The evaluation of various soil conditioners effects on the amelioration of saline-sodic soil

The soil salinity and sodicity collectively are the major problems in the soils of Pakistan and proved a continuous threat for the sustainability of agriculture.  A pot study was planned to ameliorate such problematic soils and for this purpose different soil conditioners were used viz. gypsum @ 39.078 g pot-1 soil gypsum requirement, Citric acid (CA) @ 29.067 g pot-1, H2SO4 @ 11.24 ml pot-1 and polyvinyl alcohol (PVA) @ 19.98 g pot-1 and control without any amendment and wheat was grown as a test crop. The results showed that maximum decrease in pH and SAR were 8.31 and 12.04 (mmol L-1)1/2 by application of H2SO4 and citric acid respectively. Similarly H2SO4 and citric acid treatment show significant results related to crop growth and yield. The maximum plant height (63.33cm), number of tillers (4.63), photosynthetic rate ((2.83 µmolm-2s-1), transpiration rate (0.63 molm-2s-1), stomata conductance (0.53 molm-2s-1), were by application of H2SO4. while the results related to grain yield were as maximum grain yield by H2SO4 was (15.67 g) and minimum grain yield was observed with control (6.73g). Moreover the decrease in grain yield was as H2SO4 (9.98 g) > citric acid (8.33 g) > PVA (7.36 g) > gypsum (6.12 g) > control (5.53g). From this experiment it was concluded that H2SO4 showed quick impact on soil physicochemical properties and growth parameters but gypsum and citric acid were long term and sustainable source to reclaim and to make saline-sodic soils more productive as compare to other soil conditioners. Keywords: soil conditioners, amelioration, saline-sodic soi

Caveat Emptor:The Risks of Using Big Data for Human Development

"Big Data" has the potential to facilitate sustainable development in many sectors of life such as education, health, agriculture, and in combating humanitarian crises and violent conflicts. However, lurking beneath the immense promises of Big Data are some significant risks such as 1) the potential use of Big Data for unethical ends; 2) its ability to mislead through reliance on unrepresentative and biased data; and 3) the various privacy and security challenges associated with data (including the danger of an adversary tampering with the data to harm people). These risks can have severe consequences and a better understanding of these risks is the first step towards their mitigation of these risks. In this article, we highlight the potential dangers associated with using Big Data, particularly for human development

Efficacy of exogenous application of 2, 4-Dichlorophenoxyacetic acid (2, 4-D) on growth and yield of mungbean (Vigna radiata L.)

The growth and yield promotion of mungbean in response to the use of 2, 4-Dichlorophenoxy acetic acid (2, 4-D) was investigated through a pot study which was arranged in the wire house of Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad. The study was comprised of five treatments and three replications (control, 0.2 ppm 2, 4-D, 0.5 ppm 2, 4-D, 0.8 ppm 2, 4-D, and 1 ppm 2, 4-D). The suggested dose of Nitrogen, Phosphorus and Potassium (NPK) was applied at the amount of 20, 60 and 25 kg ha-1 added as Urea, DAP and SOP, respectively at sowing time. The data regarding growth (plant height, root and shoot length, root and shoot fresh and dry weight, and total biomass), yield (grain weight, number of grains plant-1) and NPK analysis in plants and soil was recorded and statistically analyzed. The response of exogenous application of 2, 4-D was significant at all levels in improving the performance of all the growth parameters and yield as compared to untreated control treatment. Maximum performance of all the parameters was recorded at 0.8 ppm application of 2, 4-D. As the concentration of 2, 4-D increased the development of plants also showed positive effect but up to 0.8 ppm application after that it started to decrease which showed that at higher concentrations 2, 4-D acts as growth retardant

Prediction of Relative Humidity in a High Elevated Basin of Western Karakoram by Using Different Machine Learning Models

Accurate and reliable prediction of relative humidity is of great importance in all fields concerning global climate change. The current study has employed Multivariate Adaptive Regression Spline (MARS) and M5 Tree (M5T) models to predict the relative humidity in the Hunza River basin, Pakistan. Both the models provided the best prediction for the input scenario S6 (RHt-1, RHt-2, RHt-3, Tt-1, Tt-2, Tt-3). The statistical analysis displayed that the MARS model provided a better prediction of relative humidity as compared to M5T at all meteorological stations, especially, at Ziarat followed by Khunjerab and Naltar. The values of root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) were (5.98%, 5.43%, and 0.808) for Khunjerab; (6.58%, 5.08%, and 0.806) for Naltar; and (5.86%, 4.97%, 0.815) for Ziarat during the testing of MARS model whereas, the values were (6.14%, 5.56%, and 0.772) for Khunjerab; (6.19%, 5.58% and 0.762) for Naltar and (6.08%, 5.46%, 0.783) for Ziarat during the testing of M5T model. Both the models performed slightly better in training as compared to the testing stage. The current study encourages future research to be conducted at high altitude basins for the prediction of other meteorological variables using machine learning tools

Do financial development and energy efficiency ensure green environment? Evidence from R.C.E.P. economies

