Food Quality Indicators Research Articles

Trace level detection of putrescine and cadaverine in food samples using a novel rhodanine-imidazole dyad and evaluation of its biological properties

Biogenic amines are important indicators of food spoilage and quality. Food safety is significantly influenced by biogenic amines such as Putrescine and Cadaverine, produced by microbes during food spoilage. Herein, a colorimetric probe for detecting Putrescine and Cadaverine based on a chemo-dosimeter strategy has been proposed. The probe L1 irreversibly binds with Putrescine and Cadaverine through an aza-Michael addition reaction in which the dicyanomethyl group of the probe is substituted by the primary amine group from the biogenic amines. This chemical reaction rapidly changes color from colorless to pale green. The probe could detect Putrescine and Cadaverine in trace levels of 52 nM and 18 nM, without much interference from other common biogenic amines. The binding mechanism of probe L1 with biogenic amines was confirmed using 1H NMR, IR, and DFT studies. The detection procedure is made portable and affordable by using a smartphone camera to capture colorimetric changes and convert them into RGB coordinates. Test paper strips coated with the probe were developed to illustrate its real-world analytical application. The potential application of probe L1 in real samples was demonstrated using in-vivo models of Prawn and Beef using test paper strips. Probe L1 showed satisfactory performance for detecting Putrescine and Cadaverine in the vapor phase.

C:N stoichiometry and the fate of organic carbon in ecosystems of the northwest Pacific Ocean

Phytoplankton elemental composition regulates the efficiency of energy and material transfer in the interface between phytoplankton and their consumers. The ratio of particulate organic carbon to particulate organic nitrogen (POC:PON) shows considerable regional deviations from the canonical Redfield ratio in the global surface ocean. However, in certain oceanic regions such as the northwest Pacific Ocean (NWPO) POC:PON distribution and its ecological significance remain uncertain. We investigated surface ocean POC:PON distributions at 66 stations in the NWPO, and quantified the correlations between POC:PON and multiple biotic and abiotic factors including sea surface temperature (SST), nutrient concentrations and multiple lipid biomarkers (fatty acids and sterols), by combining correlation analyses and generalized additive models. POC:PON (range: 3.53–14.18 M ratios; median: 6.89) was overall higher in the (sub)tropical biome than that in the high-latitude biome. In the entire study region, SST, nutrient concentration and lipid-derived phytoplankton community structure explained 41 %, 33 % and 26 % of the variance in POC:PON, respectively, while the respective importance of each factor differed between the (sub)tropical and high-latitude biomes. Furthermore, we calculated the percentage of primary production consumed by herbivores (PPC; 54–156 %), showing a higher mean value (117 %) in the high-latitude biome and a lower one (92 %) in the (sub)tropical biome. The spatial distribution pattern of PPC can be attributed to multiple factors, with PPC correlating negatively with SST and positively with lipid-based indicators of phytoplankton food quality and POC concentrations. The increase in SST may be associated with a reduced nitrogen content, resulting in lower PPC in the (sub)tropical biome. This study highlights the significance of SST and elemental and biochemical composition of phytoplankton in regulating the transfer of organic carbon to herbivores in the NWPO.

Spatiotemporal distribution of sedimentary chloropigments and organic carbon in a shelf sea ecosystem, with a focus on the cold water mass

