Research progress of inland river water quality monitoring technology based on unmanned aerial vehicle hyperspectral imaging technology.

In recent years, increasing demand for inland river water quality precision management has heightened the necessity for real-time, rapid, and continuous monitoring of water conditions. By analyzing the optical properties of water bodies remotely, unmanned aerial vehicle (UAV) hyperspectral imaging technology can assess water quality without direct contact, presenting a novel method for monitoring river conditions. However, there are currently some challenges to this technology that limit the promotion application of this technology, such as underdeveloped sensor calibration, atmospheric correction algorithms, and limitations in modeling non-water color parameters. This article evaluates the advantages and disadvantages of traditional sensor calibration methods and considers factors like sensor aging and adverse weather conditions that impact calibration accuracy. It suggests that future improvements should target hardware enhancements, refining models, and mitigating external interferences to ensure precise spectral data acquisition. Furthermore, the article summarizes the limitations of various traditional atmospheric correction methods, such as complex computational requirements and the need for multiple atmospheric parameters. It discusses the evolving trends in this technology and proposes streamlining atmospheric correction processes by simplifying input parameters and establishing adaptable correction algorithms. Simplifying these processes could significantly enhance the accuracy and feasibility of atmospheric correction. To address issues with the transferability of water quality inversion models regarding non-water color parameters and varying hydrological conditions, the article recommends exploring the physical relationships between spectral irradiance, solar zenith angle, and interactions with water constituents. By understanding these relationships, more accurate and transferable inversion models can be developed, improving the overall effectiveness of water quality assessment. By leveraging the sensitivity and versatility of hyperspectral sensors and integrating interdisciplinary approaches, a comprehensive database for water quality assessment can be established. This database enables rapid, real-time monitoring of non-water color parameters which offers valuable insights for the precision management of inland river water quality.

Assessing groundwater quality dynamics in Madhya Pradesh: Chemical contaminants and their temporal patterns.

Groundwater is essential for maintaining ecosystem health and overall well-being as a pivotal resource for plants and animals. The increasing public consciousness of the deterioration of groundwater quality has emphasized the significance of undertaking extended evaluations of groundwater water quality, particularly in regions undergoing substantial hydrological alterations. This study primarily aims to investigate the spatio-temporal variations in groundwater quality and evaluate its suitability for potable purposes in the region of Madhya Pradesh. The study combines the Mann-Kendall (MK) test and Sen's Slope (SS) to analyze the changes in groundwater quality of all 51 districts of Madhya Pradesh, India, utilizing 12 water quality indices using MATLAB. Data was sourced from the Central Ground Water Board (CGWB) in India from the year 2001-2021. The data was then tested for homogeneity at all 1154 sampling stations using the software XLSTAT. Piper plot clustering characterized the state's groundwater as bicarbonate-calcium-magnesium (HCO3--Ca2+-Mg2+) type. The study found that the groundwater in the area is heavily impacted by high levels of nitrate and hardness, which is caused by an increase in multivalent cations. The water was classified as ranging from hard to extremely hard, and approximately 25.49% of the state's groundwater has nitrate levels that exceed the acceptable limits. The MK test showed a significant increasing correlation in trends for parameters such as nitrate, sulfate, fluoride, chloride, bicarbonate, total hardness, and electrical conductivity. It also showed a significant decreasing correlation for calcium, magnesium, potassium, and sodium. These results were observed at a confidence level of 95%. The analysis of trends has shown that human-related factors have a considerable effect on the characteristics of groundwater quality. It is therefore recommended that such human-related factors be taken into consideration when developing policies for managing groundwater resources. Consequently, these policies should emphasize the strict enforcement of rules and standards that limit the overuse of fertilizers, ensure the appropriate disposal of municipal solid and liquid wastes, and regulate industrial pollutants.

Comprehensive river water quality monitoring using convolutional neural networks and gated recurrent units: A case study along the Vaigai River.

