Food Analysis Research Articles

Hydrofluoric Acid-Free Broadband Near-Infrared Phosphors K2LiMF6:Cr3+ with Zero-Thermal Quenching: Structure, Luminescence, and Application.

Near-infrared (NIR) phosphor-converted light-emitting diodes (pc-LEDs) are considered promising light sources for night vision, food analysis, biomedicine, and plant growth. Yet, the application potential of this technology is vulnerable to the function degradation of the phosphors used, such as thermal quenching, which needs to be addressed urgently. Herein, the NIR phosphors K2LiMF6:Cr3+ (M = Al, Ga, In) with a cubic double-perovskite structure synthesized by a green hydrofluoric acid-free hydrothermal method exhibit outstanding thermal stability. Under 450 nm excitation, the as-synthesized K2LiMF6:Cr3+ phosphors all exhibited broadband NIR emission covering 650-1000 nm peaking at 755-780 nm. The prepared K2LiAlF6:Cr3+ phosphor shows a unique zero-thermal quenching performance (I423K/I298K = 102%). The comprehensive effects of a wide band gap, large thermal energy barrier, weak electron-phonon coupling effect, and high structural rigidity are responsible for the suppression of thermal quenching in this material. The output power of the NIR pc-LED device reached 285 mW at 100 mA. This series of phosphors has promise in night vision and bioimaging applications.

Validation of a global method for the simultaneous analysis of polar and non-polar pesticides by online extraction and LC-MS/MS

BackgroundMulti-residue methods for pesticide analysis in food are available for many compounds, but polar pesticides are not generally included due to their specific properties, which include high polarity and low molecular weight. Single residue methods are therefore needed for sample preparation, while chromatographic separation often requires derivatization, ion paring, or dedicated methods suitable for polar compounds, mostly ion chromatography and hydrophilic interaction liquid chromatography (HILIC). These challenges affect the important pesticide glyphosate and the related compounds aminomethylphosphonic acid (AMPA) and glufosinate. There are only a few methods including these compounds in large-scale analysis, mostly complex methods based on multidimensional chromatography. ResultsA new method, for the global online extraction and analysis of pesticides in beer was developed and validated. The method exploited an online trapping device, with reversed-phase (RP) and anion exchange properties, that can trap small molecules from liquid samples. The ion exchange mechanism was used to retain the very polar pesticides glyphosate, AMPA, and glufosinate. The hydrophobic properties of the trapping column were also exploited to trap pesticides suitable for multi-residue investigations. The chromatographic separation was optimized by comparison of HILIC and RP C30, which could separate pesticides, including the polar ones, with modulation by the trapping column after proper selection of the mobile phase composition and basic modifier. The validation for beer provided recoveries in the range 71–112 %, with <15 % RSD, and LOD and LOQ values of 0.02–1 and 0.3–3 μg L−1, respectively. The result was competitive with previous methods on polar pesticide analysis in beer. SignificanceThe method was validated for 15 pesticides, over the log Kow range from −4.4 to 4.5, using a methodology with single and fast chromatographic separation under conditions compatible with multi-residue analysis by RP-LC-MS/MS. In the case of beer, for which the method was validated, the sample preparation was also performed online, after simple degassing, and sample dilution.

Chemometrics identification of geographical origin of garlic in Korea using elements concentrations data obtained by ICP-OES and ICP-MS

Discriminant analysis was performed according to the geographical origin of garlic using 60 elements. This study aimed to develop an analytical method for determining the geographical origin of garlic using inductively coupled plasma (ICP) analysis. Statistically significant differences were observed in 25 out of 60 elements. A total of 31 variable meanings in projection were selected from orthogonal partial least square discriminant analysis. The selected elements overlapped with those with significant differences, and those that did not were also included. The prediction of the selected element was confirmed using the area under the curve value of the receiver operating characteristic curve. A heatmap was also used to identify the geographic origin, and discriminant analysis of the geographic origin exhibited 100 % accuracy in standard discriminant analysis. This elemental analysis method exhibits promise as a food and agricultural product analysis tool, and can accurately determine the geographic origin of condiment vegetables other than garlic.

