Efficient porphyrin integrated UiO-66 probes for ratiometric fluorescence sensing of antibiotic residues in milk.

Dual-emissive fluorescence probes were designed by integrating porphyrin into the frameworks of UiO-66 for ratiometric fluorescence sensing of amoxicillin (AMX). Porphyrin integrated UiO-66 showed dual emission in the blue and red region. AMX resulted in the quenching of blue fluorescence component, attributable to the charge neutralization and hydrogen bonds induced energy transfer. AMX was detected using (F438/F654) as output signals. Two linear relationships were observed (from 10 to 1000 nM and 1 to 100 µM), with a limit of detection of 27 nM. The porphyrin integrated UiO-66 probe was used to detect AMX in practical samples. This work widens the road for the development of dual/multiple emissive fluorescence sensors for analytical applications, providing materials and theoretical supporting for food, environmental, and human safety.

Global trends of dioxin and dioxin-like PCBs in animal-origin foods: a systematic review and gap areas.

Dioxins and dioxin-like polychlorinated biphenyls are a group of lipophilic compounds classified under persistent environmental pollutants (POPs). Significant sources of dioxin emissions include industrial effluents, open burning practices, and biomedical and municipal waste incinerators. These emissions will enter the food chain and accumulate in animal-origin foods (AOFs). A systematic review was conducted to analyze the global levels of dioxins and dioxin-like PCBs in AOFs using PRISMA guidelines 2020. The data on the dioxin contamination in AOFs were extracted from 53 publications based on their presence in eggs, meat and meat products, milk and dairy products, marine fish and fish products, and freshwater fish and crabs. A gap analysis was conducted based on the systematic review to understand the grey areas to be focused on the  future. No trend of dioxin contamination in AOFs was observed. A significant gap area was found in the need for nationwide data generation in countries without periodic monitoring of AOFs for dioxin contamination. Source apportionment studies need to be explored for the dioxin contamination of AOFs. Large-scale screening tests of AOFs using DR-CALUX based on market surveys are required for data generation. The outcomes of the study will be helpful for stakeholders and policyholders in framing new policies and guidelines for food safety in AOFs.

Improving the detection accuracy of the dual SERS aptasensor system with uncontrollable SERS "hot spot" using machine learning tools.

BACKGROUND: Simultaneous detection of food contaminants is crucial in addressing the collective health hazards arising from the presence of multiple contaminants. However, traditional multi-competitive surface-enhanced Raman scattering (SERS) aptasensors face difficulties in achieving simultaneous accurate detection of multiple target substances due to the uncontrollable SERS "hot spots". In this study, using chloramphenicol (CAP) and estradiol (E2) as two target substances, we introduced a novel approach that combines machine learning methods with a dual SERS aptasensor, enabling simultaneous high-sensitivity and accurate detection of both target substances. RESULTS: The strategy effectively minimizes the interference from characteristic Raman peaks commonly encountered in traditional multi-competitive SERS aptasensors. For this sensing system, the Au@4-MBA@Ag nanoparticles modified with sulfhydryl (SH)-CAP aptamer and Au@DTNB@Ag NPs modified with sulfhydryl (SH)-E2 aptamer were used as signal probes. Additionally, Fe3O4@Au nanoflowers integrated with SH-CAP aptamer complementary DNA and SH-E2 aptamer complementary DNA were used as capture probes, respectively. When compared to linear regression random forest, and support vector regression (SVR) models, the proposed artificial neural network (ANN) model exhibited superior precision, demonstrating R2 values of 0.963, 0.976, 0.991, and 0.970 for the training set, test set, validation set, and entire dataset, respectively. Validation with ten spectral groups reported an average error of 244 µg L-1. SIGNIFICANCE: The essence of our study lies in its capacity to address a persistent challenge encountered by traditional multiple competitive SERS aptasensors - the interference generated by uncontrollable SERS "hot spots" that hinders simultaneous quantification. The accuracy of the predictive model for simultaneous detection of two target substances was significantly improved using machine learning tools. This innovative technique offers promising avenues for the accurate and high-sensitive simultaneous detection of multiple food and environmental contaminants.

Gold nanoparticles-doped MXene heterostructure for ultrasensitive electrochemical detection of fumonisin B1 and ampicillin.

