Evaluation of low-cost sensors to integrate in a water quality monitor for real-time measurements.

Low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks and provide valuable water quality information to the public. However, the accuracy and precision of the values measured by the sensors are critical for widespread adoption. In this study, 19 different low-cost sensors, commonly found in the literature, from four different manufacturers are tested for measuring five water quality parameters: pH, dissolved oxygen, oxidation-reduction potential, turbidity, and temperature. The low-cost sensors are evaluated for each parameter by calculating the error and precision compared to a typical multiparameter probe assumed as a reference. The comparison was performed in a controlled environment with simultaneous measurements of real water samples. The relative error ranged from - 0.33 to 33.77%, and most of them were ≤ 5%. The pH and temperature were the ones with the most accurate results. In conclusion, low-cost sensors are a complementary alternative to quickly detect changes in water quality parameters. Further studies are necessary to establish a guideline for the operation and maintenance of low-cost sensors.

Clinical indicators to monitor health care in low back pain: a scoping review.

Clinical care indicators for low back pain can be used to monitor healthcare practices and consequently be used to evaluate success of strategies to improve care quality. The aim of this study was to identify the clinical care indicators that have been used to measure appropriateness of health care for patients with low back pain. We conducted a systematic search of five electronic databases and Google to identify clinical care indicators that have been used to measure any aspect of care for people with low back pain. Care indicators were narratively described according to their type (i.e. structure, process, or outcomes) and categorized by their purpose (e.g. to measure aspects related to assessment, imaging requests, treatment/prevention, and outcomes). A total of 3562 and 2180 records were retrieved from electronic databases and Google searches, respectively. We identified 280 indicators related to low back pain care from 40 documents and publications. Most quality indicators were process indicators (n = 213, 76%), followed by structure (n = 41, 15%) and outcome indicators (n = 26, 9%). The most common indicators were related to imaging requests (n = 41, 15%), referral to healthcare providers (n = 30, 11%), and shared decision-making (n = 21, 7%). Our review identified a range of clinical care indicators that have been used to measure the quality of health care for people with low back pain. Our findings will support a Delphi study to reach international consensus on what would be the most important and feasible indicators for a minimum dataset to be collected globally.

Internet of Things and citizen science as alternative water quality monitoring approaches and the importance of effective water quality communication.

The increasing demand for water and worsening climate change place significant pressure on this vital resource, making its preservation a global priority. Water quality monitoring programs are essential for effectively managing this resource. Current programs rely on traditional monitoring approaches, leading to limitations such as low spatiotemporal resolution and high operational costs. Despite the adoption of novel monitoring approaches that enable better data resolution, the public's comprehension of water quality matters remains low, primarily due to communication process deficiencies. This study explores the advantages and challenges of using Internet of Things (IoT) and citizen science as alternative monitoring approaches, emphasizing the need for enhancing public communication of water quality data. Through a systematic review of studies implemented on-field, we identify and propose strategies to address five key challenges that IoT and citizen science monitoring approaches must overcome to mature into robust sources of water quality information. Additionally, we highlight three fundamental problems affecting the water quality communication process and outline strategies to convey this topic effectively to the public.

The impact of data quality monitoring of a multicenter prospective registry of cardiac implantable electronic devices.

Data quality monitoring plays a crucial role in multicenter prospective registries. By maintaining high data accuracy, completeness, and consistency, researchers can improve the overall quality and reliability of the registry data, enabling meaningful conclusions and supporting evidence-based decisions. The purpose of the present study was to evaluate data quality metrics (completeness, accuracy, and temporal plausibility) of a Multicenter Registry of Cardiac Implantable Electronic Devices (CIEDs) and to perform a direct data audit of a random sample of records to assess the agreement levels with the source documents. The CIED Registry was a prospective, multicenter, real-world observational study carried out from January 2020 to December 2022 in five designated centers across Sao Paulo, Brazil. We assessed the data quality of the CIED Registry by using two distinct approaches:•Dynamic data monitoring using features of the REDCap (Research Electronic Data Capture) software, including data reports and data quality rules•Direct data audit in which information from a random sample of 10 % of cases from the coordinating center was compared with original source documents Our findings suggest that the methodological approach applied to the CIED Registry resulted in high data completeness, accuracy, temporal plausibility, and excellent agreement levels with the source documents.

