ABSTRACT
Gold (Au) nanoclusters (NCs) are novel materials with low cytotoxicity and high chemical stability. These properties are in high demand during the bioimaging. Moreover, the optical properties of gold clusters allow to use them as colorimetric and luminescent bionanosensors. Pterins are low molecular weight organic compounds, which are used in medicine as biomarkers of phenylketonuria, vitiligo, inflammation and immune system activation, cancer, COVID-19, etc. We have investigated the possibility of gold nanosensors usage to detect pterin (Ptr). Ptr-Aunq structures (n = 1–6;q = 0–2) Gibbs energy of complexation (Eb) have been obtained using density functional theory. The highest Eb was determined for the complexes of Au62+ and Au32+ in acidic and alkaline aqueous solution, respectively. The detection of pterin with gold clusters seems to be prospective using both colorimetric and fluorescent detection because of the intense S0→S1 transition in the absorption spectrum of the Au5+ complex. Raman detection of pterin should be performed at alkaline pH because of the dramatic changes in the spectrum of Ptr−1 upon the addition of Au clusters. We believe that these tunable changes of the pterin spectra due to Au clusters and nanoparticles attachment could be exploited in further studies on nanosensor design. © 2023
ABSTRACT
Introduction: Most areas under spring sugar beet cultivation face severe water restrictions and increasing the area under cultivation of this crop in most of these areas is contrary to the principle of conservation of water and soil resources. The use of new areas for winter sugar beet cultivation should be the area under cultivation of this crop in hot and dry areas. Therefore, winter sowing (pending) of sugar beet with emphasis on the limitations of the country's water resources has been proposed as a solution. Materials and Methods: In this study, the quantitative and qualitative yield of 16 sugar beet genotypes in winter planting were studied as a randomized complete block design with four replications in the Torbat-e-Jam region in the two cropping years (2020-2021 and 2021-2022). The studied genotypes included F-20739, F-20837, F-21083, SBSI-5, SBSI-15, SVZA 2019-JD389, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, FDIR 19 B 3021, FDIR 19 B 4028, F-20591, SBSI-6, SBSI-16, SBSI-7 and SBSI-17 are the breeding populations obtained from the gene bank of the Sugar Beet Seed Breeding Research Institute. In this research, traits such as root yield, sugar content, sugar yield, white sugar yield, Na, K, N, alkalinity, molasses sugar, white sugar content, and extraction coefficient of sugar were measured. Data were analyzed using SAS 9.1 software. The analysis of variance on test data and comparison to the middle of the Duncan test was performed at the 5% level. Factor analysis was calculated to identify the main factors using MINITAB software. Cluster analysis of the studied genotypes was obtained after standardizing the data by the Ward method and using Euclidean distance criterion with the help of SPSS software. Results and Discussion: The results of the combined analysis of variance showed that there was a significant difference between different genotypes of sugar beet at the level of 1% probability for all studied traits except for nitrogen content. The mean comparison showed that the SBSI-15 genotype had the highest root yield (60.66 ton.ha). It should be noted that this genotype in terms of yield index traits did not show significantly different from genotypes F-20739, SBSI-15, SVZA 2019-JD389, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, and FDIR 19 B 4028. Also, the F-20739 genotype had the highest amounts of sugar content (19.5%), white sugar content (16.3%) and extraction coefficient of sugar (83.2%) and the lowest amount of potassium (4.24 meq .100 g-1 of root weight) and Molasses sugar (2.7%). In addition, the highest sugar yield (10.69 t/ha) and white sugar yield (8.68 t/ha) were in FDIR 19 B 3021 genotype. Investigating the correlation of traits showed the highest positive and significant correlation was between sugar yield and white sugar yield (0.99**) and the highest negative and significant correlation was between extraction coefficient of sugar and molasses sugar (-0.95**). Principal factor analysis based on the mean of the traits identified three factors that accounted for a total of 91% of the variability between the data. SBSI-15, SVZA 2019-JD0398, SVZA 2019-JD0402, SVZA 2019-JD0400, SVZA 2019-JD0401, FDIR 19 B 3021, and FDIR 19 B 4028 genotypes are distinguished different from other genotypes and they were as superior genotypes in terms of yield index traits. The dendrogram generated from the cluster analysis for white sugar yield classified genotypes into three main groups.
