Open Access Original Research Article

Response of Pigeonpea (Cajanus cajan L.) to Seed Polymerization with Micronutrients and Foliar Spray at Different Growth Stages

Mallikarjun G. Handiganoor, S. B. Patil, S. N. Vasudevan

International Journal of Environment and Climate Change, Page 205-213
DOI: 10.9734/BJECC/2017/37999

Aim: To study the response of Pigeonpea to seed polymerization with micronutrients and foliar spray at different growth stages.

Place of Study: Field experiment was conducted during kharif 2014 at Main Agricultural Research Station, College of Agriculture, University of Agricultural Sciences, Raichur.

Methodology: The present study consisted of 16 different treatments wherein fresh seeds of pigeonpea were treated with different micronutrients viz., Potassium molybdate (2 or 4 ml per kg of seed), ZnSO4 (2 or 4 ml per kg of seed) and boron (2 or 4 ml per kg of seed) either individually or in combinations by using polymer at the rate of 6 ml per kg of seed which was standardized in the laboratory experiment. In addition, two foliar sprays as per the treatments either individually or in combination at an interval of 10 days during flowering stage (75 and 85 DAS) were given [Potassium molybdate (0.1%), (Zinc sulphate (0.5%) in EDTA form, Borax (0.2%)]. Various observations on growth parameter such as plant height, leaf area index and finally seed yield were recorded, analysed statistically to study the respose of Pigeonpea to seed polymerization with micronutrients and foliar spray at different growth stages.

Results: Among the different treatments imposed, seed polymer coating (@ 6 ml/kg) of pigeonpea seeds with the combination of potassium molybdate + ZnSO4 + boron (each @ 2 g / kg) of seed along with two foliar sprays of potassium molybdate (0.1%) + zinc sulphate (0.5%) in EDTA form + borax (0.2%) at an interval of 10 days during flowering stage (75 and 85 DAS) recorded significantly maximum plant height (69.2 cm, 146.7 cm and 184.7 cm), higher leaf area index (2.48, 3.08 and 2.91) at 45, 90 and 120 DAS respectively, Number of branches per plant (58.20) and highest seed yield (16.30 q) per hectare as compared to control.

Conclusion: Seed polymerization (6 ml per kg of seed) of pigeonpea seeds with the combination of micronutrients namely, potassium molybdate + ZnSO4 + boron each at 2g per kg of seed with two foliar sprays (0.1% + 0.5% + 0.2% respectively, potassium molybdate and ZnSO4 in EDTA form) at an interval of 10 days during flowering stage (75 and 85 DAS) resulted in better establishment of seedlings and produced higher growth response at all stages of growth under study thus, increasing the growth and seed yield. Seed polymer coating also acts as economical tool to enhance the efficient utilization of nutrients to mitigate the adverse climatic conditions especially in rain-fed condition.

Open Access Original Research Article

Estimating Surface CO2 Flux Based on Soil Concentration Profile

Salmawati ., K. Sasaki, S. Yuichi

International Journal of Environment and Climate Change, Page 214-222
DOI: 10.9734/BJECC/2017/38328

Aims: To estimate the surface CO2 flux derived from CO2 concentration profiles and to validate the results by previous data of surface CO2 flux obtained from the measurements using close-chamber method.

Study Design: The measurement of soil CO2 concentration profile, soil properties, and soil temperature was carried out to estimate surface CO2 flux using the derived model of mass balance equation. The results were subsequently compared with measurements of surface CO2 flux using close-chamber method.

Place and Duration of Study: INAS field located in Ito Campus of Kyushu University (Japan) from November 2015 to March 2016.

Methodology: CO2 gas was sampled in four different depths to analyze its concentration within the soil layer. Soil temperature was monitored throughout the measurement and soil properties such as density, porosity and moisture content were measured as well to estimate the diffusion rate. Derived from mass balance equation, the surface CO2 flux was estimated. It was validated using the previous measurement data of surface CO2 flux using close-chamber method that had been conducted formerly at the same location.

Results: A total of seven measurements of soil CO2 concentration profile showed that the CO2 concentration increased with soil depth and it was fitted with logarithmic trend (R2 = 0.981 in average). A range of CO2 concentration values was measured at each depth, i.e., 1300 to 8700 ppm at 0.1 m depth; 2500 to 10800 ppm at 0.2 m depth; 4200 to 13200 ppm at 0.3 m depth; and 5800 to 16500 ppm at 1.0 m depth. High CO2 concentration in 0.1 m soil depth indicated high surface CO2 flux.

Conclusions: Soil CO2 concentration in INAS field increased following a logarithmic trend. Based upon this trend, an equation to estimate the surface CO2 flux was proposed using derived model from mass balance equation and gas diffusion model. The estimated surface CO2 flux was compared and showed a good agreement with measured one. The equation presented herein is potentially suitable to estimate the surface CO2 flux.

