Document Type : Applied Article
Ph.D. Student, Agriculture Machinery Engineering Department, Faculty of Agricultural Engineering and Technology, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
Professor, Agriculture Machinery Engineering Department, Faculty of Agricultural Engineering and Technology, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran
Assistant Professor, Agricultural Engineering Research Institute, Agricultural Education and Extension Organization (AREEO), Karaj, Iran
Selection of cropping pattern is one of the main factors in increasing agricultural productivity. Optimal apportionment of land and determination of suitable crops for each region to prevent excessive consumption of inputs and reduce risks due to lack of food supply resources after scientific study of the factors affecting the cultivation pattern and considering different indicators can be achieved. The present study determines the factors affecting the cropping pattern and their prioritization. This research was conducted in Silakhor agricultural area in Dorud county, Lorestan province, Iran. The data were collected from libraries, interviews, and questionnaires. Variables that affected the cropping pattern were extracted using exploratory factor analysis then Shannon entropy-based TOPSIS method was used to prioritize crop cultivation. Factor analysis results indicated that the effective variables in selecting sustainable crop pattern in the research area can be classified into six factors including mechanization-farming, soil and climate, macro-government management, production support, social, and production margin. These factors explained 61.41% of the variance of the effective variables in the selection of cropping pattern. In addition, in the four-criterion entropy method, Access to cash capital of cultivation needed (0.236), Crop water requirement (0.233), crop profit (0.098), and cultivation area more than 1 ha (0.039) had the highest priority in choosing the cultivation pattern. They had the highest priority in selecting the pattern of cultivation. Finally, the results of TOPSIS Multi-Criteria Decision Making showed that the most influential parameters in the region's cultivation pattern were autumn sugar beet (0.598), Wheat (0.589), Barley (0.558), Canola (0.556), autumn peas (0.515). ), Rice (0.499), Quinoa (0.471), and saffron (0.390), respectively.
Ensuring the continued availability of regular food production resources is critical to food security. Food markets are supplied through domestic production and international trade. There may be a number of risks associated with supply chain disruption, commodity price fluctuations, along with other unforeseen circumstances, including natural disasters. To reduce the challenges that threaten the stability of food systems, the decision in the food sector must be increased and strengthened to be able to accommodate any changes that may result in food shortages . The fast growth of the population and the deterioration of the environment make food security, at the lowest environmental cost, essential for the sustainable development of developing countries. It is possible to reduce the risks by planning an appropriate cultivation pattern of an operational approach, based on the diverse production of farmers, especially in grain production and productivity of farmland . The advantages of the cultivation pattern include minimal consumption of fertilizers and herbicides, thus reducing food contamination with chemicals, high land use efficiency, performance stability, distribution of labor share during the growing season, less dependence on storage. Construction pointed to greater market opportunities by balancing crop production, sustainability, and long-term profitability without the need for additional financial investment will be cited . Cropping pattern changes occur under the influence of the social, economic, and environmental conditions of rural communities because of proper planning or because of an emotional response to market conditions . By prioritizing the effective criteria for reducing the sustainability of agricultural ecosystems, the researchers stated that among the ecological, social and economic criteria, the most important is related to the economic criterion . The results of a multi-criteria decision-making study showed that salinity criteria, soil organic matter, soil erosion and soil texture are considered as limiting factors of cultivation pattern in rainfed Golestan province . Researchers in analyzing the effects and factors affecting the development of saffron cultivation pattern stated that the most important components affecting the cultivation pattern are geographical factors and consumer market attractions . The results of research on the ranking of agricultural products with a multi-criteria decision-making approach showed that this method is one of the most appropriate methods in terms of priority . One of the important advantages of the TOPSIS method is that objective and subjective criteria can always be used . In different conditions and researches such as prioritizing the cultivation pattern of strategic products of Alborz province, selecting the appropriate tractor and comparing the operational management efficiency of agricultural machinery exploitation systems, researchers to finalize the research criteria and rank the options in terms of experts and methods. Expert decision makers specifically used the TOPSIS method [14, 10]. Therefore, in this study, first, the variables affecting the selection of cultivation pattern are identified among the various criteria of agricultural production and in the next step; the priority of crop cultivation is determined by relying on engineering and comprehensive methods along with practical experiences by looking at the central product model. Undoubtedly, one of the results of the cultivation pattern is food security, and in this regard, by designing a successful cultivation pattern, the effectiveness of its results can be increased.
