Quality Parameters Research Articles

Impact of thermosonication treatment on passion fruit juice: ANN/GA optimization, predictive modelling for shelf life and quality changes during storage

Abstract Optimized sugar-added passion fruit juice (OPFJ) was obtained after optimization of thermosonication treatments of passion fruit juice using hybrid Artificial neural network/Genetic algorithm. The quality parameters and shelf life of OPFJ stored at various temperatures were assessed. Baranyi and Ratkowsky’s square-root models proved the prediction accuracy of the theoretical model concerning the microbial population during storage. The lag phase value decreased with increasing storage temperature. Temperature rise from 8 to 25 °C decreased the shelf life from 17 to 8 days for OPFJ and 3.5 to 1.5 days for untreated juice. The activation energy and increase in the reaction rate on increase in temperature by 10 °C (Q 10 value) were also evaluated. Thermosonication increased the phenolic and β-carotene contents and maintained the pH, titratable acidity, ascorbic acid content, and antioxidant activity during storage. Thermosonication enhanced the quality and shelf life of juice. Predictive modelling effectively predicted the shelf life.

Delayed Luminescence in Monitoring the Postharvest Ripening of Tomato Fruit and Classifying According to Their Maturity Stage at Harvest

AbstractRipening is an irreversible phenomenon involving several physiological, biochemical and organoleptic changes that affect the nutritional value, colour, texture and taste of fruit. Amongst the physical non-destructive technologies, Delayed Luminescence (DL) has been reported able to provide valid information on the functional status of living biological systems, reflecting changes in quality parameters following the occurrence of certain metabolic processes. In this study, we followed up and analysed the variations in the colour and DL signals emitted by tomato fruit as a function of their ripening degree. Four lots of tomato fruit, similar to each other for cultivar and geographical origin, were considered. Tomatoes were harvested at various maturity stages and stored in the dark at room temperature. The changes in DL emission trends were monitored at different times after harvesting for a period of about 20 days and correlated with the a*/b* colour ratio, which is normally used as an indicator of fruit ripeness degree. Results highlighted that the emission intensities, as well as the parameters by fitting DL decay curves, were strongly dependent on harvest maturity, varying significantly even as fruit ripeness progressed after their harvesting. Significant differences were also found between DL signals emitted by field-ripened tomatoes at the beginning of storage and those emitted by postharvest-ripened tomatoes at the end of the storage period. Delayed Luminescence may be used as a fast, reliable and sensitive tool for evaluating, more generally, the sensorial quality of fruit during postharvest storage.

Defense Pathways of Wheat Plants Inoculated with Zymoseptoria tritici under NaCl Stress Conditions: An Overview

Due to being sessile, plants develop a broad range of defense pathways when they face abiotic or biotic stress factors. Although plants are subjected to more than one type of stress at a time in nature, the combined effects of either multiple stresses of one kind (abiotic or biotic) or more kinds (abiotic and biotic) have now been realized in agricultural lands due to increases in global warming and environmental pollution, along with population increases. Soil-borne pathogens, or pathogens infecting aerial parts, can have devastating effects on plants when combined with other stressors. Obtaining yields or crops from sensitive or moderately resistant plants could be impossible, and it could be very difficult from resistant plants. The mechanisms of combined stress in many plants have previously been studied and elucidated. Recent studies proposed new defense pathways and mechanisms through signaling cascades. In light of these mechanisms, it is now time to develop appropriate strategies for crop protection under multiple stress conditions. This may involve using disease-resistant or stress-tolerant plant varieties, implementing proper irrigation and drainage practices, and improving soil quality. However, generation of both stress-tolerant and disease-resistant crop plants is of crucial importance. The establishment of a database and understanding of the defense mechanisms under combined stress conditions would be meaningful for the development of resistant and tolerant plants. It is clear that leaf pathogens show great tolerance to salinity stress and result in pathogenicity in crop plants. We noticed that regulation of the stomata through biochemical applications and some effort with the upregulation of the minor gene expressions indirectly involved with the defense mechanisms could be a great way to increase the defense metabolites without interfering with quality parameters. In this review, we selected wheat as a model plant and Zymoseptoria tritici as a model leaf pathogen to evaluate the defense mechanisms under saline conditions through physiological, biochemical, and molecular pathways and suggested various ways to generate tolerant and resistant cereal plants.