The Yellow Sea is one of the most thoroughly studied shelf seas in the northwestern Pacific. However, many aspects of the northern Yellow Sea sediments remain poorly understood. Sedimentary chloropigments and total organic carbon (TOC) are crucial components that indicate benthic primary productivity and ecosystem functioning in the marginal sea system. The present study investigated the temporal and spatial variations of sediment chloroplastic pigments (Chl-a and Pha-a) and TOC contents in relation to seasons and the northern Yellow Sea Cold Water Mass (NYSCWM). Decadal trends were also examined using linear regression on time-series data from 12 cruises conducted over a nine-year period (2006–2014). The correlations between sedimentary Chorophy-a (Chl-a), Pheophorbide-a (Pha-a), TOC, and their ratios with other abiotic and biotic factors were analyzed to detect any effects of the NYSCWM on the spatiotemporal distribution of sediment Chl-a, Pha-a, TOC contents, as well as the ecological relevance of their ratios as indicators of food quality (freshness) in the benthic system. The NYSCWM substantially influences the spatial and seasonal distribution of sedimentary Chl-a, Pha-a, and TOC contents. High values of Pha-a, TOC, and the ratios of Pha-a/(Chl-a + Pha-a) and TOC/Chl-a were often observed in the central region of the NYSCWM, where Chl-a showed clear seasonal fluctuations while Pha-a and TOC remained relatively constant. While sedimentary TOC appears to negatively mirror the spatial pattern of primary productivity in the water column, the spatial pattern of sedimentary Chl-a in relation to NYSCWM is less evident. However, the contents of Pha-a and TOC in the central NYSCWM sediments were higher than those at surrounding NYSCWM stations. Surface sediment Pha-a/(Chl-a + Pha-a) ratio was negatively correlated with meiofauna abundance and biomass and positively correlated with nematode/copepod ratio. This finding indicates that the quality of sediment organic matter is important to meiofauna. Conversely, the lower organic degradation rate at the lower bottom temperature of the NYSCWM may explain the observed higher Pha-a and TOC contents in its central area. Time-series data collected over nine years at the NYSCWM stations showed a decreasing trend for Chl-a, while TOC and the ratio of Pha-a/(Chl-a + Pha-a) exhibited increasing tendencies. This trend may imply a reduced quality of food supply to the benthic food web in the shelf sea system, along with degraded ecosystem functioning and service under the impacts of global change and anthropogenic disturbances.

“Reference sample comparison method”: A new voltammetric electronic tongue method and its application in assessing the shelf life of fresh milk

Shelf life is a critical comprehensive indicator of food quality. Voltammetric electronic tongue (V-Et), is well-suited for assessing food shelf life, due to its capable of capturing food overall fingerprints. This study designed a “reference sample comparison method” for V-Et to assess the shelf life of fresh milk. Quality differences between milk samples of different shelf lives and reference samples were quantified by differential degree (Dd) values. A new “one-to-one” model of milk shelf life was established based on Dd values, and significantly improved predictive accuracy by 11.14 %–17.17 % and 14.86 %–44.47 % in overall quality shelf life assessment compared to “many-to-one” models based on SVM and DFA. Even in the more sophisticated evaluation of microbial safety and sensory quality shelf life, it attained relative errors of 13.57 % and 7.68 %, respectively. All these findings showed the significant potential of the “reference sample comparison method” in assessing food shelf life with V-Et.

Associations between Global Diet Quality Score and Risk of Metabolic Syndrome and Its Components: Tehran Lipid and Glucose Study.

Various food quality indicators have been proposed as tools for predicting metabolic syndrome (MetS). This study investigated the association between global diet quality score (GDQS) and the risks of developing MetS and its components. In this secondary analysis, we included elective adult participants (n=4,548) from the Tehran Lipid and Glucose Study. Dietary data were collected by a valid and reliable semi-quantitative food frequency questionnaire. MetS was defined according to the Iranian modified National Cholesterol Education Program. Multivariable Cox proportional hazard regression models were used to estimate the incidence of MetS in association with GDQS. This study involved 1,762 men and 2,786 women with a mean±standard deviation age of 38.6±14.3 and 35.9±11.8 years, respectively. A total of 1,279 subjects developed MetS during the mean follow-up of 6.23 years. Incidence of MetS was associated with GDQS (hazard ratio [HR], 1; 0.90 [95% confidence interval, CI, 0.82 to 0.98]; 0.84 [95% CI, 0.76 to 0.91]; 0.80 [95% CI, 0.73 to 0.89]; P for trend <0.001) after adjusting for confounding variables. The healthy food group component of GDQS was related to MetS incidence. GDQS in the range of 12%-17% in the fourth quartile was associated with a decrease in incidence of MetS components. Both healthy and unhealthy food group components of the GDQS decreased the incidence of high triglycerides, high blood pressure, and high fasting blood glucose. Higher GDQS was associated with a lower risk of the incidence of MetS or its components among Tehranian adults. Higher intake of healthy food group components and lower consumption of unhealthy food group components of the GDQS predicted lower MetS incidence and risk factors.

