Multivariate analysis of the physico-chemical properties of soils in selected locations of the floodplain of river Kaduna in Niger state, Nigeria

C. C. Onoyima, F. Okibe
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Abstract

Multivariate statistics was used to analyse the physico-chemical properties of soil in the selected locations of the floodplain of River Kaduna in Niger State, Nigeria. Samples were collected in March and September of the same year and the levels of some important soil quality parameters analysed. The data was subjected to basic statistics, cluster analysis (CA), Principal Component Analysis (PCA), Correlation Analysis, and Discriminant Analysis (DA). Descriptive statistics shows that, with the exception of silt and clay other parameters analysed decreased in value after flooding, while the predominant textual class of the soil is clay-loam. The PCA for March and September sampling periods extracted three components each which explained 84.10% and 78.90% respectively of the total variance. Cluster analysis yielded five distinct clusters for March: cluster 1 (K, Ca, EA, and pH); cluster 2 (OM, CEC, TN, Silt content, Clay content, and OC); cluster 3 (Na); cluster 4 (P), and cluster 5 (Mg and Sand content); and five separate clusters for September. From DA, seven variables (pH, OC, OM, TN, P, K and Mg) were the most significant parameters which accounted for the expected spatial/temporal variations in the soil of March, while CEC, Na, Ca, silt, sand and clay become an important discriminator in September. Flood has significant influence on the soil of the study area as level and distribution of the parameters changed from March to September.
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尼日利亚尼日尔州卡杜纳河漫滩选定地点土壤理化性质的多变量分析
采用多元统计方法对尼日利亚尼日尔州卡杜纳河漫滩选定地点土壤的理化性质进行了分析。同年3月和9月采集土壤样品,对土壤质量的一些重要参数进行了分析。对数据进行基础统计、聚类分析(CA)、主成分分析(PCA)、相关分析(Correlation analysis)和判别分析(Discriminant analysis)。描述性统计表明,除粉土和粘土外,所分析的其他参数在洪水后都有所下降,而主要的文本类别是粘土-壤土。3月和9月的主成分分析提取了3个分量,每个分量分别解释了总方差的84.10%和78.90%。聚类分析得出3月份的5个不同的聚类:聚类1 (K, Ca, EA和pH);簇2 (OM、CEC、TN、淤泥含量、粘土含量和OC);簇3 (Na);簇4 (P)和簇5 (Mg和Sand含量);九月份还有五个单独的群集。从数据上看,pH、OC、OM、TN、P、K和Mg 7个变量是3月份土壤时空变化的最显著参数,而CEC、Na、Ca、粉砂、砂和粘土是9月份土壤时空变化的重要判别因子。3 - 9月洪水对研究区土壤的影响显著,各参数的水平和分布都发生了变化。
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