Ensuring food safety: Quality monitoring using microfluidics

In the field of safety detection of fruits and vegetables, how to conduct non-destructive detection of pesticide residues is still a pressing problem to be solved. In response to the high cost and destructive nature of existing chemical detection methods, this study explored the potential of identifying different pesticide residues on Hami melon by short-wave infrared (SWIR) (spectral range of 1000–2500 nm) hyperspectral imaging (HSI) technology combined with machine learning. Firstly, the classification effects of classical classification models, namely extreme learning machine (ELM), support vector machine (SVM), and partial least squares discriminant analysis (PLS-DA) on pesticide residues on Hami melon were compared, ELM was selected as the benchmark model for subsequent optimization. Then, the effects of different preprocessing treatments on ELM were compared and analyzed to determine the most suitable spectral preprocessing treatment. The ELM model optimized by Honey Badger Algorithm (HBA) with adaptive t-distribution mutation strategy (tHBA-ELM) was proposed to improve the detection accuracy for the detection of pesticide residues on Hami melon. The primitive HBA algorithm was optimized by using adaptive t-distribution, which improved the structure of the population and increased the convergence speed. Compared the classification results of tHBA-ELM with HBA-ELM and ELM model optimized by genetic algorithm (GA-ELM), the tHBA-ELM model can accurately identify whether there were pesticide residues and different types of pesticides. The accuracy, precision, sensitivity, and F1-score of the test set was 93.50%, 93.73%, 93.50%, and 0.9355, respectively. Metaheuristic optimization algorithms can improve the classification performance of classical machine learning classification models. Among all the models, the performance of tHBA-ELM was satisfactory. The results indicated that SWIR-HSI coupled with tHBA-ELM can be used for the non-destructive detection of pesticide residues on Hami melon, which provided the theoretical basis and technical reference for the detection of pesticide residues in other fruits and vegetables.

Determination of gadolinium-based MRI contrast agents in biological and environmental samples: A review

Pesticide residues in the fruits, vegetables and agricultural commodities are harmful to humans and are becoming a health concern nowadays. Detection of pesticide residues on various commodities in an open environment is a challenging task. Hyperspectral sensing is one of the recent technologies used to detect the pesticide residues. This paper addresses the problem of detection of pesticide residues of Cyantraniliprole on grapes in open fields using multi temporal hyperspectral remote sensing data. The re ectance data of 686 samples of grapes with no, single and double dose application of Cyantraniliprole has been collected by handheld spectroradiometer (MS- 720) with a wavelength ranging from 350 nm to 1052 nm. The data collection was carried out over a large feature set of 213 spectral bands during the period of March to May 2015. This large feature set may cause model over-fitting problem as well as increase the computational time, so in order to get the most relevant features, various feature selection techniques viz Principle Component Analysis (PCA), LASSO and Elastic Net regularization have been used. Using this selected features, we evaluate the performance of various classifiers such as Artificial Neural Networks (ANN), Support Vector Machine (SVM), Random Forest (RF) and Extreme Gradient Boosting (XGBoost) to classify the grape sample with no, single or double application of Cyantraniliprole. The key finding of this paper is; most of the features selected by the LASSO varies between 350-373nm and 940-990nm consistently for all days. Experimental results also shows that, by using the relevant features selected by LASSO, SVM performs better with average prediction accuracy of 91.98 % among all classifiers, for all days.

Pesticide residues in fruits and vegetables present a significant concern for human health and safety. By 2022, an average of 3 million people worldwide is poisoned by pesticides every year, and the mortality rate can reach about 20%. This comprehensive review summarizes recent research on the detection of pesticide residues, focusing on the main detection methods and their implications. The study highlights the growing importance of biosensors as a prominent technique, offering enhanced efficiency and accuracy in pesticide residue analysis. The review addresses the challenges associated with pretreatment methods and discusses the advantages and limitations of biosensors. Furthermore, it emphasizes the need for further research to optimize the adaptive capabilities of biosensors, particularly their anti-interference abilities. The findings underscore the significance of developing intelligent adaptive sensors for on-site pesticide residue detection, eliminating the need for complex sample pretreatment. This comprehensive review serves as a valuable reference, facilitating future advancements in pesticide residue analysis, ensuring food safety, and safeguarding consumer health in modern agriculture.

