Document Type : Applicable
Authors
1 Ph.D. Student, Department of Soil Science, College of Agriculture Sciences, Lorestan, Iran
2 Professor, Department of Soil Science, College of Agriculture Sciences, Lorestan, Iran
3 Associate Professor, Department of Soil Science, College of Agriculture Sciences, Ilam, Iran
4 Assistant Professor, Department of Soil Science, College of Agriculture Sciences, Lorestan, Iran
Abstract
Introduction Assessing land suitability and determining its production potential to manage soil and land resources is one of the best sustainable agricultural policies. Barley is the second most cultivated crop in Iran after wheat. However, all soils in Iran are equally suitable for barley production. This study was conducted with the aim of evaluating the suitability of land for barley cultivation using a spatial model integrated with Geographical Information System (GIS).
Materials and Methods The suitability of the land for barley cultivation is affected by various factors including (percentage of sand, percentage of silt, percentage of clay, percentage of saturated moisture, structure, percentage of surface gravel, water retention capacity, organic matter, nitrogen, phosphorus, potassium, EC, CEC, SAR, CaCO3 and pH) that were identified in the study area. In order to evaluate the suitability of land for the production of barley crops, Cumulative Quality Index (IQI) and Numerical Quality Index (NQI) were used with two series of data sets including: Total Data Set (TDS) and Minimum Data Set (MDS) and the results of this The indices were compared with two indices, storie and square root.
Results and Discussion 17 measured parameters were used as the total data set (TDS) and 5 parameters (sand percentage, clay percentage, silt percentage, saturated moisture and pH) were used as the minimum data set (MDS). Also, the results showed that using the data set The minimum (MDS) provides a closer estimate to the storied and square-root methods compared to using the total data set (TDS), thus even considering a limited number of effective soil properties with respect to spending less time and money on quality assessment. Soil and agricultural management can provide better results.
Conclusion By calculating various indices and comparing them with the more common storie and square root methods, it becomes possible to survey and monitor land using new techniques. This helps validate the accuracy of the index performance. With the square root and storie techniques, the value of each parameter is categorised based on sources and conducted studies, and the requirements of the barley plant. Each parameter receives a specific grade. Considering the assigned grades and comparing them with the estimated values from the ground experiments, it is possible to identify which areas of land are more or less suitable for the intended purpose. Satellite images combined with ground observation data provide valuable information for land evaluation. The results showed that most of the units in the storie model and the square root were placed in the medium suitability class (S2) for barley production. Comparing the correlation between land suitability assessment methods and measuring soil quality indices method showed that there is the highest correlation between the NQIMDS method and the square root. In general, it can be said that the soil quality index can provide better results with minimum data set and less time and cost for soil quality assessment and agricultural management. The soil maps produced for agricultural suitability analysis in this research can serve as an effective aid in decision-making processes. Subsequent research should concentrate on employing new predictive tools to enhance forecasting abilities. Most studies have used fundamental GIS techniques for resource allocation. GIS is a potent tool for spatial analysis in resource allocation. Since land resources are decreasing rapidly, land use planning should be accomplished efficiently to recognize new areas for crop production. The use of advanced simulation software assists in the reduction of redundancy within other processes while simultaneously increasing their accuracy. Consequently, researchers must concentrate on carrying out studies concerning new and developed GIS software. Unmanned aerial vehicles (UAVs) could enhance accessibility, and therefore improve the effectiveness of resource allocation (Yu et al., 2014). Modelling techniques can be employed to evaluate the practical impact of resources.
The results of this research can be useful in managerial decisions. In future studies, the use of new predictive tools should be considered. As land resources are rapidly decreasing, effective land use planning should be considered to identify new crop production areas. The use of advanced simulation software helps to eliminate the redundancy of other processes and increase accuracy (82, 93). Therefore, researchers should focus on conducting studies related to new and improved GIS software. Unmanned aerial vehicles (UAVs) may increase access to increase the effectiveness of resource allocation (103). Modeling techniques can be used to assess the practical impact of resources.
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