Roberto Muñiz-Valencia

Supercritical fluid chromatography with photodiode array detection for pesticide analysis in papaya and avocado samples

To improve the analysis of pesticides in complex food matrices with economic importance, alternative chromatographic techniques, such as supercritical fluid chromatography, can be used. Supercritical fluid chromatography has barely been applied for pesticide analysis in food matrices. In this paper, an analytical method using supercritical fluid chromatography coupled to a photodiode array detection has been established for the first time for the quantification of pesticides in papaya and avocado. The extraction of methyl parathion, atrazine, ametryn, carbofuran, and carbaryl was performed through the quick, easy, cheap, effective, rugged, and safe methodology. The method was validated using papaya and avocado samples. For papaya, the correlation coefficient values were higher than 0.99; limits of detection and quantification ranged from 130-380 and 220-640 μg/kg, respectively; recovery values ranged from 72.8-94.6%; precision was lower than 3%. For avocado, limit of detection values were ˂450 μg/kg; precision was lower than 11%; recoveries ranged from 50.0-94.2%. Method feasibility was tested for lime, banana, mango, and melon samples. Our results demonstrate that the proposed method is applicable to methyl parathion, atrazine, ametryn, and carbaryl, toxics pesticides used worldwide. The methodology presented in this work could be applicable to other fruits.

Geographical Authentication of Tequila According to its Mineral Content by Means of Support Vector Machines

The elemental profile of tequila samples from the three main production areas of the State of Jalisco, namely Amatitlan, Guadalajara, and Tequila, was used to carry out their geographical characterization. With this aim, the concentration of Al, Ba, Ca, Cu, Fe, K, Mg, Mn, Na, S, Sr, and Zn was determined by inductively coupled plasma atomic emission spectroscopy. Principal component analysis was addressed to visualize data trends. The number of input variables was reduced by means of backward stepwise linear discriminant analysis and support vector machines were used to construct an adequate classification model. The best classification performance was obtained by a linear support vector machine model with 100% of prediction ability.

Characterisation of tequila according to their major volatile composition using multilayer perceptron neural networks.

Differentiation of silver, gold, aged and extra-aged tequila using 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol and furan derivatives like 5-(hydroxymethyl)-2-furaldehyde and 2-furaldehyde has been carried out. The content of 1-propanol, ethyl acetate, 2-methyl-1-propanol, 3-methyl-1-butanol and 2-methyl-1-butanol was determined by means of head space solid phase microextraction gas chromatography mass-spectrometry. 5-(Hydroxymethyl)-2-furaldehyde and 2-furaldehyde were determined by high performance liquid chromatography with diode array detection. Kruskal-Wallis test was used to highlight significant differences between types of tequila. Principal component analysis was applied as visualisation technique. Linear discriminant analysis and multilayer perceptron artificial neural networks were used to construct classification models. The best classification performance was obtained when multilayer perceptron model was applied.

Liquid chromatographic method development for anabolic androgenic steroids using a monolithic column: Application to animal feed samples

An isocratic HPLC method for the determination with screening purposes of anabolic androgenic steroids (AASs: fluoxymesterone, boldenone, nortestosterone, metandrostenolone, norethindrone, methyltestosterone and bolasterone), used as growth promoting agents, in finishing pig feed samples has been developed and validated. The separation was achieved by using a reversed-phase Chromolith RP-18e column at controlled temperature, UV-detection at 245nm and epitestosterone as internal standard. The method development involved optimization of different aqueous-organic mobile phases using methanol or acetonitrile as organic modifiers, flow-rate and temperature. The optimum separation for these compounds was achieved at 40 degrees C using ultrapure water:acetonitrile (71:29, v/v) as mobile phase and 3mLmin(-1) flow-rate, allowing the separation of AASs with baseline resolution in about 15min. The optimized method was applied to the analysis of AASs in finishing pig feed samples. Prior to HPLC, sample preparation procedure was used by leaching using acetonitrile, saponification in a basic medium and solid-phase extraction using polymeric Abselut Nexus cartridges. Method validation has been carried out according to the European Commission Decision 2002/657/EC. The extraction efficiencies, decision limits (CCalpha) and detection capabilities (CCbeta) for these compounds were in the range 83-96%, 27-37 and 32-47microgkg(-1) range, respectively. The within-laboratory reproducibility at 1, 1.5 and 2 CCbeta concentration levels were smaller than 13, 10 and 8%, respectively. Finally, the proposed method was successfully applied to nine different kinds of animal feed.