Effects of intensive agriculture and urbanization on water quality and pesticide risks in freshwater ecosystems of the Ecuadorian Amazon.

The Ecuadorian Amazon has experienced a significant land use change due to the demographic increase and the expansion of the agricultural frontier. Such changes in land use have been associated to water pollution problems, including the emission of untreated urban wastewater and pesticides. Here we provide the first report on the influence of urbanization and intensive agriculture expansion on water quality parameters, pesticide contamination and the ecological status of Amazonian freshwater ecosystems of Ecuador. We monitored 19 water quality parameters, 27 pesticides, and the macroinvertebrate community in 40 sampling locations of the Napo River basin (northern Ecuador), including a nature conservation reserve and sites in areas influenced by African palm oil production, corn production and urbanization. The ecological risks of pesticides were assessed using a probabilistic approach based on species sensitivity distributions. The results of our study show that urban areas and areas dominated by African palm oil production have a significant influence on water quality parameters, affecting macroinvertebrate communities and biomonitoring indices. Pesticide residues were detected in all sampling sites, with carbendazim, azoxystrobin, diazinon, propiconazole and imidacloprid showing the largest prevalence (>80% of the samples). We found a significant effect of land use on water pesticide contamination, with residues of organophosphate insecticides correlating with African palm oil production and some fungicides with urban areas. The pesticide risk assessment indicated organophosphate insecticides (ethion, chlorpyrifos, azinphos-methyl, profenofos and prothiophos) and imidacloprid as the compounds posing the largest ecotoxicological hazard, with pesticide mixtures potentially affecting up to 26-29% of aquatic species. Ecological risks of organophosphate insecticides were more likely to occur in rivers surrounded by African palm oil plantations, while imidacloprid risks were identified in corn crop areas as well as in natural areas. Future investigations are needed to clarify the sources of imidacloprid contamination and to assess its effects for Amazonian freshwater ecosystems.

Low-Cost Water Quality Sensors for IoT: A Systematic Review.

In many countries, water quality monitoring is limited due to the high cost of logistics and professional equipment such as multiparametric probes. However, low-cost sensors integrated with the Internet of Things can enable real-time environmental monitoring networks, providing valuable water quality information to the public. To facilitate the widespread adoption of these sensors, it is crucial to identify which sensors can accurately measure key water quality parameters, their manufacturers, and their reliability in different environments. Although there is an increasing body of work utilizing low-cost water quality sensors, many questions remain unanswered. To address this issue, a systematic literature review was conducted to determine which low-cost sensors are being used for remote water quality monitoring. The results show that there are three primary vendors for the sensors used in the selected papers. Most sensors range in price from US$6.9 to US$169.00 but can cost up to US$500.00. While many papers suggest that low-cost sensors are suitable for water quality monitoring, few compare low-cost sensors to reference devices. Therefore, further research is necessary to determine the reliability and accuracy of low-cost sensors compared to professional devices.

Effects of rainfall and land use on nutrient responses in rivers in the Brazilian semiarid region.

This paper investigated whether rainfall promotes dilution or increase in nutrient concentrations and which land use indicators are the main predictors of nutrients in intermittent rivers in a large Brazilian semiarid region. The total phosphorus (TP) and total inorganic nitrogen (TIN) were monitored between 2013 and 2018 at 92 river water quality monitoring sites. The monthly rainfall (Rn) was obtained from 575 rain gauges. Pearson's correlation (R) between Rn and nutrient concentration was performed. The correlation patterns were also analysed based on land use data: urban area (%), agricultural field area (%), demographic density (inhabitants/km2), sewer system coverage (%), and reservoir density (reservoir/km2). Backward stepwise regression was performed to identify predictors of nutrient concentrations. The results revealed a marginal effect of rainfall on nutrients when the effects of urbanisation outweigh all other aspects. However, in regions with greater accumulated rainfall and lower reservoir density, the rainfall was related to a linear increase in nutrient concentrations (R > 0.8). Contrastingly, in the basins with less accumulated rainfall and greater inter-basin hydrological disconnection, there was a linear reduction in nutrient concentration (R < - 0.5). In the backward stepwise regression, sewer system coverage and Rn had the greatest influence for TP, and the urban area was the strongest predictor for TIN. Importantly, our results demonstrated that in semiarid rivers in densely populated regions, there is no single pattern of variability in nutrient concentration, on a wide scale of assessment. Therefore, adaptative and decentralised management can be more effective in improving water quality in these regions.

