Singular spectrum analysis for improving hyperspectral imaging based beef eating quality evaluation

17 Detecting beef eating quality in a non-destructive way has been popular in recent years. 18 Among various non-destructive assessing methods, the feasibility of hyperspectral imaging 19 (HSI) system was investigated in this paper. Hyperspectral images of beef samples were 20 collected in an abattoir production line and used for predicting the beef tenderness and pH 21 value. Support vector machine (SVM) was applied to construct the prediction equation. 22 Before utilizing the original HSI spectral profiles directly, we propose to use singular 23 spectrum analysis (SSA) as a pre-processing approach, where SSA has been proven to be an 24 effective technique for time-series analysis in diverse applications. The results indicate that 25 SSA can remove the instrumental noise of HSI system effectively and therefore improve the 26 prediction performance. 27