Research Article
Effect of Spectra Correction on Water Content Prediction of Red Guava Fruit Using UV-Visible-Near Infrared Spectroscopy
@INPROCEEDINGS{10.4108/eai.11-7-2019.2297629, author={Kusumiyati Kusumiyati and Ine Elisa Putri and Yuda Hadiwijaya and Wawan Sutari and Farida Farida}, title={Effect of Spectra Correction on Water Content Prediction of Red Guava Fruit Using UV-Visible-Near Infrared Spectroscopy}, proceedings={Proceedings of the 1st International Conference on Islam, Science and Technology, ICONISTECH 2019, 11-12 July 2019, Bandung, Indonesia.}, publisher={EAI}, proceedings_a={ICONISTECH}, year={2021}, month={1}, keywords={absorbance data fruit quality nirvana ag410 respiration spectra correction}, doi={10.4108/eai.11-7-2019.2297629} }- Kusumiyati Kusumiyati
Ine Elisa Putri
Yuda Hadiwijaya
Wawan Sutari
Farida Farida
Year: 2021
Effect of Spectra Correction on Water Content Prediction of Red Guava Fruit Using UV-Visible-Near Infrared Spectroscopy
ICONISTECH
EAI
DOI: 10.4108/eai.11-7-2019.2297629
Abstract
Water content of red guava (Psidium guajava L.) can be used as an indicator of fruit texture. Determination of water content using uv-visible-near infrared spectroscopy is a non-destructive method. The research was conducted from June to September 2018 at Horticulture Laboratory, Faculty of Agriculture, Universitas Padjadjaran. The samples were 100 fresh red guava fruits. Samples were divided into 3 groups, then stored for 0 day, 4 days, and 8 days. NirVana AG410 spectrometer from 300 to 1065 nm was performed for absorbance spectra acquisition. The purpose of this research was to determine the best spectra correction to develop calibration model for predicting water content of red guava fruit. The result showed that the best spectra correction was OSC based on the value of coefficient of determination (R2), root mean squares error of calibration (RMSEC), root mean squares error of cross-validation (RMSECV) and ratio of performance to deviation (RPD). OSC displayed R2 of calibration (0.97) and validation (0.91), RMSEC (0.006), RMSECV (0.005) and RPD (3.29). This study concluded that spectra correction of OSC was able to develop the calibration model with the most reliable and accurate model for predicting water content of red guava fruit.
