Defining management zones for a papaya culture considering soil chemical attributes by fuzzy c-means

  • Fabricia Benda de Oliveira Departamento de Geologia. Universidade Federal do Espírito Santo (UFES), Alto Universitário, s/n, Caixa Postal 16, CEP: 29500-000, Alegre, ES, Brazil.
  • Julião Soares de Souza Lima Departamento de Engenharia Rural. Universidade Federal do Espírito Santo (UFES), Alto Universitário, s/n, Caixa Postal 16, CEP: 29500-000, Alegre, ES, Brazil.
  • Carlos Henrique Rodrigues de Oliveira Instituto Federal de Educação, Ciência e Tecnologia do Espírito Santo (IFES), Rodovia ES-482 (Cachoeiro-Alegre), Km 72, CEP: 29500-000, Alegre, ES, Brazil.
  • Walas Permanhane Sturião Departamento de Agronomia. Universidade Federal de Viçosa (UFV), Avenida Peter Henry Rolfs, s/n, CEP: 36570-000, Viçosa, MG, Brazil.
  • Jacyelli Sgranci Angelos Programa de Pós-graduação em Agroquímica. Universidade Federal do Espírito Santo (UFES), Alto Universitário, s/n, Caixa Postal 16, CEP: 29500-000, Alegre, ES, Brazil.

Abstract

In precision agriculture, one of the major problems is the need for a dense sampling grid. A solution to this problem has been the generation of management zones and the correlation between them. This work aims at defining management zones for a papaya culture using the fuzzy C-means grouping method, based on the following soil attributes: phosphorus, calcium, magnesium and potassium; and base saturation. The work was conducted in an approximately 1.2 ha area planted with a commercial culture of Carica papaya L. cultivated in typical Argisol found on the coastal terraces, in the municipality of São Mateus, ES, Brazil. The management zones were defined by the proposed method, based on the following analyses: soil chemical parameters P, Ca, Mg, and base saturation (V), analyzed together; soil chemical parameters P, Ca, Mg, and V, analyzed separately; and, the following combinations of soil chemical attributes Ca-Mg, Ca-V, Ca-Mg-V, P-Ca, P-Mg, P-V, P-Ca-Mg, P-Ca-V, Mg-V, and P-Ca-Mg-V. The generated management zones facilitated an understanding of the spatial variability of the attributes in the study area and the observed similarities between management zones generated from different attributes. In addition, the data were influenced especially by the P and V% attributes.

Keywords: Carica papaya L, geostatistics, grouping analysis, precision agriculture.


Published
05/03/2024
Section
Papers