Rapid and sensitive method for determining free amino acids in plant tissue by high-performance liqu

• 作者: Nengjian Zheng Huayun Xiao Zhongyi Zhang Xiaofei Gao Jingjing Zhao
• 学科: 地球科学
• 关键词: HPLC OPA FMOC Free amino acids Plant PLS-DA
• 年，卷（期）: 2022,（4）
• 页码范围: 680-696
• 页数: 16页
• 语种: 英文
• DOI: 10.1007/s11631-017-0244-5

摘要

This paper describes a reliable and rapid method for the complete separation and quantitation of twenty-five amino acids typically found in plants, based on reversed phase high-performance liquid chromatography-linked fluorescence detector using a 150 × 4.6 mm Zorbax Eclipse AAA colμMn. Plant tissue free amino acids (FAA) were extracted by ultrasonication with 5% (v/v) aqueous trifluoroacetic acid followed by ultrafiltration of extracts. The following analysis of amino acids was performed through programmed precolμMn derivatization with orthophthalaldehyde and 9-fluorenylmethyl chloroformate reagents and efficient elution of derivatives within 26 min using binary gradient scheme. The method was validated over a concentration range of 4.5–450 μMol L-1 (μM). Separation analysis showed good selectivity (resolution > 1.5) for most amino acids. The average repeatability (RSD%, relative standard deviation) of the analysis at seven calibration concentrations was below 4% and ranged from 1.13 % to 12.04%. The intra-day mean coefficient of variation at two concentrations (22.5 and 90 μM) was within 2%, and the intermediate precision was less than 4%. The limits of detection were between 0.012 and 6.68 μM. The coefficients of determination (R2) of the linear calibration curves were from 0.9989 to 0.9999. When the method was applied to plant samples, the FAA recoveries at two spiked levels (25 and 100 μM) ranged from 67.0% to 108.9% with an average of 94.4%, and the precision was 0.26%–12.31% RSD. A specific application combining this method with optimized extraction and interference removal procedures was successfully used to determine the FAA pools in different plant tissues. Finally, a PLS-DA multivariate statistics model was validated for the classification of three plant species according to their FAA profiles.