Standardization of Optimum Grading Sieve Size for Seed Processing in Black Gram [Vigna mungo (L.) Hepper] Varieties

Background: The seeds harvested from the field may not be homogenous in seed size, physical purity and viability in Black gram. Seeds are to be cleaned and graded using seed processing machineries to maintain uniformity of a seed lot. Every variety is having its individuality in seed size. Hence, the common recommendation of 2.8 mm sieve size recommended by Indian Minimum Seed Certification Standards (IMSCS) for grading black gram seeds may not be suitable to recover a maximum quality seeds in all varieties while processing. The present study was carried out to identify a suitable grading sieve size for newly released black gram varieties for getting good quality seeds with better seed recovery during processing. Methods: The study was conducted at Seed Technology Research Unit, Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal during the year 2020-2023. The experiment was laid out in completely randomized design with four replications. Four newly released black gram varieties viz., ADT 6, VBN 8, VBN 10 and VBN 11 were taken for the study. Specified quantities of unprocessed seeds have been sieved using slotted sieves of three sizes above (3.4 mm, 3.2 mm and 3.0 mm) and two sizes below (2.7 mm and 2.5 mm) the recommended sieve size of 2.8 mm for black gram varieties as per the IMSCS. The seeds retained over each sieves were collected separately and tested for seed quality parameters. Result: The results revealed that the seed recovery percent increased with decrease in sieve size while the seed quality parameters found higher with increase in sieve size.The sieve size of 2.7 mm (slotted) registered the maximum cumulative seed recovery of 87% and 89.9%, respectively in Black gram seeds of cv. ADT 6 and VBN 10 along with required seed standards. However, seeds retained from the sieve size of 3.0 mm (slotted) registered the maximum cumulative seed recovery of 91.2% and 87.5%, respectively in VBN 8 and VBN 11 with requisite seed germination and physical purity as per the IMSCS (75% and 98%). Hence, it is suggested that the sieve size of 2.7 mm may be considered as grading sieve size for seed processing in Black gram seeds of cv. ADT 6 and VBN 10 and 3.0 mm may be used as grading screen (Bottom screen) for VBN 8 and VBN 11 for getting good quality seeds with higher seed germination, physical purity and pure live seeds.

Can Microfluidics Improve Sperm Quality? A Prospective Functional Study

The same sperm selection techniques in assisted reproduction clinics have remained largely unchanged despite their weaknesses. Recently, microfluidic devices have emerged as a novel methodology that facilitates the sperm selection process with promising results. A prospective case-control study was conducted in two phases: 100 samples were used to compare the microfluidic device with Density Gradient, and another 100 samples were used to compare the device with the Swim-up. In the initial phase, a significant enhancement in progressive motility, total progressive motile sperm count, vitality, morphology, and sperm DNA fragmentation were obtained for the microfluidic group compared to Density Gradient. Nevertheless, no statistically significant differences were observed in sperm concentration and chromatin structure stability. In the subsequent phase, the microfluidic group exhibited significant increases in sperm concentration, total progressive motile sperm count, and vitality compared to Swim-up. However, non-significant differences were seen for progressive motility, morphology, DNA structure stability, and DNA fragmentation. Similar trends were observed when results were stratified into quartiles. In conclusion, in a comparison of microfluidics with standard techniques, an improvement in sperm quality parameters was observed for the microfluidic group. However, this improvement was not significant for all parameters.

