The use of green sustainable solvents and miniaturized sample preparation methods are among the drivers for green analytical chemistry. Edible oils have been shown recently to possess switchable-hydrophilicity behaviour that makes them suitable candidates for extraction and preconcentration of analytes. This study aims to investigate their applicability for the preconcentration of parabens in food and pharmaceutical samples prior to their determination by HPLC-DAD. At optimum conditions, linear calibration graphs were obtained with coefficient of determination (R2) between 0.9950 and 0.9993. The limit of detection (LOD) ranged between 0.2 and 0.5 mu g/mL (0.2-0.4 mu g/ g). The precision of the method based on percentage relative standard deviations (%RSD) were below 6.8%, with percentage relative recoveries (%RR) between 90.4% and 106.0%. Enrichment factor was achieved between 6.6 and 41.5 folds which improved the sensitivity of the method to enable detection limits within the recommended limits set by regulatory bodies for parabens in the investigated samples.

Sudan dyes are a kind of azo dye used for a variety of industrial and scientific applications. They are especially popular as food colorings due to their low cost and widespread availability. However, because they are toxic and probably carcinogenic, their use in food is restricted in most countries, including the European Union. In this study, supramolecular solvent liquid-liquid microextraction (SMS-LLME), produced from tetrahydrofuran/1-dodecanol (THF:1-DO), was utilized for the extraction of Sudan I, III, and IV dyes from spices prior to their detection by high-performance liquid chromatography. The optimum conditions for SMS-LLME were obtained using 900 mu L of THF:1-DO (8:1, % v/v) as the extraction solvent, with an extraction time of 1.0 min. Ionic strength had a negative effect on the extraction efficiency. Limit of detection (LOD) was found in the range of 0.4 to 1.5 mu g mL-1. Linear calibration graphs were obtained with a coefficient of determination greater than 0.9950 and the precision based on relative standard deviation less than 9.1%. The relative recovery was between 82.6 and 113.0%. Moreover, the method achieved an acceptable analytical greenness score based on the analytical greenness calculator and green analytical procedure index metrics.

The development of affordable, easy-to-use methods holds promise to broaden access to food analysis in resource-limited settings that will enhance food safety monitoring and the assessment of public health interventions. In this study, we propose a green extraction method called deep eutectic solvent liquid-liquid microextraction (DES-LLME), coupled with a simple detection technique referred to as the smartphone digital image colorimetry (SDIC), for the quantification of iodate in table salt. Optimization of the DES-LLME-SDIC method was conducted to enhance performance. At the optimum conditions, the proposed method achieved an enrichment factor between 6.1 and 27.8, with a limit of detection (LOD) between 0.52 and 0.84 mu mol L-1, and a limit of quantitation (LOQ) between 1.73 and 2.81 mu mol L-1. The concentration of iodate exhibited a satisfactory linear correlation with absorbance, as demonstrated by a well-fit regression model as verified by lack of fit test (p > 0.05), within a linear dynamic range from 1.73 to 25.00 mu mol L-1. The precision of the method was validated through the relative standard deviation (%RSD) for intraday (3.6%) and interday (6.3%) precision. The developed method was applied for the determination of iodate in various salt samples. Additionally, the accuracy of the proposed SDIC method was evaluated with a separate ultraviolet-visible spectrometry method. Both methods exhibited statistical agreement.

Analytical instruments used for scientific research and education are often expensive. This limitation poses a challenge for schools and educators in low-income countries to provide practical science training to students. To address this problem, the improvisation of analytical instruments and instructional materials has emerged as a viable solution. By incorporating practical experiments into science education, students have the opportunity to engage directly with scientific instruments, conduct investigations, and collect data. This hands-on approach fosters a deeper understanding of scientific principles, enhances critical thinking skills, and cultivates scientific mindsets among students. Herein, we review and discuss, step-by-step, the approach of using a smartphone for quantitative analysis, referred to as smartphone digital image colorimetry (SDIC). SDIC, with its practicality and accessibility, utilizes smartphone digital cameras for image acquisition and the freely available image processing programs, such as ImageJ and smartphone Apps, for image quantification. Using SDIC can enable students in low-income countries to develop essential scientific skills, including critical thinking, data interpretation, and an evidence-based approach to scientific research. By leveraging the ubiquity and affordability of smartphone technology, SDIC offers an accessible and cost-effective approach to practical science education, bridging the gap between theory and practice in resource-constrained settings.

