Non-destructive estimation of firmness of strawberries (Fragaria × ananassa Duch.) using NIR hyperspectral imaging

Abstract

The non-destructive estimation of internal quality of fruits for on-line grading to achieve higher product consistency and enhanced safety will greatly benefit the consumer and the fruit industry as a whole. This research was aimed at developing prediction models for firmness in strawberries (Fragaria × ananassa Duch.) using NIR hyperspectral imaging. From freshly harvested strawberries of "Akihime" variety at three levels of ripeness maturity, NIR (near infrared) hyperspectral images (650 to 1000 nm at 5 nm intervals) were taken and calibration models were developed using stepwise multiple linear regression. The three-wavelength (685, 865, and 985 nm) prediction model for firmness had a correlation and standard error for prediction of 0.786 and 0.350 MPa, respectively (50% to full-ripe group). The importance of chlorophyll absorbance peak at around 680 nm and peak of water at 980 nm was also confirmed.