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240202 ||| eng |
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|a 9783036593258
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|a 9783036593241
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|a books978-3-0365-9325-8
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| 100 |
1 |
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|a Guo, Zhiming
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| 245 |
0 |
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|a Fast Non-destructive Detection Technology and Equipment for Food Quality and Safety
|h Elektronische Ressource
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| 260 |
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|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2023
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| 300 |
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|a 1 electronic resource (348 p.)
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| 653 |
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|a machine learning
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|a variable fusion
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|a leaf mildew
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|a impurities detection
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|a NMR
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|a DFT
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|a apple grading
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|a feature selection
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|a density functional theory
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|a data fusion
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|a deep learning
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|a anthocyanidins
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|a HF
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|a logistics control
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|a Korla fragrant pear
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|a micro Raman
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|a spoilage monitoring
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|a model update
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|a hyperspectral images
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|a quality change
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|a small object detection
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|a hyperspectral imaging
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|a in situ detection
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|a polycyclic aromatic hydrocarbons
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|a early warning
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|a Research & information: general / bicssc
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|a band energy alignment
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|a Biology, life sciences / bicssc
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|a hyperspectral image
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|a degree of milling
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|a 60Co
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|a size correction
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|a visualization
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|a terahertz time-domain spectroscopy
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|a mandarins
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|a simulated annealing
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|a freshness
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|a visible/near infrared spectrum
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|a residual network model
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|a fresh jujube
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|a texture
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|a benchtop NMR
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|a liposomes
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|a near infrared hyperspectral technology
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|a maize
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|a theoretical study
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|a light penetration depth
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|a tea sample
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|a spatial-frequency domain imaging
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|a uninformative variable elimination
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|a fruit quality monitoring
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|a bi-layer indicator
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|a multi-source information fusion
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|a chromium contamination
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|a high stability
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|a catalase activity
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|a defective apples
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|a cultivation
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|a carbimazole hydrolysate
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|a stone cell content
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|a GC-IMS
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|a tomato
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|a n/a
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|a vegetables
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|a acceptability
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|a apple
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|a microfluidic chip
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|a bruise
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|a near infrared spectroscopy
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|a volatile oil
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|a fungal spores
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|a Au@Ag nanoparticles
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|a NIR
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|a intelligent evaluation
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|a adsorption energy
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|a depth-resolved
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|a fruit diameter difference
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|a scattering
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|a Bayesian optimization algorithm
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|a gas sensor
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|a shrimp
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|a room-temperature ethylene sensor
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|a object detection
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| 653 |
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|a hot air drying
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|a YOLOv5
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|a multi-scale information fusion
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|a maize seeds
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|a extinction coefficient
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|a crop disease
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|a numerical simulation
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|a support vector regression
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|a SERS detection
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|a moldy level
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|a defect detection
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| 653 |
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|a PAEs
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|a semantic segmentation
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|a walnut kernels
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| 653 |
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|a Curcumae Longae Rhizoma
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|a convolutional neural network
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| 653 |
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|a low field magnetic resonance
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| 653 |
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|a surface-enhanced Raman spectroscopy
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|a fast determination
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|a common carp
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| 653 |
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|a flexible substrate
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| 653 |
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|a Technology, engineering, agriculture / bicssc
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| 653 |
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|a Raman
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| 653 |
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|a successive projective algorithm
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| 700 |
1 |
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|a Zhang, Zhao
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| 700 |
1 |
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|a Hu, Dong
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| 700 |
1 |
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|a Guo, Zhiming
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 024 |
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|a 10.3390/books978-3-0365-9325-8
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/128803
|z DOAB: description of the publication
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|u https://www.mdpi.com/books/pdfview/book/8270
|7 0
|x Verlag
|3 Volltext
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|a 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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