“For the 2022/2023 off-season, we have a transition scenario from La Niña to El Niño, that is very favorable at this time”
Aníbal Gusso is CEO and founder of Agro Observer, postdoctoral in applied remote sensing by the Federal University of Rio Grande do Sul. Gusso was a professor of remote sensing and geostatistics at Unisinos and a consultant for the agricultural commodities market.
Aníbal Gusso, CEO and founder of Agro Observer
AgriBrasilis – How has the climate affected the main Brazilian crops and what is expected for the next harvests?
Aníbal Gusso – In the Brazilian agriculture, any percentage of loss associated with the climate will have an increasing impact on production. In the State of Mato Grosso, in 2016, the drought associated with high temperatures caused a drop of approximately 10%, representing just over 2 million tonnes of losses. Currently, the high productivity in MT allows the production of more than 40 million tonnes. Therefire, similar conditions because of the weather and climate would take away more than 4 million tonnes of soybean.
On the other hand, the growing cultivation of soybean in floodplain areas in the State of Rio Grande do Sul, that has been taking place in the last two decades, aims to avoid the impact of unfavorable conditions such as water stress, but also to take advantage of the more favorable conditions of the soil moisture. Droughts, heat waves or heavy rains have always occurred and are a major challenge for the farming of the summer crop in the state.
For the 2022/2023 off-season, we have a transition scenario from La Niña to El Niño, that is very favorable at this time. States with less expression in the production of 2nd crop corn, such as Tocantins, have been suffering from excessive rainfall. Even so, the harvest should be medium/good for the biggest producers like the States of Mato Grosso, Paraná, Goiás+Distrito Federal e Mato Grosso do Sul, with low impact and very localized losses.
For the 2023/2024 summer harvest, with the consolidation of El Niño, Agro Observer is noticing a scenario of more severe losses.
AgriBrasilis – What are the activities of Agro Observer? How are your projections made?
Aníbal Gusso – Agro Observer is a Brazilian technology company for global monitoring of soybean and corn crops. We offer consultancy to monitor the evolution and forecasts of the crop, delivering detailed weekly reports.
Our reports cover scenario analysis, maps, graphs and/or tables describing crop development conditions and projections until harvest. Our reports are prepared according to the specific demands of customers, whether they are banks, cooperatives, insurance companies, other agribusiness consultancies or individuals.
AgriBrasilis – How is monitoring carried out using satellites? How accurate are the estimates made with the data obtained?
Aníbal Gusso – In a simplified way, data collection takes place through the analysis of solar radiation reflected on the Earth’s surface. This radiation is detected by sensor instruments placed on board satellites. These instruments are capable of interpreting and separating specific wavelengths of radiation from the visible, infrared or thermal range.
Throughout the harvest, Agro Observer delivers, for example, an objective analysis with maps and projections of productivity distribution in the production fields. The maps show which are the areas with the best use of the conditions and the areas with expected losses. This helps the customer/decision maker to establish a medium-term perspective on possible scenarios.
Some of the information coming directly from satellite images are the temperature in the canopy of vegetation, vegetation index and accumulated rainfall, that have specific characteristics of precision associated with the measuring instruments that go on board the satellites. This accuracy, in turn, is continually tested and corrected through scientific work.
To give you an idea, the error in the temperature data is between 1 to 1.5 degrees in each pixel. As for products with higher added value, such as the productivity estimate, the state average margin of error is 2%, depending on the state.
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