Nutrient Monitoring Research Articles

New marine low trophic resources as food: nutritional and food safety aspects

Food agencies recommend increasing the consumption of aquatic food to promote healthy living and sustainability, and, particularly, to prevent Western lifestyle-related diseases and secure sustainable food systems. This requires growth in global seafood production, and the utilization of low trophic species (LTS) is suggested. LTS are already considered nutritious and important in Asian and Pacific diets. As the use of LTS is expanding in Western diets, producers and consumers need information on the food safety practices associated with them and their nutritional content. LTS are mainly immobile or slow-moving extractive species or organisms that feed on such, and their nutrient and contaminant content varies by species and location. Species-specific knowledge on nutritional contents and safe consumption limits is often missing, making the monitoring and analysis of contaminants, nutrients, and consumption data crucial to guiding the utilization and consumption of LTS. Using global and regional standards regarding nutrients, food hazards, and labeling, this review highlights the appropriate guidelines and regulations for guiding the utilization of selected novel species and also identifies knowledge gaps.

MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa

The research and development needed to achieve sustainability of African smallholder agricultural and natural systems has led to a wide array of theoretical frameworks for conceptualising socioecological processes and functions. However, there are few analytical tools for spatio-temporal empirical approaches to implement use cases, which is a prerequisite to understand the performance of smallholder farms in the real world. This study builds a multi-agent system (MAS) to operationalise the Sustainable Agricultural Intensification (SAI) theoretical framework (MASSAI). This is an essential tool for spatio-temporal simulation of farm productivity to evaluate sustainability trends into the future at fine scale of a managed plot. MASSAI evaluates dynamic nutrient transfer using smallholder nutrient monitoring functions which have been calibrated with parameters from Malawi and the region. It integrates two modules: the Environmental (EM) and Behavioural (BM) ones.•The EM assess dynamic natural nutrient inputs (sedimentation and atmospheric deposition) and outputs (leaching, erosion and gaseous loses) as a product of bioclimatic factors and land use activities.•An integrated BM assess the impact of farmer decisions which influence farm-level inputs (fertilizer, manure, biological N fixation) and outputs (crop yields and associated grain).•A use case of input subsidies, common in Africa, markedly influence fertilizer access and the impact of different policy scenarios on decision-making, crop productivity, and nutrient balance are simulated. This is of use for empirical analysis smallholder's sustainability trajectories given the pro-poor development policy support.

Internal nutrients dominate load and drive hypoxia in a eutrophic estuary.

The hypothesis that local hypoxia and chlorophyll concentration are spatially tethered to local, sediment-driven nutrient release was examined in a small, nutrient-impacted estuary in the Southern Gulf of St. Lawrence, Canada. Sediment reactor core samples were taken at 10 locations between 0.25 and 100% of the estuary area in spring and fall (2019) and used to estimate nitrogen and phosphate flux. Sediment organic matter, carbonate, percent nitrogen, percent carbon, δ13C, and δ15N were measured from the reactor core stations. Oxygen was recorded continually using oxygen loggers while chlorophyll and salinity were measured bi-weekly. A hydrodynamic model was used to determine water renewal time at each station. The most severe eutrophication effects were in the upper one-fifth of the estuary. There were strong local relationships between sediment biogeochemistry, hypoxia, and chlorophyll metrics but not with water renewal time. Internal nutrient loading represented 65% and 69% of total N loading, and 98% and 89% of total P loading to the estuary in June and September, respectively. Sediment nitrogen flux was highly predictable from a range of local sediment variables that reflect either nutrient content, or organic carbon enrichment in general. Percent nitrogen and percent carbon were highly correlated but sediment P flux was poorly predicted from sediment parameters examined. The highest correlations were with percent nitrogen and percent carbon. These results indicate that incorporating internal nutrient loading into nutrient monitoring programs is a critical next step to improve predictive capacity for eutrophication endpoints and to mitigate nutrient effects.

