Optimization of Acetylcholinesterase and Sucrose Concentration using Response Surface Methodology (RSM) Approach in the Development of Paper-Based Biosensor for Pesticides Detection

Excessive use of pesticides, particularly organophosphate pesticides (OPs), to increase agricultural productivity may give a risk to consumers if consumed as these pesticides are neurotoxic substances. To increase agricultural productivity, fruits and vegetables are frequently treated with excessive pesticides, particularly organophosphate pesticides (OPs). Several methods have been studied and developed to identify pesticide residue in crops, however the standard laboratory procedures for OPs analysis involves the use of HPLC or GC-MS. These methods are complex in sample preparation and require expert labor to operate. Paper-based biosensors are low-cost platforms for fast detection in the field, offering an easy and reusable option. In this study, a colorimetric paper-based biosensor based on immobilizing acetylcholinesterase (AChE) using sol-gel silica matrices and indoxyl acetate is developed. The Response Surface Methodological (RSM) approach was used to optimize AChE concentration and sucrose as a stabilizer, allowing simultaneous optimization of multiple variables using smaller-size datasets. This study used the central composite design (CCD) fractional factorial design using Design Expert 7.0 software. A quadratic model was selected to represent both immobilization yield and relative AChE activity responses. The model was evaluated using ANOVA values and Lack of Fit test which confirmed that the quadratic models for both responses are suitable for experimental data. Validation of the model demonstrates that the predictive model accurately represents of the validation research. The Limit of Detection (LoD) of the biosensor for pure profenofos pesticide after a 20-minute incubation time is 1 ppm, as indicated by a 32.55 % decrease in color intensity. After a week of storage at 4 °C, the biosensor showed a loss of 5.92 % on immobilization yield and 2.55 % on relative activity indicating a good storage stability. The mean value of lettuce samples was 200.60 ± 1.2 a.u, with pesticide concentration of 2.57 ± 1.2 ppm (n=3). HIGHLIGHTS Incorporating AChE into the sol gel matrices is a great way to enhance the stability of the enzymatic colorimetric pesticide detection. Response Surface Methodology (RSM) is considered as useful for optimizing response level of AChE and sucrose. Combination of optimum AChE and sucrose concentration show beneficial effect on the stability of the biosensor. GRAPHICAL ABSTRACT