ABSTRACT
BACKGROUND: Enhancing the quality control of medicinal plants is a complex challenge due to their rich variety of chemical compounds present at varying and extreme concentrations. Chromatographic fingerprints, which have become essential for characterising these complex natural materials, require achieving optimal separation conditions to effectively maximise the number of detected peaks. The challenges in optimising fingerprints and other complex multi-analyte samples include the unavailability of standards, the presence of unknown constituents and the substantial workload that would require conventional optimisation methods based on models. RESULTS: This work introduces an interpretive optimisation approach which operates on the premise of predicting chromatograms using global models. Initially, a multi-linear gradient experimental design is sequentially executed to accommodate all peaks in the chromatogram in an adequate time window. Following this, a small set of sample peaks (reference peaks) is selected based on their consistent traceability across all chromatograms in the design. Using this reference dataset, a global model is constructed, initially focused solely on the reference peaks and later extended to encompass all detected peaks in the sample. The aim is to find gradients that maximise resolution while minimising analysis time. These optimised gradients are applied successfully to enhance the separation of medicinal plant extracts, with particular emphasis on peppermint and pennyroyal extracts. SIGNIFICANCE: The proposed optimisation relying on global models can be applied to highly complex samples even in the absence of standards, or in cases where standards are available but their use is impractical due to workload constraints. Moreover, in discerning the most promising gradients for highly complex samples, peak purity has demonstrated superior reliability and competitiveness compared to peak capacity as chromatographic objective function.
Subject(s)
Plant Extracts , Chromatography, Liquid/methods , Plant Extracts/chemistry , Plant Extracts/analysis , Plant Extracts/isolation & purification , Plants, Medicinal/chemistry , Chromatography, High Pressure Liquid/methodsABSTRACT
As a result of their metabolic processes, medicinal plants produce bioactive molecules with significant implications for human health, used directly for treatment or for pharmaceutical development. Chromatographic fingerprints with solvent gradients authenticate and categorise medicinal plants by capturing chemical diversity. This work focuses on optimising tea sample analysis in HPLC, using a model-based approach without requiring standards. Predicting the gradient profile effects on full signals was the basis to identify optimal separation conditions. Global models characterised retention and bandwidth for 14 peaks in the chromatograms across varied elution conditions, facilitating resolution optimisation of 63 peaks, covering 99.95 % of total peak area. The identified optimal gradient was applied to classify 40 samples representing six tea varieties. Matrices of baseline-corrected signals, elution bands, and band ratios, were evaluated to select the best dataset. Principal Component Analysis (PCA), k-means clustering, and Partial Least Squares-Discriminant Analysis (PLS-DA) assessed classification feasibility. Classification limitations were found reasonable due to tea processing complexities, involving drying and fermentation influenced by environmental conditions.
Subject(s)
Principal Component Analysis , Tea , Chromatography, High Pressure Liquid/methods , Tea/chemistry , Tea/classification , Least-Squares Analysis , Discriminant Analysis , Camellia sinensis/classification , Camellia sinensis/chemistryABSTRACT
Conventional retention models lead to accurate descriptions of the elution behaviour from the fitting of data for single solutes or from a set of solutes, one by one. However, the simultaneous fitting of several solutes through a regression process that separates the contributions of column and solvent from those of each solute is also possible. The result is a global retention model constituted by a set of equations with some common parameters (those associated with column and solvent), whereas others, specific to each solute, differ for each equation. This work explores the possibilities, advantages, and limitations of global models when they are applied to the optimisation of chromatographic resolution. A set constituted by 13 drugs (diuretics and ß-blockers) and a training experimental design of seven multi-linear gradients are considered. Since standards for all compounds were available, the optimisation based on global models could be compared with the conventional optimisation, which is based on individual models. In their current state, global models do not predict changes in elution order, but they do allow for incorporating additional solutes (e.g., new analytes or matrix peaks) with only one new experiment. This possibility is explored by extending the model for the 13 analytes to include 26 peaks associated with a contamination in the injector. The combination of individual and global models allows an optimisation where the effects of matrix peaks on the separation of analytes can be integrated.