Effective monitoring of river water quality is required for long-term water resource management. Convolutional Neural Networks and Gated Recurrent Unit-based water quality monitoring (CNGRU-WQM) were used in this investigation to develop a comprehensive monitoring system along the Vaigai River. The system was designed to collect real-time data on several crucial water quality parameters. The collected characteristics encompassed factors like water pollution levels, turbidity, pH readings, temperature, and total dissolved solids, offering a comprehensive view of river water quality. The monitoring system was methodically set up, with sensors strategically positioned at various locations along the river. This ensured that data collection would take place at regular intervals. The CNGRU-WQM model achieved a validation accuracy of 97.86%, surpassing the performance of other state-of-the-art approaches. Particularly noteworthy is the fact that the actual use of this system incorporates real-time warnings, which enable stakeholders to be instantly informed if water quality measurements surpass pre-set criteria. The study's contributions include its efficient river water quality monitoring system, which encompasses a variety of indicators, and its ability to significantly affect environmental conservation efforts by offering a helpful tool for informed decision-making and timely interventions.

Evaluation of the Shelf Life of Myristica-fragrans Powder-Flavored Oils Obtained through the Application of Two Processes: Infusion and Co-Pressing Technology.

This work aimed to evaluate the impact of enrichment processing on the quality parameters, bioactivity and sensorial aspects of Myristica fragrans (mace)-flavored olive oil storage for one year. The mace powder was added to extra virgin olive oil through two different processes: immediately after crushing the olives by mixing mace (1% weight/weight (w/w)) with the olive paste (MAVOO-M) and by adding mace to extra virgin olive oil (C) (2% w/w) (MAVOO-I). A multi-analytical approach was applied to measure the main qualitative indexes, such as the free acidity, peroxide value and ultraviolet parameters. The total phenolic and carotenoid contents (TPC and TCC, respectively) and α-tocopherol were also evaluated, as well as the sensory attributes. The radical scavenging potential was estimated by using two different in vitro tests, namely, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH). A significant increase in the free acidity parameter was found in all the flavored oils, and particularly in the MAVOO-M (1.27% oleic acid); at the same time, this oil was the sample with the lowest peroxide value (i.e., 9.68 meqO2/kg) after 360 days of storage. At the end of the storage, an increase in L* values was found in both the MAVOO-M and -I vs. the C (43.88 and 43.02, respectively, vs. 42.62). The TCC was strongly influenced by the addition of mace, especially when the infusion process was used. In fact, after one year of storage, the TCC in the MAVOO-I resulted in ~34.7% more than the MAVOO-M. A promising DPPH radical scavenging activity was observed independently by the applied aromatization process, with IC50 values of 19.77 and 17.80 µg/mL for the MAVOO-M and MAVOO-I, respectively. However, this activity decreased during storage, and a similar trend was observed using the ABTS test. In conclusion the infusion as enrichment methodology led to more promising results in terms of functionality compared with the co-mixing one.

Dynamics of antimicrobial resistance and susceptibility profile in full-scale hospital wastewater treatment plants.

Drug resistance has become a matter of great concern, with many bacteria now resist multiple antibiotics. This study depicts the occurrence of antibiotic-resistant bacteria (ARB) and resistance patterns in five full-scale hospital wastewater treatment plants (WWTPs). Samples of raw influent wastewater, as well as pre- and post-disinfected effluents, were monitored for targeted ARB and resistance genes in September 2022 and February 2023. Shifts in resistance profiles of Escherichia coli, Pseudomonas aeruginosa, and Acinetobacter baumannii antimicrobial-resistant indicators in the treated effluent compared to that in the raw wastewater were also worked out. Ceftazidime (6.78 × 105 CFU/mL) and cefotaxime (6.14 × 105 CFU/mL) resistant species showed the highest concentrations followed by ciprofloxacin (6.29 × 104 CFU/mL), and gentamicin (4.88 × 104 CFU/mL), in raw influent respectively. WWTP-D employing a combination of biological treatment and coagulation/clarification for wastewater decontamination showed promising results for reducing ARB emissions from wastewater. Relationships between treated effluent quality parameters and ARB loadings showed that high BOD5 and nitrate levels were possibly contributing to the persistence and/or selection of ARBs in WWTPs. Furthermore, antimicrobial susceptibility tests of targeted species revealed dynamic shifts in resistance profiles through treatment processes, highlighting the potential for ARB and ARGs in hospital wastewater to persist or amplify during treatment.

