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Background Anthracnose of  Camellia oleifera  is a very destructive disease that commonly occurs in the  Camellia oleifera  industry, which severely restricts the development of the  Camellia oleifera  industry. In the early stage of the  Camellia oleifera  suffering from anthracnose, only the diseased parts of the tree need to be repaired in time. With the aggravation of the disease, the diseased branches need to be eradicated, and severely diseased plants should be cut down in time. At present, aiming at the problems of complex experiments and low accuracy in detecting the degree of anthracnose of  Camellia oleifera , a method is proposed to detect the degree of anthracnose of  Camellia oleifera  leaves by using terahertz spectroscopy (THz) combined with laser-induced breakdown spectroscopy (LIBS), so as to realize the rapid, efficient, non-destructive and high-precision determination of the degree of anthracnose of  Camellia oleifera . Results Mn, Ca, Ca II, Fe and other elements in the LIBS spectrum of healthy and infected  Camellia oleifera  leaves with different degrees of anthracnose are significantly different, and the Terahertz absorption spectra of healthy  Camellia oleifera  leaves, and  Camellia oleifera  leaves with different degrees of anthracnose there are also significant differences. Partial least squares discriminant analysis (PLS-DA), support vector machine (SVM), and linear discriminant analysis (LDA) are used to establish the fusion spectrum anthracnose classification model of  Camellia oleifera . Among them, the Root mean square error of prediction (RMSEP) and the prediction determination coefficient R 2 p of THz-LIBS-CARS-PLS-DA of prediction set are 0.110 and 0.995 respectively, and the misjudgment rate is 1.03%; The accuracy of the modeling set of THz (CARS)-LIBS (CARS)-SVM is 100%, and the accuracy of prediction set is 100%, after preprocessing of the multivariate scattering correction (MSC), the accuracy of the THz-LIBS-MSC-CARS modeling set is 100%, and the accuracy of prediction set is 100%; The accuracy rate of THz-LIBS-MSC-CARS-LDA of modeling set is 98.98%, and the accuracy rate of the prediction set is 96.87%. Conclusion The experimental results show that: the SVM model has higher qualitative analysis accuracy and is more stable than the PLS-DA and LDA models. The results showed that: the THz spectrum combined with the LIBS spectrum could be used to separate healthy  Camellia oleifera  leaves from various grades of anthracnose  Camellia oleifera  leaves non-destructively, quickly and accurately.

Research on anthracnose grade of Camellia oleifera based on the combined LIBS and THz technology