Precision agriculture in integrated crop-livestock systems

• Grant number: 18/24493-0
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: February 01, 2019
• End date: January 31, 2020
• Field of knowledge: Agronomical Sciences - Agronomy - Soil Science
• Agreement: Netherlands Organisation for Scientific Research (NWO)
• Principal Investigator: Paulo Sergio Graziano Magalhães
• Grantee: Livia Arantes Camargo
• Host Institution: Núcleo Interdisciplinar de Planejamento Energético (NIPE). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 17/50205-9 - Monitoring integrated crop-livestock systems through remote sensing and precision agriculture for more sustainable production - towards low carbon agriculture, AP.TEM

Abstract

Although in recent years integrated crop-livestock systems have been replacing traditional agricultural production and extensive/degraded pastureland areas, there is a lack of knowledge about its impact on soil variability and greenhouse gas flux. This proposal aims to monitor and model integrated areas, considering its dynamics, combining remote sensing, precision agriculture and biogeochemical models, in order to achieve sustainable production systems. Capturing the variability in soil-landscape properties is a challenge for crop producers attempting to integrate spatial information into the decision process of precision agriculture (PA). Data fusion technique, using the information from different sources could be used as auxiliary information to supplement site-specific management and the consequently increased efficiency under the sustainability point of view. There is increasing interest in intensifying agricultural production from pasture lands, for example by converting degraded pasture areas into mixed crop-livestock production. However, this is an area with little ongoing research and many open questions regarding land use change and management practices that maintain agroecosystem sustainability.

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)

CAMARGO, LIVIA ARANTES; DO AMARAL, LUCAS RIOS; DOS REIS, ALINY APARECIDA; BRASCO, THIAGO LUIS; GRAZIANO MAGALHAES, PAULO SERGIO. mproving soil organic carbon mapping with a field-specific calibration approach through diffuse reflectance spectroscopy and machine learning algorithm. SOIL USE AND MANAGEMENT, v. 38, n. 1, NOV 2021. (18/24985-0, 17/50205-9, 18/24493-0)