Recent Advances and Applications of Rapid Microbial Assessment from a Food Safety Perspective

Abstract

Unsafe food is estimated to cause 600 million cases of foodborne disease, annually. Thus, the development of methods that could assist in the prevention of foodborne diseases is of high interest. This review summarizes the recent progress toward rapid microbial assessment through (i) spectroscopic techniques, (ii) spectral imaging techniques, (iii) biosensors and (iv) sensors designed to mimic human senses. These methods often produce complex and high-dimensional data that cannot be analyzed with conventional statistical methods. Multivariate statistics and machine learning approaches seemed to be valuable for these methods so as to “translate” measurements to microbial estimations. However, a great proportion of the models reported in the literature misuse these approaches, which may lead to models with low predictive power under generic conditions. Overall, all the methods showed great potential for rapid microbial assessment. Biosensors are closer to wide-scale implementation followed by spectroscopic techniques and then by spectral imaging techniques and sensors designed to mimic human senses.

Combining AI Tools with Non-Destructive Technologies for Crop-Based Food Safety: A Comprehensive Review

“…Nonetheless, we will inspect only technologies and methodologies that have been implemented in food safety analysis, thus detecting contaminants, assessing microbial risks, determining the presence of pathogens, and evaluating their safety and readiness to be manufactured, stored, transported, or directly consumed. Many examples emerged, such as reviewing methods for determination of contaminants in spices and herbs [ 62 ], such as biological contaminants [ 113 , 114 ], caused by foodborne pathogenic microorganisms. These samples are subject to analytical analysis, which then, depending on the objective of the study and which aspect of food safety to tackle, will produce data.…”

“…The most referred-to analytical strategies in solving this matter were spectral imaging (SI) technologies [ 61 , 113 ], and spectroscopy-based technologies [ 52 , 61 , 63 , 64 , 76 , 81 , 82 , 88 , 89 , 100 , 113 , 114 ].…”

“…Different techniques have emerged in spectral imaging, like hyperspectral imaging (HSI) [ 58 , 61 , 65 , 70 , 82 , 103 , 112 ], for example, near-infrared hyperspectral imaging [ 112 ], as well as multispectral imaging [ 58 , 61 , 64 , 65 , 113 ] and THz spectral imaging [ 88 ]. In spectroscopy, we list ultraviolet-visible spectroscopy (UV-vis), near-infrared spectroscopy, Fourier transform infrared (FT-IR) spectroscopy, Raman spectroscopy, THz spectroscopy, THz time-domain spectroscopy(THz-TDS), laser-induced breakdown spectroscopy (LIBS), surface-enhanced Raman spectroscopy sensors (SERS), nanoenzymes, and modified chromatographic techniques that were mostly coupled with AI tools [ 76 , 81 , 88 , 100 , 112 , 113 , 114 ]. On the other hand, electroanalytical methods have risen to mimic the human senses by using sensor arrays and pattern recognition systems, known as E-nose, E-tongue, and E-eye [ 81 ].…”

Cultured Meat Safety Research Priorities: Regulatory and Governmental Perspectives

“…The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/foods12142645/s1, List of Participant Organizations (Supplementary Materials S1) [105][106][107][108][109][110][111][112][113][114][115], Issue Papers (Supplementary Materials S2). Funding: This research was funded by Soroush Pour, Lejjy Gafour, Andras Forgacs, Gabor Forgacs, Christian Gainsley, Kristin Ellis, Teel Lidow, and Liz Specht who donated to this initiative as individuals, and 22 companies and investors who donated as corporate donors.…”

Bacterial Colony Phenotyping with Hyperspectral Elastic Light Scattering Patterns

“…Multispectral systems collect signals from a few discrete spectral bands, whereas the hyperspectral approaches utilize a large number of bands approximating a continuous spectrum [ 12 ]. Therefore, hyperspectral techniques can provide more in-depth details and generate more precise spectral fingerprints than multispectral techniques [ 13 ]. Hyperspectral imaging techniques thus can leverage the benefit of traditional digital imaging, computer vision, and spectroscopy to process both spatial and spectral information [ 14 ].…”