Early transition metal carbides (MXene) hybridized by precious metals open a door for innovative electrochemical biosensing device design. Herein, we present a facile one-pot synthesis of gold nanoparticles (AuNPs)-doped two-dimensional (2D) titanium carbide MXene nanoflakes (Ti3C2Tx/Au). Ti3C2Tx MXene exhibits high electrical conductivity and yields synergistic signal amplification in conjunction with AuNPs leading to excellent electrochemical performance. Thus Ti3C2Tx/Au hybrid nanostructure can be used as an electrode platform for the electrochemical analysis of various targets. We used screen-printed electrodes modified with the Ti3C2Tx/Au electrode and functionalized with different biorecognition elements to detect and quantify an antibiotic, ampicillin (AMP), and a mycotoxin, fumonisin B1 (FB1). The ultralow limits of detection of 2.284 pM and 1.617 pg.mL-1, which we achieved respectively for AMP and FB1 are far lower than their corresponding maximum residue limits of 2.8 nM in milk and 2 to 4 mg kg-1 in corn products for human consumption set by the United States Food and Drug Administration. Additionally, the linear range of detection and quantification of AMP and FB1 were, respectively, 10 pM to 500 nM and 10 pg mL-1 to 1 µg mL-1. The unique structure and excellent electrochemical performance of Ti3C2Tx/Au nanocomposite suggest that it is highly suitable for anchoring biorecognition entities such as antibodies and oligonucleotides for monitoring various deleterious contaminants in agri-food products.

Microbiome mapping in beef processing reveals safety-relevant variations in microbial diversity and genomic features.

The microbiome of surfaces along the beef processing chain represents a critical nexus where microbial ecosystems play a pivotal role in meat quality and safety of end products. This study offers a comprehensive analysis of the microbiome along beef processing using whole metagenomics with a particular focus on antimicrobial resistance and virulence-associated genes distribution. Our findings highlighted that microbial communities change dynamically in the different steps along beef processing chain, influenced by the specific conditions of each micro-environment. Brochothrix thermosphacta, Carnobacterium maltaromaticum, Pseudomonas fragi, Psychrobacter cryohalolentis and Psychrobacter immobilis were identified as the key species that characterize beef processing environments. Carcass samples and slaughterhouse surfaces exhibited a high abundance of antibiotic resistance genes (ARGs), mainly belonging to aminoglycosides, ß-lactams, amphenicols, sulfonamides and tetracyclines antibiotic classes, also localized on mobile elements, suggesting the possibility to be transmitted to human pathogens. We also evaluated how the initial microbial contamination of raw beef changes in response to storage conditions, showing different species prevailing according to the type of packaging employed. We identified several genes leading to the production of spoilage-associated compounds, and highlighted the different genomic potential selected by the storage conditions. Our results suggested that surfaces in beef processing environments represent a hotspot for beef contamination and evidenced that mapping the resident microbiome in these environments may help in reducing meat microbial contamination, increasing shelf-life, and finally contributing to food waste restraint.

A new physical and biological strategy to reduce the content of zearalenone in infected wheat kernels: the effect of cold needle perforation, microorganisms, and purified enzyme.

With the aim of reintroducing wheat grains naturally contaminated with mycotoxins into the food value chain, a decontamination strategy was developed in this study. For this purpose, in a first step, the whole wheat kernels were pre-treated using cold needle perforation. The pore size was evaluated by scanning electron microscopy and the accessibility of enzymes and microorganisms determined using fluorescent markers in the size range of enzymes (5 nm) and microorganisms (10 µm), and fluorescent microscopy. The perforated wheat grains, as well as non-perforated grains as controls, were then incubated with selected microorganisms (Bacillus megaterium Myk145 and B. licheniformis MA572) or with the enzyme ZHD518. The two bacilli strains were not able to significantly reduce the amount of zearalenone (ZEA), neither in the perforated nor in the non-perforated wheat kernels in comparison with the controls. In contrast, the enzyme ZHD518 significantly reduced the initial concentration of ZEA in the perforated and non-perforated wheat kernels in comparison with controls. Moreover, in vitro incubation of ZHD518 with ZEA showed the presence of two non-estrogenic degradation products of ZEA: hydrolysed zearalenone (HZEA) and decarboxylated hydrolysed ZEA (DHZEA). In addition, the physical pre-treatment led to a reduction in detectable mycotoxin contents in a subset of samples. Overall, this study emphasizes the promising potential of combining physical pre-treatment approaches with biological decontamination solutions in order to address the associated problem of mycotoxin contamination and food waste reduction.

