Title:	Predicting bulk density in Brazilian soils for carbon stocks calculation: a comparative study of multiple linear regression and Random Forest models using continuous and categorical variables.
Authors:	SANTOS, W. P. dos VAZ, C. M. P. MARTIN NETO, L. ANSELMI, A. TOMASELLA, J. COSTA, F. de S. ALBUQUERQUE, J. A. LIER, Q. de J. van GALBIERI, R. PERINA, F. J.
Affiliation:	WHARLEY PEREIRA DOS SANTOS; CARLOS MANOEL PEDRO VAZ, CNPDIA; LADISLAU MARTIN NETO, CNPDIA; ADRIANO ANSELMI, BAYER; JAVIER TOMASELLA, INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS; FALBERNI DE SOUZA COSTA, CPAF-AC; JACKSON ADRIANO ALBUQUERQUE; QUIRIJN DE JONG VAN LIER, UNIVERSIDADE DE SÃO PAULO; RAFAEL GALBIERI, INSTITUTO MATO-GROSSENSE DO ALGODÃO; FABIANO JOSE PERINA, CNPA.
Date Issued:	2025
Citation:	Discover Soil, v. 2, article 7, 2025.
Description:	The present study aims to develop pedotransfer functions for estimating ρb using stepwise multiple linear regression applied to soil properties from available databases, which are considered suitable predictors (PTF-1).
Thesagro:	Química do Solo Carbono Estoque Disponibilidade de Nutriente Estimativa Análise Estatística Regressão Linear
NAL Thesaurus:	Soil chemistry Bulk density Soil organic carbon Nutrient availability Pedotransfer functions Prediction Statistical analysis Regression analysis
Keywords:	Química del suelo Densidad aparente Carbono orgánico del suelo Disponibilidad de nutrientes Funciones de edafotransferancia Predicción Análisis estadístico Análisis de regresión
ISSN:	3005-1223 (Online)
DOI:	https://doi.org/10.1007/s44378-025-00035-6
Type of Material:	Artigo de periódico
Access:	openAccess
Appears in Collections:	Artigo em periódico indexado (CNPDIA)