ABSTRACT
Peanut is one of the prime crops for the peasants in China that helps increase their income from agriculture. This chapter aims to distinguishe the grade of peanuts based on their appearance and specifications can produce results with high accuracy rate, which can have a positive impact on the peanut industry’s productivity and development. The quality of peanut kernels is referred to every aspect of the profit of supply and marketing. A back propagation neural network model of quality grade testing and identification is built based on 52 appearance features such as the shape, texture, and color using the technology of computer image processing. The level of automation in quality testing of peanut kernels is low and most of the work is done manually. The peanut kernels exported from China needs to be long-oval, light-red coated without variegation, of no crack, of uniform color, of tidiness, and handsomeness.