Non-invasive prediction of maca powder adulteration using a pocket-sized spectrophotometer and machine learning techniques.

Discriminating different cultivars of maca powder (MP) and detecting their authenticity after adulteration with potent adulterants such as maize and soy flour is a challenge that has not been studied with non-invasive techniques such as near infrared spectroscopy (NIRS). This study developed models to rapidly classify and predict 0, 10, 20, 30, 40, and 50% w/w of soybean and maize flour in red, black and yellow maca cultivars using a handheld spectrophotometer and chemometrics. Soy and maize adulteration of yellow MP was classified with better accuracy than in red MP, suggesting that red MP may be a more susceptible target for adulteration. Soy flour was discovered to be a more potent adulterant compared to maize flour. Using 18 different pretreatments, MP could be authenticated with R2CV in the range 0.91-0.95, RMSECV 6.81-9.16 g/,100 g and RPD 3.45-4.60. The results show the potential of NIRS for monitoring Maca quality.

Integrated molybdenum single atom array sensors with multichannels for nitrite detection in foods.

Nitrite (NO2-) is present in a variety of foods, but the excessive intake of NO2- can indirectly lead to carcinogenic, teratogenic, mutagenicity and other risks to the human body. Therefore, the detection of NO2- is crucial for maintaining human health. In this study, an integrated array sensor for NO2- detection is developed based on molybdenum single atom material (IMSMo-SAC) using high-resolution electrohydrodynamic (EHD) printing technology. The sensor comprises three components: a printed electrode array, multichannels designed on polydimethylsiloxane (PDMS) and an electronic signal process device with bluetooth. By utilizing Mo-SAC to facilitate electron transfer during the redox reaction, rapid and efficient detection of NO2- can be achieved. The sensor has a wide linear range of 0.1 µM-107.8 mM, a low detection limit of 33 nM and a high sensitivity of 0.637 mA-1mM-1 cm-2. Furthermore, employing this portable array sensor allows simultaneously measurements of NO2- concentrations in six different foods samples with acceptable recovery rates. This array sensor holds great potential for detecting of small molecules in various fields.

Determination of chlorothalonil in vegetables/fruits using liquid chromatography-tandem mass spectrometry with a discharge adapter interface.

RATIONALE: Chlorothalonil (CHT), a broad-spectrum fungicide, has been employed widely to control foliar diseases, whereas with a major metabolite of polar 4-hydroxychlorothalonil (CHT-4-OH), only an acceptable nonpolar CHT residue is allowed by most countries. This study involves the method development for CHT residue in vegetables/fruits using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with a novel modified discharge-adaptor (DA) interface. METHODS: CHT residue was analyzed using LC-MS/MS with DA interface (LC-DA-MS/MS), developed in our previous works. A DA was placed on the electrospray tip to switch the ionization modes. A modified quick, easy, cheap, effective, rugged, and safe (QuEChERS) method was applied to extract CHT residue of vegetables/fruits efficiently with less sample preparation time and analysis cost. RESULTS: CHT and CHT-4-OH spiked in four different vegetables/fruits were extracted using the modified QuEChERS method. After LC with isocratic elution, CHT and CHT-4-OH were separated within 3 min. Using LC-DA-MS/MS, the ion signals of CHT were improved two to three times, and the limit of quantification of 5 ng/g and linearity (r2 > 0.99) in the range of 5-200 ng/g were achieved using 10 g of vegetables/fruits. The precision and accuracy were within 15% each. The modified QuEChERS and LC-DA-MS/MS were applied to examine eight field-grown vegetables/fruits; 9.5 and 2588.9 ng/g of CHT were detected in two vegetables/fruits. CONCLUSION: LC-DA-MS/MS combined with modified QuEChERS was successfully applied to determine CHT residue <10 ng/g in vegetables/fruits and with satisfied validation results. The developed method could reduce both analysis cost and time, attributing to simplifications in modified QuEChERS, isocratic elution, and DA interface in LC-DA-MS/MS.

Comprehensive identification and risk assessment of regulated and emerging mycotoxins in infant foods and related raw materials and risk management advice: A case study of an infant food company in China.