Integration of Remote Sensing and Mexican Water Quality Monitoring System Using an Extreme Learning Machine.

Remote Sensing, as a driver for water management decisions, needs further integration with monitoring water quality programs, especially in developing countries. Moreover, usage of remote sensing approaches has not been broadly applied in monitoring routines. Therefore, it is necessary to assess the efficacy of available sensors to complement the often limited field measurements from such programs and build models that support monitoring tasks. Here, we integrate field measurements (2013-2019) from the Mexican national water quality monitoring system (RNMCA) with data from Landsat-8 OLI, Sentinel-3 OLCI, and Sentinel-2 MSI to train an extreme learning machine (ELM), a support vector regression (SVR) and a linear regression (LR) for estimating Chlorophyll-a (Chl-a), Turbidity, Total Suspended Matter (TSM) and Secchi Disk Depth (SDD). Additionally, OLCI Level-2 Products for Chl-a and TSM are compared against the RNMCA data. We observed that OLCI Level-2 Products are poorly correlated with the RNMCA data and it is not feasible to rely only on them to support monitoring operations. However, OLCI atmospherically corrected data is useful to develop accurate models using an ELM, particularly for Turbidity (R2 = 0.7). We conclude that remote sensing is useful to support monitoring systems tasks, and its progressive integration will improve the quality of water quality monitoring programs.

Spatio-temporal changes in water quality in the Guarapiranga reservoir (São Paulo, Brazil): insights from a long-term monitoring data series.

The provision of drinking water in metropolises is a challenge that requires programs for continuous monitoring of water quality and processes that impact the land cover of the watershed. In this work, we investigated through multivariate statistical analysis the temporal and spatial trends of several variables, not yet explored in a data series that includes 42 years (1978-2020) of monitoring in the hydrographic basin of the Guarapiranga reservoir, in the São Paulo Metropolitan Region-SPMR (Brazil). This reservoir is the source of drinking water for 3.8 million people and plays a strategic role in the social, environmental, and economic structure at SPMR. Our results point to the continuous degradation of water quality in the reservoir, although with different causes and spatio-temporal aspects. Between the 1970s and 1980s, variables associated with erosion/silting played a more critical role. From the 1990s, the introduction of N and P intensified, and the concentration of thermotolerant coliforms increased. The loss of quality is mainly associated with the progressive advance of urban settlements without planning combined with the inefficient initiatives to control domestic sewage pollution. If there is no rapid and comprehensive intervention, there is a risk that the Guarapiranga reservoir may become unsuitable for drinking water supply and other types of use in the future. This scenario will represent a critical obstacle to regional development and the quality of life of the population.

A spatiotemporal analysis of the physicochemical parameters after the operation of the Corumbá IV reservoir (Midwest Brazil) to support better management decision.

The study presents the characterization of the water quality of the Corumbá IV reservoir in the State of Goiás, in the Brazilian Cerrado biome, based on data from the operation period between 2007 and 2017. Few are known about the temporal and spatial variations in the water quality of the reservoir. Up to now, the water quality has been analyzed only from the point of view of compliance with the limits required by Brazilian environmental legislation. Therefore, the integrated analysis of water quality parameters and water body dynamics may bring important information to support decision-making in reservoir management. An exploratory analysis of the limnological data series provided by the company in charge of the hydroelectric plant was then carried out. Univariate and multivariate statistical techniques were applied to analyze the data period from 2007 to 2017. The results identify four distinct limnological phases representing the transition of the environment. The first phase (2007 to 2009) characterized by the decomposition of the flooded vegetal organic matter and subsequent phases, after 8 years (2010 to 2017), have featured the transition process from the lotic condition to the consolidation of the lentic environment. The spatial analysis of the results demonstrates that tributaries influence the water quality of the reservoir differently, probably due to the different impacts suffered in the sub-basins (e.g., sewage discharges; runoff). Although it is possible to evidence the impact of anthropic activities on water quality, the reservoir still presents characteristics of an environment with low trophic status.