Electrical Bioimpedance in Milk Adulterated with Water: Measurement Methodology for Quantification, Influence of Temperature, and Mathematical Modelling

Milk has a high nutritional value and is also one of the most versatile products in the food industry. Unfortunately, fraud involving the product is constant and needs to be combated. This work presents a measurement methodology to perform the electrical impedance analysis in food. The influence of temperature on the measurements has been evaluated through mathematical models specially developed for identifying the fraudulent activity of adding water to milk. The bioimpedance measurements have been performed in a sample container with a four-electrode measurement system and a digital oscilloscope. Samples of 150 mL were analysed, prepared using whole UHT milk adulterated with distilled water in different % by volume (V/V), at temperatures of 16, 28, and 37 °C. The proposed measurement methodology has been validated and showed sensitivity for analysis in milk, revealing the influence of temperature on the impedance values; from the results mathematical models were proposed for investigating adulteration in milk. This work deals with the design of a device capable of measuring bioimpedance in milk with a view to its application in physicochemical analyses. The influence of temperature on the impedance values was also evaluated to propose mathematical models to facilitate analysis with complex factors and matrices.

Determination of Some Element’s Migrants in Aqueous Simulant from Plastic Food Contact Products by Inductively Coupled Plasma Mass Spectrometer

Various chemicals present at different stages in the food supply chain can lead to the leaching of heavy metals. These metals can accumulate in the human body through the consumption of contaminated food. Consequently, it is necessary to validate an analytical technique for the quantification chemical that could contaminate food. This study presents a rapid, straightforward, and efficient analytical method for the direct quantification of some potentially toxic elements in aqueous simulants from plastic food contact products using an inductively coupled mass spectrometer (ICP-MS). The method’s validation encompassed the study of the estimated detection limits, practical quantification limits, linearity, accuracy, and measurement uncertainty of aluminium (Al), antimony (Sb), arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), iron (Fe), lead (Pb), manganese (Mn), nickel (Ni), and zinc (Zn) under optimized ICP-MS conditions. The estimated detection limits ranged from 7.5 × 10−4 to 0.074 mg/kg, while practical quantification limits spanned from 0.02 to 0.8 mg/kg. The average recoveries ± standard deviations at different spiking levels were varied between 85.7 ± 1.51 and 115.6 ± 0.88% with coefficients of variation between 0.42 and 5.85%. The method trueness was verified by using references materials (test material in aqueous acetic acid) purchased from Food Chemistry Proficiency Testing and Analysis (FAPAS) yielding satisfactory results within acceptable recovery and Z-score values. The method precision, in terms of relative standard deviation (RSD), was being below 4.22%. The method uncertainty expressed as expanded uncertainty of all validated elements was found to be ≤ 21.9%. Validated method was employed to determine specific elements in aqueous simulants of thirty commercial plastic food packaging samples, representing three distinct types of plastic polymers. The results showed that the mean concentrations, in mg/kg, were as follows: 2.04 (Al), 0.02 (As), 0.02 (Cd), 0.02 (Co), 0.06 (Cr), 0.41 (Cu), 1.55 (Fe), 0.09 (Mn), 0.15 (Ni), 0.07 (Pb), 0.05 (Sb), and 0.81 (Zn). Furthermore, 30% of analyzed samples exceeding the maximum permissible limits of Al for plastic materials and articles intended to come into contact with food.

Platinum-based fluorescent nanozyme-driven “loong frolic pearls” multifunctional nanoplatform for tri-mode ultrasensitive detection and synergistic sterilization of Burkholderia gladioli

Rapid and accurate detection of Burkholderia gladioli (B. gladioli) and effective sterilization are crucial for ensuring food safety. Hence, a novel “loong frolic pearls” platform based on platinum-based fluorescent nanozymes (Pt-OCDs) and strand exchange amplification (SEA) was reported. Magnetic nanoparticles were modified on primer SEAF, while Pt-OCDs were covalently coupled with primer SEA-R. The highly efficient amplification capability of SEA permitted the accumulation of a large number of double-labeled amplicons. After magnetic adsorption, the supernatant was detected in reverse direction to collect colorimetric-fluorescence-photothermal signal values, enabling ultra-precise detection within 1 h. Furthermore, the Pt-based multifunctional nanoplatform generated abundant •OH and 1O2, which synergistically attacked B. gladioli and its biofilm, resulting in significant bactericidal efficacy within 30 min. This “triple-detection and double-sterilization” platform has been successfully applied in the field of food analysis with good recovery rates and immediate control over B. gladioli, thus demonstrating promising prospects for broad applications.

