Dataset of Near-infrared spectroscopy measurement for amylose determination using PLS algorithms

P. Sampaio, A. Soares, A. Castanho, A. S. Almeida, J. Oliveira, C. Brites

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

In the dataset presented in this article, 168 rice samples comprising sixteen rice varieties (including Indica and Japonica sub species) from a Portuguese Rice Breeding Program obtained from three different sites along four seasons, and 11 standard rice varieties from International Rice Research Institute were characterised. The amylose concentration was evaluated based on iodine method, and the near infrared (NIR) spectra were determined. To assess the advantage of Near infrared spectroscopy, different rice varieties and specific algorithms based on Matlab software such as Standard Normal Variate (SNV), Multiple Scatter Calibration (MSC) and Savitzky-Golay filter were used for NIR spectra pre-processing.

Original languageEnglish
Pages (from-to)389-396
Number of pages8
JournalData in Brief
Volume15
DOIs
Publication statusPublished - Dec 2017

Bibliographical note

Publisher Copyright:
© 2017

Keywords

  • Amylose
  • Chemometrics
  • Near-infrared
  • PLS
  • Rice

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