MULTIVARIATE ANALYSIS OF CHEMICAL AND PHYSICAL ATTRIBUTES OF QUARTZIPSAMMENTS UNDER DIFFERENT AGRICULTURAL USES

ABSTRACT The inadequate agricultural management in the semiarid region of northeastern Brazil, associated with the fragility of most soils, has caused degradation of the quality of this resource. This study aimed to evaluate the quality of Quartzipsamments under different uses through the multivariate analysis of chemical and physical attributes. Five areas were selected: four of them with agricultural use (onion, banana, cassava, and corn) and the other with Caatinga. Soil samples were collected at depths of 0.00–0.10, 0.10–0.20, and 0.20–0.40 m for chemical and physical analyses. The data were submitted to descriptive analysis and then to the multivariate analysis using the principal component analysis (PCA) technique and Ward’s clustering method. PCA and clustering techniques allowed the identification of different production systems in subsurface layers, suggesting the effect of fertility on the differentiation of areas with onion and banana, as well as the clustering of cassava and corn cultivations. Physical attributes and sodium content of the surface layer of the area with onion showed a tendency of compaction and salinization process of this environment. In general, fertility was the main responsible for the improvement of soil quality with agricultural use when compared to the Caatinga.摘要 巴西东北部半干旱地区农业管理失当，加之多数土壤本征脆弱，已引发该区域土壤资源质量退化。本研究旨在通过化学与物理属性的多变量分析，评估不同土地利用模式下石英砂质新成土（Quartzipsamments）的质量状况。研究共选取5个区域：其中4块为农业用地，分别种植洋葱、香蕉、木薯与玉米，剩余1块为卡廷加（Caatinga）原生植被群落。分别在0.00–0.10 m、0.10–0.20 m及0.20–0.40 m三个土层采集土壤样品，用于化学与物理属性测定。数据先经描述性统计分析，随后采用主成分分析（PCA）与沃德聚类法（Ward’s clustering method）开展多变量分析。主成分分析与聚类分析可在亚表层与深层土层中识别出不同的生产系统，结果表明土壤肥力差异是区分洋葱与香蕉种植区的核心因素，且木薯与玉米种植区聚为一类。洋葱种植区表层土壤的物理属性与钠含量数据显示，该区域存在土壤压实与盐渍化的演变趋势。总体而言，相较于卡廷加原生植被区，农业利用模式下的土壤肥力提升是改善土壤质量的核心驱动因素。