Indirect ultra-trace determination of nitrate and nitrite in food samples by in-syringe liquid microextraction and electrothermal atomic absorption spectrometry

Machine learning trained poly (3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles for precise monitoring of nitrite from pickled vegetables

Precise monitoring of nitrite from real samples has gained significant attention due to its detrimental impact on human health. Herein, we have fabricated poly(3,4-ethylenedioxythiophene) functionalized carbon matrix suspended Cu nanoparticles (PEDOT-C@Cu-NPs) through a facile green synthesis approach. Additionally, we have used machine learning (ML) to optimize experimental parameters such as pH, drying time, and concentrations to predict current of the designed electrochemical sensor. The ML optimized concentration of fabricated C@Cu-NPs was further functionalized by PEDOT (π-electron mediator). The designed PEDOT functionalized C@Cu-NPs (PEDOT-C@Cu-NPs) electrode has shown excellent electro-oxidation capability towards NO2- ions due to highly exposed Cu facets, defects rich graphitic C and high π-electron density. Additionally, the designed material has shown low detection limit (3.91 μM), high sensitivity (0.6372 μA/μM/cm2), and wide linear range (5-580 μM). Additionally, the designed electrode has shown higher electrochemical sensing efficacy against real time monitoring from pickled vegetables extract.

Nitrate in groundwater and agricultural products: intake and risk assessment in northeastern Iran

The suitability of groundwater and agricultural products for human consumption requires determining levels and assessing the health risks associated with potential pollutants. Here, particularly pollution with nitrate still remains a challenge, especially for those urban areas suffering from insufficient sewage collection systems, resulting in contaminating soil, endangering food safety, and deteriorating drinking water quality. In the present study, nitrate concentrations in the commonly consumed fruit and vegetable species were determined, and the results, together with the groundwater nitrate levels, were used to assess the associated health risks for Mashhad city residents. For this assessment, 261 water samples and 16 produce types were used to compute the daily intake of nitrate. Nitrate in groundwater was analyzed using a spectrophotometer, and produce species were examined using High-Performance Liquid Chromatography. Ward's hierarchical cluster analysis was applied for categorizing produce samples with regard to their nitrate content. Additionally, to account for the sanitation hazards associated with groundwater quality for drinking purposes, total coliform and turbidity were also assessed using the membrane filter (MF) technique and a nephelometer, respectively. Nitrate concentrations exceeded the prescribed permissible limits in 42% of the groundwater wells. The outcomes also exhibit significantly higher nitrate accumulation levels in root-tuber vegetables and leafy vegetables compared to fruit vegetables and fruits. Using cluster analysis, the accumulation of nitrate in vegetables and fruits was categorized into four clusters, specifying that radish contributes to 65.8% of the total content of nitrate in all samples. The Estimated Daily Intake (EDI) of nitrate and Health Risk Index (HRI) associated with consumption of groundwater exceeded the prescribed limit for the children's target group in Mashhad's south and central parts. Likewise, EDI and HRI values for produce consumption, in most samples, were found to be in the tolerable range, except for radish, lettuce, and cabbage, potentially posing risks for both children and adult consumers. The total coliforms in groundwater were found to violate the prescribed limit at 78.93% of the sampling locations and were generally much higher over the city's central and southern areas. A relatively strong correlation (R2 = 0.6307) between total coliform and nitrate concentrations suggests the release of anthropogenic pollution (i.e., sewage and manure) in the central and southern Mashhad.

Study of nitrate levels in fruits and vegetables to assess the potential health risks in Bangladesh

Nitrate is a chemical compound naturally present in fruits and vegetables. This study aims at assessing the nitrate levels and health risks arising from high consumption of fruits and vegetables in Bangladesh. Sixteen species of fruits and vegetables were examined for nitrates using High-Performance Liquid Chromatography with Photo Diode Array (PDA) detector. Ward's hierarchical cluster analysis was carried out to identify the cluster of tested fruits and vegetables for the nitrate contents. A point estimate of the daily intake was applied to find the health risks that arise due to elevated levels of nitrate in fruits and vegetables. The results show that root and tuber vegetables accumulate significantly higher levels of nitrate in comparison to fruits and fruit vegetables (P < 0.05). In cluster analysis, the nitrate accumulation of fruits and vegetables show four clear clusters contributing to 29.54%, 7.17%, 4.42%, and 58.57% of the total nitrate content in the entire sample. The risk assessment of the Estimated Daily Intake (EDI) and Health Risk Index (HRI) of almost all the tested samples was in the acceptable range, except for radish, thereby indicating the acceptance of risk due to nitrate intake in Bangladesh. As nitrate may have had risk factor for health, during cultivation and storing the product should be properly monitored.

