A five band near-infrared portable sensor in nondestructively predicting the internal quality of pineapples

Abstract

The determination of the fruit taste and grade depends on the internal quality of the fruit such as total soluble content, pH, and acidity. This paper investigates the feasibility of a non-destructive method to classify the internal quality of the pineapples using near infrared light and artificial neural network. Five near infrared light emitting diodes (LEDs) were used as the light source to emit near infrared light. A photodiode was used to measure the intensity of the reflected near infrared light from pineapples. The data of the acquired near infrared light were used to classify the internal quality of the pineapple using neural network. The random seed and the hidden neurons of the neural network were optimised to maximise the classification accuracy. Findings indicate that the neural network with seven hidden neurons was capable of achieving 30% misclassification.