Water function zone: A method to improve the accuracy of remote sensing retrieval of water bodies

In water monitoring, it is always a hot issue to exploring a method to improve the accuracy of remote sensing inversion. To this end, based on the actual investigation of the surrounding environment and water quality characteristics of the Fuyang river, this study has established five distinct water functional zones: reservoir (RS), village river (VR), industrial river (IR), artificial lake (AL), and urban river (UR), which are considered as subdivided datasets. Meanwhile, considering that lakes and reservoirs typically contain relatively stationary or slow-moving water bodies, while river channels are characterized by moving water bodies, three multi-type datasets have been constructed for comparison. These are based on the morphological and flow characteristics of different regions within the Fuyang river and include river channel (R), lake (L), and whole basin (W). Based on multi-spectral images of unmanned aerial vehicle (UAV) and measured water quality data, ten types of inversion models were to invert six kinds of water quality parameters, and compare and analyze the performance of the optimal inversion model of the corresponding data sets. The results show that the multivariate regression model is superior to the univariate regression model, and the mean coefficient of determination (R2) of the subdivided data set is 0.936, and the root mean square error (RMSE) and mean absolute error (MAE) appear decrease in different degrees compared with the W with 3.573 and 2.662, respectively. The mean ratio performance to interquartile (RPIQ) of the corresponding model in UR and VR are 3.963 and 2.748, respectively. Extremely Randomized Trees (ERT) model is more suitable for the inversion of multi-type data sets lacking obvious water quality characteristics and with complex components, while Categorical Boosting (CatBoost) model is more suitable for the inversion of subdivided data sets with obvious water quality characteristics. The current method has practical guiding significance for improving the application level of water monitoring technology in ecological environment protection and urban water resources protection.

Robust kernel extreme learning machines with weighted mean of vectors and variational mode decomposition for forecasting total dissolved solids

A stable and accurate forecast of water quality parameters is crucial for planning and managing future investment programs. A well-known water quality indicator is the total dissolved solids (TDS), which measures the number of metals, minerals, and salts dissolved in a particular volume of water. This paper introduces an innovative approach, which combines the kernel extreme learning machine (KELM) with the robust weight mean of vectors (INFO) algorithm. The proposed technique stands out for its strategic integration of Boruta-XGBoost (B-XGB) as an exceptional feature selection method, along with variational mode decomposition (VMD) to decompose the input variables and enhance the accuracy of forecasting. The integrated model is termed V-KELM-INFO. INFO is an essential component that incorporates a complex exploration process. It utilizes a weighted mean of vectors, a vector combining operator to enhance population variety, and a localized search operator to expedite convergence. INFO, a potent tool, is included in the V-KELM training stage. It efficiently extracts optimum parameters and dramatically improves the accuracy of monthly TDS predictions at the Idenak station in southwest Iran. Also, the multi-criteria decision-making (MCDM) approach of weighted aggregated sum product assessment (WASPAS) is used to rank models. The V-KELM-INFO model was chosen based on the WASPAS results and statistical metrics (R = 0.962, RMSE = 57.84, WHD = 7.01, and U95 = 160.74) as the best model to forecast the TDS. In addition, the superiority of the proposed model was assessed against the metaheuristic-based V-KELM models, comprising the V-KELM grey wolf optimizer (V-KELM-GWO), V-KELM slime mold algorithm (V-KELM-SMA), and V-KELM equilibrium optimizer (V-KELM-EO). This work provided insight into improving the accuracy of modeling-based methodologies and spurred water quality modeling technology to develop sustainable and clean practices.

Investigation of Water Pollution in the Baghlan River Caused by Dust and Wastewater from the Ghori Cement Factory: A Case Study

