Digital tools can cut carbon emissions by up to 28.7% and enhance maize bioethanol sustainability
Manuel Pérez-Ruiz, MarÃa Barrera, Luis Sánchez-Fernández
The adoption of precision farming technologies not only improves efficiency in the use of inputs but also directly impacts reducing the carbon footprint of the corn crop destined for bioethanol production. Agriculture is often criticized for its environmental impact, yet it remains a vital sector for global food security. Recent advances in precision agriculture are proving to be an effective tool for significantly reducing carbon emissions while maintaining economic viability. This approach is based on optimizing the use of agricultural inputs, such as fertilizers and water, through the application of precision technologies that allow us to adapt to the specific needs of each plot, thus improving the productive efficiency and sustainability of the agri-food system.
In Spain, maize grown for bioethanol production plays a crucial role in the circular economy. However, this production faces significant challenges, such as optimising agricultural inputs and minimising its carbon footprint. According to European Union data, producing one ton of dry corn for bioethanol is associated with an approximately 400 kg COâ‚‚eq emission. However, data from sustainability-driven projects reveal that adopting precision farming techniques can significantly lower this figure. For instance, research from the MaÃz Sostenible Project demonstrated an average emission reduction of 235.39 kg COâ‚‚eq per ton, emphasizing the effectiveness of data-driven agronomic strategies.
In this context, Vetex Bioenergy, the leading Spanish producer of bioethanol and concentrated protein for animal feed, joined the University of Seville in the iMASO project in 2023. Specifically, this project explores innovative measures to increase the competitiveness of the corn sector, improve its resilience to climate change, and reduce greenhouse gas emissions.
The role of smart technologies in sustainable farming
Multispectral imaging from satellites and drones provides high-resolution crop health monitoring, helping farmers detect stress factors such as nutrient deficiencies, water scarcity, and pest presence before they become critical. Farmers can implement corrective actions in real-time by analyzing spectral indices like NDVI and MSAVI, ensuring optimal growth conditions while reducing waste. Furthermore, IoT-enabled machinery integrated with CAN-bus telemetry systems allows for real-time fuel consumption tracking, engine performance, and crop yield metrics. This data-driven approach enhances operational efficiency and lowers fuel consumption, further reducing the overall carbon footprint of maize cultivation.
In this project, we integrate drones as an advanced remote sensing tool, providing high-resolution images for a detailed analysis of crop conditions. They are instrumental in small and medium extensions, improving early detection of water stress, pests and nutritional deficiencies. However, they have limitations in coverage and operability in large areas. Therefore, although drones provide precision, satellite imagery remains a more scalable and efficient option for continuous monitoring in precision agriculture.
Another key tool implemented is the harvester yield monitor, which records variables such as grain weight, moisture and harvesting speed in real-time. With this information, farmers can adjust the application of inputs, improving efficiency and reducing the carbon footprint per ton of dried corn.
More precision results in reduced emissions
For the cases studied, the average carbon emissions calculated were 286.17 kg CO2eq per ton of dry weight of corn with an average of 13.89 t/ha of corn, a value below that established by the RED Directive of 400 kg CO2eq per ton of dry weight of corn. Furthermore, it is reaffirmed that nitrogen fertilization affects carbon emissions the most, accounting for 84.2% of total emissions (Figure 3).
Let’s compare the data obtained according to the type of agriculture used. We find that the average yield of precision agriculture is 1.89 t/ha more corn than those who apply conventional management practices. This means that using precision technologies represents a 28.7% reduction in carbon emissions throughout the corn production cycle.
The transition towards data-driven, low-emission farming is necessary for environmental sustainability and a competitive advantage in the evolving agricultural landscape. By adopting precision agriculture techniques, maize farmers can significantly reduce carbon emissions, optimize input costs, and increase their competitiveness in global markets. Results from the iMASO Project confirm that targeted interventions, such as site-specific fertilizer application and smart monitoring systems, can lower emissions by nearly 30% while improving overall efficiency. As more farmers embrace these technologies, the potential for sustainable, high-performance agriculture becomes a reality, paving the way for a more resilient and profitable sector.
Sources
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Kim M-Y and Lee KH (2022) Electrochemical Sensors for Sustainable Precision Agriculture—A Review. Front. Chem. 10:848320. doi: 10.3389/fchem.2022.848320
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