Predictive Mapping of Soil Micronutrients Using Geographic Information System for Site Specific Management Interventions in a Semiarid Farm, India

T. Gorai, Nayan Ahmed, Rabi N. Sahoo
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Abstract

Deficiency of soil micronutrients has an adverse impact on crop productivity in intensive agriculture. Plant availability, spatial pattern and distribution of soil micronutrients such as iron (Fe), manganese (Mn), zinc (Zn) and copper (Cu) content in surface soils were evaluated for an agricultural farm in semiarid region of India. Other soil properties viz. soil pH, electrical conductivity (EC), soil organic carbon (SOC) content and equivalent calcium carbonate (CaCO3) content at the farm were also analysed to depict the soil chemical environment, controlling micronutrient availability. Plant available micronutrient contents within farm soils had very high data variability (coefficient of variation >30%). Soil available micronutrients content were negatively correlated with soil pH and positively correlated with SOC content. As per semivariogram analysis, plant available Fe, Mn, Zn and Cu content within farm soils had moderate spatial dependency as indicated by nugget to sill ratio between 0.30 and 0.50 and had spatial parameter ranges of 404, 801, 954 and 1529 m, respectively. Prediction map of plant available Fe content by inverse distance weightage (IDW) method showed a few patches of iron deficiency (< 4.50 mg kg-1) and a marginal level (4.50 - 9.00 mg kg-1). Spatial distribution map of plant available Zn content through lognormal ordinary kriging method indicated a patch of marginal Zn level (0.60 - 1.20 mg kg-1) within the farm soils. Farm scale spatial variability maps of plant available Mn and Cu content, generated by ordinary kriging method with good accuracy and effectiveness, indicated its adequate level with respect to crop nutrition. The spatial distribution maps of soil available micronutrients content for the farm could be served as reference for its precise and site specific management for intensive crop cultivation, higher productivity and profitability.
利用地理信息系统绘制土壤微量营养元素预测图,以便在印度半干旱农场采取因地制宜的管理干预措施
土壤微量营养元素的缺乏会对集约农业中的作物产量产生不利影响。我们对印度半干旱地区一个农业农场的植物可用性、土壤微量营养元素(如表层土壤中的铁(Fe)、锰(Mn)、锌(Zn)和铜(Cu)含量)的空间模式和分布进行了评估。此外,还分析了农场的其他土壤特性,如土壤 pH 值、导电率(EC)、土壤有机碳(SOC)含量和等量碳酸钙(CaCO3)含量,以描述控制微量营养元素可用性的土壤化学环境。农场土壤中植物可用微量营养元素含量的数据变异性非常大(变异系数大于 30%)。土壤中可利用的微量营养元素含量与土壤 pH 值呈负相关,与 SOC 含量呈正相关。根据半变量图分析,农田土壤中植物可利用的铁、锰、锌和铜含量具有中等程度的空间依赖性,即金块与金边之比介于 0.30 和 0.50 之间,空间参数范围分别为 404、801、954 和 1529 米。采用反距离加权法(IDW)绘制的植物可利用铁含量预测图显示,有几处缺铁(小于 4.50 毫克/千克)和边缘水平(4.50 - 9.00 毫克/千克)。通过对数正态普通克里金法绘制的植物可利用锌含量空间分布图显示,农场土壤中存在锌含量偏低(0.60 - 1.20 mg kg-1)的区域。利用普通克里金法绘制的农场尺度植物可利用锰和铜含量空间变化图具有良好的准确性和有效性,表明植物可利用锰和铜含量足以满足作物营养需求。农场土壤可利用微量营养元素含量的空间分布图可作为精确管理和因地制宜的参考,以实现集约化作物栽培、提高生产率和收益率。
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