Reactive Blue MEBF 222 dye and textile wastewater treatment using metal-doped cobalt and nickel perovskites by batch and column adsorption process.

Water contamination is a serious issue that has an impact on the whole globe. In the current work, adsorption technique was used to remove synthetic Reactive Blue MEBF 222 textile dye utilizing Cd-doped Co (Co1 - xCd1.5xFeO3), Zn-doped Co (Co1 - xZn1.5xFeO3), Cr-doped Co (Co1 - xCr1.5xFeO3), Zn-doped Ni (Ni1 - xZn1.5xFeO3), and Cr-doped Ni (Ni1 - xCr1.5xFeO3) perovskites, synthesized by sol-gel auto-combustion approach. According to the findings of batch adsorption studies, maximum adsorption was observed at pH 3 (45.62 mg/g), 0.01 g/50 ml dosage (36.67 mg/g), 60 min (14.31 mg/g), 100 ppm dye concentration (47.41 mg/g), and 308 K (35.96 mg/g) for Co1 - xCd1.5xFeO3; at 3 pH (42.94 mg/g), 0.01 g/50 ml dosage (35.33 mg/g), 60 min (12.88 mg/g), 100 ppm dye concentration (40.52 mg/g), and 308 K (31.31 mg/g) for Co1 - xZn1.5xFeO3; at 2 pH (38.82 mg/g), 0.01 g/50 ml dosage (32.20 mg/g), 60 min (11.98 mg/g), 100 ppm dye concentration (33.54 mg/g), and 308 K (29.34 mg/g) for Co1 - xCr1.5xFeO3; at 2 pH (34.97 mg/g), 0.01 g/50 ml dosage (30.41 mg/g), 60 min (10.46 mg/g), 100 ppm dye concentration (27.19 mg/g), and 308 K (26.12 mg/g) for Ni1 - xZn1.5xFeO3; and at 2 pH (31.22 mg/g), 0.01 g/50 ml dosage (25.04 mg/g), 60 min (9.48 mg/g), 100 ppm dye concentration (21.73 mg/g), and 308 K (23.61 mg/g) for Ni1 - xCr1.5xFeO3. The pseudo-second-order model showed good fitness for adsorption kinetic data. Electrolytes, detergents/surfactants, and heavy metal ions had a substantial impact on the adsorption potential. The column adsorption experiments demonstrated optimal bed height, flow rate, and intake dye concentration to be 3 cm, 1.8 ml/min, and 70 mg/l, respectively, in the column experiment. With an adsorption capacity of 44.1 mg/g, reactive blue (RB) 222 dye was able to achieve its maximum adsorption. Detailed desorption of RB 222 dye was also achieved. The novelty of this adsorption method lies in its eco-friendliness, ease of handling, and cost-effectiveness.

Monitoring of rainwater quality in Kandy and Peradeniya, Sri Lanka.

