Critical Quality Parameters Research Articles

Association of greening bacterium with fruit morphological disorder ‘Waywar’ in monsoon cropping of Nagpur mandarin (Citrus reticulata Blanco) grown in central India

Abstract In the Vidarbha region of Maharashtra and the surrounding parts of central India, Waywar (citrus greening bacterium) fruit disorder, also known as wasteful fruit disorder, is a common manifestation of Nagpur mandarin fruit. In Vidarbha, the condition is also known as cock bund, while in China, it is called ‘Red Nose.’ According to early research, this condition is caused by abiotic stress factors, such as poor nutrition, too much moisture in the root zone, and other incorrect cultural practices. Recent research, however, has unequivocally shown that Candidatus Liberobacter asiaticus, the citrus greening bacterium, is responsible for this illness. When compared to normal growing fruits (0.82–0.89), the length to diameter ratio of Waywar fruits at the peak of incidence was reported in the range of 0.95–1.09, indicating their oblong shape. Premature Waywar fruits had higher acidity levels (1.75 to 2.04%) than normal fruits (1.65 to 2.03%) and produced seeds that were not viable. The cultural treatments applied to reduce the ill effects of the disorder improved the physico-chemical characteristics of Nagpur mandarin fruit at the time of harvesting. When compared to the untreated control, foliar spraying with growth regulators 2,4-D (15 ppm) and GA3 (15 ppm) enhanced the amount of fruit retained per plant at harvest. The critical fruit quality parameters like TSS (10.10%) and vitamin C (39.37 mg/100 ml) were highest in GA3 treated fruits. Maximum TSS/Acid ratio (14.00) and minimum acidity (0.69%) were noted with phosphorus applied at three times the RDF level at harvest.

Caracterización y Análisis de la Calidad del Agua en Entornos Urbanos mediante la implementación de un Sistema Embebido con Tecnología IoT

This study aims to characterize and analyze water quality in urban environments using an IoT embedded system, focusing on San Camilo’s community of Quevedo, Ecuador, where population growth has increased the demand for drinking water. An embedded system was designed to make use of a microcontroller and sensors to monitor critical water quality parameters in real time. The collected data is transmitted to a cloud platform for storage, analysis, and visualization. Spearman's correlation coefficient was preferred for statistical analysis of the data. This allowed for the identification of patterns and relationships between the variables examined. The data revealed significant associations in non-linear data, facilitating a decision regarding the development of predictive models for water management and treatment. The results demonstrate the feasibility and efficiency of using IoT technologies in the continuous monitoring of water quality, offering a scientific basis for the collection and processing of relevant data on the quality of drinking water in residential areas, providing a robust tool to monitor public health and the comfort of the inhabitants.

Internet of Things-Driven Precision in Fish Farming: A Deep Dive into Automated Temperature, Oxygen, and pH Regulation

The research introduces a revolutionary Internet of Things (IoT)-based system for fish farming, designed to significantly enhance efficiency and cost-effectiveness. By integrating the NodeMcu12E ESP8266 microcontroller, this system automates the management of critical water quality parameters such as pH, temperature, and oxygen levels, essential for fostering optimal fish growth conditions and minimizing mortality rates. The core of this innovation lies in its intelligent monitoring and control mechanism, which not only supports accelerated fish development but also ensures the robustness of the farming process through automated adjustments whenever the monitored parameters deviate from desired thresholds. This smart fish farming solution features an Arduino IoT cloud-based framework, offering a user-friendly web interface that enables fish farmers to remotely monitor and manage their operations from any global location. This aspect of the system emphasizes the importance of efficient information management and the transformation of sensor data into actionable insights, thereby reducing the need for constant human oversight and significantly increasing operational reliability. The autonomous functionality of the system is a key highlight, designed to persist in adjusting the environmental conditions within the fish farm until the optimal parameters are restored. This capability greatly diminishes the risks associated with manual monitoring and adjustments, allowing even those with limited expertise in aquaculture to achieve high levels of production efficiency and sustainability. By leveraging data-driven technologies and IoT innovations, this study not only addresses the immediate needs of the fish farming industry but also contributes to solving the broader global challenge of protein production. It presents a scalable and accessible approach to modern aquaculture, empowering stakeholders to maximize output and minimize risks associated with fish farming, thereby paving the way for a more sustainable and efficient future in the global food supply.

