Electrochemical biosensors for Atrazine detection as a highly toxic Triazine in wastewater
Publish Year: 1401
نوع سند: مقاله ژورنالی
زبان: English
View: 200
This Paper With 8 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
JR_ARWW-9-1_002
تاریخ نمایه سازی: 6 تیر 1401
Abstract:
Widespread use of pesticides and herbicides, and the contamination in river, lake and sea waters have been become a major environmental concern in recent years. A common example of such herbicides is atrazine and its derivatives, which have been widely used in recent years to control pests in agriculture and improve food production and meet the needs of the global population, which is increasing year by year. Most analytical methods are used to determine pesticides and herbicides in the environment which are usually highly reliable and sensitive, but they are often very complex and require advanced tools, and measurements should be performed directly in a lab. Atrazine electrochemical biosensors based on enzymatic biosensors, immunosensors, and aptasensors are reviewed in this study. For atrazine detection by enzymatic biosensors, tyrosinase commonly is used. Phenols and atrazine are the substrates and inhibitor of this enzyme, respectively. These enzymatic biosensors are based on sensing of decreasing current in the presence of atrazine. Immunosensors based on the analyte size generally categorized into two detection methods including competitive and noncompetitive that both of them were used for atrazine detection. The several aptamer sequences were used for atrazine aptasensing that could detect it in nano and picomolar concentrations.
Keywords:
Authors
Maryam Nazari
Department of Applied Chemistry, Faculty of Chemistry, Razi University, Kermanshah, Iran
Zahra Mohebi
۲Department of Natural Resources, Faculty of Agricultural Sciences & Natural Resources, Razi University, Kermanshah, Iran.
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :