An intelligent automated system for determining peanut quality

Abstract

A decreasing labor force and consumer demands for increased food quality has initiated development of an intelligent automated system for determining peanut quality. The system under development has the goal of removing all subjectivity involved in inspecting peanuts with minimal labor input. The system currently includes damage detection, bulk and single kernel moisture determination, positive sample identification, a chemical test for aflatoxin, and automated feeding, conveying, sorting, weighing, and data recording. All components are controlled by and feedback to an expert system. An estimated 50% reduction in labor can be achieved with this system. More importantly from a quality standpoint, 100% of the subjectivity is removed when determining aflatoxin values and freeze damage. Current work focuses on improving identification of other types of kernel damage, identifying foreign materials, and integration of devices to indicate flavor.<>