High technology enables digital agriculture.
Anticipating when and where a disease will break out, by up to two weeks, or defining the ideal period for harvesting fruit in order to obtain more juice sounds like a big deal.
These applications, which seem futuristic, are already adopted by Citrosuco, which developed them based on the analysis of data collected from different sources.
The company invested in connectivity, storage, management and interfaces (APIs) to connect different software. Then, it defined ways of consuming data, such as modeling and visualization panels.
Data scientists analyze the models, fed continuously for greater accuracy. The health forecast brings together individual identification data from drones, digital weather stations, plot history and field inspections.
With leprosis alone, the reduction rate reached 66%. “The model for ideal harvesting increased productivity by 12% with drone support and history”, explains COO Tomás Dandrea Balistiero.
Data collection and analysis reached the field, enabling precision agriculture, with more assertive decision-making, more productivity and better financial results. There has never been so much data, satellites, drones, weather stations, soil sensors and equipment, with diverse area maps, available for the field.
According to the Caminhos da Tecnologia no Agribusiness survey, a partnership between KPMG and SAE Brasil, almost all rural activities already use technologies for better performance, such as GPS (91% of respondents), satellite images (76%) and drones (61% ).
Programs such as Agro 4.0, from the Brazilian Industrial Development Agency, support demonstration projects - so far, around a hundred, says the program leader, Isabela Gaya.
BovControl, according to CEO Danilo Leao, has accumulated such a volume of data with animal monitoring that it has a system capable of tracking and measuring greenhouse gas emissions.
Despite the growth of data-based solutions, the challenge of using and integrating information from different sources to support decision-making and generate value remains, especially in real time, says the deputy scientific director of the Brazilian Association of Precision Agriculture (Asbraap ), Christian Bredemeier.
Aegro allows the integration of data collected by intelligent machines, from government systems and even from financial institutions to assist in management. “It works as an ‘all in one’ platform, like a backbone. Additional modules meet specialized needs”, says CEO Pedro Dusso.
Other challenges to be overcome are connection in the field, to monitor machines and make corrections in real time, and the lack of specialists in analyzing large volumes of information.
Paulo de Tarso Ziccardi, agribusiness director at Accenture Brasil, remembers that it is still difficult to see what happens on a plot to obtain correlations and understand productivity factors.
by Martha Funke
