Effects of transgenic Bt cotton on soil fertility and biology under field conditions in subtropical inceptisol

Although there is large-scale adoption of Bt cotton by the farmers because of immediate financial gain, there is concern that Bt crops release Bt toxins into the soil environment which reduces soil chemical and biological activities. However, the majorities of such studies were mainly performed under pot experiments, relatively little research has examined the direct and indirect effects of associated cover crop of peanut with fertilization by combined application of organic and inorganic sources of nitrogen under field conditions. We compared soil chemical and biological parameters of Bt cotton with pure crop of peanut to arrive on a valid conclusion. Significantly higher dehydrogenase enzyme activity and KMnO₄-N content of soil were observed in Bt cotton with cover crop of peanut over pure Bt cotton followed by pure peanut at all the crop growth stages. However, higher microbial population was maintained by pure peanut over intercropped Bt cotton, but these differences were related to the presence of high amount of KMnO₄-N content of soil. By growing cover crop of peanut between Bt cotton rows, bacteria, fungi, and actinomycetes population increased by 60%, 14%, and 10%, respectively, over Bt cotton alone. Bt cotton fertilized by combined application of urea and farm yard manure (FYM) maintained higher dehydrogenase enzyme activity, KMnO₄-N content of soil and microbial population over urea alone. Significant positive correlations were observed for dry matter accumulation, dehydrogenase enzyme activity, KMnO₄-N content, and microbial population of soil of Bt cotton, which indicates no harmful effects of Bt cotton on soil biological parameters and associated cover crop. Our results suggest that inclusion of cover crop of peanut and FYM in Bt cotton enhanced soil chemical and biological parameters which can mask any negative effect of the Bt toxin on microbial activity and thus on enzymatic activities.     

Alternative soil quality indices for evaluating the effect of intensive cropping, fertilisation and manuring for 31 years in the semi-arid soils of India

Soil quality assessment provides a tool for evaluating the sustainability of alternative soil management practices. Our objective was to develop the most sensitive soil quality index for evaluating fertilizer, farm yard manure (FYM), and crop management practices on a semiarid Inceptisol in India. Soil indicators and crop yield data from a long-term (31 years) fertilizer, manure, and crop rotation (maize, wheat, cowpea, pearl millet) study at the Indian Agricultural Research Institute (IARI) near New Delhi were used. Plots receiving optimum NPK, super optimum NPK and optimum NPK + FYM had better values for all the parameters analyzed. Biological, chemical, and physical soil quality indicator data were transformed into scores (0 to 1) using both linear and non-linear scoring functions, and combined into soil quality indices using unscreened transformations, regression equation, or principal component analysis (PCA). Long-term application of optimum inorganic fertilizers (NPK) resulted in higher soil quality ratings for all methods, although the highest values were obtained for treatment, which included FYM. Correlations between wheat (Triticum aestivum L.) yield and the various soil quality indices showed the best relationship (highest r) between yield and a PCA-derived SQI. Differences in SQI values suggest that the control (no NPK, no manure) and N only treatments were degrading, while soils receiving animal manure (FYM) or super optimum NPK fertilizer had the best soil quality, respectively. Lower ratings associated with the N only and NP treatments suggest that one of the most common soil management practices in India may not be sustainable. A framework for soil quality assessment is proposed.     

Attenuation of N2O emission rates from agricultural soil at different dicyandiamide concentrations

An experiment was conducted to assess the role of different concentrations of dicyandiamide (DCD), a potent nitrification inhibitor, on temporal changes in nitrous oxide emission from sandy loam agricultural soil. It was found that with increasing concentration of DCD i.e. from 6 to 12% of nitrogen applied in the form of urea, there was a decrease in the both average and peak N₂O emissions. However, from 14% DCD treated soil, there was a non-significant alteration in the N₂O emission. Maximum average N₂O efflux of 217.55 μg m⁻² h⁻¹ was noted from control plots. As compared to control, there was an attenuation of 50, 58, 65, and 91% average N₂O efflux from 6, 8, 10 and 12% DCD applied pots, respectively, whereas, there was a negative average of N₂O efflux from the soil with 14% DCD treatment. The soil N content also showed a significant correlation with N₂O emission. Therefore, 12% DCD treatment has been found to be the best with regard to attenuation of nitrous oxide from sandy loam agricultural soils.     

Vertical characterization of soil contamination using multi-way modeling – A case study

This study describes application of chemometric multi-way modeling approach to analyze the dataset pertaining to soils of industrial area with a view to assess the soil/sub-soil contamination, accumulation pathways and mobility of contaminants in the soil profiles. The three-way (sampling depths, chemical variables, sampling sites) dataset on heavy metals in soil samples collected from three different sites in an industrial area, up to a depth of 60 m each was analyzed using three-way Tucker3 model validated for stability and goodness of fit. A two component Tucker3 model, explaining 66.6% of data variance, allowed interpretation of the data information in all the three modes. The interpretation of core elements revealing interactions among the components of different modes (depth, variables, sites) allowed inferring more realistic information about the contamination pattern of soils both along the horizontal and vertical coordinates, contamination pathways, and mobility of contaminants through soil profiles, as compared to the traditional data analysis techniques. It concluded that soils at site-1 and site-2 are relatively more contaminated with heavy metals of both the natural as well as anthropogenic origins, as compared to the soil of site-3. Moreover, the accumulation pathways of metals for upper shallow layers and deeper layers of soils in the area were differentiated. The information generated would be helpful in developing strategies for remediation of the contaminated soils for reducing the subsequent risk of ground-water contamination in the study region.     

