Improving nitrogen use efficiency in sugarcane using remote sensing data linked to...
| Grant number: | 20/04486-9 |
| Support type: | Scholarships in Brazil - Doctorate (Direct) |
| Effective date (Start): | April 01, 2020 |
| Effective date (End): | August 31, 2022 |
| Field of knowledge: | Agronomical Sciences - Agronomy |
| Principal Investigator: | José Eduardo Corá |
| Grantee: | Almir Salvador Neto |
| Home Institution: | Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil |
| Associated research grant: | 16/13461-4 - Improving nitrogen use efficiency in sugarcane using remote sensing data linked to crop modeling and yield mapping technologies, AP.BIOEN.TEM |
Abstract The main objective of the present project is to develop new knowledge that can lead to improvements in the evaluation of the spatial and temporal variability of productivity and the management of K and P in the culture of sugarcane. To achieve the objective, commercial sugarcane areas will be monitored with different sensors embedded in drones, in order to validate vegetation indices used to evaluate the absorption of K and P by sugarcane. The knowledge obtained with the present project aims to improve methods and tools to quantify the demands for K and P for the cultivation of sugar cane and to help farmers to adopt systems of sustainable and efficient management of potassium and phosphate fertilization. While the benefits of using more accurate approaches to manage crops with additional information are recognized, the tools provided by precision farming and other information technologies have not yet been adequately and fully transferred to conventional agricultural management. The increased complexity of systems makes calculating financial benefits complicated and uncertain, delaying their adoption and diffusion. These issues can be resolved by improving the decision-making process, integrating advanced biophysical systems with economic decision models and combining precision farming solutions with innovative electronic platforms, with a view to adopting innovative solutions. Taking these questions as a basis, the hypotheses of the present study are: 1) the spatial variability of soil attributes affects the spatial and temporal patterns of sugarcane crop productivity; 2) the data, remotely obtained by sensors embedded in drones, improve the understanding of the spatial (in the field) and temporal (over the years) variability of sugarcane productivity; 3) the response of the sugarcane crop to potassium and phosphate fertilization is spatially and temporally variable; 4) the integration of crop productivity estimation models with remote sensing data can improve K and P management, leading to greater profitability and reduced environmental impacts. To test the hypotheses, the following objectives are proposed: 1) to evaluate the spatial and temporal variability of sugarcane productivity and to identify homogeneous stable and non-stable management zones; 2) develop vegetation indexes to detect K and P stress from sugarcane crops using remote sensing technologies; 3) integrate data with process-based models to simulate the spatial variability of K and P consumption and quantify economic advantages of application in varying doses and times, aiming to optimize the production of sugarcane and ethanol and reduce environmental impacts in space and in time. (AU) | |