The synthetic tunability of ionic liquids (ILs), their structural versatility, and the wide range of interest properties that can present (from water soluble to water insoluble, from low density to high density, etc.), together with their impressive solvation abilities for different organic compounds, make their use in chromatographic and electrophoretic separation techniques an obvious approach of enormous interest. In fact, the studies of ILs have covered a number of topics in chromatographic and electrophoretic methods, from basic studies of performance to the development of complete analytical methods. Thus, they have been used in high-performance liquid chromatography (HPLC) as modifiers of mobile phases, as additives of mobile phases to improve the separation of basic analytes, as novel HPLC stationary phases, and even as pseudo-stationary phases in HPLC when utilizing ionic liquid-based surfactants, in a mode of micellar liquid chromatography (MLC). They have also experienced applications in counter-current chromatography (CCC), in which all phases involved have a liquid nature, acting as mobile phases or as stationary phases. In gas chromatography (GC), ILs have experienced an important application for developing novel stationary phases, characterized by their ability to separate polar and nonpolar compounds simultaneously, which is a problem in conventional GC columns. Moreover, they have been employed in capillary electrophoresis (CE) as background electrolytes in capillary zone electrophoresis (CZE), as pseudo-stationary phases in micellar electrokinetic chromatography (MEKC) if using IL-based surfactants at concentrations ensuring micelle formation and also in on-line CE preconcentration techniques based on the use of IL-based surfactants micelles such as sweeping-MEKC or micelle to solvent stacking, among others.

Improvements in living standards have led to an increase in the consumption of animal-derived foods. Pesticides may be used illegally during animal breeding as well as meat production and processing for pest control and preservation. Pesticides applied to crops may also be enriched in animal tissues through the food chain, thereby increasing the risk of pesticide residue accumulation in muscles and visceral tissues and endangering human health. China has stipulated maximum residue limits for pesticide residues in livestock and poultry meat and their viscera. Many other major developed countries and organizations, including the European Union, Codex Alimentarius Commission, and Japan, have also set maximum residue limits for these residues (0.005-10, 0.004-10, and 0.001-10 mg/kg, respectively). Research on pretreatment technologies for pesticide residue detection in plant-derived foods is widely available, but insufficient attention has been paid to animal-derived foods. Thus, high-throughput detection technologies for pesticide residues in animal-derived foods are limited. The impurities that can interfere with the detection process for plant-derived foods mainly include organic acids, polar pigments, and other small molecular compounds; by contrast, the matrix of animal-derived foods is much more complex. Macromolecular proteins, fats, small molecular amino acids, organic acids, and phospholipids can interfere with the detection of pesticide residues in animal-derived foods. Thus, selecting the appropriate pretreatment and purification technology is of great importance. In this study, the QuEChERS technique was combined with online gel permeation chromatography-gas chromatography-tandem mass spectrometry (GPC-GC-MS/MS) to determine 196 pesticide residues in animal-derived foods. The samples were extracted with acetonitrile, purified using the QuEChERS technique coupled with online GPC, detected by GC-MS/MS, determined in multiple reaction monitoring mode (MRM), and quantified using the external standard method. The effects of the extraction solvent and purification agent type on the extraction efficiency and matrix removal of the method were optimized. The purification effect of online GPC on the sample solution was investigated. The optimal distillate receiving time was obtained by studying the recoveries of the target substances and matrix effects over different distillate receiving periods to achieve the effective introduction of target substances and efficient matrix removal. Further, the advantages of the QuEChERS technique combined with online GPC were evaluated. The matrix effects of 196 pesticides were assessed; ten pesticide residues showed moderate matrix effects, while four pesticide residues showed strong matrix effects. A matrix-matched standard solution was used for quantification. The 196 pesticides showed good linearity in the range of 0.005-0.2 mg/L, with correlation coefficients greater than 0.996. The limits of detection and quantification were 0.002 and 0.005 mg/kg, respectively. The recoveries of 196 pesticides at spiked levels of 0.01, 0.05, and 0.20 mg/kg were 65.3%-126.2%, with relative standard deviations (RSDs) of 0.7%-5.7%. The proposed method is rapid, accurate, and sensitive; thus, it is suitable for the high-throughput screening and detection of multiple pesticide residues in animal-derived foods.

The existing methods of detecting pesticide residue include gas chromatography, high performance liquid chromatography, gas chromatograph-mass, liquid chromatograph-mass, capillary electrophoresis, radioimmunoassay, biosensor and rapid detection on the spot. The paper analyzes the comparison of gas chromatography and liquid chromatogram detecting pesticide residue, for achieving the development tendency and the future goal of analyzing pesticide residue.

