Anoectochilus　roxburghii　(Wall.)　Lindl.　(Orchidaceae)　is　one　of　the　most　precious　Chinese　medicine　with　extraordinary　effects　in　medical　treatment　and　health　protection.　Planting　and　tissue-cultured　are　two　main　cultivated　methods　of　A.　roxburghii.　There　are　slight　characteristic　differences　between　Planting　and　tissue-cultured　A.　roxburghii,　but　they　show　significant　differences　in　medicinal　and　market　value.　Therefore,　the　identification　of　cultivated　methods　plays　an　important　role　in　effectively　securing　the　medicinal　efficacy　of　A.　roxburghii　and　maintaining　a　good　market　order.　However,　due　to　the　influence　of　composite　differences　such　as　different　cultivars,　different　geographical　origins　and　different　times　of　cultivation,　the　difficulty　and　complexity　of　identification　in　cultivated　methods　increase　heavily.　This　paper　proposes　an　effective　model　to　discriminative　different　cultivated　methods　of　A.　roxburghii　based　on　improved　lD-inception-CNN.　The　experiments　were　conducted　on　two　kinds　of　A.　roxburghii,　and　their　NIRS　data　were　collected　by　a　Fourier　transform　near-infrared　spectrometer.　Considering　the　unbalanced　proportion　of　planting　and　tissue-cultured　samples,　the　NIRS　data　was　over　sampled　by　using　SMOTE　first.　Secondly,　a　one-dimensional　convolutional　neural　network　based　on　improved　Inception　was　constructed　to　identify　planting　and　tissue-cultured　A.　roxburghii　though　both　include　different　varieties,　different　geographical　origins　and　different　cultivating　times.　Finally,　Bayesian　optimization　was　used　to　optimize　the　hyperparameters　of　the　model.　The　final　average　identification　accuracy,　precision,　recall,　and　Fl-score　of　five-fold　crossvalidation　reached　97.　95%,　96.16%,　100%,　and　98.　02%.　The　identification　model　proposed　in　this　experiment　provides　a　useful　method　to　identify　planting　and　tissue-cultured　A.　roxburghii　effectively　and　rapidly　and　provides　an　idea　for　the　identification　of　cultivation　methods　of　other　Chinese　herbal　medicines.　©　2024　Science　Press.　All　rights　reserved.