| چکیده انگلیسی مقاله |
Achieving self-sufficiency in agricultural production -especially in developing countries- requires accurate land suitability assessments for various crop types. Such evaluations serve as essential tools for making informed land-use decisions and are crucial for the sustainable development of agricultural resources. Although numerous land suitability studies have been conducted at local scales, no comprehensive national-level assessment has been undertaken to date. To address this gap, existing soil survey studies across Iran were compiled, digitized, and harmonized. Using satellite imagery, land-use maps, and agro-climatic zoning data, soil units in irrigated plains nationwide were identified for evaluating land suitability for irrigated cultivation of sunflower, soybean, canola, and sesame. Subsequently, climatic, soil, and topographic parameters were integrated into a custom-developed software system based on the FAO land evaluation framework, employing the parametric square root method. The results revealed that among approximately 4 million hectares (Mha) evaluated for sunflower cultivation, 158 thousand ha (Tha) were classified as S1 (highly suitable), 1.2 Mha as S2 (moderately suitable), 1.36 Mha as S3 (marginally suitable), 585 Tha as N1 (currently unsuitable), and 702 Tha as N2 (permanently unsuitable). For soybean across 1.8 Mha, 27 Tha fell into S1, 500 Tha into S2, 548 Tha into S3, 316 Tha into N1, and 450 Tha into N2. Of the 5.5 Mha evaluated for canola, 195 Tha were S1, 1.6 Mha S2, 2.4 Mha S3, 596 Tha N1, and 804 Tha N2. For sesame across 1.7 Mha, 23 Tha were S1, 135 Tha S2, 554 Tha S3, 460 Tha N1, and 537 Tha N2. Multivariate analysis of variance (MANOVA) confirmed the reliability of the land suitability classification. The primary limiting factors for sunflower cultivation included soil pH, texture, and, especially in unsuitable classes, salinity, sodicity, calcium carbonate content, and slope. For soybean, organic carbon, climate, slope, salinity and sodicity were the key constraints; for canola, pH, texture, salinity, and sodicity; and for sesame, organic carbon, pH, salinity, and sodicity were the most limiting. The results and spatial maps generated in this study provide a robust decision-support tool for farmers, producers, and policymakers, enabling more informed planning and targeted cultivation of oilseed crops across Iran's irrigated plains. |