The application discloses a nondestructive detection method for biological amine of
Spanish mackerel based on Raman spectrum technology, and belongs to the technical field of food nondestructive detection. ‑1 The method first cuts fresh
Spanish mackerel into pieces and refrigerates the pieces for different lengths of time to prepare different freshness samples, collects Raman spectra of the samples in the range of 400-2000 cm ‑1 under 532nm
laser light, simultaneously determines the
histamine,
putrescine and
cadaverine content in the samples by HPLC, carries out
principal component analysis on the spectrum baseline correction and normalization, realizes accurate classification of the freshness of
Spanish mackerel by combining LDA, SVM and RF
machine learning models, the accuracy of the SVM model reaches 100%, the spectrum characteristic variables are screened by CARS, PLSR and SVR regression models are established, and accurate quantification of the three core biological amine is realized, and the prediction correlation coefficients are all higher than 0.9. The application is nondestructive, rapid and convenient to operate, improves the early warning sensitivity of Spanish
mackerel corruption, can effectively avoid the risk of excessive
histamine, and also provides technical reference for biological amine detection of similar marine products.