Development of system for rotational grazing management based on drone images

• Grant number: 18/08576-2
• Support Opportunities: Research Grants - Innovative Research in Small Business - PIPE
• Start date: September 01, 2019
• End date: May 31, 2020
• Field of knowledge: Agronomical Sciences - Animal Husbandry - Animal Production
• Principal Investigator: Leandro Soares Martins
• Grantee: Leandro Soares Martins
• Company: Koneksi Inovação Agro Ltda
• CNAE: Criação de bovinos
• City: Piracicaba
• Associated researchers: Ériton Egidio Lisboa Valente ; Fernanda Macitelli Benez ; Flávio Augusto Portela Santos ; Luiz Gustavo Nussio

Abstract

The objective of this project is to carry out a study that will serve as a basis for the creation of a software that estimates the most appropriate moment to proceed the change of paddocks of beef cattle in rotational grazing systems, based on animal behavior and the forage availability, being such measures taken from the analysis of images captured by Drones. With the creation of such a technological instrument, it will be possible to define more accurately the most appropriate moment of withdrawal and entry of the animals into the rotated paddocks, optimizing both forage production and animal performance. With such a technological apparatus it will be possible to realize an economy with the workmanship, since the necessity of the constant displacement of a trained handler to the paddocks areas will be eliminated. For the study, a total of 250 animals will be used, all of which are zebu, predominantly of the Nellore breed, allocated in a total area of 69.1 ha divided into 8 paddocks formed by Panicum maximum, Mombaça and Colonião. The animals will be individually identified for behavior analysis, which will be performed through the appreciation of photos taken via drone. These photos will also be used to estimate the forage availability in the paddocks using the DroneDeploy® program, performing the evaluation of the images through the use of the Normalized Difference Vegetation Index (NDVI) system. The images will be captured for 12 consecutive days, with consecutive flights performed from 6:00 a.m. to 6:00 p.m., every 30 minutes. Subsequently, the variables related to animal behavior and forage availability will be measured and selected through statistical analyzes, to compose the model that will be used by the software during the necessary calculations, in order to determine the best moment for the cattle movement between the paddocks. It is expected that after conducting this study, it will be concluded that the behavioral measures and the availability of pasture evaluated through the images captured by the Drone, provide a quick and accurate estimate of when the animals need to be changed from paddock, all of this through a daily flight. Having this tool in hand in the daily management of the farm, would allow the intensive use of rotational grazing systems optimally, without the need for the constant presence of highly trained professionals. If the property already has a trained professional, the use of this workforce can still be optimized, by using such professional for other activities that demand it. (AU)