Extreme Gradient Boosting Regression Model for Soil Available Boron

Gökmen F., UYGUR V., Sukuşu E.

Eurasian Soil Science, vol.56, no.6, pp.738-746, 2023 (SCI-Expanded, Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 56 Issue: 6
  • Publication Date: 2023
  • Doi Number: 10.1134/s1064229322602128
  • Journal Name: Eurasian Soil Science
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Geobase, Pollution Abstracts, Veterinary Science Database
  • Page Numbers: pp.738-746
  • Keywords: calcareous parent material, chemometric relations, mannitol extractable boron, modeling, R statistics
  • Isparta University of Applied Sciences Affiliated: Yes

Abstract

Abstract: Soil formation processes and agricultural practices determine the amount of plant-available boron (B) concentration in soils. In this study, the relationships between soil characteristics and plant-available B concentrations of 54 soil samples collected from Gelendost and Eğirdir districts of Isparta province were investigated using the Spearman correlation and eXtreme gradient boosting regression (XGBoost) model. Plant-available B concentration was significantly correlated with the soils' phosphorus, potassium, copper, and electrical conductivity. The XGBoost model explained 63% of the variation in five components defining soil behavior, and one of these components showed the variance resulting from the plant-available B. The effects of explanatory variables on B concentration determined in the XGBoost model were the parameters that were also significant in the correlation analysis. The results indicated that the model could successfully estimate B availability from the routinely analyzed soil properties (Fig. 1). [Figure not available: see fulltext.].