The composition of atmospheric deposition is a measure of air quality, an important aspect of the health of the ecosystem. Consequently, continuous monitoring of atmospheric deposition is crucial to obtain remedial measures to avoid undesirable aspects that would affect living things. In this context, the objective of this study was to determine the rainwater quality at selected locations in Kandy and Peradeniya area of Sri Lanka, namely, Kandy, Polgolla, and University of Peradeniya (UOP), and to identify possible correlations between quality parameters through statistical means. Forty (40) rainwater samples from the UOP site and seven (07) samples each from the Kandy and Polgolla sites were collected from 18 May 2020 to 28 April 2021. The volume-weighted average (VWA) pH values of UOP, Kandy, and Polgolla sites were determined to be 7.44, 7.19, and 7.19, respectively, and moreover, acid rain (pH < 5.6) occurrences were not detected during the sampling period. The VWA values of rainfall, conductivity, salinity, TDS, and hardness at the UOP site were 40.12 mm, 51.93 µS cm-1, 0.0300 ppt, 26.59 mg L-1, and 13.55 mg L-1, respectively. The corresponding values of the Kandy site were 16.52 mm, 64.04 µS cm-1, 0.0361 ppt, 30.80 mg L-1, and 19.49 mg L-1, respectively; and those of the Polgolla site were 33.10 mm, 53.90 µS cm-1, 0.0310 ppt, 25.76 mg L-1, and 19.31 mg L-1, respectively. The VWA values of conductivity, salinity, and TDS were the highest at the Kandy site. Further, the VWA values of hardness at Kandy and Polgolla sites were approximately equal, probably due to the spring of Ca2+ and Mg2+ particulates from the dolomite quarry located in Digana area. The most prominent anion was identified as Cl- in bulk deposition at all three sites, while NO3- showed the lowest concentration of all sites. Moreover, very strong significant positive correlations were identified between conductivity-TDS, conductivity-salinity, conductivity-hardness, TDS-hardness, TDS-salinity, salinity-hardness, SO42--Cl-, and NO3--Cl- according to the relevant Pearson correlation coefficients. It is thus concluded that the pollutants come from the same sources, either natural or anthropogenic.

Exogenous Metals Atlas in Spermatozoa at Single-Cell Resolution in Relation to Human Semen Quality.

While exogenous metal/metalloid (metal) exposure has been associated with reduced human semen quality, no study has assessed the associations of exogenous metals in human spermatozoa with semen quality. Here, we developed a strategy to explore the associations between exogenous metals in spermatozoa at single-cell resolution and human semen quality among 84 men screened as sperm donors, who provided 266 semen samples within 90 days. A cellular atlas of exogenous metals at the single-cell level was created with mass cytometry (CyTOF) technology, which concurrently displayed 18 metals in more than 50 000 single sperm. Exogenous metals in spermatozoa at single-cell resolution were extremely heterogeneous and diverse. Further analysis using multivariable linear regression and linear mixed-effects models revealed that the heterogeneity and prevalence of the exogenous metals at single-cell resolution were associated with semen quality. The heterogeneity of lead (Pb), tin (Sn), yttrium (Y), and zirconium (Zr) was negatively associated with sperm concentration and count, while their prevalence showed positive associations. These findings revealed that the heterogeneous properties of exogenous metals in spermatozoa were associated with human semen quality, highlighting the importance of assessing exogenous metals in spermatozoa at single-cell resolution to evaluate male reproductive health risk precisely.

A spectral learning path for simultaneous multi-parameter detection of water quality.

Water quality parameters (WQP) are the most intuitive indicators of the environmental quality of water body. Due to the complexity and variability of the chemical environment of water body, simple and rapid detection of multiple parameters of water quality becomes a difficult task. In this paper, spectral images (named SPIs) and deep learning (DL) techniques were combined to construct an intelligent method for WQP detection. A novel spectroscopic instrument was used to obtain SPIs, which were converted into feature images of water chemistry and then combined with deep convolutional neural networks (CNNs) to train models and predict WQP. The results showed that the method of combining SPIs and DL has high accuracy and stability, and good prediction results with average relative error of each parameter (anions and cations, TOC, TP, TN, NO3--N, NH3-N) at 1.3%, coefficient of determination (R2) of 0.996, root mean square error (RMSE) of 0.1, residual prediction deviation (RPD) of 16.2, and mean absolute error (MAE) of 0.067. The method can achieve rapid and accurate detection of high-dimensional water quality multi-parameters, and has the advantages of simple pre-processing and low cost. It can be applied not only to the intelligent detection of environmental waters, but also has the potential to be applied in chemical, biological and medical fields.

