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Visualization Of Lamb Adulteration Based On Hyperspectral Imaging For Non-Destructive Quantitative Detection, Zhao Jing-Yuan, Zhang Jun-Qin, Sun Mei, Chen Xing-Hai, Liu Ye-Lin

Food and Machinery

Objective: This study aimed to establisha rapid and accurate prediction method of lamb adulteration by using visible/near-infrared (400~1 000 nm) and short-wave near-infrared (900~1 700 nm) hyperspectral imaging techniques.Methods: The data acquisition of lamb adulterated with different proportions of duck meat using visible/near-infrared (400~1 000 nm) and short-wave near-infrared (900~1 700 nm) hyperspectral imagers was performed to compare the effect of partial least squares (PLS) modeling with different spectral preprocessing methods in the two band ranges. Then the normalized preprocessing method was selected in the visible-NIR band, and the standard normal variate transformation (SNV) preprocessing method was …