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<p> Manganese nanoparticles (Mn NPs) were successfully synthesized using a cost-effective and eco-friendly biogenic approach, with <i>pinus brutia</i> pine needles<i>.</i> The produced Mn NPs were thoroughly characterized using common spectroscopic and microscopic techniques. The Mn NPs exhibited remarkable oxidase-like activity, effectively catalyzing the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) to its oxidized form (oxTMB) over a broad temperature range. This robust catalytic performance highlights their versatility and stability under varying thermal conditions, making them suitable for diverse applications. Nitrite forms orange-yellow color via diazotization of the blue oxTMB. An image processing algorithm analyzes the image changes induced by addition of nitrite. Under optimized conditions, the visual-based platform demonstrated a broad linear response for NO₂⁻ detection, spanning 0.0–58.0 uM and the detection limit was 0.11 μM. The visual method demonstrated exceptional sensitivity and recovery for nitrite detection in food samples. Combining simplicity, cost-effectiveness, and eco-friendliness, this instrument-free approach ensures accurate, portable, and point-of-care nitrite detection, ideal for real-world food testing applications.</p> Graphical Abstract <p></p>

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Pine needle-derived oxidase-like Mn nanozymes: sustainable nanozyme, scalable synthesis, and visual and colorimetric nitrite detection

  • 期刊论文

  • 发表日期：

    2025年2月11日

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  • Sameera Sh. Mohammed Ameen,
  • Faisal Algethami,
  • Khalid M. Omer

摘要

Manganese nanoparticles (Mn NPs) were successfully synthesized using a cost-effective and eco-friendly biogenic approach, with pinus brutia pine needles. The produced Mn NPs were thoroughly characterized using common spectroscopic and microscopic techniques. The Mn NPs exhibited remarkable oxidase-like activity, effectively catalyzing the oxidation of 3,3′,5,5′-tetramethylbenzidine (TMB) to its oxidized form (oxTMB) over a broad temperature range. This robust catalytic performance highlights their versatility and stability under varying thermal conditions, making them suitable for diverse applications. Nitrite forms orange-yellow color via diazotization of the blue oxTMB. An image processing algorithm analyzes the image changes induced by addition of nitrite. Under optimized conditions, the visual-based platform demonstrated a broad linear response for NO₂⁻ detection, spanning 0.0–58.0 uM and the detection limit was 0.11 μM. The visual method demonstrated exceptional sensitivity and recovery for nitrite detection in food samples. Combining simplicity, cost-effectiveness, and eco-friendliness, this instrument-free approach ensures accurate, portable, and point-of-care nitrite detection, ideal for real-world food testing applications.

Graphical Abstract