Colorimetric determination of proteins in serum is proposed based on the biuret method and replacing ultraviolet-visible spectrometric (UV-Vis) detection with a simple and affordable smartphone digital image colorimetric (SDIC) method. Optimum SDIC conditions were found as a detection wavelength of 555 nm, a region of interest of 1600 px2, and 9.0 cm between the detection camera and sample solution. Under the optimum conditions, the coefficient of determination was 0.9982 within a linear dynamic range of 0.022 to 0.35 g dL-1. The precision of the method based on the percent relative standard deviation was below 5%. The limit of detection and limit of quantitation were found to be 0.007 and 0.022 g dL-1 respectively, which were sufficient for the quantification of the total protein, albumin, and globulin in serum. The method was validated with an independent experiment using a UV-Vis method and both methods showed good statistical agreement, indicating the accuracy of the proposed SDIC method.

Simple, inexpensive and accurate analytical methods are in high demand. Dispersive solid-phase microextraction (DSPME) was used in combination with smartphone digital image colorimetry (SDIC) to determine boron in nuts as an approach replacing existing costly alternatives. A colorimetric box was designed to capture images of standards and sample solutions. ImageJ software was used to link pixel intensity to the analyte concentration. Under optimum extraction and detection conditions, linear calibration graphs were obtained with coefficients of determination (R2) above 0.9955. Percentage relative standard deviations (%RSD) were below 6.8 %. The limits of detection (LOD) ranged between 0.07 and 0.11 μg mL-1 (1.8 to 2.8 μg g-1), which were sufficient for detection of boron in nut samples (i.e., almond, ivory, peanut and walnut), with percentage relative recoveries (%RR) between 92.0 and 106.0 %.

The use of Crataegus species for the treatment of cardiovascular ailments is widely distributed. Even then only a few species are included in the Pharmacopoeias. In this study bioactive flavonoids of Crataegus azarolus and Crataegus pallasii were identified and quantified in comparison with the well-known pharmaceutical product of Crataegus; Crataegutt (R) Tropfen using reverse phase-high performance liquid chromatography. The method developed is simple, fast, reliable and sensitive. In an attempt to reduce matrix effect prior to high performance liquid chromatography analysis, a novel approach is proposed as an efficient simple clean-up technique termed "indirect-dispersive liquid-liquid microextraction". Validation parameters of the method were calculated as follows: Limit of detection ranged from 0.4 to 3.4 mg/g and limit of quantitation from 1.3 to 11.3 mg/g, intraday and interday precision expressed as percentage relative standard deviation ranged from 1.0 to 2.8 and 1.5 to 4.3, respectively and r(2) values were above 0.9950 for all analytes. The relative recovery of all analytes was more than 98 %. Four predominate peaks were identified using certified standards as Vitexin 2''-O-rhamnoside, rutin, vitexin and hyperoside, with mass concentration (% w/w) in Crataegus azarolus as 4.4 %, 2.9 %, 1.7 % and 4.4 %, in Crataegus pallasii as 4.4 %, 2.6 %, 1.4 % and 4.8 % and in Crataegutt (R) Tropfen as 1.6 %, 1.0 %, 0.6 % and 0.4 % respectively. Thus, the values met the criteria of the United States Pharmacopeia and the European Pharmacopeia monographs. Our investigations postulate that Crataegus azarolus and Crataegus pallasii could be a good source for the production of Crataegus phytomediciness.

ObjectivesThis study aims to present a method for the determination of the aluminum in antiperspirant products (APPs) by chelating it with quercetin before its detection by smartphone digital image colorimetry (SDIC).Materials and MethodsSamples were prepared by closed-vessel acid digestion in PTFE cups. This was followed by complexation of aluminum in the sample solution using quercetin as a chelating agent. Sample solutions were transferred into a quartz ultraviolet/visible detection microcuvette for detection in a homemade colorimetric box designed for capturing images of the yellow complex with a smartphone camera. The pixel intensity of the images was converted to numbers for quantitation using ImageJ software for a personal computer. An independent study using high-performance liquid chromatography-diode-array detection was conducted to check the accuracy of the proposed method.ResultsOptimum SDIC conditions included a Samsung C9 smartphone as the detection camera, a cropped region of interest of 6400 px2, and the side position of the colorimetric box were selected for capturing the images of the sample solutions placed 10.0 cm from the detection camera, whereas optimum complexation conditions were found to be as sample pH of 5.5, sample volume of 3.0 mL, complexation time of 1.0 min and a ligand concentration of 0.28 mmol L-1. Analytical performance of the method included a limit of detection of 0.5 μmol L-1 and a coefficient of determination (R2) of the calibration graph of 0.9981.ConclusionThe proposed method was successfully applied for the determination of aluminum in APPs with percentage recoveries ranging from 80.0 to 109.6%.

