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Protein digestion begins in the stomach, where the highly acidic environment can easily disrupt protein structure by exposing the peptide bonds of polypeptide chains. After polypeptide chains are broken into individual amino acids by a series of digestive enzymes, the amino acids are transported to the liver via the bloodstream to produce energy.
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Microorganisms play a crucial role in agriculture and the food industry, contributing to soil fertility, crop protection, and food production. Their functions range from nitrogen fixation and biopesticide production to fermentation and food preservation, making them indispensable to sustainable farming and food safety.Role in AgricultureNitrogen-fixing bacteria, such as Rhizobium (symbiotic) and Azotobacter (free-living), convert atmospheric nitrogen into ammonia through biological nitrogen...
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Detection of Mycotoxin Contamination in Foods Using Artificial Intelligence: A Review.

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Artificial intelligence (AI) offers a revolutionary approach to detecting mycotoxins in food, enhancing accuracy and speed. This review explores AI

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Area of Science:

  • Food Science and Technology
  • Analytical Chemistry
  • Computational Biology

Background:

  • Mycotoxin contamination in food poses significant global health risks.
  • Traditional detection methods (e.g., chromatography-mass spectrometry) are accurate but labor-intensive.
  • Artificial intelligence (AI) presents a novel, highly accurate, and credible alternative for mycotoxin detection.

Purpose of the Study:

  • To review recent advancements in AI applications for food mycotoxin detection.
  • To explore the integration of AI with smart sensing and non-conventional techniques.
  • To address challenges and future directions in AI-based mycotoxin analysis.

Main Methods:

  • Review of recent studies utilizing AI for mycotoxin identification.
  • Analysis of AI techniques including deep learning, machine learning, and neural networks.
  • Examination of AI integration with spectroscopy, biosensors, and imaging.

Main Results:

  • AI methods demonstrate high accuracy and potential to outperform traditional techniques.
  • AI can be effectively combined with smart sensing and non-conventional analytical platforms.
  • AI offers faster and less damaging detection of mycotoxins in food commodities.

Conclusions:

  • AI has the potential to transform mycotoxin monitoring systems for improved food safety.
  • Addressing data requirements, standardization, and regulatory approval are key for AI adoption.
  • Multidisciplinary collaboration is crucial for advancing AI-enabled mycotoxin detection.