An image processing method for recognition of four aquatic macroinvertebrates genera in freshwater environments in the Andean region of Colombia.

The aquatic macroinvertebrate community reflects the ecological status of a river. Typically, some extraction methods have been implemented, but the capture and preservation of organisms are necessary. The techniques of digital image processing applied to ecology have become innovative tools for the characterization of aquatic macroinvertebrates. This research implements a methodology for the processing and classification of four aquatic macroinvertebrates genera Thraulodes, Traverella (Ephemeroptera), Anacroneuria (Plecoptera), and Smicridea (Trichoptera) present in three rivers in Antioquia (Colombia), which includes two phases. The first of these was the collection and capture of organisms to obtain a database of the most abundant genera, at laboratory scale. The second was the use of simulations that allow the classification of data through a process of selection and extraction of characteristics using the bag of visual words technique. Of all the classifiers tested, Gaussian vector support machines obtained a percentage of success in the recognition up method of four organisms to the genus level of 97.1 %. The training and computational processing for classification enabled the standardization of an appropriate methodology that will serve as a starting point for aquatic biomonitoring and inventory in Colombia and internationally.

A Methodology for Data-Driven Decision-Making in the Monitoring of Particulate Matter Environmental Contamination in Santiago of Chile.

Atmospheric pollution derives mainly from anthropogenic activities that use combustion and may lead to adverse effects in exposed populations. It is generally accepted that air contamination causes cardiovascular and pulmonary morbidity in addition to increased mortality after exposure, but other epidemiological associations have also been described, including cancer as well as reproductive and immunological toxicity. Thus the concentration of chemicals in the air must be controlled. We propose that monitoring of air quality may be achieved by employing data analytics to generate information within the context of data-driven decision making to prevent and/or adequately alert the population about possible critical episodes of air contamination. In this paper, we propose a methodology for monitoring particulate matter pollution in Santiago of Chile which is based on bivariate control charts with heavy-tailed asymmetric distributions. This methodology is useful for monitoring environmental risk when the particulate matter concentrations follow bivariate Birnbaum-Saunders or Birnbaum-Saunders-t-Student distributions. A case study with real particulate matter pollution from Santiago is provided, which shows that the methodology is suitable to alert early episodes of extreme air pollution. The results are in agreement with the critical episodes reported with the current model used by the Chilean health authority.

Advantages and challenges of the implementation of a low-cost particulate matter monitoring system as a decision-making tool.

The integration of monitoring technologies in the last decades has been a key factor in the development of new ways to track air pollutants and supplementing the network of traditional monitoring systems. In this regard, the appearance of affordable and accurate sensor devices to monitor air quality has made possible to obtain relevant data about the state of the air, and moreover, eminent institutions are interested in promoting the use of novel and more affordable tools for air pollution, such as the United States Environmental Protection Agency and European institutions, within a new approach to environmental surveillance, known as Next Generation Compliance and Enforcement technologies. On other hand, in order to get more reliable measurements, the use of machine learning to support adjustment or calibration process has been used in some studies to improve the performance of monitoring devices. On this paper, led by a group of specialists of the Chilean Superintendence of Environment (henceforth, SMA from its Spanish initials), a first approach case study related to the convenience of the usage of low-cost devices in environmental enforcement will be presented. The study was made in the Metropolitan Region of Santiago and considers the spatial distribution of different particulate matter sensors in the region. Some aspects regarding communication and technical issues are presented as well as the main findings about their performance. Results illustrate that low-cost sensors, aided by machine learning algorithms, could provide a reliable enough general screening of particulate matter within a large city, constituting a valuable decision-making tool for environmental oversight, as well as a powerful preventive and deterrent approach for compliance.