A green and efficient vortex-assisted liquid-phase microextraction based on supramolecular solvent for UV-VIS determination of nitrite in processed meat and chicken products

This paper describes a simple, efficient and rapid analytical method for extraction and determination of nitrite in meat and chicken products by vortex-assisted supramolecular solvent-based liquid phase microextraction (VA-SUPRAS-LPME) prior to spectrophotometric detection. The SUPRAS was rapidly formed by the addition of a colloidal decanoic acid suspension to tetrahydrofuran (THF). The validation studies were carried out in terms of linearity, limit of detection (LOD), limit of quantitation (LOQ), matrix effects, robustness, uncertainty measurement, precision, accuracy, and certified reference material (CRM) analysis using optimized experimental conditions. The LOD, LOQ, linearity and matrix effect were 0.035 ng mL^-1, 0.1 ng mL^-1, 0.1-300 ng mL^-1, and 9.6% respectively, with high preconcentration factor (200). The method was successfully applied for the determination of nitrite in processed products. Moreover, the results obtained by the proposed method were compared to the standard Griess method, and showed no significant differences in term of Student's t-test.

Review: Microextraction Technique Based New Trends in Food Analysis

Food chemistry is the study and classification of the quality and origin of foods. The identification of definite biomarkers and the determination of residue contaminants such as toxins, pesticides, metals, human and veterinary drugs, which are a very common source of food-borne diseases. The food analysis is continuously demanding the improvement of more robust, sensitive, highly efficient, and economically beneficial analytical approaches to promise the traceability, safety, and quality of foods in the acquiescence with the consumers and legislation demands. The traditional methods have been used at the starting of the 20th century based on wet chemical methods. Now it existing the powerful analytical techniques used in food analysis and safety. This development has led to substantial enhancements in the analytical accuracy, precision, sensitivity, selectivity, thereby mounting the applied range of food applications. In the present decade, microextraction (micro-scale extraction) pays more attention due to its futures such as low consumption of solvent and sample, throughput analysis easy to operate, greener, robotics, and miniaturization, different adsorbents have been used in the microextraction process with unique nature recognized with wide range applications.

Porous ionic liquid polymer: A reusable adsorbent with broad operating pH range for speciation of nitrate and nitrite

Ionic liquids (ILs) are a class of fluids with unique physicochemical properties employing polymeric substances emerging new materials. Solidification of ILs into porous materials generates porous ionic liquid polymers that combine the unique characteristics of ILs with common porous materials and polymers. In this study, it's the first time the porous ionic liquid polymer was chosen as a sorbent for extraction and speciation of nitrite and nitrate. Porous IL was prepared through polymerization of 1-allyl-3-methylimidazolium bromide monomers in the presence of azobisisobutyronitrile (AIBN) and crosslinking of ethylene glycol dimethyl acrylate (EGDMA). Parameters affecting the adsorbent performance were optimized. Under the optimal conditions, correlation coefficient (R²) was 0.9996 and LOD was 0.1 µg L^-1. This method presented the linearity in the concentration range between 0.1-100 µg L^-1 and the relative standard deviation was 3.2%. Finally, the adsorption behavior of the obtained sorbent for nitrate and nitrite determination in various real samples was evaluated. The result indicates that the porous ionic liquid polymer showed high adsorption capacity (233 mg g^-1). The convenient preparation of the porous ionic liquid material, as well as high adsorption capacity for anionic pollutants predicted its broad application potential in anion removal materials.

Monitoring and exposure assessment of nitrate intake via fruits and vegetables in high and low risk areas for gastric cancer

BACKGROUND

Gastric cancer (GC) is the first leading cause of cancer-related deaths in Iran. GC is a multifactorial disease and is caused by the interaction of genetic and environmental factors. The aim of this study was to assess the exposure and risk of nitrate intake through fruits and vegetables (F&V) in high-risk area (HRA) and low-risk area (LRA) of GC in Iran.

METHODS

Twenty nine species of F&V were examined for nitrate by reverse-phase HPLC (RP-HPLC) method. Food frequency questionnaire (FFQ) data of 2000 adults participating in Persian cohort were applied to determine consumption patterns of F&V in those areas. A point-estimate daily intake was applied to compare two areas in terms of nitrate intake. Monte-Carlo simulation technique was applied to estimate chronic daily intake (CDI) of nitrate.

RESULTS

The results showed that point-estimate daily intake of nitrate for subjects participated in the study was 2.02 ± 1.02 mg kg-1 day-1 in HRA and 1.98 ± 1.05 mg kg-1 day-1 in LRA. 6.53% of the participants in the HRA, and 5.9% of the participants in the LRA had an unacceptable point-estimate daily intake compared with an acceptable limit of 3.7 mg kg-1 day-1 established by FAO/WHO. CDI of nitrate in HRA was 1.94 ± 0.95 mg kg-1 day-1 and in the LRA was 1.93 ± 1.06 mg kg-1 day-1.

CONCLUSION

The results showed that there is no difference between HRA and LRA in terms of nitrate intake through F&V.