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Variety Identification of Orchids Using Fourier Transform Infrared Spectroscopy Combined with Stacked Sparse Auto-Encoder

College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Institute of Horticulture, Zhejiang Academy of Agriculture Science, Hangzhou 310021, China
Author to whom correspondence should be addressed.
The first two authors contributed equally to this paper.
Molecules 2019, 24(13), 2506;
Received: 11 June 2019 / Revised: 2 July 2019 / Accepted: 3 July 2019 / Published: 9 July 2019
(This article belongs to the Section Analytical Chemistry)
PDF [2647 KB, uploaded 9 July 2019]


The feasibility of using the fourier transform infrared (FTIR) spectroscopic technique with a stacked sparse auto-encoder (SSAE) to identify orchid varieties was studied. Spectral data of 13 orchids varieties covering the spectral range of 4000–550 cm−1 were acquired to establish discriminant models and to select optimal spectral variables. K nearest neighbors (KNN), support vector machine (SVM), and SSAE models were built using full spectra. The SSAE model performed better than the KNN and SVM models and obtained a classification accuracy 99.4% in the calibration set and 97.9% in the prediction set. Then, three algorithms, principal component analysis loading (PCA-loading), competitive adaptive reweighted sampling (CARS), and stacked sparse auto-encoder guided backward (SSAE-GB), were used to select 39, 300, and 38 optimal wavenumbers, respectively. The KNN and SVM models were built based on optimal wavenumbers. Most of the optimal wavenumbers-based models performed slightly better than the all wavenumbers-based models. The performance of the SSAE-GB was better than the other two from the perspective of the accuracy of the discriminant models and the number of optimal wavenumbers. The results of this study showed that the FTIR spectroscopic technique combined with the SSAE algorithm could be adopted in the identification of the orchid varieties. View Full-Text
Keywords: orchids; variety identification; FTIR spectroscopy; stacked sparse auto-encoder orchids; variety identification; FTIR spectroscopy; stacked sparse auto-encoder

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Chen, Y.; Chen, Y.; Feng, X.; Yang, X.; Zhang, J.; Qiu, Z.; He, Y. Variety Identification of Orchids Using Fourier Transform Infrared Spectroscopy Combined with Stacked Sparse Auto-Encoder. Molecules 2019, 24, 2506.

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