Colloidal gold lateral flow immunoassay strips (AuNPs-LFIS) have been widely applied as qualitative diagnostic tools for point-of-care tests (POCT). If strip readers were incorporated, their use could be extended to quantitative analysis. However, their cost and non-portability render commercial strip readers unavailable for use in either home testing, community or rural hospital diagnosis. This is particularly true for on-site testing. Here, a smartphone-based reader was designed and 3D-printed for quantitatively assess AuNPs-LFIS. The basic principle of the devise was relying on a smartphone’s ambient light sensor (SPALS). This sensor was harnessed to measure the transmitted light intensities originating from the T-lines on the strips, the transmitted light intensities vary with concentration of AuNP on the T-lines. To validate this approach, our newly developed smartphone’s ambient light sensor-based reader (SPALS-reader) was used to readout AuNPs-LFIS of three analytical targets: cadmium ion (Cd²⁺; limit of detection (LOD) was 0.16 ng/mL), clenbuterol (CL; LOD was 0.046 ng/mL), and porcine epidemic diarrhea virus (PEDV; LOD was 0.055 μg/mL). The result showed good consistency with the results of conventional image analysis approaches, indicating that the smartphone-based device is appropriate for use in AuNPs-LFIS readouts. Compared with the traditional analysis method, the developed AuNPs-LFIS reader is easier operated, lower cost and more portable, which provided an on-site quantitative analysis tool for AuNPs-LFIS and enhances the applied range of AuNPs-LFIS.

胶体金侧流免疫分析条（AuNPs-LFIS）已广泛用作即时检验（POCT）的定性诊断工具。如果合并了条带阅读器，则它们的用途可以扩展到定量分析。然而，它们的成本和不可携带性使得商业的带状阅读器不能用于家庭测试，社区或乡村医院的诊断。对于现场测试尤其如此。在这里，设计了基于智能手机的阅读器并进行了3D打印，以定量评估AuNPs-LFIS。该设计的基本原理是依靠智能手机的环境光传感器（SPALS）。利用该传感器来测量源自条带上T线的透射光强度，透射光强度随T线上的AuNP浓度而变化。为了验证这种方法，²⁺ ; 检测限（LOD）为0.16 ng / mL），克仑特罗（CL; LOD为0.046 ng / mL）和猪流行性腹泻病毒（PEDV; LOD为0.055μg/ mL）。结果显示与常规图像分析方法的结果具有很好的一致性，表明基于智能手机的设备适用于AuNPs-LFIS读数。与传统的分析方法相比，所开发的AuNPs-LFIS阅读器更易于操作，成本更低，更便于携带，为AuNPs-LFIS提供了现场定量分析工具，并扩大了AuNPs-LFIS的应用范围。