Identification system for beeswax on Malang apple using VNIR imaging

Naufal Praditya, Adhi Harmoko Saputro

Research output: Contribution to journalConference articlepeer-review

Abstract

Wax coating identification on fruits is very difficult without a non-destructive method. In general, destructive methods were used to identify wax or coatings by soaking the fruit in hot water or using a mixture of vinegar and water. There are also destructive systems that was used such as gas chromatography linked with mass spectrometry, but this method takes much time and difficult to operate. Visible Near Infrared Imaging (VNIR) becomes the alternate solution to identify wax on the surface of the fruit without spoiling the quality of the fruit. In this study, identification system for beeswax application on apples has been made successfully. The process starts through image acquisition, image correction, object detection, window averaging, classification model, and the coating status. The VNIR image was acquired on a wavelength range from 400 to 1000 nm. The data was divided for training and testing the classification model using cross-validation method, then the model was evaluated using confusion matrix. Several classification models were used to compare the result and to conclude which model gives the best accuracy for identification and classification problems. The accuracy of the three models were 72.92% for PCA-SVM model, 81.25% for DT model, and 91.67% for RF model.

Original languageEnglish
Article number012037
JournalJournal of Physics: Conference Series
Volume1528
Issue number1
DOIs
Publication statusPublished - 9 Jun 2020
Event4th International Seminar on Sensors, Instrumentation, Measurement and Metrology, ISSIMM 2019 - Padang, West Sumatera, Indonesia
Duration: 14 Nov 201914 Nov 2019

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