Rivers are one of the most crucial fluid ecosystems, primarily due to their freshwater content. Understanding the trends in water quality changes in seas enables the anticipation of future challenges and the implementation of plans to address them. Water quality management necessitates the collection and analysis of a vast amount of data and water quality parameters. To facilitate this, various tools have been developed for simpler assessment of data and water quality, among which water quality indices are highly utilized. The objective of this study is to assess the water quality of the Balkh Sea using the (IRWQISC) and (IRWQIST) indices, alongside examining the levels of heavy metals, cations, anions, and its physical characteristics. Sampling was conducted at two time points: initially in October 2022, with heavy metal analysis performed using Flame Atomic Absorption Spectroscopy (FAAS), and subsequently in April 2023, where samples were collected from various points, and the concentrations of cations, anions, pH, and electrical conductivity (EC) were measured. Data analysis was carried out using SPSS version 26, and ArcGIS 10.4.1 was employed for map production. The research findings indicate a trend of heavy metal changes as follows: Al>As>Pb>Cd>(Cr=Co=Ni)>Hg. Based on the calculation of the toxicity index (IRWQIST), the studied water falls into the poor category. Consequently, sea water, due to the presence of heavy metals such as lead, cadmium, arsenic, and mercury, is relatively to very toxic and unsuitable for drinking. Additionally, it may cause detrimental effects for other uses such as agriculture and livestock farming.

Evaluation of Himalayan nettle (Urtica ardens) extract meal in common carp (Cyprinus carpio) feed: Impact on growth performance, digestive enzyme activity and antioxidant capacity

This research aims to evaluate the impact of an extract derived from the leaves of Himalayan nettle (Urtica ardens) leaf extract on common carp, Cyprinus carpio, growth, digestive enzymes, fish body carcass composition, antioxidant system, and water quality parameters. For a duration of 90 days, experimental diets containing nettle extract were given to 150 fish (12.38 ± 0.53 g) in 15 tanks (10 fish per tank). The five groups in triplicate were: control or T0 (untreated), T1 (fed 0.3% extract), T2 (0.6% extract), T3 (0.9% extract), and T4 (1.2% extract). Results revealed that nettle extract in the diet increases common carp growth up to 0.9% concentration of extract. Its feed conversion ratio decreases, while weight gain and specific growth rate rise significantly compared to the control diet. No mortality was observed during the 90-day experiment. Dietary nettle extract did not affect whole-body fibre and crude ash percentages (p > 0.05). Nettle-fed and control groups showed significant differences in crude protein, body fat, and total body moisture (p < 0.05). After a 90-day feeding trial, 0.9% nettle extract-fed fish had higher protease, amylase, lipase, and cellulase levels than the control group (p < 0.05). When nettle content reached 1.2%, enzyme activity decreased. Orthophosphate production peaked at 4 and 8 hours after feeding, while ammonia excretion peaked at 2 and 6 hours. The control group excreted the most ammonia and orthophosphate, while the 0.9% group excreted the least. Liver and kidney SOD levels were higher in common carp fed a 0.6% nettle extract diet. Feeding with a 0.9% nettle extract diet improved hepatic lipid peroxidation, gut and liver glutathione. Gut and kidney SOD, catalase, LPO, and GSH increased dramatically on the 1.2% diet. Statistically, the 0.9% nettle extract (T3) group showed the overall best results compared to the control diet. These findings demonstrate the potential of nettle extract as a dietary supplement in aquaculture.

Research on CC-SSBLS Model-Based Air Quality Index Prediction

Establishing reliable and effective prediction models is a major research priority for air quality parameter monitoring and prediction and is utilized extensively in numerous fields. The sample dataset of air quality metrics often established has missing data and outliers because of certain uncontrollable causes. A broad learning system based on a semi-supervised mechanism is built to address some of the dataset’s data-missing issues, hence reducing the air quality model prediction error. Several air parameter sample datasets in the experiment were discovered to have outlier issues, and the anomalous data directly impact the prediction model’s stability and accuracy. Furthermore, the correlation entropy criteria perform better when handling the sample data’s outliers. Therefore, the prediction model in this paper consists of a semi-supervised broad learning system based on the correlation entropy criterion (CC-SSBLS). This technique effectively solves the issue of unstable and inaccurate prediction results due to anomalies in the data by substituting the correlation entropy criterion for the mean square error criterion in the BLS algorithm. Experiments on the CC-SSBLS algorithm and comparative studies with models like Random Forest (RF), Support Vector Regression (V-SVR), BLS, SSBLS, and Categorical and Regression Tree-based Broad Learning System (CART-BLS) were conducted using sample datasets of air parameters in various regions. In this paper, the root mean square error (RMSE) and mean absolute percentage error (MAPE) are used to judge the advantages and disadvantages of the proposed model. Through the experimental analysis, RMSE and MAPE reached 8.68 μg·m−3 and 0.24% in the Nanjing dataset. It is possible to conclude that the CC-SSBLS algorithm has superior stability and prediction accuracy based on the experimental results.

