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Fast Non-destructive Detection Technology and Equipment for Food Quality and Safety
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Fast, non-destructive detection technology and equipment for food quality and safety is a powerful technical support tool to ensure the development of food industry informatization and intelligence, with the advantages of fast speed, convenient operation, and easy online inspection. During the past two decades, such technologies have found numerous successful applications for food and agricultural product detection and processing. Owing to improvements in the manufacturing of photoelectric sensor pieces and progress in artificial intelligence and software algorithms, fast non-destructive detection technologies are able to provide more accurate, reliable, and stable solutions for food quality and safety detection and processing. They are closely integrated with the Internet of Things and intelligent manufacturing, promoting a new wave of innovation in intelligent manufacturing in the food industry. The application of new sensing technology and equipment in the fast, non-destructive detection of food has always been at the forefront of scientific and technological research. This Special Issue aims to focus on the latest research progress of this application and jointly discuss the focus of development of this research direction.
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Keywords
- 60Co
- acceptability
- adsorption energy
- anthocyanidins
- Apple
- apple grading
- Au@Ag nanoparticles
- band energy alignment
- Bayesian optimization algorithm
- benchtop NMR
- bi-layer indicator
- Biology, Life Sciences
- bruise
- carbimazole hydrolysate
- catalase activity
- chromium contamination
- common carp
- convolutional neural network
- crop disease
- cultivation
- Curcumae Longae Rhizoma
- Data fusion
- deep learning
- defect detection
- defective apples
- degree of milling
- density functional theory
- depth-resolved
- DFT
- Early warning
- extinction coefficient
- fast determination
- feature selection
- flexible substrate
- fresh jujube
- freshness
- fruit diameter difference
- fruit quality monitoring
- fungal spores
- gas sensor
- GC–IMS
- HF
- high stability
- hot air drying
- hyperspectral image
- hyperspectral images
- hyperspectral imaging
- impurities detection
- in situ detection
- intelligent evaluation
- Korla fragrant pear
- leaf mildew
- light penetration depth
- liposomes
- logistics control
- low field magnetic resonance
- Machine learning
- Maize
- maize seeds
- mandarins
- Mathematics & science
- micro Raman
- microfluidic chip
- model update
- moldy level
- multi-scale information fusion
- multi-source information fusion
- n/a
- near infrared hyperspectral technology
- near infrared spectroscopy
- NIR
- NMR
- Numerical Simulation
- object detection
- PAES
- polycyclic aromatic hydrocarbons
- quality change
- Raman
- Reference, information & interdisciplinary subjects
- Research & information: general
- residual network model
- room-temperature ethylene sensor
- Scattering
- semantic segmentation
- SERS detection
- shrimp
- simulated annealing
- size correction
- small object detection
- spatial-frequency domain imaging
- spoilage monitoring
- stone cell content
- successive projective algorithm
- support vector regression
- surface-enhanced Raman spectroscopy
- tea sample
- Technology, engineering, agriculture
- terahertz time-domain spectroscopy
- Texture
- thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
- thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
- theoretical study
- tomato
- uninformative variable elimination
- variable fusion
- Vegetables
- visible/near infrared spectrum
- Visualization
- volatile oil
- walnut kernels
- YOLOv5
Links
DOI: 10.3390/books978-3-0365-9325-8Editions