Subject(s)
Chromatography , Research Design , Chromatography/methods , Solvents/chemistry , Diuretics , Adrenergic beta-AntagonistsABSTRACT
Medicinal plants contain a large variety of chemical compounds in highly variable concentrations, so the quality control of these materials is especially complex. With this purpose, regulatory institutions have accepted chromatographic fingerprints as a valid tool to perform the analyses. In order to improve the results, separation conditions that maximise the number of detected peaks in these chromatograms are needed. This work reports the extension of a simulation strategy, based on global retention models previously developed for selected compounds, to all detected peaks in the full chromatogram. Global models contain characteristic parameters for each component in the sample, while other parameters are common to all components and describe the combined effects of column and solvent. The approach begins by detecting and measuring automatically the position of all peaks in a chromatogram, obtained preferably with the slowest gradient. Then, the retention time for each detected component is fitted to find the corresponding solute parameter in the global model, which leads to the best agreement with the measured experimental value. The process is completed by developing bandwidth models for the selected compounds used to build the global retention model based on gradient data, which are applied to all peaks in the chromatogram. The usefulness of the simulation approach is demonstrated by predicting chromatographic fingerprints for three medicinal plants with specific separation problems (green tea, lemon balm and linden), using several multi-linear gradients that lead to problematic predictions.
Subject(s)
Melissa , Plants, Medicinal , Tea/chemistry , Tilia , Plants, Medicinal/chemistry , Plant Extracts/chemistry , Chromatography, High Pressure Liquid/methodsABSTRACT
We report here the improvement of a procedure to obtain global models, able to describe the retention behaviour of several sample components simultaneously. The reported global models include parameters that account for the general effects of column and solvent on retention and are common for all components, whereas other parameters are specific of each sample component. These models are fitted by alternate regression and offer a prediction performance comparable to individual retention models. The approach is suitable to samples of natural products including a large number of components in extremely diverse concentrations and in the absence of standards. Guidelines are given for the successful development of sample-oriented experimental designs (i.e. adapted to the elution of the components of the natural products), constituted by multi-linear gradients. These designs also facilitate peak tracking. The model proposed by Neue and Kuss to describe the retention was found to yield the best predictions. The approach is applied to the extracts of samples of green tea, lemon balm and linden, yielding excellent predictions of retention for selected components.
Subject(s)
Melissa , Tea , Chromatography, High Pressure Liquid/methods , Plant Extracts/chemistry , Solvents/chemistry , Tea/chemistry , TiliaABSTRACT
In liquid chromatography, the reliability of predictions carried out with retention models depends critically on the quality of the training experimental design. The search of the best design is more complex when gradient runs are used instead of isocratic experiments. In Part I of this work (JCA 1624 (2020) 461180), a general methodology based on the error propagation theory was developed and validated for assessing the quality of training designs involving gradients. The treatment relates the mathematical properties of a retention model with the geometry of the training designs and their subsequent predictions. In that work, only five usual designs were considered. Part II investigates in detail the effects on predictions when the features of the training design (number and distribution of the experiments, initial and final modifier content, gradient slope(s), and location of gradient nodes and pulses) are varied systematically. Several groups of related designs containing one or more isocratic steps, linear or multi-linear gradients, or mixed isocratic/gradient runs, among others (in total 38 designs) were evaluated. Box and whiskers and triple plots of expected relative uncertainties were used to evidence the differences in prediction performance. The purpose was to give recommendations to construct designs with good prediction performance. The best designs sample (considering all runs) concentrations as diverse as possible, at any gradient time.
Subject(s)
Chromatography, Liquid , Models, Chemical , Reproducibility of Results , Research DesignABSTRACT
The resolution of samples containing unknown compounds of different nature, or without standards available, as is the case of chromatographic fingerprints, is still a challenge. Possibly, the most problematic aspect that prevents systematic method development is finding models that describe without bias the retention behaviour of the compounds in the samples. In this work, the use of global models (able to describe the whole sample) is proposed as an alternative to the use of individual models for each solute. Global models contain parameters that are specific for each solute, while other parameters ârelated to the column and solventâ are common for all solutes. A special regression procedure is presented for the construction of global models, which are applied to predict highly complex chromatograms, such as chromatographic fingerprints, for diverse experimental conditions in isocratic and gradient elution. Another interesting application is the prediction of molecular properties, such as log Po/w, from the specific solute parameters of the global models. The examined adapted models are based on the equations proposed by Snyder, Schoenmakers, Neue and Kuss, Jandera, and Bosch Rosés to describe the retention. In all cases, the predictive capability was very satisfactory. Two cases of study were considered: chromatograms of camomile extracts analysed using acetonitrile gradients, and a set of 145 known compounds in a wide range of structures and functionalities, eluted isocratically with acetonitrile/water mobile phases.
