Open AccessAgricultural products quality determination by means of near infrared spectroscopy
Author(s) -
Agus Arip Munawar,
Z Zulfahrizal,
Rita Hayati,
Syahrul Syahrul
Publication year - 2022
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/951/1/012112
Subject(s) - coefficient of determination , near infrared spectroscopy , principal component analysis , chemometrics , raw material , second derivative , correlation coefficient , analytical chemistry (journal) , chemistry , standard deviation , infrared spectroscopy , environmental science , mathematics , statistics , chromatography , biology , mathematical analysis , organic chemistry , neuroscience
Cocoa is one of main agricultural products cultivated in many tropical countries and processed onto several derivative products. To determine cocoa beans qualities, laboratory procedures based on solvent extractions were mainly used, however most of them are destructive and may cause environmental pollutions. The main purpose of this present study is to employ near infrared spectroscopy (NIRS) for rapid and non-destructive assessment of cocoa beans in form of fat content. Near infrared spectral data of cocoa bean samples were measured as diffuse reflectance in wavelength range from 1000 to 2500 nm. Reference fat contents were measured using standard laboratory methods. Prediction models were developed using principal component regression with raw and baseline corrected spectra data. The results showed that fat contents of cocoa beans can be predicted and determined with maximum correlation coefficient (r) of 0.89 and ratio prediction to deviation (RPD) index of 2.87 for raw spectra and r of 0.91, RPD of 3.18 for baseline spectra correction. It may conclude that NIRS was feasible to be applied as a rapid and non-destructive method for cocoa bean quality assessment.