Introduction Pesticide contamination has severely attacked the ecosystem and food safety, gradually becoming an escalating threat to public health [1]. Current laboratory-based pesticides-analyzing conventional apparatus comprising of chromatography [2] and mass spectrometry [3] with satisfactory precision and resolution were limited by on-site monitoring. Hence, the development of convenient sensors for pesticide is of great significance. Herein, we constructed a handheld smartphone-assisted fluorometric platform for on-site quantification of pesticide with excellent selectivity and high selectivity based on the optical features of red-emission carbon dots (CDs) and signal amplification of alkaline phosphatase (ALP). The red emissive CDs whose maximum emission center was located at 605 nm with high stability could shield photodamage and autofluorescence interference and enhance anti-interference capability toward matrix. For accurate quantification, the corresponding images were captured by smartphone, together with 3D-printed auxiliary equipment. Using a self-designed application, color intensity was directly relevant to the concentration of analyte pesticide. It is believed that the proposed smartphone-based handheld platform could afford experience for designing neotype sensing strategy in pesticides monitoring. Method For smartphone-based quantitative analysis 2, 4-D, 50 μL various concentrations of 2, 4-D and 50 μL of ALP (7.0 U L-1) were equilibrated at 37 ºC for 10 min. Following, 120 μL of ascorbic acid-2-phosphate trisodium salt (AAP) (100 μmol L-1) containing Tris-HCl buffer were added for incubating another 10 min at 37 ºC and 160 μL CDs/CoOOH composite solution was added to the mixture. After equilibrated for 10 min, the cuvette was inserted into the 3D-printed smartphone reader to obtain the FL photo under the excitation of 532 nm laser. Then, the displayed photo image was directly analyzed by App installed on smartphone. Results and Conclusions Given the design and exploration above, we can directly detect 2, 4-D concentrations in real-time by collecting the optical image of sample. The collected images brightness of the probe solution was in negative connection with 2, 4-D concentrations. Coupling with the FCSMP software, the smartphone readout gray values of various analyte concentrations were acquired in Figure 1. The linear relationship (R2 = 0.990) between smartphone readout gray value and the concentration of 2, 4-D was I = 46.14825 – 2.26776 [2, 4-D], with a LOD of 100 μg L-1 (3σ). Although weaker than the FL spectrometry method on the basis of identical system, that the integrated smartphone-connected sensor displayed comparable liner range and LOD compared with other reported methods was worth noting. The results of 2, 4-D detection demonstrated that the smartphone-assisted fluorometric sensing platform possessed a low requirement for sample volume (50 μL), rapid (30 min) and easy readouts for POC testing.In summary, we have constructed an innovative and portable smartphone-based POC platform for precise quantification of 2, 4-D in a good sensitivity and excellent selectivity manner based on CDs/CoOOH composite. Employing CDs/CoOOH composite as signal indicator, a simple but potentially promising biosensor with outstanding anti-interference capability and good sensitivity have been established. The anti-interference ability was ascribed to the red emissive CDs that could shield background interference. In virtue of introducing ALP, the biosensor performed specific recognition capacity toward 2, 4-D, endowing it high-performance of selectivity. The proposed approach which integrated commercial smartphone, 3D model smartphone accessory and self-designed App into one platform simplified image processing and minimized detection device, effectively circumventing the drawback of bulk instrument with inaccessibility in carrying and complex computer-assistant data analysis. More significantly, the sample-to-answer analysis time of smartphone-based platform is 30 minutes, which was shorter or comparable than that of the immunoassay, chromatograph and enzyme-based strategies. What’s more, such a smartphone optical-sensing system has been triumphantly applied to biological and environmental samples, indicating its robust performance in biological/chemical analysis. Thus, the proposed smartphone-based handheld device provided a promising platform for on-site monitoring pesticide, possessing potential applications in environmental screening, health monitoring, and disease prevention.