Soil spatial variability mapping and optimized sampling supported by sensing techniques: bases for a more efficient and sustainable precision agriculture

• Grant number: 22/03160-8
• Support Opportunities: Research Grants - Initial Project
• Start date: February 01, 2023
• End date: January 31, 2028
• Field of knowledge: Agronomical Sciences - Agricultural Engineering
• Principal Investigator: Lucas Rios do Amaral
• Grantee: Lucas Rios do Amaral
• Host Institution: Faculdade de Engenharia Agrícola (FEAGRI). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated researchers: Alessandro Samuel Rosa ; Henrique Oldoni ; Hudson Wallace Pereira de Carvalho ; Maurício Roberto Cherubin ; Paulo Sergio Graziano Magalhães
• Associated research grant(s): 24/19167-7 - Integration of Sensing Techniques for Agricultural Soil Fertility Characterization and Creation of Management Zones, AP.R SPRINT
• Associated scholarship(s): 24/13229-0 - Complementarity of proximal and orbital sensing techniques for exploring soil variability, BP.MS; 24/14044-4 - Detailed pedological mapping and management zones: characteristics, applications, and complementarity between approaches, BP.DR; 23/02592-4 - Sampling optimization and multivariate predictions for mapping soil fertility and soil quality, BP.MS; 23/02532-1 - Proximal sensing techniques for soil variability understanding, BP.IC

Abstract

Agricultural fields are not uniform in their extension, and, therefore, the adoption of precision agriculture (PA) is mandatory to obtain greater efficiency and sustainability of agricultural production. To make this approach viable, sensing techniques to support the mapping of soil properties are essential. The mapping of soil chemical fertility from systematic sampling for variable-rate fertilization is the most adopted practice worldwide. However, several other soil properties impact crop development and productivity, which have been neglected in PA research. Therefore, the main goal of this research is to generate knowledge for the development of protocols for the spatial diagnosis of soil at the crop level so that PA can be carried out more holistically, allowing a general understanding of soil quality, its natural spatial variability, and also the portion of the variability generated by the anthropic influence that demands site-specific management. Therefore, this research project aims to bring pedology closer to PA, developing innovative knowledge both in scientific and practical terms. The proposal is divided into three main scientific objectives (sensing techniques, sampling optimization and multivariate prediction, and soil mapping approaches) and will feature long-term monitoring of three commercial fields that represent a good part of the national cropping systems (sugarcane, grains, and crop-livestock integration). This document also presents a research and teaching integrated plan resulting from the project's development. (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)

MELO, DERLEI D.; CUNHA, ISABELLA A.; AMARAL, LUCAS R.. Hierarchical Stratification for Spatial Sampling and Digital Mapping of Soil Attributes. AGRIENGINEERING, v. 7, n. 1, p. 17-pg., 2025-01-01. (24/14044-4, 23/02592-4, 22/03160-8)

DE FREITAS, RODRIGO GREGGIO; OLDONI, HENRIQUE; JOAQUIM, LUCAS FERNANDO; POZZUTO, JOAO VITOR FIOLO; DO AMARAL, LUCAS RIOS. Predicting on-farm soybean yield variability using texture measures on Sentinel-2 image. PRECISION AGRICULTURE, v. 25, n. 6, p. 24-pg., 2024-08-12. (22/03160-8)

CUNHA, ISABELLA A.; BAPTISTA, GUSTAVO M. M.; PRUDENTE, VICTOR HUGO R.; MELO, DERLEI D.; AMARAL, LUCAS R.. Integration of Optical and Synthetic Aperture Radar Data with Different Synthetic Aperture Radar Image Processing Techniques and Development Stages to Improve Soybean Yield Prediction. AGRICULTURE-BASEL, v. 14, n. 11, p. 21-pg., 2024-11-01. (22/03160-8)