Mediated self-assembled gold nanoclusters with mesoporous silica particles to boost fluorescence for enhanced on-site monitoring of organophosphate pesticides

Accurate detection of organophosphate pesticides (OPs) is paramount for ensuring food safety. Dendritic mesoporous silica sphere was employed to confine gold nanoclusters (AuNCs@dmSiO2) to ameliorate fluorescent property of AuNCs. A AuNCs@dmSiO2-based fluorescent method was developed for OPs sensing. Identification of Cu2+ by AuNCs quenched AuNCs@dmSiO2 fluorescence. Interaction between Cu2+ and generated thiocholine in catalysis of acetylcholinesterase (AChE) caused fluorescence enhancement. OPs, an inhibitor of AChE, suppressed thiocholine production to cause fluorescence quenching. Based on fluorescent variation, a fluorescent method was proposed for OPs by selecting paraoxon as a model within range of 0.05–25.0 ng/mL with a limit of detection (LOD) of 0.032 ng/mL. Besides, a portable test swab was prepared for on-site monitoring OP paraoxon with a smartphone-based 3D-printing portable device with a LOD of 0.65 ng/mL. This work is highlighted by the inspiration of designing highly fluorescent AuNCs, and the provision of a viable avenue for OPs-related food analysis.

Electrospinning-based sensing technologies: Opportunities for food applications.

The article explores the science and practice of electrospinning, tracing its history and examining the factors that influence fiber morphology, including the solution composition, processing conditions, and environmental conditions. It offers a thorough examination of electrospinning fundamentals geared toward generating an appropriate platform for creating tailored nanofibers for sensing applications in the food industry. These nanofibers play a critical role in food analysis, sensing, and traceability, and we highlight their effectiveness in identifying pesticide residues, food components, antibiotics, heavy metals, and foodborne pathogens as well as in monitoring the freshness and spoilage of food. The use of electrospinning technology is poised to make sensing platforms more accessible, affordable, and widespread, thereby significantly contributing to the improvement of food quality and safety monitoring practices.

Quasi-hydrophobic deep eutectic solvents for simultaneous automated determination of polar and non-polar dyes in food products

In this work, quasi-hydrophobic deep eutectic solvents were used for the first time for the efficient extraction of both polar (Sunset Yellow FCF (E 110), Azorubine (E122), Ponceau 4R (E124)) and non-polar (Sudan I, Sudan II, Sudan III) dyes from food products at the same time. These solvents were made from polar and nonpolar components, which made it possible to extract analytes of various natures. To automate the technique, a flow analysis method was used, which increases the speed and reliability of determining analytes in food samples. For a detailed study of extraction mechanisms, various process modeling methods were used. The proposed DES-based method addresses the limitations of traditional extraction methods, offering a more robust and efficient solution for food analysis. Validation of the method has demonstrated high precision, accuracy and extraction efficiency, making it a promising tool for regulatory compliance and consumer safety in the food industry. The following analytical characteristics were achieved: the limits of detection were 0.03–0.13 mg L−1, limits of quantification were 0.09–0.44 mg L−1, an extraction recovery exceeding 85 %, a linear range was from 1 to 100 mg L−1, and a relative standard deviation ranging from 2 % to 10 %. The experiments were confirmed by both Conductor Like Screening Model-Segment Activity Coefficient (COSMO-SAC) and the Non-Covalent Interaction using the Reduced Density Gradient of the DES-dye system in aqueous media.

Decentralized food safety and authentication on cellulose paper-based analytical platform: A review.

