Prediction of Acidity and Brix of Red Dragon Fruit Juice Non-destructively using Transmittance Visible Near Infrared Spectroscopy

Sinaga, Virginie Ratu Margareth and Hernanda, Reza Adhitama Putra and Nugraha, Bayu and Amanah, Hanim Zuhrotul and Masithoh, Rudiati Evi (2025) Prediction of Acidity and Brix of Red Dragon Fruit Juice Non-destructively using Transmittance Visible Near Infrared Spectroscopy. In: 5th International Conference on Smart and Innovative Agriculture, ICoSIA 2024, 23 October 2024 - 24 October 2024, Yogyakarta.

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Abstract

The quality of dragon fruit juice is based on brix and acidity, which determine flavour. Brix and acidity are usually tested using sensory and titration methods, which have several limitations, such as being subjective and time-consuming. Visible-Near Infrared (Vis-NIR) spectroscopy method at a wavelength of 350-1000 nm in transmittance mode is suitable for detecting the quality of dragon fruit juice. The method is non-destructive, fast, and produces no waste. In this research, pure dragon fruit juice samples were mixed using water and liquid sugar concentrations, i.e., 10, 20, 30, 40, and 50 w/w. Spectra was obtained from a portable transmittance Vis-NIR spectrometer for dragon fruit juice, which was converted into absorbance. Actual brix and acidity were obtained using an acid and brix refractometer. Prediction models of acidity and brix content using the partial least square regression (PLSR) were constructed using actual brix and acidity values and absorbance spectra. Results showed that the PLSR models could predict Brix with R2C of 0.822, RMSEC of 3.971, RPD of 1.933, and acidity with R2C of 0.433, RMSEC of 0.583 , RPD of 1.348. The research proved that Vis-NIR spectroscopy in transmittance mode allows the prediction of the Brix content of dragon fruit juice. © The Authors, published by EDP Sciences.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Cited by: 0; Conference name: 5th International Conference on Smart and Innovative Agriculture, ICoSIA 2024; Conference date: 23 October 2024 through 24 October 2024; Conference code: 207897; All Open Access, Gold Open Access
Subjects: S Agriculture > S Agriculture (General)
Divisions: Faculty of Agricultural Technology > Agricultural and Biosystems Engineering
Depositing User: Diah Ari Damayanti
Date Deposited: 30 Dec 2025 01:00
Last Modified: 30 Dec 2025 01:00
URI: https://ir.lib.ugm.ac.id/id/eprint/24358

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