Dual-color blending based visual LAMP for food allergen detection: A strategy with enlarged color variation range and contrast

Food allergy has been a serious public health problem around the world. Its prevention relies heavily on the effective avoidance of any contaminated food, making clear and accurate detection very important. LAMP is one of the most potent methods for allergen rapid detection. However, its current colorimetric readouts usually have low color contrast and narrow color variation range. Thus, here we proposed a strategy based on color evolution to enlarge the variation range as well as the contrast to improve its suitability for naked-eye observation. By simply blending two commonly used color change processes during amplification, a wider color variation window, and a near contrast color change, purple-to-green with a hues difference of 10 were obtained. Three important allergens (walnuts, hazelnuts, and peanuts) were tested with a comparable sensitivity towards fluo-rescent real-time LAMP. Its feasibility for practical use has also been studied. This simple but effective strategy provides a new idea for the colorimetric detection of LAMP amplicons and can be applied to various fields.

Automated summary

Food allergy is a serious global public health problem, and effective prevention relies on avoiding contaminated food and accurate detection. This study proposed a strategy based on color evolution to expand the color variation range and contrast of LAMP, enhancing its suitability for naked-eye observation. Testing three important allergens demonstrated the comparable sensitivity of this strategy in real-time LAMP.