Effect of Different Levels of Foliar Spray of Water Soluble Fertilizer NPK on Growth, Yield and Quality of Prickly Lettuce

A trial was conducted to evaluate the foliar application of fertilizer on growth, yield &amp; quality of prickly lettuce at Vegetable Research farm, Department of Horticulture, SHUATS. The objectives of this study were to find out suitable combination of water- soluble fertilizer of nitrogen, potassium and phosphorus for growth, yield and quality of prickly lettuce and to estimate the economics of the various treatments. The experiment was laid out in randomized block design (R.B.D) with 3 replications and 8 treatments. Results revealed that treatment T4 performed best in terms of growth parameters viz; plant height, leaf area , number of leaves per plant, plant spread, leaf area , yield parameters viz; yield per plant, yield per hectare and quality parameters viz; TSS and ascorbic acid.

Effect of Quality Attributes of Potato by Using Biochar and NPK Fertilizers with Biozyme Granules

The present study, which took place at the central Research Farm of Naini Agricultural Institute, SHUATS, spanned across the years 2022-2023 and 2023-2024. Throughout this study, an experiment was meticulously conducted utilizing a variety of Kufri badhash under the Factorial Randomized Block Design (FRBD) design. This experiment included three replications, each encompassing three levels (2.5, 5, 7.5 t ha-1) of Biochar and three levels (50%, 75%, 100%) of Inorganic fertilizers. Additionally, two levels (25 and 50 kg ha-1) of Biozyme granules were also part of this comprehensive research design. The results obtained regarding various quality parameters in the years 2022-23 and 2023-24, such as moisture content (80 and 81 100g-1), tuber dry matter content (20.98% and 21.96 %), starch content (13.54% and 14.12%), reducing sugar (0.28% and 0.30%), non-reducing sugar (0.35% and 0.37%), and total sugar (0.58% and 0.59%) were notably elevated with the application of T16. Notably, the maximum protein content (2.07 and 2.31%), carbohydrate (14.58% and 14.85%), and total soluble solid (6.44% and 6.77%) were observed with the application of T18 in accordance with the recommended practices. Conversely, the minimum values were recorded for T1, showcasing the significant impact of the application techniques on the various parameters studied.

Identification of Induced Chemical Mutants for Improving Yield and its Attributing Traits in Wheat (Triticum aestivum L.) against Changing Climate

Background: The enhancement of genetic traits in any crop relies on the existing variability within that particular crop. Through hybridization and traditional breeding methods, the variability within wheat crops has been nearly exhausted. Consequently, mutation breeding emerges as the sole viable and promising approach to introduce new variability for further improvements. Methods: An experiment was conducted during the Rabi seasons of 2020-21 (M1 generation) and 2021-22 (M2 generation) at the Crop Research Centre, Department of Genetics and Plant Breeding, ITM University Gwalior. The experiment assessed the impact of five different concentrations of Sodium Azide (0.02%, 0.03%, 0.04%, 0.05%, and 0.1%) and Hydroxyl Amine (0.2%, 0.3%, 0.4%, 0.5% and 0.6%), in addition to a control, on the wheat varieties MP-3382 and RVW-4106. It employed a randomized block design with three replications. Result: The findings revealed that Sodium Azide and Hydroxyl Amine, the most effective dosages were observed to be 0.1per cent and 0.4 per cent, respectively, in inducing genetic and phenotypic changes in seed quality parameters. Specifically, for the flag leaf area characteristic, the most effective concentrations were 0.03 per cent Sodium Azide and 0.4 percent Hydroxyl Amine. Plant height exhibited the greatest variability at 0.03 per cent Sodium Azide, 0.5 per cent Hydroxyl Amine and 0.1 percent Sodium Azide. A dosage of 0.5 per cent Hydroxyl Amine was found to be most effective in altering spike length. In terms of days to 50 per cent flowering, 0.05 per cent Sodium Azide was identified as the most effective dosage. From the study of traits in both the M1 and M2 generations, 12 mutants were confirmed, with seven validated for variety MP-3382 and five for variety RVW-4106.

