Arsenic tolerances in rice (Oryza sativa) have a predominant role in transcriptional regulation of a set of genes including sulphur assimilation pathway and antioxidant system

World wide arsenic (As) contamination of rice has raised much concern as it is the staple crop for millions. Four most commonly cultivated rice cultivars, Triguna, IR-36, PNR-519 and IET-4786, of the West Bengal region were taken for a hydroponic study to examine the effect of arsenate (As^V) and arsenite (As^III) on growth response, expression of genes and antioxidants vis-à-vis As accumulation. The rice genotypes responded differentially under As^V and As^III stress in terms of gene expression and antioxidant defences. Some of the transporters were up-regulated in all rice cultivars at lower doses of As species, except IET-4786. Phytochelatin synthase, GST and γ-ECS showed considerable variation in their expression pattern in all genotypes, however in IET-4786 they were generally down-regulated in higher As^III stress. Similarly, most of antioxidants such as superoxide dismutase (SOD), ascorbate peroxidase (APX), guaiacol peroxidase (GPX), catalase (CAT), monodehydroascorbate reductase (MDHAR) and dehydroascorbate reductase (DHAR) increased significantly in Triguna, IR-36 and PNR-519 and decreased in IET-4786. Our study suggests that Triguna, IR-36 and PNR-519 are tolerant rice cultivars accumulating higher arsenic; however IET-4786 is susceptible to As-stress and accumulates less arsenic than other cultivars.     

Emission of volatile organic compounds from religious and ritual activities in India

Worshipping activity is a customary practice related with many religions and cultures in various Asian countries, including India. Smoke from incense burning in religious and ritual places produces a large number of health-damaging and carcinogenic air pollutants include volatile organic compounds (VOCs) such as formaldehyde, benzene, 1,3 butadiene, styrene, etc. This study evaluates real-world VOCs emission conditions in contrast to other studies that examined emissions from specific types of incense or biomass material. Sampling was conducted at four different religious places in Raipur City, District Raipur, Chhattisgarh, India: (1) Hindu temples, (2) Muslim graveyards (holy shrines), (3) Buddhist temples, and (4) marriage ceremony. Concentrations of selected VOCs, respirable particulate matter (aerodynamic diameter, <5 μm), carbon dioxide, and carbon monoxide were sampled from the smoke plumes. Benzene has shown highest emission factor (EF) among selected volatile organic compounds in all places. All the selected religious and ritual venues have shown different pattern of VOC EFs compared to laboratory-based controlled chamber studies.     

Assessment of mining activities on tree species and diversity in hilltop mining areas using Hyperion and Landsat data

Environmental Science and Pollution Research - The tree species and its diversity are two critical components to be monitored for sustainable management of forest as well as biodiversity...     

Heavy metal contamination of drinking water in Kamrup district, Assam, India

This study was undertaken to assess the heavy metal concentration of the drinking water with respect to zinc, copper, cadmium, manganese, lead and arsenic in Kamrup district of Assam, India. Ground water samples were collected from tube wells, deep tube wells and ring wells covering all the major hydrogeological environs. Heavy metals in groundwater are estimated by using Atomic Absorption Spectrometer, Perkin Elmer Analyst 200. Data were assessed statistically to find the distribution pattern and other related information for each metal. The study revealed that a good number of the drinking water sources were contaminated with cadmium, manganese and lead. Arsenic concentrations although did not exceeded WHO limits but was found to be slightly elevated. Copper and zinc concentrations were found to be within the prescribed WHO limits. An attempt has also been made to ascertain the possible source of origin of the metals. Positive and significant correlation existing between manganese with zinc and copper indicates towards their similar source of origin and mobility. In view of the present study and the level of heavy metal contamination, it could be suggested to test the potability of the water sources before using it for drinking purpose.     