Subject(s)
Chromatography/methods , Models, Theoretical , Algorithms , Chamomile/chemistry , Computer Simulation , Plant Extracts/chemistry , Reference Standards , Regression Analysis , Sulfonamides/chemistry , Time Factors , Water/chemistryABSTRACT
The basis of interpretive optimisation in liquid chromatography is the prediction of resolution, from appropriate solute retention models. The reliability of the process depends critically on the quality of the experimental design. This work develops, validates and applies a general methodology aimed to evaluate the quality of any training experimental design, which will be applied in Part II to design optimisation. The methodology is based on the systematic evaluation of the uncertainties associated to the prediction of retention times in comprehensive scans of both isocratic and gradient experimental conditions. It is able to evaluate comprehensively experimental designs of arbitrary complexity. Five common training experimental designs were used to model the retention, according to the Linear Solvent Strength (LSS) and the Neue-Kuss (NK) equations, using a set of 14 sulphonamides of different polarity. The results are presented in terms of relative uncertainties in predictions, which provide significant and interpretable results. The magnitude of such uncertainties, together with the systematic, coherent and logical changes observed at increasing solute hydrophobicity, give support to the results. The NK model gave smaller errors and unbiased predictions, whereas the LSS model gave rise to lack of fit. Isocratic training designs, which are widely accepted as the most informative, are confirmed as the best. As a general conclusion, gradients are predicted with intrinsically smaller uncertainties, independently of the training experimental design. In addition, gradients are more insensitive than isocratic predictions with regard to the type of training design used. Isocratic predictions deteriorate quickly with mobile phase composition. This explains the better performance of gradient predictions, even with biased models.
Subject(s)
Chromatography, Liquid/methods , Hydrophobic and Hydrophilic Interactions , Research Design , Solvents/chemistry , Sulfonamides/chemistryABSTRACT
The development of a new comprehensive two-dimensional liquid chromatographic method is described, to obtain the profiles of polyphenolic compounds present in olive (Olea europaea L.) leaves and pulps from different genetic origin. Optimisation of the stationary phase nature, particle size, column length and internal diameter, as well as other separation conditions, was performed. Along the study, three stationary phases (C18, PFP and phenyl) in the first dimension (1D), and five (C18, amide, cyano, phenyl and PFP) in the second dimension (2D) were combined to obtain the maximal number of resolved peaks. The optimised method successfully characterised the presence of 26and 29 common polyphenols in olive leaves and pulp extracts, respectively. Peak volume ratios were used to develop linear discriminant analysis models able to distinguish olive leaves and pulp extracts among seven cultivars from several Spanish regions. The results demonstrate that polyphenolic profiles were characteristic of each cultivar.
Subject(s)
Olea/chemistry , Plant Extracts/chemistry , Polyphenols/chemistry , Chromatography, High Pressure Liquid/methods , Plant Leaves/chemistryABSTRACT
Micellar liquid chromatography (MLC) is a reversed-phase mode with mobile phases containing an organic solvent and a micellised surfactant. Most procedures developed in MLC are implemented in the isocratic mode, since the general elution problem in chromatography is less troublesome. However, gradient elution may be still useful in MLC to analyse mixtures of compounds within a wide range of polarities, in shorter times. MLC using gradients is attractive to determine by direct injection moderate to low polar compounds in physiological samples. In these analyses, the use of initial micellar conditions (isocratic or gradient) with a fixed amount of surfactant above the critical micellar concentration, keeping the organic solvent content low, will provide better protection of the column against the precipitation of the proteins in the physiological fluid. Once the proteins are swept away, the elution strength can be increased using a positive gradient of organic solvent to reduce the analysis time. This may give rise to the transition from the micellar to the submicellar mode, since micelles are destroyed at sufficiently high concentration of organic solvent. In this work, several retention models covering extended solvent domains in MLC are developed and tested, and applied to investigate the performance in isocratic, linear and multi-linear gradient separations. The study was applied to the screening of ß-adrenoceptor antagonists in urine samples, using mobile phases prepared with sodium dodecyl sulphate and 1-propanol. Predicted chromatograms were highly accurate in all situations, although suffered of baseline problems and minor shifts for peaks eluting close to a steep gradient segment. Two columns (C18 and C8) were investigated, with the C8 column being preferable owing to the smaller amount of adsorbed surfactant.