This study evaluated muti-mycotoxins in 199 samples including processed infant foods and raw materials collected randomly from an infant food company and assessed their role in dietary exposure in infants and young children via probabilistic risk assessment. Approximately 79.6 % (74/93) of the processed infant foods and 65.1 % (69/106) of the raw materials were contaminated by mycotoxins, with a mean occurrence level of 3.66-321.8 µg/kg. Deoxynivalenol (DON) and tenuazonic acid (TeA) were the more prevalent mycotoxins detected, based on their higher frequencies and levels across samples. Co-occurrence of more than two mycotoxins was detected in 61.3 % (57/93) of the processed infant foods and 53.8 % (57/106) of the raw materials. Wheat flour and derived products (e.g., infant noodles and infant biscuits) were contaminated with higher contamination levels and a greater variety of mycotoxins than other samples (e.g., infant cereal and rice grains). The estimated daily exposure to OTA, DON, ZEN, and TEN was lower than the corresponding reference health-based guidance values, indicating acceptable health risks. However, the estimated dietary exposure to alternariol monomethyl ether (AME), alternariol (AOH), and tenuazonic acid (TeA) exceeded the corresponding thresholds of toxicological concern values, indicating potential dietary intake risks. Among the various samples, cereals and cereal-based infant foods emerged as the primary contributors to mycotoxin exposure. Further research is advised to address the uncertainties surrounding the toxicity associated with emerging Alternaria mycotoxins and to conduct cumulative risk assessments concerning multiple mycotoxin exposure in infants and young children.

Occurrence of heavy metals coupled with elevated levels of essential elements in chocolates: Health risk assessment.

The presence of contaminants in cacao-derived products, especially in chocolates, has raised concerns regarding food safety and human health. The study assessed the concentration variation of 16 elements in 155 chocolate samples from the US market by cacao content and country of geographic origin. The study further examined the potential health risks posed by toxic metals and determined the contribution of essential elements to the Daily Recommended Intake (DRI), estimated based on an ounce (∼28.4 g) of daily chocolate consumption. Dark chocolates with ≥50 % cacao exhibited consecutively increasing mean levels from 1.2 to 391 µg/kg for U, Tl, Th, As, Pb, Se, Cd, and Co. Similarly, Ni, Sr, Cu, Mn, Zn, Fe, Ca, and Mg had mean concentrations from 4.0 to 1890 mg/kg. Dark chocolates sourced from Central and South America exhibited the highest mean levels of Cd, and South America samples also contained elevated Pb, whereas those from West Africa and Asia had low Cd and Pb, respectively. Cacao contents showed increasingly strong association with Cd, Co, Mn, Sr, Ni, Cu, Zn, and Mg (r = 0.60-0.84), and moderately with Se, Fe, As, and Tl (r = 0.35-0.49), indicating these elements are primarily derived from cacao beans. Weak association of cacao contents with Pb, Th, and U levels (r < 0.25), indicates post-harvest contaminations. Hazard Quotient (HQ) > 1 was found only for Cd in 4 dark chocolates, and Hazard Index (HI) > 1 for cumulative risk of Cd, Pb, Ni, As, and U was found in 33 dark chocolates, indicating potential non-carcinogenic risks for 15 kg children but none for 70 kg adults. Dark chocolate also substantially contributed to 47-95 % of the DRI of Cu for children and 50 % for adults. Dark chocolates also provided notable Fe, Mn, Mg, and Zn contributions to the DRI. These essential elements are recognized to reduce the bioavailability of toxic metals such as Cd, Pb, or Ni, thereby potentially lowering associated health risks. This study informs consumers, food industries, and regulatory agencies to target cacao origins or chocolate brands with lower toxic metal contents for food safety and minimizing adverse health effects.

Infant exposure to ochratoxin A, zearalenone, and deoxynivalenol from the consumption of milk formula and baby cereal in Chile.