Vertical Farming using Smart Farming

Nutrient content (Nitrogen, Phosphorous, Potassium) monitoring in soils is essential for the proper use of fertilizers to minimize the environmental impact of wrong pattern fertilization practice. Collecting samples from different locations and laboratory testing takes longer and costs a lot. New-generation digital sensors are smart enough to replace chemical lab testing in real-time with minimum effort and with almost precise results. The Proposed system tends to implement various suggestions that would also help improve the quality of the work being done by the soil testing laboratories. By this, we can able to test our soil parameter in that condition quickly in our field for further processes and we will get the soil parameter report without any delay. And we can get information about the fertilizer and crop matches for that result and the number of fertilizers to be used. And to demonstrate soil humidity sensors and pH sensors to measure the NPK values which determine the fertility of the soil, which helps to improve cultivating system. The results obtained from our developed sensing system are almost accurate and very close to the laboratory test readings. Arduino plays a key role in processing data received from the sensor as input, the counters used here produce the respected output values for the parameters. There the values received by the Arduino are compared with the database and provide related information which is matched to the current calculated values. The output values provided by the Arduino and sensors will be displayed on the LCD. Here the output not only provides formation on fertility present in the soil but also suggests crops to be grown on that soil. Keywords—Vertical farming, smart farming, nutrient monitoring, digital sensors, soil fertility, crop suggestions.

Development of Soil Microbial Fuel Cell for Continuous Real-time Monitoring of Soil Data

The planet is getting hotter due to human activities that release greenhouse gases. Promoting renewable energy, which doesn’t emit carbon, can help mitigate global warming. Farmland, which covers a large portion of the Earth’s land area, can also be used as an energy source through the help of indigenous microorganisms in the soil that transform chemical energy into electrical energy with electrolysis. Real-time monitoring of soil nutrients is necessary to obtain an accurate yield from crops. This is achieved with the use of sensors that are powered by the energy generated from the soil. Zinc and copper electrodes are used to generate power, and a combination of 15x6 cells is used to maximize voltage and current generation. The output powers soil sensors like FC-28 and NPK sensors, and the data is sent to the AWS cloud for real-time monitoring of soil parameters. The experimental results show that a single SMFC cell generates 0.6V, while a series-parallel combination generates approximately 9V. By using a current booster circuit, the efficiency of the setup can be further improved. This technology is not yet widely used in the agricultural industry, but it has the potential to help farmers conveniently monitor soil conditions by utilizing the power generated from the soil itself.

Climate-driven intensification of hypolimnetic deoxygenation in Lake Fuxian, a monomictic lake in south-western China, since the 1990s

In monomictic lakes, the potential intensification of hypolimnetic deoxygenation due to human activities and climate change threatens lake ecosystems and water quality. Understanding the trends and mechanisms of hypolimnetic deoxygenation would allow for the adaptive management of monomictic lakes. This study investigated the trends and drivers of hypolimnetic deoxygenation in Lake Fuxian (a monomictic lake in south-western China) over the past 150 years using paleolimnological evidence and historical records. Analysis of enrichment factors for molybdenum (Mo), uranium (U), and vanadium (V), and ratios of U/thorium (Th), pristane (Pr)/phytane (Ph), and total organic carbon (TOC)/total phosphorus (TP) in a dated sediment core indicated that the extent of hypolimnetic deoxygenation was relatively low before 1994 and increased substantially thereafter. Nutrient monitoring records and sediment n-alkane proxies indicated notable eutrophication of the lake since 1986 and a greater degree of human disturbance in the catchment between 1951 and 1967. Due to their asynchronous occurrence, eutrophication and catchment disturbance could not be the major drivers of hypolimnetic deoxygenation. Interestingly, climate records indicated that the local ambient temperature exhibited similar trends to that of hypolimnetic deoxygenation, including markedly higher temperatures after 1994. This implies that prolonged water column stratification due to climate warming could have promoted hypolimnetic deoxygenation by limiting oxygen exchange between the upper and lower water columns. In comparing the results with those of Lake Erhai, another monomictic lake with contrasting morphology and hydrology characteristics, we found that the low surface area/depth ratio and long water residence time in Lake Fuxian enable dissolved oxygen of the lake hypolimnion vulnerable to temperature over the lake.

