Background and Objective: Azolla plants with the capability of fixing nitrogen, potassium and phosphorus, which are used as green manure and the nutrients in the compost, can be considered as a source of nutrition for plants. This study was designed to investigate the combined effects of Azolla with organic and inorganic fertilizers on soil NPK levels on study the growth index of Populous Deltoids. Method: The Azolla were collected from ponds of Joibar city located in Mazandaran province. Azolla compost was used in combination with inorganic and organic materials and the amount of NPK in these compounds and its effects on growth parameters (height, stem diameter and leaf fresh weight) were investigated. The compost of Azolla 100% and straw 100% had the highest and the lowest NPK that resulted in significant increases in growth indices of Populus deltoides in comparison with control one. Findings: Growth Indices in the compost of Azolla 100% showed the significant increase in comparison to other fertilizer treatments (different percentages of Azolla, straw and urea). Also, the mixed manure of Azolla and organic compost (Azolla 50%+ straw 50%) (With 0. 32% nitrogen, 0. 02% phosphorus and 0. 24% K) with inorganic fertilizer of urea was significantly increased growth parameters of plant than control. Discussion and Conclusion: According to the results, compound fertilizer 50% Azolla +50% straw + urea and Azolla 100% compost were had the greatest impact on improving the soil and finaly, plants growth. Therefore, use of green manure and green manure combined with a combination of organic and inorganic fertilizers, according to the effects on soil chemical traits, resulted in fertility improvement and increase of crop and by reducing the use of chemical fertilizer in agriculture will prevent environmental pollution and its staggering costs and contribute to the sustainable development of agriculture.

Background and Objective: Phenol presence and its derivatives in water and waste water on human health and the environment is one the major concerns. Because of the toxicity of phenol and also because of the presence of even low concentrations in natural resources, water disinfection and oxidation processes can lead to the formation of additional components. This material is one of the most common organic pollutants in water. In this research, adsorption of phenol from wastewater by sawdust was simulated using intelligent techniques. Method: Intelligent techniques including multi-layer Perceptron, radial basis functions network and support vector regression were used. To design the network structure as well as the training and testing of 125 sets of experimental data is used. Performance evaluation criteria and stop network consists of % AARE and R2, which is used for all three models. Findings: All models compared results showed that the support vector regression with 0. 5132 and 0. 979, respectively, for %AARE and R2 is the best model. All models are better results than the quadratic polynomial model showed. Discussion and Conclusion: Models showed good agreement with experimental data. The optimum conditions for the removal of phenol were 127. 6 mg/l of initial phenol concentration, 0. 84 g/l of adsorbent dose, natural pH value of 3. 62 and 146. 9 min of contact time, under these conditions the maximum removal efficiency was 91. 23%.