Subject(s)
Chemistry Techniques, Analytical/methods , Chromatography, Liquid , Micelles , Solvents/chemistry , 1-Propanol/chemistry , Adrenergic beta-Antagonists/analysis , Adrenergic beta-Antagonists/urine , Adsorption , Humans , Indicators and Reagents , Sodium Dodecyl Sulfate/chemistry , Surface-Active Agents/chemistryABSTRACT
Multi-linear gradients are a convenient solution to get separation of complex samples by modulating carefully the gradient slope, in order to accomplish the local selectivity needs for each particular solute cluster. These gradients can be designed by trial-and-error according to the chromatographer experience, but this strategy becomes quickly inappropriate for complex separations. More evolved solutions imply the sequential construction of multi-segmented gradients. However, this strategy discards part of the search space in each step of the construction and, again, cannot deal properly with very complex samples. When the complexity is too large, the only valid alternative for finding the best gradient is the use of global search methods, such as genetic algorithms (GAs). Recently, a new global approach where the level of detail is increased along the search has been proposed, namely Multi-scale optimisation (MSO). In this strategy, cubic splines are applied to build intermediate curves to define any arbitrary solvent variation function. Subdivision schemes are used to generate the cubic splines and control their level of detail. The search was subjected to a number of restrictions, such as avoiding long elution and favouring a balanced peak distribution. The aim of this work is evaluating and comparing the results of GAs and MSO. Both approaches were tested with a set of 14 diuretics and probenecid, eluted with acetonitrile-water mixtures using a C18 column. Satisfactory baseline resolution was obtained with an analysis time of 15-16â¯min. We found that GAs optimisation offered results equivalent to those provided by MSO, when the penalisation parameters were included in the cost function.
Subject(s)
Algorithms , Chromatography, Reverse-Phase/methods , Diuretics/isolation & purification , Acetonitriles/chemistry , Solvents , Water/chemistryABSTRACT
The development of methacrylate-based monolithic columns was studied for the separation of pharmaceutical hydrophilic compounds in nano-liquid chromatography. The selected polymerisation mixture consisted of 7.5% hexyl methacrylate, 4.5% methacrylic acid and 18.0% ethylene dimethacrylate (w/w), in a binary porogenic solvent (35:35 w/w 1-propanol/1,4-butanediol). The polymer synthesised with this mixture has a good permeability, not excessive back-pressure, and reasonable retention times for polar and non-polar solutes. Monolithic columns (12â¯cm total capillary length, 100⯵m i.d.), prepared with this mixture, were able to produce hydrogen bonding and electrostatic interactions, giving rise to promising separations. To evaluate the chromatographic system, alkylbenzenes (neutral and hydrophobic compounds) and sulphonamides (hydrophilic drugs) were assayed. To optimise the chromatographic mobile phase in isocratic elution and characterise the retention mechanism for a mixture of eight sulphonamides, the performance of several mathematic models was checked in the description of retention. The behaviour of the monolithic capillary column was compared, in terms of selectivity and peak shape, to that obtained with a C18 column (9â¯cmâ¯×â¯4.6â¯mm i.d., 5⯵m particle size) using a conventional HPLC equipment. The results revealed substantial differences in the interactions established for sulphonamides between the monolithic and C18 columns.
ABSTRACT
Gradient elution may provide adequate separations within acceptably short times in a single run, by gradually increasing the elution speed. Similarly to isocratic elution, chromatograms can be predicted under any experimental condition, through strategies based on retention models. The most usual approach implies solving an integral equation (i.e., the fundamental equation of gradient elution), which has an analytical solution only for certain combinations of retention model and gradient programme. This limitation can be overcome by using numerical integration, which is a universal approach although at the cost of longer computation times. In this work, several alternatives to improve the performance in the resolution of the integral equation are explored, which can be especially useful with multi-linear gradients. For this purpose, the application of several root-finding methods that include the Newton's and bisection searches is explored in three frameworks: isolated predictions, regression modelling problems using gradient training sets, and optimisation of multi-linear gradients. Significant reductions of computation times were obtained. The substitution of non-integrable retention models by Tchebyshev polynomial approximations, which are pre-calculated before solving the integral equation in optimisation problems, is also investigated.
