The application discloses a method for detecting and controlling the quality of pseudo-detection of
Corydalis ambigua, and belongs to the field of pseudo-detection screening. The method comprises the following steps: collecting
Corydalis ambigua samples, pseudo-product
Thalictrum petaloideum samples and THz
absorbance spectrum data of
Thalictrum petaloideum under different pseudo-detection concentrations (5%-75%); preprocessing the spectrum data by using a Tukey
window function; extracting features by using a UMAP
algorithm; inputting the extracted
feature matrix into a DCNN classifier to qualitatively identify
Corydalis ambigua and
Thalictrum petaloideum; and simultaneously, in order to improve the quantitative prediction accuracy of the pseudo-detection concentration, combining a SPXY
algorithm and an XGBoost regression model to divide samples and predict the concentration. The above method provides a reliable and practically applicable technical means for the field of pseudo-detection of
Corydalis ambigua. The high accuracy and efficiency of the method make it have a wide application prospect in the moderate discrimination of pseudo-detection of
Corydalis ambigua and related fields.