Prediction of phosphorus adsorption in areas cultivated with sugar cane by data mining techniques

• Grant number: 18/12279-3
• Support Opportunities: Scholarships in Brazil - Master
• Start date: January 01, 2019
• End date: March 31, 2020
• Field of knowledge: Agronomical Sciences - Agricultural Engineering - Soil and Water Engineering
• Principal Investigator: Zigomar Menezes de Souza
• Grantee: Jeison Andrey Sánchez Parra
• Host Institution: Faculdade de Engenharia Agrícola (FEAGRI). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

The availability of macronutrients such as phosphorus in the soil is a determinant factor in the growth of plant species. The adsorption of phosphorus is characterized by different attributes and the natural processes of soil exposure, which are expressed in a database of hard interpretation, to use efficient methodologies for extraction of knowledge is essential, as the case of data mining. Thus, the aim of research will be the application of data mining techniques to predict the adsorption of phosphorus in soil with different relief forms cultivated with sugarcane. The characterization was carried out in agricultural areas of sugar cane in the Catanduva region, state of São Paulo, in two plots of one hectare, whose agricultural practices were identical along the last years, one in concave area of relief and another in a convex area adjacent to the relief. In each area, a sample grid containing 121 points with a spacing of 10 x 10m was installed, where soil samples were collected to determine the physical, chemical and mineralogical attributes of the soil. Data mining techniques will be used, such as: classification and regression, to predict the adsorption of phosphorus in the soil, from the variables determined in the soil. At the end of the project, it is expected to obtain a model with high predictive potential that allows the decision making in a precise and fast way with respect to the adsorption of phosphorus in the soil. In addition, to identify the degree of importance of each analyzed variable, in order to establish the main and secondary attributes in the soil phosphorus adsorption process. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

PARRA, JEISON SANCHEZ; DE SOUZA, ZIGOMAR MENEZES; DE MEDEIROS OLIVEIRA, STANLY ROBSON; VIEIRA FARHATE, CAMILA VIANA; MARQUES, JOSE; SIQUEIRA, DIEGO. Phosphorus adsorption prediction through Decision Tree Algorithm under different topographic conditions in sugarcane fields. CATENA, v. 213, p. 11-pg., 2022-02-18. (18/12279-3)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

PARRA, Jeison Andrey Sánchez. Phosphorus adsorption model in areas cultivated with sugarcane using data mining techniques. 2020. Master's Dissertation - Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Agrícola Campinas, SP.