A Study on Ionizing Emissions from Limestone Samples using CR-39 Solid State Nuclear Track Detector

Limestone is an item most commonly consumed by the people in the Barak Valley area of Assam along with betel leaves. Also limestone chips are extensively used for water treatment in filter beds of these areas. A preliminary investigation on the activity of the samples of limestone, collected from the local market at Silchar, Assam, indicated the presence of beta and gamma-ray activity, prompting further investigations for the presence of alpha particle emitting radionuclides. Also the study of the ionising emissions from these samples using solid state nuclear track detector (SSNTD) has revealed the presence of spontaneous fission fragments along with alpha particles. This paper presents an account of the results obtained from the SSNTD studies of these limestone samples.     

A simple chemical method for the synthesis of Cu2+ engrafted MgAl2O4 nanoparticles: Efficient fluoride adsorbents, photocatalyst and latent fingerprint detection

An adaptable, energy efficient chemical process is employed to synthesize Cu~(2+)engrafted MgAl_2O_4 nanoparticles(Mg_(1-x)Cu_xAl_2O_4, x = 0, 0.1, 0.3, 0.5 abbreviated as MCA0, MCA1, MCA3,and MCA5 respectively), using chelating ligand and the calcination temperature was determined by the thermogravimetric analysis of the precursor mass.They acted as good fluoride adsorbent in the presence of co-ions, different pH(2–11) via chemisorption revealed from Fourier-transform infrared spectroscopy(FTIR) and photodegraded Methylene Blue(MB).The satisfactory results were for MCA1(specific surface area 25.05 m~2/g) with 97%fluoride removal at pH 7.0 for the 10 mg/L initial fluoride concentration for 1.5 g/L adsorbent dose with 45 min contact time obeying the Langmuir isotherm model with negative thermodynamic parameters and 4 mmol of MCA3 with 98.51% photodegradation for 10~(-5) mol/L MB solution obeying pseudo-second-order and pseudo-first-order kinetics respectively.The proposed photodegradation mechanism of MB was established by the FTIR and high-performance liquid chromatography(HPLC) analysis.The nanoparticles are cubic, estimated through X-ray diffraction(XRD) and transmission electron microscopy(TEM) analysis.The band gap energies, grain size, and the effective working pH were estimated by diffuse reflectance spectra(DRS), scanning electron microscope(SEM), and zero-point potential analysis respectively.A soil candle with MCA1 also fabricated for the household purpose and tested with some fluorinated field samples.The MCA3 was able to enhance the latent fingerprint on smooth surfaces.     

Enhancement of nutritional value of fried fish using an artificial intelligence approach

Frying affects the nutritional quality of fish detrimentally. In this study, using Catla catla and mustard oil, experiments were carried out in varying temperatures (140–240 °C), times (5–20 min), and oil amounts (25–100 ml/kg of fish) which established drastic reduction of 44.97% and 99.40% for polyunsaturated fatty acid (PUFA)/saturated fatty acids (SFA) and index of atherogenicity (IA) profile, respectively. Artificial neural network (ANN) was implemented successfully to provide an association between the independent inputs with dependent outputs (values of R² were 0.99 and 0.98; RMSE were 0.038 and 0.046; and performance were 0.038 and 0.067 for PUFA/SFA and IA, respectively) by exhaustive search of various algorithms and activation functions available in literature. ANN model–based meta-heuristic, stochastic optimization formalisms, genetic algorithm (GA) and particle swarm optimization (PSO), were applied to optimize the combination of cooking parameters for improving the nutritional quality of food which improved the nutritional value by maximizing the PUFA/SFA profile up to 63.05% and minimizing the IA profile to 99.64%. Multi-objective genetic algorithm (MOGA) was also employed to tune the inputs by maintaining a balance between the contrasting outputs and enhance the overall food value simultaneously with multi-objective (beneficial for health, economic, and environment-friendly) proposal. MOGA was able to improve the PUFA/SFA profile up to 44.76% and reduce the IA profile to 92.94% concurrently with the reduction of wastage of culinary media and energy consumption, following the optimized cooking condition (118.92 °C, 6.06 min, 40 ml oil/kg of fish).