies in the meat sector. Industry 4.0 components, such as robotics, Internet of Things, Big Data, augmented reality, cybersecurity, and blockchain, have recently transformed many industrial and manufacturing sectors, including agri-food sectors, such as the meat industry. The need for digitalised and automated solutions throughout the whole food supply chain has increased remarkably during the COVID-19 pandemic. This review will introduce the concept of Meat 4.0, highlight its main enablers, and provide an updated overview of recent developments and applications of Industry 4.0 innovations and advanced techniques in digital transformation and process automation of the meat industry. A particular focus will be put on the role of Meat 4.0 enablers in meat processing, preservation and analyses of quality, safety and authenticity. Our literature review shows that Industry 4.0 has significant potential to improve the way meat is processed, preserved, and analysed, reduce food waste and loss, develop safe meat products of high quality, and prevent meat fraud. Despite the current challenges, growing literature shows that the meat sector can be highly automated using smart technologies, such as robots and smart sensors based on spectroscopy and imaging technology.

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Section: Imaging Technologymentioning

confidence: 99%

Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry

Echegaray

Hassoun²,

Jagtap

et al. 2022

Applied Sciences

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“…Fluorescence spectroscopy is known as a non-thermal processing technology since gaining interest due to efficient control of the quality and authenticity of fish and fish products [ 110 ]. Fluorescence spectroscopy is particularly applied to evaluate the freshness quality of most fish species stored under different light and vacuum packaging conditions and to monitor the access of lipid oxidation occurring in fatty and lean fish species during various storage and processing conditions such as canning, refrigerated and frozen storage [ 111 ].…”

Section: Processing Technology Approaches Of Fishmentioning

confidence: 99%

Research Progress on Nutritional Value, Preservation and Processing of Fish—A Review

Ali

Wei

Ali³

et al. 2022

Foods

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The global population has rapidly expanded in the last few decades and is continuing to increase at a rapid pace. To meet this growing food demand fish is considered a balanced food source due to their high nutritious value and low cost. Fish are rich in well-balanced nutrients, a good source of polyunsaturated fatty acids and impose various health benefits. Furthermore, the most commonly used preservation technologies including cooling, freezing, super-chilling and chemical preservatives are discussed, which could prolong the shelf life. Non-thermal technologies such as pulsed electric field (PEF), fluorescence spectroscopy, hyperspectral imaging technique (HSI) and high-pressure processing (HPP) are used over thermal techniques in marine food industries for processing of most economical fish products in such a way as to meet consumer demands with minimal quality damage. Many by-products are produced as a result of processing techniques, which have caused serious environmental pollution. Therefore, highly advanced technologies to utilize these by-products for high-value-added product preparation for various applications are required. This review provides updated information on the nutritional value of fish, focusing on their preservation technologies to inhibit spoilage, improve shelf life, retard microbial and oxidative degradation while extending the new applications of non-thermal technologies, as well as reconsidering the values of by-products to obtain bioactive compounds that can be used as functional ingredients in pharmaceutical, cosmetics and food processing industries.

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“…RGB imaging makes it possible to determine the overall colour and visually evaluate the analysed samples. Generally, RGB imaging is very beneficial, although it provides limited information (Fan and Su, 2022). To overcome this problem, RGB image analysis is often combined with deep learning.…”

Section: Introductionmentioning

confidence: 99%

“…CNNs can learn the representation and can perform shift-invariant classification on the input information according to a hierarchical structure. Normally, CNN is most often used as a tool to analyse images, such as in the case of white meat classification (Fan and Su, 2022). CNN models have already been trained on forest data sets and shown to perform well (Egli and Höpke, 2020).…”

Section: Introductionmentioning

confidence: 99%

An innovative technique for faecal score classification based on RGB images and artificial intelligence algorithms

Ortenzi¹,

Violino²,

Costa³

et al. 2023

J. Agric. Sci.

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The milk production is strongly influenced by the dairy cow welfare related to a good nutrition and the analysis of the digestibility of feeds allows us to evaluate the health status of the animals. Through faeces’ visual examination it is possible to estimate the quality of diet fed in terms of lacking in fibre or too high in non-structural carbohydrates. The study was carried out in 2021, on four dairy farms in central Italy. The purpose of this work is the classification and evaluation of dairy cow faeces using RGB image analysis through an artificial intelligence (AI) (convolutional neural network (CNN)) algorithm. The main features to analyse are pH, colour and consistency. For the latter two RGB imaging was combined with deep learning and AI to reach objectivity in samples’ evaluation. The images have been captured with several smartphones and cameras, under various light conditions, collecting a data set of 441 images. Images acquired by RGB cameras are then analysed through CNN technology that extracts features and data previously standardized by a faecal score index assigned after a visual analysis and based on five classes. The results achieved with different training strategies show a training accuracy of 90% and a validation accuracy of 78% of the model which allow us to identify problems in bovine digestion and to intervene promptly in feed variation. The method used in this study eliminates subjectivity in field analysis and allows future improvement of increasing the data set to strengthen the model.

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Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review

Cited by 25 publications

References 103 publications

Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry

Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry

Research Progress on Nutritional Value, Preservation and Processing of Fish—A Review

An innovative technique for faecal score classification based on RGB images and artificial intelligence algorithms

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