Real-time quality analysis of baked goods using advanced technologies

Some critical quality variables of baked goods baked in tunnel ovens cannot be monitored in real-time and quickly after baking. Generally, these variables are measured individually and manually. Analysis of some variables can be done in laboratory environments. It is very difficult to continuously and accurately read the quality variables of products, especially at the exits of industrial tunnel ovens operating at high speeds. With current systems, important quality variables of the products are assessed through widely spaced sampling, and most of the time the measurements made do not represent the entire batch. Additionally, interventions in the process may be delayed due to the time required for analysis, allowing defective products to reach consumers. In this study, experiments were carried out to enable real-time and high-speed identification of important quality variables such as product geometry, surface color, image features, and moisture. The developed system aims to monitor products such as cookies, cakes, biscuits, crackers and bread. Through this system, the size of the products that can represent the lot or even the entire batch can be analyzed when desired. Thus, quality oscillations can be kept within very narrow ranges. The developed hybrid system is applied to the exit of tunnel ovens, and the data read through sensors and cameras are transferred to computers using specially developed algorithms through interfaces. It has been observed that process control signals can also be generated by considering the lower and upper control limits of quality variables. With the developed software, changes can be instantly seen on the screens in the form of graphics, audio, and visual warnings can be created, historical data can be recorded, and reports can be obtained. At the end of the study, it was found that important quality variables such as circularity, diameter, thickness, color, image area, and moisture could be read with a sample size of up to 100%. As a result of the experiments, it was seen that the change in product diameters could be defined within the range of 40.30±0.5 mm. The circularity ratio between horizontal and vertical diameters can be monitored within 1.008 ± 0.018%. The change in moisture within the range of 2.741±0.164 g/100g. The light-dark image area ratios within the range of 0.486±0.033%, and the product thickness within the range of 11.56±0.178 mm. Resultly, all critical quality parameters taken into account can be detected within a range that will not affect product and process quality.

Variability of bio-optical properties of Sundarbans mangrove estuarine ecosystem using elemental analysis, Sentinel 3 OLCI imageries and neural network models

Coastal water bodies face significant contamination risks stemming from various factors, such as growing populations, rapid urban development, dam construction, heightened industrial operations (notably in ports), and increasing tourism activities. The release of untreated sewage from municipalities, industrial discharges, and various recreational and commercial activities along the coast significantly deteriorates water quality and presents a serious risk to marine ecosystems, food chains, and human health. Hence, continual monitoring of coastal water quality is essential for the ecological sustainability of marine and aquatic ecosystems. This study examines the spatiotemporal variability of optical characteristics within the Sundarbans estuary system, a transboundary ecosystem shared by India and Bangladesh. The study employs Sentinel-3 OLCI satellite data alongside in-situ measurements of critical water quality parameters, including chlorophyll-a (Chl-a), total suspended matter (TSM), and chromophoric dissolved organic matter (CDOM), collected from 100 sampling sites across the Sundarbans estuarine system during the pre-monsoon, monsoon, and post-monsoon periods of 2021 and 2022.This study employs the sophisticated C2RCC model, a machine learning-based neural network-driven approach recognized for its robustness and precision. It examines the various bio-optical properties in tropical estuarine environments. The C2RCC model addresses this challenge directly. This advanced processor, powered by neural network technology, effectively interprets the complex optical signals found in Case-2 waters, offering essential insights into their quality. The findings indicate the highest TSM levels during the pre-monsoon seasons of both years. Additionally, the estimated Chl-a concentrations indicated a rise during the monsoon season (0.03–4 mg m3), whereas the intensified pre-monsoon CDOM levels showed consistency across both years. The strong positive correlation observed between in-situ and satellite data, with an average R2 value ranging from 0.90 to 0.99, underscores the reliability of the high-resolution remote sensing approach. The study illustrates the efficacy of OLCI data in observing near-shore and coastal ecosystems, clearly exceeding conventional methods for evaluating Chl-a, TSM, and CDOM. This study underscores the potential of high spatial and spectral resolution of Sentinel-3 Ocean color data for effective monitoring and management of the complex estuarine ecosystem of the Sundarbans. The findings of this study provide important insights to inform the development of sustainable coastal water resource management strategies. Furthermore, the findings will be crucial in achieving Sustainable Development Goal 14, which focuses on life below water, particularly in the conservation and management of marine and coastal biodiversity.

