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The process to develop a chromatographic method for fingerprinting complex matrices should be performed through a multiparameter approach that could lead to the desired separation and save environmental resources such as organic solvents and energy. In other words, this process should be pursued by employing an optimized experimental design and having a response function which takes into consideration separation parameters together with environmental parameters. Green Analytical Chemistry principles should be pursued during all steps of the research. This work presents a heuristic approach to develop a highperformance liquid chromatography method for fingerprinting an extract from leaves of Cynara scolymus L., a food plant consumed worldwide. A fractional factorial design was used to identify relevant chromatographic variables followed by a comprehensive design for optimization purposes (Doehlert design). A response function called green chromatographic fingerprinting response was employed to obtain a compromise between fingerprint quality and low environmental impact of the method. This optimized approach led to the development of a robust and green method for fingerprinting C. scolymus by HPLC-PAD. This method proved to be greener than the reference method reported in literature and compatible even with no state of art HPLC instruments because the system backpressure did not exceed 15 MPa and the column temperature was 35°C.

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Introduction: Soybean is one of the most important crops in the world, an important source of isoflavones, and used to treat various chronic diseases. High-performance liquid chromatography (HPLC), associated with multivariate experiments and green solvents, is increasingly used to develop comprehensive elution methods for quality control of plants and derivatives.Objective: The work aims to establish a HPLC fingerprinting method for soybean seeds employing Green Chemistry Principles, a sustainable solvent with low toxicity, and a comprehensive experimental design that reduces the number of experiments. Materials and Methods:The fingerprinting method was optimised through Design of Experiments by evaluating seven chromatographic variables: initial percentage of ethanol (X1), final percentage of ethanol (X2), temperature (X3), percentage of acetic acid in water (X4), flow rate (X5), run time (X6), and stationary phase (X7). The dependent variable was the number of peaks (n).Results: An initial factorial design for screening purposes indicated that the most significant quantitative parameters to separate soybean metabolites were X1 and X3.The conditions were optimised by a Doehlert design, to obtain a HPLC-PAD (photodiode array detector) fingerprinting of the polar extract of soybean seeds with the markers identified by liquid chromatography electrospray ionisation tandem mass spectrometry (LC-ESI-MS/MS). The optimum fingerprinting method was determined as 5-55% of ethanol in 30 min, at 35 C, and flow rate of 1 mL/min, by employing a phenyl-hexyl column (150 mm × 4.6 mm). Conclusion:The developed green method enabled markers of soybean to be separated and identified and could be an eco-friendlier alternative for soybean quality control that covered seven Green Analytical Chemistry Principles.