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Showing 2 results for Sheikhzeinoddin

A. Sheikhzeinoddin, A. K. Esmaeili1 , M. Noshadi,
Volume 19, Issue 74 (Winter 2016)
Abstract

Chemical fertilizers have important role in modern agriculture, and in the other hand led to rigid environmental pollution. Urea fertilizer is one of the most widely used and least expensive nitrogen fertilizers in Iran. Since it is high solubility in water a significant of it, if irrigation or precipitation is heavy, easily washed and led to change to change the quality of groundwater, rivers or seas. Hence, in this study the effects of deficit irrigation and fertilization on pollution using SWAT for Tashk-Bakhtegan basin (land area between Dorudzan dam and Khan Bridge) were simulated. This model by comparing model outputs with actual observations of hydrological, crop yield (wheat, barely, corn and rice) and nitrate by using SUFI2 algorithm in SWAT_CUP software were calibrated and validated. Then the calibrated model used to evaluate different management strategies (e.g. irrigation and fertilizer amount). When the impacts of different levels of urea (0 to 70 percent reduction in urea application) were modeled, yield of these crops reduced between 1 to 27, 0.8 to 24, 0.42 to 21 and 0.47 to 9 percent for wheat, barely, corn and rice, respectively. However, these tends to decline nitrate leaching 16-81, 18-80, 15-85 and 12.5 to 83.6 percent, respectively for these crops.  Therefore, by comparing yield and nitrogen loss changes, this result can conclude that a significant reduction in nitrogen loss by minimum cost on yield can achieved by optimize fertilizer application. 


S. Motalebani, M. Zibaei, A. Sheikhzeinoddin,
Volume 24, Issue 3 (Fall 2020)
Abstract

The interaction of population growth, technological improvement and climate change have impacted severely on agricultural and environmental sustainability. In Iran, conventional tillage practice has resulted in soil erosion and loss of soil organic matter. In this regard, Conservation Agriculture (CA) forms part of this alternative paradigm to agricultural production systems approaches and can be regarded as a means to enhancing food productivity, reducing poverty, and mitigating the consequences of climate change in rural households. The objectives of this study were to examine the determinants and impacts of CA technology on wheat yield, poverty gap and water use. To this end, an endogenous switching regression (ESR) model was employed to estimate the impacts of CA technology on continuous variables such as wheat yield, poverty gap and water use. A sample of 260 farmers from Zarghan district was selected for interview collection of necessary farm level data. The results indicated that in the select equation of ESR model, ten coefficients (out of 12) are significant at the 5% level or higher. Knowledge of soil quality, access to credit, access to information, education, farm size, ownership of machinery, participation in agricultural extension activities and farmer’ perception have positive and significant effects on the probability of adopting CA. In contrast, variables such as the distance to shopping center and number of land parcels have negative and significant influence on adoption. Also, the results of ESR model and counterfactual analysis showed that wheat yield would increase by 1.05 tons and poverty gap and water use would decrease by 20% and 910 cubic meters per hectare respectively if farmers adopt CA technology.


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