Assessing Genetic Variability in Cowpea Yield Components and Seed Quality Parameters; A Comprehensive Review

Cowpea (Vigna unguiculata L. Walp) is an important leguminous crop with significant economic and nutritional value. In this comprehensive review, we delve into the genetic diversity observed in cowpea populations with a focus on yield components and seed quality parameters. Cowpea (Vigna unguiculata) is a crucial legume crop known for its nutritional value and adaptability to various agroecological conditions. Understanding the genetic variability within cowpea populations is essential for crop improvement programs aimed at enhancing yield components and seed quality parameters. This comprehensive review provides an overview of the methods used to assess genetic variability in cowpea, focusing specifically on yield components such as plant height, pod length, and seed weight, as well as seed quality parameters including protein content, amino acid composition, and mineral nutrient levels. Various factors influencing genetic variability in cowpea, such as domestication history, breeding systems, and environmental factors, are discussed. The implications of genetic variability for cowpea breeding and the development of improved varieties with enhanced yield and nutritional quality are also examined. Overall, this review highlights the importance of genetic variability assessment in cowpea for sustainable agriculture and food security.

Effect of Different Sources and Levels of Sulphur in Sesame on Yield, Nutrient Uptake and Soil Fertility in Acid Alfisols of Odisha, India

Aims: To examine the impact of different sources and levels of Sulphur on yield and oil content of sesame in acid Alfisols of Dhenkanal district of Odisha. Study Design: Randomized Block Design with three replications. Place and Duration of Study: During 2018 and 2019, this experiment was carried out at the Odisha University of Agriculture and Technology's Regional Research and Technology Transfer Station, which is located in Mahisapat, Dhenkanal district, Mid Central Table Land Zone, Odisha. Methodology: The treatments were T1- STBFR (S control), T2- STBFR + 30 kg ha-1 S from Ammonium Phosphate Sulphate, T3- STBFR + 40 kg ha-1 S from Ammonium Phosphate Sulphate, T4- STBFR + 30 kg ha-1 S from Gypsum, T5- STBFR + 40 kg ha-1 S from Gypsum, T6- STBFR + 30 kg ha-1 S from SSP, T7- STBFR + 40 kg ha-1 S from SSP. Results: Among seven treatments, T7 (STBFR along with 40 kg ha-1 S from SSP) was superior among all the sources and doses w.r.t. yield components and yield. The quality parameters like oil content under different sulphur fertilization was found to be maximum with STBFR along with 40 kg ha-1 S from SSP. Highest total nutrient uptake in terms of N, P, K and S of 55, 26, 37 and 5 kg/ha was recorded with the same treatment. Conclusion: Sulphur fertilization (T7) in the acid Alfisols of Odisha exhibited improved yield, oil content and nutrient uptake in sesame.

