Visible and NIR hyperspectral imaging and chemometrics for prediction of microbial quality of beef Longissimus dorsi muscle under simulated normal and abuse storage conditions

Achata, Eva M.; Oliveira, Márcia; Esquerre, Carlos; Tiwari, Brijesh K.; O’Donnell, Colm P.

doi:10.1016/j.lwt.2020.109463

Cited by 28 publications

(11 citation statements)

References 31 publications

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“…In the case of other meat matrices, hyperspectral images have also been employed in order to predict microbial contamination in real time. For example, Achata et al [112] developed a prediction model (based on PLSR) to determine the total viable count (TVC) in beef, while Zhou et al [113] proposed a model for Pseudomonas fluorescens prediction in pork (based on Baranyi model in combination with the Ratkowsky square-root model and the Huang model in combination with the Ratkowsky square-root model). In the case of TVC prediction, this is done mainly using wavelengths around 596 nm, which are related to the oxyhaemoglobin absorption bands [114], meanwhile the differentiation of bacterial species is based on the different absorption spectra shown between them [115].…”

Section: Application Of Industry 40 Technologies For Meat Safetymentioning

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: Application Of Industry 40 Technologies For Meat Safetymentioning

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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“…To support the goal of achieving consistently low microbial counts on meat carcasses and meat cuts, there is need for at-or near-line monitoring of microorganisms to support real-time process control and management as part of HACCP systems. While conventional microbiological methods including culturing and colony-counting can detect low numbers of cells, they require several days to obtain a result (Wang et al, 2018) and are thus unsuitable for online monitoring and process control in meat production processes (Wang et al, 2018;Achata et al, 2020). There are a number of emerging techniques which could be used near-line or atline based on fluorescent sensors, spectroscopic and spectral imaging techniques, such as infrared spectroscopy (IRS), Raman spectroscopy, fluorescence spectroscopy, HSI and multispectral imaging (MSI) for the rapid detection of total or specific microorganisms in meat.…”

Section: Monitoring Of Microorganisms In Fresh Meat Productionmentioning

confidence: 99%

“…The application of this promising method, however, requires further investigation in commercial meat plant settings. Achata et al (2020) assessed the potential of HSI in the visible (445-970 nm) and NIR (957-1664 nm) range with chemometrics in the prediction of TVC in beef. Partial least squares regression (PLSR) and principal components analysis (PCA) were compared, along with a variety of spectral preprocessing techniques and band selection methods before data fusion combined the information, which produced a more accurate model.…”

Section: Monitoring Of Microorganisms In Fresh Meat Productionmentioning

confidence: 99%

Current research and emerging tools to improve fresh red meat quality

Gagaoua

Duffy

Álvarez

et al. 2022

Irish Journal of Agricultural and Food Research

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A consumer’s decision to purchase red meat is guided by a combination of many interacting factors including safety, nutrition, sustainability and perception of healthiness along with a variety of sensory characteristics such as colour, marbling, tenderness, juiciness and flavour. Red meat quality is complex and influenced by many intrinsic and extrinsic factors, spanning the chain from breed/genetics through to the final end product with key influences coming from on-farm management and post-mortem processing. As a result of various factors, including consumer demands, the importance of both red meat quality and safety has in recent times come to the fore for the meat industry, with steps to meet these requirements having a large bearing on profitability. Therefore, a critical review of steps which can help control these traits is very important. Accordingly, several processing strategies were proposed at the research and industry level aiming to improve fresh red meat quality traits. This review summarises the current methods applied to improve fresh red meat quality and safety, including the advances in management and prediction tools for carcass and technological and sensory quality traits. These methods are also relevant to the safety and microbiological status of carcasses and meat produced, along with the recent developments in sensory analysis, which aim to understand the sensory properties of red meat and consumers responses. The potential of foodomics approaches is discussed under the topics of genomics, proteomics and metabolomics, which help our understanding of the underlying biological mechanisms behind the variation of sensory and technological quality traits and their use for the discovery of putative biomarkers. We further considered the current and emerging sequencing-based methods used to understand microbial community composition of fresh red meat.

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“…The same system was used to predict the TVC value of cooked beef and samples were distinguished with three classes (freshness, medium freshness, and spoilage) based on the value of TVC (correct classification rate = 97.14%) ( Yang et al, 2017 ). Achata et al (2020) predicted the TVC of the beef Longissimus dorsi muscle with two storage condition by using line-scan Vis-NIR HSI (400–1000 nm, 880–1720 nm), data fusion of both spectral regions was developed for beef samples with storage at 4 °C and 10 °C (R2p = 0.96; RMSEP = 0.58 and R2p = 0.94; RMSEP = 0.97, respectively). Various storage situations brought the complicated circumstance of detecting TVC value and these applications provide broad prospects for real-time monitoring of TVC content.…”

Section: Recent Applications Of Hyperspectral Imaging For Meat Produc...mentioning

confidence: 99%

Hyperspectral Imaging (HSI) for meat quality evaluation across the supply chain: Current and future trends

Jia

Ruth

Scollan

et al. 2022

Current Research in Food Science

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Visible and NIR hyperspectral imaging and chemometrics for prediction of microbial quality of beef Longissimus dorsi muscle under simulated normal and abuse storage conditions

Cited by 28 publications

References 31 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

Current research and emerging tools to improve fresh red meat quality

Hyperspectral Imaging (HSI) for meat quality evaluation across the supply chain: Current and future trends

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