AIMC Topic: Food Microbiology

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Comparative machine learning strategies for improving antioxidant properties and aroma quality in fermented mung bean milkby Lactobacillus plantarum PC4.

International journal of food microbiology
This study compares least squares support vector machine (LSSVM) and artificial neural network (ANN) models, integrated with the NSGA-II algorithm, to optimize the fermentation of mung bean milk by Lactobacillus plantarum PC4. Given its superior pred...

Dynamic forecasting of beef freshness using multi-step time series analysis of electronic nose signals.

Biosensors & bioelectronics
The preservation of microbial quality in meat products represents a fundamental challenge in contemporary food supply chain management due to the highly perishable nature of these commodities. Although modern testing techniques, particularly electron...

Design, characterization, and application of novel antimicrobial peptides against Bacillus cereus.

International journal of food microbiology
Foodborne pathogens such as Bacillus cereus threaten food safety, necessitating novel antimicrobial solutions. Antimicrobial peptides (AMPs) offer broad-spectrum activity and potential applications in food preservation. In this study, we designed a l...

Escherichia coli O157:H7 survival and transfer dynamics on cold chain packaging materials: An integrated experimental-machine learning framework.

International journal of food microbiology
This study presents a comprehensive investigation of Escherichia coli O157:H7 survival and transfer on six cold chain packaging materials through experimental characterization and machine learning modeling. Survival experiments revealed significant m...

Microbes in Fermentation: Guardians or Threats to Food Safety?

Journal of agricultural and food chemistry
Fermentation plays a pivotal role in food preservation, with fermentative microbes enhancing food safety and stability. However, improper conditions can introduce risks. This perspective examines the dual role of microbes (the benefits of fermentativ...

Prediction of blown pack in vacuum-packaged beef based on microbiome profiles and supervised machine learning.

International journal of food microbiology
The preservation of vacuum-packaged beef products is essential for maintaining shelf life. However, the occurrence of blown pack phenomenon, characterized by the expansion of packaging due to gas production by spoilage microorganisms, is still a chal...

Nondestructive freshness recognition of chicken breast meat based on deep learning.

Scientific reports
Identifying chicken breast freshness is an important component of poultry food safety. Traditional methods for chicken breast freshness recognition suffer from issues such as high cost, difficulty in recognition, and low efficiency. In this study, th...

Smart Detection of Food Spoilage Using Microbial Volatile Compounds: Technologies, Challenges, and Future Outlook.

Journal of agricultural and food chemistry
Microbial volatile organic compounds (MVOCs) serve as early, noninvasive indicators of food spoilage and microbial contamination. This review critically assesses current methods for MVOC detection, including gas chromatography-mass spectrometry (GC-M...

Genomic diversity of Cronobacter sakazakii across the food system to consumers at the global scale.

International journal of food microbiology
Understanding how foodborne pathogens adapt to changing environments is essential for improving food safety monitoring and control. Cronobacter sakazakii, a persistent opportunistic pathogen associated with powdered infant formula outbreaks, poses cr...

MFDF-UNet: Multiscale feature depth-enhanced fusion network for colony adhesion image segmentation.

Journal of microbiological methods
Colony counting plays a crucial role in evaluating food quality and safety. The segmentation of colony adhesion images can significantly enhance the accuracy of food safety assessments. To achieve high-precision segmentation of colony adhesion images...