Separation methods for pharmacologically active xanthones

Background Thalassemia and haemoglobinopathies pose a huge burden on Indian population, especially in Eastern India. Several studies indicated that abnormal hemoglobin variants influence Hb A1c estimation by High Performance Liquid Chromatography (HPLC) in patients with haemoglobinopathies. We opted capillary electrophoresis (CE) as an alternative method for Hb A1c measurement and aimed to evaluate Hb A1c test results done by (HPLC) with capillary electrophoresis (CE) to rule out the interference caused by abnormal hemoglobin variants. Methods A total of 3000 patients were tested for haemoglobinopathy in our laboratory from (1st -31th) January, 2025. Haemoglobinopathy were screened by Bio-Rad Variant II hemoglobin testing system. Both HPLC and CE methods were employed for Hb A1C testing in the group of patients (137/3000) with haemoglobinopathy using Bio-Rad Variant II Turbo and Sebia Minicap Flex Piercing respectively. Reference range defined for Hb A1c by HPLC: Non-diabetic: 4-5.7, Pre-Diabetic:5.7-6.4, Diabetic =6.5 and reference range for HbA1C by CE: <6 %. Statistical interpretation by was done by SPSS version 26.0. P value less than 0.05 was considered as significant. Statistical correlation was obtained by using Linear regression study. Results : 4.5% (137/3000) of total patients were reported to have abnormal hemoglobin variants in their HPLC chromatogram. 52% (72/137) Hb E carrier, 7.2% (10/137) homozygous E, 23.3% (32/137) beta thalassemia carriers, 1.4% (2/137) beta thalassemia major, 7.2% (10/137) Hb S carrier, 1.4% (2/137) homozygous S ,5.1% (7/137) Hb D carrier and 1.4% (2/137) HPFH (hereditary persistence of fetal hemoglobin) carrier comprised the group of haemoglobinopathies. We compared Hb A1c test results measured by HPLC and CE techniques. Hb A1c test values measured by using both the techniques were observed to be within reference range (Mean±SD: 5.24±1.05 by HPLC, Mean±SD: 5.19±1.08 by CE) in all patients with haemoglobinopathy. Hb A1c tests conducted in patients with haemoglobinopathies by HPLC and CE methods showed strong correlation in test results (Hb E trait: r=0.75 at p =0.01; beta thalassaemia traits: r=0.89 at p=0.04; Hb D: r=0.94 at p=0.2 Hb S: r=0.78 at p=0.21). In contrast to many reported studies, no observable difference was found in Hb A1c values in persons with haemoglobinopathies. HPLC and CE, both the methodologies failed to detect Hb A1c values in homozygous E, homozygous S and beta thalassaemia major patients. The study is limited by less number (n) of participants in each category which might attribute to high p value for determining level of significance. Conclusion Hb A1c test results done by HPLC and CE were in perfect concordance with each other. No such interference by abnormal haemoglobin variants on Hb A1c test results was observed in our study using HPLC method. Replacement of HPLC by CE as an alternative methodology is not necessitated rather both the methods can interchangeably be used for Hb A1c testing in patients with haemoglobinopathies. However, the present study is limited with small number of patients. An extensive study with larger participants is planned to validate the results claimed by our pilot study.

The excessive pesticide residues in cereals, fruit and vegetables is a big threat to human health, and it is necessary to develop a portable, low-cost and high-precision pesticide residue detection scheme to replace the large-scale laboratory testing equipment for rapid detection of pesticide residues. In this study, a colorimetric device for rapid detection of organophosphorus pesticide residues with high precision based on a microfluidic mixer chip was proposed. The microchannel structure with high mixing efficiency was determined by fluid dynamics simulation, while the corresponding microfluidic mixer chip was designed. The microfluidic mixer chip was prepared by a self-developed liquid crystal display (LCD) mask photo-curing machine. The influence of printing parameters on the accuracy of the prepared chip was investigated. The light source with the optimal wavelength of the device was determined by absorption spectrum measurement, and the relationship between the liquid reservoir depth and detection limit was studied by experiments. The correspondence between pesticide concentration and induced voltage was derived. The minimum detection concentration of the device could reach 0.045 mg·L−1 and the average detection time was reduced to 60 s. The results provide a theoretical and experimental basis for portable and high-precision detection of pesticide residues.

Evaluation of the CapillaryS 2 CE System for Hemoglobinopathy Investigations.