Aplicação de análise multivariada no estudo da frequência de amostragem e do número de estações de monitoramento de qualidade da água / Multivariate analysis applied for study of the sampling frequency and the number of sampling stations in water quality monitoring

RESUMO O cerne do presente trabalho consistiu em aplicar ferramentas de análise exploratória multivariada objetivando avaliar o número de estações de monitoramento de qualidade da água e a frequência de amostragem. Para tal, utilizou-se banco de dados disponibilizado pelo Instituto Mineiro de Gestão das Águas (IGAM) referente à Bacia do Rio das Velhas, na região central mais populosa de Minas Gerais. Foram utilizadas as técnicas de análise das componentes principais (ACP) e a rede neural de Kohonen, que culminaram na significativa redução da frequência de amostragem, em alguns casos de mensal para anual ou semestral, e na redução do número de estações de monitoramento de 36 para 33. Os resultados permitem abrir a possibilidade do emprego dos métodos utilizados como ferramentas de gestão de recursos hídricos de bacias hidrográficas visando à otimização dos programas de monitoramento de qualidade de água.

ABSTRACT The core of this work consisted of applying multivariate exploratory analysis tools to evaluate the number of water quality monitoring stations and the sampling frequency. In such way, the database provided by the Minas Gerais Institute of Water Management (IGAM) on the river basin of Rio das Velhas, in the most populous central region of Minas Gerais state, was used. The Principal Components Analysis and the Kohonen neural network techniques were applied, resulting in a significant reduction in sampling frequency, in some cases from monthly to annual or semi-annual, and in the reduction of the number of monitoring stations from 36 to 33. The results open the possibility of using these methods as watershed water resources management tools aimed at optimization of water quality monitoring programs.

Detection, provenance and associated environmental risks of water quality pollutants during anomaly events in River Atoyac, Central Mexico: A real-time monitoring approach.

River Atoyac is considered to be one of the most polluted rivers in Mexico due to the discharges of untreated or partially treated wastewater from industrial and municipal activities. In order to improve the river water quality, it is obligatory to identify the possible contaminant sources for upholding a well-balanced ecosystem. Henceforth, the present study incorporates the application of a continuous real-time monitoring system to identify the provenance of pollutants of the river mainly from anomaly events. Four monitoring stations were installed all along the River Atoyac in the State of Puebla, Central Mexico. The real-time monitoring systems have an ability to measure various water quality parameters for every 15 minutes such as Temperature (T), pH, Conductivity (EC), turbidity (TURB), Dissolved Oxygen (DO), Oxidation Reduction Potential (ORP) and Spectral Absorption Coefficient (SAC). In total, eight water samples of anomaly events (i.e.) 2 per monitoring station during rainy (August-September) and winter seasons (November-December), that were detected using the parameters previously mentioned were procured and also analyzed in the laboratory for evaluating almost 54 physicochemical, inorganic and organic characteristics. Statistical results of factorial analysis explained that 30% of the total variance corresponded to textile effluents, 23% related to discharges produced by automobile and petrochemical industries, and 18% of the total variance defined the agricultural activities. Additionally, indices like Overall Index Pollution, Heavy Metal Evaluation Index, Screening Quick Reference Table and Molecular ratios of hydrocarbons for PAH sources was also calculated to estimate the grade of pollution and associated ecotoxicological risks. The present study also enlightens the fact that the assessed results will definitely provide valuable information for the management of river water quality by developing stringent public policies by governmental agencies for the sustainable conservation of Atoyac River.

Observing home-visiting quality at scale with the home visit rating scales and a supervisor checklist in Peru.

As home-visiting programs expand, there is a need to develop cost-effective tools to monitor their quality at scale. We compare the Home Visit Rating Scales (HOVRS), an instrument to measure home-visit process quality widely used in the United States, to a checklist designed for the Peruvian national home-visiting program, Cuna Mas. Both instruments were administered to a sample of 554 home visits and an equal number of mother-child dyads by their 176 home visitors. While the HOVRS was scored on video recordings of the visits by trained coders, the checklist was scored live by Cuna Mas supervisors. We assessed the validity of both measures in their first application in rural Peru, compared their performance, and selected a subset of items in the checklist to propose a simplified, shorter, and more cost-efficient instrument. To this end, we reorganized checklist items into constructs that best mapped those covered by the HOVRS and selected the highest performing according to predefined criteria. We found that both the HOVRS and the checklist had high reliability and acceptable levels of validity. We argue that the simplified checklist could prove useful for quality monitoring of service delivery of at-scale home-visiting programs and as a tool to support in-service training.