Smartphone digital image colorimetry (SDIC) was coupled with supramolecular solvent-based liquid-liquid microextraction (SMS-LLME) for the determination of curcumin. Images, captured for sample solutions placed inside a homemade colorimetric box, were split into their red-green-blue channels and the intensity of the blue channel was correlated to the concentration of curcumin. Optimum SDIC performance was achieved at a distance of 9.0 cm between the sample cuvette and the detection camera, a region of interest of 1600 px2 and a light source at 15% brightness. Optimum SMS-LLME efficiency was obtained with 1000 mu L of tetrahydrofuran/1undecanol (4:1, v/v) as the supramolecular extraction solvent, pH of sample solution adjusted to 7.0, and 2.0% (w/v) sodium chloride within 60 s extraction time. Limits of detection (LOD) were found in the range of 0.2-0.9 mu g mL-1 (0.04-0.18%, w/w). Calibration graphs demonstrated good linearity with coefficients of determination higher than 0.9965 and relative standard deviations lower than 8.5%. The proposed SMS-LLMESDIC method was applied to determine curcumin in turmeric and tea samples from which percentage relative recoveries between 94.0 and 104.0% were obtained.

Smartphone digital image colorimetry (SDIC), combined with solidification of floating organic drop-dispersive liquid-liquid microextraction (SFOD-DLLME), was proposed for the determination of iodate ions. A colorimetric box was designed to capture images of sample solutions. Factors affecting the efficiency of SDIC included type of phone, region of interest, position of camera, and distance between camera and sample solution. Optimum SFOD-DLLME conditions were achieved with 1-undecanol (500 mu L) as the extraction solvent, ethanol (1.5 mL) as the disperser solvent within 20 s extraction time. Limit of detection (LOD) was found as 0.1 mu M (0.2 mu g g(-1)) and enrichment factors ranged between 17.4 and 25.0. Calibration graphs showed good linearity with coefficients of determination higher than 0.9954 and relative standard deviations lower than 5.6%. The proposed method was efficiently applied to determine iodate in table salt samples with percentage relative recoveries ranging between 89.3 and 109.3%.

Switchable-hydrophilicity solvent liquid-liquid microextraction and dispersive liquid-liquid microextraction were compared for the extraction of piperine from Piper nigrum L. prior to its analysis by using high-performance liquid chromatography with UV detection. Under optimum conditions, limits of detection and quantitation were found as 0.2-0.6 and 0.7-2.0 mu g/mg with the two methods, respectively. Calibration graphs showed good linearity with coefficients of determination (R-2) higher than 0.9962 and percentage relative standard deviations lower than 6.8%. Both methods were efficiently used for the extraction of piperine from black and white pepper samples from different origins and percentage relative recoveries ranged between 90.0 and 106.0%. The results showed that switchable-hydrophilicity solvent liquid-liquid microextraction is a better alternative to dispersive liquid-liquid microextraction for the routine analysis of piperine in food samples. A novel scaled-up dispersive liquid-liquid microextraction method was also proposed for the isolation of piperine providing a yield of 102.9 +/- 4.9% and purity higher than 98.0% as revealed by NMR spectroscopy.

Dispersive liquid-liquid microextraction (DLLME) was combined with high-performance liquid chromatography-diodearray detector (HPLC-DAD) for the extraction and quantitation of three major capsaicinoids (i.e. capsaicin, dihydrocapsaicin and nordihydrocapsaicin) from pepper (Capsicum annuum L.). Chloroform (extraction solvent, 100 mu L), acetonitrile (disperser solvent, 1250 mu L) and 30 s extraction time were found optimum. The analytes were back-extracted into 300 mu L of 50 mM sodium hydroxide/ methanol, 45/55% (v/v), within 15 s before being injected into the instrument. Enrichment factors ranged from 3.3 to 14.7 and limits of detection from 5.0 to 15.0 mu g g(-1). Coefficients of determination (R-2) and %RSD were higher than 0.9962 and lower than 7.5%, respectively. The proposed method was efficiently applied for the extraction and quantitation of the three capsaicinoids in six cultivars of Capsicum annuum L. with percentage relative recoveries in the range of 92.0%-108.0%. DLLME was also scaled up for the isolation of the three major capsaicinoids providing purity greater than 98.0% as confirmed by liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) analysis, which significantly reduced the extraction time and organic solvent consumption.

Experimental.Plant materials and phytopharmaceutical productChemicals and apparatusPreparation of Standards and samplesInstrumentation and Chromatographic conditionsFiguresOptimisation of chromatographic conditionsS1:Effect of organic solvent type in the mobile phase on separation S2:Effect of initial and final concentration of ACN in the mobile phase on separation S3:Effect of gradient time on separation S4:Effect of column temperature on separation S5:Effect of flow rate on corrected peak area S6:Peak characterization in the crude extracts Indirect-dispersive liquid-liquid microextractionS7: Effect of IDLLME on the baseline, (a) before (b) after IDLLME, Peaks: 1, vitexin 2''-O-rhamnoside, 2, rutin, 3, vitexin, and 4, hyperoside.TablesS1:Optimum chromatographic conditions Determination of analytes in real samples S2:Concentration of analytes in the real samples