Application of hyperspectral imaging technology for rapid identification of Ruditapes philippinarum contaminated by heavy metals

Human beings are confronted with a serious health hazard when ingesting Ruditapes philippinarum contaminated with heavy metals, and thus it is significantly necessary to identify heavy metal contaminated Ruditapes philippinarum. This study investigates the feasibility of hyperspectral imaging to ide...

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Veröffentlicht in:	RSC advances 2021-10, Vol.11 (54), p.33939-33951
Hauptverfasser:	Liu, Yao, Qiao, Fu, Wang, Shuwen, Wang, Runtao, Xu, Lele
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Chemistry Chemistry, Multidisciplinary Contamination Feasibility studies Health hazards Heavy metals Hyperspectral imaging Machine learning Metals Pattern analysis Pattern recognition Physical Sciences Pretreatment Science & Technology Set theory Shellfish Technology assessment Training
Online-Zugang:	Volltext
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