Determination of flavonoids and phenolic acids in the extract of bamboo leaves using near-infrared spectroscopy and multivariate calibration

  • B Lu
  • J Chen
  • W Huang
  • D Wu
  • W Xu
  • Q Xie
  • X Yu
  • L Li
Keywords: Near-infrared spectroscopy, extract of bamboo leaves (EBL), flavonoids, phenolic acids, partial least squares models, least squares-support vector machine models.

Abstract

The content of flavonoids and phenolic acids in the extract of bamboo leaves (EBL) was determined using near-infrared spectroscopy. Optimal partial least squares models and least squares-support vector machine models were developed to enable rapid and non-destructive validation based on EBL contents as determined by photocolorimetric methods and high performance liquid chromatography. The least squares-support vector machine models performed slightly better than the partial least squares models. For least squares-support vector machine models, the correlation coefficients (R) and root mean square errors (RMSE) of calibration and validation were R(cal)= 0.9998, RMSE(cal)= 0.05, R(val)= 0.9418 and RMSE(val)= 3.91 for total flavonoids (TF) and R(cal)= 0.9778, RMSE(cal)= 2.49, R(val)= 0.9535, and RMSE(val)= 3.61 for total phenolic acids (TP). For optimal partial least squares models, the corresponding values were 0.9962, 1.12, 0.9124 and 4.97 for TF and 0.9966, 0.98, 0.9325 and 4.33 for TP. The results indicated that near-infrared spectroscopy with least squares-support vector machine could be utilized as a precise method for the determination of flavonoids and phenolic acids in EBL.

Key words: Near-infrared spectroscopy, extract of bamboo leaves (EBL), flavonoids, phenolic acids, partial least squares models, least squares-support vector machine models.

Published
2013-10-17
Section
Articles

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eISSN: 1684-5315