Planta Medica Letters 2016; 3(04): e81-e86
DOI: 10.1055/s-0042-102202
Georg Thieme Verlag KG Stuttgart · New York

Brachiaria plantaginea as a Potential (New) Source of Shikimic Acid. Quantification by NIR and PLS Regression

Maria Cristina A. Costa
1   Theoretical and Applied Chemometrics Laboratory (LQTA), Institute of Chemistry, University of Campinas – Unicamp, Campinas – SP, Brazil
Marcus B. Matallo
2   Instituto Biológico, Jardim das Palmeiras, Campinas – SP, Brazil
Márcia M. C. Ferreira
1   Theoretical and Applied Chemometrics Laboratory (LQTA), Institute of Chemistry, University of Campinas – Unicamp, Campinas – SP, Brazil
Sonia C. N. Queiroz
3   Embrapa Meio Ambiente, Jaguariúna – SP, Brazil
Sydnei B. Dionísio de Almeida
2   Instituto Biológico, Jardim das Palmeiras, Campinas – SP, Brazil
Daniel A. de Siqueira Franco
2   Instituto Biológico, Jardim das Palmeiras, Campinas – SP, Brazil
› Author Affiliations
Further Information

Publication History

received 16 October 2015
revised 10 December 2015

accepted 18 January 2016

Publication Date:
14 March 2016 (online)


Shikimic acid is a natural organic compound produced in the biochemical pathways of eukaryotic organisms and is generally utilized as a starting material of the antiviral drug Oseltamivir (Tamiflu®). This study shows the results of shikimic acid accumulation in Brachiaria plantaginea, an abundant, grassy plant found in Brazil and other countries in Africa and America, after glyphosate spraying at three different doses. B. plantaginea plants harvested after 6 days of exposure to the herbicide showed that shikimic acid accumulation increased by 345 %, on average, compared to unsprayed plants. The combination of near infrared spectroscopy and multivariate analysis using partial least square regression was applied for the quantification of shikimic acid in B. plantaginea. Spectra of 44 samples were obtained using the diffuse reflectance mode in the range of 4000 to 10 000 cm−1 with 4 cm−1 resolution. Different mathematical pretreatments were applied to the spectra. As preprocessing, the data were mean-centered. The calibration model with seven factors on twenty-nine samples (training set) exhibited a coefficient of determination = 0.9930 and a standard error of calibration = 84.05. For external validation (11 samples on the test set), the coefficient of determination = 0.9317 and the standard error of prediction = 154.91. The percent calibration error range was 1 to 10 % for most of the samples and only two samples presented an error greater than 20 %. For external validation, the mean prediction error was 10 % and the range error ratio was 9.42, indicating that the model is qualified for screening calibration.

Supporting Information

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