Integrating deep learning techniques for effective river water quality monitoring and management

Effective river water quality monitoring is essential for sustainable water resource management. In this study, we established a comprehensive monitoring system along the Kaveri River, capturing real-time data on multiple critical water quality parameters. The parameters collected encompassed water contamination levels, turbidity, pH measurements, temperature, and total dissolved solids (TDS), providing a holistic view of river water quality. The monitoring system was meticulously set up with strategically positioned sensors at various river locations, ensuring data collection at regular 5-min intervals. This data was then transmitted to a cloud-based web portal, facilitating storage and analysis. To assess water quality, we introduced a novel hybrid approach, combining Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks. The proposed CNN-LSTM model achieved a validation accuracy of 98.40%, surpassing the performance of other state-of-the-art methods. Notably, the practical application of this system includes real-time alerts, promptly notifying stakeholders when water quality parameters exceed predefined thresholds. This feature aids in making informed decisions in water resource management. The study's contributions lie in its effective river water quality monitoring system, which encompassing various parameters, and its potential to positively impact environmental conservation efforts by providing a valuable tool for informed decision-making and timely interventions.

Urbanization and Suspended Sediment Transport Dynamics: A Comparative Study of Watersheds with Varying Degree of Urbanization Using Concentration-Discharge Hysteresis.

Suspended sediment is a critical water quality parameter and an indicator of geomorphic processes, but suspended sediment dynamics in urban streams may not conform to the first-flush model widely used for other pollutants. We analyzed discharge and turbidity data for 367 events from three urban watersheds (impervious cover 16-45%) in Cleveland, Ohio (USA). Less intensely urbanized watersheds exhibit higher turbidity compared to that of the most highly urbanized watershed. Proportionally, more counterclockwise hysteresis is observed in the two less urbanized watersheds, and more clockwise hysteresis occurs in the highly urbanized watershed. However, hysteresis patterns are driven by different mechanisms in each watershed, and geomorphic analysis was critical to identifying the underlying mechanisms. In the least urbanized watershed, spatial rainfall variability controls sediment hysteresis. In the intermediate watershed, the erosion of upstream weathered shale banks during dry periods plays a significant role in the sediment supply and shaping hysteresis. In the most urbanized watershed, high eroding banks in downstream reaches lead to more frequent clockwise hysteresis. Overall, we suggest that as the impervious surfaces increase, the availability of instream sediments (bed and banks) plays an increased role in suspended sediment dynamics, and geomorphology remains essential for guiding management decisions.

Physicochemical and sensory quality of high antioxidant fruit leather of red dragon fruit and watermelon rind enriched with seaweed

Fruit, as a source of antioxidants and phenolic compounds, is perishable. It also has an underutilized component. Fruit leather has a long shelf life in the form of thin sheets with a distinctive texture. This study aimed to investigate the effect of seaweed (Eucheuma cottonii) addition on the physicochemical and sensory quality of fruit leather made from the combination of red dragon fruit and watermelon rind. The physicochemical quality was characterized by measuring the critical quality parameters of fruit leathers, including proximate analysis, water activity, total phenol, antioxidant activity, texture, and organoleptic analysis. The statistical analysis of phenolic compound activity, antioxidant activity, vitamin C, moisture content, carbohydrates, and water activity (aw) was conducted using a one-way ANOVA test, while the analysis of ash content, protein, fat, tensile strength, elongation, and organoleptic properties was performed using the Kruskal–Wallis test. Increasing seaweed concentration significantly increased moisture, ash, protein, vitamin C, total phenol, water activity, and elongation but decreased fat content. Furthermore, the increase in seaweed concentration reduced liking toward taste and color significantly but increased texture liking. The best product was the F2 product with 10% seaweed. F2 has the following attributes: 11.07% of moisture content, 2.34% of ash, 1.53% of protein, 0.19% of fat, 84.86% of carbohydrate, 8.17 mg/100 g of vitamin C, 0.41 of water activity, 0.54 N/m2 of tensile strength, 22.22% of elongation, 107.39 ppm of IC50, 1.66 mg/GAE g of total phenolics.

