Synthesis of mg/al layered double hydroxide (LDH) nanoplates for efficient removal of nitarate from aqueous solutions

Leaching of nitrate is an important issue on the losses of nitrate from agriculture soils in temperate zone. Decomposition of plants and other organic residues in the soil and improper discharge of sewage lead to the presence of nitrates in the sources of surface and groundwater and flowing water drainage in agricultural drainage networks and their pollution. This study aimed to study the potential use of chloride layered double hydroxide (LDH) nanoplates to remove nitrate from aqueous solutions. The nano-material of chloride-LDH was made by hydrothermal technique and then, its characteristics were specified through scanning electron micrograph and removal of nitrate from aqueous solution by the minerals was investigated in terms of pH, time, speed of shaker, different concentrations of adsorbent and surface adsorption isotherm. Microscopic images of built nanoplates were examined using FESEM and SEM electron microscope with two magnifications. The thickness of nanoplates was about 20nm and their diameter was about 250 nm. Magnified image of the synthesized nanostructures shows squamous-shape. Surface adsorption isotherm of nitrate by chloride- LDH nanoplate was explained with Langmuir model shown with the values greater than 2R. In surface adsorption of nitrate, the optimal values were measured as following: pH = 7, speed = 250 rpm, time = 45 min, concentration of adsorbent = 0.1gr.  This material could adsorb nitrates from aqueous solutions efficiently and effectively.Keywords: pollution, nitrate, layered double hydroxide, hydrothermal, surface adsorptio

The Growth Analysis of Corn (Zea mays L. cv. SC 604) With Different Fertilizers Application

To investigate the responses growth indices of corn (Zea mays L. cv. SC 604) to using plant growth promoting rhizobacteria (PGPR) and phosphate solubilizing microorganisms (PSM) and rhizobacteria, a field experiment was conducted during 2008. The study was arranged in split plot experiment based on randomized complete block design with three replications. Three levels of manures, consisted of 20 Mg.ha-1 farmyard manure, 15 Mg.ha-1 green manure and check or without any manures assigned to main plots and eight levels of fertilizer combinations (consisted of 1-NPK or recommended fertilizer application; 2-NPK+PSM+PGPR; 3-NP50%K+PSM +PGPR; 4-N50%PK+PSM+ PGPR; 5-N50%P50%K+PSM+ PGPR; 6-PK+PGPR; 7-NK+PSM and 8-PSM+ PGPR) to sub plots. Results showed that the maximum dry matter (13/2 g.m-2), leaf area index (3/8) and crop growth rate (34/5 g.m-2.day-1) were, produced by using both farmyard manure and application of NPK plus biofertilizers. Application of green manure and biofertilizer significantly increased dry matter by 11% compared to control. Meanwhile, farmyard manure and green manure application markedly increased the leaf area index by 17 and 10%, respectively. NPK treatment in farmyard manure plots and inoculation of PGPR and PSM significantly increased crop growth rate in corn plants compared to green manure and control plots. However, inoculation of biofertilizer and reducing P application by 50% did not significant influence growth indices such as total dry matter accumulation, leaf area index, and crop growth rate significantly. In conclusion, it seems that biofertilizers could be recommended as an effective option to reduce phosphate chemical fertilizers, improve the growth indices of corn plants, which ultimately result in grain yield increase

The Effect of Trichoderma harzianum and Cadmium on Tolerance Index and Yield of Barley (Hordeum vulgare L.)

To investigate the effect of Trichoderma harzianum, as a bioabsorbant to ameliorate the harmful effects of cadmium (Cd) on growth and yield of barley (Hordeum vulgare L. variety ‘Sahra’), a factorial pot experiment based on completely randomized design with three replicates was conducted. Trichoderma harzianum withtwo levels (with and without inoculation) and cadmium nitrate with four levels (0, 50, 100 and 150 mg.L-1) were the treatments. Results of ANOVA revealed that there was a significant interaction between Trichoderma and cadmium nitrate in terms of biological yield, straw yield, harvest index, spike number per plant and seed number per spike. Mean comparisons showed that Trichoderma inoculation at all Cd levels significantly improved both biological and straw yields. Trichoderma at 50 and 100 mg.L-1 of Cd also increased the spike number per plant (up to 120 and 66%, respectively) significantly. Increasing Cd levels decreased seed yield (19%), 1000 seed weight (18%), partitioning coefficient (57%) and tolerance index (23%) significantly. Inoculation of Trichoderma into growth medium had a significant effect on seed yield and tolerance index (up to 17 and 22%, respectively). In conclusion, Trichoderma harzianum inoculation at lower concentrations of Cd (50 and 100 mg.L-1) could be effective to improve growth parameters of barley plant

