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This paper presents a summary of an extensive programme of research to develop the first automated detector for insects, rodent droppings and ergot in post-harvest grain. The developed system, currently at the laboratory model stage, consists of a high-speed integrated machine vision software package used with a monochrome CCD camera and personal computer. The aim is to deliver a low-cost, high-throughput device for scanning grain in transit. Progress in extending detector capability to include grain weevil larvae hidden inside wheat kernels, by using machine vision with near-infrared imaging, is also presented.