Çok Değişkenli İstatistiksel Analizler ile Akkaya Gölü Rezervuar Topraklarındaki Ağır Metallerin Veri Analizi

Tarım sahalarının çevresinde, sulama amaçlı yapılan göllerin rezervuar alanlarında biriken ağır metallerin kökeninin belirlenmesi ve toksik etkisinin anlaşılmasında, veri analizinin yapılması önemlidir. Çalışmanın amacı, Akkaya Gölü rezervuar sahasındaki toprakların kimyasal içeriklerinde çok değişkenli istatistik analizler kullanılarak Akkaya Gölü rezervuar sahasında tespit edilen ağır metallerin kendi arasındaki davranışlarını bunlar arasındaki ilişkilerinin belirlenmesi ve bu metallerin olası kökeninin açıklanması şeklindedir. Kimyasal analiz içeriklerinin bollukları Mg > Al > Fe > S > Ti > Zn > V > As > Cu > Ni > Pb > Co > Mo > Sn > Cd > Hg olarak sıralanmıştır. Fe ile Mg, Si, K, Co, V, Cu, As, Ni, Zn ve Pb arasında yüksek pozitif korelasyon bulunur. Faktör analizine göre toplam varyans 72.080 (% kümülatif) olup, 3 (üç) faktöre ayrılmıştır. Hiyerarşik kümeleme analizine göre 3 grup ve elementlerin kümeleme analizine göre 4 grup oluşmuştur. Bu grupların kendi aralarında benzer özellik sundukları anlaşılmıştır. Çok değişkenli istatistik analizleri bu çalışma için başarılı olmuştur.

Data Analysis of Heavy Metals in Akkaya Lake Reservoir Soils Using Multivariate Statistical Analysis

Data analysis is important in determining the origin of heavy metals accumulated in reservoir areas of lakes built for irrigation and understanding their toxic effects around agricultural areas. The aim of the study is to determine the behaviors of the heavy metals detected, the relationships among them, and to explain the possible origin of these metals by using multivariate statistical analyzes in the chemical contents of the soils in the Akkaya Lake reservoir area. The abundance of chemical analysis contents is listed as Mg> Al> Fe> S> Ti> Zn> V> As> Cu> Ni> Pb> Co> Mo> Sn> Cd> Hg. There is a high positive correlation between Fe and Mg, Si, K, Co, V, Cu, As, Ni, Zn and Pb. According to factor analysis, the total variance is 72.080 (% cumulative), divided into 3 (tree) factors. There were 3 groups according to the hierarchical cluster analysis and 4 groups according to the cluster analysis of the elements. It is understood that these groups offer similar characteristics among themselves. Multivariate statistical analysis was successful for this study.

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