ArticleScientific reports2019
Prediction of various freshness indicators in fish fillets by one multispectral imaging system.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Quality Assessment in Frozen Seafood: Advances in Sensing Technologies and Artificial Intelligence.Foods (Basel, Switzerland) · 2026Review
- Predicting the Freshness of Starch-Coated Snakehead Fish Fillets During Storage Using Hyperspectral Imaging Combined with Transfer Learning.Foods (Basel, Switzerland) · 2026Article
- Transformative artificial intelligence integration in aquatic supply chains: synergizing precision aquaculture with intelligent logistics and data-driven consumption.Food chemistry: X · 2026Review
- A Deep Learning-Based Sensing System for Identifying Salmon and Rainbow Trout Meat and Grading Freshness for Consumer Protection.Sensors (Basel, Switzerland) · 2025Article
- Near-Infrared Spectroscopy Detection of Off-Flavor Compounds in Tench (Foods (Basel, Switzerland) · 2025Article
- Quality Differences in Frozen Mackerel According to Thawing Method: Potential Classification via Hyperspectral Imaging.Foods (Basel, Switzerland) · 2024Article
- Prediction and Visualization of Total Volatile Basic Nitrogen in Yellow Croaker (Foods (Basel, Switzerland) · 2024Article
- Line Laser Scanning Combined with Machine Learning for Fish Head Cutting Position Identification.Foods (Basel, Switzerland) · 2023Article
- Quality Evaluation of Mackerel Fillets Stored under Different Conditions by Hyperspectral Imaging Analysis.Food science of animal resources · 2023Article
- Determination of Freshness of Mackerel (Foods (Basel, Switzerland) · 2023Article
- Rapid Assessment of Fish Freshness for Multiple Supply-Chain Nodes Using Multi-Mode Spectroscopy and Fusion-Based Artificial Intelligence.Sensors (Basel, Switzerland) · 2023Article
- Non-destructive detection of protein content in mulberry leaves by using hyperspectral imaging.Frontiers in plant science · 2023Article
- Prediction of storage time in different seafood based on color values with artificial neural network modeling.Journal of food science and technology · 2022Article
- Large volume headspace GC/MS analysis for the identification of volatile compounds relating to seafood decomposition.Food science & nutrition · 2022Article
- Applications of Fluorescence Spectroscopy, RGB- and MultiSpectral Imaging for Quality Determinations of White Meat: A Review.Biosensors · 2022Review
- Advances in Machine Learning and Hyperspectral Imaging in the Food Supply Chain.Food engineering reviews · 2022Review
- Implementation of Whale Optimization for Budding Healthiness of Fishes with Preprocessing Approach.Journal of healthcare engineering · 2022Review
- Article
- Evaluation of the total volatile basic nitrogen (TVB-N) content in fish fillets using hyperspectral imaging coupled with deep learning neural network and meta-analysis.Scientific reports · 2021Article
- Sensing Technology for Fish Freshness and Safety: A Review.Sensors (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In current study, a simple multispectral imaging (430-1010 nm) system along with linear and non-linear regressions were used to assess the various fish spoilage indicators during 12 days storage at 4 ± 2 °C. The indicators included Total-Volatile Basic Nitrogen (TVB-N) and Psychrotrophic Plate Count (PPC) and sensory score in fish fillets. immediately, after hyperspectral imaging, the reference values (TVB-N, PPC and sensory score) of samples were obtained by traditional method. To simplify the calibration models, nine optimal wavelengths were selected by genetic algorithm. The prediction performance of various chemometric models including partial least-squares regression (PLSR), multiple-linear regression (MLR), least-squares support vector machine (LS-SVM) and back-propagation artificial neural network (BP-ANN) were compared. All models showed acceptable performance for simultaneous predicting of PPC, TVB-N and sensory score (R
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.