Rapid and Non-Destructive Prediction of Total Soluble Solids of Guava Fruit at Various Storage Periods Using Handheld Near-Infrared Instrument
Kusumiyati*, Yuda Hadiwijaya, Ine Elisa Putri
Department of Agronomy, Faculty of Agriculture, Padjadjaran University, Sumedang 45363, Indonesia
*kusumiyati[at]unpad.ac.id
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. This 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. Spectral 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 on the model that was pre-treated by orthogonal signal correction (OSC) and calibrated using the PLSR. Coefficient of determination (R2) of calibration and validation were 0.848 and 0.722, respectively, while the root mean squares error of calibration (RMSEC) and root mean squares error of prediction (RMSEP) were 0.389 and 0.480, respectively.
Keywords: Fruit quality, intact fruit, non-destructive sensing, rapid prediction, spectroscopy
Topic: International Conference on Sustainable Agriculture