ArticleSensors (Basel, Switzerland)2020
Application of Convolutional Neural Network-Based Feature Extraction and Data Fusion for Geographical Origin Identification of Radix Astragali by Visible/Short-Wave Near-Infrared and Near Infrared Hyperspectral Imaging.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Spectroscopic technologies and data fusion: Applications for the dairy industry.Frontiers in nutrition · 2022Pooled it
- Rapid discrimination of geographical origin and analysis of chemical characterization of tobacco leaves from multiple countries.Frontiers in chemistry · 2026Article
- Construction and interpretation of tobacco leaf position discrimination model based on interpretable machine learning.Frontiers in plant science · 2025Article
- Progress in the application of hyperspectral imaging technology in quality detection and in the modernization of Chinese herbal medicines.Frontiers in chemistry · 2025Review
- Non-destructive analysis ofFrontiers in chemistry · 2025Article
- Hyperspectral reflectance imaging for visualizing reducing sugar content, moisture, and hollow rate in red ginseng.Heliyon · 2024Article
- Early diagnosis of Cladosporium fulvum in greenhouse tomato plants based on visible/near-infrared (VIS/NIR) and near-infrared (NIR) data fusion.Scientific reports · 2024Article
- Application of Data Fusion in Traditional Chinese Medicine: A Review.Sensors (Basel, Switzerland) · 2023Review
- The Identification ofFoods (Basel, Switzerland) · 2023Article
- Development status of novel spectral imaging techniques and application to traditional Chinese medicine.Journal of pharmaceutical analysis · 2023Review
- Machine learning applications for multi-source data of edible crops: A review of current trends and future prospects.Food chemistry: X · 2023Review
- The Image Definition Assessment of Optoelectronic Tracking Equipment Based on the BRISQUE Algorithm with Gaussian Weights.Sensors (Basel, Switzerland) · 2023Article
- Application of Near-Infrared Spectroscopy and Hyperspectral Imaging Combined with Machine Learning Algorithms for Quality Inspection of Grape: A Review.Foods (Basel, Switzerland) · 2022Review
- Early warning and diagnostic visualization of Sclerotinia infected tomato based on hyperspectral imaging.Scientific reports · 2022Article
- Identification of Near Geographical Origin of Wolfberries by a Combination of Hyperspectral Imaging and Multi-Task Residual Fully Convolutional Network.Foods (Basel, Switzerland) · 2022Article
- Visible and near-infrared spectroscopy and deep learning application for the qualitative and quantitative investigation of nitrogen status in cotton leaves.Frontiers in plant science · 2022Article
- Hyperspectral imaging with machine learning for non-destructive classification ofFrontiers in plant science · 2022Article
- Evaluation of processing mechanism in Astragali Radix by low-field nuclear magnetic resonance and magnetic resonance imaging.PloS one · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Radix Astragali is a prized traditional Chinese functional food that is used for both medicine and food purposes, with various benefits such as immunomodulation, anti-tumor, and anti-oxidation. The geographical origin of Radix Astragali has a significant impact on its quality attributes. Determining the geographical origins of Radix Astragali is essential for quality evaluation. Hyperspectral imaging covering the visible/short-wave near-infrared range (Vis-NIR, 380-1030 nm) and near-infrared range (NIR, 874-1734 nm) were applied to identify Radix Astragali from five different geographical origins. Principal component analysis (PCA) was utilized to form score images to achieve preliminary qualitative identification. PCA and convolutional neural network (CNN) were used for feature extraction. Measurement-level fusion and feature-level fusion were performed on the original spectra at different spectral ranges and the corresponding features. Support vector machine (SVM), logistic regression (LR), and CNN models based on full wavelengths, extracted features, and fusion datasets were established with excellent results; all the models obtained an accuracy of over 98% for different datasets. The results illustrate that hyperspectral imaging combined with CNN and fusion strategy could be an effective method for origin identification of Radix Astragali.
Indexed as
Identifiers
What Socratic holds
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 Socratic graph.