Comparative Effect of Fish Feeds on the Initial Growth and Survival Rate of Juvenile Redbreast Tilapia (Coptodon rendalli) under Early Hatchery Conditions

This study compared the effects of three supplementary diets—egg yolk, Artemia, and commercial pellets with 48% crude protein—on the growth performance and survival rate of redbreast tilapia (Coptodon rendalli) under intensive culture conditions at the Kamutjonga Inland Fisheries Institute in the Kavango East region of Namibia. The study was conducted from December 2023 to January 2024 using a complete randomized design replicated thrice. Results showed that fish fed with commercial pellets exhibited the highest specific growth rate (1.39 ± 0.80%) compared to egg yolk (0.94 ± 0.54%) and Artemia (0.33 ± 0.19%). Commercial pellets also had the best survival rate (76.19 ± 43.099), compared to egg yolk and Artemia (70.47 ± 40.69; 33 ± 19.05), respectively. However, egg yolk had the best feed conversion ratio (0.20 ± 0.05) compared to the commercial pellets (0.22 ± 0.04) and Artemia (0.26 ± 0.07). Critical water quality parameters were maintained within acceptable survival ranges for C. rendalli across all treatments. These findings highlight the importance of dietary protein content in optimizing the growth and survival of C. rendalli under intensive culture conditions and provide insights for effective feeding strategies. However, commercial pellets are expensive and inaccessible to small-scale fish farmers. As an alternative, egg yolk emerged as a viable and affordable feed option, promoting fish growth and supporting the establishment of small-scale farming practices in the region.

Development of radio frequency drying protocols for preserving the color and fragrance of lotus bee pollen

This investigation delves into radio frequency (RF) drying as a novel approach for preserving the inherent quality and extending shelf life of lotus bee pollen, a primary agricultural product enriched with essential nutrients and bioactive compounds. Through a comparative analysis with conventional hot air (HA) drying conducted at 50 °C, 55 °C, and 60 °C, this study evaluated the impact of both drying techniques on critical quality parameters of bee pollen. These parameters included moisture content, fatty acid profile, color, aroma characteristics, pigment concentrations, and malondialdehyde levels. Findings revealed that RF drying significantly reduced drying time while maintaining superior quality attributes of bee pollen, such as enhanced color retention (ΔE < 5) and diminished lipid oxidation, in comparison to HA drying. Notably, RF drying at 55 °C for 130 min emerged as the optimum condition for preserving the sensory and nutritional qualities of lotus bee pollen. The study underscores the potential of RF drying as an efficient and quality-preserving method that could be advantageous for commercial applications in food industry, aiming at enhancing shelf life and safety of bee pollen.

Optimization of thermosonication conditions for critical quality parameters of watermelon juice using response surface methodology

Topical consumer interest in natural, healthier, safer and nutritional juice, has inspired the search for innovative technologies that can minimize product degradation. In this regard, thermosonication has been proposed as a potential processing technology that can preserve and produce “fresh” products. Watermelon (Citrulluslanatus) juice is a nutrient-rich fruit juice that is desired by consumers due to its appealing color, pleasant odor, sweet taste and low-calorie content. This fruit juice is, however, highly perishable and prone to microorganisms, because of its neutral pH value and high amount of water activity. In addition, it is thermo-sensitive and therefore degrades quickly under thermal processing. This study aimed to identify the optimal thermosonication processing conditions for retaining the critical quality parameters (lycopene, β-carotene, ascorbic acid and total polyphenolic content) of watermelon juice. Response surface methodology, employing a central composite design, was used to determine the effects of temperature (18–52 °C), processing time (2–13 min) and amplitude level (24–73 μm) at a constant frequency of 25 kHz. The highest quality parameters were obtained at 25 °C, 2 min, and 24 µm at a constant frequency of 25 kHz, which resulted in lycopene of 8.10 mg/100 g, β-carotene of 0.19 mg/100 g, ascorbic acid of 3.11 mg/100 g and total polyphenolic content of 23.96 mg/GAE/g with a desirability of 0.81. The proposed model was adequate (p < 0.0001), with a satisfactory determination coefficient (R2) of less than 0.8 for all phytochemicals. Thermosonicated watermelon juice samples showed minimal changes in their phytochemical properties, when compared to fresh juices; the lycopene content showed a significant increase after thermosonication, and a significant retention of β-carotene, ascorbic acid and total polyphenolic acid was observed. According to the findings, thermosonication could be a viable method for preserving watermelon juice, with minimal quality loss and improved functional attributes.