Biosorption potential of viable and dead Aspergillus flavus biomass on polluted pond water.

The State Industries Promotion Corporation of Tamil Nadu Ltd (SIPCOT) Lake is never dry; it is always full of water and was recently used as a waste reservoir by the native peoples and industrialists. Thus, this investigation was performed to assess the quality of the lake water and evaluate the possible biosorption potential of Aspergillus flavus on this lake water sample through batch model biosorption study. The water quality parameters analyses revealed that the lake water has been polluted with number of contaminates which including organic and inorganic. The most of the parameters such as pH (9.5 ± 0.7), turbidity (38 ± 1.1 NT unit), TDS (2350.12 ± 31.24 mg L-1), BOD (40.21 ± 3.27 mg L-1), and COD (278.61 ± 11.84 mg L-1), Ca (212.85 ± 9.64 mg L-1), Fe (3.1 ± 0.8 mg L-1), NH3 (15.62 ± 0.5 mg L-1), NO3-(5.84 ± 0.14 mg L-1), Cl- (1257.85 ± 4.6 mg L-1),Cd (15.64 ± 0.29 mg L-1), Cr (6.86 ± 0.34 mg L-1), Pb (25.61 ± 3.41 mg L-1), and Hg (1.8 ± 0.024 mg L-1) content of water sample were beyond the acceptable limits. Fortunately, the A. flavus dead biomass showed considerable biosorption potential (Cd: 27.5 ± 1.1%, Cr: 13.48 ± 1.2%, Pb: 21.27 ± 1.5%, and Hg: 6.49 ± 0.86% in 180 min of contact time) than viable form on polluted lake water. Since, reduced the quantities of most of the parameters which beyond the permissible limit and also increased remarkable percentage of DO in the water sample in a short period of contact time. These findings suggest that A. flavus dead biomass can be used for bioremediation of polluted water in a sustainable manner.

Acoustic Characterization Study of Beef Loins Using Ultrasonic Transducers.

The objective of this study was to non-destructively characterize samples of fresh beef loin by low-intensity ultrasound inspection at various frequencies and to correlate the acoustic parameters of these inspections with quality parameters. In this regard, ultrasonic parameters such as ultrasound pulse velocity (UPV) and variables related to attenuation and frequency components obtained from fast Fourier transform (FFT) were considered. For this, pulsed ultrasonic signal transducers with a frequency of 0.5 and 1.0 MHz were used. Acoustic parameters and those obtained through traditional instrumental analyses (physicochemical and texture) underwent a Pearson correlation analysis. The acoustic determinations revealed numerous significant correlations with the rest of the studied parameters. The results demonstrate that ultrasonic inspection has the ability to characterize samples with a non-destructive nature, and likewise, this methodology can be postulated as a promising predictive tool for determining quality parameters in beef loin samples.

Short-term variations and correlations in water quality after dam removal in the Chishui river basin.

Dam damming has an adverse effect on river connectivity, leading to downstream nutrient transport and ecosystem fragmentation. Dam demolition has already been used as an effective measurement to promote the ecological restoration of rivers. Few studies have analyzed the short-term variations of water quality following dam removal. This study investigated the response of multi-element and multi-form water quality parameters, such as water temperature (TEM), dissolved oxygen (DO), pH, biochemical oxygen demand (BOD5), chemical oxygen demand (COD), ammonia nitrogen (NH3-N), total nitrogen (TN) and total phosphorus (TP), to the demolition of 4 dams in Chishui River Basin in short term. The study employed Spearman correlation analysis and Generalized Additive Models to identify the critical variables and examine the inter-relationship between these water quality parameters. Our results show that COD, BOD5, and TP increased after two weeks of dam removal, while NH3-N and TN decreased. Dams with larger volumes and higher heights led to more obvious deterioration for DO, COD, and BOD5. We also found that denitrification and resuspension dominantly affect the water quality indicators following dam removal. Denitrification is responsible for downstream TN increase, and resuspension and related sediment transport contribute to downstream TP increase. Our study provides an opportunity to explore the transformation and migration of N and P in reservoirs following dam removal in the short term and presents a scientific basis and new thought for the short-term protection and management following the clean-up and rectification of multiple small hydropower plants.

