ReviewMolecules (Basel, Switzerland)2021
A Review of the Discriminant Analysis Methods for Food Quality Based on Near-Infrared Spectroscopy and Pattern Recognition.
Review in Molecules (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Visible and near-infrared spectroscopic method for correlative joint tissue analysis and visual and histologic grading.MethodsX · 2026Article
- Methodologies for Assessing Chemical Toxicity to Aquatic Microorganisms: A Comparative Review.Molecules (Basel, Switzerland) · 2026Review
- Improving nitrogen use efficiency in rice by estimating leaf nitrogen content with near-infrared spectroscopy and chemometric modeling.Scientific reports · 2025Article
- Quinolizidine Alkaloid Composition of White Lupin Landraces and Breeding Lines, and Near-Infrared Spectroscopy-Based Discrimination of Low-Alkaloid Material.Plants (Basel, Switzerland) · 2025Article
- Non-Destructive Detection of Fruit Quality: Technologies, Applications and Prospects.Foods (Basel, Switzerland) · 2025Review
- Application of Fourier Transform Near-Infrared Spectroscopy and Chemometrics for Quantitative Analysis of Milk of Lime (MOL) Used in the Sugar Industry.Molecules (Basel, Switzerland) · 2025Article
- Article
- Discriminating Mung Bean Origins Using Pattern Recognition Methods: A Comparative Study of Raman and NIR Spectroscopy.Foods (Basel, Switzerland) · 2025Article
- Fingerprinting of Green Arabica Coffee Volatile Organic Compounds (VOCs): HS-GC-IMS Versus GC × GC-MS.International journal of food science · 2025Article
- Developing a prediction model in a lightweight packaging waste sorting plant using sensor-based sorting data combined with data of external near-infrared and LiDAR sensors.Waste management & research : the journal of the International Solid Wastes and Public Cleansing Association, ISWA · 2024Article
- NIR sensors combined with chemometric algorithms in intelligent quality evaluation of sweetpotato roots from 'Farm' to 'Table': Progresses, challenges, trends, and prospects.Food chemistry: X · 2024Review
- Application of flash GC e-nose and FT-NIR combined with deep learning algorithm in preventing age fraud and quality evaluation of pericarpium citri reticulatae.Food chemistry: X · 2024Article
- Automated detection and recognition system for chewable food items using advanced deep learning models.Scientific reports · 2024Article
- Efficient Near-Infrared Spectrum Detection in Nondestructive Wood Testing via Transfer Network Redesign.Sensors (Basel, Switzerland) · 2024Article
- Article
- Differentiation of Goat Meat Freshness Using Gas Chromatography with Ion Mobility Spectrometry.Molecules (Basel, Switzerland) · 2023Article
- Vis-NIR Spectroscopy Combined with GAN Data Augmentation for Predicting Soil Nutrients in Degraded Alpine Meadows on the Qinghai-Tibet Plateau.Sensors (Basel, Switzerland) · 2023Article
- Antioxidant Activity Enhancement Effect of Silver-Ionized Water: Silver Cation Prepared by Electrolysis.Antioxidants (Basel, Switzerland) · 2023Article
- Application of Near Infrared Spectroscopy to Monitor the Quality Change of Sour Cherry Stored under Modified Atmosphere Conditions.Sensors (Basel, Switzerland) · 2023Article
- Pretreatment to terahertz absorption curves by narrow undulation constraint and Its quick implementation suggested by convex hull.Scientific reports · 2022Article
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9 authors.
Funding
Abstract
Near-infrared spectroscopy (NIRS) combined with pattern recognition technique has become an important type of non-destructive discriminant method. This review first introduces the basic structure of the qualitative analysis process based on near-infrared spectroscopy. Then, the main pretreatment methods of NIRS data processing are investigated. Principles and recent developments of traditional pattern recognition methods based on NIRS are introduced, including some shallow learning machines and clustering analysis methods. Moreover, the newly developed deep learning methods and their applications of food quality analysis are surveyed, including convolutional neural network (CNN), one-dimensional CNN, and two-dimensional CNN. Finally, several applications of these pattern recognition techniques based on NIRS are compared. The deficiencies of the existing pattern recognition methods and future research directions are also reviewed.
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