Prototype Sistem Monitoring Nutrisi dan Tingkat pH Air pada Budidaya Hidroponik Sayur Pakcoy Menggunakan Teknologi Internet of Things (IoT)

The agricultural industry is critical in supplying food and fiber demands, but there is a demand-supply imbalance due to decreased land availability. Hydroponic techniques can be utilized to alleviate agricultural land loss by using water as a growing medium. Farmers must constantly examine plant condition and harvesting schedules. The pH of the water and nutrients are important indications for hydroponic farmers to monitor. Therefore, the implementation of the Internet of Things (IoT) allows farmers to conduct real-time monitoring more easily and regularly. IoT is defined as a system that allows integrated hardware to communicate with the internet network. The IoT device is built by attaching a NodeMCU 8266 microcontroller to an adapter, which provides electrical voltage while also regulating a water pump that delivers nutrients and water to plants. The acquired data is then transmitted to the blynk program, allowing real-time monitoring of the results via a smartphone. The present research system's usefulness and performance are improved by including pH and TDS sensors. The average accuracy of pH monitoring utilizing a pH sensor and a manual pH meter was 92.09%. Meanwhile, the average accuracy of nutrient monitoring utilizing TDS sensors and a TDS meter was 73.19%.

Estimation of Nitrogen Concentration in Walnut Canopies in Southern Xinjiang Based on UAV Multispectral Images

Nitrogen is one of the most important nutrients affecting the growth and fruit quality of walnut trees. Rapid and accurate monitoring of nitrogen concentration in the walnut canopy can provide a digital basis for its nutritional diagnosis and precision fertilization. Consequently, the main purpose of this study was to use Unmanned Aerial Vehicle (UAV) remote sensing technology to monitor the nitrogen concentration of walnut canopies. In this study, UAV multispectral images of the canopies of nine walnut orchards with different management levels in Wensu County, South Xinjiang, China, were collected during the fast-growing (20 May), sclerotization (25 June), and near-maturity (27 August) periods of walnut fruit, and canopy nitrogen concentration data for 180 individual plants were collected during the same periods. The validity of the information extracted via the outline canopy and simulated canopy methods was compared. The accuracy of nitrogen concentration inversion for three modeling methods, partial least squares regression (PLSR), support vector machine (SVM), and random forest (RF), was analyzed; the effects of different combinations of variables on model accuracy were compared; and the spatial distribution of the nitrogen concentration in the walnut canopy was numerically mapped using the optimal model. The results showed that the accuracy of the model created using the single plant information extracted from the outlined canopy was better than that of the simulated canopy method, but the simulated canopy method was more efficient in extracting effective information from the single plant canopy than the outlined canopy. The simulated canopy method overcame the difficulty of mismatching the spectral information of individual plants extracted, by outlining the canopy in the original image for nitrogen distribution mapping with the spectral information of image elements in the original resolution image. The prediction accuracy of the RF model was better than that of the SVM and PLSR models; the prediction accuracy of the model using a combination of waveband texture information and vegetation index texture information was better than that of the single-source model. The coefficients of determination (R2) values of the RF prediction model built using the band texture information extracted via the simulated canopy method with the vegetation index texture information were in the range of 0.61–0.84, the root mean square error (RMSE) values were in the range of 0.27–0.43 g kg−1, and the relative analysis error (RPD) values were in the range of 1.58–2.20. This study shows that it is feasible to monitor the nitrogen concentration of walnut tree canopies using UAV multispectral remote sensing. This study provides a theoretical basis and methodological reference for the rapid monitoring of nutrients in fruit trees in southern Xinjiang.

Bloom-induced internal release controlling phosphorus dynamics in large shallow eutrophic Lake Taihu, China

High phosphorus (P) concentrations are commonly observed in lakes during algal blooms despite massive efforts on external nutrient reduction. However, the knowledge about the relative contribution of internal P loading linked with algal blooms on lake phosphorus (P) dynamics remains limited. To quantify the effect of internal loading on P dynamics, we conducted extensive spatial and multi-frequency nutrient monitoring from 2016 to 2021 in Lake Taihu, a large shallow eutrophic lake in China, and its tributaries (2017–2021). The in-lake P stores (ILSP) and external loading were estimated and then internal P loading was quantified from the mass balance equation. The results showed that the in-lake total P stores (ILSTP) ranged from 398.5 to 1530.2 tons (t), and exhibited a dramatic intra- and inter-annual variability. The annual internal TP loading released from sediment ranged from 1054.3 to 1508.4 t, which was equivalent to 115.6% (TP loading) of the external inputs on average, and responsible for the fluctuations of ILSTP on a weekly scale. High-frequency observations exemplified that ILSTP increased by 136.4% during algal blooms in 2017, while by only 47.2% as a result of external loading after heavy precipitation in 2020. Our study demonstrated that both bloom-induced internal loading and storm-induced external loading are likely to run counter significantly to watershed nutrient reduction efforts in large shallow lakes. More importantly, bloom-induced internal loading is higher than storm-induced external loading over the short term. Given the positive feedback loop between internal P loadings and algal bloom in eutrophic lakes, which explains the significant fluctuation of P concentration while nitrogen concentration decreased. It is emphasized that internal loading and ecosystem restoration are unignorable in shallow lakes, particularly in the algal-dominated region.

