Open AccessNon-Destructive Method for Predicting Sapodilla Fruit Quality Using Near Infrared Spectroscopy
Author(s) -
Kusumiyati Kusumiyati,
Syariful Mubarok,
Wawan Sutari,
Farida Farida,
Jajang Sauman Hamdani,
Yuda Hadiwijaya,
Ine Elisa Putri
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/334/1/012045
Subject(s) - partial least squares regression , calibration , mean squared error , near infrared spectroscopy , moisture , water content , spectroscopy , analytical chemistry (journal) , root mean square , infrared spectroscopy , absolute deviation , chemistry , mathematics , statistics , chromatography , physics , optics , geology , organic chemistry , quantum mechanics , geotechnical engineering
The non-destructive method was used to predict the moisture content, firmness, total dissolved solids, and color values (including L*, a*, b*, h ⊘ and C*) of sapodilla fruit using near infrared spectroscopy with wavelength of 312 - 1050 nm. Irradiated and measured sapodilla samples were analyzed using partial least squares (PLS) algorithm of multivariate calibration technique to build the calibration models. Validation analysis was performed to build validation models and verify the calibration models. The accuracy of the validation models were defined by the ratio performance deviation (RPD) and root mean squares error of prediction (RMSEP) values on each parameters. The RPD and RMSEP values of moisture content, firmness, total dissolved solids, L * , a * , b * , h ⊘ and C * were 1.35 (0.01), 3.82 (2.08), 2.04 (1.70), 3.32 (1.30), 3.20 (0.82), 3.41 (1.38), 3.64 (2.03) and 3.11 (1.32), respectively. The results showed that nondestructive method using near infrared spectroscopy was able predict the quality of sapodilla fruit with high accuracy and low error.