ArticleSensors (Basel, Switzerland)2024
Prediction of Soluble-Solid Content in Citrus Fruit Using Visible-Near-Infrared Hyperspectral Imaging Based on Effective-Wavelength Selection Algorithm.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Postharvest Fruit Grading Technologies and Equipment: A Review.Foods (Basel, Switzerland) · 2026Review
- Use of Machine Learning Techniques for Fertilization Traceability Discrimination via Core Quality Indicators of Korla Fragrant Pear Fruits.Foods (Basel, Switzerland) · 2026Article
- Reconstruction-Assisted Band Selection for Non-Destructive Prediction of Citrus Soluble Solids Content from VNIR Hyperspectral Images.Foods (Basel, Switzerland) · 2026Article
- Study on Quality Detection Methods for Table Grapes Based on Spectral and Imaging Information.Sensors (Basel, Switzerland) · 2026Article
- HyperVision-HSI: a classification-guided spectral-spatial decoupling framework for adaptive multi-category fruit SSC detection.Frontiers in plant science · 2026Article
- Principles, Applications, and Future Evolution of Agricultural Nondestructive Testing Based on Microwaves.Sensors (Basel, Switzerland) · 2025Review
- Detection of Soluble Solid Content in Citrus Fruits Using Hyperspectral Imaging with Machine and Deep Learning: A Comparative Study of Two Citrus Cultivars.Foods (Basel, Switzerland) · 2025Article
- In situ nondestructive identification of citrus fruit ripeness via hyperspectral imaging technology.Plant methods · 2025Article
- Non-Destructive Detection of Chilled Mutton Freshness Using a Dual-Branch Hierarchical Spectral Feature-Aware Network.Foods (Basel, Switzerland) · 2025Article
- Relationship between optical properties and internal quality of Orah Mandarins during storage.Scientific reports · 2025Article
- Detection of Pear Quality Using Hyperspectral Imaging Technology and Machine Learning Analysis.Foods (Basel, Switzerland) · 2024Article
- Application of Hyperspectral Technology with Machine Learning for Brix Detection of Pastry Pears.Plants (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Citrus fruits were sorted based on external qualities, such as size, weight, and color, and internal qualities, such as soluble solid content (SSC), acidity, and firmness. Visible and near-infrared (VNIR) hyperspectral imaging techniques were used as rapid and nondestructive techniques for determining the internal quality of fruits. The applicability of the VNIR hyperspectral imaging technique for predicting the SSC in citrus fruits was evaluated in this study. A VNIR hyperspectral imaging system with a wavelength range of 400-1000 nm and 100 W light source was used to acquire hyperspectral images from citrus fruits in two orientations (i.e., stem and calyx ends). The SSC prediction model was developed using partial least-squares regression (PLSR). Spectrum preprocessing, effective wavelength selection through competitive adaptive reweighted sampling (CARS), and outlier detection were used to improve the model performance. The performance of each model was evaluated using the coefficient of determination (R
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