Chemometric approach to the optimisation of LC-FL and GC-MS methods for the determination of nitrite and nitrate in some biological, food and environmental samples

ABSTRACT

Gas chromatography–mass spectrometry (GC-MS) method and a liquid chromatography–fluorescence (LC-FL) detection method using experimental design and optimisation approach were improved for the quantitative determination of nitrite and nitrate in biological, food and environmental samples. The obtained recoveries of nitrite and nitrate ions from samples based on both GC-MS and LC-FL results ranged from 98.5% to 98.9% for nitrite and 97.9% to 98.4% for nitrate. The precision of these methods, as indicated by the relative standard deviations (RSDs), was within the range from 2.4% to 3.6% for nitrite and 2.5% to 3.8% for nitrate, respectively. The limits of detection of nitrite and nitrate ions from samples based on GC-MS and LC-FL results ranged from 0.01 to 0.14 ng L⁻¹ for nitrite and 0.02 to 0.71 ng L⁻¹ for nitrate, respectively. The optimised isolation procedure by central composite design was successfully applied to real samples. The results revealed that the proposed procedure combined with GC-MS and LC-FL techniques is more sensitive, reliable and selective compared to the other methods available for the precise determination of trace levels of nitrite and nitrate in biological, food and environmental samples.

KEYWORDS:

• Chemometrics
• nitrite
• nitrate
• gas chromatography–mass spectrometry
• liquid chromatography–fluorescence

Acknowledgements

The authors thank the Editing Office of Bülent Ecevit University for linguistic corrections. The authors also wish to thank Bülent Ecevit University (2007-13-02-02) for the opportunity and support to carry out this research. In this work, the mathematical and statistical computations for the experimental design and optimisation were done within the Chemometrics Laboratory of Faculty of Pharmacy and it was supported by the scientific research project No. 10A3336001 of Ankara University. The authors are grateful to Ankara University for the research support.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

In this work, the mathematical and statistical computations for the experimental design and optimisation were done within the Chemometrics Laboratory of Faculty of Pharmacy and it was supported by the scientific research project [No. 10A3336001] of Ankara University.