Rapid and non-destructive prediction of total soluble solids of guava fruits at various storage periods using handheld near-infrared instrument

Abstract

Guava fruit is one of the most popular horticulture products because it has various health benefits. Once fruit is harvested, the fruit is still carrying out the respiration process during storage which results in changes in physical and chemical properties. One of chemical properties that is concerned by consumers is the total soluble solids, which explain the rough sugar content. The study examined the use of handheld near-infrared instruments to predict the total soluble solids of guava fruit at various storage periods rapidly and non-destructively. The research method used in this study was multivariate data analysis. Spectra pre-treatments were applied to correct the spectra and increase the accuracy of prediction. Calibration model was done by partial least squares regression (PLSR) and principal component regression (PCR). The results showed that the use of handheld near-infrared instrument was able to predict the total soluble solids of guava fruit with high accuracy. The best calibration model was produced by PLSR calibration method integrated with orthogonal signal correction (OSC) spectra pre-processing technique.