Food safety and authenticity analysis play a pivotal role in guaranteeing food quality, safeguarding public health, and upholding consumer trust. In recent years, significant social progress has presented fresh challenges in the realm of food analysis, underscoring the imperative requirement to devise innovative and expedient approaches for conducting on-site assessments. Consequently, cellulose paper-based devices (PADs) have come into the spotlight due to their characteristics of microchannels and inherent capillary action. This review summarizes the recent advances in cellulose PADs in various food products, comprising various fabrication strategies, detection methods such as mass spectrometry and multi-mode detection, sampling and processing considerations, as well as applications in screening food safety factors and assessing food authenticity developed in the past 3 years. According to the above studies, cellulose PADs face challenges such as limited sample processing, inadequate multiplexing capabilities, and the requirement for workflow integration, while emerging innovations, comprising the use of simplified sample pretreatment techniques, the integration of advanced nanomaterials, and advanced instruments such as portable mass spectrometer and the innovation of multimodal detection methods, offer potential solutions and are highlighted as promising directions. This review underscores the significant potential of cellulose PADs in facilitating decentralized, cost-effective, and simplified testing methodologies to maintain food safety standards. With the progression of interdisciplinary research, cellulose PADs are expected to become essential platforms for on-site food safety and authentication analysis, thereby significantly enhancing global food safety for consumers.

Phosphorous intake in foods and phosphorus status markers in circulation in the Boston Puerto Rican Health Study

Phosphorus (P) additives may be deleterious for health. We measured the P content of key foods, and associations of P intake with biomarkers in the Boston Puerto Rican Health Study (BPRHS). Direct chemical analysis of 92 foods was done with the molybdenum blue spectrophotometric method and inductively coupled plasma mass spectrometry (ICP-MS). A novel algorithm was used to determine bioavailable, natural, and added P. We estimated P intakes from foods in 1323 participants, aged 45–75 y, and associations of these with serum P, fibroblast growth factor 23 (FGF23), parathyroid hormone (PTH), and Klotho. Relationships between intakes and status markers were assessed with Pearson’s correlations and t-tests. Our food analyses generally support P values in the USDA nutrient database, with the exceptions of American and cheddar cheese, which had more P than in the database. Women had higher added P intake than men, and younger participants had higher added P than those older. Total P intake tended to be positively associated with serum P and klotho, and inversely associated with PTH, but relationships were not strong. Puerto Rican adults have high intake of additive P. Culturally sensitive interventions that highlight dietary quality are needed.

An analysis of the safety of Sevoflurane drugs: A disproportionality analysis based on Food and Drug Administration Adverse Event Reporting System.

Sevoflurane is a volatile anesthetic that can tolerate inhalation induction and is widely used for inducing anesthesia due to its pleasant odor. As a drug that has been on the market for nearly 30 years, the vast majority of adverse reactions have been documented. This study aims to improve the adverse reactions related to Sevoflurane through the mining, organizing and analysis of Food and Drug Administration Adverse Event Reporting System database data. We collected, organized, and analyzed reports from the first quarter of 2004 to the fourth quarter of 2022. We performed disproportionality analysis algorithms, including reporting odds ratio, the proportional reporting ratio values, to quantify the signal values of different adverse events (AEs). A total of 1126 AEs and 27 system organ classes were identified by performing statistics analysis system software. By combining algorithm calculations, we create a forest map of the top 30 AEs of the reporting odds ratio signal. Based on the reviewing relevant literature, we found that the vast majority of AEs have been reported in relevant studies. However, there is currently no study revealing the correlation between atrial fibrillation and Sevoflurane, which means that atrial fibrillation may be an unreported AE of Sevoflurane. In the present study, we found that atrial fibrillation may be a new adverse reaction of Sevoflurane through the Food and Drug Administration Adverse Event Reporting System database, which can function as a novel guideline to guide us in the more standardized use of Sevoflurane in clinical practice.

Recent Developments in Personal Glucose Meters as Point-of-Care Testing Devices (2020-2024).

Point-of-care testing (POCT) is a contemporary diagnostic approach characterized by its user-friendly nature, cost efficiency, environmental compatibility, and lack of reliance on professional experts. Therefore, it is widely used in clinical diagnosis and other analytical testing fields to meet the demand for rapid and convenient testing. The application of POCT technology not only improves testing efficiency, but also brings convenience and benefits to the healthcare industry. The personal glucose meter (PGM) is a highly successful commercial POCT tool that has been widely used not only for glucose analysis, but also for non-glucose target detection. In this review, the recent advances from 2020 to 2024 in non-glucose target analysis for PGMs as POCT devices are summarized. The signal transduction strategies for non-glucose target analysis based on PGMs, including enzymatic transduction, nanocarrier transduction (enzyme or glucose), and glucose consumption transduction are briefly introduced. Meanwhile, the applications of PGMs in non-glucose target analysis are outlined, encompassing biomedical, environmental, and food analysis, along with other diverse applications. Finally, the prospects of and obstacles to employing PGMs as POCT tools for non-glucose target analysis are discussed.