A slurry approach to identify nutrient critical source areas from subtropical catchment erosion

Targeting catchment nutrient critical source areas (CSAs) (areas contributing most of the nutrients in a catchment) is an efficient way to prioritize remediation sites for reducing nutrient runoff to waterways. We tested if the soil slurry approach – with particle sizes and sediment concentrations representative of those in streams during high rainfall events – can be used to identify potential CSAs within individual land use types, examine fire impacts, and identify the contribution of leaf litter in topsoil to nutrient export in subtropical catchments. We first confirmed the slurry approach met the prerequisite to identify CSAs with relatively higher nutrient contribution (not absolute load estimation) by comparing the slurry sampling with stream nutrient monitoring data. We validated that: 1) differences in slurry total nitrogen to phosphorus mass ratios from different land uses were consistent with stream monitoring data; and 2) our estimated nutrient export contribution from agricultural land, via the slurry approach, was comparable to that derived from monitoring data. Additionally, we found nutrient concentrations in slurries differed across soil types and management practice within individual land uses, correlating with nutrient concentrations in fine particles. These results indicate the slurry approach can be used to identify potential small-scale CSAs. Slurry results from burnt soils were also comparable to other studies showing increased levels of dissolved nutrient loss and higher nitrogen than phosphorus loss, than non-burnt soils. The slurry method also showed the contribution of leaf litter to slurry nutrient concentrations from topsoil was greater for dissolved nutrients than particulate nutrients, indicating different forms of nutrients need to be considered for impacts of vegetation. Our study reveals that the slurry method can be used to identify potential small-scale CSAs within the same land use from erosion and can account for impacts of vegetation and bushfires, providing timely information to guide catchment restoration actions.

The effect of aquaponics on tomato (Solanum lycopersicum) sensory, quality, and safety outcomes.

Resource-efficient food production practices are needed to support a sustainable food system. Aquaponics, a system where fish and produce are grown symbiotically in the same water circulating system, minimizes water usage, fertilizer input, and waste production. However, the impact of aquaponics on produce quality is underexplored. We utilize objective testing, descriptive analysis, and consumer acceptance to characterize the impact of aquaponics on tomato quality. Two tomato varieties were grown in an aquaponics system and compared with soil-grown controls across 3years. Safety was assessed by analyzing coliforms and confirming the absence of Escherichia coli. Weight, texture, color, moisture, titratable acidity, brix, and phenolic and antioxidant measurements were assessed. A semitrained descriptive sensory panel assessed 13 tomato attributes and acceptance was determined using untrained participants. Aquaponic tomatoes were frequently lighter and yellower in color and lower in brix. Descriptive analysis indicated significant differences in several sensory attributes, though these findings were inconsistent between years and varieties. Nutrient deficiencies may explain quality differences, as iron supplementation improved outcomes. Notably, the objective and descriptive differences minimally impacted consumer acceptance, as we found no significant differences in taste, texture, or appearance liking between production method in either variety. Despite variation in produce quality across years, aquaponics tomatoes pose minimal E. coli risk and are liked as much as soil-grown tomatoes. These findings demonstrate that aquaponics can produce products that are as acceptable as their soil-grown counterparts. PRACTICAL APPLICATION: Aquaponic tomatoes are as safe as soil-grown tomatoes. Furthermore, aquaponics tomatoes are liked as much as soil-grown tomatoes. Careful monitoring of nutrients in an aquaponic system may optimize quality. Overall, aquaponics has a minimal impact on tomato quality and thus is a sustainable food production method that can compete with conventional products on quality.

