Variety identification method of coated maize seeds based on near-infrared spectroscopy and chemometrics

Published Date

May 2015, Vol.63:21–26, doi:10.1016/j.jcs.2014.07.003

Title 

Variety identification method of coated maize seeds based on near-infrared spectroscopy and chemometrics

• Author 

• Shiqiang Jia ^a,b
• Dong An ^a,c,,
• Zhe Liu ^a
• Jiancheng Gu ^e
• Shaoming Li ^a
• Xiaodong Zhang ^a
• Dehai Zhu ^a
• Tingting Guo ^d
• Yanlu Yan ^a

• aCollege of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
• bKey Laboratory of Agricultural Information Acquisition Technology (Beijing), Ministry of Agriculture, Beijing 100083, China
• cModern Precision Agriculture System Integration Research Key Laboratory of Ministry of Education, Beijing 100083, China
• dNational Maize Improvement Center of China, China Agricultural University, Beijing 100193, China
• eBeijing Kings Nower Seed S&T CO., LTD., Beijing 100080, China

Received 17 February 2014. Revised 14 July 2014. Accepted 15 July 2014. Available online 1 August 2014.

Highlights

• •
  NIR spectroscopy is used to identify varieties of maize seeds.
• •
  The influence of seed coating agent on NIR spectra is evaluated.
• •
  Biomimetic pattern recognition method (BPR) is improved and applied.

Abstract

Near infrared spectroscopy (NIRS) has been used to identify variety authenticity of bare maize kernels. However, maize seeds are coated with seed coating agents in practice. Therefore it is of great significance to investigate the feasibility of identifying coated maize kernels by NIRS. This study employed NIRS to quickly determine the variety to which a sample of coated seed belonged. The NIR spectra of clean and coated seeds were obtained using MPA spectrometry in diffuse reflectance mode by three methods. Influence of seed coating agent on NIR spectra was discussed based on spectra collected from whole single seed by method 1. In method 2, to eliminate the influence of seed coat, the seed coat agent on the back side of the seed was polished away. In method 3, clean and coated seeds were cut open along the crease on the embryo side, and the sections were scanned by the spectrometer, so as to acquire information on the seed, and to avoid the influence of the seed coating agent. Then, support vector machine (SVM), soft independent modeling of class analogy (SIMCA), and biomimetic pattern recognition (BPR) were employed to establish the identification model for four maize varieties. Performance of variety models based on spectra measured by method 1 and 2 were poor. In method 3, the SIMCA model showed better performance than SVM and BPR models, and achieved an accuracy rate of 97.5%. The results demonstrated the feasibility of utilizing NIRS and chemometrics, as an objective and rapid method for the identification of maize seeds with seed coating agents.

Keywords

• Maize
• Seed coating agents
• Variety identification
• Near-infrared spectroscopy

Abbreviations

• BPR, Biomimetic pattern recognition
• NIR, Near-Infrared
• NIRS, near-infrared reflectance spectroscopy
• FT-NIR, Fourier transform near infrared
• KS, Kennard-Stone
• PCA, principal component analysis
• SIMCA, soft independent modeling of class analogy
• SVM, support vector machine

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• ∗ 
  Corresponding author. College of Information and Electrical Engineering, China Agricultural University, No. 17, Qinghuadonglu, Box 63, Beijing 100083, China. Tel.: +86 13366883406.

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