Covariables of Soil-Forming Factors and Their Influence on pH Distribution and Spatial Variability

Pedro Yescas-Coronado, Miguel Ángel Segura-Castruita (), Arturo Moisés Chávez-Rodríguez, Juan Florencio Gómez-Leyva, Aldo Rafael Martínez-Sifuentes, Osvaldo Amador-Camacho and Raúl González-Medina
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Pedro Yescas-Coronado: División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México/Instituto Tecnológico de Tlajomulco, Tlajomulco de Zúñiga 45640, Mexico
Miguel Ángel Segura-Castruita: División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México/Instituto Tecnológico de Tlajomulco, Tlajomulco de Zúñiga 45640, Mexico
Arturo Moisés Chávez-Rodríguez: División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México/Instituto Tecnológico de Tlajomulco, Tlajomulco de Zúñiga 45640, Mexico
Juan Florencio Gómez-Leyva: División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México/Instituto Tecnológico de Tlajomulco, Tlajomulco de Zúñiga 45640, Mexico
Aldo Rafael Martínez-Sifuentes: Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP), Centro Nacional de Investigación Disciplinaria en Relación Agua, Suelo, Planta, Atmósfera (CENID-RASPA), Gómez Palacio 35069, Mexico
Osvaldo Amador-Camacho: División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México/Instituto Tecnológico de Tlajomulco, Tlajomulco de Zúñiga 45640, Mexico
Raúl González-Medina: División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México/Instituto Tecnológico de Tlajomulco, Tlajomulco de Zúñiga 45640, Mexico

Agriculture, 2022, vol. 12, issue 12, 1-14

Abstract: The objectives of this study were to identify and rank the covariables of soil-forming factors that affect the distribution and spatial variability of pH in an agricultural area and to obtain a predictive map of soil pH. Samples of topsoil were obtained from different sites and taken to the laboratory, where they were prepared to determine the pH, organic matter, and percentages of particle size. In addition, the values of environmental covariables that affect pH were obtained. A database of the coordinates, laboratory results, and values of the covariables was constructed. Principal component analysis of the covariables was performed, and an analysis of the pH spatial structure was conducted and interpolated to obtain a predictive map of pH. Of the soil physical characteristics, the covariables clay and sand had a greater influence on the spatial behavior of pH with respect to the rest of the covariables of soil-forming factors, while human activity acted as a catalyst of the acidification process. Soil pH exhibited autocorrelation and moderate spatial dependence (66.7%) and was thus spatially predictable. The pH prediction map was accurate (RMSE = 0.158 and MEB = 0.020).

Keywords: active soil acidity; geostatistics; ordinary Kriging model; soil formation (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
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