Rapid pesticide residues detection by portable filter-array hyperspectral imaging.

Abstract

The detection of pesticide residues in agricultural products is crucial for ensuring food safety. However, traditional methods are often constrained by slow processing speeds and a restricted analytical scope. This study presents a novel method that uses filter-array-based hyperspectral imaging enhanced by a dynamic filtering demosaicking algorithm, which significantly improves the speed and accuracy of detecting pesticide residues. Our approach enhances the spatial and spectral resolution of hyperspectral images, thereby providing a rapid and cost-effective alternative to conventional methods with an image integration time of 20 ms. Tested on both synthetic datasets and real agricultural samples, this technology demonstrates superior performance under high noise conditions and exceptional precision in spectral reconstruction at critical color edges. The practicality of this system is demonstrated by integrating a hyperspectral microfilter array with a smartphone's imaging sensor, thereby showcasing the feasibility of deploying this advanced detection technology in everyday portable devices for quick and convenient monitoring of pesticide residues.