Influence of farmers’ socio-economic characteristics on nutrient flow and implications for system sustainability in smallholdings: a review

The rise in global human population, coupled with the effects of climate change, has increased the demand for arable land. Soil fertility has been the most affected, among other things. Many approaches to soil fertility management have been proposed by studies in Sub-Saharan Africa (SSA); however, the question of sustainability remains. Nutrient monitoring (NUTMON), which combines biophysical and socio-economic features for soil fertility management, gives an in-situ soil fertility status of a given land use system, which ultimately provides guidance in proposing appropriate soil management techniques in a given land use system. In this review, the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) approach was deployed for a systematic search of the literature materials. The review evaluated various studies on nutrient monitoring in SSA soils in order to understand the socioeconomic attributes and their influence on farming systems, as well as nutrient flow and balances. The review identified two dominant smallholder farming systems in SSA: mixed crop-livestock and mixed crop farming systems. Also, this review revealed that most nutrient balance studies in SSA have been done in mixed crop and livestock farming systems. However, regardless of the farming systems, the overall mean nutrient balances in all studies, particularly those of nitrogen (N) and potassium (K), were negative, indicating significant nutrient mining. The review further revealed a vast range of biophysical soil fertility management technologies; however, their adoption has been limited by socio-economic aspects including land ownership, gender, financial position, literacy level, and access to inputs. Therefore, in view of this situation, integrating biophysical and socioeconomic disciplines could address the problem of soil nutrient depletion holistically, thus decreasing the existing negative nutrient balances in the SSA region.

Groundwater as a source of phosphorus and silicate in an estuarine zone: results from continuous monitoring of nutrients and 222Rn

The concentrations of 222Rn and dissolved inorganic nutrients in river water at a fixed station of the Nakdong River estuary which has an artificial barrage were continuously measured from October 2014 to May 2015. Monthly benthic 222Rn flux from the river bottom was estimated using a simple mass balance model, taking into account 222Rn sources and sinks. The estimated benthic 222Rn flux shows a significant correlation with groundwater level, suggesting that groundwater level can be used as a representative of the groundwater input. Based on correlation analyses, the concentration of dissolved inorganic nitrogen (DIN) was found to be dependent primarily on river water input. In contrast, the concentrations of dissolved inorganic phosphorus (DIP) and dissolved inorganic silicate (DSi) were predominantly controlled by groundwater input. Our results suggest that groundwater input may be an important source of DIP, especially under P-limited condition, which can affect marine primary production and ecological problems such as eutrophication and algal blooms in the coastal zones.

Time‐dependent effects of ecological rehabilitation on soil phosphorus fractions on cut slopes in the mountains of Southwest China

AbstractWhen a cut slope is excavated, the ecological environment in the footprint is destroyed. Soil spray seeding technique is used for the ecological rehabilitation of cut slopes in the mountain areas of Southwest China. However, there have been few studies of the temporal variation in soil phosphorus (P) fractions during the rehabilitation of the cut slopes. In this study, time‐dependent changes in soil inorganic P (Pi) and organic P (Po) fractions of the cut slopes were assessed at selected post‐rehabilitation ages (i.e., 1 year, 1a; 3 years, 3a; 5 years, 5a; and 11 years, 11a). The results showed that the amounts of Pi and Po fractions in soils on rehabilitated cut slopes varied with time. The reduction in the total Po (TPo) content was mainly caused by the change in high concentration hydrochloric acid‐soluble Po (HHCl‐Po) in the soil. The reason for the highest TP content in 3a was the addition of inorganic fertilizer and straw in the artificial soil. The analyses of Pearson correlation and multiple stepwise linear regression showed that TPo and N:P were the main factors affecting the availability of soil P. With the increase in the post‐rehabilitation age, the limitation of soil P gradually weakened, but nitrogen became one of the limiting factors for plant growth. Overall, soil nutrient monitoring is very important for vegetation restoration of the cut slopes. Applying organic fertilizer after 5 years of ecological rehabilitation is conducive to long‐term supply of nutrients required for plant growth.

Vis-NIR Spectroscopy Combined with GAN Data Augmentation for Predicting Soil Nutrients in Degraded Alpine Meadows on the Qinghai-Tibet Plateau.

