Rapid Identification of Fritillaria Spp. Using Multi-Wavebands Spectroscopy and Multi-Source Data Fusion Strategies DOI
Yuchen Tang,

Wennan Nie,

Yao Zhang

и другие.

Опубликована: Янв. 1, 2024

Язык: Английский

A Clustering Algorithm Based on Local Relative Density DOI Open Access
Yujuan Zou, Zhijian Wang, Xiangchen Wang

и другие.

Electronics, Год журнала: 2025, Номер 14(3), С. 481 - 481

Опубликована: Янв. 24, 2025

DBSCAN and DPC are typical density-based clustering algorithms. These two algorithms have their drawbacks, such as difficulty in when there significant differences density between clusters. This study proposes a algorithm, RDBSCAN, which is based on local relative density, drawing the extension strategy of allocation mechanism DPC. The algorithm first uses k-nearest neighbors to calculate original then sorts points descending order this density. It selects point with highest from unprocessed center next cluster. Based center, RDBSCAN calculates determines core objects, performs cluster expansion. Drawing DPC, secondary for clusters that too small complete final clustering. Comparative experiments using eight other were conducted, test results show ranks performance metrics among all synthetic datasets second real-world datasets.

Язык: Английский

Процитировано

1
Rapid and accurate identification of Panax ginseng origins based on data fusion of near-infrared and laser-induced breakdown spectroscopy DOI

Jiacong Ping,

Nan Hao,

Xuting Guo

и другие.

Food Research International, Год журнала: 2025, Номер 204, С. 115925 - 115925

Опубликована: Фев. 7, 2025

Язык: Английский

Процитировано

1
Characterizing Chinese saffron Origin, Age and grade using VNlR hyperspectral imaging and Machine learning DOI

Jiahui Wu,

Jing Nie,

Hu Hao

и другие.

Food Research International, Год журнала: 2025, Номер 202, С. 115585 - 115585

Опубликована: Янв. 2, 2025

Язык: Английский

Процитировано

0
Analysis of Volatile Compounds and Vintage Discrimination of Raw Pu-erh Tea Based on GC-IMS and GC-MS Combined with Data Fusion DOI
Haoran Huang, Xinyu Chen, Ying Wang

и другие.

Journal of Chromatography A, Год журнала: 2025, Номер 1743, С. 465683 - 465683

Опубликована: Янв. 14, 2025

Язык: Английский

Процитировано

0
Data integrity of food and machine learning: Strategies, advances and prospective DOI
Chenming Li, Jieqing Li,

Yuanzhong Wang

и другие.

Food Chemistry, Год журнала: 2025, Номер unknown, С. 143831 - 143831

Опубликована: Март 1, 2025

Язык: Английский

Процитировано

0
Rapid identification of Fritillaria spp. using multi-wavebands spectroscopy and multi-source data fusion strategies DOI
Yuchen Tang,

Wennan Nie,

Yao Zhang

и другие.

Journal of Applied Research on Medicinal and Aromatic Plants, Год журнала: 2025, Номер unknown, С. 100636 - 100636

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Rapid and chemical-free technique based on hyperspectral imaging combined with artificial intelligence for monitoring quality and shelf life of dried shrimp DOI
Ubonrat Siripatrawan, Yoshio Makino

Food Research International, Год журнала: 2025, Номер unknown, С. 116422 - 116422

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
The Prediction of Kiwi Quality Attributes Based on Multi-Source Data Fusion Comprehensive Analysis Model Using HSI and FHSI DOI

Yuchen Xiao,

Dongyu Yuan, Zhiyong Zou

и другие.

Journal of Food Composition and Analysis, Год журнала: 2025, Номер unknown, С. 107645 - 107645

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0
Unraveling volatile metabolites in pigmented onion (Allium cepa L.) bulbs through HS-SPME/GC–MS-based metabolomics and machine learning DOI Creative Commons

Kaiqi Cheng,

Jin-Chang Xiao,

Jingyuan He

и другие.

Frontiers in Nutrition, Год журнала: 2025, Номер 12

Опубликована: Апрель 22, 2025

Introduction Colored onions are favored by consumers due to their distinctive aroma, rich phytochemical content, and diverse biological activities. However, comprehensive analyses of profiles volatile metabolites remain limited. Methods In this study, total phenols, flavonoids, anthocyanins, carotenoids, antioxidant activities three colored onion bulbs were evaluated. Volatile identified using headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GC-MS). Multivariate statistical analyses, feature selection techniques (SelectKBest, LASSO), machine learning models applied further analyze classify the metabolite profiles. Results Significant differences in composition observed among types. A 243 detected, sulfur compounds accounting for 51-64%, followed organic acids derivatives (4-19%). analysis revealed distinct profiles, 19 key as biomarkers. Additionally, 33 38 selected SelectKBest LASSO, respectively. The features LASSO enabled clear differentiation types via PCA, UMAP, k-means clustering. Among four tested, random forest model achieved highest classification accuracy (1.00). SHAP confirmed 20 potential markers. Conclusion findings suggest that combination HS-SPME/GC-MS learning, particularly algorithm, is a powerful approach characterizing classifying onions. This method holds quality assessment breeding applications.

Язык: Английский

Процитировано

0
Combining with acid-base titration, HPLC, ATR-FTIR and chemometrics to study the effects of sulfur fumigation on medicinal and edible starchy samples DOI
Yuchen Tang, Jianyu Zhang, Ying Xu

и другие.

Journal of Food Composition and Analysis, Год журнала: 2024, Номер 137, С. 106967 - 106967

Опубликована: Ноя. 14, 2024

Язык: Английский

Процитировано

2