The effect of layers of high tunnel covering and soil mulching on tomato fruit quality.

BACKGROUND: High tunnels (HT) and plastic mulch can increase yield, extend growing seasons, protect plants from harsh weather conditions, and produce more marketable and attractive tomatoes. However, plastic covering reduces solar radiation, which may affect the quality of tomatoes. This study investigated the effects of single-layer versus double-layer HT and plastic mulch versus bare soil on the quality of fully ripe tomato fruits. The study was conducted over 2 years (2021 and 2022). The fruit color (L*, a*, and b*), vitamin C, pH, total titratable acid (TTA), total soluble solids (TSS), and lycopene content of the two tomato cultivars (Brandywine and Rebelski) were quantified. RESULTS: The results showed that quality parameters varied with the plastic layers of HT, plastic mulch, and planting year. The double-layer HT only showed a slight but significant influence on the color of tomatoes of both cultivars in the same year (P < 0.05). Brandywine tomatoes grown in the double-layer HT had significantly lower pH and lycopene content than those grown in single-layer HT, regardless of mulching. The effect of plastic layers on TTA, TSS, and lycopene depended on whether the soil was mulched. Tomatoes grown on bare soil had higher TTA and TSS values than those grown on mulched soil in double-layer HT. Tomatoes grown in single-layer HTs had significantly higher vitamin C content than those in the double-layer HT for both cultivars regardless of mulching. CONCLUSION: This study demonstrates that double-layer HT is unnecessary for the improvement of the overall quality of tomatoes. © 2023 Society of Chemical Industry.

Assessment of Gualaxo do Norte River water quality (Minas Gerais, Brazil) affected by the dam breach of Fundão utilizing exploratory multivariate techniques.

At the end of 2015, the Fundão dam belonging to the Samarco S.A. mining company was ruptured, releasing a flood of mud into the Gualaxo do Norte River, which advanced into the Doce River. The aim of the present study was to apply exploratory multivariate approaches to water quality data obtained during sampling campaigns at the Gualaxo do Norte River during the dry and rainy seasons, between July 2016 and June 2017. A total of 27 locations along the river were sampled, covering unaffected areas and regions influenced by the tailings waste from the dam. Determinations of chemical, physical, and microbiological water quality parameters were performed. Application of principal component analysis (PCA) resulted in the first two components together explaining 39.49% and 37.91% of the total variance for the dry and rainy season data, respectively. In both cases, the PCA groups were related to variables such as turbidity and total solids, which both presented higher values in regions affected by the mud flow. These results are in agreement with those obtained by the Kohonen neural network method, where two-dimensional maps confirmed the samples according to the affected and unaffected area by the disaster.

A comprehensive review of water quality indices for lotic and lentic ecosystems.

Freshwater resources play a pivotal role in sustaining life and meeting various domestic, agricultural, economic, and industrial demands. As such, there is a significant need to monitor the water quality of these resources. Water quality index (WQI) models have gradually gained popularity since their maiden introduction in the 1960s for evaluating and classifying the water quality of aquatic ecosystems. WQIs transform complex water quality data into a single dimensionless number to enable accessible communication of the water quality status of water resource ecosystems. To screen relevant articles, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was employed to include or exclude articles. A total of 17 peer-reviewed articles were used in the final paper synthesis. Among the reviewed WQIs, only the Canadian Council for Ministers of the Environment (CCME) index, Irish water quality index (IEWQI) and Hahn index were used to assess both lotic and lentic ecosystems. Furthermore, the CCME index is the only exception from rigidity because it does not specify parameters to select. Except for the West-Java WQI and the IEWQI, none of the reviewed WQI performed sensitivity and uncertainty analysis to improve the acceptability and reliability of the WQI. It has been proven that all stages of WQI development have a level of uncertainty which can be determined using statistical and machine learning tools. Extreme gradient boosting (XGB) has been reported as an effective machine learning tool to deal with uncertainties during parameter selection, the establishment of parameter weights, and determining accurate classification schemes. Considering the IEWQI model architecture and its effectiveness in coastal and transitional waters, this review recommends that future research in lotic or lentic ecosystems focus on addressing the underlying uncertainty issues associated with the WQI model in addition to the use of machine learning techniques to improve the predictive accuracy and robustness and increase the domain of application.