Multistimuli responsive microcapsules produced by the prilling/vibration technique for targeted colonic delivery of probiotics

This study aimed to microencapsulate the probiotic strain Lactiplantibacillus plantarum 4S6R (basonym Lactobacillus plantarum) in both microcapsules and microspheres by prilling/vibration technique. A specific polymeric mixture, selected for its responsiveness to parallel colonic stimuli, was individuated as a carrier of microparticles. Although the microspheres were consistent with some critical quality parameters, they showed a low encapsulation efficiency and were discarded. The microcapsules produced demonstrated high yields (97.52%) and encapsulation efficiencies (90.06%), with dimensional analysis and SEM studies confirming the desired size morphology and structure. The results of thermal stress tests indicate the ability of the microcapsules to protect the probiotic. Stability studies showed a significant advantage of the microcapsules over non-encapsulated probiotics, with greater stability over time. The release study under simulated gastrointestinal conditions demonstrated the ability of the microcapsules to protect the probiotics from gastric acid and bile salts, ensuring their viability. Examination in a simulated faecal medium revealed the ability of the microcapsules to release the bacteria into the colon, enhancing their beneficial impact on gut health. This research suggests that the selected mixture of reactive polymers holds promise for improving the survival and efficacy of probiotics in the gastrointestinal tract, paving the way for the development of advanced probiotic products.

A Human Skin Explant Test as a Novel In Vitro Assay for the Detection of Skin Sensitization to Aggregated Monoclonal Antibodies.

Introduction: Monoclonal antibodies (mAbs) are important therapeutics. However, the enhanced potential for aggregation has become a critical quality parameter during the production of mAbs. Furthermore, mAb aggregation may also present a potential health risk in a clinical setting during the administration of mAb therapeutics to patients. While the extent of immunotoxicity in patient populations is uncertain, reports show it can lead to immune responses via cell activation and cytokine release. In this study, an autologous in vitro skin test designed to predict adverse immune events, including skin sensitization, was used as a novel assay for the assessment of immunotoxicity caused by mAb aggregation. Material and Methods: Aggregation of mAbs was induced by a heat stress protocol, followed by characterization of protein content by analytical ultra-centrifugation and transmission electron microscopy, revealing a 4% aggregation level of total protein content. Immunotoxicity and potential skin sensitization caused by the aggregates, were then tested in a skin explant assay. Results: Aggregated Herceptin and Rituximab caused skin sensitization, as shown by histopathological damage (grade II-III positive response) together with positive staining for Heat Shock Protein 70 (HSP70). Changes in T cell proliferation were not observed. Cytokine analysis revealed a significant increase of IL-10 for the most extreme condition of aggregation (65 °C at pH3) and a trend for an overall increase of IFN-γ, especially in response to Rituximab. Conclusions: The skin explant assay demonstrated that aggregated mAbs showed adverse immune reactions, as demonstrated as skin sensitization, with histopathological grades II-III. The assay may, therefore, be a novel tool for assessing immunotoxicity and skin sensitization caused by mAb aggregation.