A medida que los programas de visita a casa se expanden, hay una necesidad de desarrollar herramientas de costo eficaz para vigilar la calidad de los mismos a una escala. Comparamos las Escalas de Evaluación de Visitas a Casa (HOVRS), un instrumento para medir la calidad de los procesos de visita a casa ampliamente usado en los Estados Unidos, con una lista de control diseñada para el programa nacional de visitas a casa de Perú, Cuna Mas. Los 176 visitadores a casa le administraron ambos documentos a un grupo muestra de 554 visitas a casa y a un número equivalente de díadas mamá-niño. Los codificadores entrenados evaluaron HOVRS por medio de grabaciones de video de las visitas, mientras que la lista de control fue evaluada en persona por los supervisores de Cuna Mas. Nosotros evaluamos la validez de ambas medidas en su primera puesta en práctica en el Perú rural, comparamos su rendimiento y seleccionamos un subgrupo de categorías en la lista de control para proponer un instrumento simplificado, más corto y de costo más eficaz. Con este fin, reorganizamos las categorías de la lista de control en segmentos que mejor cubren aquellas que están presentes en HOVRS y seleccionamos las que presentan mayor rendimiento de acuerdo con criterios predefinidos. Nos dimos cuenta de que tanto HOVRS como la lista de control presentaban una alta confiabilidad y niveles aceptables de validez. Sostenemos que la lista de control simplificada pudiera demostrar utilidad en cuanto a la calidad de la supervisión del ofrecimiento del servicio de programas de visitas a casa a una escala y como una herramienta para apoyar la capacitación en el empleo.

Du fait que les programmes de visite à domicile se développement, on voit un besoin de développer également des outils rentables afin de contrôler leur qualité à grande échelle. Nous comparons les Echelles d'Evaluation de la Visite à Domicile (en anglais Home Visit Rating Scales, soit HOVRS), un instrument destiné à mesurer la qualité du processus de visite à domicile largement utilisé aux Etats-Unis, à une checklist conçue pour le programme national péruvien de visite à domicile, Cuna Mas. Les deux instruments ont été utilisés avec un échantillon de 554 visites à domiciles et une nombre égal de dyades mère-enfant par leurs 176 visiteurs à domicile. Alors que la HOVRS était évaluée au moyen d'enregistrements vidéo des visites par des évaluateurs entraînés, la checklist a été évaluée en temps réel par les superviseurs de Cuna Mas. Nous avons évalué la validité des deux mesures dans leur première application dans le Pérou rural, comparé leur performance, et sélectionné un sous-groupe d'éléments de la checklist afin de proposer un instrument simplifié, plus court et plus rentable. Pour ce faire nous avons réorganisé les éléments de la checklist en structures cartographiant le mieux ceux couverts par les HOVRS et sélectionné les plus performants selon des critères prédéfinis. Nous avons trouvé qu'à la fois les HOVRS et la checklist faisaient preuve d'une fiabilité élevée et de niveaux de validité acceptables. Nous concluons que la checklist simplifiée pourrait s'avérer utile pour le contrôle de la qualité des prestations de service de programmes de visites à domicile à grande échelle et en tant qu'outil utilisé pour soutenir la formation continue.

Proposal of a Method to Determine the Correlation between Total Suspended Solids and Dissolved Organic Matter in Water Bodies from Spectral Imaging and Artificial Neural Networks.

Water quality monitoring through remote sensing with UAVs is best conducted using multispectral sensors; however, these sensors are expensive. We aimed to predict multispectral bands from a low-cost sensor (R, G, B bands) using artificial neural networks (ANN). We studied a lake located on the campus of Unisinos University, Brazil, using a low-cost sensor mounted on a UAV. Simultaneously, we collected water samples during the UAV flight to determine total suspended solids (TSS) and dissolved organic matter (DOM). We correlated the three bands predicted with TSS and DOM. The results show that the ANN validation process predicted the three bands of the multispectral sensor using the three bands of the low-cost sensor with a low average error of 19%. The correlations with TSS and DOM resulted in R² values of greater than 0.60, consistent with literature values.