ABSTRACT
COVID-19 is a pandemic that affected the majority of countries of the world. After the COVID-19 outburst, the Indian Government declared the complete lockdown starting on the night of 24 March 2020. The lockdown period is in its 4th phase. In the recent year it has been very fascinating to remind that the behaviour in the environment is vastly optimistic and all layers of the earth are under the repairing mode during the lockdown. With these healing environments, the conditions of the Yamuna River water in Mathura (polluted river) have also been found to be upgrading. In this present concern, we work on the concentration of BOD, COD, pH, and other physicochemical parameters for the study, i.e. TDS, Chlorides, Alkalinity, Magnesium, Calcium, Fluoride, Sulphate, Nitrate, Hardness and Total Coliform of Yamuna River (Mathura), respectively, which was found to be reduced as compared to pre-lockdown concentration, i.e. 57, 57, 3.6, 11.7, 5.1, 7.4, 9.5, 4.2, 62.5, 14.8, 33.3, and 4.5%. In the present work, the water of Yamuna River was analysed during the lockdown phase in ITL Labs Pvt. Ltd., Delhi (India). Yamuna River showed a better quality of water during the lockdown. As per results and trend analysis, the value was reducing in this lockdown phase, which is a matter of concern. Major locations of Yamuna water sample collection are Mathura region, i.e. adjacent to the road 50 m from Adda village in Naujheel of Mathura district in Uttar Pradesh. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Onsite molecular diagnostics can revolutionize fecal pollution source tracking. We aimed to validate a method for onsite qPCR assays with a miniature speaker-sized Q qPCR instrument and other portable equipment items. We showed that marker genes for total bacteria (16S) and E. coli (rodA) in 100 mL of river water measured with this method agreed within ±0.3 log10 units with results obtained when using conventional laboratory equipment items. We then deployed the portable method in a mobile laboratory (‘lab in a van’) and quantified HF183 marker genes for human host associated Bacteroides in river water within 3 h of sampling. We also used the mobile laboratory to investigate urban river water and effluents from two storm drains and a retention pond and collected comprehensive microbial and physicochemical water quality data. We found significantly higher HF183 gene levels in the older storm drain compared to the river water (6.03 ± 0.04 vs. 4.23 ± 0.03 log10 gene copies per 100 mL), and a principal component analysis revealed that storm drain effluent retention in a pond beneficially altered water characteristics, making them more like those of the receiving river. In conclusion, onsite qPCR assays can be performed with portable equipment items to quickly test water.
ABSTRACT
The water supply in drylands mainly relies on groundwater, making it a crucial resource. Springs in southern Africa are often underutilized, and are neither protected nor monitored. Thus, the aim of this study was to evaluate their quality in a sample area in northwestern Namibia and to propose solutions for the sustainable use of springs. In total, 35 springs and hot springs were evaluated in the study area located in the drier part of Namibia (Pmean = 150–400 mm/year), an area highly impacted by ongoing climate change with longer and more frequent drought seasons. The springs there are mostly uncaptured and the discharge is in the form of surface runoff, which is mainly lost to the atmosphere by evaporation. Most of the studied springs were perennial, despite a severe drought period. Local communities rely on the springs mainly for livestock and human consumption, as well as for irrigation. However, 71% of the springs do not have any protective measures. The temperature, pH, conductivity and alkalinity were tested in situ. In total, 20 samples were collected and analyzed for major ions (boron, fluoride, silica and strontium) and total dissolved solids (TDS). The physical and inorganic results mostly indicated good and excellent quality water for human consumption, while the hot springs tended to have poor water quality in terms of Namibian standards, indicating that the water was not fit for human consumption.
ABSTRACT
A detailed coastal water monitoring near Diu coast, western part of India was performed from October, 2020 to May, 2021 covering the 2nd lockdown time. Average monthly fluctuation from 7 different sampling stations of total 9 physico-chemical parameters such as pH, salinity, turbidity, nitrite (NO2), nitrate (NO3), ammonia (NH3), phosphate (PO4), total alkalinity and silicate were recorded. Initially, Mann-Kendall trend test for all the 9 parameters showed non-zero trend, which may be either linear or non-linear. During 2nd lockdown period, there was a fluctuation of value for parameters like pH, salinity, nitrate, nitrite and phosphate. Average total bacterial count and differential bacterial count also gradually decreased from March, 2021 sampling. Principal component analysis (PCA) plot covering all the physico-chemical parameters as well as the differential bacterial count showed a distinct cluster of all bacterial count with total alkalinity value. Subsequently, mathematical equation was formulated between total alkalinity value and all differential bacterial count. Upto our knowledge, this is the first report where mathematical equation was formulated to obtain value of different bacterial load based on the derived total alkalinity value of the coastal water samples near Diu, India.