Rapid Seafood Species Identification Using Chip-Based Capillary Electrophoresis and Protein Pattern Matching

毛细管电泳 鲶鱼 微流控芯片 鱼 色谱法 计算生物学 生物 计算机科学 化学 炸薯条 渔业 电信
作者
Calvin C Walker,Cheryl L Lassitter,Shannara N Lynn,Courtney B Ford,Kevin R. Rademacher,Angela D. Ruple,Jon W. Bell
出处
期刊:Journal of AOAC International [Oxford University Press]
卷期号:100 (5): 1500-1510 被引量:5
标识
DOI:10.5740/jaoacint.17-0178
摘要

Authenticity is crucial to the seafood industry, as substitution and mislabeling have important economic, environmental, and food safety consequences. To address this problem, protein profiling and software algorithm techniques were developed to classify fish muscle samples by species. The method uses water-based protein extraction, chip-based microfluidic electrophoresis (Agilent 2100 Bioanalyzer) for the analysis of high abundance fish muscle proteins, and a novel data analysis method for species-specific protein pattern recognition. The method's performance in distinguishing commercially important fish from commonly reported substitutions was evaluated using sensitivity, specificity, and accuracy determinations with all three performance measures at >98% for common substitutions. This study demonstrates that uncooked seafood products of commercially important species of catfish, snapper, and grouper can be rapidly distinguished from commonly substituted species with a high level of confidence. A tiered testing approach to seafood species verification by sequentially applying a rapid screening method and DNA testing is proposed to more effectively ensure accurate product labeling.

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