Open Access Original Research Article

Detecting Non-negligible New Influences in Environmental Data via a General Spatio-temporal Autoregressive Model

Yuehua Wu, Xiaoying Sun, Elton Chan, Shanshan Qin

International Journal of Environment and Climate Change, Page 223-235
DOI: 10.9734/BJECC/2017/37044

In some environmental problems, it is required to find out if new influences (e.g., new influences on the ozone concentration) occurred in one area of the region (named as a treatment area) have affected the measurements there substantially. For convenience, the area of the region that is free of influences is named as the control area. To tackle such problems, we propose a change-point detection approach. We first introduce a general spatio-temporal autoregressive (GSTAR) model for the environmental data, which takes into account effects of different spatial location surroundings, seasonal cyclicities, temporal correlations among observations at the same locations and spatial correlations among observations from different locations. An EM-type algorithm is provided for estimating the parameters in a GSTAR model. We then respectively model the data collected from the treatment and control areas of the region by the GSTAR models. If new influences occurred in the treatment area are not negligible, there should be detectable changes in the time-dependent regression coefficients in the GSTAR model for that area compared to those in the GSTAR model for the control area. A change-point detection method can be applied to the differences of regression coefficient estimates of these two models. We illustrate our method through one real data example of daily ozone concentration measurements and one simulated data example with two scenarios.

Open Access Original Research Article

Characterization of Particulate Matter in Urban Environments and Its Effects on the Respiratory System of Mice

Venkatareddy Venkataramana, Azis Kemal Fauzie, Sreenivasa .

International Journal of Environment and Climate Change, Page 236-251
DOI: 10.9734/BJECC/2017/36547

Aims: To investigate the characteristics of ambient particulate matter (PM) and its impacts on animal respiratory system.

Place and Duration of Study: The study was conducted in urban area of Mysore city from 2014 to 2017.

Methodology: The elemental composition, image interpretation, and size distribution of particles was analysed using energy dispersive X-ray spectroscopy, scanning electron microscopy, and dynamic light scattering methods, respectively. Bronchoalveolar lavage analysis was performed to determine the differential cell counts of leucocytes and lymphocytes in the mice lungs. Histological and histopathological studies have been demonstrated to observe the effect of PM exposure on the lungs tissue of mice.

Results: The particle characterization analysis found that roadside PM was dominated by 56% black carbon and trace amount of metal elements. The analysis also shows that almost 90% of ambient particulate matter collected in the urban traffic roads was fine particles (PM2.5). By using bronchoalveolar lavage fluid, bronchial biopsies studies have found the compositional changes in neutrophils, eosinophils, mast cells, monocytes and lymphocytes after exposure to PM. Elevated expression and concentrations of inflammatory mediators have similarly been observed in the respiratory tract of mice. The pathological change like degeneration of alveolar region, pycnotic nuclei, and intercellular spaces with prominent vacuolization in epithelial cells followed by parenchyma and accumulation of particle laden macrophages was evident.

Conclusion: Exposure to PM induces pathological changes, differential cell counts, and inflammatory response in the mice lungs in a dose and duration dependent pattern.

Open Access Original Research Article

Modelling of Soil Loss through RUSLE2 for Soil Management in an Agricultural Field of Uccle, Belgium

M. N. A. Siddique, J. Sultana, M. R. Abdullah, Kamrun Naher Azad

International Journal of Environment and Climate Change, Page 252-260
DOI: 10.9734/BJECC/2017/35336

Revised universal soil loss equation (RUSLE2) was applied to assess the soil loss in an agricultural field of Uccle, Belgium. Determination of soil loss required lots of information and data sets from various variables related to RUSLE2 in different formats scales. The effect of each factor affection soil loss and or erosion was estimated. Soil loss was influenced by soil properties (textural class), rainfall, topography (slope gradient), crop management and conservation practices (soil cover, type of tillage). The influence of erosion control practices (up and down slope ploughing, perfect contouring and buffer strip) on soil loss was also analysed. Results indicated that among three textural class of soils highest loss found in the silty soil followed by loamy sand and clayey soil had the least soil loss. This showed that the silty soil had the highest erodibility. It was evident from the modelling that as the slope steepness and slope length increased the soil loss increased, but when the slope steepness and slope length were reduced the soil loss decreased. Soil cover and tillage contributed greatly in soil erosion. The bare soil (silt) had the highest soil loss 22 Mg ha-1yr-1 but the dense grass cover had the lowest soil loss of 0.034 Mg ha-1yr-1. While the conventional tillage had higher soil loss 15 Mg ha-1yr-1 compared with the conservation tillage 11 Mg ha-1yr-1. In case of conservation practices, filter strips had the lowest soil loss from detachment of 4.4 Mg ha-1yr-1 but the most important is that despite the detachment very little soil leaves the field as indicated by the slope delivery 0.00092 Mg ha-1yr-1. Ploughing up and down the slope resulted in the highest soil (39 Mg ha-1yr-1) loss and should be discouraged. These results will be used for soil protection measures and land use planning in agriculture.