The methods of analysis for sulphonamide residues in edible animal products are reviewed. Sulphonamides are widely used for therapeutic and prophylactic purposes in both humans and animals, sometimes as growth promoters as additives in animal feed. As a result of their widespread use, there is concern about whether the levels used of these drugs can generate serious problems in human health, e.g., allergic or toxic reactions. Several methods for the determination of sulphonamides have been reported in the literature and this review considers high-performance liquid chromatography (HPLC), liquid chromatography-mass spectrometry (LC/MS), gas chromatography (GC), thin-layer chromatography (TLC), high-performance capillary electrophoresis (HPCE), enzyme-linked immunosorbant assay (ELISA), biosensor immunoassay (BIA) and microbiological methods. Specific aspects of analysing sulphonamides, such as sample handling, chromatographic conditions and detection methods are discussed. Methods for drug residue monitoring should be accurate, simple, economical in both time and cost, and capable of detecting residues below the maximum residue limits (MRL). The current sulphonamide detection technologies are based on chromatographic methods or bacteriological growth inhibition. The instrumental methods such as HPLC and GC are both sensitive and specific, but are laborious and expensive. Because of the labour-intensive processes, only a few cases of GC methods applied to residue analysis have been published. These methods are suitable for confirmation but not for screening of large numbers of samples. Microbiological methods do not require highly specialized and expensive equipment. They also use highly homogeneous cell populations for testing and thus result in better assay precision. Although HPCE has powerful separation ability, the precision is poor and the instrument still needs to be improved. To date, this technique has not been widely applied to routine analysis. Currently, TLC has been almost replaced by other instrumental analysis. A rapid, sensitive and specific assay is required to detect positive samples in routine analysis, which can then be confirmed for the presence of sulphonamides by HPLC. Immunochemical methods such as ELISA can be simple, rapid and cost-effective, with enough sensitivity and specificity to detect small molecules. This review can be considered as a basis for further research aimed at identifying the most efficient approaches.

Determination of silymarine in the extract from the dried silybum marianum fruits by high performance liquid chromatography and capillary electrophoresis

In the last few years capillary electrophoresis (CE) has become established alongside high performance liquid chromatography (HPLC) as a complementary, powerful separation technique for peptides and proteins. Along with the high speed, low sample requirement and overall lower running costs, a major advantage of CE is its flexibility. On one hand, typical HPLC separation modes, like reversed phase HPLC using differences in the hydrophobicity of components or ion-exchange chromatography using differences in the net charge of components can also be performed by micellar electrokinetic chromatography (MEKC) or capillary zone electrophoresis (CZE), respectively. On the other hand, typical slab gel electrophoresis separation modes like SDS (sodium dodecyl sulfate)—polyacrylamide gel electrophoresis (SDS-PAGE) or isoelectric focusing (IEF) can also be carried out by CE as capillary gel electrophoresis (CGE) or capillary isoelectric focusing (CIEF).

The abuse of pesticides in home gardens may lead to contamination of home-grown eggs. This study aimed to determine the prevalence of hexachlorocyclohexane (HCH), aldrin, and malathion pesticides residues in egg white and egg yolk of home-grown eggs in Jordan; and the effect of refrigerated storage and heat treatment (boiling and frying) on residues level. High-performance liquid chromatography was used to detect pesticide residues in egg samples (n = 200) obtained from households that raise laying hens in Jordan. About 96% of the tested eggs showed pesticide residues. None of the tested egg samples showed residual level above maximum residue limit (MRL 0.02mg/kg) for HCH, whereas 33% and 44% of samples were above MRL for aldrin and malathion, respectively. All studied pesticide residues were detected from both egg yolk and egg white. The concentrations of malathion and aldrin (0.075 and 0.067mg/kg) in egg yolk were higher than those (0.049 and 0.058mg/kg) in egg white samples. Pesticide residue levels were quite stable during refrigeration storage whereas heat treatment (boiling at 100°C and frying at 160°C) significantly reduced contamination levels to values below MRL. The high level of pesticide residues in home-grown egg in Jordan may reflect the improper use of pesticides in home gardens and thus exposing the environment to unwanted pollution and the risk they may pose on human health. PRACTICAL APPLICATION: Home-grown eggs could be exposed to pesticides more than commercial eggs as free-range hens interact directly with the environment and ingest soil or materials on/in the soil that might be contaminated with pesticides used in home gardens or farms. Exploring pesticides residues in home-grown eggs and effect of refrigerated storage and heat treatment (boiling and frying) on residue levels would be useful to consumers and health authorities.