Conclusion 
Figure 5: Division of three feature regions of L15 detail signal in the CWT domain: (a) yellow foxtail seed, (b) giant foxtail
seed, and (c) green foxtail seed.
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Using the seed as material to obtain FT-IR spectra is an effective way to classify plants because the seed of the reproductive
organ contains more stable characters than the vegetative organ.
Figure 6: The artificial neural network calculation flowchart.
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The HATR–FT-IR method can directly measure yellow foxtail seed, giant foxtail seed, and green foxtail seed of the sibling
plants to obtain spectra that enable easier comparison.
Figure 7: Back-propagation algorithm flow chart.
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Wavelet transform can be used to extract the features of the same family plants whose infrared absorption is similar in FT-IR.
The selected eigenvectors in the section 11, 13, and 15 resolution were used to successfully classify the sibling plant seeds
through the artificial neural network. The integration of spectroscopy and computer science technologies provides an efficient
analyzing tool for further study in plant taxonomy.
Acknowledgments This research was supported by the National Natural Science Foundation of China under project number 30800705. The authors
would like to thank Dr. Shuiliang Guo of Department of Biology, Zhejiang Normal University, China, for identifying the plant
samples. Cungui Cheng, Wei Xiong, and Yumei Tian are with the Zhejiang Key Laboratory for Reactive Chemistry on Solid Surfaces, Department of Chemistry, Zhejiang Normal University,
Jinhua, China. E-mail Cungui Cheng at ccg@zjnu.cn
.
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