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Analysis of influencing factors on soil Zn content using generalized additive model.
Jiang, Yan; Gao, Wen-Wu; Zhao, Jin-Ling; Chen, Qian; Liang, Dong; Xu, Chao; Huang, Lin-Sheng; Ruan, Li-Min.
Afiliação
  • Jiang Y; School of Economics, Anhui University, Hefei, 230601, China.
  • Gao WW; School of Economics, Anhui University, Hefei, 230601, China.
  • Zhao JL; National United Engineering Research Center for Analysis and Application of Agro-Ecological Big Data, Anhui University, Hefei, 230601, China. aling0123@163.com.
  • Chen Q; School of Economics, Anhui University, Hefei, 230601, China.
  • Liang D; National United Engineering Research Center for Analysis and Application of Agro-Ecological Big Data, Anhui University, Hefei, 230601, China.
  • Xu C; National United Engineering Research Center for Analysis and Application of Agro-Ecological Big Data, Anhui University, Hefei, 230601, China.
  • Huang LS; National United Engineering Research Center for Analysis and Application of Agro-Ecological Big Data, Anhui University, Hefei, 230601, China.
  • Ruan LM; National United Engineering Research Center for Analysis and Application of Agro-Ecological Big Data, Anhui University, Hefei, 230601, China.
Sci Rep ; 8(1): 15567, 2018 10 22.
Article em En | MEDLINE | ID: mdl-30349120
ABSTRACT
Soil zinc (Zn) plays a crucial role in plant growth, but excessive accumulation in the environment may lead to air, water and soil pollution. It is affected by various chemical, environmental and spatial factors. Therefore, it is important to identify the factors influencing Zn content in the landscape. The main motivation for this study is to determine the suitability of a generalized additive model (GAM) to describe change in soil Zn content due to influencing factors. A total of 1497 soil nutrient samples were collected in Fangshan District, Beijing, China. Organic matter (OM), available phosphorus (AP), available potassium (AK), alkali-hydrolyzed nitrogen (AHN) and slowly available potassium (SAK) are considered. The relationship between Zn, nutrients and geographic location (latitude & longitude) is investigated using the GAM. More precisely, the Akaike information criterion (AIC) is used to select influencing factors on Zn content and cross-validated to avoid overfitting of the multivariate model. The results show that Zn content reaches its maximum at latitude 39.8°N and longitude 115.9°E. Zinc content increases as AP increases to 150 mg/kg. When OM content is greater than 90 g/kg, Zinc content decreases with an increase in OM content. Factors that affected Zn content, in descending order of significance derived from deviance explained and adjustment coefficient of determination (Adj.R2) were AP, latitude, AHN, AK and OM. Moreover, the interactions between latitude and longitude, AHN and AP, OM and AK have significant impact on Zn.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2018 Tipo de documento: Article