February 2025
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6 Reads
Trends in Food Science & Technology
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February 2025
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6 Reads
Trends in Food Science & Technology
November 2024
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151 Reads
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10 Citations
Food fraud undermines consumer trust, creates economic risk, and jeopardizes human health. Therefore, it is essential to develop efficient technologies for rapid and reliable analysis of food quality and safety for food authentication. Machine vision–based methods have emerged as promising solutions for the rapid and nondestructive analysis of food authenticity and quality. The Industry 4.0 revolution has introduced new trends in this field, including the use of deep learning (DL), a subset of artificial intelligence, which demonstrates robust performance and generalization capabilities, effectively extracting features, and processing extensive data. This paper reviews recent advances in machine vision and various DL‐based algorithms for food authentication, including DL and lightweight DL, used for food authenticity analysis such as adulteration identification, variety identification, freshness detection, and food quality identification by combining them with a machine vision system or with smartphones and portable devices. This review explores the limitations of machine vision and the challenges of DL, which include overfitting, interpretability, accessibility, data privacy, algorithmic bias, and design and deployment of lightweight DLs, and miniaturization of sensing devices. Finally, future developments and trends in this field are discussed, including the development of real‐time detection systems that incorporate a combination of machine vision and DL methods and the expansion of databases. Overall, the combination of vision‐based techniques and DL is expected to enable faster, more affordable, and more accurate food authentication methods.
October 2024
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8 Reads
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3 Citations
Food Research International
August 2024
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69 Reads
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14 Citations
Trends in Food Science & Technology
July 2024
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543 Reads
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15 Citations
Lactobacillus acidophilus is a probiotic bacterium that possesses numerous health-promoting properties and has significant technological applications in the fermentation of a wide range of food products and beverages. This review discusses the health benefits of L. acidophilus, including its ability to enhance immunity; promote digestive wellness; and exhibit antioxidant, antitumor, and antimicrobial properties. This review also discusses the production of bioactive peptides and extracellular polysaccharides (EPS) by L. acidophilus. Factors, such as salinity, temperature, carbon sources, and nutrient availability, influence the growth of L. acidophilus, which can affect the survival and bioactive potential of fermented products. The proteolytic effects of L. acidophilus contribute to protein breakdown, which leads to the release of bioactive peptides with various health benefits. This review also discusses the applications of L. acidophilus in the fermentation of dairy products, cereal beverages, soymilk, fruit and vegetable juices, and other functional food preparations, highlighting its potential for improving the nutritional value, organoleptic properties, and probiotic delivery of these products. This review highlights the importance of understanding and controlling fermentation conditions to maximize the growth and health-promoting benefits of L. acidophilus in various food and beverage products.
... Moreover, the complex shapes, diverse colors, and varying surface textures of food products also make image segmentation and feature extraction more challenging. Often, the integration of high-quality hardware and advanced deep learning algorithms, which can be expensive and intricate, is necessary to overcome these obstacles [ 8 ]. It is possible to enhance the adaptability of MV to environmental conditions by utilizing adaptive algorithms and integrating advanced lighting systems [ 9 ]. ...
November 2024
... To prevent errors and anomalies, the first set of data was discarded and statistical analysis was performed on the remaining three sets. 16 Construction of the 3D structure of the TMC4 protein Building on previous research, we successfully constructed the TMC4 receptor model using the trRosetta deep learning tool. 17 The specific method was as follows: the amino acid sequence of the TMC4 protein (accession number: NP_001138775) was procured from the NCBI database (https://www.ncbi.nlm.nih.gov). ...
October 2024
Food Research International
... A variety of salt reduction strategies have been developed, including the substitution of sodium chloride with metal chlorides, optimization of salt composition, and the incorporation of salty taste enhancers, but they have different limitations (Khan et al., 2024). Metal chlorides, such as MgCl 2 and KCl, often impart undesirable bitterness or astringency and are commonly used in highly flavored foods like cheese. ...
August 2024
Trends in Food Science & Technology
... Bifidobacterium and Lactobacillus acidophilus are widely used probiotics in the food industry [16,17], and Bifidobacterium animalis subsp. lactis BLa80 and Lactobacillus acidophilus LA85 have been favored by researchers for their potential physiological functions. ...
July 2024