Integrated RF-CNN-GRU ensemble for enhanced beef quality classification: A multi-modal approach

Ensuring food safety is crucial for health and economic sustainability. A key indicator of food quality is its smell, which can be assessed using an electronic nose (e-nose). Combining e-nose technology with machine learning methods has shown promise in enhancing classification accuracy. However, traditional methods such as Support Vector Machines (SVM), k-Nearest Neighbors (KNN), and Convolutional Neural Networks (CNN) often fall short in accurately distinguishing between fresh and spoiled beef.To address these limitations, this study proposes a novel hybrid model that integrates Random Forest, CNN for local feature extraction, and Gated Recurrent Unit (GRU) for global feature extraction. Utilizing data from 11 e-nose sensors, this model achieves an unprecedented accuracy of up to 0.9977 in differentiating fresh from spoiled beef across all 12 types of cuts. The hybrid model demonstrates superior performance metrics, including accuracy, precision, recall, F1 score, coefficient of determination (R2), root mean square error (RMSE), and residual predictive deviation (RPD), significantly outperforming traditional approaches in beef quality classification. By incorporating both local and global features, our approach offers innovative insights and marks a significant advancement in machine learning applications for food quality assessment.

The Application of Multi-Parameter Multi-Modal Technology Integrating Biological Sensors and Artificial Intelligence in the Rapid Detection of Food Contaminants.

Against the backdrop of continuous socio-economic development, there is a growing concern among people about food quality and safety. Individuals are increasingly realizing the critical importance of healthy eating for bodily health; hence the continuous rise in demand for detecting food pollution. Simultaneously, the rapid expansion of global food trade has made people's pursuit of high-quality food more urgent. However, traditional methods of food analysis have certain limitations, mainly manifested in the high degree of reliance on personal subjective judgment for assessing food quality. In this context, the emergence of artificial intelligence and biosensors has provided new possibilities for the evaluation of food quality. This paper proposes a comprehensive approach that involves aggregating data relevant to food quality indices and developing corresponding evaluation models to highlight the effectiveness and comprehensiveness of artificial intelligence and biosensors in food quality evaluation. The potential prospects and challenges of this method in the field of food safety are comprehensively discussed, aiming to provide valuable references for future research and practice.

Non-invasive measurement of spoilage of packed fish using halochromic sensor

Purpose This study aims to develop a pH-functional thin-film sensor for non-invasive measurement of spoilage of packed fish. Design/methodology/approach At first, polymers of natural origin such as hydroxy(propyl)methyl cellulose, potato dextrose agar and starch alongside a pH sensitive-mixed indicator formulation were used to produce thin film sensor. The developed thin film sensor was tested for monitoring the spoilage of seafood stored at 4°C. Using ultraviolet-visible and Fourier-transform infrared spectroscopy, the halochromic sensor was characterised. In addition, the halochromic response of the thin film was directly correlated to the total volatile base nitrogen emitted by the packaged fish, pH, microbial activity and sensory evaluation. Findings The results suggested the developed biopolymer-based thin film sensor showed different colours in line with the spoilage of the packed fish, which could be well correlated with the total volatile base nitrogen, microbial activity and sensory evaluation. In addition, the thin film sensors exhibited a high degree of biodegradability. The biopolymers-based thin film halochromic sensor has exhibited excellent biodegradability along with sensitiveness towards the spoilage of the packed fish. Originality/value In the future, consumers and retailers may prefer seafood containers equipped with such halochromic sensors to determine the degree of food deterioration as a direct indicator of food quality.

A feature extractor for temporal data of electronic nose based on parallel long short-term memory network in flavor discrimination of Chinese vinegars

Volatile flavor is a key indicator of food quality which can directly affect consumer preference and purchase intention. Electronic nose is considered as a promising intelligent sensory analysis tool for food flavor assessment, however, extracting effective features from the gas sensor array is still a major challenge, which largely determines the performance of subsequent classifiers. Here, a parallel long short-term memory (LSTM) network is proposed as a feature extractor for automatically extracting features from the whole time series of sensor responses in flavor discrimination of five Chinese vinegars. The network was trained by the temporal data from the sensor array and yielded different feature patterns corresponding to different vinegars, which were then fed to other conventional classifiers for pattern recognition. We also evaluated the influence of the extracted feature dimension that is related to the dimension of the hidden state of the LSTM layer on the classification performance. The results indicate that a larger dimension of extracted feature is unnecessary for promoting classification accuracy, instead, the optimum dimension 4 of the hidden state gives the highest accuracy of 95.8% in this application under the softmax evaluator. Moreover, much higher accuracies were obtained when combined with other sophisticated classifiers such as support vector machine. The results demonstrate that the proposed network is competent to extract features directly and automatically from the temporal data of the electronic nose.

