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Information Journal Paper

Title

Modeling the relationship between cadmium and some soil physical and chemical properties in pistachio orchards using regression and artificial neural network

Pages

  177-188

Abstract

 Introduction: Increasing concentrations of heavy metals in the environment have raised serious environmental concerns. Cadmium is one of the most toxic heavy elements in organisms and it has no biological role. So far, little research has been done on the status of heavy metals in pistachio orchards and factors affecting them. Therefore, the purpose of this study was to determine the relationship between cadmium extracted with DTPA in soil and other soil physical and chemical properties in agricultural soils of Rafsanjan using Stepwise Regression and Artificial Neural Network Modeling. Material and methods: In this study, 140 soil samples from two depths of 0 to 40 and 40 to 80 cm were collected from pistachio orchards in six regions of Rafsanjan suburb. Soil characteristics including available Cd and Zn concentration measured using DTPA, P concentration by Olsen method, percent of sand, clay and silt by hydrometer method, and pH and electrical conductivity of soil saturated extract by pH meter and EC meter, respectively, were measured. In order to investigate the relationship between available Cd and physical and chemical properties of the soil, Stepwise Regression and Artificial Neural Network (multi-layer feed forward) were used. Results and dissussion: The results showed a significant and positive correlation between Phosphorus and clay content and soil cadmium, a negative and significant correlation between Cd-DTPA and pH and clay percentage, and a positive correlation between available Cd and available Zn, total Zn, and total Cd. The results also showed that both Modeling methods are accurate in estimating soil cadmium concentration, although the neural network model was more accurate. The R2 and root of mean square error for the neural network model were 84. 3% and 0. 01% for the test data, and 27. 2% and 1. 43% for the Stepwise Regression model, respectively. Also, cadmium concentration showed the highest sensitivity to Zinc concentration and other parameters such as clay, pH, Phosphorus, EC, and sand were in the next order of importance, respectively. These results confirm that due to the consumption of Zinc containing fertilizers and the increased consumption of phosphate fertilizers which have high impurity in the amount of cadmium, an increase in soil cadmium concentration is observed in the pistachio orchards. Conclusion: Zinc and Phosphorus fertilizers used in pistachio orchards have a significant impurity of cadmium that can cause soil contamination by cadmium due to its long-term use and absorption of this toxic element in pistachio plant and fruit. Therefore, while complying with national and international standards in the production and import of fertilizers, the use of these fertilizers should be optimized by analyzing and interpreting the results of soil and leaf analysis to reduce the risk of pistachio fruit contamination to cadmium.

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    APA: Copy

    HOSSEINIFARD, SEYED JAVAD, SHIRANI, HOSSEIN, SADR, SOMAYEH, & Hashemipour, Hakimeh. (2019). Modeling the relationship between cadmium and some soil physical and chemical properties in pistachio orchards using regression and artificial neural network. ENVIRONMENTAL SCIENCES, 17(3 ), 177-188. SID. https://sid.ir/paper/117733/en

    Vancouver: Copy

    HOSSEINIFARD SEYED JAVAD, SHIRANI HOSSEIN, SADR SOMAYEH, Hashemipour Hakimeh. Modeling the relationship between cadmium and some soil physical and chemical properties in pistachio orchards using regression and artificial neural network. ENVIRONMENTAL SCIENCES[Internet]. 2019;17(3 ):177-188. Available from: https://sid.ir/paper/117733/en

    IEEE: Copy

    SEYED JAVAD HOSSEINIFARD, HOSSEIN SHIRANI, SOMAYEH SADR, and Hakimeh Hashemipour, “Modeling the relationship between cadmium and some soil physical and chemical properties in pistachio orchards using regression and artificial neural network,” ENVIRONMENTAL SCIENCES, vol. 17, no. 3 , pp. 177–188, 2019, [Online]. Available: https://sid.ir/paper/117733/en

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