SERAG (Smart Enzymatic Reader for Agriculture Grains): A Multiplex Enzymatic Detection Kit for Rapid, On-Site Diagnosis of Mixed Stored-Grain Insect Infestations

Stored grain infestations caused by <i>Sitophilus oryzae</i>, <i>Tribolium castaneum</i>, and <i>Rhyzopertha dominica</i> contribute significantly to postharvest losses worldwide. Traditional and molecular detection methods often fall short in sensitivity, cost-efficiency, or scalability, particularly for early and mixed-species infestations. This study presents a novel, multiplexed colorimetric approach using a Smart Enzymatic Reader for Agriculture Grains (SERAG), designed to detect specific enzymatic biomarkersamylase, protease, and Chitinasesecreted by key pest species during feeding. The SERAG platform integrates three enzyme-responsive zones on a single test strip, offering dual analytical readouts: a visual color response detectable by the naked eye and a quantitative RGB-based measurement achievable via smartphone imaging under standardized lighting. Sterilized wheat grains were artificially infested with single and mixed insect populations, and aqueous extracts were analyzed using enzyme-specific and multiplexed SERAG strips. Distinct enzyme activity profiles were detected: <i>S. oryzae</i> produced rapid amylase responses; <i>T. castaneum</i> triggered high protease activity; and <i>R. dominica</i> demonstrated Chitinase release. Triple infestations generated significantly stronger and faster cumulative enzyme responses (<i>p</i> < 0.001), confirming synergistic enzymatic expression. RGB color data further enabled objective quantification and differentiation of pest profiles. SERAG strips provided clear diagnostic signatures within 30 min without laboratory instrumentation. This study presents the first trienzyme multiplex assay capable of visually and digitally distinguishing single and mixed infestations in real-time. The SERAG system is rapid, cost-effective, and field-deployable, offering a practical solution for postharvest pest management. Future development will include a smartphone application for automated RGB calibration and cloud-based data interpretation, advancing smart biosensing in grain protection and food-quality monitoring.