Material and methods
Research area was located at Lower Silakhur plain, between the cities of Dorud and Boroujerd (380 36' 56 " N, 480 31' 39" E), Lorestan province, Iran. In this study, in order to gain a more accurate understanding of the factors affecting the cropping pattern, the following steps were taken from both a scientific (documentary and expert view) and a practical (farmers) perspective. A questionnaire consisting of 22 items was designed within initial 78-item with expert opinion. One hundred and fifty five questionnaires were distributed among farmers and the relevant interviews were conducted with them in the field from 2016 to 2017. To determine data suitability for factor analysis and significant correlation of variables, sampling adequacy index (KMO) and Bartlett test were used, respectively, and for analysis of principal factors, the Varimax rotation method was used in SPSSv22 software. Based on Shannon entropy method a decision matrix was used to calculate the weights of the indices. These weights were used in the TOPSIS steps to rank the options. After normalizing the decision matrix and calculating the weight of indices by using the entropy method, TOPSIS method was developed in Excel software.
Discus and Results
Based on the Kaiser Scale Mechanization-Farming factors as the first and most important factor with a specific value of 3.96 alone explain 18.03% of the variance of factors affecting cropping patterns. Soil and climate factors with 11.28%, macroeconomic policy factor with 9.88%, production support factors with 8.09% social factors with 7.90%, and marginal factors with 6.04% of variance explained. In addition, the results showed that soil chemical properties factor with 78.1%, mean precipitation with 77.9%, and quantity and quality of access to water resources with 74.1% had the highest share among groups. In this regard, the first factors can be called Mechanization-Farming factors. The next ones were climate and soil factors related to the cropping pattern, and so were components such as maintaining crop sustainability, having consistent seed, having guaranteed purchases and government incentive policies on crops in the third factor, which can also be called macroeconomic factors of government and policymaking. The fourth factor, including product insurance and cash capital needed for cultivation, was considered as supporting factors for production. The fifth were the social factors related to the cropping pattern such as farmers’ experiences and customs which were the most important characteristics of such factors because the experience of farming one or more specific crops over the years affects the selection of cropping pattern. Finally, the plant pest of the area and the average temperature of the growing season were ranked as the sixth factors influencing the crop pattern. The priority of cropping pattern with TOPSIS decision cultivation in the study area was determined by crops, Autumn Sugar beet, Wheat, Barley, Canola, Autumn Chickpea, Rice, Quinoa, and Saffron, respectively. Comparing the results of this study with previous studies on the pattern of cultivation, showed that in terms of using the expert system, determining the cropping pattern is similar to designing an expert cultivation pattern in Mazandaran . The factors affecting of cropping pattern and using multi-criteria decision-making methods, in relief with research indicators, the ranking of agricultural products is multi-criteria decision making . In addition, in prioritizing the most important indicators of crop cultivation and using expert methods, decision-making is consistent with the results of priority cultivation of agricultural products in Kermanshah .
The results obtained from the study of the effects of different factors on cropping pattern and factor analysis showed that mechanization-agronomic factors with a specific value of 3.96 justify 18% of the total variances in total plays the most important and crucial role in explaining the pattern of cultivation. Among the subsets of this factor, the presence of mechanized equipment, crop yield, and crop water requirement were particularly important with factor loads of 0.75, 0.74 and 0.74, respectively climate and macroeconomic management of the State with eigenvalues of 2.48 and 2.17, respectively, explained 21.16% of the total variance of the cropping pattern factors. This shows the crucial role of decision making in the upstream sectors. Because without motivating qualifications, it is difficult for farmers to change the pattern of cultivation, and it is necessary to encourage targeted policies to reform the pattern of cultivation. The results of the TOPSIS decision showed that sugar beet, wheat, barley and canola cultivars have the highest priority among the 8 selected crops with 0.559, 0.558, 0.555 and 0.556, respectively. The current cropping pattern of the region is mainly composed of three crops of wheat, barley and rice crops. The water supply method for rice cultivation is the use of deep wells and groundwater, which continues to lead to environmental disaster and depletion of water resources. Based on the multi-criteria decision-making results and considering the effective components of crop pattern, sugar beet and canola can be added to the region's cropping pattern by keeping the farmers' profit margin constant. Optimal design of the cropping pattern leads to policies that first allow farmers access to land and other agricultural inputs to increase farm productivity and household income and secondly to reduce the risk of food shortages in the country. The future has a major role to play in enforcing this policy effectively.