Microbial contamination pathways in a poultry abattoir provided clues on the distribution and persistence of Arcobacter spp.

The consumption of contaminated poultry meat is a significant threat for public health, as it implicates in foodborne pathogen infections, such as those caused by Arcobacter. The mitigation of clinical cases requires the understanding of contamination pathways in each food process and the characterization of resident microbiota in the productive environments, so that targeted sanitizing procedures can be effectively implemented. Nowadays these investigations can benefit from the complementary and thoughtful use of culture- and omics-based analyses, although their application in situ is still limited. Therefore, the 16S-rRNA gene-based sequencing of total DNA and the targeted isolation of Arcobacter spp. through enrichment were performed to reconstruct the environmental contamination pathways within a poultry abattoir, as well as the dynamics and distribution of this emerging pathogen. To that scope, broiler's neck skin and caeca have been sampled during processing, while environmental swabs were collected from surfaces after cleaning and sanitizing. Metataxonomic survey highlighted a negligible impact of fecal contamination and a major role of broiler's skin in determining the composition of the resident abattoir microbiota. The introduction of Arcobacter spp. in the environment was mainly conveyed by this source rather than the intestinal content. Arcobacter butzleri represented one of the most abundant species and was extensively detected in the abattoir by both metataxonomic and enrichment methods, showing higher prevalence than other more thermophilic Campylobacterota. In particular, Arcobacter spp. was recovered viable in the plucking sector with high frequency, despite the adequacy of the sanitizing procedure.IMPORTANCEOur findings have emphasized the persistence of Arcobacter spp. in a modern poultry abattoir and its establishment as part of the resident microbiota in specific environmental niches. Although the responses provided here are not conclusive for the identification of the primary source of contamination, this biogeographic assessment underscores the importance of monitoring Arcobacter spp. from the early stages of the production chain with the integrative support of metataxonomic analysis. Through such combined detection approaches, the presence of this pathogen could be soon regarded as hallmark indicator of food safety and quality in poultry slaughtering.

ОЦЕНКА РАСПРЕДЕЛЕНИЯ ОСТАТОЧНЫХ КОЛИЧЕСТВ ЛЕКАРСТВЕННОГО ПРЕПАРАТА ПЕНИЦИЛЛИНА-G В МОЛОКЕ И МОЛОЧНЫХ ПРОДУКТАХ

The purpose of the study is to assess the impact of contamination of dairy raw materials with residual amounts of the drug penicillin-G on food quality indicators, as well as to monitor it using the Extenso multifunctional device and the arbitration method of high-performance liquid chromatography. The study took place at the All-Russian Research Institute of the Dairy Industry (Moscow). The objects of the study were scientific papers by Russian and foreign scientists published from 2017 to 2022, devoted to the study of the distribution of antibiotics in milk and its processed products, as well as control systems for veterinary drugs and medicinal substances in them. The search was carried out in the databases Pub Med, Scopus, Science Direct and Webof Science, as well as in the electronic scientific library eLibrary.ru using keywords: residues of veterinary drugs, distribution of antibiotics, milk, dairy raw materials, determination methods. Analysis of sources showed that the distribution of antibiotics among milk fractions depends on their lipophilic or hydrophilic properties. If the processing regimes (normalization, pasteurization and homogenization) of the starting raw materials are observed, antibiotics are stored in dairy products, binding to the structural components of milk (proteins and fats). Contamination of dairy raw materials with penicillin has a negative impact on the biological safety of products and leads to serious problems for both human health and the production process. However, this problem has received insufficient attention. It is necessary to expand control systems for veterinary drugs and medicinal substances in raw milk to ensure the toxicological safety of products and technological stages of production. One of the modern methods for studying beta-lactam antibiotics is the multifunctional Extenso system, which allows you to monitor veterinary residual drugs in a fast and cost-effective way.