Subject(s)
Algorithms , Chromatography, Liquid/methodsABSTRACT
The advantages and disadvantages of the use of isocratic experimental designs including transient increments of organic solvent (i.e., pulses) in the mobile phase(s) of lowest elution strength are explored with modelling purposes. For retained solutes, this type of mixed design offers similar or better predictive capability than gradient designs, shorter measurement time than pure isocratic designs, and retention model parameters that agree with those derived from pure isocratic experiments, with similar uncertainties. The predicted retention times are comparable to those offered by models adjusted from pure isocratic designs, and the solvent waste is appreciably lower. Under a practical standpoint, mixed designs including pulse(s) can be easily constructed by replacing the slowest isocratic runs with runs containing a pulse of short duration at an intermediate time. This allows the elution of the fastest solutes with appreciable retention in the initial sector of the elution program, previous to the pulse, and the elution of the slow solutes after the pulse, also in acceptable times. The fitting of the retention data obtained with pulses is simpler compared to gradient elution, and involves solving the integral equation of gradient elution, simplified by the presence of isocratic sectors. Experiments involving pulses reveal the existence of discrepancies in the predictions for solutes eluting in the nearby of the pulse, offered by the fundamental equation of gradient elution when this is solved using numerical integration. The correction of such discrepancies implies the inclusion of intra-column delays, in the arrival of changes in the concentration of organic modifier in the gradient to the instantaneous position of the solute, along the whole migration.
Subject(s)
Chromatography, Liquid/methods , Models, Chemical , Solvents/chemistry , Time FactorsABSTRACT
Peak capacity (PC) is a key concept in chromatographic analysis, nowadays of great importance for characterising complex separations as a criterion to find the most promising conditions. A theoretical expression for PC estimation can be easily deduced in isocratic elution, provided that the column plate count is assumed constant for all analytes. In gradient elution, the complex dependence of peak width with the gradient program implies that an integral equation has to be solved, which is only possible in a limited number of situations. In 2005, Uwe Neue developed a comprehensive theory for the calculation of PC in gradient elution, which is only valid for certain situations: single linear gradients, absence of delays and extra-column effects, Gaussian peaks and constant plate count. Going beyond these limitations implies resolving algebraic expressions that unfortunately cannot be integrated. In this work, PC is predicted for multiple situations based on peak simulation. The approach is more general and can be applied for situations out of the scope of the Neue outline, such as complex multi-linear gradients, including asymmetrical peaks. The plots of PC versus retention time of the last eluted solute give rise to Pareto fronts, and can be useful for the probabilistic enhancement of peak resolution in situations where complex multi-analyte samples are processed.
Subject(s)
Chromatography/methods , Models, Chemical , Computer SimulationABSTRACT
In reversed phase-liquid chromatography, the usual solution to the "general elution problem" is the application of gradient elution with programmed changes of organic solvent (or other properties). A correct quantification of chromatographic peaks in liquid chromatography requires well resolved signals in a proper analysis time. When the complexity of the sample is high, the gradient program should be accommodated to the local resolution needs of each analyte. This makes the optimization of such situations rather troublesome, since enhancing the resolution for a given analyte may imply a collateral worsening of the resolution of other analytes. The aim of this work is to design multi-linear gradients that maximize the resolution, while fulfilling some restrictions: all peaks should be eluted before a given maximal time, the gradient should be flat or increasing, and sudden changes close to eluting peaks are penalized. Consequently, an equilibrated baseline resolution for all compounds is sought. This goal is achieved by splitting the optimization problem in a multi-scale framework. In each scale κ, an optimization problem is solved with Nκâ¯≈â¯2κ variables that are used to build the gradients. The Nκ variables define cubic splines written in terms of a B-spline basis. This allows expressing gradients as polygonals of M points approximating the splines. The cubic splines are built using subdivision schemes, a technique of fast generation of smooth curves, compatible with the multi-scale framework. Owing to the nature of the problem and the presence of multiple local maxima, the algorithm used in the optimization problem of each scale κ should be "global", such as the pattern-search algorithm. The multi-scale optimization approach is successfully applied to find the best multi-linear gradient for resolving a mixture of amino acid derivatives.
