Determination of Astringent Fruit in ‘Le Lectier’ Pears Using Visible and Near-infrared Spectroscopy and Neural Network

Abstract

It is impossible to distinguish the astringent fruit in ‘Le Lectier’ pears by visual inspection. This study aimed to develop nondestructive determination of the astringent fruit and quality assurance of the intact fruit using neural network classification, visible and near-infrared spectroscopy. For this study, 51 pears harvested in Sanjo City and 46 pears harvested in the Tsukigata area of Niigata City, 97 pears in all were collected. The recognition ratio was established by neural network learning and validation repeatedly using leave-one-out cross validation. The average recognition ratio was 81.1 % when the neural network was discussed using 15 hidden layer units and set an error goal to 0.11 and calculated by 10 times cross validation.