Assessment of water quality parameters in Muthupet estuary using hyperspectral PRISMA satellite and multispectral images.

The continuous availability of spatial and temporal distributed data from satellite sensors provides more accurate and timely information regarding surface water quality parameters. Remote sensing data has the potential to serve as an alternative to traditional on-site measurements, which can be resource-intensive due to the time and labor involved. This present study aims in exploring the possibility and comparison of hyperspectral and multispectral imageries (PRISMA) for accurate prediction of surface water quality parameters. Muthupet estuary, situated on the south side of the Cauvery River delta on the Bay of Bengal, is selected as the study area. The remote sensing data is acquired from the PRISMA hyperspectral satellite and the Sentinel-2 multispectral instrument (MSI) satellite. The in situ sampling from the study area is performed, and the testing procedures are carried out for analyzing different water quality parameters. The correlations between the water sample results and the reflectance values of satellites are analyzed to generate appropriate algorithmic models. The study utilized data from both the PRISMA and Sentinel satellites to develop models for assessing water quality parameters such as total dissolved solids, chlorophyll, pH, and chlorides. The developed models demonstrated strong correlations with R2 values above 0.80 in the validation phase. PRISMA-based models for pH and chlorophyll displayed higher accuracy levels than Sentinel-based models with R2 > 0.90.

Impact of graded levels of coated calcium butyrate on growth performance and serological indices during pre-weaning stage in Holstein calves.

The study aimed to analyze the impact of calcium butyrate supplementation in calf starter on growth performance indices associated with early rumen development to decrease the volume of milk or milk replacer feeding and enhance early starter intake in Holstein calves. For this purpose, twelve Holstein calves were randomly assigned into three treatments (n = 4/treatment); a control without coated calcium butyrate, T1, and T2 treatments supplemented with coated calcium butyrate 3 g and 6 g per day/head, respectively. Body weight was measured at days 7, 14, 21, 28, 35, 42, 49, and 56 of the trial, and the average daily weight gain and feed conversion ratio were determined. Blood samples were collected at 14, 28, 42, and 56 days of trial for serological parameters. Gut morphometry was performed at the end of trial at slaughtering by collecting duodenal samples. Furthermore, the meat was also evaluated for its quality parameters including pH and tenderness after slaughtering. The results indicated that the feed intake, average daily weight gain, feed conversion ratio, and gut morphometric parameters involving villus height and crypts depth of calves were improved in coated calcium butyrate-supplemented groups. Furthermore, the supplementation of calf starter with coated calcium butyrate significantly enhanced serum concentrations of glucose and total protein. Besides, Beta hydroxy butyrate (BHBA) levels of blood were also found to be elevated in both treatment groups. However, it was revealed that coated calcium butyrate supplementation had no significant effect on meat quality parameters. In conclusion, the supplementation of calf starter with coated calcium butyrate could improve calf performance.

Clinical and in vitro evaluation of red blood cells collected and stored in a non-DEHP plasticized bag system.