The effect of nutrition education on knowledge, nutrients intake, and physical activity of children with overweight and obesity at elementary school in Jakarta Indonesia

Background: Obesity is one of the triple burden malnutrition in Indonesia, alongside undernutrition that increasing over the years. The study was done to evaluate the effect of four weeks nutrition education intervention among children with overweight and obesity. Methods: This study was a cluster randomized control trial in two elementary school in Jakarta. SD Kramat Pela 07 were selected as a control and SD Kramat Pela 09 as an intervention group. Intervention on school children were conducted for four weeks. Samples were students who were selected with the criteria of having overweight and obesity. An education through video was delivered from the teachers consecutively to the students every week. Nutrition knowledge was collected with a Google-form questionnaire that consist of 15 questions. Nutrient intake was collected with 24-hour recalls before and after the intervention. Results: A significant increase of nutrition knowledge on both group after the intervention (p&lt;0.05). There was a significant change of fiber intake (p&lt;0.05) after four weeks of intervention. The average duration of physical activity for respondents showed an increase in the intervention group, but it was not statistically significant (p&gt;0.05). Conclusions: After four weeks intervention, nutrition education improved the knowledge, nutrients intake, and physical activity among school children with overweight and obesity. We recommend the school authorities to enhance the capacity and capabilities of teachers in fostering efforts to improve the health and nutrition of students through school-based learning. Additionally, the consumption of fiber is considered an indicator of healthy food quality in controlling overweight and obesity.

Reliability of the New Index of Global Food Quality and its relationship with sociodemographic variables and physical activity levels in the Chilean population.

surveys play a crucial role in evaluating the quality of food in populations, especially in healthcare settings, helping identify important characteristics of food descriptions and improving efficiency in the collection and management of data in dietary surveys. the primary aim of this study was to analyze the internal consistency of the New Index of Global Food Quality (NIGFQ) instrument and assess its applicability to sociodemographic variables and levels of physical activity (IPAQ-S) in a specific region of Chile. a descriptive, comparative, and correlational study that utilizes the online platform of Google Forms for data collection using the New Index of Global Food Quality (NIGFQ) and IPAQ-S instruments, in addition to considering sociodemographic variables, in a sample of 1,331 participants from the metropolitan region of Chile. the study shows an improvement in the reliability of the GQIN (Cronbach's alpha: 0.63 to 0.71). Findings reveal significant inverse correlations between fruits (r = -0.31; p ≤ 0.05) and legumes (r = -0.34; p ≤ 0.05) with body mass. it is concluded that values above 52.5 points are considered healthy on the new evaluation scale of the index, supported by statistical reliability tests. Similarly, the components of the adjusted New Index of Global Food Quality, particularly fruits and vegetables in greater proportion, show a beneficial relationship with daily consumption in reducing body mass index and body weight.

Irreversible colorimetric bio-based curcumin bilayer membranes for smart food packaging temperature control applications.

Research into innovative food safety technologies has led to the development of smart packaging with embedded chemical sensors that can monitor food quality throughout the supply chain. Thermochromic materials (TM), which are able to dynamically change colour in response to temperature fluctuations, have proven to be reliable indicators of food quality in certain environments. Natural colourants such as curcumin are becoming increasingly popular for smart packaging due to their low toxicity, environmental friendliness and ability to change colour. The innovation in this research lies in the production of a bio-based bilayer membrane specifically designed for irreversible temperature monitoring. Membrane A was prepared by dissolving cellulose acetate and curcumin in acetone at room temperature, with glycerol serving as a plasticiser. At the same time, membrane B was carefully formulated by dissolving cellulose acetate and triethanolamine in acetone, with sorbitol as plasticiser. The preparation of these different membranes revealed a remarkable event: a gradual and irreversible colour transition from an initial yellow to a brick-red hue after 24 hours of storage at 25 °C. The chemical structure and morphological analyses of the membranes were performed using several techniques, including FTIR, DSC and SEM. The membrane labels were adhered to aluminium cans and their colorimetric response was observed over a period of 10 days. Minimal colour variations were observed, confirming the reproducibility and stability of the curcumin-based membranes as temperature sensors.

