中文摘要：

主要部件分析( PCA )能由用代替多维的参数简化数据库的结构相对，不太全面的变量在起始的 data.In 输了以便保证最小这份报纸，从不同地点的十八件黑土壤样品被测试， 13 个特殊索引被选择用主要部件分析评估黑 soil.By 的退化， 13 种尺寸的变量能被减少到六无关的主要 indexes.Analysis s

英文摘要：

Principal Component Analysis （PCA） can simplify the structure of database by replacing multidimensional parameters with relatively less comprehensive variables in order to ensure the minimum lost in initial data. In this paper, eighteen black soil samples from different sites were tested and thirteen distinctive in- dexes were chosen to evaluate the degeneration of black soil. By using principal component analysis, variables of thirteen dimensions can be diminished to six unrelated principal indexes. Analysis shows that the soluble salt content, Fulvic acids （FA） and aggregation degree have a high weighing coefficient, indicating these three indexes are the major parts for the evaluation of black soil degradation. It also provides a new path to the degenerated black soil treatment in Northeast China.