Estimation of uranium and radon concentration in some drinking water samples of Upper Siwaliks, India

Uranium and radon concentration was assessed in water samples taken from hand pumps, natural sources and wells collected from some areas of Upper Siwaliks, Northern India. Fission track registration technique was used to estimate the uranium content of water samples. The uranium concentration in water samples was found to vary from 1.08 +/- 0.03 to 19.68 +/- 0.12 microg l(-1). These values were compared with safe limit values recommended for drinking water. Most of the water samples were found to have uranium concentration below the safe limit of 15 microg l(-1) (WHO, World Health Organization, Guidelines for drinking-water quality (3rd ed.). Geneva, Switzerland: WHO, 2004). The radon estimation in these water samples was made using alpha-scintillometry to study its correlation with uranium. The radon concentration in these samples was found to vary from 0.87 +/- 0.29 to 32.10 +/- 1.79 Bq l(-1). The recorded values of radon concentration were within the recommended safe limit of 4 to 40 Bq l(-1) (UNSCEAR, United Nations Scientific Committee on the Effects of Atomic Radiations, Sources and effects of ionizing radiation. New York: United Nations, 1993). No direct correlation was found between uranium concentration and radon concentration in water samples belonging to Upper Siwaliks. The values of uranium and radon concentration in water were compared with that from the adjoining areas of Punjab state, India.     

Bacterial contamination in drinking water: a case study in rural areas of northern Rajasthan, India

Acid deposition has caused detrimental effects on tree growth near industrial areas of the world. Preliminary work has indicated that concentrations of NO(3-), SO(4)(2-), F( - ) and Al in soil solutions were 2 to 33 times higher in industrial areas compared to non-industrial areas in Korea. This study evaluated soil nutrient bioavailability and nutrient contents of red pine (Pinus thunbergii) needles in forest soils of industrial and non-industrial areas of Korea. Results confirm that forest soils of industrial areas have been acidified mainly by deposition of sulfate, resulting in increases of Al, Fe and Mn and decreases of Ca, Mg and K concentrations in soils and soil solutions. In soils of industrial areas, the molar ratios of Ca/Al and Mg/Al in forest soils were <2, which can lead to lower levels and availability of nutrients for tree growth. The Ca/Al molar ratio of Pinus thunbergii needles on non-industrial sites was 15, while that of industrial areas was 10. Magnesium concentrations in needles of Pinus thunbergii were lower in soils of industrial areas and the high levels of acid cations such as Al and Mn in these soils may have antagonized the uptake of base cations like Mg. Continued acidification can further reduce uptake of base cations by trees. Results show that Mg deficiency and high concentrations of Al and Mn in soil solution can be limiting factors for Pinus thunbergii growth in industrial areas of Korea.     

DO-BOD modeling of River Yamuna for national capital territory, India using STREAM II, a 2D water quality model

The study illustrates the utility of STREAM II as a modeling package to determine the pollution load due to organic matter in the River Yamuna during its course through the National Capital Territory that is Delhi, India. The study was done for a period from 1995–2005. Model simulates the dissolved oxygen and biochemical oxygen demand parameters in a two-dimensional fashion by performing the numerical solution to a set of differential equations representing aquatic life with the help of Crank–Nicholson finite difference method. The model was simulated and calibrated through the field water-quality primary data and the secondary data which were taken from Central Pollution Control Board. The main reasons for the high river pollution is increasing population of Delhi and other states, leading to generation of huge amounts of domestic sewage into the river Yamuna. The model gave a good agreement between calibrated and observed data, thus, actualizing the validity of the model. However, discrepancies noticed during model calibrations were attributed to the assumptions adopted in the model formulation and to lack of field data.     

Adaptive nitrogen and integrated weed management in conservation agriculture: impacts on agronomic productivity,greenhouse gas emissions,and herbicide residues

Increasing nitrogen (N) immobilization and weed interference in the early phase of implementation of conservation agriculture (CA) affects crop yields. Yet, higher fertilizer and herbicide use to improve productivity influences greenhouse gase emissions and herbicide residues. These tradeoffs precipitated a need for adaptive N and integrated weed management in CA-based maize (Zea mays L.)—wheat [Triticum aestivum (L.) emend Fiori & Paol] cropping system in the Indo-Gangetic Plains (IGP) to optimize N availability and reduce weed proliferation. Adaptive N fertilization was based on soil test value and normalized difference vegetation index measurement (NDVM) by GreenSeeker? technology, while integrated weed management included brown manuring (Sesbania aculeata L. co-culture, killed at 25 days after sowing), herbicide mixture, and weedy check (control, i.e., without weed management). Results indicated that the ‘best-adaptive N rate’ (i.e., 50% basal + 25% broadcast at 25 days after sowing + supplementary N guided by NDVM) increased maize and wheat grain yields by 20 and 14% (averaged for 2 years), respectively, compared with whole recommended N applied at sowing. Weed management by brown manuring (during maize) and herbicide mixture (during wheat) resulted in 10 and 21% higher grain yields (averaged for 2 years), respectively, over the weedy check. The NDVM in-season N fertilization and brown manuring affected N₂O and CO₂ emissions, but resulted in improved carbon storage efficiency, while herbicide residuals in soil were significantly lower in the maize season than in wheat cropping. This study concludes that adaptive N and integrated weed management enhance synergy between agronomic productivity, fertilizer and herbicide efficiency, and greenhouse gas mitigation.