Efeitos do tamanho da partícula e da concentração de sedimentos suspensos sobre a turbidez / Effect of particle size and suspended sediment concentration on turbidity

RESUMO Neste estudo foram avaliados os efeitos do tamanho da partícula e de variações da concentração de sedimentos suspensos (CSS) sobre as leituras de turbidez de três sensores óptico-nefelométricos, com iguais características ópticas e geométricas, utilizando amostras de sedimentos suspensos coletadas na seção fluviométrica da bacia do Turcato (19,5 km²), localizada na Região Sul do Brasil. O material coletado passou por processos de peneiramento e pipetagem para fracionamento nas granulometrias areia e silte. Para cada diâmetro foram separadas frações com diferentes concentrações de sedimentos, variando entre 0,01 e 5,00 g.L-1. Os resultados demonstram grande influência da CSS e do tamanho da partícula sobre a turbidez. Para qualquer situação, o aumento da turbidez é inverso ao tamanho da partícula e diretamente relacionado ao aumento da CSS. As variações da turbidez, expressas em função da CSS (sensibilidade do sensor), são maiores para menores diâmetros, atingindo valores quase constantes para partículas de areia. As leituras de turbidez dos três sensores não apresentaram diferença significativa no nível de 5% pelo teste de Mann-Whitney rank sum . Para uma mesma CSS, a leitura de turbidez pode ser diferente, conforme a classe granulométrica analisada. A turbidez registrada pelo sensor para a classe silte equivale a uma turbidez observada para uma CSS dez vezes menor para a classe das areias.

ABSTRACT This study evaluates the effects of particle size and variations of CSS on turbidity readings of three optical-nephelometric sensors using sediment samples collected in the field. Samples were collected in fluviometric station at Turcato basin (19.5 km²), located in the South region of Brazil. The collected material underwent screening and pipetting processes for fractionation in sand and silt grain size. For each diameter were separated fractions with different sediment concentration ranging between 0.01 and 5.00 g.L-1. The results demonstrate great influence of CSS and particle size on turbidity readings. The increase in turbidity is opposite to particle size and directly related to CSS. Variations in turbidity, expressed in CSS function (sensor sensitivity), are higher for smaller diameters, reaching almost constant values for sand particles. Turbidity readings of the three sensors showed no significant difference in the level of 5% by the Mann-Whitney rank sum test. For a given CSS, the turbidity reading may be different, depending on the granulometric class analyzed. Turbidity recorded by the sensor to the silt-class is equivalent to a sensor response observed for a CSS ten times lower for the sand class.

Omics approaches in fish quality and safety / Procedimentos ômicos aplicados em qualidade e segurança de pescado

Omics is a new technology that uses genomics, proteomics, and metabolomics to investigate metabolites from foods. The global demand for fish has shown a progressive increase because it is a significant source of high quality protein, polyunsaturated fatty acids, especially omega-3, and essential minerals. However, there are barriers in the fishery production chain such as lack of standardization, knowledge, and technology transfer to industry. Moreover, fish effective monitoring is difficult due to restricted quality parameters and analytical methods determined by current Brazilian legislation. This review details the limiting chemical parameters and recent advances in analytical procedures for fish quality determination. To improve fish quality monitoring, total volatile basic nitrogen (TVB-N), trimethylamine (TMA), ammonia, pH, and biogenic amines values should be revised and established by fish category and/or type of fish product. On the other hand, protein carbonyl concentration, free fatty acids (FFAs), peroxide values (POV), and thiobarbituric acid reactive substances (TBARS) should be included in the national legislation. Simultaneously, the official authorities should take into account effective, practical, and low cost analytical methodologies, which lead to faster results in order to facilitate and enhance the quality control of the products from the fish production chain, ensuring the consumer's health. Moreover, analytical techniques for the identification of fish species must be introduced in the Brazilian legislation in order to avoid illegal substitutions and negative impacts to consumers.(AU)