Ammonium nanochelators in conjunction with arginine-specific enzymes in amperometric biosensors for arginine assay

Amino acid L-arginine (Arg), usually presented in food products and biological liquids, can serve both as a useful indicator of food quality and an important biomarker in medicine. The biosensors based on Arg-selective enzymes are the most promising devices for Arg assay. In this research, three types of amperometric biosensors have been fabricated. They exploit arginine oxidase (ArgO), recombinant arginase I (ARG)/urease, and arginine deiminase (ADI) coupled with the ammonium-chelating redox-active nanoparticles. Cadmium-copper nanoparticles (nCdCu) as the most effective nanochelators were used for the development of ammonium chemosensors and enzyme-coupled Arg biosensors. The fabricated enzyme/nCdCu-containing bioelectrodes show wide linear ranges (up to 200 µM), satisfactory storage stabilities (14 days), and high sensitivities (A⋅M−1⋅m−2) to Arg: 1650, 1700, and 4500 for ADI-, ArgO- and ARG/urease-based sensors, respectively. All biosensors have been exploited to estimate Arg content in commercial juices. The obtained data correlate well with the values obtained by the reference method. A hypothetic scheme for mechanism of action of ammonium nanochelators in electron transfer reaction on the arginine-sensing electrodes has been proposed.Graphical abstract

Recent Studies and Applications of Hydrogel-Based Biosensors in Food Safety.

Food safety has increasingly become a human health issue that concerns all countries in the world. Some substances in food that can pose a significant threat to human health include, but are not limited to, pesticides, biotoxins, antibiotics, pathogenic bacteria, food quality indicators, heavy metals, and illegal additives. The traditional methods of food contaminant detection have practical limitations or analytical defects, restricting their on-site application. Hydrogels with the merits of a large surface area, highly porous structure, good shape-adaptability, excellent biocompatibility, and mechanical stability have been widely studied in the field of food safety sensing. The classification, response mechanism, and recent application of hydrogel-based biosensors in food safety are reviewed in this paper. Furthermore, the challenges and future trends of hydrogel biosensors are also discussed.

The association between Diet Quality Index-International score and risk of diminished ovarian reserve: a case-control study.

Although limited evidence exists on the beneficial reproductive effects of diet quality indices, the association is still largely unknown. We aimed to investigate the association between Diet Quality Index-International (DQI-I) and antral follicle count (AFC) and serum antimullerian hormone (AMH) as precise and sensitive markers of ovarian reserve and to assess the risk of diminished ovarian reserve (DOR) in women seeking fertility treatments. In a case-control study, 370 women (120 women with DOR and 250 women with normal ovarian reserve as controls), matched by age and body mass index (BMI), were recruited. Dietary intake was obtained using a validated 80-item semi-quantitative food frequency questionnaire (FFQ). The quality of diets was assessed using DQI-I, which included four major dietary components: variety (0-20 points), adequacy (0-40 points), moderation (0-30 points), and overall balance (0-10 points). DQI-I score was categorized by quartiles based on the distribution of controls. AFC, serum AMH and anthropometric indices were measured. Logistic regression models were used to estimate multivariable odds ratio (OR) of DOR across quartiles of DQI-I score. Increased adherence to DQI-I was associated with higher AFC in women with DOR. After adjusting for potential confounders, the odds of DOR decreased with increasing DQI-I score (0.39; 95% CI: 0.18-0.86). Greater adherence to DQI-I, as a food and nutrient-based quality index, may decrease the risk of DOR and improve the ovarian reserve in women already diagnosed with DOR. Our findings, though, need to be verified through prospective studies and clinical trials.