Statistical Modeling of Within-Laboratory Precision Using a Hierarchical Bayesian Approach.

Reproducibility has been well studied in the field of food analysis; the RSD is said to follow a Horwitz curve with certain exceptions. However, little systematic research has been done on predicting repeatability or intermediate precision. We developed a regression method to estimate within-laboratory SDs using hierarchical Bayesian modeling and analyzing duplicate measurement data obtained from actual laboratory tests. The Hamiltonian Monte Carlo method was employed and implemented using R with Stan. The basic structure of the statistical model was assumed to be a Chi-squared distribution, the fixed effect of the predictor was assumed to be a nonlinear function with a constant term and a concentration-dependent term, and the random effects were assumed to follow a lognormal distribution as a hierarchical prior. By analyzing over 300 instances, we obtained regression results that fit well with the assumed model, except for moisture, which was a method-defined analyte. The developed method applies to a wide variety of analytes measured using general principles, including spectroscopy, GC, and HPLC. Although the estimated precisions were within the Horwitz ratio criteria for repeatability, some cases using high-sensitivity detectors, such as mass spectrometers, showed SDs below that range. We propose utilizing the within-laboratory precision predicted by the model established in this study for internal QC and measurement uncertainty estimation without considering sample matrices. Performing statistical modeling on data from double analysis, which is conducted as a part of internal QCs, will simplify the estimation of the precision that fits each analytical system in a laboratory.

Electrochemical detection of salicylic acid in fruit products with ternary ZnO/CuO/Y2O3 nanocomposites embedded PEDOT:PSS by differential pulse voltammetry

In this approach, a novel electrochemical sensor for the determination of salicylic acid (SA) in fruit juices was developed using a nanocomposite (NC) of ZnO/CuO/Y2O3 coated on a glassy carbon electrode (GCE). The ternary metal oxide NCs were synthesized via a facile hydrothermal method and thoroughly characterized using techniques such as X-ray photoelectron spectroscopy (XPS), X-Ray diffraction analysis (XRD), UV–Vis spectroscopy (UV–Vis), Fourier Transform Infrared Spectroscopy (FTIR), Field emission scanning electron microscopy (FESEM), and Energy-Dispersive X-Ray Spectroscopy (EDS). The NCs were then used to modify a flat-polished GCE surface, with a conducting polymer binder (PEDOT:PSS) used to facilitate the coating. Differential pulse voltammetry (DPV) was employed for the selective electrochemical detection of SA using this NC-modified GCE sensor. The DPV analysis exhibited a linear relationship between the peak current and SA concentration over a wide range of 1.5 ∼ 15.0 μM, indicating a large linear dynamic range. The sensor demonstrated excellent sensitivity, with a value of 5.79 μA μM−1 cm−2, and a low limit of detection of 0.18 ± 0.09 μM for SA. Additionally, the sensor’s performance was evaluated in terms of pH optimization, response time, stability, reproducibility, and repeatability. Importantly, the developed ZnO/CuO/Y2O3 NC-modified GCE sensor was successfully applied to the analysis of real fruit juice samples, showcasing its potential for practical applications in food analysis and quality control.

Reliable delineation of Bacillus cytotoxicus from other members of the Bacillus cereus group by MALDI-TOF MS – An extensive validation study

Bacillus cytotoxicus is classified as a thermotolerant member of the Bacillus cereus group, producing the diarrhoea causing cytotoxin K1. This species came into the focus of food microbiologists when the type strain was isolated as the cause of a fatal food-borne outbreak. However, knowledge of the role of B. cytotoxicus as a food-borne microbe and data on its prevalence in food is still limited today. One reason for this is the lack of an easy to perform method of identification at the species level other than PCR, due to the highly similar phenotype of many B. cereus group representatives. Matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS) is widely used for the identification of microorganism species. This study describes the formal validation of a MALDI-TOF MS system for a reliable differentiation between B. cytotoxicus and other members of the B. cereus group. An extensive number of well-supported individual spectra from B. cytotoxicus, several other species of the B. cereus group, and 652 other microorganism species in a taxonomically wide range served as data sets. These were used to perform the validation for two database compilations: the commercial MALDI-Biotyper version K, and an extended compilation, including reference spectra from an open collection of spectra created by several users. Using both database combinations, the obtained values fulfil the formal criteria for the targeted identification of B. cytotoxicus in accordance with a national guideline for the validation of MALDI-TOF MS parameters in food analysis, with significant improvements due to the expanded database. By using 183 single spectra from 170 isolates, created in eleven different laboratories, the number of samples significantly exceeded the sample sizes for validation currently specified for ISO 16140–4:2020 for the validation of identification methods in food microbiology by single laboratories. Therefore, the method is suitable for routine application in an accredited laboratory context.