Direct immersion single drop micro-extraction method for multi-class pesticides analysis in mango using GC–MS

Due the negative effects of pesticides on environment and human health, more efficient and environmentally friendly methods are needed. In this sense, a simple, fast, free from memory effects and economical direct-immersion single drop micro-extraction (SDME) method and GC-MS for multi-class pesticides determination in mango samples was developed. Sample pre-treatment using ultrasound-assisted solvent extraction and factors affecting the SDME procedure (extractant solvent, drop volume, stirring rate, ionic strength, time, pH and temperature) were optimized using factorial experimental design. This method presented high sensitive (LOD: 0.14-169.20μgkg-1), acceptable precision (RSD: 0.7-19.1%), satisfactory recovery (69-119%) and high enrichment factors (20-722). Several obtained LOQs are below the MRLs established by the European Commission; therefore, the method could be applied for pesticides determination in routing analysis and custom laboratories. Moreover, this method has shown to be suitable for determination of some of the studied pesticides in lime, melon, papaya, banana, tomato, and lettuce.

GC‐MS method development and validation for anabolic steroids in feed samples

A GC-MS method for the determination of AAS used as growth promoting agents using SIM in piglet feed samples has been developed and validated, using testosterone as internal standard. The formation of volatile steroid derivatives was carried out by derivatization with N-methyl-N-(trimethylsilyl)trifluoroacetamide. The optimum separation was achieved using a Zebron ZB-5 column under a gradient temperature elution, allowing the separation of steroids in 18 min. The required sample treatment process was discussed. A leaching using ACN, saponification using a binary NaOH/MgCl2 solution, and LLE using ethyl acetate were finally selected. Method validation has been carried out according to the Commission Decision 2002/657/EC criteria established for quantitative confirmatory methods. The extraction efficiencies, CCalpha and CCbeta for these compounds were in the ranges 78-98%, 10-21 and 18-35 mug/kg, respectively. The repeatability and the within-laboratory reproducibility at 1, 1.5, and 2 CCbeta concentration levels were smaller than 8.2, 7.5, and 5.8% and 12.2, 9.5, and 7.5%, respectively. Accuracy was in the 99-103% range. The robustness was evaluated using the Youden robustness test. The proposed method was applied to the analysis of steroids spiked in different kinds of animal feed samples with satisfactory results.

Some practical considerations for linearity assessment of calibration curves as function of concentration levels according to the fitness-for-purpose approach

Since linear calibration is mostly preferred for analytical determinations, linearity in the calibration range is an important performance characteristic of any instrumental analytical method. Linearity can be proved by applying several graphical and numerical approaches. The principal graphical criteria are visual inspection of the calibration plot, the residuals plot, and the response factors plot, also called sensitivity or linearity plot. All of them must include confidence limits in order to visualize linearity deviations. In this work, the graphical representation of percent relative errors of back-calculated concentrations against the concentration of the calibration standards is proposed as linearity criterion. This graph considers a confidence interval based on the expected recovery related to the concentration level according to AOAC approach. To illustrate it, four calibration examples covering different analytical techniques and calibration situations have been studied. The proposed %RE graph was useful in all examples, helping to highlight problems related to non-linear behavior such as points with high leverage and deviations from linearity at the extremes of the calibration range. By this way, a numerical decision limit which takes into account the concentration of calibration standards can be easily included as linearity criterion in the form of %RETh=2·C-0.11. Accordingly, this %RE parameter is accurate for the decision-making related to linearity assessment according to the fitness-for-purpose approach.

