Quality Classification of Dragon Fruits Based on External Performance Using a Convolutional Neural Network

Nguyen Minh Trieu,Nguyen Truong Thinh

doi:10.3390/app112210558

Nguyen Minh Trieu, Nguyen Truong Thinh

Open Access

https://doi.org/10.3390/app112210558

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Abstract

Currently, most agricultural products in developing countries are exported to many countries around the world. Therefore, the classification of these products according to different standards is necessary. In Vietnam, dragon fruit is considered as the fruit with the highest export rate. Currently, the classification of dragon fruit is carried manually, lead to low-quality classification high labor costs. Therefore, this study describes an automatic dragon fruit classifying system using non-destructive measurements, based on a convolutional neural network (CNN). This classifying system uses a combination of a model of machine learning and image processing using a convolutional neural network to identify the external features of dragon fruits; the fruits are then classified and evaluated by groups. The dragon fruit is recognized by the system, which extracts the objects combined with the signal obtained from the loadcell to calculate and determine dragon fruit in each group. The training data are collected from the dragon fruit processing system, with a dataset of images obtained from more than 1287 dragon fruits, to train the model. In this system, the classification of the processing speed and accuracy are the two most important factors. The results show that the classification system achieves high efficiency. The system is effective with existing dragon fruit types. In Vietnamese factories, the processing speed of the system increases the sorting capacity of export packing facilities to six times higher than that of the manual method, with an accuracy of more than 96%.

Highlights

IntroductionThere are two species of dragon fruit: Hylocereus undatus (white flesh) and H. polyrhizus (red flesh)
Dragon fruit, known as pitaya, is a tropical fruit that is widely grown in about20 countries and territories in Asia, the Middle East and America, with a large concentration in the Asia-Pacific region, especially in Vietnam, Thailand, Indonesia, Philippines, Mainland China, and Taiwan, because of its appealing taste and rich nutritional properties [1].At the present time, there are two species of dragon fruit: Hylocereus undatus and H. polyrhizus
The data were enough for the system to identify the components of the dragon fruit, and to combine with the image processing method to extract features of the fruit

Summary

Introduction

There are two species of dragon fruit: Hylocereus undatus (white flesh) and H. polyrhizus (red flesh). They are widely cultivated in 63/65 provinces/cities of Vietnam; total production for export is more than a million tons [2]. The quality of dragon fruit is evaluated largely by the shape and external defects of the fruit. Dragon fruit are classified according to the standards of each different country in order to export them. The current classification is carried out by humans This process is time-consuming and its accuracy is not high. Dragon fruit is divided into different groups, depending on the weight, volume and external defects, according to the import standards of individual countries

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