Monitoring 36-year water clarity dynamics in turbid waters of the Pearl River Estuary, China, using Landsat data

Water clarity, commonly determined by Secchi disk depth (SDD), is a critical water quality parameter for assessing estuarine ecosystems heath. Since the 1980s, significant changes in SDD have been observed in the Pearl River Estuary (PRE), a robust, economical, and densely populated estuary in southern China. However, its long-term patterns and associated drivers have not yet been systematically investigated. In this study, three novel semi-analytical algorithms suitable for Landsat 5, 7, and 8 images were applied to 36-year (1987–2022) Landsat series data to explored the spatiotemporal heterogeneity of SDD in the PRE. The results indicated that the proposed SDD estimation algorithms yielded well-accepted performances and few errors, with mean absolute percentage errors <27% and root mean square errors <0.105 m. Spatially, the SDDs in the Western regions of the PRE (0.25 ± 0.1 m) were significantly lower than that in the Open areas (0.55 ± 0.15 m). In addition, the SDD showed an overall increasing trend from 1987 to 2022 with a rate of 0.032 m/y over the entire area, indicating gradually improved water quality in the PRE, owing to the less anthropogenic perturbations and landscape change. This research not only produces a 36-year historical SDD dataset for estuarine areas, but also imparts new insights into the complex mechanisms involved in watershed management.

Quality assessment of metformin hydrochloride tablets retailed in Lagos, Nigeria

Background: Metformin is a biguanide antihyperglycemic drug used with diet and exercise for glycemic control in type 2 diabetes mellitus.Objectives: This research aims to compare and analyze different metformin products to ascertain their critical quality parameters. The goal is to ensure that prescribed medicine effectively treats patients and protects the public.Materials and Methods: We evaluated the quality of ten metformin tablet brands in Lagos (Mushin and Surulere area) using official methods to assess weight, hardness, friability, disintegration time, and dissolution. Active ingredient content was also measured.Results: Out of all the tablets tested, only 10 % had weights outside of the official British Pharmacopoeia 2002 limits (not more than two tablets should deviate from ±5% and none of the tablets should deviate by ± I0). The hardness test was passed by all the tablets (A minimum hardness of 4 kgF is a pass), while 80 % passed the friability test (weight loss of ≤ 1 %w/w is a pass). Additionally, all film-coated tablets disintegrated within 30 minutes according to United States Pharmacopoeia/National Formulary 2003 (film-coated tablets disintegrate within 30 minutes). Ninety percent of the tablets passed the dissolution test (drug release within 60 minutes should be between 93 and 103 %) and 90 % of all brands examined passed the assay test for the active ingredient contents. The British Pharmacopoeia 2019 standard was used for the dissolution test.Conclusion: Routine pharmaceutical analysis is essential for the quality of pharmaceutical products and the safety of consumers.

Improving Fish Quality and Yield: An Automated Monitoring System for Intensive Aquaculture

The growing interest in the fish farming industry is driven by the depletion of natural fish stocks in the market. However, intensive aquaculture systems, which involve raising fish in artificial tanks and cages, can lead to challenges such as low-quality fish and increased mortality rates, depending on the species being cultivated. To address these issues and maximize yield, this paper proposes a fish quality monitoring system with automatic correction. The system focuses on monitoring and maintaining critical water quality parameters essential for fish growth, including temperature, water level, and pH level. The system comprises an Arduino connected to sensors and a web-based application for data collection and monitoring. Correction devices such as an aquarium heater, a valve, and a water pump are integrated into the system to maintain these parameters at optimal levels for fish development. To assess the system's efficiency and reliability, two fish monitoring setups were compared: one using the proposed controlled system and the other using a traditional setup. Results indicate that the controlled system increased efficiency, reduced stress on fish farmers, decreased fish mortality rates, and improved product quality compared to the traditional setup.