Comparative study of As, Cd, Cu, Cr, Mg, Mn, Ni, Pb and Zn concentrations between sediment and water from estuary and port

The contents of As, Cd, Cu, Cr, Mg, Mn, Ni, Pb and Zn have been determined in sediment and water samples from Valle de las Garzas estuary and Port Manzanillo (Colima, Mexico) using ICP-AES. The concentrations of these elements were used for a comparative study to determine the distribution of heavy metals and to evaluate which elements reflect natural or anthropogenic backgrounds. For this purpose, seven sampling points were selected: Four of them correspond to the lagoon, and three were situated in the port. Statistical analysis of the mineral content was assessed. Initially, data comparison was assessed by statistical tests for each variable. Principal component analysis was then applied considering the influence of all variables at the same time by obtaining the distribution of samples according to their scores in the principal component space. In this way, four studies were carried out: (1) study of sediments collected during the dry season; (2) study of sediments collected during the rainy season; (3) comparative study between sediments from rainy and dry season; and (4) study of water composition collected during rainy season. From the results of the performed analyses, it can be concluded that metals distribution pattern reflected natural and anthropogenic backgrounds (e.g., sediments from the lagoon, situated at the beginning of the rain channel, presented high contents of Zn and Cu, perhaps related to anthropogenic activities or the influence of igneous sediments).

Sample preparation for the determination of steroids (corticoids and anabolics) in feed using LC

An improved sample preparation procedure for the determination of 17 steroids (corticoids (CC) and androgenic anabolic steroids (AAS)), used potentially as growth promoters, in feed samples has been developed. This procedure is based on two reported LC-UV methods. The improved procedure includes a leaching process using ACN, saponification, and SPE using polymeric cartridges. The proposed method was validated according to the EU criteria established for quantitative screening methods in PFS. The extraction efficiencies, decision limits (CCalpha) and detection capabilities (CCbeta), for these compounds were in the ranges of 82-100%, 19-40, and 24-53 microg/kg, respectively. The repeatability and the within-laboratory reproducibility at 1.0, 1.5, and 2.0 CCbeta levels were smaller than 10%. Accuracy was in the 97-101% range. The robustness was evaluated using the Youden robustness test. This method was applied to the analysis of steroids in different kinds of FS with satisfactory results.

Supercritical-Fluid Chromatography with Diode-Array Detection for Emerging Contaminants Determination in Water Samples. Method Validation and Estimation of the Uncertainty

Here we present a communication about the article “Salvatierra-Stamp VC, Ceballos-Magana SG, Gonzalez J, Ibarra-Galvan V, Muniz-Valencia R (2015) Analytical method development for the determination of emerging contaminants in water using supercritical-fluid chromatography coupled with diode-array detection. Analytical and Bioanalytical Chemistry 407:4219-4226”. In this paper, a selective, linear, accurate and precise supercritical-fluid chromatography coupled with diode-array detection method was developed and validated for the determination of seven emerging contaminants: two pharmaceuticals, three endocrine disruptors, one bactericide and one pesticide. The compounds were base-line separated in around 10 minutes. Also, the method involved a sample treatment optimization by means of C18-OH solid phase extraction cartridges. The developed method was validated. In this sense, the correlation coefficient and recovery was higher than 0.9997 and 94%, respectively. Limit of detection and quantification was in the range of 0.10-1.59 μg/L and 0.31-4.83 μg/L, respectively. The measurement uncertainty was evaluated using the top-down model considering six sources of uncertainty. For all compounds, the uncertainty associated with accuracy and linearity regression was the main contribution to the combined uncertainty. Expanded uncertainties for each compound in method analysis were lower than 10.8%. Finally the method was successfully applied to environmental water samples.