A Feasibility Inquiry to the Sustainable Utilization of Few Invasive Flora

Objectives: The study focuses on utilising invasive flora affecting the indigenous plants and thereby bring about monetary benefits to the local people by means of handmade papers from the invasive weeds. Methods: Handmade paper from five invasive plants namely, Eichhornia crassipes, Eupatorium odorata, Combretum indicum, Lantana camara and Hyptis capitata was attempted. These plants after collection from Nilambur, Kerala were subjected to treatment with washing soda, blending, vat preparation, moulding and drying. This is followed by checking the paper quality parameters viz., Productivity, Clarity/opacity/transparency, Strength, Grammage, Paper grain, Ageing of paper and Moisture content. Findings: Out of the five invasive plants tested, the fibre yield was maximum for Eichhornia, but the productivity rate was less compared to other samples. Lantana and Hyptis yielded maximum productivity even though the fibre yield from these plants was less. The fibre uniformity of paper developed was positively detected for all the 4 plants except Eichhornia thereby proving the feasibility for paper manufacture. All sample paper allows the light; so, all are translucent in nature. Integrity of paper samples was retained in the paint test. The age test also yielded positive results. The gsm test showed lowest for Eichhornia as 98.12g/m2; Lantana 111.87g/m2; Combretum 131.87g/m2; Hyptis 163.75g/m2; Eupatorium is 255g/m2. Even though the gsm of Eichhornia is the best for paper manufacture according to gsm standards, the lack of fibre uniformity is a withdrawing feature for feasibility. The moisture content appeared high for Eichhornia and lowest for Combretum. Novelty: To date, studies on invasive plant utilisation done individually; no comparative study on productivity done. Current study can be further refined for environmental sustenance along with livelihood for local people. Keywords: Invasive Flora, Paper manufacture, Grammage test, Productivity, Ecological sustainability

Neurovascular Imaging with Ultra-High-Resolution Photon-Counting CT: Preliminary Findings on Image Quality Evaluation.

The first-generation photon-counting detector (PCD) CT was recently introduced into clinical practice and represents a promising innovation in high-resolution CT imaging. The purpose of this study was to assess the image quality of ultra-high-resolution (UHR) PCD-CT compared with energy-integrating detector (EID)-CT, and to explore different reconstruction kernel sharpness levels for the evaluation of intracranial aneurysms. Ten patients with intracranial saccular aneurysms, who had previously undergone conventional EID-CT, were prospectively enrolled. CT angiograms were acquired on a clinical dual-source PCD-CT in UHR mode, and reconstructed with four vascular kernels (Bv36, Bv40, Bv44, Bv48). Quantitative and qualitative image quality parameters of the intracranial arteries were evaluated. For the quantitative analysis (image noise, SNR, CNR), regions of interest were manually placed at standard anatomical intracranial and extracranial locations by one author. In addition, vessel border sharpness was evaluated quantitatively. For the qualitative analysis, three blinded neuroradiologists rated PCD-CT and EID-CT image quality for the evaluation of the intracranial vessels (i.e., the aneurysms and nine standard vascular branching locations) on a 5-point Likert-type scale. Additionally, readers independently selected their preferred kernel among the four kernels evaluated on PCD-CT. In terms of quantitative image quality, Bv48, the sharpest kernel, yielded increased image noise, and decreased SNR and CNR parameters compared to Bv36, the smoothest kernel. Compared to EID-CT, the Bv48 kernel offered better quantitative image quality for the evaluation of small intracranial vessels (p < .001). Image quality ratings of the Bv48 were superior to those of the EIDCT, and not significantly different from ratings of the B44 reconstruction kernel. When comparing side-by-side all four PCD-CT reconstruction kernels, readers selected the B48 kernel as the best to visualize the aneurysms in 80% of cases. UHR PCD-CT provides improved image quality for neurovascular imaging. Although the less sharp kernels provided superior SNR and CNR, the sharpest kernels delivered the best subjective image quality on PCD-CT for the evaluation of intracranial aneurysms.CNR ＝ Contrast-to-Noise Ratio; EID-CT ＝ Energy-Integrating Detector CT; PCD-CT ＝ Photon-Counting Detector CT; QIR ＝ Quantum Iterative Reconstruction; UHR ＝ Ultra-High-Resolution.

