Analysis of organic acids of tricarboxylic acid cycle in plants using GC-MS, and system modeling

Background: Leaves of 15 plant species were collected from the catchment areas of the river Beas, Punjab, India, and analyzed for organic acids of tricarboxylic acid cycle, viz., citric acid (CA), succinic acid (SA), fumaric acid (FmA), and malic acid (MA). Methods: Gas chromatography-mass spectrometry (GC-MS) was used to determine the content of organic acids in the leaves of plant species. Two microliters of plant sample was injected into the GC-MS, and the concentration of organic acids was quantified using standard curve. Results: Average concentrations of these acids in the leaves of plants studied were 4.79, 0.98, 0.54, and 8.36 mg/g dw, respectively. The maximum contents of these acids were found in the leaves of Chenopodium album (CA = 6.42 mg/g dw), Argemone mexicana (SA = 1.27 and FmA = 0.73 mg/g dw), and Rumex dentatus (MA = 18.0 mg/g dw). Factor analysis revealed mainly two underlying factors for organic acids: Factor-1 having maximum loadings on SA and FmA and Factor-2 had maximum loadings on CA and MA. Multiple linear regression analysis of MA on other acids showed that CA and SA have positive regressions, whereas FmA has a negative regression on MA. In artificial neural network analysis, correlation between the target and output values of MA was found to be highly significant. System transfer coefficients were calculated from simulation graphs fitted to the mean values of different organic acids by using difference equations. Conclusions: From the present study, it was found that citric acid has a maximum direct effect on the malic acid as compared to succinic and fumaric acids as revealed by path analysis. System modeling revealed that the rate of utilization of malic acid is about 9%. The present study describes a new system simulation technique in which a pathway comprising of linear transformation of biochemical constituents may be characterized in terms of its rate transfer coefficients.