Determination of apple firmness using hyperspectral imaging technique and multivariate calibrations

Abstract

Hyperspectral imaging technology is applied to nondestructive quality determination of agricultural and food products. It has a greater advantage of combining spatial image and spectral measurement which can determine both external and internal quality of the product. Feasibility of using hyperspectral imaging technique and multivariate calibrations to determine apple firmness was studied. Forecasting model of apple firmness was established by effective spectral information extracted in hyperspectral image. Support vector regression (SVR) and partial least square (PLS) were applied comparatively to calibrate model. The result showed that the optimal spectral range of apple firmness was 785.11-872.45 nm. The SVR calibration model was superior to PLS model in fruit firmness determination. The correlation coefficient between the hyperspectral imaging prediction results and reference measurement results was R=0.6808 in the prediction. In conclusion, hyperspectral imaging technique can be applied to determine apple firmness.