Ochratoxin A (OTA), zearalenone (ZEN), and deoxynivalenol (DON) are mycotoxins whose exposure is associated with various adverse health effects, including cancer and renal disorders, estrogenic effects, and immunosuppressive and gastrointestinal disorders, respectively. Infants (<2 years) are the most vulnerable group to mycotoxins, representing a unique combination of restricted food consumption types, low body weight, lower ability to eliminate toxins, and more future years to accumulate toxins. This study aimed to estimate the infant́s exposure to OTA, DON, and ZEN due to the consumption of milk formula and baby cereals in Chile. Milk formula samples (n = 41) and baby cereals (n = 30) were collected and analyzed using commercial ELISA kits for OTA, DON, and ZEA determination. Exposure was assessed by the Estimated Daily Intake (EDI) approach (mean and worst-case scenario, WCS) with the levels found in a modified Lower Bound (mLB) and Upper Bound (UB); ideal consumption (<6m, 7-12 m, and 13-24 m); adjusted by the weight of each group. The risk was estimated by comparing the EDI with a reference tolerable daily intake or by the margin of exposure (MOE) in the case of OTA. DON and OTA occurrence in infant formula were 34 % and 41 %, respectively. The co-occurrence between these mycotoxins was 22 %. Mycotoxin contents were below LOQ values except for OTA determined in one sample (0.29 ng/ml). No milk formulae were contaminated with ZEN. In the case of baby cereals, the occurrences were 17 % for OTA, 30 % for DON, and 7 % for ZEN, all below LOQ. Co-occurrence was seen in two samples between ZEN and OTA. According to exposure calculations, the MOE for OTA was less than 10,000 in all models for milk formula between 0 to 12 months of age and in the UB and WCS for cereal consumption. Health concerns were observed for DON in the WCS and UB for milk consumption in all ages and only in the UB WCS for cereal consumption. Considering the high consumption of milk formula in these age groups, regulation of OTA and other co-occurring mycotoxins in infant milk and food is strongly suggested.

Discrimination of three commercial tuna species through species-specific peptides: From high-resolution mass spectrometry discovery to MRM validation.

The risk of tuna adulteration is high driven by economic benefits. The authenticity of tuna is required to protect both consumers and tuna stocks. Given this, the study is designed to identify species-specific peptides for distinguishing three commercial tropical tuna species. The peptides derived from trypsin digestion were separated and detected using ultrahigh-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UPLC-Q-TOF/MS) in data-dependent acquisition (DDA) mode. Venn analysis showed that there were differences in peptide composition among the three tested tuna species. The biological specificity screening through the National Center for Biotechnology Information's Basic Local Alignment Search Tool (NCBI BLAST) revealed that 93 peptides could serve as potential species-specific peptides. Finally, the detection specificity of species-specific peptides of raw meats and processed products was carried out by multiple reaction monitoring (MRM) mode based on a Q-Trap mass spectrometer. The results showed that three, one and two peptides of Katsuwonus pelamis, Thunnus obesus and Thunnus albacores, respectively could serve as species-specific peptides.

Upconversion nanoparticles-modified aptasensors for highly sensitive mycotoxin detection for food quality and safety.

Mycotoxins, highly toxic and carcinogenic secondary metabolites produced by certain fungi, pose significant health risks as they contaminate food and feed products globally. Current mycotoxin detection methods have limitations in real-time detection capabilities. Aptasensors, incorporating aptamers as specific recognition elements, are crucial for mycotoxin detection due to their remarkable sensitivity and selectivity in identifying target mycotoxins. The sensitivity of aptasensors can be improved by using upconversion nanoparticles (UCNPs). UCNPs consist of lanthanide ions in ceramic host, and their ladder-like energy levels at f-orbitals have unique photophysical properties, including converting low-energy photons to high-energy emissions by a series of complex processes and offering sharp, low-noise, and sensitive near-infrared to visible detection strategy to enhance the efficacy of aptasensors for novel mycotoxin detection. This article aims to review recent reports on the scope of the potential of UCNPs in mycotoxin detection, focusing on their integration with aptasensors to give readers clear insight. We briefly describe the upconversion photoluminescence (UCPL) mechanism and relevant energy transfer processes influencing UCNP design and optimization. Furthermore, recent studies and advancements in UCNP-based aptasensors will be reviewed. We then discuss the potential impact of UCNP-modified aptasensors on food safety and present an outlook on future directions and challenges in this field. This review article comprehensively explains the current state-of-the-art UCNP-based aptasensors for mycotoxin detection. It provides insights into potential applications by addressing technical and practical challenges for practical implementation.

Systematic evidence mapping of potential correlates of exposure for per- and poly-fluoroalkyl substances (PFAS) based on measured occurrence in biomatrices and surveys of dietary consumption and product use.