Os procedimentos ômicos são uma nova tecnologia que utiliza a genômica, proteômica e metabolômica para avaliar metabólitos dos alimentos. A demanda mundial de pescado tem aumentado progressivamente devido à elevada qualidade de proteínas, minerais e ácidos graxos poli-insaturados, especialmente ômega-3. Todavia, a cadeia produtiva aquícola apresenta limitações como falta de padronização, ausência de conhecimento e transferência de tecnologia para as indústrias. Além disso, torna-se difícil garantir um monitoramento efetivo do pescado em decorrência das limitações dos parâmetros de qualidade atuais e dos métodos analíticos estabelecidos pela legislação nacional. O presente trabalho analisa os fatores limitantes relacionados aos parâmetros químicos, bem como os avanços recentes nos procedimentos analíticos, para determinação da qualidade do pescado. Levando-se em consideração a melhoria no controle de qualidade dessa matriz, os parâmetros de bases voláteis totais (BVT), trimetilamina (TMA), amônia, pH e aminas biogênicas deveriam ser revisados e estabelecidos por categorias de pescado e/ou por tipo de produto à base de pescado. Em contrapartida, parâmetros relacionados à concentração de carbonilas, ácidos graxos livres (AGLs), índice de peróxidos (IP) e malonaldeído (MDA) poderiam ser inseridos na legislação nacional. Simultaneamente, as autoridades oficiais devem levar em consideração metodologias analíticas que apresentem efetividade, praticidade, baixo custo e rapidez, facilitando e aprimorando o controle de qualidade de produtos de pescado e garantindo a saúde dos consumidores. Além disso, técnicas analíticas para identificação das espécies de peixes devem ser incluídas na legislação brasileira visando evitar substituições ilegais e impactos negativos aos consumidores.(AU)

Omics approaches in fish quality and safety / Procedimentos ômicos aplicados em qualidade e segurança de pescado

Omics is a new technology that uses genomics, proteomics, and metabolomics to investigate metabolites from foods. The global demand for fish has shown a progressive increase because it is a significant source of high quality protein, polyunsaturated fatty acids, especially omega-3, and essential minerals. However, there are barriers in the fishery production chain such as lack of standardization, knowledge, and technology transfer to industry. Moreover, fish effective monitoring is difficult due to restricted quality parameters and analytical methods determined by current Brazilian legislation. This review details the limiting chemical parameters and recent advances in analytical procedures for fish quality determination. To improve fish quality monitoring, total volatile basic nitrogen (TVB-N), trimethylamine (TMA), ammonia, pH, and biogenic amines values should be revised and established by fish category and/or type of fish product. On the other hand, protein carbonyl concentration, free fatty acids (FFAs), peroxide values (POV), and thiobarbituric acid reactive substances (TBARS) should be included in the national legislation. Simultaneously, the official authorities should take into account effective, practical, and low cost analytical methodologies, which lead to faster results in order to facilitate and enhance the quality control of the products from the fish production chain, ensuring the consumer's health. Moreover, analytical techniques for the identification of fish species must be introduced in the Brazilian legislation in order to avoid illegal substitutions and negative impacts to consumers.(AU)

Os procedimentos ômicos são uma nova tecnologia que utiliza a genômica, proteômica e metabolômica para avaliar metabólitos dos alimentos. A demanda mundial de pescado tem aumentado progressivamente devido à elevada qualidade de proteínas, minerais e ácidos graxos poli-insaturados, especialmente ômega-3. Todavia, a cadeia produtiva aquícola apresenta limitações como falta de padronização, ausência de conhecimento e transferência de tecnologia para as indústrias. Além disso, torna-se difícil garantir um monitoramento efetivo do pescado em decorrência das limitações dos parâmetros de qualidade atuais e dos métodos analíticos estabelecidos pela legislação nacional. O presente trabalho analisa os fatores limitantes relacionados aos parâmetros químicos, bem como os avanços recentes nos procedimentos analíticos, para determinação da qualidade do pescado. Levando-se em consideração a melhoria no controle de qualidade dessa matriz, os parâmetros de bases voláteis totais (BVT), trimetilamina (TMA), amônia, pH e aminas biogênicas deveriam ser revisados e estabelecidos por categorias de pescado e/ou por tipo de produto à base de pescado. Em contrapartida, parâmetros relacionados à concentração de carbonilas, ácidos graxos livres (AGLs), índice de peróxidos (IP) e malonaldeído (MDA) poderiam ser inseridos na legislação nacional. Simultaneamente, as autoridades oficiais devem levar em consideração metodologias analíticas que apresentem efetividade, praticidade, baixo custo e rapidez, facilitando e aprimorando o controle de qualidade de produtos de pescado e garantindo a saúde dos consumidores. Além disso, técnicas analíticas para identificação das espécies de peixes devem ser incluídas na legislação brasileira visando evitar substituições ilegais e impactos negativos aos consumidores.(AU)