فهرست مطالب نیلوفر یاراحمدی

Agricultural sector is one of the main production sectors in each country. Increasing the growth and efficiency of this sector requires the development of a proper, accurate and realistic model of crops planting based on different goals and criteria, in order to provide the benefits of the whole beneficiary community in long term. The purpose of this research was to identify, validate and rank the effective criteria on crops prioritization for being selected in the cropping pattern, using a hybrid research method of exploratory factor analysis and analytical network process. In order to achieving the research goals, in the first phase, by aid of literature reviewing, effective criteria on crops prioritization have been selected, and then by using exploratory factor analysis method and application of SPSS 25 software, these criteria have been loaded on 6 factors named: cultural and social, political, passive defense, water, environmental impacts and economics. The final step of this phase was the construction of the conceptual model of the factors and effective criteria. In second phase the criteria were ranked by using analytical network process method and application of Super Decisions software. According the results the most important criteria in the process of assessing the prioritization of crops are listed as below: “Domestic Resource Cost” with a weight of 0.2277, “consent culture” with a weight of 0.1468, “risk taking attitude of farmer” with a weight of 0.1160, and “crops’ irrigation water demand” with a weight of 0.0754. The conceptual model can facilitate the selection process of crops and ease the designing of optimal crop pattern.

Because of the key role of the agricultural sector in achievement of food security, increasing climatic variations due to global change and the dependence of agricultural yields to climatic conditions, it is essential to study the long-term relationship between climatic conditions and agricultural yields in order to coordinate agricultural activities with climate change trend. In this study, a screener algorithm considering the climatic conditions of the region has been developed to rank the most suitable agricultural products with the climatic conditions of Soumar plain in Kermanshah province. For this purpose, the sensitivity of the defined agroecosystem to climatic conditions of the region was calculated using the Shannon-Wiener index. Then, using Multiple Linear Regression method and SPSS software, regression models were developed between climatic data and crop yield data. In the next step, the accuracy of the developed models was confirmed considering the conditions of using linear regression for all models. Afterward, the weight of effective climatic parameters was determined using pairwise comparison methods. According to the results, the minimum monthly temperature parameter with weight of 0.169 and the average monthly wind speed parameter with weight of 0.032 were considered the most and the least effective climatic parameters, respectively. Finally, crops ranking in the study area was completed using TOPSIS method and calculating Ci index which shows the score of each crop. According to the results, bean, barley and canola with the Ci of 0.601, 0.537 and 0.564 and tobacco, tomato and fodder corn with the Ci of 0.376, 0.513 and 0.518 show the most and the least compatibility with the climate conditions of the region, respectively.