BACKGROUND AND OBJECTIVES: Di-ethyl-hexyl-phthalate (DEHP) is currently the main plasticizer used for whole blood collection systems. However, in Europe, after May 2025, DEHP may no longer be used above 0.1% (w/w) in medical devices. DEHP stabilizes red cell membranes, thereby suppressing haemolysis during storage. Here we compared in vitro quality parameters of red cell concentrates (RCCs) collected and stored in DEHP-, DINCH- or DINCH/BTHC-PVC hybrid blood bags with saline-adenine-glucose-mannitol (SAGM) or phosphate-adenine-glucose-guanosine-saline-mannitol (PAGGSM) storage solution. Last, we performed haemovigilance surveillance for RCC collected in DINCH-PVC and stored in PAGGSM/BTHC-PVC. MATERIALS AND METHODS: In vitro quality parameters of RCC were determined during 42 days of storage. Haemovigilance surveillance was conducted to compare the frequency and type of transfusion reaction. RESULTS: Haemolysis levels were increased in SAGM/BTHC-PVC as compared to SAGM/DEHP-PVC (0.66% ± 0.18% vs. 0.36% ± 0.17%). PAGGSM storage solution was able to adequately suppress haemolysis to levels observed during storage in SAGM/DEHP-PVC, both in BTHC-PVC (0.38% ± 0.12%), and to a slightly lesser extent in DINCH-PVC (0.48% ± 0.17%). A total of 1650 PAGGSM/BTHC-PVC and 5662 SAGM/DEHP-PVC RCC were transfused yielding a transfusion reaction frequency of 0.24% (95% CI 0.0000-0.0048) and 0.44% (95% CI 0.0027-0.0061) respectively. CONCLUSION: The in vitro quality of RCC stored in PAGGSM/BTHC-PVC and SAGM/DEHP-PVC is comparable. There is no indication that transfusion of erythrocytes stored in PAGGSM/BTHC-PVC results in increased transfusion reaction frequency. These initial results provide a basis for further clinical evaluation to narrow down the confidence interval of transfusion reaction frequency.

Effect of ambient air pollution and meteorological factors on the potential transmission of COVID-19 in Turkey.

There is a need to improve the understanding of air quality parameters and meteorological conditions on the transmission of SARS-CoV-2 in different regions of the world. In this preliminary study, we explore the relationship between short-term air quality (nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and particulate matter (PM2.5, PM10)) exposure, temperature, humidity, and wind speed on SARS-CoV-2 transmission in 41 cities of Turkey with reported weekly cases from February 8 to April 2, 2021. Both linear and non-linear relationships were explored. The nonlinear association between weekly confirmed cases and short-term exposure to predictor factors was investigated using a generalized additive model (GAM). The preliminary results indicate that there was a significant association between humidity and weekly confirmed COVID-19 cases. The cooler temperatures had a positive correlation with the occurrence of new confirmed cases. The low PM2.5 concentrations had a negative correlation with the number of new cases, while reducing SO2 concentrations may help decrease the number of new cases. This is the first study investigating the relationship between measured air pollutants, meteorological factors, and the number of weekly confirmed COVID-19 cases across Turkey. There are several limitations of the presented study, however, the preliminary results show that there is a need to understand the impacts of regional air quality parameters and meteorological factors on the transmission of the virus.

Potential of Near-Infrared Spectroscopy for the Determination of Olive Oil Quality.

The analysis of the physico-chemical parameters of quality of olive oil is still carried out in laboratories using chemicals and generating waste, which is relatively costly and time-consuming. Among the various alternatives for the online or on-site measurement of these parameters, the available literature highlights the use of near-infrared spectroscopy (NIRS). This article intends to comprehensively review the state-of-the-art research and the actual potential of NIRS for the analysis of olive oil. A description of the features of the infrared spectrum of olive oil and a quick explanation of the fundamentals of NIRS and chemometrics are also included. From the results available in the literature, it can be concluded that the four most usual physico-chemical parameters that define the quality of olive oils, namely free acidity, peroxide value, K232, and K270, can be measured by NIRS with high precision. In addition, NIRS is suitable for the nutritional labeling of olive oil because of its great performance in predicting the contents in total fat, total saturated fatty acids, monounsaturated fatty acids, and polyunsaturated fatty acids in olive oils. Other parameters of interest have the potential to be analyzed by NIRS, but the improvement of the mathematical models for their determination is required, since the errors of prediction reported so far are a bit high for practical application.