ArticleFoods (Basel, Switzerland)2024
Garlic Origin Traceability and Identification Based on Fusion of Multi-Source Heterogeneous Spectral Information.
Article in Foods (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Comprehensive volatile profiling and metabolomics analysis of cowpea.Food chemistry: X · 2026Article
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- Construction and optimization of quantitative analysis models for pigments in broccoli (Food chemistry: X · 2025Article
- Long-Term Year-Interval Effect of Continuous Maize/Soybean Intercropping on Maize Yield and Phosphorus Use Efficiency.Plants (Basel, Switzerland) · 2025Article
- Impact of tillage and fertilizer management on Soybean-Cotton rotation system: effects on yield, plant nutrient uptake, and soil fertility for sustainable agriculture.Scientific reports · 2025Article
- Remote sensing-based maize growth process parameters revel the maize yield: a comparison of field- and regional-scale.BMC plant biology · 2025Article
- Optical band gap modulation in functionalized chitosan biopolymer hybrids using absorption and derivative spectrum fitting methods: A spectroscopic analysis.Scientific reports · 2025Article
- Prediction of air temperature and humidity in greenhouses via artificial neural network.PloS one · 2025Article
- Identification of rice leaf disease based on DepMulti-Net.Frontiers in plant science · 2025Article
- Development and laboratory evaluation of a novel IoT-based electric-driven metering system for high precision garlic planter.PloS one · 2025Article
- TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection.Frontiers in plant science · 2025Article
- Anthocyanin profiles and color parameters of fourteen grapes and wines from the eastern foot of Helan Mountain in Ningxia.Food chemistry: X · 2024Article
- Understanding the triacylglycerol-based carbon anabolic differentiation in Cyperus esculentus and Cyperus rotundus developing tubers via transcriptomic and metabolomic approaches.BMC plant biology · 2024Article
- Plant Microbe Interaction-Predicting the Pathogen Internalization Through Stomata Using Computational Neural Network Modeling.Foods (Basel, Switzerland) · 2024Article
- Enhancing plant disease detection through deep learning: a Depthwise CNN with squeeze and excitation integration and residual skip connections.Frontiers in plant science · 2024Article
- What the fish? Tracing the geographical origin of fish using NIR spectroscopy.Current research in food science · 2024Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The chemical composition and nutritional content of garlic are greatly impacted by its production location, leading to distinct flavor profiles and functional properties among garlic varieties from diverse origins. Consequently, these variations determine the preference and acceptance among diverse consumer groups. In this study, purple-skinned garlic samples were collected from five regions in China: Yunnan, Shandong, Henan, Anhui, and Jiangsu Provinces. Mid-infrared spectroscopy and ultraviolet spectroscopy were utilized to analyze the components of garlic cells. Three preprocessing methods, including Multiple Scattering Correction (MSC), Savitzky-Golay Smoothing (SG Smoothing), and Standard Normalized Variate (SNV), were applied to reduce the background noise of spectroscopy data. Following variable feature extraction by Genetic Algorithm (GA), a variety of machine learning algorithms, including XGboost, Support Vector Classification (SVC), Random Forest (RF), and Artificial Neural Network (ANN), were used according to the fusion of spectral data to obtain the best processing results. The results showed that the best-performing model for ultraviolet spectroscopy data was SNV-GA-ANN, with an accuracy of 99.73%. The best-performing model for mid-infrared spectroscopy data was SNV-GA-RF, with an accuracy of 97.34%. After the fusion of ultraviolet and mid-infrared spectroscopy data, the SNV-GA-SVC, SNV-GA-RF, SNV-GA-ANN, and SNV-GA-XGboost models achieved 100% accuracy in both training and test sets. Although there were some differences in the accuracy of the four models under different preprocessing methods, the fusion of ultraviolet and mid-infrared spectroscopy data yielded the best outcomes, with an accuracy of 100%. Overall, the combination of ultraviolet and mid-infrared spectroscopy data fusion and chemometrics established in this study provides a theoretical foundation for identifying the origin of garlic, as well as that of other agricultural products.
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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.