Multi-element fingerprints of muscle tissues of Eriocheir sinensis from 8 major production areas in China to promote geographical origin and food safety authentication
Year: 2025
Type: article
Abstract: Geographic traceability plays a crucial role in ensuring quality assurance, brand establishment, and sustainable development of the Eriocheir sinensis industry. This study developed an innovative workflow for origin identification of Eriocheir sinensis using multi-element fingerprints technology and evaluated associated health risks from consumption. Inductively coupled plasma mass spectrometry (ICP-MS) was used to analyze 25 elements in 335 samples of muscle tissue from eight major production areas in China, revealing significant regional differences in elemental composition. Through orthogonal partial least squares discriminant analysis (OPLS-DA), 10 variables with variable importance in projection (VIP) values >1 were selected from muscle tissue data. These were combined with linear discriminant analysis (LDA) to establish a traceability model. The model provided detailed discriminant formulas, significantly improving operability, and achieved 96.1 % classification accuracy with 94.3 % cross-validation accuracy. This workflow offers a cost-effective and user-friendly solution for origin authentication. Risk assessment based on target hazard quotients (THQs) indicated all values were below 1, suggesting no significant health risks from regular consumption. • Mineral elements in Eriocheir sinensis are profiled across 8 major production areas in China. • In the OPLS-DA, 10 origin-specific indicators of Eriocheir sinensis were identified. • A user-friendly and applicable traceability model was established for Eriocheir sinensis . • Eriocheir sinensis from 8 major production areas could be differentiated with accuracy 96.1 %. • Health risk assessments indicated that the THQ values for all eight regions were below 1.
Source: Food Chemistry X
Authors: Shuyan Bai, Ningning Du, Song Wu, Shizhan Tang, Chenhui Li, Zhongxiang Chen, Peng Wang, Lei Gao, Dongli Qin
Language: English
Topic: Heavy Metals in Plants
Subfield: Analytical Chemistry
Field: Chemistry
Domain: Physical Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $2,330
Award: G3615026946
OpenAlex ID: W4414570457