Per- and poly-fluoroalkyl substances (PFAS) are widely observed in environmental media and often are found in indoor environments as well as personal-care and consumer products. Humans may be exposed through water, food, indoor dust, air, and the use of PFAS-containing products. Information about relationships between PFAS exposure sources and pathways and the amounts found in human biomatrices can inform source-contribution assessments and provide targets for exposure reduction. This work collected and collated evidence for correlates of PFAS human exposure as measured through sampling of biomatrices and surveys of dietary consumption and use of consumer products and articles. A systematic evidence mapping approach was applied to perform a literature search, conduct title-abstract and full-text screening, and to extract primary data into a comprehensive database for 16 PFAS. Parameters of interest included: sampling dates and locations, cohort descriptors, PFAS measured in a human biomatrix, information about food consumption in 11 categories, use of products/articles in 11 categories, and reported correlation values (and their statistical strength). The literature search and screening process yielded 103 studies with information for correlates of PFAS exposures. Detailed data were extracted and compiled on measures of PFAS correlations between biomatrix concentrations and dietary consumption and other product/article use. A majority of studies (61/103; 59%) were published after 2015 with few (8/103; 8%) prior to 2010. Studies were most abundant for dietary correlates (n = 94) with fewer publications reporting correlate assessments for product use (n = 56), while some examined both. PFOA and PFOS were assessed in almost all studies, followed by PFHxS, PFNA, and PFDA which were included in >50% of the studies. No relevant studies included PFNS or PFPeS. Among the 94 studies of dietary correlates, significant correlations were reported in 83% of the studies for one or more PFAS. The significant dietary correlations most commonly were for seafood, meats/eggs, and cereals/grains/pulses. Among the 56 studies of product/article correlates, significant correlations were reported in 70% of the studies. The significant product/article correlations most commonly were for smoking/tobacco, cosmetics/toiletries, non-stick cookware, and carpet/flooring/furniture and housing. Six of 11 product/article categories included five or fewer studies, including food containers and stain- and water-resistant products. Significant dietary and product/article correlations most commonly were positive. Some studies found a mix of positive and negative correlations depending on the PFAS, specific correlate, and specific response level, particularly for fats/oils, dairy consumption, food containers, and cosmetics/toiletries. Most of the significant findings for cereals/grains/pulses were negative correlations. Substantial evidence was found for correlations between dietary intake and biomatrix levels for several PFAS in multiple food groups. Studies examining product/article use relationships were relatively sparse, except for smoking/tobacco, and would benefit from additional research. The resulting database can inform further assessments of dietary and product use exposure relationships and can inform new research to better understand PFAS source-to-exposure relationships. The search strategy should be extended and implemented to support living evidence review in this rapidly advancing area.

Insights from modelling sixteen years of climatic and fumonisin patterns in maize in South Africa.

Mycotoxin contamination of agricultural commodities is a global public health problem that has remained elusive to various mitigation approaches, particularly in developing countries. Climate change and its impact exacerbates South Africa's vulnerability to mycotoxin contamination, and significantly threatens its's food systems, public health, and agro-economic development. Herein we analyse sixteen years (2005/2006-2020/2021) of annual national meteorological data on South Africa which reveals both systematic and erratic variability in critical climatic factors known to influence mycotoxin contamination in crops. Within the same study period, data on fumonisin (FB) monitoring show clear climate-dependent trends. The strongest positive warming trend is observed between 2018/2019 and 2019/2020 (0.51 °C/year), and a strong positive correlation is likewise established between FB contamination and temperature (r ranging from 0.6 to 0.9). Four machine learning models, viz support vector machines, eXtreme gradient boosting, random forest, and orthogonal partial least squares, are generalized on the historical data with suitable performance (RMSE as low as 0.00). All the adopted models are able to predict future FB contamination patterns with reasonable precision (R2 ranging from 0.34 to 1.00). The most important model feature for predicting average FB contamination (YA) is the historical pattern of average FB contamination in maize within the region (ΣFBs_avg). The two most significant features in modelling maximum FB contamination (YM) are minimum temperature from the CMIP6 data (Pro_tempMIN) and observed precipitation from the CRU data (O_prep). Our study provides strong evidence of the impact of climate change on FB in South Africa and reiterates the significance of machine learning modelling in predicting mycotoxin contamination in light of changing climatic conditions, which could facilitate early warnings and the adoption of relevant mitigation measures that could help in mycotoxin risk management and control.

Optical sensing for real-time detection of food-borne pathogens in fresh produce using machine learning.

