Heavy metals concentration and availability of serpentine soils in southwestern Turkey


Altunbaş S.

CHILEAN JOURNAL OF AGRICULTURAL RESEARCH, cilt.83, sa.3, ss.248-379, 2023 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 83 Sayı: 3
  • Basım Tarihi: 2023
  • Dergi Adı: CHILEAN JOURNAL OF AGRICULTURAL RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Fuente Academica Plus, ABI/INFORM, Agricultural & Environmental Science Database, CAB Abstracts, Food Science & Technology Abstracts, Veterinary Science Database, DIALNET
  • Sayfa Sayıları: ss.248-379
  • Akdeniz Üniversitesi Adresli: Evet

Özet

Soils developed on serpentine rocks have serious limitations for agriculture. Intensive agriculture and forestry activities are carried out in the lands developed on the serpentine rocks in the southwest of Turkey. Because of lack of information about heavy metal contents and some important soil physic-chemical properties of soils in this area some properties and especially heavy metal contents of the soils were aimed to be determined in this study. The results of the study showed that total Cd (5.4-6.8 mg kg-1 ) concentrations with plant available fraction ranging from 0.52% to 0.90% of the total Cd were high. Total Ni (61%) and total Co (44%) concentrations of soil samples were found at high levels. Plant available Ni and Cr concentrations in soils were ranged between 0.08%-8.52% and 0.007%-0.56% of the total Ni and total Cr concentrations respectively. In addition, very high levels of the total Fe (17039-50883 mg kg-1 ) and Mn (218-1790 mg kg-1 ) concentrations were determined in the examined serpentine soils. Total Zn (33.0-87.5 mg kg-1 ) and Cu (8.8-99.9 mg kg-1 ) concentrations were ranged within the given limit values (≤ 140 mg kg-1 for Cu and 300 mg kg-1 for Zn). With regard to macronutrients, 70% N, 61% P, 56% K and 87% Ca contents of soils were found to be at the adequate levels. The present study demonstrated that the first 10 principal components with an eigenvalue greater than 1 could explain 89.74% of the total variation in the population.