Subject(s)
Algorithms , Chromatography, Reverse-Phase/methods , Amino Acids/chemistry , Solvents/chemistryABSTRACT
The data processing step of complex signals in high-performance liquid chromatography may constitute a bottleneck to obtain significant information from chromatograms. Data pre-processing should be preferably done with little (or no) user supervision, for a maximal benefit and highest speed. In this work, a tool for the configuration of a state-of-the-art baseline subtraction algorithm, called BEADS (Baseline Estimation And Denoising using Sparsity) is developed and verified. A quality criterion based on the measurement of the autocorrelation level was designed to select the most suitable working parameters to obtain the best baseline. The use of a log transformation of the signal attenuated artifacts associated to a large disparity in signal size between sample constituents. Conventional BEADS makes use of trial-and-error strategies to set up the working parameters, which makes the process slow and inconsistent. This constitutes a major drawback in its successful application. In contrast, the assisted BEADS simplifies the setup, shortens the processing time and makes the baseline subtraction more reliable. The assisted algorithm was tested on several complex chromatograms corresponding to extracts of medicinal herbs analysed with acetonitrile-water gradients, and a mixture of sulphonamides eluted with acetonitrile gradients in the presence of the non-ionic surfactant Brij-35 under micellar conditions.
Subject(s)
Chromatography, High Pressure Liquid/instrumentation , Electronic Data Processing/methods , Acetonitriles/chemistry , Algorithms , Polyethylene Glycols/chemistryABSTRACT
Liquid chromatography with single columns often does not succeed in the analysis of complex samples, in terms of resolution and analysis time. A relatively simple solution to enhance chromatographic resolution is the modulation of the stationary phase through the serial coupling of columns. This can be implemented with any type of column using compatible elution conditions and conventional instruments. This review describes the key features of column coupling and published procedures, where two or more columns were coupled in series to solve separation problems. In all reports, the authors could not resolve their samples with single columns, whereas significant enhancement in chromatographic performance was obtained when the columns were combined. Particularly interesting is the reduction in the analysis time in the isocratic mode, which alleviates the "general elution problem" of liquid chromatography, and may represent a stimulus for the proposal of new procedures, especially in combination with mass spectrometric, electrochemical and refractometric detection. Developments proposed to make the serial coupling of columns useful in routine and research laboratories are outlined, including optimisation strategies that facilitate the selection of the appropriate column combination and elution conditions (solvent content, flow rate or temperature) in both isocratic and gradient modes. The availability of zero dead volume couplers, able to connect standard columns, and the commercialisation of short columns with multiple lengths, have expanded the possibilities of success.
ABSTRACT
A new approach is reported for high-performance liquid chromatography to measure the level of information in fingerprints. For this purpose, the concept of peak prominence, which is the protruding part of each visible peak with regard to the valleys that delimit it, was used. The peaks in the fingerprints are ranked according to the areas of the peak prominences, and a threshold is established to discriminate between the significant peaks and those that are irreproducible. The approach was applied to evaluate the impact of several extraction conditions (solvent nature and composition, time and temperature of the treatment, amount of sample, and time and temperature of conservation of the extracts) on the number of significant peaks found in the fingerprints of a medicinal herb (a green tea sample), using PlackettBurman designs. Acetonitrile, ethanol and methanol were used for the extraction, and a linear gradient for chromatographic analysis, where the acetonitrile content was increased from 5.0% to 42.5% (v/v) in 45 min. The maximal number of significant peaks in the fingerprints was obtained using a methanolwater mixture as extraction solvent, high ultrasonication time and high temperature. The reported approach can be generalised to other complex samples and situations.
Subject(s)
Chemistry Techniques, Analytical/methods , Chromatography, High Pressure Liquid , Plant Extracts/chemistry , Plants, Medicinal/chemistry , Acetonitriles/chemistry , Solvents/chemistry , Tea/chemistryABSTRACT
Getting useful chemical information from samples containing many compounds is still a challenge to analysts in liquid chromatography. The highest complexity corresponds to samples for which there is no prior knowledge about their chemical composition. Computer-based methodologies are currently considered as the most efficient tools to optimise the chromatographic resolution, and further finding the optimal separation conditions. However, most chromatographic objective functions (COFs) described in the literature to measure the resolution are based on mathematical models fitted with the information obtained from standards, and cannot be applied to samples with unknown compounds. In this work, a new COF based on the automatic measurement of the protruding part of the chromatographic peaks (or peak prominences) that indicates the number of perceptible peaks and global resolution, without the need of standards, is developed. The proposed COF was found satisfactory with regard to the peak purity criterion when applied to artificial peaks and simulated chromatograms of mixtures built using the information of standards. The approach was applied to mixtures of drugs containing unknown impurities and degradation products and to extracts of medicinal herbs, eluted with acetonitrile-water mixtures using isocratic and gradient elution.