Soil nutrients play vital roles in vegetation growth and are a key indicator of land degradation. Accurate, rapid, and non-destructive measurement of the soil nutrient content is important for ecological conservation, degradation monitoring, and precision farming. Currently, visible and near-infrared (Vis-NIR) spectroscopy allows for rapid and non-destructive monitoring of soil nutrients. However, the performance of Vis-NIR inversion models is extremely dependent on the number of samples. Limited samples may lead to low prediction accuracy of the models. Therefore, modeling and prediction based on a small sample size remain a challenge. This study proposes a method for the simultaneous augmentation of soil spectral and nutrient data (total nitrogen (TN), soil organic matter (SOM), total potassium oxide (TK2O), and total phosphorus pentoxide (TP2O5)) using a generative adversarial network (GAN). The sample augmentation range and the level of accuracy improvement were also analyzed. First, 42 soil samples were collected from the pika disturbance area on the QTP. The collected soils were measured in the laboratory for Vis-NIR and TN, SOM, TK2O, and TP2O5 data. A GAN was then used to augment the soil spectral and nutrient data simultaneously. Finally, the effect of adding different numbers of generative samples to the training set on the predictive performance of a convolutional neural network (CNN) was analyzed and compared with another data augmentation method (extended multiplicative signal augmentation, EMSA). The results showed that a GAN can generate data very similar to real data and with better diversity. A total of 15, 30, 60, 120, and 240 generative samples (GAN and EMSA) were randomly selected from 300 generative samples to be included in the real data to train the CNN model. The model performance first improved and then deteriorated, and the GAN was more effective than EMSA. Further shortening the interval for adding GAN data revealed that the optimal ranges were 30-40, 50-60, 30-35, and 25-35 for TK2O, TN, TP2O5, and SOM, respectively, and the validation set accuracy was maximized in these ranges. Therefore, the above method can compensate to some extent for insufficient samples in the hyperspectral prediction of soil nutrients, and can quickly and accurately estimate the content of soil TK2O, TN, TP2O5, and SOM.

Development and Testing of an IoT Spectroscopic Nutrient Monitoring System for Use in Micro Indoor Smart Hydroponics

Nutrient monitoring in Micro Indoor Smart Hydroponics (MISH) relies on measuring electrical conductivity or total dissolved solids to determine the amount of nutrients in a hydroponic solution. Neither method can distinguish concentrations of individual nutrients. This study presents the development and testing of a novel spectroscopic sensor system to monitor nitrogen changes in nutrient solutions for MISH systems. The design phase determined that using an inexpensive AS7265x Internet of Thing (IoT) sensor in a transflective spectroscopic application could effectively detect small fluctuations in nitrogen concentraation. Next, a novel transflective sensor apparatus was designed and constructed for use in a MISH system experiment, growing lettuce over 30 days. Two solution tanks of different sizes, 80 L and 40 L, were used in the deployment of the system. Samples from each tank were analyzed for nitrogen concentration in a laboratory, and multilinear regression was used to predict the nitrogen concentrations using the AS7265x 18 spectral channels recorded in the sensor system. Significant results were found for both tanks with an R2 of 0.904 and 0.911 for the 80 and 40 L tanks, respectively. However, while the use of all wavelengths produced an accurate model, none of the individual wavelengths were indicative on their own. These findings indicate that the novel system presented in this study successfully and accurately monitors changes in nitrogen concentrations for MISH systems, using low cost IoT sensors.

Portable All-in-One Electrochemical Actuator-Sensor System for the Detection of Dissolved Inorganic Phosphorus in Seawater.

We present a methodology for the detection of dissolved inorganic phosphorous (DIP) in seawater using an electrochemically driven actuator-sensor system. The motivation for this work stems from the lack of tangible solutions for the in situ monitoring of nutrients in water systems. It does not require the addition of any reagents to the sample and works under mild polarization conditions, with the sample confined to a thin-layer compartment. Subsequent steps include the oxidation of polyaniline to lower the pH, the delivery of molybdate via a molybdenum electrode, and the formation of an electroactive phosphomolybdate complex from DIP species. The phosphomolybdate complex is ultimately detected by either cyclic voltammetry (CV) or square wave voltammetry (SWV). The combined release of protons and molybdate consistently results in a sample pH < 2 as well as a sufficient excess of molybdate, fulfilling the conditions required for the stoichiometric detection of DIP. The current of the voltammetric peak was found to be linearly related to DIP concentrations between 1 and 20 μM for CV and 0.1 and 20 μM for SWV, while also being selective against common silicate interference. The analytical application of the system was demonstrated by the validated characterization of five seawater samples, revealing an acceptable degree of difference compared to chromatography measurements. This work paves the way for the future DIP digitalization in environmental waters by in situ electrochemical probes with unprecedented spatial and temporal resolution. It is expected to provide real-time data on anthropogenic nutrient discharges as well as the improved monitoring of seawater restoration actions.

Spatial distribution and quantitative source identification of nutrients and beneficial elements in the soil of a typical suburban area, Beijing.

