Engineering Commons^™

Application Of Hyperspectral Imaging And Acoustic Emission Techniques For Apple Quality Prediction, Nader Ekramirad, Ahmed Rady, Akinbode A. Adedeji, Reza Alimardani

Biosystems and Agricultural Engineering Faculty Publications

There is a growing demand for developing effective non-destructive quality assessment methods with quick response, high accuracy, and low cost for fresh fruits. In this study, hyperspectral reflectance imaging (400 to 1000 nm) and acoustic emission (AE) tests were applied to ‘GoldRush‘ apples (total number, n = 180) to predict fruit firmness, total soluble solids (TSS), and surface color parameters (L*, a*, b*) during an eight-week storage period. Partial least squares (PLS) regression, least squares support vector machine (LS-SVM), and multivariate linear regression (MLR) methods were used to establish models to predict the quality attributes of the apples. The results …