AIMC Topic: Food Technology

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Practical guide for food scientists to build AI: data, algorithms, and applications.

Food chemistry
Artificial intelligence (AI) is rapidly transforming scientific disciplines, yet its adoption in food science remains fragmented and often constrained to narrow application scenarios. This perspective provides a practical guide for food scientists to...

Recent Advances in Integrating Machine Learning with Omics Approaches in Food Science and Nutrition Research.

Journal of agricultural and food chemistry
Omics technologies are revolutionizing food and nutrition research by enabling high-throughput analysis of food components and microorganisms and revealing the intricate relationships between food and human health. Machine learning (ML) methods are p...

Future horizons of Raman spectroscopy in food science: Emerging techniques and innovations for enhanced analysis.

Food chemistry
Raman spectroscopy is a key technology for to ensure sustainable and efficient food safety practices owing to its non-invasive and sensitive molecular analysis. This review highlights the recent advancements in Raman-based techniques, which offer imp...

Comprehensive review of dysphagia and technological advances in dysphagia food.

Food research international (Ottawa, Ont.)
As the global population ages, dysphagia is becoming increasingly common among the elderly, posing serious risks such as choking, aspiration pneumonia, and even death. Leveraging advanced technologies to develop specialized food products for those wi...

Flavor Engineering: A comprehensive review of biological foundations, AI integration, industrial development, and socio-cultural dynamics.

Food research international (Ottawa, Ont.)
This state-of-the-art review comprehensively explores flavor development, spanning biological foundations, analytical methodologies, and the socio-cultural impact. It incorporates an industrial perspective and examines the role of artificial intellig...

A comprehensive review of machine learning and its application to dairy products.

Critical reviews in food science and nutrition
Machine learning (ML) technology is a powerful tool in food science and engineering offering numerous advantages, from recognizing patterns and predicting outcomes to customizing and adjusting to individual needs. Its further development can enable r...

Neural network in food analytics.

Critical reviews in food science and nutrition
Neural network (i.e. deep learning, NN)-based data analysis techniques have been listed as a pivotal opportunity to protect the integrity and safety of the global food supply chain and forecast $11.2 billion in agriculture markets. As a general-purpo...

Exploring the role of green and Industry 4.0 technologies in achieving sustainable development goals in food sectors.

Food research international (Ottawa, Ont.)
In recent years, the rapid increase in the global population, the challenges associated with climate change, and the emergence of new pandemics have all become major threats to food security worldwide. Consequently, innovative solutions are urgently ...

The fourth industrial revolution in the food industry-part II: Emerging food trends.

Critical reviews in food science and nutrition
The food industry has recently been under unprecedented pressure due to major global challenges, such as climate change, exponential increase in world population and urbanization, and the worldwide spread of new diseases and pandemics, such as the CO...

Deep learning in food science: An insight in evaluating Pickering emulsion properties by droplets classification and quantification via object detection algorithm.

Advances in colloid and interface science
Understanding the complicated emulsion microstructures by microscopic images will help to further elaborate their mechanisms and relevance. The formidable goal of the classification and quantification of emulsion microstructure appears difficult to a...