Correlational Analysis of Food and Nutrition Literacy and Academic Performance among Intermediate-Level Students

This study aimed to determine the significant relationship between food and nutrition literacy and academic performance among intermediate-level students. Total population sampling was used which included fifty-three respondents. Through non-experimental quantitative descriptive-correlational research technique, validated questionnaire, Mean, and Pearson-Product Moment Correlation Coefficient (Pearson-r); results showed that the level of food and nutrition literacy was high or evident. It was also found out that the level of students’ academic performance was satisfactory. There was a no significant relationship between food and nutrition literacy and students’ academic performance. This means that the level of knowledge and skills about food and nutrition does not have a significant association to the academic performance of the students. In other words, whether a student knows a lot or a little about food and nutrition does not significantly correlate with their grades or academic success. The researchers recommended that teachers continue educating students about food and nutritional concepts, as well as developing academic performance. In addition to that, future researchers may conduct longitudinal studies to track the impact of food and nutrition literacy over time.

Low-cost heat assisted ambient ionization source for mass spectrometry in food and pharmaceutical screening.

Ambient Ionization Mass Spectrometry (AI-MS) techniques have revolutionized analytical chemistry by enabling rapid analysis of samples under atmospheric conditions with minimal to no preparation. In this study, the optimization of a cold atmospheric plasma for the analysis of food and pharmaceutical samples, liquid and solid, using a Heat-Assisted Dielectric Barrier Discharge Ionization (HA-DBDI) source is described. A significant enhancement in analyte signals was observed when a heating element was introduced into the design, potentially allowing for greater sensitivity. Furthermore, the synergy between the inlet temperature of the mass spectrometer and the heating element allows for precise control over the analytical process, leading to improved detection sensitivity and selectivity. Incorporating computational fluid dynamic (CFD) simulations into the study elucidated how heating modifications can influence gas transport properties, thereby facilitating enhanced analyte detection and increased signal intensity. These findings advance the understanding of HA-DBDI technology and provide valuable insights for optimizing AI-MS methodologies for a wide range of applications in food and pharmaceutical analysis.

Green synthesis of N,S dual heteroatom-doped fluorescent carbon dots (N,S-CDs) and their applications in gentamicin sensing and dual-switch anti-counterfeiting encryption

Herein, we report a facile one-step solvothermal synthesis of nitrogen and sulfur co-doped fluorescent carbon dots (N,S-CDs) using benzoic acid as the carbon source and sulfonamide as the doping agent. The synthesized N,S-CDs exhibit stable photoluminescence with an impressive fluorescence quantum yield of 16.8 %. These N,S-CDs maintain their luminescent properties under various challenging conditions, including high salt concentrations, elevated temperatures, UV radiation exposure, acidic or alkaline environments, long-term storage, and different solvents. Notably, the photoluminescence of N,S-CDs is excitation-wavelength dependent, with emission wavelengths tunable from 470 nm to 585 nm. Furthermore, the N,S-CDs display distinct fluorescent hues in aqueous and ethanolic media, presenting a novel dual-switch anti-counterfeiting ink system. Leveraging the sensitivity of N,S-CDs to gentamicin, we have developed a facile and rapid detection method for this antibiotic, which has been successfully applied to the analysis of authentic milk samples. This research contributes a novel and efficient protocol for the fabrication of high-performance carbon dots, thereby expanding their potential applications in food analysis and anti-counterfeiting technologies.

Deep Eutectic Solvent Liquid-Liquid Microextraction Prior to Smartphone Digital Image Colorimetry for the Determination of Iodate in Table Salt

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 µmol L−1, and a limit of quantitation (LOQ) between 1.73 and 2.81 µmol 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 µmol 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.