A ratiometric carbon dots/AgInS2 quantum dots sensing probe for the kinetic determination of histamine resorting to N-PLS chemometric model

Biogenic amines are compounds that play several crucial roles in the human body but can also cause serious health problems when present at high concentrations in foodstuffs. Therefore, it is important to develop rapid, simple, cost-effective, and reliable analytical techniques for their monitoring, acting as indicators of food quality and preventing potential risks. In this sense, carbon dots and 3-mercaptopropionic acid (MPA)-capped AgInS2 (AIS) quantum dots were used as fluorescent probes to implement a ratiometric sensing platform, coupled to chemometrics, for the kinetic fluorometric determination of histamine in foodstuffs using second-order data. The obtained data were analysed through unfolded partial least squares (U-PLS) and N-way partial least squares (N-PLS). The model optimization revealed that the application of N-PLS yielded the best results and that a kinetic spectral acquisition for 5 minutes was enough to ensure reliable measurements. The developed method was evaluated using spiked samples of different complex matrices (tuna, tomato and hake fish), at different concentration levels, and the obtained results, in terms of figures of merit, confirmed its suitability, accuracy and effectiveness. In fact, a relative percentage error below 10%, with a coefficient of determination for the prediction higher than 0.9, was obtained, together with a LOD and LOQ of 1.26 and 3.80 mg L−1, respectively, which are much lower than the maximum threshold value established by European Union legislation for histamine in fishery products (200 mg kg−1). These results were obtained with samples containing uncalibrated species and without using toxic reagents, which attest the suitability of the procedure. Globally, the developed methodology proved to be accurate and much simpler and faster than the reference procedures.

Application of VIS-NIR Hyperspectral Imaging to the Detection and Quantification of MPs in Simulant Shellfish

As the world has become increasingly reliant on single-use plastics, plastic litter has increased exponentially, especially in marine ecosystems. One type of plastic litter affecting marine life is microplastics, which are plastics under 5mm in diameter. Microplastics are consumed by marine animals, which are then consumed by people. Study of the environmental and human health effects of these microplastics has proven difficult, in part due to difficulty detecting and quantifying microplastics. This study aims to detect microplastics in shellfish by utilizing the nondestructive method of hyperspectral imaging as an indicator of both marine ecosystem health and food quality. Gelatin models of shellfish were injected with a known concentration of microplastics (polyvinyl chloride (PVC) and polystyrene (PS), specifically). The hyperspectral camera then took 3-dimensional images of the models, with the wavelength dimension ranging from 400 nm to 1000 nm. Next, an algorithm called Partial Least Squares Regression Analysis was developed to analyze the relationship between the wavelengths and the amount of plastic in the sample. Preliminary results have shown slight variation in reflectance spectra between models spiked with microplastics and control models past the 950 nm range. Therefore, hyperspectral imaging might be a viable tool to detect and quantify microplastics in shellfish, but the range of the camera used in this study is a limitation.

Optimization of the Spray-Deposited Carbon Nanotube Semiconducting Channel for Electrolyte-Gated Field-Effect Transistor-Based Biosensing Applications

Electrochemical biosensors are widely investigated as they represent attractive analytical tools for detection of a broad range of bio-molecules, thanks to their simplicity, high sensitivity and short response time. Especially, biosensors employing an electrolyte-gated field-effect transistors (EG-FETs) as electrochemical transduction element have gained increasing interest, due to the signal amplification and the intrinsic low voltage range of operation. In this work we report the fabrication of flexible EG-FETs using spray-deposited semiconducting carbon nanotubes (CNTs), with a specific focus on the optimization of the CNT channel to optimize the performance of the resulting CNT-based EG-FET (EG-CNTFET). The transfer and the output characteristic of different devices with varying spraying parameters were tested, finding out that only devices with source-drain resistance of about ≤10 kΩ showed proper EG-CNTFET operation: for these devices we recorded a typical p-type behavior with an on–off ratio of 214 A/A up to 469 A/A (depending on number of the spray-deposited CNT layers). The fabricated EG-CNTFETs were functionalized with anti-spermidine antibodies to detect polyamine spermidine - a well-known chemical indicator of food quality. To ensure controlled immobilization and at the same time to preserve the electrical properties of the nanotubes, the spray-deposited films were modified with a bifunctional molecule, which attaches to the CNT via non-covalent π - π interactions and leaves a free NHS-ester group for amide coupling of the antibodies. The fabricated EG-CNTFET-based immunosensors showed a linear detection range for spermidine from 10-3 to 102 nM, with the sensitivities ranging from -1.03 to -2.45 μA/decade.