New Fuzzy Model for Risk Assessment Based on Different Types of Consequences

A new risk assessment methodology by using fuzzy logic is proposed in this paper. The new Fuzzy Inference System (FIS) was established by the Mamdani algorithm based on different consequences of an incident. A combination of two FIS formed the proposed fuzzy method. Human knowledge and brainstorming were the devices for making the rules and interdependencies between variables in the new model. Different types of consequences and effective parameters were considered as inputs for the first fuzzy inference system. The final consequence was the preliminary result of the first inference model. It added to the probability of failures, as inputs of the second inference model. The result of the second inference model was the risk factor, which was considered as the final output of the proposed new fuzzy model. This model makes risk assessment more convenient in the absence of suitable data. In addition, decision-making will be easier, since its results are more understandable than the results of classical methods. A case study and a comparison between the classic method and the new fuzzy model illustrated that the results of the proposed model are more accurate, reliable and convenient for use in decision-making

New Fuzzy Model for Risk Assessment Based on Different Types of Consequences

A new risk assessment methodology by using fuzzy logic is proposed in this paper. The new Fuzzy Inference System (FIS) was established by the Mamdani algorithm based on different consequences of an incident. A combination of two FIS formed the proposed fuzzy method. Human knowledge and brainstorming were the devices for making the rules and interdependencies between variables in the new model. Different types of consequences and effective parameters were considered as inputs for the first fuzzy inference system. The final consequence was the preliminary result of the first inference model. It added to the probability of failures, as inputs of the second inference model. The result of the second inference model was the risk factor, which was considered as the final output of the proposed new fuzzy model. This model makes risk assessment more convenient in the absence of suitable data. In addition, decision-making will be easier, since its results are more understandable than the results of classical methods. A case study and a comparison between the classic method and the new fuzzy model illustrated that the results of the proposed model are more accurate, reliable and convenient for use in decision-making

Effects of long-term municipal waste compost application on the concentrations of macro elements and yield of rice

An experiment was conducted as randomized complete block design with three replications and 14 fertilizer treatments in year 2014. The treatments were including the control, application of chemical fertilizers according the soil analysis, application of 15, 30 and 45 tons of municipal  waste compost per ha as simple and with 25, 50 and 75% of chemical fertilizers. The results revealed that the 7 years using of municipal waste compost significantly increased the concentrations of nitrogen, phosphorus and potassium of the soils and rice grains and it improved the yield of rice as well. The highest concentrations of macro-nutrients (Nitrogen, Phosphorus and Potassium) were obtained in the treatment of 45 t/ha of municipal waste compost + 75% chemical fertilizers. The concentrations of nitrogen, phosphorus and potassium were increased 73.68, 230.0 and 30.74%, respectively, compared to the control treatment. Treatment of 45 t/ha + 25% of chemical fertilizer had the highest 1000 grains weight. The percentage of 1000 grains weight was increased 9.82 compared to the control treatment. The highest yield of pad was obtained by using of 45 tons + 25% of chemical fertilizers that compared to the control treatment showed 51.33% increase. Finally, from the results, it can be concluded that the combination of municipal waste compost and chemical fertilizers are reliable organic waste and fertilizers management strategy to increase the concentrations of macro-nutrients in rice and increase the rice yield as well

New Fuzzy Model for Risk Assessment Based on Different Types of Consequences

A new risk assessment methodology by using fuzzy logic is proposed in this paper. The new Fuzzy Inference System (FIS) was established by the Mamdani algorithm based on different consequences of an incident. A combination of two FIS formed the proposed fuzzy method. Human knowledge and brainstorming were the devices for making the rules and interdependencies between variables in the new model. Different types of consequences and effective parameters were considered as inputs for the first fuzzy inference system. The final consequence was the preliminary result of the first inference model. It added to the probability of failures, as inputs of the second inference model. The result of the second inference model was the risk factor, which was considered as the final output of the proposed new fuzzy model. This model makes risk assessment more convenient in the absence of suitable data. In addition, decision-making will be easier, since its results are more understandable than the results of classical methods. A case study and a comparison between the classic method and the new fuzzy model illustrated that the results of the proposed model are more accurate, reliable and convenient for use in decision-making