Traditional methods for the detection in food science, food safety, and food nutrition are time-consuming, inefficient, and destructive. Modern techniques (e.g., modern analytical techniques, big data, and sensors) have been proven to overcome these disadvantages. Besides, modern techniques could also increase the throughput and frequency of detection.
This Research Topic aims to contribute to filling the gap in the knowledge about modern techniques used in food science, food safety, and food nutrition. Modern techniques include but are not limited to Vis/NIR spectroscopy, Raman spectroscopy, electronic nose, electronic tongue, image processing (e.g., RGB imaging, hyperspectral imaging, and multispectral imaging), machine learning, algorithms, big data analysis, deep learning, remote sensing, and artificial intelligence. Both research articles and reviews are welcome.
We welcome but not limited to the following techniques used in food science and nutrition research:
• Big data analysis;
• Advanced image processing methods, such as convolutional neural network;
• Improved analytical methods for more robust models;
• Advanced sensors, including online detection using optical sensors, and equipment development for foodstuffs.
Traditional methods for the detection in food science, food safety, and food nutrition are time-consuming, inefficient, and destructive. Modern techniques (e.g., modern analytical techniques, big data, and sensors) have been proven to overcome these disadvantages. Besides, modern techniques could also increase the throughput and frequency of detection.
This Research Topic aims to contribute to filling the gap in the knowledge about modern techniques used in food science, food safety, and food nutrition. Modern techniques include but are not limited to Vis/NIR spectroscopy, Raman spectroscopy, electronic nose, electronic tongue, image processing (e.g., RGB imaging, hyperspectral imaging, and multispectral imaging), machine learning, algorithms, big data analysis, deep learning, remote sensing, and artificial intelligence. Both research articles and reviews are welcome.
We welcome but not limited to the following techniques used in food science and nutrition research:
• Big data analysis;
• Advanced image processing methods, such as convolutional neural network;
• Improved analytical methods for more robust models;
• Advanced sensors, including online detection using optical sensors, and equipment development for foodstuffs.