Effects of Liquid Whey Supplementation with Water on Egg Production and Egg Quality in Layer Chickens

Background: Liquid whey is a milk by-product and contains good quality protein and minerals. Due to lack of proper knowledge and sufficient technology it remains unutilized and thrown away as a waste. So, keeping in view of its profitable utilization, a study was planned to include liquid whey as feed supplement to layer poultry. Methods: A study was conducted by supplementation of liquid whey to layer chickens to study the effect on egg production and egg quality. A total of 120 layer birds (indicate the age) were supplemented with liquid whey ad libitum in the drinking water @ 0, 5, 10 and 15% up to 90 days. The data were collected with respect to egg production and egg quality parameters. Result: Supplementation of liquid whey in drinking water improved egg production and egg quality in laying chickens. It may be concluded that liquid whey can be supplemented with drinking water at the rate of 5% (v/v) for better egg production in layers and for production of premium quality of bigger size and weight of eggs, supplementation of whey up to 15% (v/v) can be recommended.

Fish Diversity and Hydrological Parameters of Indrasagar Reservoir (Khandwa District)

The state of Madhya Pradesh is the central state of India &amp; one of the important aquatic biodiversity hotspots of the country, having bestowed with a large number of water bodies both lotic and lentic, the state boasts of rich fish biodiversity. The aim of this study is collection and identification of finfish that found in Indira sagar reservoir and the water quality parameter of the reservoir in which the fishes thriving. Total 54 species of 9 order were found in the reservoir in Khandwa district including labeo rohita,Catla catla, Cirrhinus mrigala, Ctenopharyngodon idella Labeo calbasu, Puntius sophore, Pethia ticto,Puntius chola, Cyprinus carpio, Pangasianodon hypophthalmus, Oreochromis mossambicus, Glossogobius giuris, Channa marulius, Channa gachua , Channa striata and Clarias magur etc. The 03 species of transplanted Indian major carps Catla catla, Cirrhinus mrigala and Labeo rohita are dominating the fishermen catches The authors are of firm opinion that the exotic species are posing competition for food and space to the native species.. To certain extend even hybrid of catla and rohu are available in the fish catches The water quality parameters were significantly found suitable for freshwater cultivable species including the temperature, dissolved oxygen, Total hardness , dissolved oxygen and temperature are higher in summer season and lower in winter season. This may be due to higher photosynthetic rate in summer season. Whereas the pH value is higher in winter season and lower in summer season. It indicates reduction in photosynthetic activities in winter which reduces assimilation of carbon dioxide and bicarbonates.

Seasonal and interannual changes (2005-2021) of lake water quality and the implications for sustainable management in a rapidly growing metropolitan region, central China.

A series of restoration measures such as municipal wastewater treatment and aquaculture closures have been implemented in Wuhan City during recent years. In order to explore the impact of restoration measures and climate change on lake water quality, long-term (2005-2021) water quality data of 47 lakes were explored to reveal spatiotemporal changes in lake water quality. Percentages of polluted lakes were calculated according to six water-quality parameters, including total phosphorus (TP), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biological oxygen demand (BOD), chemical oxygen demand using potassium permanganate as oxidant (CODMn) and petroleum contamination (PET), at interannual and monthly timescales. At the interannual timescale, percentages of COD, BOD, CODMn and PET pollution decreased significantly, suggestive of water quality improvement during recent years. At the monthly timescale, low percentages of NH3-N and BOD pollution in March 2020 probably resulted from the sharp reduction in human activities during the COVID-19 lockdown. At the monthly timescale, temperature was positively correlated with percentage of CODMn pollution, but negatively correlated with percentage of NH3-N pollution; precipitation was negatively correlated with percentage of BOD pollution. The similarity of water-quality parameters generally decreased with an increase in geographical distance between each pair of lakes. However, the regression coefficients between the similarity of lake water quality and the geographical distance decreased with time, probably resulting from enhanced similarity of water quality parameters among all lakes with rapid urbanization. Our results highlight the importance of active restoration measures for sustainable management of lakes in Wuhan City, as well as in similar developing regions.