Contaminated fresh produce remains a prominent catalyst for food-borne illnesses, prompting the need for swift and precise pathogen detection to mitigate health risks. This paper introduces an innovative strategy for identifying food-borne pathogens in fresh produce samples from local markets and grocery stores, utilizing optical sensing and machine learning. The core of our approach is a photonics-based sensor system, which instantaneously generates optical signals to detect pathogen presence. Machine learning algorithms process the copious sensor data to predict contamination probabilities in real time. Our study reveals compelling results, affirming the efficacy of our method in identifying prevalent food-borne pathogens, including Escherichia coli (E. coli) and Salmonella enteric, across diverse fresh produce samples. The outcomes underline our approach's precision, achieving detection accuracies of up to 95%, surpassing traditional, time-consuming, and less accurate methods. Our method's key advantages encompass real-time capabilities, heightened accuracy, and cost-effectiveness, facilitating its adoption by both food industry stakeholders and regulatory bodies for quality assurance and safety oversight. Implementation holds the potential to elevate food safety and reduce wastage. Our research signifies a substantial stride toward the development of a dependable, real-time food safety monitoring system for fresh produce. Future research endeavors will be dedicated to optimizing system performance, crafting portable field sensors, and broadening pathogen detection capabilities. This novel approach promises substantial enhancements in food safety and public health.

Dietary intake of methylmercury by 0-5 years children using the duplicate diet method in Japan.

BACKGROUND: The developing brains are sensitive to methylmercury (MeHg). However, the exposure to MeHg in baby foods and toddler meals remains unknown. This study aimed to determine MeHg intake from baby food or toddler meals, and to investigate the relationship with child hair total mercury (THg). METHODS: A total of 3 days of 24-hour dietary diet and hair samples were collected from 260 consenting children aged 0-5 years. We measured the concentrations of THg and MeHg in the diet and THg in the hair. RESULTS: The results of measuring THg were below both the method detection and method quantification limits or either of both in powdered milk (93.8%), 5-6 months (53.3%), and 7-8 months (39.5%). The median daily THg intake was 20.3 (95% confidence interval 0.72-232.5) ng/kgbw. MeHg was not detected in 213 samples with dietary THg concentrations below 1 ng/g. The MeHg concentration with THg concentrations of 1 ng/g or higher was 1.70 (0.87-6.21) ng/g, and MeHg percentage in THg was 90.0%. To estimate MeHg intake, we multiplied the THg concentration by 90.0%, resulting in an estimated MeHg intake of 18.3 (0.65-209.2) ng/kgbw/day. The THg in children's hair was 1.05 (0.31-3.96) ppm, and a weak positive correlation was observed between hair THg and dietary MeHg (r = 0.170). CONCLUSIONS: This study highlights the accurate estimation of MeHg intake in children using a duplicate method. Japanese children consume fish, the MeHg intakes exceeded the reference dose and/or provisional tolerable weekly intake in several children. Further discussion based on epidemiological data is required.

Risk assessment of trace elements in vegetables grown in river Yamuna floodplain in Delhi.

Urban agriculture is common in fertile river floodplains of many developing countries. However, there is a risk of contamination in highly polluted regions. This study quantifies health risks associated with the consumption of vegetables grown in the floodplain of the urban river 'Yamuna' in the highly polluted yet data-scarce megacity Delhi, India. Six trace elements are analyzed in five kinds of vegetable samples. Soil samples from the cultivation area are also analyzed for elemental contamination. Ni, Mn, and Co are observed to be higher in leafy vegetables than others. Fruit and inflorescence vegetables are found to have higher concentrations of Cr, Pb, and Zn as compared to root vegetables. Transfer Factor indicates that Cr and Co have the highest and least mobility, respectively. Vegetable Pollution Index indicates that contamination levels follow as Cr > Ni > Pb > Zn. Higher Metal Pollution Index of leafy and inflorescence vegetables than root and fruit vegetables indicate that atmospheric deposition is the predominant source. Principal Component Analysis indicates that Pb and Cr have similar sources and patterns in accumulation. Among the analyzed vegetables, radish may pose a non-carcinogenic risk to the age group of 1-5 year. Carcinogenic risk is found to be potentially high due to Ni and Cr accumulation. Consumption of leafy vegetables was found to have relatively less risk than other vegetables due to lower Cr accumulation. Remediation of Cr and Ni in floodplain soil and regular monitoring of elemental contamination is a priority.