The issue of climate change and environmental degradation has been prevailing for the last few decades. Yet economies are further expanding due to free trade agreement which accelerates the trade of energy and carbon intensive commodities across the regions. A prominent example of such free trade is the Regional Comprehensive Economic Partnership (R.C.E.P.), which mostly remains ignored. The current research study explores the influence of financial development (F.D.) and energy efficiency (E.N.E.F.) on carbon emissions in the R.C.E.P. economies. Also, this study analyses the role of economic growth and renewable energy on environmental quality during the period from 1990 to 2020. Panel data approaches such as slope heterogeneity, crosssection dependence, and the second-generation panel unit root test are used. The non-normally distributed variables are found cointegrated. Therefore, a novel method of moments quantile regression is used. The results demonstrate that F.D. and economic growth are positively associated with CO2 emissions. At the same time, E.N.E.F. and renewable energy consumption (R.E.C.) significantly reduce the emissions level and promote a green environment in all quantiles. The environmental Kuznets curve is found valid in the R.C.E.P. economies. These results are robust as validated by Fully-Modified Ordinary Least Square – a parametric approach. A two-way significant causal association exists between carbon-economic growth, carbon-F.D., carbon- R.E.C., and carbon-E.N.E.F.. The findings suggest an enhancement in R.E.C., improvement in the E.N.E.F. approaches, and implications for green F.D. in the region

Ethnoveterinary Study of Medicinal Plants in a Tribal Society of Sulaiman Range

The aims of the present study were (i) to document ethnoveterinary plants and their formulation techniques in an unexplored region of Pakistan and (ii) to select candidate medicinal plants with high consensus factor and fidelity value for further in vitro investigation. A total of 60 informants were interviewed using semistructured questionnaire. A total of 41 plants belonging to 30 families were used to treat livestock ailments in study area. Mostly leaves (47%) were used in recipes formulation mostly in the form of decoction. Gastrointestinal infections were found more common and majority of the plants were used against cow (31) and buffaloes (24) ailments. Recovery time of majority of the recipes was three to four days. Informant consensus factor (Fic) results have shown a high degree of consensus for gastrointestinal, respiratory, and reproductive (0.95 each) ailments. Fidelity level (FL) results showed that Asparagus gracilis ranked first with FL value 93% followed by Rumex hastatus ranked second (91%) and Tinospora cordifolia ranked third (90%). Aged farmers and nomads had more traditional knowledge as compared to younger ones. Plants with high Fic and FL values could be further investigated in vitro for the search of some novel bioactive compounds and young generation should be educated regarding ethnoveterinary practices

Theoretical investigation on insulin dimer - b - cyclodextrin interactions using docking and molecular dynamics simulation

In our study, molecular docking and molecular dynamics (MD) simulations were performed in order to explore the interactions between human insulin and β-cyclodextrin (β-CD). Molecular docking study was performed using the Autodock v4.2 program to determine the number of β-CD molecules that adhere to the binding sites of insulin. A random structure docking approach using an initial ratio of 1:1 insulin-β-CD was conducted and from these, additional β-CDs were added. Molecular docking results revealed that a maximum of four β-CDs are able to bind to the insulin structure with the 1:3 insulin-β-CD ratio producing the lowest binding free energy. The docked conformations showed that hydrophobic interactions played a crucial role in insulin-β-CD conformational stability in addition to the formation of hydrogen bonds. A 50 ns MD simulation was further conducted using an NPT ensemble to verify the results obtained by molecular docking. The analysis of the MD simulation results of the 1:3 insulin-β-CD formation system conclude that a good interaction exists between insulin and β-CDs and the RMSD value obtained was 4.00 ± 0.50 Å. The RMSF profiles of insulin in the 1:3 insulin-β-CD formation also show reduced amino acid residues flexibility as compared to the free insulin system. The theoretical results indicated the presence of significant interactions between insulin and β-CD which could provide interesting insights into an insulin formulation

A field survey to identify the problems in adaptability of Direct Seeded Rice

During Kharif (July –October) 2015 a field survey study was conducted to identify the problems in adaptability of direct seeded rice (DSR) from three districts falling in Adaptive Research zone Gujranwala, Pakistan. Sixty farmers who had cultivated both transplanted rice and DSR were selected by convenience sampling method due to time and cost constraint and interviewed for primary data collection. The results revealed that DSR practice was adopted on 21.1% of the rice area on surveyed farms. Additional grain yield (11%) was estimated for traditional transplanted crop than DSR. Major problems raised by the farmers regarding DSR practice were more weed infestation, more disease/pest attack, less yield, more fertilizer requirement and more lodging factor. Total economic cost of production and net income for transplanted rice were respectively 11.3% and 9% higher than DSR. However Benefit cost ratio difference was found non-significant between both sowing methods. Expense on land preparation, labor charges for nursery management and transplanting, and irrigation expense for continuous flooding were the factors for higher cost of transplanted rice production. Therefore it was concluded that both sowing methods might be alternative to each other keeping in view the availability of labor, water and soil type