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Effects of Varieties, Producing Areas, Ears, and Ear Positions of Single Maize Kernels on Near-Infrared Spectra for Identification and Traceability

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Listed:
  • Dong An
  • Yongjin Cui
  • Xu Liu
  • Shiqiang Jia
  • Shuyun Zheng
  • Xiaoping Che
  • Zhe Liu
  • Xiaodong Zhang
  • Dehai Zhu
  • Shaoming Li

Abstract

The effects of varieties, producing areas, ears, and ear positions of maize on near-infrared (NIR) spectra were investigated to determine the factors causing the differences in NIR fingerprints of maize varieties. A total of 130 inbred lines were grown in two regions in China, and 12,350 kernel samples were analyzed through NIR spectroscopy. Spectral differences among varieties, producing areas, ears, and ear positions were determined and compared on the basis of pretreated spectra. The bands at 1300–1470, 1768–1949, 2010–2064, and 2235–2311 nm were mainly affected by the producing area. Band selection and principal component analysis were applied to improve the influence of variety on NIR spectra by processing the pretreated spectra. The degrees of the influence of varieties, producing areas, ears, and ear positions were calculated, and the percentages of the influence of varieties, producing areas, ears, and ear positions were 45.40%, 42.66%, 8.22%, and 3.72%, respectively. Therefore, genetic differences among maize inbred lines are the main factors accounted for NIR spectral differences. Producing area is a secondary factor. These results could provide a reference for researchers who authenticate varieties, perform geographical origin traceabilities, and conduct maize seed breeding.

Suggested Citation

  • Dong An & Yongjin Cui & Xu Liu & Shiqiang Jia & Shuyun Zheng & Xiaoping Che & Zhe Liu & Xiaodong Zhang & Dehai Zhu & Shaoming Li, 2016. "Effects of Varieties, Producing Areas, Ears, and Ear Positions of Single Maize Kernels on Near-Infrared Spectra for Identification and Traceability," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-12, September.
  • Handle: RePEc:plo:pone00:0161489
    DOI: 10.1371/journal.pone.0161489
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    Cited by:

    1. Titilayo D.O. Falade & Yasmina Sultanbawa & Mary T. Fletcher & Glen Fox, 2017. "Near Infrared Spectrometry for Rapid Non-Invasive Modelling of Aspergillus -Contaminated Maturing Kernels of Maize ( Zea mays L.)," Agriculture, MDPI, vol. 7(9), pages 1-13, September.

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