Jayjit Majumdar

In vitro assessment on the impact of soil arsenic in the eight rice varieties of West Bengal, India.

Rice is an efficient accumulator of arsenic and thus irrigation with arsenic-contaminated groundwater and soil may induce human health hazard via water-soil-plant-human pathway. A greenhouse pot experiment was conducted on three high yielding, one hybrid and four local rice varieties to investigate the uptake, distribution and phytotoxicity of arsenic in rice plant. 5, 10, 20, 30 and 40 mg kg(-1) dry weights arsenic dosing was applied in pot soil and the results were compared with the control samples. All the studied high yielding and hybrid varieties (Ratna, IET 4094, IR 50 and Gangakaveri) were found to be higher accumulator of arsenic as compared to all but one local rice variety, Kerala Sundari. In these five rice varieties accumulation of arsenic in grain exceeded the WHO permissible limit (1.0 mg kg(-1)) at 20 mg kg(-1) arsenic dosing. Irrespective of variety, arsenic accumulation in different parts of rice plant was found to increase with increasing arsenic doses, but not at the same rate. A consistent negative correlation was established between soil arsenic and chlorophyll contents while carbohydrate accumulation depicted consistent positive correlation with increasing arsenic toxicity in rice plant.

Biotransformation and bioaccumulation of arsenic by Brevibacillus brevis isolated from arsenic contaminated region of West Bengal.

Microorganisms influence the fate of metals in environment. Increasing anthropogenic and geogenic activity had increase the risk of arsenic pollution and this has forced the future research area to involve microbes-metal toxicity to achieve bioremediation. The present study deals with the role of arsenite transforming bacteria and incorporates them into remediation design. Sample was collected from Haringhata in Nadia district which is a known arsenic contaminated zone. Out of six isolated bacteria one bacterium revealed as arsenic tolerant bacteria which shows molecular similarity with Brevibacillus brevis from 16s rRNA studies. It can tolerate upto 1000 mg/L of arsenite and 500 mg/L of arsenate. Both the arsenic species has toxic effects on its protein concentration. The strains can tolerate upto a certain limit after that their growth ceased. This strain can accumulate and also transform arsenite to arsenate. The transformation capacity of strain was assessed qualitatively and quantitatively. The strain can transform 90% of arsenite to arsenate. But the transformation capacity only reveals as detoxification mechanism and has no relation with their respiration. Morphological biochemical and molecular identification was done. As arsenate is absorbed into iron oxyhydroxides and get immobilize thus a remediation mechanism can be designed with this strain.

Impact of raking and bioturbation-mediated ecological manipulation on sediment–water phosphorus diagenesis: a mesocosm study supported with radioactive signature

The study examined the impact of raking and fish bioturbation on modulating phosphorus (P) concentrations in the water and sediment under different trophic conditions. An outdoor experiment was set to monitor physicochemical and microbiological parameters of water and sediment influencing P diagenesis. A pilot study with radioactive 32P was also performed under the agency of raking and bacteria (Bacillus sp.). Raking was more effective in release of P under unfertilized conditions by significantly enhancing orthophosphate (35%) and soluble reactive phosphate (31.8%) over respective controls. Bioturbation increased total and available P in sediments significantly as compared to control. The rates of increase were higher in the unfertilized conditions (17.6–28.4% for total P and 12.2 to 23.2% for available P) than the fertilized ones (6.5–12.4% for total P and 9.1 to 15% for available P). The combined effects of raking and bioturbation on orthophosphate and soluble reactive phosphate were also stronger under unfertilized state (54.5 and 81.8%) than fertilized ones (50 and 70%). The tracer signature showed that coupled action of introduced bacteria and repeated raking resulted in 59.2, 23 and 16% higher counts of radioactive P than the treatments receiving raking once, repeated raking and bacteria inoculation, respectively. Raking alone or in sync with bioturbation exerted pronounced impact on P diagenesis through induction of coupled mineralization and nutrient release. It has significant implication for performing regular raking of fish-farm sediments and manipulation of bottom-grazing fish to regulate mineralization of organic matter and release of obnoxious gases from the system. Further, they synergistically can enhance the buffering capacity against organic overload and help to maintain aquatic ecosystem health.

Nutrient modeling of an urban lake using best subset method

Lakes are functionally integral and biologically complex freshwater ecosystems which provide a vast array of ecosystem goods and services to society. Nowadays aquatic ecosystems are being used, misused and abused by diverse anthropogenic activities at an unprecedented rate. The management of lake water quality is usually directed to resolution of conflicts between maintenance of desirable water quality and human-induced degradation of aquatic environment. Nutrients play a decisive role in determining lake’s environmental state through regulation of its primary production. The present study on Saheb Bundh Lake located in Purulia District, West Bengal, India, was undertaken to assess the status of nutrients (nitrogen and phosphorus) subject to certain anthropogenic activities, and to construct models using best subset method which could be adopted as a nutrient management tool. The water samples were monitored for different physicochemical parameters adopting standard methods. It was found that the set of variables including turbidity, temperature, pH, redox potential and total hardness has been championed as the best subset of water quality explaining the dynamics of total phosphorus concentration of freshwater Saheb Bundh Lake. The suite of factors comprising dissolved oxygen, pH, temperature, turbidity and total hardness has been proved as the best subset for estimating total nitrogen concentration. The models developed have been validated for total phosphorus and total nitrogen concentration. For total phosphorus, the model values were found to be very close to the measured values but the values varied widely for total nitrogen, championing the former as a very potent down-to-earth model.