Application of the Field Hyperspectral Sensing to Estimate the Oxidation-Reduction Potential (ORP) in Tropical Urban Waters

Oxidation-reduction potential (ORP) is one of the critical water quality parameters used in determining the biochemical condition of water, especially in wastewater treatment. Conventional measurement of ORP requires physical contact with the water samples. A relative version of the ORP measurement that is faster and requires non-contact with the water can be helpful, especially for environmental monitoring. One way to perform this is by measuring the radiated electromagnetic wave from water bodies such as drainage, rivers, and streams that are exposed to sunlight. The reflected radiation from various water samples was obtained using a handheld hyperspectral sensor that is sensitive to 350 – 250 nm radiation and the ORP measurement was performed using the water quality probes sensor equipped with the ORP sensor. Forty-four water samples were taken from multiple locations, including rivers, tributaries, drainage, and streams. Our analysis revealed that the wave spectra at 654 nm can estimate ORP values ranging from 0 to 500 with moderate performance (R² = 0.581). The reflectance spectra need to undergo normalization, and the second derivative filtering of the Savitsky-Golay is required to obtain such desired results. This preliminary experiment demonstrated that the ORP estimation is plausible using the hyperspectral remote sensor with moderate accuracy for water that potentially experiences nitrification, denitrification, carbonaceous biochemical oxygen demand, and phosphorus waste.

Enhanced Water Quality Prediction in the Yellow River Basin: The Application of the HHO-LSTM Model

In the pivotal water resource region of the Yellow River Basin in China, precise prediction of water resources is essential for their effective and rational management. This study introduces a novel approach to water resource prediction by employing the Harris Hawks Optimization-Long Short-Term Memory (HHO-LSTM) model. This method overcomes the constraints faced by traditional techniques in processing time series data and various variable factors. It encompasses a comprehensive description of the multi-source hydrological data collection process within the Yellow River Basin, followed by meticulous data preprocessing. The data set for this study includes estimates of four critical water quality parameters, and the efficacy of the model is gauged through the mean squared error (MSE) and root mean squared error (RMSE) metrics. This facilitates the projection of future water quality trends in specific areas by leveraging historical water quality data. The HHO-LSTM model has demonstrated outstanding accuracy and robustness in predicting water quality across diverse temporal scales and water resource variables, marking a significant advancement in water resource management within the Yellow River Basin. This approach not only enhances current management strategies but also contributes valuable insights for ongoing water resource research and decision-making processes.

Predicting and analyzing the algal population dynamics of a grass-type lake with explainable machine learning

Algal blooms, exacerbated by climate change and eutrophication, have emerged as a global concern. In this study, we introduce a novel interpretable machine learning (ML) workflow tailored for investigating the dynamics of algal populations in grass-type lakes, Liangzi lake. Utilizing seven ML methods and incorporating the covariance matrix adaptation evolution strategy (CMA-ES), we predict algal density across three distinct time periods, resulting in the construction of a total of 30 ML models. The CMA-ES-CatBoost model consistently demonstrates superior predictive accuracy and generalization capability across these periods. Through the collective validation of various interpretable tools, we identify water temperature and permanganate index as the two most critical water quality parameters (WQIs) influencing algal density in Liangzi Lake. Additionally, we quantify the independent and interactive effects of WQIs on algal density, pinpointing key thresholds and trends. Furthermore, we determine the minimum combination of WQIs that achieves near-optimal predictive performance, striking a balance between accuracy and cost-effectiveness. These findings offer a scientific and economically efficient foundation for governmental agencies to formulate strategies for water quality management and sustainable development.

Calibration Techniques for Water Content Measurements in Solid Biofuels

This paper presents methodologies and equipment for SI-traceable inline measurements of water content (a critical quality parameter) in solid biofuels. Inline measurement systems for water content are commonly used at CHP plants, providing continuous real-time data. However, the accuracy of these systems is in most cases unsatisfactory, mainly because the systems are not calibrated representatively for the relevant material, and until now, calibrations traceable to the SI system have not been available. To provide reliable and accurate inline water content data, new procedures and equipment for calibrating measurement systems were developed. Two reference methods for the determination of water content were developed; one measures the airflow and dewpoint of desorbed water in the air passing a test sample, while the other uses a P2O₅-sensor. Additionally, a transfer standard based on a cavity resonance sensor was developed for fast onsite calibration of the inline sensor at the power plant. This new instrument allows for quick and accurate measurements. The transfer standard is made metrologically traceable to the primary measurement standards. The entire system was demonstrated by calibrating an inline microwave-based (MW) sensor at the CHP plant of VERDO in Randers, Denmark. Thus, a complete metrological traceability chain was established from an industrial to a primary standard.