[Feasibility study on an approach for identifying corn kernel varieties with seed coating agents via near infrared spectroscopy].
It is generally accepted that near infrared reflectance spectroscopy (NIRS) can be used to identify variety authenticity of bare maize seeds. In practical, maize seeds are covered with seed coating agents. Therefore it's of huge significance to investigate the feasibility of identifying coated maize seeds by NIRS. This study employed NIRS to quickly determine the variety of coated maize seeds. Influence of seed coating agent on NIR spectra was discussed. The NIR spectra of coated maize seeds were obtained using an innovative method to avoid the impact of the seed coating agent. Coated seeds were cut open, and the sections were scanned by the spectrometer, so as to acquire the information of the seed itself. Then, support vector machine (SVM), soft independent modeling of class analogy (SIMCA), and biomimetic pattern recognition (BPR) was employed to establish the identification model for four maize varieties, and yield 93%, 95.8%, 98% average correct rate respectively. BPR model showed better performance than SVM and SIMCA models. The robustness of identification model was tested by seeds harvested from four regions and model showed good performance.
Shi-Qiang
SQ
Jia
Ting-Ting
TT
Guo
Zhe
Z
Liu
Yan-Lu
YL
Yan
Dong
D
An
Jian-Cheng
JC
Gu
Shao-ming
SM
Li
Shao-Ming
SM
Zhang
De-Hai
DH
Zhu
D005240:Feasibility Studies; D008962:Models, Theoretical; D012639:Seeds; D012984:Software; D019265:Spectroscopy, Near-Infrared; D060388:Support Vector Machine; D003313:Zea mays / Q000145:classification*