Agri-product such as grains, fruits and vegetables play a very important role in people's daily life. The agri-product quality directly affects human life and health. Agri-product quality refers to the quality characteristics acceptable to consumers, which mainly includes external factors such as size, shape, color, defect and texture, and internal factors such as physical properties, chemical composition and tissue diseases. Generally speaking, variety, climate, soil, cultivation techniques, diseases and pests are all factors that affect the agri-product quality. Traditional methods for agri-product quality evaluation are time-consuming, complex, and expensive. With the continuous development of modern science and technology, rapid and nondestructive detection technologies are applied to evaluate the quality of agri-product. These technologies could obtain the optical, acoustics and electrical properties of a specific substance and then reveal the appearance and internal quality of the agri-product. Furthermore, the trend today is that consumers have become more exigent for information about the products they purchase, which makes the nondestructive detection technology has more important application value in the field of agri-product quality evaluation.
Nowadays, a variety of signal enhancement techniques (e.g., machine vision, near-infrared spectroscopy, hyperspectral imaging, raman spectroscopy, electronic nose, ultrasound technique, magnetic resonance imaging technique, radio technique, and terahertz imaging technology) and data analytics methods (e.g., machine learning, deep learning) are used for improving the detection speed and sensitivity of agri-product quality.
This Research Topic intends to probe the feasibility of using up-to-date detection techniques, methods and equipment to investigate the key parameters that affect agri-product quality, which will be conducive to the development of rapid non-destructive testing technology for agri-product quality.
This Research Topic covers the latest developments and applications of advanced rapid and non-destructive sensing technologies for quality evaluation of agri-product, with relevant areas including but not limited to:
• Nondestructive detection for external qualities such as visible defects, invisible defects and texture;
• Nondestructive evaluation for internal qualities such as physical properties, chemical composition and tissue diseases;
• Nondestructive evaluation for the parameters affecting the agri-product safety such as heavy metals and toxins;
• Design and development of advanced rapid and nondestructive sensing system;
• Data analytics and artificial intelligence in all aspects of sensing technologies
Agri-product such as grains, fruits and vegetables play a very important role in people's daily life. The agri-product quality directly affects human life and health. Agri-product quality refers to the quality characteristics acceptable to consumers, which mainly includes external factors such as size, shape, color, defect and texture, and internal factors such as physical properties, chemical composition and tissue diseases. Generally speaking, variety, climate, soil, cultivation techniques, diseases and pests are all factors that affect the agri-product quality. Traditional methods for agri-product quality evaluation are time-consuming, complex, and expensive. With the continuous development of modern science and technology, rapid and nondestructive detection technologies are applied to evaluate the quality of agri-product. These technologies could obtain the optical, acoustics and electrical properties of a specific substance and then reveal the appearance and internal quality of the agri-product. Furthermore, the trend today is that consumers have become more exigent for information about the products they purchase, which makes the nondestructive detection technology has more important application value in the field of agri-product quality evaluation.
Nowadays, a variety of signal enhancement techniques (e.g., machine vision, near-infrared spectroscopy, hyperspectral imaging, raman spectroscopy, electronic nose, ultrasound technique, magnetic resonance imaging technique, radio technique, and terahertz imaging technology) and data analytics methods (e.g., machine learning, deep learning) are used for improving the detection speed and sensitivity of agri-product quality.
This Research Topic intends to probe the feasibility of using up-to-date detection techniques, methods and equipment to investigate the key parameters that affect agri-product quality, which will be conducive to the development of rapid non-destructive testing technology for agri-product quality.
This Research Topic covers the latest developments and applications of advanced rapid and non-destructive sensing technologies for quality evaluation of agri-product, with relevant areas including but not limited to:
• Nondestructive detection for external qualities such as visible defects, invisible defects and texture;
• Nondestructive evaluation for internal qualities such as physical properties, chemical composition and tissue diseases;
• Nondestructive evaluation for the parameters affecting the agri-product safety such as heavy metals and toxins;
• Design and development of advanced rapid and nondestructive sensing system;
• Data analytics and artificial intelligence in all aspects of sensing technologies