Jalhoum Mohamed E M, Abdellatif Mostafa A, Mohamed Elsayed Said, Kucher Dmitry E, Shokr Mohamed
National Authority for Remote Sensing and Space Science (NARSS), Cairo, 11843, Egypt.
Department of Environmental Management, Institute of Environmental Engineering (RUDN University), 6 Miklukho-Maklaya St, Moscow, 117198, Russia.
Heliyon. 2024 Mar 4;10(5):e27577. doi: 10.1016/j.heliyon.2024.e27577. eCollection 2024 Mar 15.
Assessing soil quality marks the initial step in precision farming and agricultural management. Developing countries like Egypt face numerous hurdles in ensuring food security due to increasing populations and limited agricultural resources. A geographic information system (GIS) and multivariate analysis were utilized in the current work to evaluate and map a soil quality index (SQI). Moreover, the land suitability of the land for two plantations of the tree's oak (), and pine (), respectively was assessed using a parametric approach. A total of 82 soil profiles were selected to fulfill the objectives of the study. Based on the samples' PC scores, and agglomerative hierarchical clustering (AHC, the data was divided into two clusters: Cluster I and Cluster II, which collectively account for approximately 57% and 43% of the total data, respectively.. . The findings indicated that land suitability for planting planted identified 2.14% of the research area as highly suitable (S1), 37.98% as moderately suitable (S2), and 59.89% as not suitable (N). Furthermore, the assessment of suitability for indicated that 50.88% of the investigated area was classified into: S1, 48.73% as S2, and 0.39% as N, which means it is not suitable for conservation activities. The research identified that soil depth beside excessive salinity and calcium carbonate as the primary soil constraints in the area in both clusters. The average soil depth, ECd and CaCO3 were 113.62 ± 12.41, 17.27 ± 10.23, 16.83 ± 6.57 in Cluster 1 and 45.43 ± 15.21, 22.42 ± 12.43, 21.55 ± 5.63 in Cluster II. The study demonstrates that integrating multivariate analysis with GIS enables a precise and streamlined assessment of the Soil Quality Index (SQI). Soil suitability modelling underscores the importance of implementing efficient management practices to attain agricultural sustainability in arid regions, particularly amidst intensive land utilization pressures.
评估土壤质量是精准农业和农业管理的第一步。像埃及这样的发展中国家，由于人口增长和农业资源有限，在确保粮食安全方面面临诸多障碍。在当前工作中，利用地理信息系统（GIS）和多变量分析来评估和绘制土壤质量指数（SQI）。此外，分别采用参数方法评估了土地对橡树（）和松树（）两种种植园的适宜性。总共选择了82个土壤剖面以实现研究目标。基于样本的主成分得分和凝聚层次聚类（AHC），数据被分为两个聚类：聚类I和聚类II，它们分别占总数据的约57%和43%……研究结果表明，种植的土地适宜性确定研究区域的2.14%为高度适宜（S1），37.98%为中度适宜（S2），59.89%为不适宜（N）。此外，对的适宜性评估表明，50.88%的调查区域被分类为：S1，48.73%为S2，0.39%为N，这意味着它不适用于保护活动。研究确定，除了盐分过高和碳酸钙外，土壤深度是两个聚类区域的主要土壤限制因素。聚类1中土壤平均深度、电导率和碳酸钙分别为113.62±12.41、17.27±10.23、16.83±6.57，聚类II中分别为45.43±15.21、22.42±12.43、21.55±5.63。该研究表明，将多变量分析与GIS相结合能够对土壤质量指数（SQI）进行精确且简化的评估。土壤适宜性建模强调了实施有效管理措施以在干旱地区实现农业可持续性的重要性，特别是在土地利用压力较大的情况下。