Source identification and quality monitoring of soil nutrients and beneficial elements (NBEs) are crucial for agricultural production and environmental protection. In this study, grid sampling (223 topsoil samples and 223 subsoil samples) was carried out in the Tongzhou District of Beijing. The concentration level of representative NBEs (N, P, K, Ca, Mg, Se, V, Ge, Mn, Zn) and some typical soil properties representing indicators (total organic carbon, TFe2O3, Al2O3/SiO2, and pH) in soils and their spatial distribution were analyzed. The major sources contributing to these NBEs were assessed by principal component analysis (PCA), redundancy analysis (RDA), and positive matrix factorization (PMF) analysis. The results suggested that the soil parent material contributed 40.09-69.84% to Zn, V, Ge, Mn, F, and K in soils; the local external source contributed 54.89-75.04% to N, Se, and TOC; and the hydrous system contributed 40.67-77.31% to Ca and Mg. The enrichment degree of each NBE was calculated using the standardized concentration ratio method. These indices exhibited the influence and mixing process of different sources on the target NBEs in topsoils. The individual concentrations of the target NBEs and the combined concentrations of N, P, and K were used to evaluate the soil quality. Our study estimated the relative contributions from dominant sources to NBEs in soils from a typical suburban area, providing a basis for agricultural activities and environmental protection.

Effects of filtration timing and pore size on measured nutrient concentrations in environmental water samples

AbstractNutrient monitoring is important for informing management decisions to mitigate eutrophication in aquatic systems. Many nutrient monitoring programs use filter pore sizes that allow microorganisms to pass into samples and/or wait extended times between sample collection and filtration/preservation, allowing microbial processes to alter nutrient concentrations. Here, 34 sites were sampled to determine how filter pore size and filtration timing affected measured ammonium (NH4+) and orthophosphate (ortho‐P) concentrations. Three filter pore sizes (0.22, 0.45, and 0.70 μm) were used to filter water immediately upon collection and after 5 and 22 h in a bottle. NH4+ and ortho‐P concentrations varied relative to “baseline” measurements (i.e., 0.22 μm, field‐filtered samples), both over time and with different filter pore sizes, and showed no predictable direction of change based on ambient nutrient concentration or trophic status. As expected, larger relative changes occurred with lower ambient concentrations; however, for the entire dataset, samples with &gt; 1 μmol L−1 ortho‐P and &gt; 3 μmol L−1 NH4+ were lower by 11 and 33%, respectively, which would result in reported nutrient concentrations that were not representative of in situ conditions. Whole‐water samples filtered after 22 h varied up to 3070% for NH4+ and 480% for ortho‐P from baseline concentrations. Filtering water samples with a 0.22 filter (or 0.45 μm, at worst), immediately upon collection, should be adopted as standard practice to ensure that reported nutrient concentrations represent the most accurate measurement possible. Inconsistent and/or insufficient sampling and sample handling procedures can lead to poorly calibrated models and misinformed management and legislative decisions.

Synchronous enhancement of electromagnetic and chemical effects-induced quantitative adsorptive detection of quercetin based on flexible polymer-silver-ZIF-67 SERS substrate

Surface-enhanced Raman scattering (SERS) is a prospective and ultrasensitive analytical technique because of its prominent molecular fingerprint diagnosis ability. Nonetheless, the tested molecules are typically required to be steadily attached onto a SERS-active region, which makes it tough to monitor feebly adsorbed molecules. In this study, a polydimethylsiloxane (PDMS)-based flexible SERS substrate combined with silver nanocubes (Ag NCs) and ZIF-67 was developed with a facile layer-by-layer strategy. A superhigh enhancement factor (EF) of 9.1 × 108 M was obtained by electromagnetic enhancement from the promising Ag NCs in conjunction with the molecular anchoring surface and chemical enhancement ability of ZIF-67. Furthermore, the practical SERS-based detection of quercetin with an ultra-low limit of detection (LOD) of 2.3 × 10−5 mg/mL was subsequently achieved utilizing this multifunctional substrate, indicating its intriguing outlook in the direct monitoring of food nutrients. Notably, the intrinsic Raman signal at 2905 cm−1 of PDMS framework was adequately utilized as an internal standard to promote the reliability of such detection. It is anticipated that this smart platform with both prominent SERS performance and quantitative test ability may find an extensive application in the domains of food and biochemical assay.